US20130117033A1 - Healthcare performance measurement and equitable provider reimbursement system - Google Patents

Healthcare performance measurement and equitable provider reimbursement system Download PDF

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US20130117033A1
US20130117033A1 US13/289,284 US201113289284A US2013117033A1 US 20130117033 A1 US20130117033 A1 US 20130117033A1 US 201113289284 A US201113289284 A US 201113289284A US 2013117033 A1 US2013117033 A1 US 2013117033A1
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hospital
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William C. Mohlenbrock
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VERRAS HEALTHCARE GROUP Inc
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    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06QDATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
    • G06Q50/10Services
    • G06Q50/22Social work
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06QDATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00Administration; Management
    • G06Q10/06Resources, workflows, human or project management, e.g. organising, planning, scheduling or allocating time, human or machine resources; Enterprise planning; Organisational models
    • GPHYSICS
    • G16INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16HHEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H10/00ICT specially adapted for the handling or processing of patient-related medical or healthcare data
    • G16H10/60ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records

Abstract

The present invention incorporates medical knowledge into the processes and algorithms that combine inpatient quality outcomes, ambulatory quality measures and health insurers' financial data into actionable information that hospitals and physicians can use to improve the efficacies and efficiencies of their care. It then quantifies the financial net savings that predictably accrue as a result of the providers' improved medical outcomes. This information enables a hospital or health insurer to equitably share the net saving with the physicians and hospitals as incentives to continuously improve the quality of their patients' care and control costs.

Description

    FIELD OF THE INVENTION
  • The technologies and techniques embodied in this invention solves the major healthcare delivery problems of: (1) Facilitating the improvement of physicians' and hospitals' clinical and operational outcomes through the use of Verras' two technologies, Sherlock and Watson; (2) Objectively documenting hospitals' and physicians' improvements in the major metrics of quality and cost efficiencies; (3) Through the invention of the Index of Quality Improvement (IQI), to differentiate hospitals' and physicians' abilities to improve their quality and efficiency outcomes over multiple years in a transparent and easily understood manner; and (4) Differentially reimbursing physicians and hospitals on the basis of quality through the use of the Quality Assurance and Equitable Reimbursement System.
  • BACKGROUND OF THE INVENTION
  • The present invention relates to technologies, processes and algorithms that quantify medical quality and cost efficiencies for the purpose of creating financial incentives for rewarding medical providers (hospitals and physicians). The invention uses objectively defined metrics of clinical quality and cost efficiency improvements that are trended over a multi-year period to determine an “Index of Quality Improvement” (IQI). The IQI quantifies the relative quality and cost efficiencies of hospitals and clinical services within the hospitals (orthopedics, cardiology etc.) and determines relative reimbursement rates based on the providers' outcomes. Higher quality and greater efficiencies yield higher reimbursements for the providers. More particularly, the invention's technologies, processes and algorithms transform routinely used, hospital and insurance data into actionable, clinical quality information, which physicians can use to improve the outcomes of their patients' care. The invention's algorithms then aggregate the results of physicians' practice pattern improvements and assign appropriate provider (physician and hospital) and insurer remunerations based on the observed quality and cost efficiency outcomes.
  • Beginning in the late 1980's and up to the present, US private and public healthcare purchasers and their insurers have been relying on managed care entities to control widely varying levels of questionable medical quality and escalating healthcare costs. To control costs, these third-party, managed care entities limited patients' access to their chosen physicians and implemented stringent price controls. These measures have been only partially effective. After two decades of managed care controls, the quality and costs of patient care remain uncontrolled and excessive leaving America's entire financial future in question.
  • Employers can no longer sustain their employees' cost increases and patients are more interested in access to their physicians than in their employers' cost savings. For patients, access to their physicians has come at a significant price because employers have begun to shift their cost burdens back onto the employees. The levels of angst have grown to the point that policy makers and even some employers are now suggesting, in spite of all evidence to the contrary, that a nationalized, single-payer system is the only viable option to control costs by the aligning of financial incentives of all stake-holders (providers, public and private purchasers and their insurers as well as patients). The recently enacted federal Patient Protection and Affordable Care Act (PPACA) was a direct response to uncontrolled costs but it did not implement a single-payer system. However it did usher in other alternatives that involve global payments to hospitals and physicians such as Accountable Care Organizations (ACO), Acute Care Episodes (ACE) and Consumer Operated and Oriented Plans (CO-OP). These new delivery systems allow hospitals and physicians to share net-savings, which hold great promise for improving quality and controlling healthcare costs because physicians can now participate in the savings they helped create through improved clinical outcomes. However, these cost sharing mechanisms will be successful only if quality and efficiencies are accurately assessed and providers are appropriately reimbursed for their efforts. Verras' technologies and techniques are unique in their abilities to assist physicians and hospitals with quality and cost efficiency improvements and to translate the changes in practice patterns to appropriate reimbursements for hospitals and physicians who deliver high quality, cost efficient healthcare.
  • Patients want their choice of providers at reasonable prices. Public and private purchasers, as well as insurers need to know the value of the services they receive for their money; and providers need the latitude to practice their professions unencumbered by third party intrusions. But these ideals have not materialized for any number of reasons, not the least of which is the misalignment of financial incentives between purchasers, insurers, hospitals and physicians. Currently, for one of these groups to financially win, one or more of the others must lose. The effects of misaligned incentives have created a bizarre triad of: excessive profits for insurance and managed care companies that do not deliver care; insufficient funding for providers who are dedicated and trained to deliver quality care; and diminished access, coverage and services for patients who need care. Distrust among all parties and chaos in the system are the unintended consequences of misaligned incentives and the inability to contract for healthcare services on the basis of objectively defined value, that is, quality and costs.
  • For these reasons, the alignment of providers' and hospitals' incentives and their integration into common provider groups are viewed as critical components of the solution to control medical quality and costs. To these ends, numerous care delivery models have been tried but few have met with anything but marginal success. This invention changes this and solves the primary, non-political problems relating the quality and cost issue facing the United States' healthcare system.
  • There are a few examples in which physicians, hospitals and their insurance entities have aligned their incentives and integrated themselves to achieve reasonable levels of medical quality, and to some extent, cost efficiencies and patient satisfaction. The first example is a health maintenance organization (HMO) model, such as Kaiser Permanente. The second is represented by the Mayo Clinic-type model. Delivery systems of these types can be found in a number of cities throughout the country. What is common to both models is their integration and alignment of quality and financial incentives of the three principal components—physicians, hospitals and insurance entities. Their physicians are generally on salary and receive additional remunerations if the enterprise prospers. However, from a national perspective, these models cannot accommodate the majority of US patients who are treated by independent physicians and hospitals with limited access to integrated provider enterprise's, such as these examples.
  • Another attempt to align providers' incentives and thereby control costs is a program called “pay-for-performance.” These initiatives involve the insurer awarding bonuses to physicians for improving a few selected quality indicators. Pay-for-performance has been a largely unsuccessful attempt to achieve what this invention has accomplished, which is the alignment of quality and financial incentives for independent hospitals, physicians and insurers through the novel provisioning of clinical quality improvement and financial information. The key to achieving the invention's enhanced benefits is transforming the readily available hospital and insurance information into actionable data for physicians to create clinical improvements and aggregating the data into transparent and easily understood measure of quality and efficiencies for the benefit of all stakeholders. The most recent delivery models created by the aforementioned federal legislation (PPACA) make this invention even more valuable than before.
  • The PPACA legislation implements global budgeting for hospitals and physicians who will be financially incentivized by Centers for Medicare and Medicaid Services (CMS) for improving the quality and efficiencies of their care. The previously mentioned ACOs, ACEs, and CO-OPs are three other federally designed delivery systems that are dependent on global budgets that will be divided between the hospital and physicians on the basis of objective measures. The technologies, algorithms and quality indices of this invention are uniquely designed to provide the objectively defined, appropriate reimbursements for the hospital and physician providers.
  • SUMMARY OF THE INVENTION
  • The invention's technologies, processes and algorithms facilitate an integrated, value-based delivery system across the continuum of care (inpatient and outpatient) in which a healthcare insurer or public agency can financially incentivize providers who will knowledgeably share the net savings between the hospital and physician providers whose practice patterns demonstrate superior performance.
  • These unique processes utilize risk-adjusted, clinical quality data from hospitals' medical records departments, hospital Medicare specific data, insurers'routinely aggregated claims data, patients' ambulatory outcomes collected by physicians' offices and other examples, but not limited to, National Hospital Quality Measures and Accountable Care Organization Measures. What is pragmatic and synergistic about the invention is its ability to re-purpose the hospitals', physicians' and insurers' routinely used data, which in and of themselves, are not unique. However, the invention's ability to use these same data for four critical functions is unique. First, the invention's processes transform the routinely used data into actionable, clinical quality improvement data for physicians. Second, its algorithms quantify the results of physicians' practice pattern enhancements, third, the algorithms assign appropriate provider remunerations based on the quality and cost efficiency outcomes and fourth, the invention converts these data into an Index of Quality Improvement that documents a hospital's and medical staff's outcomes over time. For the first time, independent physicians and hospitals will have inpatient, outpatient and insurance data, which can be used to improve clinical, financial and patient centered outcomes while directly linking their quality improvements to appropriate financial rewards. Moreover, employers, patients, public agencies and the providers themselves will have a transparent and accurate measure of the providers' quality and cost efficiencies over time.
  • Testaments to the uniqueness of this invention are the many literature references to the need for providers and insurers to align their incentives for quality and cost control purposes; juxtaposed to the numerous unsuccessful attempts in the marketplace to accomplish the alignment. Using this invention's technologies, processes and algorithms, providers and insurers will be able to align their incentives, control costs and deliver transparent, superior quality outcomes to the benefit of their patients, themselves and our entire US healthcare system.
  • Historically, independent physicians, hospitals and insurers have each had their own data, which has been used for their specific and independent purposes. Prior to this invention, there had never been a process for transforming these disparate, but readily available, clinical and financial data into actionable repositories of information.
  • The current invention incorporates medical knowledge into the processes and algorithms that combine inpatient quality outcomes, ambulatory quality measures and health insurers' financial data into actionable information that hospitals and physicians can use to improve the efficacies and efficiencies of their care. It then quantifies the financial net savings that predictably accrue as a result of the providers' improved medical outcomes. The invention's processes and algorithms also provide the information necessary for the health insurer to equitably share the net saving with the physicians and hospitals as incentives to continuously improve the quality of their patients' care and control costs. In this manner the providers and insurer align their quality and financial incentives and create a virtual integrated delivery system of independent practitioners.
  • Moreover, this invention facilitates the formation of integrated delivery systems that can be scaled to every community in the nation, which can maximize the health benefits for our entire society.
  • One advantage of the present invention is the incorporation of clinical decisions, processes and algorithms transform four types of commonly used data into actionable information with which physicians improve clinical quality and cost efficiencies. (Insurers' claims data, hospital medical records data, hospital Medicare-specific quality data and patients' self-assessed quality outcomes generated from physicians' offices.)
  • Another advantage is that clinical decisions and processes determine which clinical specialties to include in the quality improvement initiative and the number of physicians in each.
  • Yet another advantage of the current invention is that clinical decisions determine which Major Diagnostic Categories (MDC) and Diagnosis Related Groups (DRG) to assign to which of the clinical specialty groups.
  • Another advantage of the current invention is the ability to use clinical decisions to determine case volumes that constitute adequate numbers of patients.
  • Yet another advantage of the current invention is that clinical and administrative processes determine which patient groups to include in the initiative and calculations by geography, type of insurance plan, etc.
  • Still another advantage of the present invention uses clinical decisions and administrative processes to determine how many and which DRGs to include in the RIV computations for financial bonuses.
  • Another advantage of the current invention is that clinical decisions determine which of the CMS indicators and other clinical indicators are appropriate for quality measurement and remuneration.
  • Yet another advantage of the current invention is that clinical decisions determine what level of hospital's clinical indicator compliance should be considered as an acceptable quality level for each indicator group.
  • Still another advantage of the current invention uses algorithms to calculate the net changes in quality indicators, determine the quality bonus factor, apply the results to the sliding scale and calculate the bonus distribution between physicians and hospital.
  • Still another advantage of the current invention is that clinical processes are established to determine the improvement percentages that are attributable to the hospital personnel and those to the physicians.
  • Another advantage of the current invention is that processes determine who and how the “improvements” are to be determined for remuneration (Acceptable Indicators or mortality etc.)
  • Yet another advantage of the current invention is that insurer's data and administrative processes are used to determine expected inflation rates for Inpatient, Outpatient and Professional components of future expenditures to calculate physicians' bonuses for inpatient care.
  • Another advantage of the current invention is that insurer's data, actuarial process and algorithms calculate overall Per Member Per Month (PMPM) saving over 16 month periods to determine net saving for value-sharing among insurer, physicians and hospital. (For all inpatient, outpatient and ambulatory care.)
  • Still another advantage of the current invention is that clinical decisions and administrative processes designed Excel spreadsheet algorithms that determine bonuses and value-sharing among the three constituents (Physicians, hospitals and insurer).
  • Still another advantage of the current invention is that Algorithms assess, quantify and summarize the clinical quality and efficiency improvements. Insurer's claims data and the invention's calculations determine whether bonuses are awarded based on improvements. (Bonuses dependent on quality being maintained or improved.)
  • Another advantage of the current invention is that clinical and actuarial processes were established to determine “Claims Paid Dollars” and sliding scales of Claims Paid Dollars used by quality metrics. (Quality measures 1, 2 and 7 use sliding scales.)
  • A further advantage of the current invention is that clinical processes determine “Calculated Net Percentage Change” that constitute “improvement” or declination of quality
  • Yet another advantage of the present invention is that clinical processes determine “Clinical Indicators (CI) Net Percentage Change Multiplier” that should be rewarded for “improvement.”
  • Another advantage of the present invention is that clinical, actuarial and administrative processes determine who and how computation of “improvements” will be determined at the end of the year.
  • Still another advantage of the present invention is that clinical and administrative processes determine which of the paid dollar categories from the insurer's data should be considered for bonuses (Inpatient, Outpatient, Professional Dollars, etc.?)
  • Another advantage of the present invention is that clinical decisions and administrative processes determine the improvements that are attributable to the hospital personnel and those to the physicians to determine percentage remuneration.
  • Yet another advantage of the present invention is that clinical processes determine how the decision-support tool arrays data using four quadrant graphs in order to determine reductions in variation of care processes.
  • Furthermore, another advantage of the current invention is that the clinical and administrative processes determine the technique to be used for measuring weight adjusted dollar averages at year's end.
  • Yet another advantage of the current invention is that clinical decision and administrative processes determine appropriate “Annual Improvement Percentage” that determines appropriate “Bonus Percentage.”
  • Still another advantage of the current invention is that Algorithms calculate the expected, year-end dollar resource consumptions (expenditures) using insurer's inflation rates (Inpatient 8.7%, Outpatient 5.5%, Professional 6.3%).
  • Another advantage of the current invention is that clinical decisions determined how to measure Reductions In Variation (RIV) of Charges and Length of Stay (LOS) for selected DRGs. Changes in Departmental Variations are measured using a decision-support tool “Sherlock” that arrays the hospitals' medical records data and computes variations.
  • Yet another advantage of the current invention is that clinical decisions determine if or when to include readmission rates in algorithm for remuneration.
  • Still another advantage of the current invention is that administrative decision processes determine “Bonus Percentage” for each “Level of Individual Participation,” that is, physician participation.
  • Another advantage of the current invention is that clinical, administrative and actuarial processes determine percentage of sharing between insurer, hospital, physicians and Verras.
  • Yet another advantage of the current invention is that actuarial and clinical processes determine dollars that are available for bonuses and value-sharing using algorithm based on 3 year averages of insurer's paid dollars for each of the clinical specialties that physicians used to improve quality and efficiencies.
  • Furthermore, another advantage of the present invention is that administrative and actuarial processes determine a method of distributing available dollars if no, or only a portion of value-sharing dollars are available.
  • Another advantage of the present invention is that administrative processes determine how start-up costs are covered, by whom and with which dollars.
  • A further advantage of the current invention is that algorithms determine bonuses for “inpatient” and “facility outpatient care” as well as for value-sharing (net-savings) for total resource, utilization, inpatient, facility outpatient, professional fees and ambulatory (office) care.
  • BRIEF DESCRIPTION OF THE DRAWINGS
  • The above mentioned and other objects and features of this invention and the manner of attaining them will become apparent, and the invention itself will be best understood by reference to the following description of the embodiment of the invention in conjunction with the accompanying drawings, wherein:
  • FIG. 1 depicts a flow chart indicating the flow of, use of and dissemination of hospital data, physician's office data, public (MedPar) data and data from insurance companies;
  • FIGS. 2A and 2B shows multiple index of quality improvement (IQI) calculations using 6 metrics and depicting 3 year trends of performance scores for 8 hospitals in both graphical (FIG. 2A) and tabular (FIG. 2B) forms;
  • FIGS. 2C and 2D depicts a 3 year trend of IQI using 7 metrics and illustrating the performance score for a single hospital, here hospital F, in both graphical (FIG. 2C) and tabular (FIG. 2D) forms;
  • FIG. 3 illustrates the relationship between the Sherlock computational model and the Watson analytic model, and the flow of information between the two systems;
  • FIGS. 4A and 4B depict a two-part flow chart indicating the four primary sources of medical data collection, the processing of that data, and the seven quality metrics and the specific Tables which represent their calculation;
  • Table 1 represents a spreadsheet showing hospital and physician quality measures, specifically inpatient and outpatient facility paid dollars, and professional paid dollars;
  • Table 2 represents a spreadsheet showing hospital and physician quality measures, specifically bonus calculations illustrating total paid dollars;
  • Table 3 represents a spreadsheet showing a spreadsheet depicting value sharing calculations, specifically projected spending figures;
  • Table 4 represents a spreadsheet depicting clinical services and numbers of physicians for bonuses;
  • Table 5 represents spreadsheet total bonus and value sharing summaries, which includes total bonuses, potential value share calculation and bonuses and value sharing, hospital and MDs;
  • Table 6 represents a spreadsheet showing total MD bonuses by service utilizing the present invention and non-hospital MDs;
  • Table 7 represents a spreadsheet detailing quality category summaries of hospital and physician measures;
  • Table 8 represents a spreadsheet continuing with clinical, rate-based indicators for total bonus, hospital bonus, MD bonuses and bonus per MD;
  • Table 9 represents a spreadsheet, illustrating breakdown of the total reductions in variation detailed according to service;
  • Table 10 represents a spreadsheet showing changes in resources consumption, financial by service (Service 1: Cardiopulmonary, Service 2: neurosurgery, Service 3: Neurology, Service 4: Orthopedics, Service 5: OB/GYN) for inpatient and outpatient breakdowns culminating in total bonuses for inpatient and outpatient figures for both Hospital bonus and MD bonus;
  • Table 11 represents a spreadsheet which depicts quality category summaries of physician measures indicating total bonus dollars per service (service 1: cardiopulmonary, service 2: Neurosurgery, service 3: neurology, service 4: orthopedic surgery and service 5: OB/GYN)
  • Table 12 represents a spreadsheet demonstrating the use of computerized patient health record (PHR) with a total sum and average bonus per MD;
  • Table 13 represents a spreadsheet depicting the total of all bonuses;
  • Table 14 represents a spreadsheet showing details the hospital and physician quality measures, more specifically, the CMS (Medicare) clinical indicators, hospital bonus, MD bonuses and bonus per MD;
  • Table 15 represents a spreadsheet focusing on the formula used to determine clinical, rate-based indicators;
  • Table 16 represents a spreadsheet illustrating the formulae used to determine the hospital bonus (25%), MD Bonuses (75%), and the average bonus per MD according to the present invention;
  • Table 17 represents a spreadsheet depicting an example of a cardiopulmonary inpatient using a weighted average based on the percent improvement of the per case, weighted adjusted resource consumption;
  • Table 18 represents a spreadsheet showing an example of a neurosurgery inpatient, using a weighted average to determine resource consumption, total bonus, hospital bonus, MD bonuses and bonus per MD;
  • Table 19 represents a spreadsheet demonstrating an example of a neurology patient using a weighted average for calculating hospital bonus, MD bonuses and bonus per MD;
  • Table 20 represents a spreadsheet illustrating an orthopedics inpatient using a weighted average to calculate hospital bonus, MD bonuses and bonus per MD;
  • Table 21 represents a spreadsheet demonstrating the use of weighted average in calculating the hospital bonus, MD bonuses and bonus MD in an OB/GYN inpatient;
  • Table 22 represents a spreadsheet used to calculate the expected cost in 2007, the weighted average in 2007, the annual improvement or degradation and the annual improvement percent bonus;
  • Table 23 represents a spreadsheet showing the calculation of the expected cost for a cardiopulmonary outpatient utilizing a weighted average to calculate the total bonus, hospital bonus, MD bonuses and bonus per MD;
  • Table 24 represents a spreadsheet for a neurosurgery outpatient utilizing weighted averages and expected cost to calculate total bonus, hospital bonus, MD bonuses, and bonus per MD;
  • Table 25 represents a spreadsheet illustrating the use of a weighted average, and formula to establish total bonus, hospital bonus, MD bonuses and bonus per MD for a neurology outpatient;
  • Table 26 represents a spreadsheet calculation of total bonus, hospital bonus, MD bonuses and bonus per MD utilizing weighted averages for an orthopedics outpatient;
  • Table 27 represents a spreadsheet demonstrating the use of weighted averages in the calculation of OB/GYN, outpatient service 5, to determine total resource consumption, hospital bonus, MD bonuses and bonus per MD;
  • Table 28 represents a spreadsheet for another outpatient, not included in bonused services, utilizing weighted averages to determine expected cost, weighted average cost, annual improvement/degradation and annual improvement %;
  • Table 29 represents a spreadsheet which illustrates how to determine physician quality measures utilizing clinical pathway development and use;
  • Table 30 represents a spreadsheet demonstrating the current annual paid dollars and formula to determine MD bonuses for clinical pathways, service 2, neurosurgery, total bonuses;
  • Table 31 represents a spreadsheet showing the formula used to determine clinical pathways (services 3-neurology) total bonus;
  • Table 32 represents a spreadsheet demonstrating the formula used to calculate total bonus for clinical pathways (service 4—orthopedics) total bonus;
  • Table 33 represents the spreadsheet showing the use of the formula to determine the total bonus for clinical pathways (service 5—OB/GYN); and
  • Table 34 represents a spreadsheet showing the use of an electronic health record (EHR) in determining the individual physicians with 10% patient use of to determine the total bonus and the average bonus per MD.
  • DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENT
  • The accompanying drawings, which are incorporated in and form a part of this specification, illustrate embodiments of the invention and together with the description, serve to explain the principals of this invention.
  • Referring now to the drawings, wherein similar parts are identified by like reference numerals, FIG. 1 shows a flow chart of data leading to the calculation of an IQI, and the pathways of use of that IQI. Data is originally sourced from hospital records, public data like MedPar, insurance companies and physician's offices. The data is fed to AIM technology algorithms and sent to Sherlock for conversion into hospital level data. Data from Sherlock also is sent to a Chart Abstraction Tool (CAT) and Watson knowledge system for transference into MD and patient level data. Both hospital level data and MD and patient level data are sent to a physician directed best practices knowledge base, and used in metric calculations. High quality efficiency outcomes lead to 7 or more metrics available for use in calculating an IQI. In FIG. 1, 7 metrics are shown: 1. National Hospital Quality Measures (NHQM); 2. Patient Satisfaction; 3. Mortality; 4. Morbidity; 5. reductions in variation (RIV); 6. Resource consumption; and 7. Accountable Care Measures (ACO.M), ambulatory outcomes (AMB.O) from outpatient MD offices. One or more additional factors, represented by metric 8 can also be used in the calculation of IQI. Once an IQI is determined, it is sent to public agencies, consumer, employers and optionally CO-Ops, and optionally may be sent back to the physician directed best practices knowledge base. CO-Ops may use the IQI information through their CO-OP Board and disseminated to employers/consumers, board MDs and hospital personnel. Therefore, as illustrated in FIG. 1 the present invention is a system for healthcare performance measurement and equitable provider reimbursement comprising the elements of: (a) gather medical information from hospital patients charts data, hospital medical records department data, insurance company data, and physician's office data; (b) aggregate the gathered data and calculating the following quality metrics: National Hospital Quality Measures (NHQM) mandated by Centers for Medicare and Medicaid Services (CMS), patient satisfaction, morbidity, mortality, reduction in variation, resource consumption; (c) calculate an index of quality improvement (IQI) for each healthcare provider; (d) generate value sharing computations and calculate overall net savings; and (e) distribute said net savings to physicians, hospitals, CO-OPs and insurers in the form of reimbursements.
  • FIGS. 2A and 2B shows multiple index of quality improvement (IQI) calculations depicting 3 year trends of performance scores for 8 hospitals in both graphical (FIG. 2A) and tabular (FIG. 2B) forms. The IQI is calculated using the six enumerated metrics and ambulatory outcomes and Accountable Care Organization (ACO) metrics from outpatient and physician's offices as a seventh metric added to the IQI calculation. IQI may be tracked for one or more healthcare providers and for one or more years, with resulting IQI performance trend information sent to employers, consumers, public agencies, CO-OPs and hospital personnel for the purpose of making decisions regarding healthcare provider performance and improvement.
  • FIGS. 2C and 2D depicts a 3 year trend of 7 performance score for a single hospital, here hospital F, in both graphical (FIG. 2C) and tabular (FIG. 2D) forms. Quality assurance and equitable reimbursement system (QAERS) algorithms are employed to generate value sharing computations and calculate overall net savings, wherein said value sharing computations and calculate overall net savings are used to calculate reimbursement rewards to be distributed to hospitals, clinical practice groups and physicians.
  • FIG. 3 illustrates the characteristics of and relationships between Sherlock and Watson, and in particular is illustrates the data flow between the two systems. AIM technology algorithms (as seen in FIG. 1) are employed to aggregate data gathered from medical information from hospital patients charts data, hospital medical records department data, insurance company data, and physician's office data, prior to providing the resulting information to a Sherlock sub-system. Sherlock sub-system aggregated data is further analyzed by a Watson sub-system which explains diagnoses and procedures by who, what and why, sequence of events and what was not documented, explains specific resources by specific type of tests, breakdown of drugs, identifies why extra days were spent in hospital, and converts to true costs, and create a best practices framework by database of clinical variation by diagnosis and procedure, establishes a computerized physician order entry (CPOE) customization and facilitates clinical pathway construction. At the revenue code level—every billed item in a hospital has a revenue code. For example a Chest X-ray is 320. Sherlock has the capability of telling us that during a specific hospital stay, there were 10 chest rays using these codes. However, the revenue code level cannot tell you the specific type of chest X-ray nor when it was ordered and who ordered it. Watson's Chart Audit tools use the Revenue Codes targeted by Sherlock to discovery the basis of why, who, when these order were written. CPOE is short for Computerized Physician Order Entry. Now that all hospitals are moving toward the Electronic Health Record (EHR or EMR), a physician must bring up a screen and decide what orders are required rather than just pull the chart and write them out. In order to expedite this process, templates are built by diagnosis to list the most appropriate or likely test based on diagnosis. Watson will use a physician's actual order history, pull out their best practices and customize these templates. The value here is that by customizing (shortening) this list it improves compliance with the CPOE and hopefully stops the physician from over-ordering.
  • FIG. 4A shows a flow chart of data as it is generated by hospital medical records, physician's office and insurer reimbursement (paid) as the data are identified as patient risk-adjustment, patient self-assessed outcomes, aggregated insurer data.
  • The data is submitted for physician and hospital quality improvement activities, ambulatory quality improvement activities and inpatient charges outpatient charges professional charges and overall PMPM data. The congregate of data is then submitted for processes for assessment of quality outcomes and cost efficiency improvements in FIG. 4B. It is anticipated that IQI may be calculated using other metrics as they become recognized national standards for measuring quality assurance and efficient performance of healthcare providers. Additionally, said method may include the step of ranking quality metrics as to importance for quality and financial incentives, prior to said step of calculating an index of quality improvement (IQI) for each healthcare provider.
  • The data is then processed for decisions, that is, which quality metrics for bonuses and which for value-sharing, ranking quality metrics as to importance for quality and financial incentives and how to quantify improvements.
  • The decisions for rational distributions of bonuses for inpatient care and value-sharing for overall quality and cost efficiencies are next and finally, algorithm construction to appropriately distribute net savings to physicians, hospitals and insurer.
  • Background
  • Verras Medical, Inc. has provided health care services to hospitals and their medical staffs for the past 24 years. The company's unique services consist, in part, of reformatting risk-adjusted hospital data using a proprietary decision-support tool, Sherlock, and demonstrating the clinical quality variations in physicians' practice patterns. Using these data and its proven clinical process improvement techniques, Verras is able to assist physicians in their efforts to demonstrably improve the outcomes of care for their hospitalized patients. Some progressive hospitals and their medical staffs have taken these additional efforts for purely quality improvement reasons. However, these initiatives are not widespread as they require additional time and expenditures. Many policy makers now believe that physicians and hospitals who objectively improve their quality and efficiency performances should benefit from the same financial incentives enjoyed by virtually every other market. Financial incentives are the primary reason that the majority of American industries have outpaced healthcare in terms of continuously improving the quality and efficiencies of the products and services they offer.
  • The Fundamental Problem
  • During the late 1980's and early 1990's, private and public healthcare purchasers sought relief from escalating medical costs through managed care entities. These third parties implemented stringent price controls that were predictably effective, but only for a short time. After the first wave of managed care, a patient backlash is now underway because third parties have no allegiance to the patient-physician relationship and patients are more interested in access to their physicians than in their employers' or Medicare's cost savings. Patients need their choice of providers; purchasers need to know the value of the services for which they are paying large sums of money and providers need the latitude to practice their professions without micro-management encumbrances by third parties. But these ideals have not materialized. Now, for insurers, purchasers and policy makers are looking around and asking, “what's next,” there is a solution created by Verras Medical Inc. for a hospital and not-for-profit Insurer in a western state. It is imperative that the Insurer be not-for-profit because providers would know that any efficiency created by their practice pattern changes would not accrue to their benefit as it would in other industries. The net profits would first go into the pockets of the investors as it has in the past.
  • The Current Marketplace as a Guide to the Future
  • There are two integrated healthcare delivery systems that have stood the test of time and are well recognized for their efficiencies. The first is a Health Maintenance Organization (HMO), Kaiser Permanente. The second model is the Mayo Clinic-type systems, which are integrated healthcare delivery systems. Such integrated systems can be found in a few cities throughout the country. The structural component that is common to both of these systems is their integration of the three components—physicians, hospitals and insurance entities. In these systems, all stakeholders have the same quality and financial incentives. If one constituent improves its quality and efficiencies, the other two parties also benefit. In these models the physicians are on salary, thus obviating the need to precisely measure the quality or cost efficiencies of individual doctors or the specific hospitals or clinics in which they practice. All receive bonuses if the enterprise prospers.
  • However, the vast majority of patients in the US are treated by independent physicians and hospitals. Based on the experiences of the two previously mentioned models, the need to integrate independent hospitals and medical staffs into provider enterprises with similar quality and financial incentives has long been recognized. Without the hospitals being on the same charge master and physicians on the same payroll, there has been no means of quantifying the quality and cost efficiencies of each of the component parts and differentially rewarding them. Without integrating the disparate data used by these entities and the Insurers with whom they contract, there has been no means of compensating the providers according to their respective quality and efficiency performances. This has led many to speculate that the only way of creating the necessary integration of these divergent constituencies is to devolve to a single-payer, nationalized system. This must not be the nation's only option.
  • The Solution
  • There is a more American-like solution made possible by the Verras algorithms in the form of an integrated, value-based system comprised of independent physicians and hospitals in which the quality and economic incentives of the insurer, hospital and physicians are all aligned.
  • The solution for an effective American healthcare system should be founded on rational, free market forces where public and private purchasers contract with properly incentivized providers for services using established measures of quality and price. When purchasers, their insurers and patients have reliable information with which they can knowledgeably reward providers who demonstrate superior performance, then effective and efficient healthcare will be the norm. What has been unavailable until now are the means to appropriately incentivize hospitals, insurers and physicians on the basis of objective clinical data improvements and create a virtual integrated delivery system of independent providers and insurers. This requires algorithms that combine physicians' clinical process improvement data, ambulatory outcomes, hospital quality data and insurers' financial data. Without these algorithms and processes, an integrated, private fee-for-service model that aligns all stakeholders' incentives is not possible. Moreover, the delivery system must be scalable to every community in the nation for maximum societal benefits.
  • The Role for Verras' Processes and Algorithms Using New Technologies
  • Inpatient clinical systems and new Internet-based outpatient technologies are now available to monitor all aspects of medical quality and assist doctors as they strive to optimize medical outcomes and the appropriate use of resources. However, testaments to the fact that such technologies are not being effectively utilized are the wide variations in diagnostic and treatment options physicians deploy for comparable clinical conditions. These variations have persisted for years in spite of reams of medical, evidence-based literature. Without the means to use these data sources to appropriately align provider's incentives so they will modify their practice patterns, these quality variations and inefficiencies will persist unabated.
  • In order to document that hospital care is significantly improving patients' health, it is as important to measure patients' post-discharge longitudinal health and functional metrics as their inpatient outcomes. This continuous quality-monitoring feature is unique to the initiative that has been used to develop the Verras processes and algorithms. It is made possible by new Internet technologies that use patient-centric, office medical records techniques. These electronic health records (EHRs) can facilitate patient-physician collaboration by enabling patients to assist physicians in creating their medical office records. This function is a major time and cost savings for doctors, which is why they will adopt them. Moreover, physicians have condition-specific, evidence-based information at hand exactly when they need it, which is when they're with the patient. Patients' education is also facilitated through condition-specific information that is chosen by the doctor and available on the patient's electronic chart in the physician's office record. The outputs of this system are a significant part of the algorithms for assessing and rewarding outpatient metrics of quality. These outcomes are patients' longitudinal health and functional status that can now be monitored using SF-36s and condition-specific functional questionnaires that are available for analysis every 6 months. These are metrics necessary for quality improvement and doctors' quality reimbursements.
  • Technologies such as these facilitate the shift toward a consumer-driven healthcare system. The time has come for patients (consumers) to participate in the medical decision-making process and Verras algorithms facilitate payments for physicians who interact with their patients to improve patients' satisfaction and clinical outcomes.
  • A Unique Approach and a Model for the Nation
  • The promise of an integrated, value-based, market-driven healthcare delivery system comprised of independent physicians, hospitals and insurers has not materialized to date for a number of reasons, not the least of which has been the inability to quantify the quality and efficiencies of these three constituents. There has also been the paucity of patients' ambulatory health outcomes information that has led to the recent emphasis on trying to gets providers to adopt transportable, electronic health records. These impediments no longer exist because of Internet technology and risk-adjustment technologies critical to the assessment of clinical quality. The only missing element is to align the incentives of independent physicians, hospitals and non-profit insurers and appropriate reward each stakeholder in accordance to their contributions to the enterprises' overall quality and cost efficiency improvements. This is now possible using Verras' clinical improvement technologies and processes that have created algorithms to define and measure each metric of quality and associated efficiencies.
  • These processes algorithms represent a significant step toward the value-based delivery goal by defining and quantifying the contributions of each constituent when inpatient and outpatient outcomes are improved. The algorithms allow for the rewarding of providers' performances on standard quality and efficiency outcomes, but also in three novel ways.
      • 1. They reward providers who measure and control variations in hospital clinical processes and outcomes. (Uncontrolled variations are well documented sources of dis-quality and inefficiencies.)
      • 2. They recognize patients' satisfaction as an important quality metric and propose to reward physicians on this self-assessed outcome over time using an EHR.
      • 3. The algorithms reward physicians who monitor and improve patients' health and functional outcomes in the ambulatory sector, including medical offices using a transportable electronic health record (EHR).
  • The alignment and equitable remuneration of physicians', hospitals' and not-for-profit insurance companies' incentives will create provider “teams” that can successfully collaborate and implement value-base delivery systems. There are no political or structural changes at the national level that could be more valuable to the future viability of Medicare and our private, healthcare delivery system than to implement and expand quality-based models such as are possible using these processes and algorithms. Initiatives such as this will be made possible when insurers and providers integrate and utilize these algorithms to appropriately reimburse the highest quality, most cost efficient physicians and hospitals. When the Verras algorithms are used to properly incentivize and reimburse providers, it is no exaggeration to state that this will be the most comprehensive inpatient and outpatient quality and cost efficiency effort ever implemented by the private healthcare sector.
  • Verras' Technologies that Support the Verras Process
  • Sherlock and Watson Descriptions:
  • Verras has spent the past four years developing the processes necessary to create algorithms that define and quantify clinical quality and cost efficiency improvements for the purpose of appropriately rewarding providers. These unique processes utilize risk-adjusted clinical quality data from hospitals' Uniform Hospital Discharge Data (UHDDS) in combination with insurers' routinely aggregated claims data and patients' self-assessed, ambulatory outcomes (Health Status, Functional Status and Patient Satisfaction). The risk-adjusted clinical hospital data, the insurer's claims data and the self-assessed outcomes data, in and of themselves, are not unique. However, the processes that transform these data into actionable information in the hands of motivated providers and the algorithms that calculate and collate the results of their practice pattern enhancements into appropriate provider remunerations are unique. For the first time, physicians and hospitals will have inpatient, outpatient and insurance data they can use to improve their clinical and patient centered processes and outcomes and have their improvements be directly correlated with appropriate financial rewards.
  • Without the novel means provided by Verras' processes and algorithms that combine and objectively quantify the quality and cost efficiency metrics that are attributable to each of the three constituencies, (hospital, physician and insurance company), an integrated, value-based system for independent physicians and hospitals is not possible. These algorithms provide a new and effective means to objectively align the incentives of physicians, hospitals and Insurers and appropriately reward those who improve clinical quality and cost efficiencies.
  • Each portion of this detail description of the preferred embodiment of the invention in the present application is divided into;
  • 1. Data sources
  • 2. Processes and decisions necessary to design the algorithms
  • 3. Algorithms
  • The Verras Algorithms are designed to:
      • 1. Measure numerous types of quality improvements and
      • 2. Compute and reward providers' resource consumption efficiencies based on the results of the quality improvements; in Quality Assurance Equitable Reimbursement Systems (QAERS), if quality is not maintained or improved, there are no bonuses.
      • 3. To be specific to each data source and quality indicator
  • Two Types of Financial Incentives for Providers:
      • I. Bonuses—Bonuses are rewarded for inpatient care only.
      • II. Value-sharing—Value-sharing is computed on inpatient, facility outpatient and ambulatory outpatient (medical office) care.
  • I. Bonus calculations are calculated by each of five clinical services: cardiopulmonary, neurosurgery, neurology, orthopedics and obstetrics. (Inpatient inflation rates are experiential at 8.5%, Outpatient—5.5% and Professional 6.3%.)
  • II. Value-sharing calculations are for the physicians in the 5 clinical services plus all physicians using the electronic health record (EHR) and are based on the physicians being able to off-set their historic 7.1% inflation rate with efficiencies that create a 0.01% inflation rate in year one. (The Insurer's experiential PMPM inflation rate is 7.1%).
  • I. BONUS CALCULATIONS by Quality Metrics: 1-7—(References are by Table Numbers to the Accompanying Tables found on drawing sheets). Regional Medical Center (RMC) and Health Center North (HCN) are used as two Example hospitals.
  • 1. MEDICARE, MEDICAID (CMS) & JCAHO—Quality Metric 1
  • (see Table 7 and Table 14 on drawing sheets)
  • Data Source
  • Hospital staff personnel manually abstract Medicare (CMS) defined data from patients' charts. (Example—Time from admission to receiving antibiotics.) These data are aggregated by Verras, or other CMS Vendor, and submitted to CMS and JCAHO. (These “data source” steps are not a part of the Verras patent applications. They are processes all hospital use that prepare the data used by QAERS).
  • Verras Process:
  • The process of preparing the data for use by Verras Algorithms is to determine:
      • 1. Which clinical specialties to include in the quality improvement initiative and the number of physicians in each group. Decisions based on case volume, total resources of the clinical service and the interest in participation by each physician. (Should all physicians on the staff be included? Should primary care physicians be included? Should hospitalists be included, if so, with cardiopulmonary group or in their own group?)
      • 2. Which Major Diagnostic Categories (MDC) and Diagnosis Related Groups to assign to which of the clinical specialty groups. ((Examples are Major Diagnosis Group (MDC) 4 (Pulmonary) and MDC 5 (Cardiac) are place into one clinical group in the example hospital to form the Cardiopulmonary Group.))
      • 3. Which of the CMS indicators are appropriate for use for quality measurement given the choices of clinical specialties? (There are 5 categories of Medicare Indicators but in the example hospital only 4 are submitted to CMS. Should all be included?)
      • 4. Determine which patient groups to include in the initiative and calculations by geography, type of insurance plan etc. (Which counties of the state should be included, should catastrophic cases (>530,000/case) be included? Which patients for which type of insurance coverage should be included? Should self-insured employer's patient be included?)
      • 5. Confer with insurer as to which dollars will be in the bonus pool. Should it be costs, charges or paid dollars?
      • 6. What level of hospital's indicator compliance should be considered as an acceptable quality level for each indicator group?
      • 7. How and who determines acceptable compliance at the end of the year?
      • 8. Determine the improvement percentages that are attributable to the hospital personnel and those to the physicians. Bonus sharing should be determined by level of expertise and effort, such as should the sharing be 50/50 between hospital and physicians?
      • 9. Collaborate with insurer to determine expected inflation rates for Inpatient, Outpatient and Professional components of the costs. (Five years of historic data should be used to determine inflation rates.)
      • 10. Determine which of the paid dollar categories from the insurer's data should be considered for bonuses (Inpatient, Outpatient, Professional Dollars, etc.?)
      • 11. Determine bonus percentages and sliding scale of Claims Paid Dollars
      • 12. Determine monitoring and reporting cycles. (Every quarter, 6 months, 1 year?)
      • 13. Determine how the results of the quality indicator will be reported to hospital staff and physicians.
      • 14. Determine if one or both hospitals' indicators should be used, if so determine clinical reasoning for decision.
      • 15. Determine the relative impact on overall inpatient quality that the CMS indicators impart compared to other medical indicators in order to build the algorithms appropriately.
      • 16. Determine if physicians should get a bonus for quality improvements on a flat rate of dollars, or should they get increased bonuses if they maintain or improve quality based on percentages of total dollars to also reward cost efficiencies based on a sliding scale. If so, design the sliding scale and create a means to change the ranges on the scale if dollars are higher or lower than expected.
      • 17. Design Excel Spreadsheet algorithms to determine bonuses and value-sharing.
  • Verras Algorithms:
  • Hospital-Specific Centers for Medicare and Medicaid Services (CMS) and JCAHO Core Measures—[Annual Monitoring and Reporting]
  • Bonus from Insurer:
      • 1. Measurement: All Regional Medical Center (RMC) business (all commercial and Medicare), all MDCs, all services for Facility Inpatient and Facility Outpatient.
      • 2. Bonus Criteria: Bonuses are predicated on these quality metrics being maintained at an acceptable level as determined by JCAHO/CMS, or improved. Potential bonuses for 4 standard CMS groupings, containing 23 specific indicators that are hospital specific and in keeping with these agencies quality indicators (Appendix A)
      • 3. Bonus received for each of 4 criteria at 70% level.
      • 4. Bonuses: Calculated based on insurer total claims paid dollars: Inpatient Facility and Outpatient Facility paid dollars only, all MDCs, all services for participating groups only, for members with addresses in the six county area: Jackson, Lake, Jefferson, Lincoln, Toole and Tyler.
      • 5. Bonus percentage: An increasing bonus percentage is applied as total paid dollars decrease to reward physicians' efficiencies in resource consumption.
      • 6. Verras measures, computes results and reports data at the end of year-one.
  • IN-TEXT TABLE 1A
    Actual Total Claims Paid Dollars
    Bonus Percentage Inpatient and Outpatient Facility
    0.000% Greater than $6,500,000
    0.030% $6,400,000 to $6,500,000
    0.035% $6,300,000 to $6,399,999
    0.040% $6,200,000 to $6,299,999
    0.045% $6,100,000 to $6,199,999
    0.050% $6,000,000 to $6,099,999
    0.055% $5,900,000 to $5,999,999
    0.060% $5,800,000 to $5,899,999
    0.065% $5,700,000 to $5,799,999
    0.070% $5,600,000 to $5,699,999
    0.075% $5,500,000 to $5,599,999
    0.080% Less than $5,500,000
  • Bonus Distribution: 25% Hospital and 75% MDs
  • Formula for Bonus:
      • A. Actual Total Claims Paid Dollars multiplied by corresponding Bonus Percentage (using in-text Table 1A above)=single group bonus
      • B. Single group bonus multiplied by number of compliant groups (Maximum of 4)=Total Bonus paid to hospital and physicians
      • Example of 4 compliant groups
      • $5,500,000×0.075%=$4,125×4=$16,500 Bonus to Hospital & MDs
        • Hospital Bonus (25%)—$4,125
        • MD Bonus (75%—$12,375
        • Bonus per MD (No. 24)—$516
  • 2. CLINICAL RATE-BASED INDICATORS—Quality Metric 2
  • (see Table 8 and Table 0.15 on drawing sheets)
  • Data Source
  • Uniform Hospital Discharge Data Set (UH DDS)—routinely and automatically gathered by hospitals' medical records departments.
  • (These “data source” steps are not a part of the Verras patent applications. They are processes all hospital use.)
  • However, the process that Sherlock uses to aggregate the rate-based indicator data in preparation for use by QAERS is a part of this patent because it reformats data in a way that is new.
      • Verras Process to Facilitate Providers Improving their quality and cost efficiency outcomes.
    Sherlock Watson
  • Verras Process to Create QAER Algorithms:
  • The process of preparing the data for use by Verras Algorithms is:
      • Verras computes the rate based indicators and formats the data for use by clinicians. (Example—Rates of caesarian sections for the past 3 years.)
      • 2. Determine how to determine the clinical significant for presentation to physicians. (Use 2 standard deviation error bars to demonstrate statistical significance. Determine format for data presented to physicians using Verras decision support tool “Sherlock”.)
      • 3. Determine if calculated should be based on insurer total claims paid dollars: Inpatient Facility and Outpatient facility only? Whether on all MDCs? All services for participating groups only? Should members with addresses in the six county area be used or should all patients be included?
      • 4. Determine the monitoring cycle and reporting cycle.
      • 5. Determine the relative impact on overall inpatient quality that the CMS indicators impart compared to other medical indicators in order to build the algorithms appropriately.
      • 6. Determine which of the indicators are appropriate for inclusion in the algorithms for reimbursement
      • 7. Determine which indicators are appropriate for presentation to which clinical specialties.
      • 8. Determine who and how computation of “improvements” will be determined at the end of the year.
      • 9. Determine the improvement percentages that are attributable to the hospital personnel and those to the physicians. Bonus sharing should be determined by level of expertise and effort, such as should the sharing be 50/50 between hospital and physicians?
      • 10. Determine which of the paid dollar categories from the insurer's data should be considered for bonuses (Inpatient, Outpatient, Professional Dollars, etc.?)
      • 11. Determine the algorithm to determine if improvements or quality compromises are present.
      • 12. Determine “Calculated Net Percentage Change” that constitute “improvement” or declination of quality
      • 13. Determine “CI Net Percentage Change Multiplier” that should be rewarded for “improvement”.
      • 14. Determine the sliding scale: Bonus Percentage and Actual Total Claims Paid Dollars—Inpatient and Outpatient Facility
      • 15. Determine the improvements that are attributable to the hospital personnel and those to the physicians to determine percentage remuneration.
      • 16. Determine if physicians should be bonus for quality improvements on a flat rate of dollars, or should they get increased bonuses if the maintain or improve quality based on a percentages of total dollars to also reward cost efficiencies based on a sliding scale. If so, design the sliding scale and create a means to change the ranges on the scale if dollars are higher or lower than expected.
      • 17. Design Excel Spreadsheet algorithms to determine bonuses and value-sharing.
  • Verras Algorithms:
  • Clinical, Rate-Based Indicators (CI)—38 Required: Annual
  • Monitoring and Reporting
  • For Clinical Indicators increments of bonuses, the dollars are tied to the model. The bonuses are incrementally divided by $100,000 improvements. Those dollar amounts will be changed depending on the actual value calculated by the model at the end of the year.
  • Bonus from Insurer:
      • 1. Measurement: All RMC business (commercial and Medicare) all MDCs, all services for Facility Inpatient and Facility Outpatient.
      • 2. Bonus Criteria: Bonuses are predicated on these quality metrics being maintained at an acceptable level or improved as determined by the ratio of improved or stable numbers of clinical indicators and those that were degraded. (CIs selected are 38 standard rate-based, quality indicators that will be expanded over time. (see Appendix B).
      • 3. Bonuses: Calculated based on insurer total claims paid dollars: Inpatient Facility and Outpatient facility only, all MDCs, all services for participating groups only, for members with addresses in the six county area: Jackson, Lake, Jefferson, Lincoln, Toole and Tyler.
      • 4. Bonus Percentage: The net improvement in Clinical Indicators must be unchanged or improved for providers to receive bonuses for outcomes improvements.
      • 5. CI Net Percentage Change Multiplier determines reward levels for quality improvements.
      • 6. Verras measures, computes results and reports CI data at the end of each year.
  • IN-TEXT TABLE 2A
    Calculated Net Percentage CI Net Percentage Change
    Change Multiplier
      0%-4.9% 100.00%
     5%-20% 200.00%
    21%-34% 300.00%
    35% or higher 400.00%
  • IN-TEXT TABLE 2B
    Actual Total Claims Paid Dollars-
    Bonus Percentage Inpatient and Outpatient Facility
     0.00% Greater than $6,500,000
    0.030% $6,400,000-$6,500,000
    0.035% $6,300,000-$$6,399,999
    0.040% $6,200,000-$6,299,999
    0.045% $6,100,000-$6,199,999
    0.050% $6,000,000-$$6,099,999
    0.055% $5,900,000-$5,999,999
    0.060% $5,800,000-$5,899,999
    0.065% $5,700,000-$5,799,999
    0.070% $5,600,000-$5,699,999
    0.075% $5,500,000-$5,599,999
    0.080% Less than $5,500,000
  • Bonus Distribution: 25% Hospital and 75% MD's
  • Formula for Bonus:
      • A. Determine the net change in numbers of Clinical Indicators (CIs): (Number of CI unchanged or improved minus Number of Cl degraded=Net change in CIs.)
      • B. Compute the Percentage of Net Change (must be positive for bonus) (Net Change in CIs divided by total number of Cl's equals Net Percentage Change in CI)
      • C. Determine Net Percentage Change Multiplier based on the Calculated Net Percentage Change (see In-text Table 2A)
      • D. Determine Bonus Percentage using the Actual Total Claims Paid Dollars (Table 2B).
      • E. Compute Base CI Bonus by multiplying the corresponding Bonus Percentage by Claims Paid Dollars
      • F. Compute Total Bonus by multiplying Base CI bonus by Net Percentage Change Multiplier
  • Example:
      • 22 (CIs Unchanged/Improved)—14 (CI Degraded)=8 Net Change
      • 8 (Net Change)/36 (Total)=22% Net Percentage Change
        • Net Percentage Change Multiplier=300% (see In-text Table 2A)
      • $5,500,000×0.075%=$4,125 Base CI Bonus×300%=$12,375 Total Bonus for Hospital and MDs
        • Hospital Bonus (25%)—$9,281
        • MD Bonus (75%—$3,094
        • Bonus per MD (24)—$387
  • 3. REDUCTIONS IN VARIATION—Quality Metric 3
  • (see Table 9 and Table 16 on drawing sheets)
  • Data Source
  • Uniform Hospital Discharge Data Set (UHDDS)—routinely and automatically gathered by hospitals' medical records departments.
  • The process that Sherlock uses to aggregate and reformat the risk-adjusted data in preparation for use by QAERS is not a part of this patent. Sherlock reformats data used to assist physicians with the Verras' clinical process improvement (CPI) techniques. These techniques are the means clinicians use to reduce variation in their resource consumption (charges) and length of stay (LOS) outcomes to improve both quality and cost efficiencies over time.
  • Verras Process:
  • Decision support tool “Sherlock” arrays risk-adjusted data using four quadrant graphs.
      • 1. Sherlock uses the risk-adjusted data (APR-DRGs or Yale-DRGs, compares the outcomes of each acuity level against the hospital's self norm and arrays the data on a four quadrant graph. (See Exhibit A—APR-DRG 194 example)
      • 2. Measure Reductions In Variation (RIV) of Charges and LOS—(Change in Departmental Variation) are measured using Sherlock, Computes variations using Hospital Charges and LOS and presents data to physicians using 2 standard deviation ovals and one to three years of data by DRG specific data.
      • 3. Verras physician and hospital quality personnel present data to physicians to implement Continuous Quality Improvement activities (CQI)
      • 4. Determine the relative impact on overall inpatient quality that the Reduction In Variation (RIV) imparts compared to other medical indicators in order to build the algorithms appropriately.
      • 5. Determine case volumes that constitute adequate numbers of patients
      • 6. Determine adjustment percentage of paid dollars to be used and if it should be the same or different for each clinical service.
      • 7. Determine if caps are necessary on total bonuses.
      • 8. Determine how many and which DRGs to include in the RIV computations for financial bonuses.
      • 9. Determine inpatient and/or outpatient dollars to be used in computations
      • 10. Determine who and how the “improvements” are to be determined for remuneration.
      • 11. Determine the improvements that are attributable to the hospital personnel and those to the physicians.
      • 12. Design and create Excel Spreadsheet algorithms to determine bonuses and value-sharing
  • Verras Algorithms
  • Bonus from Insurer:
      • 1. Measurement: All RMC business (commercial and Medicare)—RIV of top 5 DRG's per service (top 5 DRGs identified by largest number of hospital charges, as used for UB-92 submission)—5 clinical services (Cardiopulmonary, Neurosurgery, Neurology, Orthopedics, OB/GYN) (facility inpatient only).
      • 2. Bonus Criteria: Bonuses for Reductions In Variation (RIV) are awarded only for charges, not LOS, though both are measured for quality improvements. (LOS and charges are associated) Each service's net DRG variations in top 5 DRGs, in which the case volumes are 20 or greater, must be unchanged or improved to receive bonus.
      • 3. Bonus: Calculated based on insurer claims paid dollars: Inpatient hospital paid dollars only and calculated individually for each clinical service. (Cardiopulmonary, Neurosurgery, Neurology, Orthopedics, OB/GYN). Participating groups only, and only for members with addresses in the six county area: Jackson, Lake, Jefferson, Lincoln, Toole and Tyler. Time period is dates Of service Jan. 1, 2007-Dec. 31, 2007 for year one.
      • 4. Adjusted Bonus Percentage: Percentages will be adjusted at the end of the measurement period to apply the appropriate incentive amount and cap the total bonus at $20,000 per service.
      • 5. Verras measures, computes results and reports RIV data at the end of year-one.
      • 6. Bonus Distribution: MDs 75% and Hospital 25%
      • 7. Formula for Bonus: Bonuses are calculated for each service.
        • A. Compute Hospital's Bonus: (Adjusted Percentage×Departmental claims paid dollars)×0.25=Hospital Bonus
        • B. Compute Total MD's Bonus: (Adjusted Percentage×Departmental claims paid dollars)×0.75=MDs Total Bonus
        • C. Compute Individual MD Bonus: MDs Total Bonus divided by number of MDs in each service.
          • Example: Cardiopulmonary (11 MDs)
            • 2% (Adjusted %)×$811,083 (Dept. Paid Dollars for service 1 (‘cardiopulmonary’)=$16,221 Total Bonus (Hospital and Physicians)
            • $16,221×0.25=$4,055 Total Hospital Bonus
            • $16,221×0.75=$12,166 cardiopulmonary service bonus
            • $12,166 divided by 11 MDs=$1,106 Bonus per MD
        • D. Formula Repeated for each Service.
  • 4. CHANGES IN RESOURCE CONSUMPTION—Quality Metric 4 Financial (Changes in Departmental Paid Dollars)
  • (see Table 10 and Tables 17-22 ‘inpatient’ and Tables 23-28 ‘outpatient’ on drawing sheets)
  • Data Sources
      • 1. Verras aggregates Hospital Charges from hospitals' UHDDS.
      • 2. Insurer's paid dollars
  • Uniform Hospital Discharge Data Set (UHDDS) is a part of standard processes all hospital medical records departments use to create medical statistics and billing data. Likewise, there are like processes that insurers use to process claims and pay medical bills to hospitals and physicians.
  • Verras Process:
  • Decision support tool “Sherlock” arrays UHDDS data that has been risk-adjusted by either 3M—APR-DRGs or Yale DRGs using four quadrant graphs for medical staff's Clinical Process Improvement activities.
      • 1. Verras utilizes risk-adjusted data for the hospital and array the data using the severity score of each patient within DRGs.
      • 2. Verras physician and hospital quality personnel present Sherlock generated data to physicians to implement Continuous Quality Improvement activities (CQI)
  • Insurer's paid dollars used to determine bonus remunerations
      • 3. Which Major Diagnostic Categories (MDC) and Diagnosis Related Groups to assign to which of the clinical specialty groups.
      • 4. Determine how many and which DRGs to include in the computations for financial bonuses.
      • 5. Determine which of the categories of dollars to be used for bonuses: charges, costs, paid dollars etc.
      • 6. Determine which of the paid dollar categories from the insurer's data should be considered for bonuses (Inpatient, Outpatient, Professional Dollars, etc.?)
      • 7. Determine who and how the “improvements” are to be determined for remuneration (Acceptable Indicators or mortality etc.)
      • 8. Determine the relative impact on overall inpatient quality that changes in resource consumption impart compared to other medical indicators in order to build the algorithms appropriately.
      • 9. Determine the improvements that are attributable to the hospital personnel and those to the physicians.
      • 10. Determine geographic and therefore patient populations for inclusion.
      • 11. Calculate 3 year averages of insurer's paid dollars for EACH of the clinical specialties.
      • 12. Calculate the expected, year-end dollar resource consumptions (expenditures) using insurer's inflation rates (Inpatient 8.7%, Outpatient 5.5%, Professional 6.3%).
      • 13. Decide of expected numbers of patients for Year One.
      • 14. Determine the technique to be used for measuring weight adjusted dollar averages at year's end.
      • 15. Determine appropriate “Annual Improvement Percentage” that determines “Bonus Percentage.”
      • 16. Determine appropriate “Bonus Percentage” for providers' remuneration.
      • 17. Design and create Excel Spreadsheet algorithms to determine bonuses and value-sharing.
      • 18. Each clinical services' calculations must be treated separately
  • Verras Algorithm
  • Bonus from Insurer:
      • 1. Measurement: All Regional Medical Center (RMC) business (commercial and Medicare)—all DRG's within each of 5 services—measured per service using Hospitals' charge masters' charge amounts for Facility Inpatient and Facility Outpatient only.
      • 2. Bonus Criteria: Bonuses for changes in Resource Consumption are dependent on the CMS & JCAHO Clinical Indicators and 38 Clinical Indicators being stable at an acceptable rate or improved. (Acceptable—as defined by CMS, JCAHO and as determined by the ratio of improved or stable of the 38 clinical indicators compared to those that were degraded.)
      • a. Bonus: Insurer total claims paid dollars, Inpatient Facility and Outpatient Facility only. Calculated per service for each of 5 clinical services for participating groups only for members with addresses in the 6 county area (Jackson, Lake, Jefferson, Lincoln, Toole and Tyler). Bonus is calculated based on actual weighted average cost per case for the measurement year versus expected cost per case for the measurement year, which, initially, is year-one. Time period is dates of service Jan. 1, 2007-Dec. 31, 2007 for year one.
      • b. Expected costs are calculated based on three separate expected inflation rates for Inpatient facility, Outpatient facility and Professional Services as provided by insurer. (Table 4A) The inflation rates were calculated based on the covered amount on the claim.
      • 3. Improvements/Degradations are calculated separately, per each of 5 services and bonuses are dependent of Percent Improvements.
      • 4. The 11 MDs in CV, CVS, Pulmonary and hospitalists are considered as one department—Cardiopulmonary
  • IN-TEXT TABLE 4A
    Percentage Change (Expected by Insurer):
    Expected Percentage Inflation
    Place of Service Jan. 01, 2007-Dec. 31, 2007
    Facility Inpatient 8.7%
    Facility Outpatient 5.5%
    Professional Services - all places of 6.3%
    service
  • IN-TEXT TABLE 4B
    Bonus Percentage:
    Annual Improvement Percentage Bonus Percentage
    0.1% to 3.9%, 50% of improvement percentage
    4.0% to 9.9%, 50% of improvement percentage
    10.0% to 14.9%, 50% of improvement percentage
    15% or greater  8%
  • Bonus Distribution: 90% MD and 10% Hospital
  • Formula for Bonus [formula to be repeated for each of the 5 services—inpatient and outpatient calculated separately]:
      • 1. Calculate Expected Cost per Case for measurement year: Actual Paid Dollar Cost for baseline year multiplied by Expected % Inflation (see In-text Table 4A)=Expected Paid Dollar Cost per case for measurement year
      • 2. Determine Actual Weighted Ave. Cost per Case for measurement year
      • 3. Calculate Annual Improvement/Degradation: Expected Paid Dollar Costs per case in measurement year minus Actual Weighed Ave. Costs per case in measurement year=Annual Improvement/Degradation Cost per case (Must be positive for bonus)
      • 4. Calculate the Annual Improvement Percentage: Annual Improvement or Degradation amount divided by Expected Costs per case=Annual Improvement Percentage
      • 5. Annual Improvement Percentage determines Bonus Percentage (Capped at 8%—Table 4B)
      • 6. Actual Weighted Average per case in measurement year multiplied by Bonus Percentage=Per Case Bonus
      • 7. Per Case Bonus multiplied by Actual number of cases=Total Bonus for Service
        • Total Bonus for Service×10%=Hospital Bonus
        • Total Bonus for Service×90%=Total MD Bonus
      • 8. Total MD Bonus divided by number of MD's participating in service=Bonus per MD
      • Example: (Cardiopulmonary Inpatient)
        • $10,659 (cost/case baseline year)×8.7% (Table 4A)=$11,586 Exp. cost/case measurement year $11,586 minus $10,571 (actual weighted Avg. measurement year)=$1,015 Annual Improvement $1,015/$11,586=8.759% Percent Annual Improvement 8.759%×50% (see In-text Table 4B)=4.380% (Bonus Percent) $10,571 (actual wt. avg./case measurement year)×4.380%=$463 per case bonus
        • $463 per case bonus×70 (est. measurement year number of cases)=$32,410
          • Hospital Bonus (10%)—$3,241
          • Physicians' Bonus (90%)—$29,169
          • Bonus per MD (bonus/number of MD's in service—11)—$2,652
  • 5. HOSPITAL READMISSION RATES—Quality Metric 5
  • Data Source
  • Rates that are manually abstracted by hospital personnel. Verras reports results.
  • Verras Process
      • 1. Determine if or when to include in algorithm for remuneration in year one and in subsequent years.
      • 2. Determine the relative impact on overall inpatient quality that readmission rates impart compared to other medical indicators in order to build the algorithms appropriately.
      • 3. Present the data to physicians for quality assessment and improvement activities
  • No Bonus from Insurer:
  • Hospital readmission rates serve as a quality check on excessively low LOS and/or high post-admission complication rates, but no bonuses will be allocated for this indicator during year-one. This rate will be monitored for RMC and HCN and reported to insurer by lameter.
  • 6. CLINICAL PATHWAY PRODUCTION AND USE—Quality Metric 6 (see Tables 29-33 on drawing sheets)
  • Data Source
  • Information accumulated during, the year by Hospital's quality assurance professionals.
  • Individual Physician's Participation is Assessed by Hospital Personnel:
  • Verras Process
      • 1. Determine levels of physicians' participation that generates bonus
      • 2. Determine bonus percentages associated with level of MD participation.
      • 3. Work with hospital quality staff to determine criteria of participation
      • 4. Determine which of the paid dollar categories from the insurer's data should be considered for bonuses (Inpatient, Outpatient, Professional Dollars, etc.?)
      • 5. Determine who and how to present data at year's end
      • 6. Determine “Bonus Percentage” for each “Level of Individual Participation”
      • 7. Determine the relative impact on overall inpatient quality that the clinical pathway production and use imparts compared to other medical indicators in order to build the algorithms appropriately.
      • 8. Determine the improvements that are attributable to the hospital personnel and those to the hospital personnel
      • 9. Design and Create Excel Spreadsheet Algorithms for bonuses and value-sharing
  • Verras Algorithm
  • Bonus from Insurer:
  • Data Source
  • Verras reports participation using hospitals' information that is manually abstracted.
      • 1. Measurement: RMC's administration's Quality Assurance personnel will determine each physician's percentage of group participation within their service. (Cardiopulmonary, Neurosurgery, Neurology, Orthopedics, OB/GYN).
      • 2. Bonus: The bonus is calculated per service, based on Inpatient Facility paid dollars only, for participating groups only, and only for members with addresses in the six county areas: Jackson, Lake, Jefferson, Lincoln, Toole, and Tyler.
      • 3. Bonus Percentage determined by level of individual MD's participation
  • IN-TEXT TABLE 6A
    Level of Individual Participation Bonus Percentage
    Less Than 50% Participation 0.00%
     50% Participation bonus 0.10%
    100% Participation bonus 0.20%
  • Bonus Distribution: 100% MD
  • Formula for Bonus [formula to be repeated for each of the 5 services]:
      • 1. Determine bonus percentage based on level of individual participation (from In-text Table 6A above).
      • 2. Total Claims paid dollars for service×percentage bonus from table above
        • Example: Each of six cardiopulmonary physicians has 50% participation
        • 0.10% (For 50% participation—Table 6A)×$811,043 (paid dollars for cardiopulmonary service)=$811 bonus per MD
      • 7. USE OF ELECTRONIC HEALTH RECORD (EHR)—Quality Metric 7 (see Table 34 in drawing sheets)
  • Data Source
  • Cobalt Medicals recording of physician users of ChartBuilder® (EHR)
  • Individual Physician's Participation is Rewarded:
  • Verras Process
      • 1. Determine number of physician participants, how to choose them.
      • 2. Determine level of participation that determines bonus.
      • 3. Determine bonus calculations and value-based bonuses for bonuses.
      • 4. Determine the relative impact on overall inpatient quality that the use of EHR imparts compared to other medical indicators in order to build the algorithms appropriately.
      • 5. Determine “Bonus Percentage” sliding scale.
      • 6. Determine “Claims Paid Dollars” to define a sliding scale for bonuses (Inpatient, Outpatient, Professional).
      • 7. Design and Create Excel Spreadsheet Algorithms for bonuses and value-sharing.
  • Verras Algorithm
  • Bonus from Insurer:
  • Data Source
  • Verras reports usage as compiled by Cobalt Medical the EHR Vendor.
      • 1. Measurement: 24 physicians within initiative plus any other participating physicians using approved EHR, to an estimated number of 50 MDs. Initially, the bonuses are for using ChartBuilder® with which to produce a typed, electronic medical record. Providers must meet a threshold of 10% of patients using the ChartBuilder® system during the final month of year one (or an approved alternative system). ChartBuilder® and any alternate system must provide transferable or shared medical records among the participating physicians and the capability of gathering SF-36 information on their patients for 6 months of year one. Providers should begin collecting Health Status, Functional Status and Satisfaction data at the 12-month measurement period; however, this will not be a component of the bonus for year one.
      • 2. Data provided by Verras and Cobalt Medical.
      • 3. Bonus: Calculation based on data provided by Verras. Bonus based on insurer total claims paid dollars: Professional Provider Ambulatory Office only, for 153 listed MD's and only their patients with addresses in the 6 county area: Jackson, Lake, Jefferson, Lincoln, Toole, and Tyler.
      • 4. Bonus Percentage: An increasing bonus percentage is applied as total Professional Provider Ambulatory Office paid dollars decrease to reward physicians' efficiencies in resource consumption.
  • IN-TEXT TABLE 7A
    Claims Paid Dollars-Professional Provider
    Bonus Percentage Ambulatory Office
    0.000% Greater than $4,500,000
    0.030% $4,400,000 to $4,500,000
    0.035% $4,300,000 to $4,399,999
    0.040% $4,200,000 to $4,299,999
    0.045% $4,100,000 to $4,199,999
    0.050% $4,000,000 to $4,099,999
    0.055% $3,900,000 to $3,999,999
    0.060% $3,800,000 to $3,899,999
    0.065% $3,700,000 to $3,799,999
    0.070% $3,600,000 to $3,699,999
    0.075% $3,500,000 to $3,599,999
    0.080% Less than $3,500,000
  • Bonus Distribution: 100% MD
  • Bonus Formula
      • 1. Determine Bonus Percentage based on claims paid dollars for professional provider ambulatory office (using In-text Table 7A above).
      • 2. Actual Total paid Claims Dollars for Professional Provider Ambulatory Office multiplied by Appropriate Bonus Percentage (see In-text Table 7A above)=Individual MD Bonus.
      • 3. Individual MD Bonus multiplied by total number of MD's=Total MD Bonus Example:
      • $4,250,000 (Total Professional Provider Paid Dollars)×0.040% (see In-text Table 7A above)=$1,700/MD
      • $1,700×50 MDs=$85,000 Total Bonus to MDs
  • II. VALUE-SHARING COMPUTATIONS
  • (see Table 3 on drawing sheets)—(THIS SECTION WILL BE COMPLETED BY VERRAS AND INSURER AFTER BASELINE YEAR DATA IS RUN BY INSURER).
  • Data Source
  • Verras computes value-sharing distributions for physicians, hospitals and insurer using information from all sources.
  • Verras Process
  • 1. Collaborate with insurer to determine experiential, previous year PMPM base rate.
      • 2. Collaborate with insurer to determine experiential PMPM inflation rate.
      • 3. Determine the year one expected PMPM.
      • 4. Determine the number of insurer's members.
      • 5. Determine the “Target” PMPM using “flat” inflation rate.
      • 6. Determine total paid dollar year one target.
      • 7. Design and Create Excel Spreadsheet Algorithms for bonuses and value-sharing
      • 8. Determine dollars that are available for bonuses and value-sharing using algorithm.
      • 9. Determine a method of distributing available dollars if no, or only a portion of value-sharing dollars are available (see Tables 27-29).
      • 10. Determine percentage of sharing between insurer, hospital, physicians and Verras
      • 11. Determine how start-up costs are covered, by whom and when.
      • 12. Calculate Total Bonuses for Hospital and Physicians (see Table 5).
      • 13. Determine percentage of saving to be share between insurer, providers and Verras (see Table 5).
      • 14. Calculate Potential Value Share (see Table 5).
      • 15. Calculate bonuses and value sharing, hospital and MDs (see Table 5).
      • 16. Calculate bonuses by service for MDs (see Table 6).
      • 17. Calculate bonuses and value sharing for non-hospital MDs who use ChartBuilder® (see Table 6).
  • Verras Algorithms
  • Value Sharing is the financial savings that result from improved clinical quality that leads to the accrued “gains” in efficiencies. The Per Member/Per Month (PMPM) trend of 7.1% will be used for the Value-sharing calculation, to more completely reflect the overall inflation and usage rates of change. The trend was established using insurer “covered dollars”. The measurement period for year one is projected to be services incurred from the start of the project and to run through 12 months of data, with paid run out through the 4th month thereafter.
  • Value Sharing is calculated using the example diagramed below. For this example, 2006 is used as the baseline year and 2007 as the measurement year:
      • The 2006 Baseline PMPM amount is (insert amount here when available).
      • This is based on covered dollars.
      • At the end of the 12-month observation period, plus the 4-month claims run-out period, the following calculations will be performed.
      • A. The 2006 Baseline PMPM will be adjusted after the end of the observation period in order to account for benefit level consistency. The resulting figure is the 2006 Adjusted Baseline PMPM. This adjustment will be done in a fashion that facilitates benefit level consistency between the baseline period and the observation period.
        • Formula for 2006 Adjusted Baseline PMPM: =2006 Baseline Covered PMPM×(2007 Observation Year Paid Dollars/2007 Observation Year Covered Dollars)
      • B. The result of “A” is the 2006 Adjusted Baseline PMPM formula for 2006.
        • Adjusted, Trended Baseline PMPM=2006 Adjusted Baseline PMPM×1.071
      • C. This Adjusted Trended Baseline PMPM will be multiplied by the member months for the time period of year one. The member months will be determined at the end of the 12 month measurement period. Member months is the number calculated by adding the number of members insured each month for each of the corresponding months in a specific time frame. This result is the 2006 Adjusted Trended Baseline Dollars that the providers will try to improve upon. Formula for 2006 Adjusted Trended Baseline that providers will try to improve upon:
        • =2006 Adjusted Trended Baseline PMPM×2007 Member Months
      • D. Calculate the Total Value Sharing Dollars. The following formula will be used:
        • =2006 Adjusted Trended Baseline Dollars−Measurement Period Paid Claim Dollars=(2006 Adjusted Trended Baseline PMPM×Measurement Period Member Months)−(Paid Measurement Period Dollars/Measurement period member months)×Measurement. Period Member Months=(2006 Adjusted Trended Baseline PMPM×Measurement Period Member Months)−Paid Measurement Period Dollars
      • E. The resulting dollar figure represents the Total Value Sharing Amount for the payout of (in this order) insurer startup costs*, bonuses, and Remaining Value Sharing Dollars.
        • a. *Startup costs are:
        • $75,000 Implementation of ChartBuilder®—year 1; possibly prorated for year 2
        • $30,000 Creation of insurer Initiative, Creation of reports and data collection by Verras Medical, Inc.—year 1 and year 2
        • Actual approved cost of Education of Physicians, Purchasers, and Insurer by Verras Medical, Inc.—year 1 and year 2. After startup costs and bonuses are deducted, the Remaining Value Sharing Dollars amount is divided as follows: 45% Insurer, 45% RMC/HCN, and 10% Verras Medical, Inc.
        • b. If, after insurer startup costs are deducted not enough remains to pay out 100% of bonuses, the bonuses will be pro-rated and no Remaining Value Sharing Dollars will be paid. This means, that if 100% of bonuses cannot be paid, the percentage of each bonus to be paid shall be the total amount available from section (D) above, minus startup costs, divided by the total of all bonuses to be paid.
        • c. if Paid Measurement Period Dollars are greater than the 2006 Adjusted Trended Baseline Dollars no dollars will be paid out in insurer startup costs, bonuses, or Remaining Value Sharing Dollars. Startup costs could be recovered in later years if funds are available.
  • Adjustment to Value Sharing PMPM for Benefit Consistency
    Member PMPMs
    Year Covered $ Paid $ Months Covered Paid
    Example 1:
    2006 (Baseline) $12,100,000 $7,744,000 220,000 $55.00 $35.20
    2007 $13,409,000 $8,179,490 230,000 $58.30 $35.56
    (Observation)
    2006 Adjusted Baseline PMPM: $33.55 = $55.00 ×
    [$8,179,490/$13,409,000].
    2006 Adjusted, Trended Baseline PMPM: $35.93 = $33.55 × 1.071
    Example 2:
    2006 (Baseline) $12,100,000 $7,744,000 220,000 $55.00 $35.20
    2007 $13,409,000 $8,984,030 230,000 $58.30 $39.06
    (Observation)
    2006 Adjusted Baseline PMPM: $36.85 = $55.00 ×
    [$8,984,030/$13,409,000].
    2006 Adjusted, Trended Baseline PMPM: $39.47 = $36.85 × 1.071
  • EXAMPLE SCENARIOS Example 1
  • Sufficient funds available to recoup startup costs, pay physician and hospital bonuses, and Remaining Value Sharing Dollars.
  • $18,000,000.00 Adjusted Trended Baseline PMPM × member months
    $16,500,000.00 Less Actual claims paid data
    $1,500,000 Amount remaining for payout of insurer startup costs
    and bonuses
    $1,500,000.00 Amount remaining from above
    $120,000.00 Less startup costs
    $1,380,000.00 Amt remaining for bonus
    $1,380,000.00 Amount remaining from above
    $700,000.00 Less bonus amount
    $680,000.00 Remaining Value Sharing Dollars Amount
    $306,00000 Amt remaining from above × 45% for Insurer
    $306,00000 Amt remaining from above × 45% for RMC and HCN
    $68,000.00 Amt remaining from above × 10% for Verras
    Medical, Inc.
  • Example 2
  • Sufficient funds available to recoup insurer startup costs, pay pro-rated physician and hospital bonuses; no Remaining Value Sharing Dollars.
  • $18,000,000.00   Adjusted Trended Baseline PMPM × member
    months
    $17,436,402.00   Less Actual claims paid data
    $563,598.00 Amount remaining for payout of insurer startup
    costs and bonuses
    $563,598.00 Amount remaining from above
    $120,000.00 Less startup costs
    $443,598.00 Amt remaining for bonus
    $443,598.00 Amount remaining from above
    $700,000.00 Less bonus amount
    $(256,402.00)

    In this example, amount remaining is not sufficient to pay calculated bonuses, so Prorate. Divide $443,598.00 by $700,000.00. Result is 63.371%
    Calculated bonus amounts will be multiplied by 63.371% to determine actual bonuses to be paid.
  • In this example, there are no Remaining Value Sharing Dollars to allocate.
  • Example 3
  • Insufficient funds available to recoup insurer startup costs, pay physician and hospital bonuses, or Remaining Value Sharing Dollars.
  • $18,000,000.00 Adjusted Trended Baseline PMPM × member months
    $18,436,702.00 Less Actual claims paid data
      $(436,702.00) No dollars available for startup costs, bonuses, or
    Remaining Value Sharing Dollars

    In this example, the actual claims paid amount is greater than the baseline trended PMPM×member months,
    so that insurer startup costs, bonuses, and Remaining Value Sharing Dollars are not paid.
  • 4.0 VALUE SHARING SUMMARIES (see Table 5 on drawing sheets)
  • These examples use baseline year of 2006 and measurement year of 2007 (Dollar amounts in this section are for illustration purposes only.)
  • 4.1. Total Bonus Summaries:
  • Examples:
  • Hospital + Physicians (Total) $273,745
    Hospital Bonuses (Total) $63,922
    Physicians' Bonuses (Total) $209,823
    Individual MD Bonus Ave. Service 1 $4,445
    Individual MD Bonus Ave. Service 2 $4,235
    Individual MD Bonus Ave. Service 3 $1,141
    Individual MD Bonus Ave. Service 4 $14,269
    Individual MD Bonus Ave. Service 5
    Individual MD Bonus as ChartBuilder ® User $1,700
  • 4.2. Potential Value-Share Calculations:
  • (Assumes 2007 paid dollars equals 2006)
    2006 Actual Spending $12,958,843
    Projected 2007 Paid Dollar spending $13,878,921
    (7.10% > 2006 rate)
    Total Value Sharing Dollars Available 2006/2007 (TBD) $920,078
    (delta)
    Less Insurer Expenses −$105,000
    Less Total Bonuses Paid 2007 −$273,745
    Remaining Value Sharing Dollars to be Shared $541,333
    Value Sharing Dollars to Insurer (45%) $243,600
    Value Sharing Dollars to Hospital and MDs (45%) $243,600
    Value Sharing Dollars to Verras Medical (10%) $54,133
  • 4.3. By Physician Overall:
  • Value Share to Hospital + MDs $243,600
    Less Hospital Expense −$30,000
    Value Share to MDs $213,600
    Value Share to 24 Hosp. MDs (33%) $71,129
    Value Share to each Hosp. MD $3,744
    Value Share to ChartBuilder ® Users (67%) $142,257
    Value Share to each CB User $2,845
  • 4.4. By Total MD Bonuses by Service for ChartBuilder® Users:
      • 1. Cardiopulmonary (Service 1):
  • Bonus Service 1 $5,058
    Bonus ChartBuilder ® $1,700
    Value Share $3,744
    Value Share-CB $2,845
    Total $13,347
      • 2. Neurosurgery (Service 2):
  • Bonus Service 2 $5,024
    Bonus ChartBuilder ® $1,700
    Value Share $3,744
    Value Share-CB $2,845
    Total $13,313
      • 3. Neurology (Service 3):
  • Bonus Service 3 $1,677
    Bonus ChartBuilder ® $1,700
    Value Share $3,744
    Value Share-CB $2,845
    Total $9,966
      • 4. Orthopaedics (Service 4):
  • Bonus Service 4 $14,863
    Bonus ChartBuilder ® $1,700
    Value Share $3,744
    Value Share-CB $2,845
    Total $23,152
      • 5. OB/GYN (Service 5):
  • Bonus Service 5 $11,111
    Bonus ChartBuilder ® $1,111
    Value Share $1,111
    Value Share-CB $1,111
    Total $11,111
  • 4.5. By Total MD Bonus for Non-Hospital ChartBuilder® Users:
  • Bonus ChartBuilder ® $1,700
    Value Share - CB $2,845
    Total $4,545
  • With respect to the above description then, it is to be realized that the optimum dimensional relationships for the parts of the invention, to include variations in size, materials, shape, form, function and manner of operation, assembly and use, are deemed readily apparent and obvious to one skilled in the art, and all equivalent relationships to those illustrated in the drawings and described in the specification are intended to be encompassed by the present invention. Therefore, the foregoing is considered as illustrative only of the principles of the invention. Further, since numerous modifications and changes will readily occur to those skilled in the art, it is not desired to limit the invention to the exact construction and operation shown and described, and accordingly, all suitable modifications and equivalents may be resorted to, falling within the scope of the invention.
  • The above description, together with the objects of the invention and the various features of novelty which characterize the invention, are pointed out with particularity in the claims annexed to and forming a part of this disclosure. For a better understanding of the invention, its operating advantages and the specific advantages attained by its uses, reference should be made to the accompanying drawings and descriptive matter in which there are illustrated preferred embodiments of the invention.
  • Furthermore, the purpose of the foregoing abstract is to enable the U.S. Patent and Trademark Office and the public generally, and especially the scientists, engineers and practitioners in the art who are not familiar with patent or legal terms or phraseology, to determine quickly from a cursory inspection the nature and essence of the technical disclosure of the application. The abstract is neither intended to define the invention of the application, which is measured by the claims, nor is it intended to be limiting as to the scope of the invention in any way.
  • APPENDIX A CMS and JCAHO Quality Indicators
  • JCAHO Core Measure Sets (Update as of Jul. 1, 2005), Group 4 (Pregnancy) is monitored by Iameter at this time but is not reported to JCAHO.
      • 1. AMI (Acute Myocardial Infarction)—Nine (9) individual measures that are all from chart abstraction
        • a. Aspirin at arrival
        • b. Aspirin prescribed on discharge
        • c. ACE Inhibitors for LVSD
        • d. Adult Smoking Cessation counseling
        • e. Beta blocker on arrival
        • f. Beta blocker prescribed on discharge
        • g. Thrombolytic agent received within 30 min. of hospital arrival
        • h. PTCA within 90 min. of hospital arrival
        • i. AMI Compliance Index
      • 2. Pneumonia Care
        • a. Oxygenation assessment
        • b. Pneumococcal vaccination given or screened
        • c. Blood cultures performed before first antibiotic received in hospital
        • d. Pneumonia care Compliance Index
        • e. Initial antibiotic received within 4 hrs. of hospital arrival
      • 3. Heart Failure
        • a. Discharge instructions—includes a set of 6 different instructions
        • b. LVF assessment
        • c. ACE Inhibitor for LVSD
        • d. Adult smoking cessation counseling
        • e. Heart Failure Compliance Index
      • 4. Pregnancy—KRMC and HCNW have not elected to incorporate the OB section in their CMS/JCAHO reporting. This is not included in bonus for CMS/JCAHO Core Measures.
        • a. VBAC
        • b. Third or fourth degree laceration
        • c. Neonatal mortality
        • d. Cesarean delivery rate
      • 5. Surgical Infection Prevention (SIP)
        • a. Antibiotic within 1 hr. of incision
        • b. Antibiotic selection
        • c. Antibiotic discontinued within 24 hrs.
        • d. Surgery Infection Prevention Compliance Index
  • APPENDIX B
    CLINICAL, RATE-BASED INDICATORS (38)
    Clinical Indicator Name Description
    Hospital Mortality Rate Percent of patients that died - risk adjusted
    MDC Mortality Rate Percent of patients that died by MDC - risk
    adjusted
    DRG Mortality Rate Percent of patients that died by DRG - risk
    adjusted
    AMI Mortality Rate Percent of patients admitted with acute
    myocardial infarction that died.
    AMI Mortality Rate - Percent of female patients admitted with acute
    Female myocardial infarction that died.
    AMI Mortality Rate - Percent of male patients admitted with acute
    Male myocardial infarction that died.
    Hospital Re-Admission Percent of patients readmitted within 30 days
    Rate
    CABG over 96 hr Mech. Percent of CABG patients with greater than
    Vent 96 hours of mechanical ventilation.
    Complicated Deliveries Vaginal delivery with complications
    C-Section Patients with surgical delivery of a fetus
    through incision in the abdominal wall and the
    uterine wall. Does not include removal of the
    fetus from the abdominal cavity in case of
    rupture of the uterus or abdominal pregnancy.
    Prolonged LOS - GYN GYN Surgery with LOS >10 Days
    Surgery
    High Risk Obstetrics Patients with complicated obstetrical needs
    Vaginal Del. with 4th Patients with rupture or tear involving anal
    Degree Laceration sphincter, rectovaginal septum, and anal
    mucosa.
    VBAC Patients with vaginal birth after cesarean
    section
    CVA w/ Aspiration CVA patients with aspiration pneumonia
    Pneumonia
    Decubitus Ulcer - Medical patients with decubitus ulcer (post-
    Medical admission and co morbid)
    Line Sepsis Rate - Patients with Bacteremia and/or Sepsis due to
    Medical Service a vascular device, implant, or graft (post-
    admission and co morbid)
    Nosocomial pneumonia Medical patients who have a secondary
    diagnosis of pneumonia except those in
    Respiratory MDC.
    Surgical Percent of all coronary artery procedures
    Revascularization Rate resulting in a CABG
    Post-admission All medical patients with a secondary
    Aspiration Pneumonia diagnosis of aspiration pneumonia
    Post-admission Percent of medical patients with septicemia
    Septicemia (post-admission and co morbid).
    Post-admission Percent of medical patients with
    Thromboembolism Thromboembolism (post-admission or co
    morbid).
    Postoperative Aspiration Surgical patients who have a secondary
    Pneumonia diagnosis of aspiration pneumonia
    Postoperative DVT - Orthopedic patients with Deep Vein
    Orthopedic - Lower Thrombosis of the lower extremity
    Extremity
    Postoperative Surgical patients who have secondary
    Hemorrhage diagnosis of hemorrhage postoperatively.
    Postoperative Cardiac surgical patients who have secondary
    Hemorrhage - diagnosis of hemorrhage postoperatively.
    Cardiac Surgery
    Postoperative Orthopedic surgical patients with hemorrhage
    Hemorrhage - Orthopedic postoperatively.
    Surgery - Lower
    Extremity
    Postoperative Infection Surgical patients with postoperative infections
    (wound infections).
    Postoperative Infection - Cardiac surgical patients with postoperative
    Cardiac Surgery infections (wound infections).
    Postoperative Infection - Surgical patients with postoperative infections
    Orthopedic Surgery (wound infections).
    Postoperative Pneumonia Surgical patients with postoperative
    pneumonia
    Postoperative Orthopedic surgical patients with
    Pneumonia - Orthopedic postoperative pneumonia
    Surgery
    Postoperative Pulmonary Percent of surgical patients with pulmonary
    Embolism embolism.
    Postoperative Respiratory Surgical patients with Respiratory Arrest
    Arrest Postoperatively
    Postoperative Septicemia Surgical patients with septicemia
    postoperatively.
    Prolonged LOS - CHF CHF patients with Length of Stay over 10
    days
    Postoperative UTI Surgical patient with urinary tract infection
    postoperatively.
    Nosocomial UTI Percent of medical patients having UTI not in
    a DRG for urinary tract infections.

Claims (20)

1. A computer-implemented system for healthcare performance measurement and equitable provider reimbursement comprising:
gather medical information from hospital patients charts data, hospital medical records department data, insurance company data, and physician's office data
aggregate the gathered data wherein said aggregation of data includes the use of a Sherlock computer program sub-system and memory database which targets cases by type, physician, severity and clinical services, diagnoses and procedures at a revenue code level, use of resources and create graphics by case;
wherein said Sherlock computer sub-system aggregated data is further analyzed by a Watson based computer sub-system which explains diagnoses and procedures by who by specific physician, what and why, sequence of events and what was not documented, explains specific resources by specific type of tests, breakdown of drugs, identifies why extra days were spent in hospital, and converts to true costs, and create a best practices framework by database of clinical variation by diagnosis and procedure, establishes a computerized physician order entry (CPOE) customization and facilitates clinical pathway construction; and calculating the following quality metrics: those National Hospital Quality Measures (NHQM) as determined to be mandated by Centers for Medicare and Medicaid Services (CMS), patient satisfaction, morbidity, mortality, reduction in variation (RIV), and resource consumption;
calculate an index of quality improvement (IQI) for each healthcare provider;
generate value sharing computations and calculate overall net savings; and
distribute said net savings to physicians, hospitals, Accountable Care Organizations (ACOs), CO-OPs and insurers in the form of reimbursements.
2. (canceled)
3. (canceled)
4. A computer-implemented system for healthcare performance measurement and equitable provider reimbursement according to claim 1, wherein said system includes the element of ranking quality metrics as to importance for predicting quality and financial incentives, prior to calculating an index of quality improvement (IQI) for each healthcare provider.
5. A computer-implemented system for healthcare performance measurement and equitable provider reimbursement according to claim 1, wherein said index of quality improvement (IQI) is calculated using the six enumerated metrics and ambulatory outcomes (AMB.O) and Accountable Care Organization metrics (ACO.M) outpatient physician's offices as a seventh metric added to the IQI calculation.
6. A computer-implemented system for healthcare performance measurement and equitable provider reimbursement according to claim 1, wherein said IQI is tracked for one or more healthcare providers and for one or more years, with resulting IQI performance trend information sent to employers, consumers, public agencies, CO-OPs and hospital personnel for the purpose of making decisions regarding healthcare provider performance and improvement.
7. A computer-implemented system for healthcare performance measurement and equitable provider reimbursement according to claim 1, wherein quality assurance and equitable reimbursement system (QAERS) algorithms are employed to generate value sharing computations and calculate overall net savings.
8. A computer-implemented system for healthcare performance measurement and equitable provider reimbursement according to claim 7, wherein said value sharing computations and calculate overall net savings are used to calculate reimbursement rewards to be distributed to hospitals, clinical practice groups and physicians.
9. A computer-implemented system for healthcare performance measurement and equitable provider reimbursement according to claim 1, wherein AIM technology algorithms are employed to aggregate data gathered from medical information from hospital patients charts data, hospital medical records department data, insurance company data, and physician's office data, prior to providing the resulting information to a Sherlock sub-system.
10. A computer-implemented system for healthcare performance measurement and equitable provider reimbursement according to claim 1, wherein said IQI is calculated using future metrics at which time the become recognized national standards for measuring quality assurance and efficient performance of healthcare providers.
11. A computer-implemented method for using a system for healthcare performance measurement and equitable provider reimbursement, comprising the steps of:
(a) gathering medical information from hospital patients charts data, hospital medical records department data, insurance company data, and physician's office data;
(b) aggregating the gathered data wherein said aggregation of data includes the use of a Sherlock computer program sub-system and memory database which targets cases by type, physician, severity and clinical services, diagnoses and procedures at a revenue code level, use of resources and create graphics by case;
wherein said Sherlock computer sub-system aggregated data is further analyzed by a Watson based computer sub-system which explains diagnoses and procedures by who by specific physician, what and why, sequence of events and what was not documented, explains specific resources by specific type of tests, breakdown of drugs, identifies why extra days were spent in hospital, and converts to true costs, and create a best practices framework by database of clinical variation by diagnosis and procedure, establishes a computerized physician order entry (CPOE) customization and facilitates clinical pathway construction; and calculating the following quality metrics: National Hospital Quality Measures (NHQM), patient satisfaction, morbidity, mortality, reduction in variation, resource consumption;
(c) calculating an index of quality improvement for each healthcare provider;
(d) generating value sharing computations and calculating overall net savings; and
(e) distributing said net savings as a reimbursement to physicians, hospitals, Accountable Care Organizations (ACOs), CO-OPs and insurers in the form of reimbursements.
12. (canceled)
13. (canceled)
14. The computer-implemented method for using a system for healthcare performance measurement and equitable provider reimbursement according to claim 11, wherein said method includes the step of ranking quality metrics as to importance for predicting quality and financial incentives, prior to said step of calculating an index of quality improvement (IQI) for each healthcare provider.
15. The computer-implemented method for using a system for healthcare performance measurement and equitable provider reimbursement according to claim 11, wherein said index of quality improvement (IQI) is calculated using the six enumerated metrics and ambulatory outcomes (AMB.O) and Accountable Care Organization metrics (ACO.M) from outpatient and physician's offices as a seventh metric added to the IQI calculation.
16. The computer-implemented method for using a system for healthcare performance measurement and equitable provider reimbursement according to claim 11, wherein said IQI is tracked for one or more healthcare providers and for one or more years, with resulting IQI performance trend information sent to employers, consumers, public agencies, CO-OPs and hospital personnel for the purpose of making decisions regarding healthcare provider performance and improvement.
17. The computer-implemented method for using a system for healthcare performance measurement and equitable provider reimbursement according to claim 11, wherein quality assurance and equitable reimbursement system (QAERS) algorithms are employed to generate value sharing computations and calculate overall net savings.
18. The computer-implemented method for using a system for healthcare performance measurement and equitable provider reimbursement according to claim 17, wherein said value sharing computations and calculate overall net savings are used to calculate reimbursement rewards to be distributed to hospitals, clinical practice groups and physicians.
19. The computer-implemented method for using a system for healthcare performance measurement and equitable provider reimbursement according to claim 11, wherein AIM technology algorithms are employed to aggregate data gathered from medical information from hospital patients charts data, hospital medical records department data, insurance company data, and physician's office data, prior to providing the resulting information to a Sherlock sub-system.
20. The computer-implemented method for using a system for healthcare performance measurement and equitable provider reimbursement according to claim 11, wherein said IQI is calculated using future metrics at which time they become recognized national standards for measuring quality assurance and efficient performance of healthcare providers.
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