Dario A. Giuse

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

Integrating pointer variables into one-way constraint models

Pointer variables have long been considered useful for constructing and manipulating data structures in traditional programming languages. This article discusses how pointer variables can be integrated into one-way constraint models and indicates how these constraints can be usefully employed in user interfaces. Pointer variables allow constraints to model a wide array of dynamic application behavior, simplify the implementation of structured objects and demonstrational systems, and improve the storage and efficiency of constraint-based applications. This article presents two incremental algorithms—one lazy and one eager— for solving constraints with pointer variables. Both algorithms are capable of handling (1) arbitrary systems of one-way constraints, including constraints that involve cycles, and (2) editing models that allow multiple changes between calls to the constraint solver. These algorithms are fault tolerant in that they can handle and recover gracefully from formulas that crash due to programmer error. Constraints that use pointer variables have been implemented in a comprehensive user interface toolkit, Garnet, and our experience with applications written in Garnet have proven the usefulness of pointer variable constraints. Many large-scale applications have been implemented using these constraints.

The importance of pointer variables in constraint models

Graphical tools are increasingly using constraints to specify the graphical layout and behavior of many parts of an application. However, conventional constraints directly encode the objects they reference, and thus cannot provide support for the dynamic rttntime creation and manipulation of application objects. This paper discusses an extension to current constraint models that allows constraints to indirectly reference objects through pointer variables. Pointer variables permit programmers to create the constraint equivalent of procedures in traditional programming languages. This procedural abstraction allows constraints to model a wide array of dynamic application behavior, simplifies the implementation of structured object and demonstrational systems, and improves the storage and efficiency of highly interactive, graphical applications. It also promotes a simpler, more effective style of programming than conventional constraints. Constraints that use pointer variables are powerful enough to allow a comprehensive user interface toolkit to be built for the first time on top of a constraint system.

Lessons learned about one-way, dataflow constraints in the Garnet and Amulet graphical toolkits

One-way, dataflow constraints are commonly used in graphical interface toolkits, programming environments, and circuit applications. Previous papers on dataflow constraints have focused on the design and implementation of individual algorithms. In contrast, this article focuses on the lessons we have learned from a decade of implementing competing algorithms in the Garnet and Amulet graphical interface toolkits. These lessons reveal the design and implementation tradeoffs for different one-way, constraint satisfaction algorithms. The most important lessons we have learned are that (1) mark-sweep algorithms are more efficient than topological ordering algorithms; (2) lazy and eager evaluators deliver roughly comparable performance for most applications; and (3) constraint satisfaction algorithms have more than adequate speed, except that the storage required by these algorithms can be problematic.

Towards computer-assisted maintenance of medical knowledge bases

Abstract The problem of knowledge acquisition is especially severe for medical knowledge bases. At least two strategies can help alleviate the problem: creating computer-based tools which assist experts in entering knowledge into the knowledge base, and promoting situations where several organizations contribute simultaneously and independently to a single knowledge base. This article describes a set of tools currently under development at the Section of Medical Informatics of the University of Pittsburgh which incorporate both strategies. The tools, which operate within the framework of the Quick Medical Reference (QMR) knowledge base, perform tasks ranging from checking syntax and semantics to suggesting initial skeletons for new knowledge base entries. Extensive use of interactive direct-manipulation techniques and built-in knowledge of many details of the knowledge base makes these tools very effective in supporting the creation and maintenance of new knowledge base entries.

Expanding the Scope of Health Information Systems - From Hospitals to Regional Networks, to National Infrastructures, and Beyond

OBJECTIVES To identify current developments, obstacles, and opportunities for health information systems. METHODS International reports were discussed during an IMIA HIS Working Conference with a focus on architectural design, project goals and drivers, obstacles, and opportunities. RESULTS Technology and standards are available to build regional and national health IT networks, and successful implementations are currently being realized. There is, however, little consensus and communication concerning goals, benefits and risks of large-scale health IT initiatives. Complexity tends to be under-estimated, and the public needs to be more involved in the decision-making process. CONCLUSION On all levels and across borders, a climate of exchange of ideas, experiences - both successes and failures-, policies, standards, systems, and information should be created.

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.

Generating Clinical Notes for Electronic Health Record Systems

Clinical notes summarize interactions that occur between patients and healthcare providers. With adoption of electronic health record (EHR) and computer-based documentation (CBD) systems, there is a growing emphasis on structuring clinical notes to support reusing data for subsequent tasks. However, clinical documentation remains one of the most challenging areas for EHR system development and adoption. The current manuscript describes the Vanderbilt experience with implementing clinical documentation with an EHR system. Based on their experience rolling out an EHR system that supports multiple methods for clinical documentation, the authors recommend that documentation method selection be made on the basis of clinical workflow, note content standards and usability considerations, rather than on a theoretical need for structured data.

Information Needs of Health Care Professionals in an Aids Outpatient Clinic as Determined by Chart Review

OBJECTIVE To examine the information needs of health care professionals in HIV-related clinical encounters, and to determine the suitability of existing information sources to address those needs. SETTING HIV outpatient clinic. PARTICIPANTS Seven health care professionals with diverse training and patient care involvement. METHODS Based on patient charts describing 120 patient encounters, participants generated 266 clinical questions. Printed and on-line information sources were used to answer questions in two phases: using commonly available sources and using all available medical library sources. MEASUREMENTS The questions were divided into 16 categories by subject. The number of questions answered, their categories, the information source(s) providing answers, and the time required to answer questions were recorded for each phase. RESULTS Each participant generated an average of 3.8 clinical questions per chart. Five categories accounted for almost 75% of all questions; the treatment protocols/regimens category was most frequent (24%). A total of 245 questions (92%) were answered, requiring an average of 15 minutes per question. Most (87%) of the questions were answered via electronic sources, even though paper sources were consulted first. CONCLUSIONS The participating professionals showed considerable information needs. A combination of on-line and paper sources was necessary to provide the answers. The study suggests that present-day information sources are not entirely satisfactory for answering clinical questions generated by examining charts of HIV-infected patients.

The Heidelberg Conference: Setting an agenda for the IMIA working group on Health Information Systems

In April 2002, the International Medical Informatics Association (IMIA) Working Group on Health Information Systems (HIS) held its fourth working conference in Heidelberg, Germany. After a predecessor conference in Capetown 1979, this Working Group was officially founded as IMIA WG 10, Hospital Information Systems, in 1983 [1]. It was amalgamated with the IMIA Working Group on Health Professional Workstations in 1996. In 2001, the WG changed its name to ‘‘Health Information Systems’’. We will refer to it as HIS Working Group in the following. During Medinfo 2001 in London, the Scientific Program Committee for the 2002 Working Conference met. M.J. Ball, A.R. Bakker, P. Degoulet, D.A. Giuse, and K.A. Kuhn chose five tracks to be elaborated and discussed in Heidelberg.