Thomas H. Payne

Enhancing patient safety and quality of care by improving the usability of electronic health record systems: recommendations from AMIA

In response to mounting evidence that use of electronic medical record systems may cause unintended consequences, and even patient harm, the AMIA Board of Directors convened a Task Force on Usability to examine evidence from the literature and make recommendations. This task force was composed of representatives from both academic settings and vendors of electronic health record (EHR) systems. After a careful review of the literature and of vendor experiences with EHR design and implementation, the task force developed 10 recommendations in four areas: (1) human factors health information technology (IT) research, (2) health IT policy, (3) industry recommendations, and (4) recommendations for the clinician end-user of EHR software. These AMIA recommendations are intended to stimulate informed debate, provide a plan to increase understanding of the impact of usability on the effective use of health IT, and lead to safer and higher quality care with the adoption of useful and usable EHR systems.

A Cross-site Qualitative Study of Physician Order Entry

OBJECTIVE To describe the perceptions of diverse professionals involved in computerized physician order entry (POE) at sites where POE has been successfully implemented and to identify differences between teaching and nonteaching hospitals. DESIGN A multidisciplinary team used observation, focus groups, and interviews with clinical, administrative, and information technology staff to gather data at three sites. Field notes and transcripts were coded using an inductive approach to identify patterns and themes in the data. MEASUREMENTS Patterns and themes concerning perceptions of POE were identified. RESULTS Four high-level themes were identified: (1) organizational issues such as collaboration, pride, culture, power, politics, and control; (2) clinical and professional issues involving adaptation to local practices, preferences, and policies; (3) technical/implementation issues, including usability, time, training and support; and (4) issues related to the organization of information and knowledge, such as system rigidity and integration. Relevant differences between teaching and nonteaching hospitals include extent of collaboration, staff longevity, and organizational missions. CONCLUSION An organizational culture characterized by collaboration and trust and an ongoing process that includes active clinician engagement in adaptation of the technology were important elements in successful implementation of physician order entry at the institutions that we studied.

Evaluating Clinical Decision Support Systems: Monitoring CPOE Order Check Override Rates in the Department of Veterans Affairs' Computerized Patient Record System

OBJECTIVE To measure critical order check override rates in VA Puget Sound Health Care Systems computerized practitioner order entry (CPOE) system and to compare 2006 results to a similar 2001 study. DESIGN Analysis of ordering and order check data gathered by a post-hoc logging program. Use of Pearsons chi-square contingency table test comparing results from this study and the earlier study. MEASUREMENTS Factors measured were total number of orders, frequency of order check types, frequency of order check overrides by order check type and comparisons of these results with previous results. RESULTS A total of 37,040 orders generated 908 (2.5%) critical order checks. Drug-drug critical alert override rate was 74/85 (87%) in 2006 compared to 95/108 (88%) in 2001 (X ( 2 )=0.04, df=1, p=0.85). The drug-allergy override rate was 341/420 (81%) compared to 72/105 (69%) in 2001 (X ( 2 )=7.97, df=1, p=0.005). In 2001, 0.25% (105/42,621) orders generated a drug-allergy order check compared to 1.13% (420/37,040) in 2006 (X ( 2 )=238.45, df=1, p<0.0001). CONCLUSION Override rates of critical drug-drug and drug-allergy order checks remain high at VA Puget Sound Health Care System including significant increases in drug-allergy order checks. We recommend that monitoring override rates be regular practice in clinical computing systems and conclude that qualitative research should be carried out to better understand how physicians interact with decision support at the point of ordering.

Active assistance technology for health-related behavior change: an interdisciplinary review.

Background Information technology can help individuals to change their health behaviors. This is due to its potential for dynamic and unbiased information processing enabling users to monitor their own progress and be informed about risks and opportunities specific to evolving contexts and motivations. However, in many behavior change interventions, information technology is underused by treating it as a passive medium focused on efficient transmission of information and a positive user experience. Objective To conduct an interdisciplinary literature review to determine the extent to which the active technological capabilities of dynamic and adaptive information processing are being applied in behavior change interventions and to identify their role in these interventions. Methods We defined key categories of active technology such as semantic information processing, pattern recognition, and adaptation. We conducted the literature search using keywords derived from the categories and included studies that indicated a significant role for an active technology in health-related behavior change. In the data extraction, we looked specifically for the following technology roles: (1) dynamic adaptive tailoring of messages depending on context, (2) interactive education, (3) support for client self-monitoring of behavior change progress, and (4) novel ways in which interventions are grounded in behavior change theories using active technology. Results The search returned 228 potentially relevant articles, of which 41 satisfied the inclusion criteria. We found that significant research was focused on dialog systems, embodied conversational agents, and activity recognition. The most covered health topic was physical activity. The majority of the studies were early-stage research. Only 6 were randomized controlled trials, of which 4 were positive for behavior change and 5 were positive for acceptability. Empathy and relational behavior were significant research themes in dialog systems for behavior change, with many pilot studies showing a preference for those features. We found few studies that focused on interactive education (3 studies) and self-monitoring (2 studies). Some recent research is emerging in dynamic tailoring (15 studies) and theoretically grounded ontologies for automated semantic processing (4 studies). Conclusions The potential capabilities and risks of active assistance technologies are not being fully explored in most current behavior change research. Designers of health behavior interventions need to consider the relevant informatics methods and algorithms more fully. There is also a need to analyze the possibilities that can result from interaction between different technology components. This requires deep interdisciplinary collaboration, for example, between health psychology, computer science, health informatics, cognitive science, and educational methodology.

Recommendations to Improve the Usability of Drug-Drug Interaction Clinical Decision Support Alerts

OBJECTIVE To establish preferred strategies for presenting drug-drug interaction (DDI) clinical decision support alerts. MATERIALS AND METHODS A DDI Clinical Decision Support Conference Series included a workgroup consisting of 24 clinical, usability, and informatics experts representing academia, health information technology (IT) vendors, healthcare organizations, and the Office of the National Coordinator for Health IT. Workgroup members met via web-based meetings 12 times from January 2013 to February 2014, and two in-person meetings to reach consensus on recommendations to improve decision support for DDIs. We addressed three key questions: (1) what, how, where, and when do we display DDI decision support? (2) should presentation of DDI decision support vary by clinicians? and (3) how should effectiveness of DDI decision support be measured? RESULTS Our recommendations include the consistent use of terminology, visual cues, minimal text, formatting, content, and reporting standards to facilitate usability. All clinicians involved in the medication use process should be able to view DDI alerts and actions by other clinicians. Override rates are common but may not be a good measure of effectiveness. DISCUSSION Seven core elements should be included with DDI decision support. DDI information should be presented to all clinicians. Finally, in their current form, override rates have limited capability to evaluate alert effectiveness. CONCLUSION DDI clinical decision support alerts need major improvements. We provide recommendations for healthcare organizations and IT vendors to improve the clinician interface of DDI alerts, with the aim of reducing alert fatigue and improving patient safety.

Report of the AMIA EHR 2020 task force on the status and future direction of EHRs

Over the last 5 years, stimulated by the changing healthcare environment and the Health Information Technology for Economic and Clinical Health (HITECH) Meaningful Use (MU) Electronic Health Record (EHR) Incentive program, EHR adoption has increased remarkably, and there is early evidence that such adoption has resulted in healthcare safety and quality benefits.1,2 However, with this broad adoption, many clinicians are voicing concerns that EHR use has had unintended clinical consequences, including reduced time for patient-clinician interaction,3 new and burdensome data entry tasks being transferred to front-line clinicians,4,5 and lengthened clinician workdays.6–8 Additionally, interoperability between different EHR systems has languished despite large efforts towards that goal.9,10 These challenges are contributing to physicians’ decreased satisfaction with their work lives.11–13 In professional journals,14 press reports,15–17 on wards, and in clinics, we have heard of the difficulties that the transition from paper records to EHRs has created.18 As a result, clinicians are seeking help to get through their work days, which often extend into evenings devoted to writing notes. Examples of comments we have received from clinicians and patients include: “Computers always make things faster and cheaper. Not this time,” and “My doctor pays more attention to the computer than to me.” Ultimately the healthcare systems goal is to create a robust, integrated, and interoperable healthcare system that includes patients, physician practices, public health, population management, and support for clinical and basic sciences research. This ecosystem has been referred to as the “learning health system.”19 EHRs are an important part of the learning health system, along with many other clinical systems, but future ways in which information is transformed into knowledge will likely require all parts of the system working together. Potentially every patient encounter could present an …

Transition from paper to electronic inpatient physician notes

UW Medicine teaching hospitals have seen a move from paper to electronic physician inpatient notes, after improving the availability of workstations, and wireless laptops and the technical infrastructure supporting the electronic medical record (EMR). The primary driver for the transition was to unify the medical record for all disciplines in one location. The main barrier faced was the time required to enter notes, which was addressed with data-rich templates tailored to rounding workflow, simplified login and other measures. After a 2-year transition, nearly all physician notes for hospitalized patients are now entered electronically, approximately 1500 physician notes per day. Remaining challenges include time for note entry, and the perception that notes may be more difficult to understand and to find within the EMR. In general, the transition from paper to electronic notes has been regarded as valuable to patient care and hospital operations.

A text processing pipeline to extract recommendations from radiology reports

Communication of follow-up recommendations when abnormalities are identified on imaging studies is prone to error. The absence of an automated system to identify and track radiology recommendations is an important barrier to ensuring timely follow-up of patients especially with non-acute incidental findings on imaging examinations. In this paper, we present a text processing pipeline to automatically identify clinically important recommendation sentences in radiology reports. Our extraction pipeline is based on natural language processing (NLP) and supervised text classification methods. To develop and test the pipeline, we created a corpus of 800 radiology reports double annotated for recommendation sentences by a radiologist and an internist. We ran several experiments to measure the impact of different feature types and the data imbalance between positive and negative recommendation sentences. Our fully statistical approach achieved the best f-score 0.758 in identifying the critical recommendation sentences in radiology reports.

National-scale clinical information exchange in the United Kingdom: lessons for the United States.

Over the last four decades, the UK has made large investments in healthcare information technology. The authors conducted interviews and reviewed published and unpublished documents to describe national-scale clinical information exchange in England, how it was achieved, and the problems experienced that the USA might avoid. Clinical information exchange in the UK was accomplished by establishing a foundation of policy, infrastructure, and systems of care, by creating and acquiring clinical computing applications and with strong use of financial and clinical incentives. Many software and hardware vendors played a part in this effort; they participated in a national framework created by the NHS in which standards for exchange are specified and their applications designed to make clinical information exchange part of normal practice. Great potential exists for cost reduction, increased safety, and greater patient involvement as a result of clinical information exchange.

Prescriber and staff perceptions of an electronic prescribing system in primary care: a qualitative assessment

BackgroundThe United States (US) Health Information Technology for Economic and Clinical Health Act of 2009 has spurred adoption of electronic health records. The corresponding meaningful use criteria proposed by the Centers for Medicare and Medicaid Services mandates use of computerized provider order entry (CPOE) systems. Yet, adoption in the US and other Western countries is low and descriptions of successful implementations are primarily from the inpatient setting; less frequently the ambulatory setting. We describe prescriber and staff perceptions of implementation of a CPOE system for medications (electronic- or e-prescribing system) in the ambulatory setting.MethodsUsing a cross-sectional study design, we conducted eight focus groups at three primary care sites in an independent medical group. Each site represented a unique stage of e-prescribing implementation - pre/transition/post. We used a theoretically based, semi-structured questionnaire to elicit physician (n=17) and staff (n=53) perceptions of implementation of the e-prescribing system. We conducted a thematic analysis of focus group discussions using formal qualitative analytic techniques (i.e. deductive framework and grounded theory). Two coders independently coded to theoretical saturation and resolved discrepancies through discussions.ResultsTen themes emerged that describe perceptions of e-prescribing implementation: 1) improved availability of clinical information resulted in prescribing efficiencies and more coordinated care; 2) improved documentation resulted in safer care; 3) efficiencies were gained by using fewer paper charts; 4) organizational support facilitated adoption; 5) transition required time; resulted in workload shift to staff; 6) hardware configurations and network stability were important in facilitating workflow; 7) e-prescribing was time-neutral or time-saving; 8) changes in patient interactions enhanced patient care but required education; 9) pharmacy communications were enhanced but required education; 10) positive attitudes facilitated adoption.ConclusionsPrescribers and staff worked through the transition to successfully adopt e-prescribing, and noted the benefits. Overall impressions were favorable. No one wished to return to paper-based prescribing.