S. Trent Rosenbloom

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.

Data from clinical notes: a perspective on the tension between structure and flexible documentation

Clinical documentation is central to patient care. The success of electronic health record system adoption may depend on how well such systems support clinical documentation. A major goal of integrating clinical documentation into electronic heath record systems is to generate reusable data. As a result, there has been an emphasis on deploying computer-based documentation systems that prioritize direct structured documentation. Research has demonstrated that healthcare providers value different factors when writing clinical notes, such as narrative expressivity, amenability to the existing workflow, and usability. The authors explore the tension between expressivity and structured clinical documentation, review methods for obtaining reusable data from clinical notes, and recommend that healthcare providers be able to choose how to document patient care based on workflow and note content needs. When reusable data are needed from notes, providers can use structured documentation or rely on post-hoc text processing to produce structured data, as appropriate.

Prompting clinicians about preventive care measures: a systematic review of randomized controlled trials

Preventive care measures remain underutilized despite recommendations to increase their use. The objective of this review was to examine the characteristics, types, and effects of paper- and computer-based interventions for preventive care measures. The study provides an update to a previous systematic review. We included randomized controlled trials that implemented a physician reminder and measured the effects on the frequency of providing preventive care. Of the 1,535 articles identified, 28 met inclusion criteria and were combined with the 33 studies from the previous review. The studies involved 264 preventive care interventions, 4,638 clinicians and 144,605 patients. Implementation strategies included combined paper-based with computer generated reminders in 34 studies (56%), paper-based reminders in 19 studies (31%), and fully computerized reminders in 8 studies (13%). The average increase for the three strategies in delivering preventive care measures ranged between 12% and 14%. Cardiac care and smoking cessation reminders were most effective. Computer-generated prompts were the most commonly implemented reminders. Clinician reminders are a successful approach for increasing the rates of delivering preventive care; however, their effectiveness remains modest. Despite increased implementation of electronic health records, randomized controlled trials evaluating computerized reminder systems are infrequent.

The impact of peer management on test-ordering behavior

Context Can simple electronic aids help physicians reduce unnecessary, costly test ordering? Contribution In this interrupted time-series study from a large academic hospital, a committee of peer leaders selected ways to use their care provider order entry (CPOE) system to reduce unnecessary test ordering. Computer prompts questioning repetitive orders for routine tests and unbundling of tests within metabolic panel tests both reduced test orders. Patient readmission rates, length of stay, transfer to intensive care units, and mortality rates remained stable. Implications Peer-designed interventions using CPOE systems can improve provider test-ordering behavior. The Editors Providers of clinical care order excessive tests for hospitalized patients for defensive reasons (1) or ease of access (2) or because they cannot manage the fear of uncertainty (3, 4). Excessive ordering increases the use of technology and adds unnecessary costs to the delivery of health care. Motivated by studies demonstrating substantial variation in testing behaviors among providers (2, 5-14), inappropriate or unnecessary testing (15-23), and test addiction (24-26), investigators over the past decade have tried to impose sustainable limits on diagnostic evaluations. However, many recommended approaches are too time-consuming (27), difficult to scale across an institution (28), counterproductive to training (29), detrimental to clinical decision making (26), or inappropriately intrusive (26). One study suggested that short-term reductions in the amount of testing were not sustainable (30). In a review of various approaches to limit testing, Solomon and colleagues (24) noted that multifaceted interventions are most likely to succeed. The Institute of Medicine (31, 32) and industry leaders (33, 34) recently advocated the use of information systems to improve health care delivery, especially in the area of care provider order entry (CPOE) (35). Several studies document that computer-based reminders (25, 36-38) and just-in-time decision support (39) improve test-ordering practices. Care provider order entry systems also are an effective way to manage and implement change (38, 40) and can be used to reduce variability in provider behavior (41). Citing an alarming increase in the use of expensive or duplicate testing, the Vanderbilt University Medical Center, Nashville, Tennessee, chartered a resource utilization committee (RUC) to reduce variability in laboratory testing, imaging, and formulary use without restricting access to necessary or reasoned inquiry. Members of the committee included many clinical leaders in the institution (Appendix). The committee first identified specific patterns of excessive resource utilization in the hospital and subsequently devised several interventions using CPOE to reduce repetitive testing. The institutional review board approved the study, and the need for informed consent was waived. Methods Study Sample Vanderbilt University Hospital is a 658-bed tertiary care facility that houses 2 floors of the Vanderbilt Childrens Hospital. During the study period (1999 to 2001), more than 10000 orders were placed daily through the use of CPOE systems from 35 of the 37 patient care units; these 35 units cover approximately 600 beds of the hospital. The pediatric and neonatal intensive care units (ICUs) were not using CPOE systems during this interval. The study sample consisted of attending physicians, housestaff, medical students, nurses, advance practice nurses, and other clinical staff at Vanderbilt University Hospital who used CPOE systems. Physicians directly entered 70% of orders, and other members of the patient care team entered the remainder of orders. Care Provider Order Entry Like many systems, our CPOE system processes test orders as follows. First, a provider enters an order with a specified duration of recurrences. Second, the system generates up to 1 week of orders for individual tests. Third, each test is performed as scheduled unless a provider cancels subsequent occurrences. Finally, for recurring orders still active after each week, the software queues up a subsequent week of individual occurrences. Resource Utilization Committee Interventions To determine how and where to intervene, the RUC analyzed past CPOE log files for testing patterns and used bibliographic resources and its own expertise to determine optimal strategies for ordering individual tests. From December 1999 through the study period, during weekly to monthly committee meetings with all RUC members invited, the committee reviewed CPOE summary data that indicated the volume of laboratory, radiology, and cardiology tests that were ordered per month on each hospital ward. This was done prospectively to identify opportunities for intervention and was also done after the intervention to determine effectiveness. (No study intervention described in this paper was changed on the basis of this feedback, although the transition from the first intervention method to the second intervention method was catalyzed by such analysis.) Physician behaviors were not analyzed individually. Simple RUC member consensus after committee discussions determined which interventions to implementinformed by the data, the expertise of the chiefs of the clinical services serving on the RUC (who at times also consulted faculty experts within their departments and the literature), and the informatics faculty members of the RUC (who could speak to feasibility of various proposed CPOE-based interventions). In designing the educational components of the interventions, various RUC members (or their expert faculty designees within their departments) often provided literature-based synopses of evidence that were converted to hypertext markup language (HTML) documents and made available through the CPOE system at ordering time. Individuals creating such documents were responsible for regularly reviewing them to keep their content current. The first RUC intervention was implemented on 5 December 1999 as a broad attempt to reduce open-ended test ordering beyond 72 hours in the future. Each morning, the CPOE system would display a pop-up message that listed orders for scheduled laboratory tests, radiography, and electrocardiography extending beyond 72 hours. The pop-up prompted the provider to choose whether to continue the order, discontinue the order, or defer a decision until later in the day. If the provider chose to continue or discontinue the order, no other provider would receive pop-up reminders about that order until possibly the next day. The second RUC intervention involved several specific ordering constraints. The RUC reasoned that most repetitive orders for routine blood tests, radiology, and electrocardiography could not be justified without an intervening bedside visit. They then developed several specific ordering constraints. First, individual orders were limited to 1 occurrence in a fixed period of time. Second, the metabolic panel was unbundled and could be ordered only as individual components. Third, a graphical display of results from the previous week was placed on the ordering page for frequently ordered serum chemistry tests. This display made it difficult to claim that previous results were unknown at the time when additional tests were ordered. On 20 January 2000, the RUC initiated the second intervention by making all portable chest radiography orders one-time only. Starting on 1 February 2000, electrocardiograms could be ordered only once or twice in 8 hours per individual order. Providers still could order more electrocardiograms or portable chest radiographs by entering additional one-time orders with different start dates and times. On 21 March 2000, the RUC also implemented specific ordering constraints for unbundled components of the serum metabolic panel: Sodium, potassium, chloride, bicarbonate, and glucose tests could be ordered once or at recurring intervals up to hourly but not beyond 24 hours; blood urea nitrogen (BUN) or serum creatinine tests could be ordered only once in 24 hours. Orders for a complete blood count were not constrained during this second intervention period so that the complete blood count test could be used as a control for ordering behavior. Statistical Analysis The RUC examined 2 methods of counting test orders: on the basis of the day tests were first ordered or on the basis of the day tests were intended to occur. Because providers frequently enter orders to discontinue tests, the RUC defined net orders as the number of tests not discontinued before their time of occurrence. Some tests could be ordered as panels, so that a metabolic panel contributed 7 tests (sodium, potassium, chloride, bicarbonate, glucose, BUN, and creatinine tests) to the overall count of ordered component tests, whereas a portable chest radiograph or electrocardiogram counted as 1 test each. The data were evaluated by using interrupted time-series analyses. Patient name, individual ordering provider, and attending physician were not identified as part of the analysis. Each order was assessed in 3 ways to account for all possible outcomes. First, we noted the date that the order was written to determine whether constraining the duration of the order resulted in increased daily ordering. Second, we analyzed the daily number of net orders to approximate the number of ordered tests performed each day. Third, we counted the number of tests resulted in our institutional data repository to determine the actual number of tests performed. We ultimately used orders rather than test results as our primary measure because log file review revealed that net orders for a test closely reflected the actual number of tests performed and because tests ordered during system downtime were not subject to the intervention. The primary outcome was the daily number of new tests ordered and discontinued. Every CPOE order for each targeted test was considered. We ev

The future state of clinical data capture and documentation: a report from AMIA's 2011 Policy Meeting

Much of what is currently documented in the electronic health record is in response toincreasingly complex and prescriptive medicolegal, reimbursement, and regulatory requirements. These requirements often result in redundant data capture and cumbersome documentation processes. AMIAs 2011 Health Policy Meeting examined key issues in this arena and envisioned changes to help move toward an ideal future state of clinical data capture and documentation. The consensus of the meeting was that, in the move to a technology-enabled healthcare environment, the main purpose of documentation should be to support patient care and improved outcomes for individuals and populations and that documentation for other purposes should be generated as a byproduct of care delivery. This paper summarizes meeting deliberations, and highlights policy recommendations and research priorities. The authors recommend development of a national strategy to review and amend public policies to better support technology-enabled data capture and documentation practices.

VA national drug file reference terminology: A cross-institutional content coverage study

BACKGROUND Content coverage studies provide valuable information to potential users of terminologies. We detail the VA National Drug File Reference Terminologys (NDF-RT) ability to represent dictated medication list phrases from the Mayo Clinic. NDF-RT is a description logic-based resource created to support clinical operations at one of the largest healthcare providers in the US. METHODS Medication list phrases were extracted from dictated patient notes from the Mayo Clinic. Algorithmic mappings to NDF-RT using the SmartAccess Vocabulary Server (SAVS) were presented to two non-VA physicians. The physicians used a terminology browser to determine the accuracy of the algorithmic mapping and the content coverage of NDF-RT. RESULTS The 509 extracted documents on 300 patients contained 847 medication concepts in medication lists. NDF-RT covered 97.8% of concepts. Of the 18 phrases that NDF-RT did not represent, 10 were for OTCs and food supplements, 5 were for prescription medications, and 3 were missing synonyms. The SAVS engine properly mapped 773 of 810 phrases with an overall sensitivity (precision) was 95.4% and positive predictive value (recall) of 99.9%. CONCLUSIONS This study demonstrates that NDF-RT has more general utility than its initial design parameters dictated

Perceived increase in mortality after process and policy changes implemented with computerized physician order entry.

To the Editor .— Han et al1 describe a retrospective study in which the mortality rate for interfacility transfers into an ICU was compared before and after implementation of a computerized provider order entry (CPOE) system. The authors found that the mortality rate increased from 2.8% (30 deaths of 1394 patient transfers during 13 months) before CPOE implementation to 6.6% (36 deaths of 548 transfers during 5 months) after. The authors conclude that the increased mortality was associated directly with modifications in standard clinical processes, including the following changes: (1) not allowing order communication until the patient was physically present and registered in the admitting system; (2) relocating medication dispensing to a central (rather than a satellite) pharmacy; (3) increasing the physical separation of nursing and physician staff during the time that orders were generated; (4) implementing computerized order entry; and (5) system-wide provider role changes to support the CPOE system. Perhaps the most important lesson from this study is that there exists an intimate association between care-delivery processes and health information technology. Any shift in the methods used to manage patient care (such as implementing and using a CPOE system) is associated with significant changes in clinical workflows, communication among providers, and distribution of responsibilities.2–4 Decades of research in medical informatics have underscored the importance of this observation, a message that was not lost on the authors. In this study, they note that the increased unadjusted mortality may reflect problems with the process of change, including the extremely rapid implementation plan adopted by their organization. The authors describe other major changes in workflow and patient care processes that occurred coincident with the CPOE system implementation. For example, their …

MyHealthAtVanderbilt: policies and procedures governing patient portal functionality.

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.

Experiences mapping a legacy interface terminology to SNOMED CT.

BackgroundSNOMED CT is being increasingly adopted as the standard clinical terminology for health care applications. Existing clinical applications that use legacy interface terminology need to migrate to the preferred SNOMED CT standard. In this paper, we describe our experience and methodology for mapping concepts from a legacy system to SNOMED CT.MethodsOur approach includes the establishment of mapping rules between terminologists and back and forth collaboration of the mapped results through one or more iterations in order to reach consensus on the final maps.ResultsWe highlight our results not only in terms of the number of matches, quality of maps, use of post-coordination, and multiple maps but also include our observations about SNOMED CT including inconsistencies, redundancies and omissions related to our legacy mapping.ConclusionOur methodology and lessons learned from this mapping exercise may be helpful to other terminologists who may be similarly challenged to migrate their legacy terminology to SNOMED CT. This mapping process and resulting discoveries about SNOMED CT may further contribute to refinement of this dynamic, clinical terminology standard.

Implementing Pediatric Growth Charts into an Electronic Health Record System

Electronic health record (EHR) systems are increasingly being adopted in pediatric practices; however, requirements for integrated growth charts are poorly described and are not standardized in current systems. The authors integrated growth chart functionality into an EHR system being developed and installed in a multispecialty pediatric clinic in an academic medical center. During a three-year observation period, rates of electronically documented values for weight, stature, and head circumference increased from fewer than ten total per weekday, up to 488 weight values, 293 stature values, and 74 head circumference values (p<0.001 for each measure). By the end of the observation period, users accessed the growth charts an average 175 times per weekday, compared to 127 patient visits per weekday to the sites that most closely monitored pediatric growth. Because EHR systems and integrated growth charts can manipulate data, perform calculations, and adapt to user preferences and patient characteristics, users may expect greater functionality from electronic growth charts than from paper-based growth charts.