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Using the time and motion method to study clinical work processes and workflow: methodological inconsistencies and a call for standardized research

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JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION 2011年第5期18卷 704-710页

作者： Zheng, Kai Guo, Michael H. Hanauer, David A. Univ Michigan Sch Publ Hlth Dept Hlth Management & Policy Ann Arbor MI 48109 USA Univ Michigan Sch Informat Ann Arbor MI 48109 USA Univ Florida Coll Med Gainesville FL USA Univ Michigan Dept Pediat Ann Arbor MI 48109 USA Univ Michigan Ctr Comprehens Canc Ann Arbor MI 48109 USA

Objective To identify ways for improving the consistency of design, conduct, and results reporting of time and motion (TEM) research in health informatics. Materials and methods We analyzed the commonalities and divergences of empirical studies published 1990-2010 that have applied the T&M approach to examine the impact of health IT implementation on clinical work processes and workflow. The analysis led to the development of a suggested 'checklist' intended to help future T&M research produce compatible and comparable results. We call this checklist STAMP (Suggested Time And Motion Procedures). Results STAMP outlines a minimum set of 29 data/information elements organized into eight key areas, plus three supplemental elements contained in an 'Ancillary Data' area, that researchers may consider collecting and reporting in their future T&M endeavors. Discussion TEM is generally regarded as the most reliable approach for assessing the impact of health IT implementation on clinical work. However, there exist considerable inconsistencies in how previous TEN studies were conducted and/or how their results were reported, many of which do not seem necessary yet can have a significant impact on quality of research and generalisability of results. Therefore, we deem it is time to call for standards that can help improve the consistency of TEN research in health informatics. This study represents an initial attempt. Conclusion We developed a suggested checklist to improve the methodological and results reporting consistency of T&M research, so that meaningful insights can be derived from across-study synthesis and health informatics, as a field, will be able to accumulate knowledge from these studies.

关键词： Time and motion studies (F02.784.412.846.707) workflow (L01.906.893) health information technology (L01.700) medical informatics applications (L01.700.508) collaborative technologies personal health records and self-care systems developing/using clinical decision support (other than diagnostic) and guideline systems systems supporting patient-provider interaction human-computer interaction and human-centered computing improving healthcare workflow and process efficiency system implementation and management issues social/organizational study qualitative/ethnographic field study cognitive study (including experiments emphasizing verbal protocol analysis and usability) methods for integration of information from disparate sources information storage and retrieval (text and images) data exchange communication integration across care settings (inter- and intra-enterprise) visualization of data and knowledge developing/using computerized provider order entry

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Development and evaluation of a comprehensive clinical decision support taxonomy: comparison of front-end tools in commercial and internally developed electronic health record systems

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JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION 2011年第3期18卷 232-242页

作者： Wright, Adam Sittig, Dean F. Ash, Joan S. Feblowitz, Joshua Meltzer, Seth McMullen, Carmit Guappone, Ken Carpenter, Jim Richardson, Joshua Simonaitis, Linas Evans, R. Scott Nichol, W. Paul Middleton, Blackford Brigham & Womens Hosp Div Gen Med & Primary Care Boston MA 02115 USA Partners HealthCare Boston MA USA Harvard Univ Sch Med Boston MA USA Univ Texas Houston UT Mem Hermann Ctr Healthcare Qual & Safety Sch Biomed Informat Houston TX USA Oregon Hlth & Sci Univ Dept Med Informat & Clin Epidemiol Portland OR 97201 USA Kaiser Permanente Ctr Hlth Res Portland OR USA Providence Portland Med Ctr Reg Informat Serv Portland OR USA Weill Cornell Med Coll Ctr Healthcare Informat & Policy New York NY USA Indiana Univ Sch Med Regenstrief Inst Inc Indianapolis IN USA Intermt Hlth Care Dept Med Informat Salt Lake City UT USA Vet Hlth Adm Patient Care Serv Seattle WA USA

Background Clinical decision support (CDS) is a valuable tool for improving healthcare quality and lowering costs. However, there is no comprehensive taxonomy of types of CDS and there has been limited research on the availability of various CDS tools across current electronic health record (EHR) systems. Objective To develop and validate a taxonomy of front-end CDS tools and to assess support for these tools in major commercial and internally developed EHRs. Study design and methods We used a modified Delphi approach with a panel of 11 decision support experts to develop a taxonomy of 53 front-end CDS tools. Based on this taxonomy, a survey on CDS tools was sent to a purposive sample of commercial EHR vendors (n=9) and leading healthcare institutions with internally developed state-of-the-art EHRs (n=4). Results Responses were received from all healthcare institutions and 7 of 9 EHR vendors (response rate: 85%). All 53 types of CDS tools identified in the taxonomy were found in at least one surveyed EHR system, but only 8 functions were present in all EHRs. Medication dosing support and order facilitators were the most commonly available classes of decision support, while expert systems (eg, diagnostic decision support, ventilator management suggestions) were the least common. Conclusion We developed and validated a comprehensive taxonomy of front-end CDS tools. A subsequent survey of commercial EHR vendors and leading healthcare institutions revealed a small core set of common CDS tools, but identified significant variability in the remainder of clinical decision support content.

关键词： Developing/using computerized provider order entry knowledge representations classical experimental and quasi-experimental study methods (lab and field) designing usable (responsive) resources and systems statistical analysis of large datasets discovery text and data mining methods automated learning human-computer interaction and human-centered computing qualitative/ethnographic field study clinical decision support manning maddux decision support biomedical informatics developing and refining EHR data standards (including image standards) controlled terminologies and vocabularies measuring/improving patient safety and reducing medical errors machine learning electronic health records meaningful use

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The feasibility of automating audit and feedback for ART guideline adherence in Malawi

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JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION 2011年第6期18卷 868-874页

作者： Lewis, Zach Landis Mello-Thoms, Claudia Gadabu, Oliver J. Gillespie, E. Miranda Douglas, Gerald P. Crowley, Rebecca S. Univ Pittsburgh Dept Biomed Informat Ctr Hlth Informat Underserved Pittsburgh PA 15260 USA Baobab Hlth Trust Lilongwe Malawi Univ Pittsburgh Dept Med Div Gen Internal Med Med Ctr Pittsburgh PA 15260 USA

Objective To determine the feasibility of using electronic medical record (EMR) data to provide audit and feedback of antiretroviral therapy (ART) clinical guideline adherence to healthcare workers (HCWs) in Malawi. Materials and methods We evaluated recommendations from Malawi's ART guidelines using GuideLine Implementability Appraisal criteria. Recommendations that passed selected criteria were converted into ratio-based performance measures. We queried representative EMR data to determine the feasibility of generating feedback for each performance measure, summed clinical encounters representing each performance measure's denominator, and then measured the distribution of encounter frequency for individual HCWs across nurse and clinical officer groups. Results We analyzed 423 831 encounters in the EMR data and generated automated feedback for 21 recommendations (12%) from Malawi's ART guidelines. We identified 11 nurse recommendations and eight clinical officer recommendations. Individual nurses and clinical officers had an average of 45 and 59 encounters per month, per recommendation, respectively. Another 37 recommendations (21%) would support audit and feedback if additional routine EMR data are captured and temporal constraints are modeled. Discussion It appears feasible to implement automated guideline adherence feedback that could potentially improve HCW performance and supervision. Feedback reports may support workplace learning by increasing HCWs' opportunities to reflect on their performance. Conclusion A moderate number of recommendations from Malawi's ART guidelines can be used to generate automated guideline adherence feedback using existing EMR data. Further study is needed to determine the receptivity of HCWs to peer comparison feedback and barriers to implementation of automated audit and feedback in low-resource settings.

关键词： eHealth HIV/AIDS audit and feedback clinical practice guidelines low-resource settings JAMIA Point of care touchscreen systems developing world malawi improving patient care ICT4D human-computer interaction and human-centered computing intelligent tutoring and tailored information representation improving the education and skills training of health professionals

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2010 i2b2/VA challenge on concepts, assertions, and relations in clinical text

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JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION 2011年第5期18卷 552-556页

作者： Uzuner, Oezlem South, Brett R. Shen, Shuying DuVall, Scott L. SUNY Albany Coll Comp & Informat Dept Informat Studies Albany NY 12222 USA VA Salt Lake City Hlth Care Syst Salt Lake City UT USA Univ Utah Dept Internal Med Salt Lake City UT 84112 USA Univ Utah Dept Biomed Informat Salt Lake City UT USA

The 2010 i2b2/VA Workshop on Natural Language Processing Challenges for Clinical Records presented three tasks: a concept extraction task focused on the extraction of medical concepts from patient reports;an assertion classification task focused on assigning assertion types for medical problem concepts;and a relation classification task focused on assigning relation types that hold between medical problems, tests, and treatments. i2b2 and the VA provided an annotated reference standard corpus for the three tasks. Using this reference standard, 22 systems were developed for concept extraction, 21 for assertion classification, and 16 for relation classification. These systems showed that machine learning approaches could be augmented with rule-based systems to determine concepts, assertions, and relations. Depending on the task, the rule-based systems can either provide input for machine learning or post-process the output of machine learning. Ensembles of classifiers, information from unlabeled data, and external knowledge sources can help when the training data are inadequate.

关键词： Information storage and retrieval (text and images) discovery and text and data mining methods Other methods of information extraction Natural-language processing Automated learning visualization of data and knowledge uncertain reasoning and decision theory languages and computational methods statistical analysis of large datasets advanced algorithms discovery other methods of information extraction automated learning human-computer interaction and human-centered computing NLP machine learning Informatics

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Clinician characteristics and use of novel electronic health record functionality in primary care

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JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION 2011年第SUPPLEMENT_1期18卷 I87-I90页

作者： Linder, Jeffrey A. Rigotti, Nancy A. Schneider, Louise I. Kelley, Jennifer H. K. Brawarsky, Phyllis Schnipper, Jeffrey L. Middleton, Blackford Haas, Jennifer S. Brigham & Womens Hosp Div Gen Med & Primary Care Boston MA 02120 USA Harvard Univ Sch Med Boston MA USA Massachusetts Gen Hosp Tobacco Res & Treatment Ctr Boston MA 02114 USA Massachusetts Gen Hosp Div Gen Med Boston MA 02114 USA

Background Conventional wisdom holds that older, busier clinicians who see complex patients are less likely to adopt and use novel electronic health record (EHR) functionality. Methods To compare the characteristics of clinicians who did and did not use novel EHR functionality, we conducted a retrospective analysis of the intervention arm of a randomized trial of new EHR-based tobacco treatment functionality. Results The novel functionality was used by 103 of 207 (50%) clinicians. Staff physicians were more likely than trainees to use the functionality (64% vs 37%;p<0.001). Clinicians who graduated more than 10 years previously were more likely to use the functionality than those who graduated less than 10 years previously (64% vs 42%;p<0.01). Clinicians with higher patient volumes were more likely to use the functionality (lowest quartile of number of patient visits, 25%;2nd quartile, 38%;3rd quartile, 65%;highest quartile, 71%;p<0.001). Clinicians who saw patients with more documented problems were more likely to use the functionality (lowest tertile of documented patient problems, 38%;2nd tertile, 58%;highest tertile, 54%;p=0.04). In multivariable modeling, independent predictors of use were the number of patient visits (OR 1.2 per 100 additional patients;95% CI 1.1 to 1.4) and number of documented problems (OR 2.9 per average additional problem;95% CI 1.4 to 6.1). Conclusions Contrary to conventional wisdom, clinically busier physicians seeing patients with more documented problems were more likely to use novel EHR functionality.

关键词： Electronic health records physicians' practice patterns primary health care decision support systems clinical human-computer interaction and human-centered computing developing/using clinical decision support (other than diagnostic) and guideline systems other specific EHR applications (results review) medication administration disease progression quality improvement patient safety clinical decision support hospital medicine image managem knowledge representations uncertain reasoning and decision theory designing usable (responsive) resources and systems personal health records and self-care systems knowledge acquisition and knowledge management demonstrating return on it investment

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MyHealthAtVanderbilt: policies and procedures governing patient portal functionality

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JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION 2011年第SUPPLEMENT_1期18卷 I18-I23页

作者： Osborn, Chandra Y. Rosenbloom, S. Trent Stenner, Shane P. Anders, Shilo Muse, Sue Johnson, Kevin B. Jirjis, Jim Jackson, Gretchen Purcell Vanderbilt Univ Med Ctr Div Gen Internal Med & Publ Hlth Ctr Hlth Serv ResDept Med Nashville TN 37232 USA Vanderbilt Univ Med Ctr Dept Biomed Informat Nashville TN 37232 USA Vanderbilt Univ Med Ctr Dept Pediat Nashville TN 37232 USA Vanderbilt Univ Med Ctr Dept Anesthesiol Nashville TN 37232 USA Monroe Carell Jr Childrens Hosp Vanderbilt Dept Pediat Surg Nashville TN USA

Explicit guidelines are needed to develop safe and effective patient portals. This paper proposes general principles, policies, and procedures for patient portal functionality based on MyHealthAtVanderbilt (MHAV), a robust portal for Vanderbilt University Medical Center. We describe policies and procedures designed to govern popular portal functions, address common user concerns, and support adoption. We present the results of our approach as overall and function-specific usage data. Five years after implementation, MHAV has over 129 800 users;45% have used bi-directional messaging;52% have viewed test results and 45% have viewed other medical record data;30% have accessed health education materials;39% have scheduled appointments;and 29% have managed a medical bill. Our policies and procedures have supported widespread adoption and use of MHAV. We believe other healthcare organizations could employ our general guidelines and lessons learned to facilitate portal implementation and usage.

关键词： Patient portal personal health records consumer health informatics medical informatics computing support US Gov't PHS user-computer interface behavioral informatics medication management health literacy ethical study methods text generation from discrete data classical experimental and quasi-experimental study methods (lab and field) developing and refining EHR data standards (including image standards) controlled terminologies and vocabularies human-computer interaction and human-centered computing surveys and needs analysis qualitative/ethnographic field study policy legal historical Shane Stenner cognitive study (including experiments emphasizing verbal protocol analysis and usability) measuring/improving outcomes in specific conditions and patient subgroups measuring/improving patient safety and reducing medical errors collaborative technologies clinical informatics biomedical informatics pediatrics e-prescribing human factors portal patient MyHealthatVanderbilt PHR

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Development and validation of a survey instrument for assessing prescribers' perception of computerized drug-drug interaction alerts

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JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION 2011年第SUPPLEMENT_1期18卷 I51-I61页

作者： Zheng, Kai Fear, Kathleen Chaffee, Bruce W. Zimmerman, Christopher R. Karls, Edward M. Gatwood, Justin D. Stevenson, James G. Pearlman, Mark D. Univ Michigan Dept Hlth Management & Policy Sch Publ Hlth Ann Arbor MI 48109 USA Univ Michigan Sch Informat Ann Arbor MI 48109 USA Univ Michigan Coll Pharm Ann Arbor MI 48109 USA Univ Michigan Dept Pharm Serv Univ Michigan Hlth Syst Ann Arbor MI 48109 USA Univ Michigan Dept Qual Improvement Univ Michigan Hlth Syst Ann Arbor MI 48109 USA Univ Michigan Dept Obstet & Gynecol Sch Med Ann Arbor MI 48109 USA

Objective To develop a theoretically informed and empirically validated survey instrument for assessing prescribers' perception of computerized drug-drug interaction (DDI) alerts. Materials and methods The survey is grounded in the unified theory of acceptance and use of technology and an adapted accident causation model. Development of the instrument was also informed by a review of the extant literature on prescribers' attitude toward computerized medication safety alerts and common prescriber-provided reasons for overriding. To refine and validate the survey, we conducted a two-stage empirical validation study consisting of a pretest with a panel of domain experts followed by a field test among all eligible prescribers at our institution. Results The resulting survey instrument contains 28 questionnaire items assessing six theoretical dimensions: performance expectancy, effort expectancy, social influence, facilitating conditions, perceived fatigue, and perceived use behavior. Satisfactory results were obtained from the field validation;however, a few potential issues were also identified. We analyzed these issues accordingly and the results led to the final survey instrument as well as usage recommendations. Discussion High override rates of computerized medication safety alerts have been a prevalent problem. They are usually caused by, or manifested in, issues of poor end user acceptance. However, standardized research tools for assessing and understanding end users' perception are currently lacking, which inhibits knowledge accumulation and consequently forgoes improvement opportunities. The survey instrument presented in this paper may help fill this methodological gap. Conclusion We developed and empirically validated a survey instrument that may be useful for future research on DDI alerts and other types of computerized medication safety alerts more generally.

关键词： Decision support systems clinical (L01.700.508.300.190) medical order entry systems (L01.700.508.300.408.600) drug interactions (G07.690.812.240) psychology social (F01.829) Questionnaires (L01.280.800) collaborative technologies personal health records and self-care systems personal health records and self-care systems developing/using clinical decision support (other than diagnostic) and guideline systems systems supporting patient-provider interaction human-computer interaction and human-centered computing improving healthcare workflow and process efficiency system implementation and management issues social/organizational study qualitative/ethnographic field study pharmacy clinical decision support outcome quality improvement medications surveys business intelligence quality improvement patient satisfaction employee satisfaction pharmacy quality patient safety machine learning knowledge bases

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Drug side effect extraction from clinical narratives of psychiatry and psychology patients

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JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION 2011年第SUPPLEMENT_1期18卷 I144-I149页

作者： Sohn, Sunghwan Kocher, Jean-Pierre A. Chute, Christopher G. Savova, Guergana K. Mayo Clin Div Biomed Stat & Informat Dept Hlth Sci Res Rochester MN 55905 USA Childrens Hosp Boston MA 02115 USA Harvard Univ Sch Med Boston MA 02115 USA

Objective To extract physician-asserted drug side effects from electronic medical record clinical narratives. Materials and methods Pattern matching rules were manually developed through examining keywords and expression patterns of side effects to discover an individual side effect and causative drug relationship. A combination of machine learning (C4.5) using side effect keyword features and pattern matching rules was used to extract sentences that contain side effect and causative drug pairs, enabling the system to discover most side effect occurrences. Our system was implemented as a module within the clinical Text Analysis and Knowledge Extraction System. Results The system was tested in the domain of psychiatry and psychology. The rule-based system extracting side effects and causative drugs produced an F score of 0.80 (0.55 excluding allergy section). The hybrid system identifying side effect sentences had an F score of 0.75 (0.56 excluding allergy section) but covered more side effect and causative drug pairs than individual side effect extraction. Discussion The rule-based system was able to identify most side effects expressed by clear indication words. More sophisticated semantic processing is required to handle complex side effect descriptions in the narrative. We demonstrated that our system can be trained to identify sentences with complex side effect descriptions that can be submitted to a human expert for further abstraction. Conclusion Our system was able to extract most physician-asserted drug side effects. It can be used in either an automated mode for side effect extraction or semi-automated mode to identify side effect sentences that can significantly simplify abstraction by a human expert.

关键词： Natural language processing machine learning information extraction electronic medical record Information storage and retrieval (text and images) discovery and text and data mining methods Other methods of information extraction Natural-language processing bioinformatics Ontologies Knowledge representations Controlled terminologies and vocabularies Information Retrieval HIT Data Standards human-computer interaction and human-centered computing Providing just-in-time access to the biomedical literature and other health information Applications that link biomedical knowledge from diverse primary sources (includes automated indexing) Linking the genotype and phenotype

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A clinical decision support needs assessment of community-based physicians

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JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION 2011年第SUPPLEMENT_1期18卷 I28-I35页

作者： Richardson, Joshua E. Ash, Joan S. Weill Cornell Med Coll Dept Publ Hlth New York NY USA Oregon Hlth & Sci Univ Dept Med Informat & Clin Epidemiol Portland OR 97201 USA

Objective To conduct a grounded needs assessment to elicit community-based physicians' current views on clinical decision support (CDS) and its desired capabilities that may assist future CDS design and development for community-based practices. Materials and methods To gain insight into community-based physicians' goals, environments, tasks, and desired support tools, we used a human-computer interaction model that was based in grounded theory. We conducted 30 recorded interviews with, and 25 observations of, primary care providers within 15 urban and rural community-based clinics across Oregon. Participants were members of three healthcare organizations with different commercial electronic health record systems. We used a grounded theory approach to analyze data and develop a user-centered definition of CDS and themes related to desired CDS functionalities. Results Physicians viewed CDS as a set of software tools that provide alerts, prompts, and reference tools, but not tools to support patient management, clinical operations, or workflow, which they would like. They want CDS to enhance physician-patient relationships, redirect work among staff, and provide time-saving tools. Participants were generally dissatisfied with current CDS capabilities and overall electronic health record usability. Discussion Physicians identified different aspects of decision-making in need of support: clinical decision-making such as medication administration and treatment, and cognitive decision-making that enhances relationships and interactions with patients and staff. Conclusion Physicians expressed a need for decision support that extended beyond their own current definitions. To meet this requirement, decision support tools must integrate functions that align time and resources in ways that assist providers in a broad range of decisions.

关键词： Qualitative/ethnographic field study biomedical informatics developing/using clinical decision support (other than diagnostic) and guideline systems knowledge acquisition and knowledge management human-computer interaction and human-centered computing social/organizational study developing/using computerized provider order entry you have improving the education and skills training of health professionals system implementation and management issues

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