CA2588347A1 - Method for assessing and communicating organizational human error risk - Google Patents

Abstract

A method of preventing human error in an organization, the method comprising (1) collecting psychosocial construct data, over an error prediction time period, from individuals performing tasks within the organization; (2) collecting data, over an error prediction time period, on human error incidents within the organization; (3) analysing the psychosocial construct data and error incident data to determine whether the level of one or more awareness factors predicts human error; and (4) if yes, notifying the organization the nature of the human error predicted, and the cause of the human error.

Description

Title: METHOD FOR ASSESSING AND COMMUNICATING
ORGANIZATIONAL HUMAN ERROR RISK

FIELD OF THE INVENTION
This invention relates to the field of industrial psychology, and in particular, the field of human error.

BACKGROUND OF THE INVENTION
Human error is a source of heavy economic costs, injury and death in many different fields, and there are certain fields in which human error can have particularly catastrophic results. Examples include aviation, medicine, pharmacology, nuclear energy, transportation, emergency response services (police, fire, ambulance), military, security services, manufacturing, and supply distribution.
For example, the failure of an operator in a nuclear power plant to notice a dangerous condition could lead to many deaths and injuries, and enormous economic damage. A passenger jet pilot failing to properly appreciate the local weather conditions as he takes off or lands could result in the jet crashing, a catastrophic outcome.
Even non-catastrophic human error can have very significant harmful economic consequences. For example, if baggage handlers working at an airport often crash the baggage/cargo carts, thus damaging equipment, cargo and baggage, the economic consequences for the cargo owner, and the airline, will be substantial. While it is rare for this type of human error to have catastrophic results, there is still a substantial economic benefit associated with identifying and reducing the risk of this type of human error.
Typically, industries in which human error can be catastrophic are regulated, and these regulations typically require that each organization have a dedicated safety officer, who reports directly to the chief executive officer of the organization. The reason for this requirement is that, in the past, persons aware of safety risks have attempted to communicate those risks through the organization's bureaucracy, but the warnings did not reach persons capable of initiating action in time to prevent a catastrophe. By having a dedicated safety officer with a direct link to the chief executive officer, persons with concerns about safety can communicate with the safety officer, who in turn will communicate directly with the CEO who has the power to take action to prevent catastrophe.
The most commonly used method for prospective reduction of error risk is Failure Mode and Effects Analysis (FMEA). FMEA is used to select remedial actions that reduce the risk of errors, as well as the impact of the consequences of those errors. The three basic parameters in FMEA are (1) severity (S); (2) likelihood of occurrence (0), or probability (P); and (3) inability of controls to detect the error (D). In FMEA, the overall risk of each failure is called the Risk Priority Number (RPN), and the RPN is the product of S, 0 and D. The RPN is used to prioritize all potential failures and to decide upon actions that reduce the risk of the failure, usually by reducing likelihood of occurrence and improving controls for detecting the failure.
The main problem with FMEA, particularly in respect of human error, is that FMEA does not attempt to determine the causes of errors.
Rather, FMEA is focused exclusively on error rates and severity of consequences. Thus, an organization may be aware of what types of errors happen most often, and cause the most severe damage, but using only FMEA gives little guidance on what steps to take to prevent the errors from happening. The result may be that the organization takes action to prevent error, but the action is unrelated to the actual cause, and is therefore ineffective.

SUMMARY OF THE INVENTION
Therefore, what is required is a method of preventing human error in an organization, which method is able not only to predict error, but to identify the cause of the error to permit effective action to remove the risk before the error occurs. According to the present invention, there is provided a method of preventing human error in an organization, the method comprising:
collecting psychosocial construct data, over an error prediction time period, from individuals performing tasks within the organization;
collecting data, over an error prediction time period, on human error incidents within the organization;
analysing the psychosocial construct data and error incident data to determine whether the level of one or more awareness factors predicts human error;
if said one or more awareness factors predicts human error, notifying the organization the nature of the human error predicted, and the cause of the human error.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS
Scientific research has found that the risk of human error is a function of nine types of human awareness, otherwise known as psychosocial constructs or awareness factors. Using these nine psychosocial constructs, it is possible to determine not only whether there is an elevated risk of human error; it is also possible to determine, with greater specificity than that available from FMEA, the cause of such elevated risk of human error.
The nine psychosocial constructs associated with human error are:
(1) Anticiaatoy Awareness - awareness that imagines and anticipates possible scenarios. Such awareness includes, for example, the forecasting of potential situational variables and their movement, and the ability to imagine multiple scenarios while interpreting the implications and consequences of each.
(2) Task-Empirical Awareness - awareness of how to assess for the "normal" operation of the task at hand. This type of awareness involves, for example, the individual understanding the normal operational limits of the task for him, and taking steps to maintain himself within those normal operational limits.
(3) Affective Awareness - awareness of how one's emotions, feelings and/or sensory experience informs safe operation.
This involves, for example, both awareness of one's own emotional state, and knowing that shifts in the feeling or emoting experience of an individual signal a situational change which may require adaptation.
(4) Compensatory Awareness - awareness that causes the individual to adjust or compensate for situational variables.
This type of awareness is the product of flexibility and accommodation within the individual in order to maintain safe operation given specific situational dynamics. Thus, for example, this type of awareness would cause the subject to knowingly modify their behaviour in response to operational distractions such as, for example, disruptive behaviour, loud external noises or catastrophic events. An individual having this type of awareness typically makes an immediate adjustment in thinking and behaviour to accommodate for situational conditions that the individual has read and interpreted.

(5) Critical Awareness - awareness that causes and individual to assess and evaluate the task at hand against his own bank of experience. So, for example, an individual with high Critical Awareness would likely have a clear understanding of the risks associated with working while sleep-deprived or medicated.
Such an individual also knows, from experience, what operational pace is appropriate to ensure safety. Similarly, other aspects of his experience are used by the individual to assess and evaluate the present task at hand.

(6) Relational Awareness - awareness for how the "other' influences safe operations. This type of awareness can have a number of different aspects. Thus, for example, if a particular individual feels that his concerns about safety are less important than other people's concerns, then he may lack Relational Awareness. An understanding of the value of team cohesion in operational success and in safety is an aspect of Relational Awareness. Similarly, Relational Awareness would typically include clearly understanding the roles played by each individual in the completion of the task.

(7) Functional Awareness - awareness for the meaning or function of objects of the individual's experience. Thus, being aware of why the individuai would don a mask during air plane depressurization is example of Functional Awareness.

(8) Environmental Awareness - awareness of how variables in this physical and cultural environment impact safety. This awareness covers both how physical objects affect safety (e.g.
improper positioning of the seat in a vehicle) and how cultural factors do so (e.g. support from management forthe raising of safety issues by employees).

(9) Hierarchical Awareness - awareness of an object's place, order or hierarchy or importance in a sequence. For example, in a transportation-related context, this type of awareness would involve knowing the implications of specific weather conditions, road surfaces and traffic patterns according to their order of importance.
According to the present invention, risk of human error is determined by collecting data about the awareness factors, or psychosocial constructs, described above, within the members of the organization at issue. The data is preferably held in a database, providing the resources for storage and analysis of the data. In the preferred embodiment, members of the organization will be asked a selection of questions a minimum of four times per year, though it will be appreciated that higher or lower frequencies are possible, depending on the circumstances. The questions are selected to determine the levels of the awareness factors described above. Also, because each member answers such questions periodically over time, the changes in the awareness factors among the organization members over time can be tracked.
It will be appreciated that, to exhaustively probe the level of any particular type of awareness, it is preferable to ask a wide variety of questions whose answers provide information on various aspects of the particular kind of awareness. So, for example, regarding Anticipatory Awareness, two example questions that may be asked are whether early signs of an operational challenge are always evident to the individual, and whether the individual can see how here-and-now events will unfold in the near future. These two questions are directed to different aspects of Anticipatory Awareness. Preferably, an inventory of questions is available that exhaustively covers the various aspects of each psychosocial construct.
Furthermore, preferably, each individual answers a subset of the inventory each time data is collected from him, so that once the member has completed his series of question-answering sessions (e.g. four per year), he has answered the entire inventory of questions.
Itwill be appreciated that, preferably, questions from the inventory are not asked of each organization member in the same order. Most preferably, after the first data collection, each of the questions of the inventory will have been asked of at least one organization member. This approach is preferable, because data becomes immediately available on all aspects of each psychosocial construct, and it may be possible, depending on the sample size and other statistical parameters, to be able to draw valid conclusions from the data even though each member has not yet answered all, or even most, of the questions in the inventory.
Preferably, organization members will answer questions confidentially or anonymously, using an internet-based questionnaire provided to them.
It will be appreciated that the questions relating to psychosocial constructs often demand an answer that could make an individual fear discipline or dismissal. An individual may also have an incentive to answer the question dishonestly to make himself look better than he actually is, hoping that the organization see his answer and think more highly of him. For example, in relation to Affective Awareness, an individual may be asked whether he tends to deny the negative effects of exhaustion on his performance. An individual facing such a question may legitimately fear negative consequences from answering in the affirmative. As another example, in relation to Anticipatory Awareness, an individual may be asked to agree or disagree with the statement, "I will not ignore the performance shortcomings of my peers and coworkers." The individual may be tempted to agree with this statement even if the answer is false, hoping that his employers will see him as an exceptional employee with leadership potential. Thus, the shielding of the identity of the employee is helpful for encouraging honest responses. It is preferred that individuals know that their answers will not have any impact on their individual employment, whether positive or negative.
It will be appreciated that tracking of levels of the various psychosocial constructs overtime will provide useful information in a number of ways. First, simply having data about the levels of the various types of awareness at a single point in time provides useful information, as such data may show that one or more types of awareness are at dangerously low levels, pointing to the risk of particular kinds of human error, and indicating what the cause of the error will be.
Thus, for example, it may become apparent, even after the first collection of data when no time has yet passed, that there is a dangerously low level of Anticipatory Awareness among the members of the organization.
Specifically, the data may show that members of the organization are unusually lacking in anticipation of possible scenarios during the performance of their tasks. It may further be apparent from the answers given to the initial set of questions that the reason for low Anticipatory Awareness is a cultural one; members of the organization, for example, may rarely be asked by their superiors for feedback on possible situations that may arise, and may not be encouraged to consider this issue. Thus, a recommendation can be made to the safety officer of the organization that management of the organization effect a change in the organizational culture that will encourage greater Anticipatory Awareness.
Collecting data repeatedly over time can also provide information on changes in the risk of human error over time, and possible strategies for reducing the risk. In particular, the levels of one or more types of awareness may change over time, indicating a progressively growing risk of human error. For example, collection of data over time may show that a particular subset of the organization has declining Anticipatory Awareness. One of the factors associated with Anticipatory Awareness is familiarity with co-workers and team members. A typical worker will have greater Anticipatory Awareness when working with familiar team members with whom he is comfortable. In this example, it may turn out to be the case that this same subset of the organization has seen substantial turnover of personnel in the recent past. Thus, it may be possible to trace the declining levels of Anticipatory Awareness to the lower levels of comfortand familiarity between workers. The safety officer can be notified of the risk, together with a recommendation that measures be to increase familiarity and comfort between the workers in the particular subset of the organization.
Preferably, all error incident reports generated by the organization are provided to the database, so that data regarding human error can be used in association with data collected regarding psychosociai factors. Most preferably, they are entered onto a website questionnaire form for uploading to the database. However, other modes of receiving and recording error incident reports may also be used. For example, if the organization uses paper incident reports, then the paper report can be received and the particulars recorded in the database.
It will be appreciated that all data, whether related to error incidents psychosocial constructs or any other subject, should preferably be communicated to the database as promptly as possible. Therefore, it is preferred that the data be entered through a web-based form for immediate uploading to the database. However, in a case where paper forms are used to record data, it is preferable that the paper form be sent by a relatively fast method of transmission (e.g. fax) to a data entry point at which the data is entered into the database. Ultimately, any method of recording data can be used which results in adequately fast entry of the data into the database.
It will be appreciated that, in some industries, certain types of errors are automatically recorded. For example, modern passenger jets automatically record many types of pilot error, and this data is transmitted automatically to the airline. Preferably, the database of the present invention automatically receives such automatically-recorded data in real time for use in data analysis.
Preferably, the error incident data and psychosocial construct data are analysed in association with one another to identify elevated risk of human error, and the cause of such elevated risk. For example, if, over time, a certain psychosocial construct or combination of constructs correlates with particular human errors, the organization can be notified of the causal connection, and provided with recommendation on how to prevent future errors that would otherwise take place if no action is taken.
The correlation between the psychosocial construct(s) and errors could take a number of forms. For example, the correlation could involve a change in both over time, or may involve lower levels of awareness in a specific section of the organization correlating with an unusually high number of certain types of errors in that specific section. By analysing error data and psychosocial construct data together, causal relationships are found between psychosocial constructs and errors, risk is identified, errors are predicted, and recommendations are made on how to avoid predicted error.
Preferably, once initial psychosocial construct data collection has begun, data, including both psychosocial construct data and error data, can be continuously received, and the database updated. Most preferably, this updating can take place at any time, 24 hours per day, 7 days per week, by many of automated processes. It will be appreciated that analysis of the data also preferablytakes place, using computing resources associated with the database, 24 hours per day, 7 days per week. Constant updating and analysis of data is preferred because an indication can arise at any time in the data that error is likely. Furthermore, it is always possible that an error predicted by data analysis can occur very soon after the prediction is made.
Thus, it is strongly preferred that the database of the present invention be updated continuously, and new data analysed promptly.
Data in the database are analysed and evaluated to determine whether a risk of human error is indicated, and what is causing the risk. The presence and cause of a risk are preferably determined from analysing the psychosocial construct data, error data, and any other available data. Once a risk is predicted, and its cause identified, the Safety Officer of the organization is contacted and informed of the type of error predicted by the data, and the cause as revealed by the psychosocial construct data. For example, suppose that an airport baggage handler has driven his vehicle into several baggage/cargo carts, damaging equipment, cargo and baggage.
Meanwhile, data collected from baggage handlers shows that 37 percent of baggage handlers are reporting a lack of effective training in operational procedures, and 30 percent say that how they operate differs from standard operating procedure. The data in this case indicate that there will be additional human error resulting from lack of knowledge and understanding of operating procedures, a Functional Awareness problem.
Taking the same accident as an example, but with different data, the data may show that baggage handlers are well aware of operating procedures, and may be following those procedures, but that 43 percent of baggage handlers are not typically aware when they are in a fatigued state.
In such a case, the Safety Officer would be notified that the data predict further error among baggage handlers caused by fatigue combined with a failure to be aware of the fatigue and take it into account.
This example demonstrates one of the main benefits of the present invention, namely, that the causes of errors are identified. As this example shows, a particular error could have one cause (e.g. fatigue) but if the cause is not identified, the organization may take action (e.g. more training) that will not be effective in preventing the error.
It will be appreciated that the prediction of error, and its cause, can be communicated to the organization through some channel other than through the Safety Officer. However, the Safety Officer is the preferred channel because of his dedication to safety issues and his channels of communication to those, such as the CEO, who can take action to prevent errors from occurring.
Embodiments of and modifications to the described invention that would be obvious to those skilled in the art are intended to be covered by the appended claims. Some variations have been discussed above, and others will be apparent. For example, though use of the internet is preferred for data collection is preferred, it is not required.

Claims (8)

1. A method of preventing human error in an organization, the method comprising:
collecting psychosocial construct data, over an error prediction time period, from individuals performing tasks within the organization;
collecting data, over an error prediction time period, on human error incidents within the organization;
analysing the psychosocial construct data and error incident data to determine whether the level of one or more awareness factors predicts human error;
if said one or more awareness factors predicts human error, notifying the organization the nature of the human error predicted, and the cause of the human error.

2. The method as claimed in claim 1, wherein the step of collecting psychosocial construct data comprises asking members of the organization questions at least four times per year.

3. The method as claimed in claim 2, wherein the steps of collecting psychosocial construct data comprises asking questions on an online questionnaire.

4. The method as claimed in claim 3, wherein the step of collecting psychosocial data comprises asking an inventory of questions, wherein a subset of the inventory is asked at least four times per year, and wherein the asking of subsets of questions continues until each individual has answered all of the questions in the inventory.

5. The method as claimed in claim 1, wherein the collecting of psychosocial construct data and the collection of error data can be done any day, at any time of day.

6. The method as claimed in claim 1, wherein the analysing step comprises finding temporal correlations between errors and psychosocial constructs.

7. The method as claimed in claim 1, wherein the analysing step comprises finding unsafely low levels of one or more types of awareness within the psychosocial construct data.

8. The method as claimed in claim 1, wherein the analysing step comprises finding a correlation between a portion of the organization with which one or more errors have occurred and levels of awareness within that portion of the organization.