EP3847654A1 - Vorhersage des dokumentationsaufwands - Google Patents
Vorhersage des dokumentationsaufwandsInfo
- Publication number
- EP3847654A1 EP3847654A1 EP19758765.2A EP19758765A EP3847654A1 EP 3847654 A1 EP3847654 A1 EP 3847654A1 EP 19758765 A EP19758765 A EP 19758765A EP 3847654 A1 EP3847654 A1 EP 3847654A1
- Authority
- EP
- European Patent Office
- Prior art keywords
- study
- documentation
- test sheet
- electronic test
- effort
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Withdrawn
Links
- 238000013474 audit trail Methods 0.000 claims abstract description 18
- 238000000034 method Methods 0.000 claims abstract description 15
- 238000004590 computer program Methods 0.000 claims abstract description 7
- 238000012360 testing method Methods 0.000 claims description 45
- 230000015654 memory Effects 0.000 claims description 7
- 239000003814 drug Substances 0.000 claims description 4
- 238000007619 statistical method Methods 0.000 claims description 3
- 230000003936 working memory Effects 0.000 claims description 3
- 238000013528 artificial neural network Methods 0.000 claims description 2
- 238000013500 data storage Methods 0.000 claims description 2
- 238000013461 design Methods 0.000 claims description 2
- 229940079593 drug Drugs 0.000 claims description 2
- 230000000771 oncological effect Effects 0.000 description 5
- 238000013475 authorization Methods 0.000 description 3
- 229940126601 medicinal product Drugs 0.000 description 3
- 230000002093 peripheral effect Effects 0.000 description 3
- 230000002411 adverse Effects 0.000 description 2
- 238000004364 calculation method Methods 0.000 description 2
- 229940124301 concurrent medication Drugs 0.000 description 2
- 239000000902 placebo Substances 0.000 description 2
- 229940068196 placebo Drugs 0.000 description 2
- 239000013543 active substance Substances 0.000 description 1
- 230000006399 behavior Effects 0.000 description 1
- 238000013481 data capture Methods 0.000 description 1
- 238000003745 diagnosis Methods 0.000 description 1
- 238000012544 monitoring process Methods 0.000 description 1
- 238000012545 processing Methods 0.000 description 1
- 238000011160 research Methods 0.000 description 1
Classifications
-
- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H10/00—ICT specially adapted for the handling or processing of patient-related medical or healthcare data
- G16H10/20—ICT specially adapted for the handling or processing of patient-related medical or healthcare data for electronic clinical trials or questionnaires
Definitions
- the present invention deals with the prediction of the effort for documenting patient data in the context of a study, preferably a non-interventional study.
- the present invention relates to a method, a computer system and a computer program product for predicting the effort for the documentation of patient data in the context of a study.
- Another object of the present invention is the use of the data stored in an audit trail of an EDC system to predict a documentation effort of an upcoming study.
- Medicinal Products Act AMG
- section 4 (23) sentence 2 a non-interventional study is an examination in the context of which findings from the treatment of people with medicinal products are analyzed using epidemiological methods; Thereby, the treatment, including the diagnosis and monitoring, does not follow a predetermined test plan, but exclusively the medical practice; insofar as it is a medicinal product that is subject to authorization or that is subject to authorization according to ⁇ 2la paragraph 1 AMG, this is also carried out according to the information specified in the authorization or approval for its use.
- test sheet is used to document the patient data for each participant (hereinafter also referred to as the patient).
- patient data for each participant
- CRF Case Report Form
- Test sheets are documented in pseudonymized form. Test sheets are provided by the sponsor of the study on paper, in electronic form as so-called eCRF or as an online questionnaire. The content of the test sheets - depending on the type of study - can differ greatly. In addition to basic and patient history data, concomitant medication and adverse events are recorded during the study.
- EDC Electronic Data Capture
- test doctor receives remuneration only for the time required to document patient data as part of a non-interventional study. This will agreed in advance with the sponsor, whereby the time required for the documentation is estimated. Such an estimate is inaccurate.
- the documentation effort for a study is predicted on the basis of data that were collected in the past when electronic test sheets were filled out.
- the audit trails from past data acquisitions are used to predict benchmarks for documentation times.
- a first object of the present invention is a method for predicting a documentation effort for an upcoming study, comprising the following steps:
- Another object of the present invention is a computer system for predicting a documentation effort for an upcoming study, comprising
- guide values for fill-in time periods are stored in the data memory, the guide values being determined on the basis of time periods which were spent filling out at least one electronic test sheet in the context of at least one previous study, the time periods being determined from at least one audit trail of at least one EDC system were
- the input unit being configured to receive information about a forthcoming study from a user
- the computing unit is configured to use the information provided by the user and the guide values to calculate an expected documentation effort for the upcoming study
- the output unit being configured to output the calculated documentation effort.
- Another object of the present invention is a computer program product comprising a program code which is stored on a data carrier and which causes a computer to carry out the following steps when the program code is loaded into a working memory of the computer: Receiving information about an upcoming study from a user,
- Another object of the present invention is the use of the data stored in at least one audit trail of at least one EDC system relating to the failure of at least one electronic test sheet for predicting the documentation effort of an upcoming study.
- the aim of the present invention is to predict a reliable value for the effort / costs for the documentation of patient data in the context of a study.
- the term “study” is to be interpreted broadly in the context of the present invention.
- the term “study” is intended to encompass all studies in which an investigator receives remuneration for the documentation of patient data from a sponsor and an agreement between the investigator and sponsor on the expected documentation effort can be reached in advance.
- the present invention helps to objectively determine the documentation effort on the basis of real data.
- the study is preferably a non-interventional study.
- the invention can also be used, for example, in clinical (interventional) studies.
- the term “investigator” is understood to mean a natural or legal person who receives remuneration from the sponsor of the study for the documentation of patient data in the context of a study.
- the investigator does all or part of the documentation himself; It is also conceivable that the documentation is carried out by an employee and / or an authorized representative. For the sake of simplicity, the investigator is regarded in the following description as the person who carries out the documentation; however, the invention is to be understood in such a way that other people, for example one or more project nurses or one or more study coordinators, can at least partially carry out the documentation.
- the term "sponsor” is understood to mean a natural or legal person who pays a investigator for the documentation of patient data as part of a study.
- documentation effort means the time required to document patient data in the context of a study. This refers to the total effort, i.e. the total of all the time periods that a investigator and / or an employee and / or an authorized representative has spent documenting patient data in the course of the study in an EDC system - from its beginning to its completion ) is.
- the term "documentation costs” is to be understood as the costs for the documentation of patient data in the context of a study that the investigator charges the sponsor (possibly in addition to other costs such as administration costs).
- the documentation costs are the product of the documentation effort and a time record (cost per unit of time) or several time records.
- both the expected documentation effort and the expected documentation costs are calculated and output. In principle, however, it is conceivable that only one of the variables is calculated and / or output. Usually at least one of the sizes is calculated and / or output in advance (before the start of the documentation).
- the invention includes a computer system that is configured to receive input from a user, to calculate the documentation effort to be expected for a study on the basis of the input, and to output the calculated documentation effort to be expected.
- a “computer system” is a system for electronic data processing that processes data by means of programmable calculation rules. Such a system usually comprises a “computer”, the unit which comprises a processor for performing logical operations, and a peripheral device.
- Peripherals in computer technology are all devices that are connected to the computer and are used to control the computer and / or as input and output devices. Examples are monitor (screen), printer, scanner, mouse, keyboard, Drives, camera, microphone, speakers etc. Internal connections and expansion cards are also considered peripherals in computer technology.
- Today's computer systems are often divided into desktop PCs, portable PCs, laptops, notebooks, netbooks and tablet PCs and so-called handhelds (e.g. smartphones); all of these systems can be used to practice the invention.
- the inputs into the computer system are made via input means such as a keyboard, a mouse, a microphone and / or the like.
- Input should also be understood to mean the selection of an entry from a virtual menu or a virtual list or the clicking of a selection box and the like.
- the computer system according to the invention comprises several computers.
- the present invention uses data from at least one audit trail of at least one EDC system for prediction.
- this data is used to calculate guide values that are used to predict the documentation effort of upcoming studies.
- These guide values are preferably values which are recorded from a plurality of test sheets using statistical methods. They are preferably mean values, the term mean value in the present description preferably referring to the arithmetic mean.
- a guideline value is an expected value for a filling period.
- a guideline value can be, for example, the average time span for filling out a field in an electronic test sheet. This guideline value can be determined, for example, by adding the time periods for filling out all the individual fields and dividing the result by the number of filled out fields (arithmetic mean).
- a guideline value can be, for example, the average time span for filling out a specific section in an electronic test sheet.
- a test form usually comprises several components (sections): in addition to basic and patient history data, concomitant medication and adverse events are recorded during the study; it is conceivable that specific guide values are determined for individual sections, such as, for example, an average time period for filling out the section for the basic data.
- a guideline value can be, for example, the average time span for filling out an electronic test sheet for an individual patient. It is conceivable that specific guidelines for specific characteristics of studies are calculated.
- the study design e.g. placebo-controlled / non-placebo-controlled, randomized / non-randomized, unlinked / single blind / double blind, single dose / multiple dose, ...
- phase e.g. phase O study, phase I study, phase II study, phase III study, phase IV study
- input means used to enter information (pen, mouse, keyboard, microphone, touchscreen)
- the audit trails from a large number of past studies are preferably analyzed using statistical methods in order to identify those features which have the greatest influence on the documentation effort. Specific guide values for the identified characteristics can then be calculated.
- the prediction tool can be, for example, a regression model or an artificial neural network.
- the calculated guide values can be saved in a data memory.
- the data memory can be an integral part of the computer system according to the invention; however, it can also be a data memory which the computer system according to the invention can access via a network.
- the calculated guide values are then used to calculate the documentation effort of an upcoming study.
- the upcoming study is initially specified in more detail. This usually happens when a user has information about the upcoming study.
- the information about the upcoming study is then linked to one or more benchmarks.
- the documentation effort for an upcoming study should be determined on the basis of a guideline that indicates the average time span for a patient to fail an electronic test sheet.
- a user provides the information that a number N of patients will participate in the upcoming study, where N is an integer and greater than 1.
- the documentation effort for the upcoming study is then obtained by multiplying an average (arithmetically averaged) time span by the number N.
- the guide value (s) suitable for the upcoming study are identified. For example, it is conceivable that specific guide values for various indications (oncology, cardiology, etc.) are stored in the database. For example, if the user indicates that the upcoming study is an oncological study, the guide value (s) for oncological studies is / are read from the database and used to calculate the documentation effort.
- Information about the upcoming study is usually provided by a user entering the computer system according to the invention. It is also conceivable that information can be read from a database, which can be an integral part of the computer system according to the invention, or which can be connected to the computer system according to the invention via a network.
- the documentation costs can be calculated by multiplying the documentation effort by a time record (cost per unit of time) or several time records.
- time sets e.g. a time record for a test doctor, a time record for an assistant to the test doctor and the like. It is also conceivable that there are different time records for different types of documentation; i.e., depending on what documentation is carried out, a different time record is used to calculate the documentation costs.
- the calculated documentation effort and the calculated documentation costs can be output via output means of the computer system according to the invention (for example a screen, a printer, a loudspeaker or the like). Output is usually made to the user of the computer system according to the invention (usually the sponsor). However, it is also conceivable that the output is made to another person.
- output means of the computer system according to the invention for example a screen, a printer, a loudspeaker or the like.
- Output is usually made to the user of the computer system according to the invention (usually the sponsor). However, it is also conceivable that the output is made to another person.
- the computer system (1) comprises an input unit (10), a computing unit (20), an output unit (30) and a data memory (40).
- a user can use the input unit (10) to input information about an upcoming study into the computer system (1).
- Guide values for filling time periods are stored in the data memory (40).
- the guideline values were calculated on the basis of periods of time spent filling out at least one electronic test sheet in the context of at least one previous study.
- the time periods were determined from at least one audit trail of at least one EDC system.
- the computing unit (20) is configured in such a way that it uses the information provided by the user and the guide values to calculate an expected documentation effort for the upcoming study.
- the calculated expected documentation effort is output via the output unit (30).
- FIG. 2 schematically shows a data flow which can be the basis of the present invention.
- data (50) for input to the EDC system / EDC systems are stored. It is saved who made which entries in the (respective) EDC system and when.
- time periods (60) are determined that were spent filling out at least one electronic test sheet in the context of at least one past study.
- Guide values (70) for filling time periods are determined from the time periods (60).
- a guideline corresponds to an expected value for entering data in one or more electronic test sheets.
- a guideline value can be a medium period of time for filling a single field of an electronic test sheet and / or it can be a medium period of time for filling a section of an electronic test sheet and / or it can be a medium time period for filling out a electronic test sheet for a single patient. It is conceivable that there are specific guidelines for specific studies.
- Data (80) on the upcoming study are also available. The data (80) for the upcoming study and the guideline values (70) are combined to calculate the expected documentation effort (90) for the upcoming study.
- FIG. 3 schematically shows a further data flow which can be the basis of the present invention.
- the data flow shown in FIG. 3 corresponds to the data flow shown in FIG. 2, with the addition that on the basis of the data (80) for the upcoming study, specific guide values (70) are queried, which are used to calculate the expected documentation effort (90) .
- FIG. 4 shows an example and schematic of a sequence in the calculation of a documentation effort for an upcoming study.
- a user specifies a category K of the upcoming study.
- the categorization is based on the indication.
- the upcoming study is an oncological study (K: Oncology). This information is used to identify, from a database (40) in which guide values for filling periods are stored, those guide values which are to be used for oncological studies.
- a second step (II) the user selects from a plurality of sections (S1 to S6) those sections which are to be used in the electronic test sheet for the upcoming study and must therefore be filled out; in the present example it is the sections S1, S2 and S5.
- Such a section can be, for example, a section of the test sheet in which basic data, anamnesis data, undesirable events and / or the like must be entered.
- guideline values for a section it is also conceivable that there are several guideline values for a section; it is also conceivable that several sections have the same guide value.
- RI guideline value for the section S1, which indicates the average time span for filling the section S1.
- a number F of fields in section S5 is determined for section S5. It is conceivable that this information is provided by the user; however, it is also conceivable that this information is automatically determined from the electronic test sheet; it is also conceivable that this information is made available from a database.
- a next step (IV) the user enters the number N of patients participating in the upcoming study.
- the information is used in a next step (V) to calculate the effort for documenting the patient data in the context of the upcoming study.
- the effort A results from multiplying the effort to fill out a test sheet for a patient by the number N of the patients participating in the study.
- the effort to fill out a test sheet for a patient results from the addition of the expenses for the failure of the individual sections S1, S2 and S5.
- the expected failure period corresponds to the middle period RI
- the expected failure period corresponds to the middle period R2
- the expected completion period corresponds to the middle period R5 multiplied by the number F of fields.
Landscapes
- Health & Medical Sciences (AREA)
- Engineering & Computer Science (AREA)
- Epidemiology (AREA)
- General Health & Medical Sciences (AREA)
- Medical Informatics (AREA)
- Primary Health Care (AREA)
- Public Health (AREA)
- Medical Treatment And Welfare Office Work (AREA)
Abstract
Description
Claims
Applications Claiming Priority (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| EP18192677 | 2018-09-05 | ||
| PCT/EP2019/073060 WO2020048859A1 (de) | 2018-09-05 | 2019-08-29 | Vorhersage des dokumentationsaufwands |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| EP3847654A1 true EP3847654A1 (de) | 2021-07-14 |
Family
ID=63517737
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| EP19758765.2A Withdrawn EP3847654A1 (de) | 2018-09-05 | 2019-08-29 | Vorhersage des dokumentationsaufwands |
Country Status (2)
| Country | Link |
|---|---|
| EP (1) | EP3847654A1 (de) |
| WO (1) | WO2020048859A1 (de) |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20160085943A1 (en) * | 2014-09-22 | 2016-03-24 | Medidata Solutions, Inc. | System and Method for Monitoring Clinical Trial Progress |
-
2019
- 2019-08-29 WO PCT/EP2019/073060 patent/WO2020048859A1/de not_active Ceased
- 2019-08-29 EP EP19758765.2A patent/EP3847654A1/de not_active Withdrawn
Also Published As
| Publication number | Publication date |
|---|---|
| WO2020048859A1 (de) | 2020-03-12 |
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