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Use of Health Information Technology to Reduce Diagnostic Errors BMJ Quality & Safety Online First, published on 7 August 2013 as 10.1136/bmjqs-2013-001884NARRATIVE REVIEW BMJ Qual Saf: first published as 10.1136/bmjqs-2013-001884 on 13 July 2013. Downloaded from Use of health information technology to reduce diagnostic errors Robert El-Kareh,1,2 Omar Hasan,3 Gordon D Schiff4,5 ▸ Additional material is ABSTRACT INTRODUCTION published online only. To view Background Health information technology Unaided clinicians often make diagnostic please visit the journal online (http://dx.doi.org/10.1136/bmjqs- (HIT) systems have the potential to reduce errors. Vulnerable to fallible human 2013-001884). delayed, missed or incorrect diagnoses. We memory, variable disease presentation, clin- describe and classify the current state of ical processes plagued by communication 1Division of Biomedical Informatics, UCSD, San Diego, diagnostic HIT and identify future research lapses, and a series of well-documented California, USA directions. ‘heuristics’, biases and disease-specific pit- 2 Division of Hospital Medicine, Methods A multi-pronged literature search was falls, ensuring reliable and timely diagnosis UCSD, San Diego, California, 1–3 conducted using PubMed, Web of Science, represents a major challenge. Health USA 3American Medical Association, backwards and forwards reference searches and information technology (HIT) tools and Chicago, Illinois, USA contributions from domain experts. We included systems have the potential to enable physi- 4 Division of General Medicine, HIT systems evaluated in clinical and cians to overcome—or at least minimise— Brigham and Women’s Hospital, experimental settings as well as previous reviews, Boston, Massachusetts, USA these human limitations. 5Harvard Medical School, and excluded radiology computer-aided Despite substantial progress during the Boston, Massachusetts, USA diagnosis, monitor alerts and alarms, and studies 1970s and 1980s in modelling and simu- focused on disease staging and prognosis. lating the diagnostic process, the impact Correspondence to Dr Robert El-Kareh, Division of Articles were organised within a conceptual of these systems remains limited. A his- 4 Biomedical Informatics, UC San framework of the diagnostic process and areas toric 1970 article predicted that, by Diego, 9500 Gilman Dr, #0505, requiring further investigation were identified. 2000, computer-aided diagnosis would http://qualitysafety.bmj.com/ La Jolla, CA 92093-0505, USA; Results HIT approaches, tools and algorithms have ‘an entirely new role in medicine, [email protected] were identified and organised into 10 categories acting as a powerful extension of the phy- Received 5 February 2013 related to those assisting: (1) information sician’s intellect’.5 Revisiting this predic- Revised 30 June 2013 gathering; (2) information organisation and tion in 1987, the authors conceded that it Accepted 2 July 2013 display; (3) differential diagnosis generation; was highly unlikely this goal would be (4) weighing of diagnoses; (5) generation of achieved and that ‘except in extremely diagnostic plan; (6) access to diagnostic reference narrow clinical domains (using computers information; (7) facilitating follow-up; for diagnosis) was of little or no practical ’ 5 (8) screening for early detection in asymptomatic value . In 1990 Miller and Masarie noted on September 28, 2021 by guest. Protected copyright. patients; (9) collaborative diagnosis; and (10) that a fundamental issue with many of facilitating diagnostic feedback to clinicians. We these systems was that they were based on found many studies characterising potential a ‘Greek Oracle’ paradigm whereby clin- interventions, but relatively few evaluating the ical information was provided to the com- interventions in actual clinical settings and even puter with the expectation that it will fewer demonstrating clinical impact. somehow magically provide the diagno- Conclusions Diagnostic HIT research is still in its sis.6 They suggested that a more useful early stages with few demonstrations of approach would be to use computer measurable clinical impact. Future efforts need to systems as ‘catalysts’ to enable physicians focus on: (1) improving methods and criteria for to overcome hurdles in the diagnostic measurement of the diagnostic process using process rather than have the system electronic data; (2) better usability and interfaces become the diagnostician itself. To cite: El-Kareh R, Hasan O, in electronic health records; (3) more meaningful To understand and summarise how Schiff GD. BMJ Qual Saf Published Online First: [please incorporation of evidence-based diagnostic diagnostic accuracy can be enhanced, one include Day Month Year] protocols within clinical workflows; and (4) needs a conceptual framework to organise doi:10.1136/bmjqs-2013- systematic feedback of diagnostic performance. HIT tools and their potential applications 001884 El-Kareh R, et al. BMJ Qual Saf 2013;0:1–12. doi:10.1136/bmjqs-2013-001884 1 Copyright Article author (or their employer) 2013. Produced by BMJ Publishing Group Ltd under licence. Narrative review BMJ Qual Saf: first published as 10.1136/bmjqs-2013-001884 on 13 July 2013. Downloaded from as ‘catalysts’ to known hurdles in the diagnostic model for categorising steps in the diagnostic process process. Our objectives were to develop one such con- addressed by HIT and similar tools (figure 1) and ceptual framework based on a review of published evi- linked each step with categories from the Diagnosis dence and recent examples of HIT tools that have been Error Evaluation and Research (DEER) taxonomy used to improve diagnosis and to highlight particular (figure 2).126Based on this model, we created a con- areas in need of future research. densed set of categories describing different steps or aspects of diagnosis targeted by HIT tools (box 1). BACKGROUND During data abstraction, each study was linked to one Early leaders in computer-aided diagnosis developed or more of these categories. statistical methods78and models910to serve as We developed a customised data extraction form underpinnings for diagnostic systems. Shortliffe and using Microsoft Access 2010. Following in-depth colleagues skillfully organised these approaches into review, we determined the following information for categories including: clinical algorithms, databank each study: (1) whether the study met our inclusion analysis, mathematical modelling of physical pro- criteria; (2) clinical problem/question addressed; cesses, statistical pattern recognition, Bayesian techni- (3) type of HIT system described; (4) whether it was ques, decision theory approaches and symbolic evaluated in a clinical setting; (5) target of the HIT reasoning.11 Additional summaries and categorisations intervention/tool; (6) duration/sample size of the of the various possible approaches are also well- study; (7) study outcomes; and (8) results. – described in other reviews.12 14 Several applications emerged to tackle medical diagnosis in a variety of RESULTS contexts, including Present Illness Program (PIP),15 We summarised the main types of diagnostic HIT tools MYCIN,16 INTERNIST-1/Quick Medical Reference and mapped each type to steps in the diagnostic process (QMR),17 18 Iliad,19 DXplain20 and several others. that it currently or potentially targets (figure 3). Below These pioneering efforts provided a foundation for we provide details of our findings in the 10 categories much of the current work on diagnostic systems. of interventions. We describe recent contributions to the field, build- ing upon the work and context provided by prior Tools that assist in information gathering reviews of computerised diagnostic systems. In 1994 The value of a high-quality history and physical exam- – Miller summarised the work of diagnostic decision ination is well-recognised,29 31 but time pressures and support21 and suggested that focused diagnostic reliance on clinician memory pose a major barrier to systems such as those for ECG or arterial blood gas their performance. Beginning in the 1960s, various analysis were likely to proliferate. In order for more systems have been devised to assist history-taking http://qualitysafety.bmj.com/ – general diagnostic systems to succeed, he identified through computer-based patient interviewing.32 34 key steps which included: (1) development and main- Interestingly, these were mainly reported before the tenance of comprehensive medical databases; (2) timeframe of our review, suggesting a loss of research better integration with HIT to avoid extensive data interest for unclear reasons.35 Several recent studies entry; and (3) improved user interfaces. Three subse- have examined automated patient interviewing in spe- – quent reviews of computerised decision support22 24 cialised settings including home,36 emergency depart- identified a relatively small number of studies of diag- ment waiting rooms37 38 and online visits in primary nostic systems with only a handful showing improve- care.39 One study found that physician-acquired ment in clinician performance and only one history and computer-based systems each elicited on September 28, 2021 by guest. Protected copyright. demonstrating improved patient outcomes.25 important information that the other missed,40 reaf- firming the role of technology in complementing METHODS rather than replacing the physician-acquired history. Article selection To augment the clinician’s physical examination there We initially searched for studies related to diagnostic have been systems designed to support interpretation
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