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OBJECTIVES: The objectives of this paper are to review and discuss the methods that are being used internationally to report on, mitigate, and eliminate technology-induced errors. METHODS: The IMIA Working Group for Health Informatics for Patient Safety worked together to review and synthesize some of the main methods and approaches associated with technology- induced error reporting, reduction, and mitigation. The work involved a review of the evidence-based literature as well as guideline publications specific to health informatics. RESULTS: The paper presents a rich overview of current approaches, issues, and methods associated with: (1) safe HIT design, (2) safe HIT implementation, (3) reporting on technology-induced errors, (4) technology-induced error analysis, and (5) health information technology (HIT) risk management. The work is based on research from around the world. CONCLUSIONS: Internationally, researchers have been developing methods that can be used to identify, report on, mitigate, and eliminate technology-induced errors. Although there remain issues and challenges associated with the methodologies, they have been shown to improve the quality and safety of HIT. Since the first publications documenting technology-induced errors in healthcare in 2005, we have seen in a short 10 years researchers develop ways of identifying and addressing these types of errors. We have also seen organizations begin to use these approaches. Knowledge has been translated into practice in a short ten years whereas the norm for other research areas is of 20 years.

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With these comments on the paper "Attitude of Physicians Towards Automatic Alerting in Computerized Physician Order Entry Systems", written by Martin Jung and co-authors, with Dr. Elske Ammenwerth as senior author [1], the journal wants to stimulate a broad discussion on computerized physician order entry systems. An international group of experts have been invited by the editor of Methods to comment on this paper. Each of the invited commentaries forms one section of this paper.

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OBJECTIVES: The objectives of this paper are to explore issues and perspectives from four regions of the world where health information systems are contributing to patient empowerment and influencing patient safety. METHODS: Members of the IMIA Working Group for Health Information Systems Safety came together to explore global issues at the intersection of health information systems safety, patient empowerment and patient safety. The group carried out a review and synthesis of the empirical and grey literature in four different regions/countries of the world that have differing health information system safety priorities. RESULTS: Regions/countries from differing parts of the world are developing: (1) high quality, safe information for individuals to use in their health related decision making, (2) patient portals and testing them for their safety, (3) methods for identifying unsafe health information system features and functions, and (4) ways of engaging citizens in identifying unsafe features and functions of health information systems. CONCLUSIONS: Internationally, there has been a rise in the number of health information systems and technologies that are being developed to support patient care. The amount of health information available on the World Wide Web (WWW), and the use of mobile phone software to support consumer health behaviours and self-management of chronic illnesses has also grown. The use of some of these health information systems and technologies has helped citizens to improve their health status (e.g. patient portals, mobile phones). However, the safety of these systems and technologies has come into question. As a result, there is a need to refine these systems and ensure their safety when they are used by patients and their families.

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OBJECTIVE: The objective of this paper is to examine the extent, range and scope to which frameworks, models and theories dealing with technology-induced error have arisen in the biomedical and life sciences literature as indexed by Medline®. METHODS: To better understand the state of work in the area of technology-induced error involving frameworks, models and theories, the authors conducted a search of Medline® using selected key words identified from seminal articles in this research area. Articles were reviewed and those pertaining to frameworks, models or theories dealing with technology-induced error were further reviewed by two researchers. RESULTS: All articles from Medline® from its inception to April of 2011 were searched using the above outlined strategy. 239 citations were returned. Each of the abstracts for the 239 citations were reviewed by two researchers. Eleven articles met the criteria based on abstract review. These 11 articles were downloaded for further in-depth review. The majority of the articles obtained describe frameworks and models with reference to theories developed in other literatures outside of healthcare. The papers were grouped into several areas. It was found that articles drew mainly from three literatures: 1) the human factors literature (including human-computer interaction and cognition), 2) the organizational behavior/sociotechnical literature, and 3) the software engineering literature. CONCLUSIONS: A variety of frameworks and models were found in the biomedical and life sciences literatures. These frameworks and models drew upon and extended frameworks, models and theoretical perspectives that have emerged in other literatures. These frameworks and models are informing an emerging line of research in health and biomedical informatics involving technology-induced errors in healthcare.

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The purpose of this paper is to argue for an integration of cognitive and socio-technical approaches to assessing the impact of health information systems. Historically, health informatics research has examined the cognitive and socio-technical aspects of health information systems separately. In this paper we argue that evaluations of health information systems should consider aspects related to cognition as well as socio-technical aspects including impact on workflow (i.e. an integrated view). Using examples from the study of technology-induced error in healthcare, we argue for the use of simulations to evaluate the cognitive-socio-technical impacts of health information technology [36]. Implications of clinical simulations and analysis of cognitive-social-technical impacts are discussed within the context of the system development life cycle to improve health information system design, implementation and evaluation.

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The objective of this research is to assess the suitability of the Apriori association analysis algorithm for the detection of adverse drug reactions (ADR) in health care data. The Apriori algorithm is used to perform association analysis on the characteristics of patients, the drugs they are taking, their primary diagnosis, co-morbid conditions, and the ADRs or adverse events (AE) they experience. This analysis produces association rules that indicate what combinations of medications and patient characteristics lead to ADRs. A simple data set is used to demonstrate the feasibility and effectiveness of the algorithm.

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Health information systems have the ability to reduce medical errors but they can also introduce new types of errors. In the cognitive and human factors literature there is a recognition that many of the high profile accidents that have occurred in other industries outside of healthcare have had their origins in the complexities of organizational work and how work is structured. The authors propose that in order to have a fully robust framework for diagnosing technology-induced errors one must understand the development and implementation of a technology and the influences of policy using a multi-organizational model. The authors propose that technology-induced errors may have their origins in up to four or more organizational structures that make up complex health care systems in addition to the health care provider: governments, model organizations, software development organizations, and local healthcare organizations. In this paper a framework for considering the origins of technology-induced error in healthcare is presented, along with our experiences to date in the application of the framework.

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This paper describes the analysis of the impact of a medication administration system on clinical workflow. The methodological framework employed was based on in-depth analysis of simulated user interactions with a medication administration system. The approach involved the collection of rich data consisting of audio and video recordings of interactions between 16 subjects (5 nurses and 11 physicians) as they interacted with a medication administration system. Methodological considerations and issues in conducting such studies are discussed. The study indicated that use of the system would have a significant impact on nurse and physician workflow and that this impact could be accurately identified using simulation approaches prior to widespread release of such systems in real clinical environments.

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We sought to study the phenomenon of patients having access to their own medical records in order to determine the impact on them and on their relationship with their health care providers. We created the Patient Clinical Information System (PatCIS) to interface with the clinical data repository at New York Presbyterian Hospital to allow patients to add to and review their medical data. We also provided educational resources and automated advice programs. We provided access to the system to thirteen subjects over a nineteen-month period and reviewed their activities in the system's usage log. We also collected data via questionnaire and telephone interview. We found that patients varied in their use of the system, from once a month or less to one or more times per day. All patients primarily used the system to review laboratory results. Both they and their physicians believed that use of the system enhanced the patients' understanding of their conditions and improved their communication with their physicians. There were no adverse events encountered during the study.

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OBJECTIVE: To explore the use of an observational, cognitive-based approach for differentiating between successful, suboptimal, and failed entry of coded data by clinicians in actual practice, and to detect whether causes for unsuccessful attempts to capture true intended meaning were due to terminology content, terminology representation, or user interface problems. DESIGN: Observational study with videotaping and subsequent coding of data entry events in an outpatient clinic at New York Presbyterian Hospital. PARTICIPANTS: Eight attending physicians, 18 resident physicians, and 1 nurse practitioner, using the Medical Entities Dictionary (MED) to record patient problems, medications, and adverse reactions in an outpatient medical record system. MEASUREMENTS: Classification of data entry events as successful, suboptimal, or failed, and estimation of cause; recording of system response time and total event time. RESULTS: Two hundred thirty-eight data entry events were analyzed; 71.0 percent were successful, 6.3 percent suboptimal, and 22.7 percent failed; unsuccessful entries were due to problems with content in 13.0 percent of events, representation problems in 10.1 percent of events, and usability problems in 5.9 percent of events. Response time averaged 0.74 sec, and total event time averaged 40.4 sec. Of an additional 209 tasks related to drug dose and frequency terms, 94 percent were successful, 0.5 percent were suboptimal, and 6 percent failed, for an overall success rate of 82 percent. CONCLUSIONS: Data entry by clinicians using the outpatient system and the MED was generally successful and efficient. The cognitive-based observational approach permitted detection of false-positive (suboptimal) and false-negative (failed due to user interface) data entry.

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The World Wide Web provides an unprecedented opportunity for widespread access to health-care applications by both patients and providers. The development of new methods for assessing the effectiveness and usability of these systems is becoming a critical issue. This paper describes the distance evaluation (i.e. 'televaluation') of emerging Web-based information technologies. In health informatics evaluation, there is a need for application of new ideas and methods from the fields of cognitive science and usability engineering. A framework is presented for conducting evaluations of health-care information technologies that integrates a number of methods, ranging from deployment of on-line questionnaires (and Web-based forms) to remote video-based usability testing of user interactions with clinical information systems. Examples illustrating application of these techniques are presented for the assessment of a patient clinical information system (PatCIS), as well as an evaluation of use of Web-based clinical guidelines. Issues in designing, prototyping and iteratively refining evaluation components are discussed, along with description of a 'virtual' usability laboratory.

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Decision making by health care professionals is often complicated by the need to integrate ill-structured, uncertain, and potentially conflicting information from various sources. In this paper cognitive approaches to the study of decision making are presented within the context of a variety of complex health care applications. In recent years it has become increasingly accepted that in order to build information systems that can support complex decision making it will be necessary to more fully understand human decision-making processes. Methodological approaches are described that aim to explicate the decision making and reasoning skills of subjects as they perform activities involving the processing of complex information. The paper begins by presenting the theoretical foundations for cognitive analyses of decision making, including discussion of major approaches to the study of decision making in a range of real-world domains, including medicine. Applications of cognitive approaches are then illustrated, including a description of a study in which subjects were asked to "think aloud" in providing treatment decisions for complex medical cases. The resulting protocols were then analyzed for subjects' use of decision strategies and problems in reasoning. Extension of cognitive approaches to the study of group decision-making processes is also described. Recent approaches are discussed which borrow from advances in the study of human-computer interaction and which utilize video analysis of decision-making activities involving information technologies. Using these approaches it has been found that health care information systems, such as computerized patient record systems, may have inadvertent effects on human decision making. Implications of a cognitive approach to improving our understanding of complex decision making are discussed in the context of developing appropriate computer-based decision support for both individuals and groups.

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This paper describes initial experience with the Web-based Patient Clinical Information System (PatCIS). The system was designed to serve as a framework for the integration of applications that help patients access their electronic medical record, add data to their record, review on-line health information, and apply their own clinical data (automatically) to guideline programs that offer health advice. The architecture supports security functions and records user activities, relieving application developers from concerns about safe information practices and the evaluation process. PatCIS is being used to study the social and cognitive impact of allowing patients to have access to their health records via the Web. To date, PatCIS has grown to include 15 clinical functions and 4 dynamic links to literature (called infobuttons). Eleven patients have been enrolled since April, 1999; five have been active users. Experience shows that the PatCIS architecture supports application integration while providing adequate security and evaluation functions. Initial caution with the patient enrollment process has limited recruitment and, consequently, usage. However, experience thus far suggests that PatCIS has good usability and utility. No adverse events, including undesirable impact on doctor-patient interactions, have been reported. There do not appear to be any technical impediments to scaling up the enrollment to continue to observe patient usage.

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The advent of Internet-based information systems has provided unprecedented opportunity for the widespread access to medical information. However, issues related to the evaluation of such systems to ensure their usability, effectiveness and to assess their effect on the provider-patient relationship pose a considerable challenge. This paper describes a framework for the distance evaluation of web-based information technologies. The methods are described in the context of an ongoing evaluation of a system known as PatCIS, designed to be accessed by patients from home for obtaining health information, and for management of chronic diseases. We employ a multi-method approach that involves collection of a rich data set, including Web-based questionnaires, automatic logging of user activity and e-mail communication with users. Our work in evaluation design is influenced from research in the areas of cognitive science and the field of usability engineering which aims to characterize the interaction of users with information technologies.

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OBJECTIVE: To assess the effects of a computer-based patient record system on human cognition. Computer-based patient record systems can be considered "cognitive artifacts," which shape the way in which health care workers obtain, organize, and reason with knowledge. DESIGN: Study 1 compared physicians' organization of clinical information in paper-based and computer-based patient records in a diabetes clinic. Study 2 extended the first study to include analysis of doctor-patient-computer interactions, which were recorded on video in their entirety. In Study 3, physicians' interactions with computer-based records were followed through interviews and automatic logging of cases entered in the computer-based patient record. RESULTS: Results indicate that exposure to the computer-based patient record was associated with changes in physicians' information gathering and reasoning strategies. Differences were found in the content and organization of information, with paper records having a narrative structure, while the computer-based records were organized into discrete items of information. The differences in knowledge organization had an effect on data gathering strategies, where the nature of doctor-patient dialogue was influenced by the structure of the computer-based patient record system. CONCLUSION: Technology has a profound influence in shaping cognitive behavior, and the potential effects of cognition on technology design needs to be explored.

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This paper reports on a study that examines physicians' understanding of concepts and decision making in problems pertaining to hypercholesterolemia and coronary heart disease (CHD). The study was carried out in two phases: (1) a simulated clinical interview in which two clinical problems were presented and (2) a session in which subjects responded to a series of questions. The questions were related to the analysis of risk factors, diagnostic criteria (DC) for determining elevated lipid values, and differential diagnosis for lipid disorders. The subjects included 12 family practitioners who were randomly selected from a continuing medical education program at McGill University. The results indicate that all subjects exhibited gaps in their understanding of domain concepts. In particular, most physicians demonstrated a lack of knowledge concerning the primary genetic disorders that contribute to CHD, as well as deficiencies in understanding the secondary causes of hypercholesterolemia. The majority of subjects tended to overestimate the lipid value intervals for determining patients at high risk. Physicians had no difficulty diagnosing the first patient problem of familial hypercholesterolemia, but failed to identify the problem of elevated lipids secondary to hypothyroidism. We observed a dissociation between subjects' conceptual understanding and their application of knowledge in solving patient problems. The implications of this work are discussed in terms of the cognitive dimensions of technologies for supporting learning and evidence-based decision making.

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This paper presents a psychological perspective on key issues related to medical vocabularies. There have been rapid advances in the development of computer technology underlying medical information systems. However, in keeping with technological progress, we must also take into account advances in our understanding of human behaviour and learn from failures in human performance. A central issue examined in this paper is the extent to which we can develop generic vocabularies that are also flexible and adaptable to specific situations. Empirical research indicates that variability in human performance is much greater than what current medical classifications take into account. A related challenge is that of how to best develop vocabularies that meet the needs of users. Based on theoretical perspectives and research emerging from the domain of cognitive psychology, we suggest that an understanding of the cognitive mechanisms underlying the comprehension and application of terminology is required. It is argued that rather than beginning with highly specified terminologies, i.e. the normative approach, we might instead begin by examining the natural context of how health care workers acquire, understand and negotiate knowledge in practice.

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This paper describes cognitive methods for analyzing medical decision making and evaluating medical information systems. The overall approach focuses on understanding the processes involved in the decision making and reasoning of health care workers, both with and without the use of information technologies. The issue of developing appropriate evaluation tools, for use in the design and analysis of medical information systems is considered to be of great importance. However, conventional methods are limited in their ability to identify and characterize the effects of information technology on the cognitive processes involved in decision making and reasoning. In this paper a range of methods are described involving video recording for collecting data on the use of information systems. The techniques described allow for the collection of an integrated data set consisting of transcripts of health care workers as they 'think aloud' in interacting with a medical system, along with complete video records of user-computer interaction. In addition, the methods can be extended to allow for the collection of process data from video recording of systems in actual clinical and emergency situations. The use of a variety of approaches, borrowing from research in cognitive science, is discussed. The development and application of these evaluation methods within the Canadian Centres of Excellence network HEALNet is subsequently described. Finally, implications for the development and evaluation of medical information systems are considered.

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This paper proposes and defends the small worlds hypothesis, which states that expert physicians organize diagnostic knowledge on the basis of similarities between disease categories, forming 'small worlds' consisting of small subsets of diseases and their distinguishing features. Examining existing data from several previous studies, the authors provide support for the small worlds hypothesis and for a characterization of the process of expert medical diagnostic reasoning as a succession of limited comparisons involving related diagnostic hypotheses. In one study, subjects were presented clinical endocrine cases one statement at a time and were prompted to think aloud after presentation of each statement. A combination of discourse and protocol analysis techniques were used to investigate hypothesis generation and evaluation. In another study, dialogues from doctor-patient interviews were examined. It was found that expert subjects rapidly select relatively small sets of plausible diagnostic hypotheses (small worlds) and focus on the most relevant medical findings that distinguish among the diseases in such small worlds. Results from both studies indicate that expert physicians use efficient strategies for discriminating among these alternative hypotheses in a stepwise process. In contrast, non-experts often generate large numbers of possible diagnostic hypotheses, belonging to widely differing disease categories. The results provide empirical support for the theoretical basis of small worlds. The implications of these results for the study of medical expertise and knowledge engineering are discussed, as well as considerations for the development of decision support systems.

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An important challenge in the development of computer-based health care environments is the design of effective user interfaces. In this paper we consider a number of aspects of interface design related to the study of human-computer interaction from a cognitive perspective. It is argued that user interfaces must be designed with consideration of the information requirements, cognitive capabilities and limitations of the end users. Greater concern for fundamental research in design of user interfaces is also needed to complement short-term goals and approaches to improving user interfaces. Towards these objectives, several emerging trends are beginning to have an important impact in the design of health care interfaces. This includes the recognition of the need for iterative design and evaluation of user interfaces, applying theoretical frameworks and methods from cognitive science. An understanding of distributed as well as individual cognition will also become critical in the development of effective user interfaces as access to health care systems becomes increasingly widespread.

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