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Commercial off-the-shelf consumer health informatics interventions: recommendations for their design, evaluation and redesign

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JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION 2012年第1期19卷 137-142页

作者： Marquard, Jenna L. Zayas-Caban, Teresa Univ Massachusetts Engn Lab 219 Dept Mech & Ind Engn 160 Governors Dr Amherst MA 01003 USA Agcy Healthcare Res & Qual Rockville MD USA

Objective The goal of this paper is to describe the successful application of a use case-based evaluation approach to guide the effective design, evaluation and redesign of inexpensive, commercial, off-the-shelf consumer health informatics (CHI) interventions. Design Researchers developed four CHI intervention use cases representing two distinct patient populations (patients with diabetes with high blood pressure, post-bariatric surgery patients), two commercial off-the-shelf CHI applications (Microsoft HealthVault, Google Health), and related devices (blood pressure monitor, pedometer, weight scale). Three patient proxies tested each intervention for 10 days. Measurements The patient proxies recorded their challenges while completing use case tasks, rating the severity of each challenge based on how much it hindered their use of the intervention. Two independent evaluators categorized the challenges by human factors domain (physical, cognitive, macroergonomic). Results The use case-based approach resulted in the identification of 122 challenges, with 12% physical, 50% cognitive and 38% macroergonomic. Thirty-nine challenges (32%) were at least moderately severe. Nine of 22 use case tasks (41%) accounted for 72% of the challenges. Limitations The study used two patient proxies and addressed two specific patient populations and low-cost, off-the-shelf CHI interventions, which may not perfectly generalize to a larger number of proxies, actual patient populations, or other CHI interventions. Conclusion CHI designers can employ the use case-based evaluation approach to assess the fit of a CHI intervention with patients' health work, in the context of their daily activities and environment, which would be difficult or impossible to evaluate by laboratory-based studies.

关键词： Classic experimental and quasi-experimental study methods (laboratory and field) cognitive study (including experiments emphasizing verbal protocol analysis and usability) designing usable (responsive) resources and systems human–computer interaction and human-centered computing supporting practice at a distance (telehealth) surveys and needs analysis uncertain reasoning and decision theory visualization of data and knowledge

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Collaborative knowledge acquisition for the design of context-aware alert systems

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JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION 2012年第6期19卷 988-994页

作者： Joffe, Erel Havakuk, Ofer Herskovic, Jorge R. Patel, Vimla L. Bernstam, Elmer Victor Tel Aviv Univ Tel Aviv Sourasky Med Ctr IL-69978 Tel Aviv Israel Univ Texas Hlth Sci Ctr Sch Biomed Informat Houston TX USA New York Acad Med New York NY USA Univ Texas Hlth Sci Ctr Sch Med Dept Internal Med Houston TX USA

Objective To present a framework for combining implicit knowledge acquisition from multiple experts with machine learning and to evaluate this framework in the context of anemia alerts. Materials and Methods Five internal medicine residents reviewed 18 anemia alerts, while 'talking aloud'. They identified features that were reviewed by two or more physicians to determine appropriate alert level, etiology and treatment recommendation. Based on these features, data were extracted from 100 randomly-selected anemia cases for a training set and an additional 82 cases for a test set. Two staff internists assigned an alert level, etiology and treatment recommendation before and after reviewing the entire electronic medical record. The training set of 118 cases (100 plus 18) and the test set of 82 cases were explored using RIDOR and JRip algorithms. Results The feature set was sufficient to assess 93% of anemia cases (intraclass correlation for alert level before and after review of the records by internists 1 and 2 were 0.92 and 0.95, respectively). High-precision classifiers were constructed to identify low-level alerts (precision p=0.87, recall R=0.4), iron deficiency (p=1.0, R=0.73), and anemia associated with kidney disease (p=0.87, R=0.77). Discussion It was possible to identify low-level alerts and several conditions commonly associated with chronic anemia. This approach may reduce the number of clinically unimportant alerts. The study was limited to anemia alerts. Furthermore, clinicians were aware of the study hypotheses potentially biasing their evaluation. Conclusion Implicit knowledge acquisition, collaborative filtering and machine learning were combined automatically to induce clinically meaningful and precise decision rules.

关键词： Clinical (L01.700.508.300.190) clinical research informatics cognitive study (including experiments emphasizing verbal protocol analysis and usability) computer-assisted (L01.700.508.100) computerized (L01.700.508.300.695) decision making decision support systems expert systems (L01.700.568.110.065.190) human–computer interaction and human-centered computing improving the education and skills training of health professionals information retrieval information storage and retrieval (text and images) measuring/improving patient safety and reducing medical errors medical records systems qualitative/ethnographic field study reminder systems (L01.700.508.300.790)

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The EpiCanvas infectious disease weather map: an interactive visual exploration of temporal and spatial correlations

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JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION 2012年第6期19卷 954-959页

作者： Gesteland, Per Hans Livnat, Yarden Galli, Nathan Samore, Matthew H. Gundlapalli, Adi V. Univ Utah Sch Med Dept Biomed Informat Salt Lake City UT 84113 USA Intermt Healthcare Inst Hlth Care Delivery Res Salt Lake City UT USA Univ Utah Sci & Comp Imaging Inst Salt Lake City UT 84113 USA Univ Utah Sch Med Dept Internal Med Salt Lake City UT USA VA Salt Lake City Hlth Care Syst Salt Lake City UT USA Univ Utah Sch Med Dept Pediat Salt Lake City UT USA

Advances in surveillance science have supported public health agencies in tracking and responding to disease outbreaks. Increasingly, epidemiologists have been tasked with interpreting multiple streams of heterogeneous data arising from varied surveillance systems. As a result public health personnel have experienced an overload of plots and charts as information visualization techniques have not kept pace with the rapid expansion in data availability. This study sought to advance the science of public health surveillance data visualization by conceptualizing a visual paradigm that provides an 'epidemiological canvas' for detection, monitoring, exploration and discovery of regional infectious disease activity and developing a software prototype of an 'infectious disease weather map'. Design objectives were elucidated and the conceptual model was developed using cognitive task analysis with public health epidemiologists. The software prototype was pilot tested using retrospective data from a large, regional pediatric hospital, and gastrointestinal and respiratory disease outbreaks were re-created as a proof of concept.

关键词： Biosurveillance correlation of data data display detecting disease outbreaks and biological threats developing/using clinical decision support (other than diagnostic) and guideline systems discovery human–computer interaction and human-centered computing improving healthcare workflow and process efficiency infectious disease outbreaks measuring/improving outcomes in specific conditions and patient subgroups methods for integration of information from disparate sources modeling physiological and disease processes other methods of information extraction public health surveillance simulation of complex systems (at all levels: molecules to work groups to organizations) statistical data analysis systems to support and improve diagnostic accuracy text and data mining methods visualization of data and knowledge

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The dangerous decade

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JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION 2012年第1期19卷 2-5页

作者： Coiera, Enrico Aarts, Jos Kulikowski, Casimir Univ New S Wales Ctr Hlth Informat Sydney NSW 2052 Australia Erasmus Univ Inst Hlth Policy & Management Rotterdam Netherlands Rutgers State Univ Dept Comp Sci Piscataway NJ USA

Over the next 10 years, more information and communication technology (ICT) will be deployed in the health system than in its entire previous history. Systems will be larger in scope, more complex, and move from regional to national and supranational scale. Yet we are at roughly the same place the aviation industry was in the 1950s with respect to system safety. Even if ICT harm rates do not increase, increased ICT use will increase the absolute number of ICT related harms. Factors that could diminish ICT harm include adoption of common standards, technology maturity, better system development, testing, implementation and end user training. Factors that will increase harm rates include complexity and heterogeneity of systems and their interfaces, rapid implementation and poor training of users. Mitigating these harms will not be easy, as organizational inertia is likely to generate a hysteresis-like lag, where the paths to increase and decrease harm are not identical.

关键词： Cognitive study (including experiments emphasizing verbal protocol analysis and usability) collaborative technologies communication decision support developing/using computerized provider order entry ethical study methods historical human–computer interaction and human-centered computing legal policy qualitative/ethnographic field study safety social/organizational study surveys and needs analysis system implementation and management issues

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Handling anticipated exceptions in clinical care: investigating clinician use of 'exit strategies' in an electronic health records system

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JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION 2011年第6期18卷 883-889页

作者： Zheng, Kai Hanauer, David A. Padman, Rema Johnson, Michael P. Hussain, Anwar A. Ye, Wen Zhou, Xiaomu Diamond, Herbert S. Univ Michigan Sch Informat Dept Hlth Management & Policy Sch Publ Hlth Ann Arbor MI 48109 USA Univ Michigan Dept Pediat Ann Arbor MI 48109 USA Carnegie Mellon Univ H John Heinz Coll 3 Pittsburgh PA 15213 USA Univ Massachusetts Dept Publ Policy & Publ Affairs John W McCormack Grad Sch Policy Studies Boston MA 02125 USA United Hlth Serv Hosp Johnson City NY USA Univ Michigan Sch Publ Hlth Dept Biostat Ann Arbor MI 48109 USA Rutgers State Univ Sch Commun & Informat New Brunswick NJ 08903 USA Univ Pittsburgh Sch Med Dept Med Div Rheumatol Pittsburgh PA USA

Unpredictable yet frequently occurring exception situations pervade clinical care. Handling them properly often requires aberrant actions temporarily departing from normal practice. In this study, the authors investigated several exception-handling procedures provided in an electronic health records system for facilitating clinical documentation, which the authors refer to as 'data entry exit strategies.' Through a longitudinal analysis of computer-recorded usage data, the authors found that (1) utilization of the exit strategies was not affected by postimplementation system maturity or patient visit volume, suggesting clinicians' needs to 'exit' unwanted situations are persistent;and (2) clinician type and gender are strong predictors of exit-strategy usage. Drilldown analyses further revealed that the exit strategies were judiciously used and enabled actions that would be otherwise difficult or impossible. However, many data entries recorded via them could have been 'properly' documented, yet were not, and a considerable proportion containing temporary or incomplete information was never subsequently amended. These findings may have significant implications for the design of safer and more user-friendly point-of-care information systems for healthcare.

关键词： Electronic health records (E05.318.308.940.968.625.500) workflow (L01.906.893) documentation (L01.453.245) exit strategy exception-handling 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 and integration across care settings (inter- and intraenterprise) visualization of data and knowledge developing/using computerized provider order entry diamond

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A study of machine-learning-based approaches to extract clinical entities and their assertions from discharge summaries

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JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION 2011年第5期18卷 601-606页

作者： Jiang, Min Chen, Yukun Liu, Mei Rosenbloom, S. Trent Mani, Subramani Denny, Joshua C. Xu, Hua Vanderbilt Univ Sch Med Dept Biomed Informat Nashville TN 37232 USA Vanderbilt Univ Sch Med Dept Med Nashville TN 37232 USA

Objective The authors' goal was to develop and evaluate machine-learning-based approaches to extracting clinical entities including medical problems, tests, and treatments, as well as their asserted status from hospital discharge summaries written using natural language. This project was part of the 2010 Center of Informatics for Integrating Biology and the Bedside/Veterans Affairs (VA) natural-language-processing challenge. Design The authors implemented a machine-learning-based named entity recognition system for clinical text and systematically evaluated the contributions of different types of features and ML algorithms, using a training corpus of 349 annotated notes. Based on the results from training data, the authors developed a novel hybrid clinical entity extraction system, which integrated heuristic rule-based modules with the ML-base named entity recognition module. The authors applied the hybrid system to the concept extraction and assertion classification tasks in the challenge and evaluated its performance using a test data set with 477 annotated notes. Measurements Standard measures including precision, recall, and F-measure were calculated using the evaluation script provided by the Center of Informatics for Integrating Biology and the Bedside/VA challenge organizers. The overall performance for all three types of clinical entities and all six types of assertions across 477 annotated notes were considered as the primary metric in the challenge. Results and discussion Systematic evaluation on the training set showed that Conditional Random Fields outperformed Support Vector Machines, and semantic information from existing natural-language-processing systems largely improved performance, although contributions from different types of features varied. The authors' hybrid entity extraction system achieved a maximum overall F-score of 0.8391 for concept extraction (ranked second) and 0.9313 for assertion classification (ranked fourth, but not statistically

关键词： Natural language processing machine learning named entity recognition clinical text processing NLP 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 Automated learning Translational research—application of biological knowledge to clinical care Uncertain reasoning and decision theory Linking the genotype and phenotype languages computational methods Advanced algorithms discovery text and data mining methods Knowledge representations Knowledge bases

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Development and preliminary evidence for the validity of an instrument assessing implementation of human-factors principles in medication-related decision-support systems-I-MeDeSA

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JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION 2011年第Sup1期18卷 I62-I72页

作者： Zachariah, Marianne Phansalkar, Shobha Seidling, Hanna M. Neri, Pamela M. Cresswell, Kathrin M. Duke, Jon Bloomrosen, Meryl Volk, Lynn A. Bates, David W. Partners Healthcare Syst CIRD Wellesley MA 02481 USA Brigham & Womens Hosp Div Gen Internal Med Boston MA 02115 USA Harvard Univ Sch Med Boston MA USA Univ Heidelberg Dept Clin Pharmacol & Pharmacoepidemiol Heidelberg Germany Univ Hosp Geneva Div Med Informat Sci Geneva Switzerland Univ Edinburgh Ctr Populat Hlth Sci eHlth Res Grp Edinburgh Midlothian Scotland Regenstrief Inst Hlth Care Indianapolis IN USA Amer Med Informat Assoc Bethesda MD USA

Background Medication-related decision support can reduce the frequency of preventable adverse drug events. However, the design of current medication alerts often results in alert fatigue and high over-ride rates, thus reducing any potential benefits. Methods The authors previously reviewed human-factors principles for relevance to medication-related decision support alerts. In this study, instrument items were developed for assessing the appropriate implementation of these human-factors principles in drug-drug interaction (DDI) alerts. User feedback regarding nine electronic medical records was considered during the development process. Content validity, construct validity through correlation analysis, and inter-rater reliability were assessed. Results The final version of the instrument included 26 items associated with nine human-factors principles. Content validation on three systems resulted in the addition of one principle (Corrective Actions) to the instrument and the elimination of eight items. Additionally, the wording of eight items was altered. Correlation analysis suggests a direct relationship between system age and performance of DDI alerts (p=0.0016). Inter-rater reliability indicated substantial agreement between raters (kappa=0.764). Conclusion The authors developed and gathered preliminary evidence for the validity of an instrument that measures the appropriate use of human-factors principles in the design and display of DDI alerts. Designers of DDI alerts may use the instrument to improve usability and increase user acceptance of medication alerts, and organizations selecting an electronic medical record may find the instrument helpful in meeting their clinicians' usability needs.

关键词： human factors medication-related decision support clinical decision support medication alerts name visualization of data and knowledge designing usable (responsive) resources and systems developing/using clinical decision support (other than diagnostic) and guideline systems human–computer interaction and human-centered computing policy health IT innovation patient safety decision support data exchange

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Collaborative search in electronic health records

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JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION 2011年第3期18卷 282-291页

作者： Zheng, Kai Mei, Qiaozhu Hanauer, David A. Univ Michigan Sch Publ Hlth Dept Hlth Management & Policy Sch Informat Ann Arbor MI 48109 USA Univ Michigan Dept Elect Engn & Comp Sci Ann Arbor MI 48109 USA Univ Michigan Dept Pediat Ann Arbor MI 48109 USA Univ Michigan Ctr Comprehens Canc Ann Arbor MI 48109 USA

Objective A full-text search engine can be a useful tool for augmenting the reuse value of unstructured narrative data stored in electronic health records (EHR). A prominent barrier to the effective utilization of such tools originates from users' lack of search expertise and/or medical-domain knowledge. To mitigate the issue, the authors experimented with a 'collaborative search' feature through a homegrown EHR search engine that allows users to preserve their search knowledge and share it with others. This feature was inspired by the success of many social information-foraging techniques used on the web that leverage users' collective wisdom to improve the quality and efficiency of information retrieval. Design The authors conducted an empirical evaluation study over a 4-year period. The user sample consisted of 451 academic researchers, medical practitioners, and hospital administrators. The data were analyzed using a social-network analysis to delineate the structure of the user collaboration networks that mediated the diffusion of knowledge of search. Results The users embraced the concept with considerable enthusiasm. About half of the EHR searches processed by the system (0.44 million) were based on stored search knowledge;0.16 million utilized shared knowledge made available by other users. The social-network analysis results also suggest that the user-collaboration networks engendered by the collaborative search feature played an instrumental role in enabling the transfer of search knowledge across people and domains. Conclusion Applying collaborative search, a social information-foraging technique popularly used on the web, may provide the potential to improve the quality and efficiency of information retrieval in healthcare.

关键词： 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 intraenterprise) visualization of data and knowledge developing/using computerized provider order entry

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A partnership model for implementing electronic health records in resource-limited primary care settings: experiences from two nurse-managed health centers

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JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION 2011年第6期18卷 820-826页

作者： Dennehy, Patricia White, Mary P. Hamilton, Andrew Pohl, Joanne M. Tanner, Clare Onifade, Tiffiani J. Zheng, Kai Univ Michigan Sch Publ Hlth Dept Hlth Management & Policy Ann Arbor MI 48109 USA Glide Hlth Serv San Francisco CA USA Univ Calif San Francisco Dept Community Hlth Syst San Francisco CA USA Wayne State Univ Campus Hlth Ctr Detroit MI USA Wayne State Univ Coll Nursing Detroit MI 48202 USA Alliance Chicago Community Hlth Serv Chicago IL USA Univ Michigan Sch Nursing Ann Arbor MI 48109 USA Michigan Publ Hlth Inst Inst Nursing Ctr Okemos MI USA Michigan Publ Hlth Inst Ctr Data Management & Translat Res Okemos MI USA Univ Michigan Sch Informat Ann Arbor MI 48109 USA

Objective To present a partnership-based and community-oriented approach designed to ease provider anxiety and facilitate the implementation of electronic health records (EHR) in resource-limited primary care settings. Materials and Methods The approach, referred to as partnership model, was developed and iteratively refined through the research team's previous work on implementing health information technology (HIT) in over 30 safety net practices. This paper uses two case studies to illustrate how the model was applied to help two nurse-managed health centers (NMHC), a particularly vulnerable primary care setting, implement EHR and get prepared to meet the meaningful use criteria. Results The strong focus of the model on continuous quality improvement led to eventual implementation success at both sites, despite difficulties encountered during the initial stages of the project. Discussion There has been a lack of research, particularly in resource-limited primary care settings, on strategies for abating provider anxiety and preparing them to manage complex changes associated with EHR uptake. The partnership model described in this paper may provide useful insights into the work shepherded by HIT regional extension centers dedicated to supporting resource-limited communities disproportionally affected by EHR adoption barriers. Conclusion NMHC, similar to other primary care settings, are often poorly resourced, understaffed, and lack the necessary expertise to deploy EHR and integrate its use into their day-to-day practice. This study demonstrates that implementation of EHR, a prerequisite to meaningful use, can be successfully achieved in this setting, and partnership efforts extending far beyond the initial software deployment stage may be the key.

关键词： Collaborative technologies community health care developing/using clinical decision support (other than diagnostic) and guideline systems electronic health records (E05.318.308.940.968.625.500) health information technology for economic and clinical health act (N03.706.615.049) human–computer interaction and human-centered computing improving healthcare workflow and process efficiency nurse-managed health centers personal health records and self-care systems qualitative/ethnographic field study regional extension centers social/organizational study system implementation and management issues systems supporting patient–provider interaction

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How to improve the delivery of medication alerts within computerized physician order entry systems: an international Delphi study

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JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION 2011年第6期18卷 760-766页

作者： Riedmann, Daniel Jung, Martin Hackl, Werner O. Ammenwerth, Elske UMIT Univ Hlth Sci Med Informat & Technol Inst Med Informat Eduard Wallnofer Zentrum 1 A-6060 Hall In Tirol Austria

Objectives To determine what information can be helpful in prioritizing and presenting medication alerts according to the context of the clinical situation. To assess the usefulness of different ways of delivering medication alerts to the user. Design An international Delphi study with two quantitative rounds. 69 researchers with expertise in computerized physician order entry (CPOE) systems were asked to estimate the usefulness of 20 possible context factors, and to assess the potential impact of six innovative ways of delivering alert information on adverse drug event (ADE) rates. Results Participants identified the following top five context information items (in descending order of usefulness): (1) severity of the effect of the ADE the alert refers to;(2) clinical status of the patient;(3) probability of occurrence of the ADE the alert refers to;(4) risk factors of the patient;and (5) strength of evidence on which the alert is built. The ways of delivering alert information with the highest estimated ADE reduction potential are active alerting, proactive prescription simulation and a patient medication module that gives patient-oriented alert information. Limitations Most participants had a research-oriented focus;therefore the results may not reflect the opinions of CPOE users or CPOE implementers. Conclusion The study results may provide CPOE system developers and healthcare institutions with information on how to design more effective alert mechanisms.

关键词： classic experimental and quasi-experimental study methods (lab and field) demonstrating return on IT investment human–computer interaction and human-centered computing improving healthcare workflow and process efficiency measuring/improving patient safety and reducing medical errors medical informatics nursing informatics personal health records and self-care systems qualitative/ethnographic field study

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