Identifying barriers to hypertension guideline adherence using clinician feedback at the point of care.

Factors contributing to low adherence to clinical guidelines by clinicians are not well understood. The user interface of ATHENA-HTN, a guideline-based decision support system (DSS) for hypertension, presents a novel opportunity to collect clinician feedback on recommendations displayed at the point of care. We analyzed feedback from 46 clinicians who received ATHENA advisories as part of a 15-month randomized trial to identify potential reasons clinicians may not intensify hypertension therapy when it is recommended. Among the 368 visits for which feedback was provided, clinicians commonly reported they did not follow recommendations because: recorded blood pressure was not representative of the patient's typical blood pressure; hypertension was not a clinical priority for the visit; or patients were nonadherent to medications. For many visits, current quality-assurance algorithms may incorrectly identify clinically appropriate decisions as guideline nonadherent due to incomplete capture of relevant information. We present recommendations for how automated DSSs may help identify "apparent" barriers and better target decision support.

Offline testing of the ATHENA Hypertension decision support system knowledge base to improve the accuracy of recommendations.

ATHENA-HTN is a clinical decision support system (CDSS) that delivers guideline-based patient-specific recommendations about hypertension management at the time of clinical decision-making. The ATHENA-HTN knowledge is stored in a knowledge-base (KB). Changes in best-practice recommendations require updates to the KB. We describe a method of offline testing to evaluate the accuracy of recommendations generated from the KB. A physician reviewed 100 test cases and made drug recommendations based on guidelines and the "Rules" (descriptions of encoded knowledge). These drug recommendations were compared to those generated by ATHENA-HTN. Nineteen drug-recommendation discrepancies were identified: ATHENA-HTN was more complete in generating recommendations (15); ambiguities in the Rules misled the physician (3); and content in the Rules was not encoded (1). Three new boundaries were identified. Three updates were made to the KB based on the results. The offline testing method was successful in identifying areas for KB improvement and led to improved accuracy of guideline-based recommendations.

Multimedia quality of life assessment: advances with FLAIR.

Assessing impact of functional dependency on quality of life (QOL) among older adults can provide an in-depth understanding of health preferences. Utilities as a measure of preferences are necessary in conducting cost-effectiveness evaluations of healthcare interventions designed to improve overall QOL. We describe further development of a multimedia utility elicitation instrument that is highly portable and easily accessible. An earlier version, FLAIR1, introduced features designed for older adult, computer inexperienced users. FLAIR2 includes modifications such as migration to a web-based platform, consistency checks, audio/visual updates, and more response methods. As compared with FLAIR1, more FLAIR2 respondents (n=318) preferred using the computer and found the computer program to be enjoyable, easy to use, and easily understood. There were also fewer inconsistencies among FLAIR2 respondents. FLAIR2 enhancements have increased portability, minimized invariance and inconsistency, and produced a more user friendly design.

Leveraging point-of-care clinician feedback to study barriers to guideline adherence.

Studies of barriers to guideline adherence have generally surveyed clinicians temporally remote from the clinical scenario in which recommendations were delivered, potentially adversely biasing clinician observations. The user interface of ATHENA DSS, a guideline-based decision support system for hypertension, includes a point-of-care feedback window that accepts clinician-user comments during the display of recommendations. Analysis of this feedback has revealed a number of intriguing patient, provider, and technical barriers to adherence collected during real-time system use.

Evaluating provider adherence in a trial of a guideline-based decision support system for hypertension.

Measurement of provider adherence to a guideline-based decision support system (DSS) presents a number of important challenges. Establishing a causal relationship between the DSS and change in concordance requires consideration of both the primary intention of the guideline and different ways providers attempt to satisfy the guideline. During our work with a guideline-based decision support system for hypertension, ATHENA DSS, we document a number of subtle deviations from the strict hypertension guideline recommendations that ultimately demonstrate provider adherence. We believe that understanding these complexities is crucial to any valid evaluation of provider adherence. We also describe the development of an advisory evaluation engine that automates the interpretation of clinician adherence with the DSS on multiple levels, facilitating the high volume of complex data analysis that is created in a clinical trial of a guideline-based DSS.

The Effects of CPOE on ICU workflow: an observational study.

Computerized physician order entry (CPOE) has had demonstrated benefits in error reduction and guideline adherence, but its implementation has often been complicated by disruptions in established workflow processes. We conducted an observational study of the healthcare team in an intensive care unit after the implementation of mandatory CPOE. We found that policies designed to increase flexibility and safety led to an increased coordination load on the healthcare team, and created opportunities for new sources of error. We attribute this in part to implicit assumptions in the CPOE system design that execution of physician orders is a linear work process. Observational workflow studies are an important tool to understand how to redesign CPOE systems so as to avoid harm and achieve the full potential of benefit for improved patient safety.

Quality of life assessment software for computer-inexperienced older adults: multimedia utility elicitation for activities of daily living.

Functional status as measured by dependencies in the Activities of Daily Living (ADLs) is an important indicator of overall health for older adults. Methodologies for outcomes-based medical-decision-making for public policy, such as decision modeling and cost-effectiveness analysis, require utilities for outcome health states. Utilities have been reported for many disease states, but have not been indexed by functional status, which is a strong predictor of outcome in geriatrics. We describe here a utility elicitation program developed specifically for use with computer-inexperienced older adults: Functional Limitation And Independence Rating (FLAIR1). FLAIR1 design features address common physical problems of the aged and computer attitudes of inexperienced users that could impede computer acceptance. We interviewed 400 adults ages 65 years and older with FLAIR1. In exit interviews with 154 respondents, 118 (76%) found FLAIR1 easy to use. Design features in FLAIR1 can be applied to other software for older adults

Building an explanation function for a hypertension decision-support system.

ATHENA DSS is a decision-support system that provides recommendations for managing hypertension in primary care. ATHENA DSS is built on a component-based architecture called EON. User acceptance of a system like this one depends partly on how well the system explains its reasoning and justifies its conclusions. We addressed this issue by adapting WOZ, a declarative explanation framework, to build an explanation function for ATHENA DSS. ATHENA DSS is built based on a component-based architecture called EON. The explanation function obtains its information by tapping into EON's components, as well as into other relevant sources such as the guideline document and medical literature. It uses an argument model to identify the pieces of information that constitute an explanation, and employs a set of visual clients to display that explanation. By incorporating varied information sources, by mirroring naturally occurring medical arguments and by utilizing graphic visualizations, ATHENA DSS's explanation function generates rich, evidence-based explanations.

What should be reported in a methods section on utility assessment?

BACKGROUND: The measurement of utilities, or preferences, for health states may be affected by the technique used. Unfortunately, in papers reporting utilities, it is often difficult to infer how the utility measurement was carried out. PURPOSE: To present a list of components that, when described, provide sufficient detail of the utility assessment. METHODS: An initial list was prepared by one of the authors. A panel of 8 experts was formed to add additional components. The components were drawn from 6 clusters that focus on the design of the study, the administration procedure, the health state descriptions, the description of the utility assessment method, the description of the indifference procedure, and the use of visual aids or software programs. The list was updated and redistributed among a total of 14 experts, and the components were judged for their importance of being mentioned in a Methods section. RESULTS: More than 40 components were generated. Ten components were identified as necessary to include even in an article not focusing on utility measurement: how utility questions were administered, how health states were described, which utility assessment method(s) was used, the response and completion rates, specification of the duration of the health states, which software program (if any) was used, the description of the worst health state (lower anchor of the scale), whether a matching or choice indifference search procedure was used, when the assessment was conducted relative to treatment, and which (if any) visual aids were used. The interjudge reliability was satisfactory (Cronbach's alpha = 0.85). DISCUSSION: The list of components important for utility papers may be used in various ways, for instance, as a checklist while writing, reviewing, or reading a Methods section or while designing experiments. Guidelines are provided for a few components.

Patient safety in guideline-based decision support for hypertension management: ATHENA DSS.

The Institute of Medicine recently issued a landmark report on medical error.1 In the penumbra of this report, every aspect of health care is subject to new scrutiny regarding patient safety. Informatics technology can support patient safety by correcting problems inherent in older technology; however, new information technology can also contribute to new sources of error. We report here a categorization of possible errors that may arise in deploying a system designed to give guideline-based advice on prescribing drugs, an approach to anticipating these errors in an automated guideline system, and design features to minimize errors and thereby maximize patient safety. Our guideline implementation system, based on the EON architecture, provides a framework for a knowledge base that is sufficiently comprehensive to incorporate safety information, and that is easily reviewed and updated by clinician-experts.

Integration of textual guideline documents with formal guideline knowledge bases.

Numerous approaches have been proposed to integrate the text of guideline documents with guideline-based care systems. Current approaches range from serving marked up guideline text documents to generating advisories using complex guideline knowledge bases. These approaches have integration problems mainly because they tend to rigidly link the knowledge base with text. We are developing a bridge approach that uses an information retrieval technology. The new approach facilitates a versatile decision-support system by using flexible links between the formal structures of the knowledge base and the natural language style of the guideline text.

Implementing clinical practice guidelines while taking account of changing evidence: ATHENA DSS, an easily modifiable decision-support system for managing hypertension in primary care.

This paper describes the ATHENA Decision Support System (DSS), which operationalizes guidelines for hypertension using the EON architecture. ATHENA DSS encourages blood pressure control and recommends guideline-concordant choice of drug therapy in relation to comorbid diseases. ATHENA DSS has an easily modifiable knowledge base that specifies eligibility criteria, risk stratification, blood pressure targets, relevant comorbid diseases, guideline-recommended drug classes for patients with comorbid disease, preferred drugs within each drug class, and clinical messages. Because evidence for best management of hypertension evolves continually, ATHENA DSS is designed to allow clinical experts to customize the knowledge base to incorporate new evidence or to reflect local interpretations of guideline ambiguities. Together with its database mediator Athenaeum, ATHENA DSS has physical and logical data independence from the legacy Computerized Patient Record System (CPRS) supplying the patient data, so it can be integrated into a variety of electronic medical record systems.

Ethical decision making and patient autonomy: a comparison of physicians and patients in Japan and the United States.

BACKGROUND: Patient-centered decision making, which in the United States is typically considered to be appropriate, may not be universally endorsed, thereby harboring the potential to complicate the care of patients from other cultural backgrounds in potentially unrecognized ways. This study compares the attitudes toward ethical decision making and autonomy issues among academic and community physicians and patients of medical center outpatient clinics in Japan and the United States. METHODS: A questionnaire requesting judgments about seven clinical vignettes was distributed (in English or Japanese) to sample groups of Japanese physicians (n = 400) and patients (n = 65) as well as US physicians (n = 120) and patients (n = 60) that were selected randomly from academic institutions and community settings in Japan (Tokyo and the surrounding area) and the United States (the Stanford/Palo Alto, CA, area). Responses were obtained from 273 Japanese physicians (68%), 58 Japanese patients (89%), 98 US physicians (82%), and 55 US patients (92%). Physician and patient sample groups were compared on individual items, and composite scores were derived from subsets of items relevant to patient autonomy, family authority, and physician authority. RESULTS: A majority of both US physicians and patients, but only a minority of Japanese physicians and patients, agreed that a patient should be informed of an incurable cancer diagnosis before their family is informed and that a terminally ill patient wishing to die immediately should not be ventilated, even if both the doctor and the patient's family want the patient ventilated (Japanese physicians and patients vs US physicians and patients, p < 0.001). A majority of respondents in both Japanese sample groups, but only a minority in both US sample groups, agreed that a patient's family should be informed of an incurable cancer diagnosis before the patient is informed and that the family of an HIV-positive patient should be informed of this disease status despite the patient's opposition to such disclosure (Japanese physicians and patients vs US physicians and patients, p < 0.001). Physicians in both Japan and the United States were less likely than patients in their respective countries to agree with physician assistance in the suicide of a terminally ill patient (Japanese physicians and patients vs US physicians and patients, p < 0.05). Across various clinical scenarios, all four respondent groups accorded greatest authority to the patient, less to the family, and still less to the physician when the views of these persons conflicted. Japanese physicians and patients, however, relied more on family and physician authority and placed less emphasis on patient autonomy than the US physicians and patients sampled. Younger respondents placed less emphasis on family and physician authority. CONCLUSIONS: Family and physician opinions are accorded a larger role in clinical decision making by the Japanese physicians and patients sampled than by those in the United States, although both cultures place a greater emphasis on patient preferences than on the preferences of the family or physician. Our results are consistent with the view that cultural context shapes the relationship of the patient, the physician, and the patient's family in medical decision making. The results emphasize the need for clinicians to be aware of these issues that may affect patient and family responses in different clinical situations, potentially affecting patient satisfaction and compliance with therapy.

Why can't we do better breast examinations?

The professional practice of clinical breast examination (CBE) is a crucial element in early detection of neoplasms, but it is often compromised by insufficient formal training and conflicting demands on professional time. From an extensive research base, a training technology has been developed which generates highly proficient CBE. This technology is being adopted by agencies concerned with improved screening for breast cancer. New strategies for enhancing the role of CBE in breast cancer detection might include training and licensing personnel whose primary function would be to perform highly proficient CBE under professional supervision.

Integrating a modern knowledge-based system architecture with a legacy VA database: the ATHENA and EON projects at Stanford.

We present a methodology and database mediator tool for integrating modern knowledge-based systems, such as the Stanford EON architecture for automated guideline-based decision-support, with legacy databases, such as the Veterans Health Information Systems & Technology Architecture (VISTA) systems, which are used nation-wide. Specifically, we discuss designs for database integration in ATHENA, a system for hypertension care based on EON, at the VA Palo Alto Health Care System. We describe a new database mediator that affords the EON system both physical and logical data independence from the legacy VA database. We found that to achieve our design goals, the mediator requires two separate mapping levels and must itself involve a knowledge-based component.

Decision analysis and Alzheimer disease: three case studies.

Decision analysis may be useful to people facing Alzheimer disease (AD) decisions. The use of decision analysis in three such cases is reported. The first case involved a middle-aged person worried about early-onset AD and deciding whether to seek genetic testing. The analysis let the participant reject testing and consider innovative care options. The second case involved a middle-aged person concerned about later-onset AD. The analysis for her was more complex, and led to the assignment of some limited value on genetic testing for her. The third case revolved around a caregiver's treatment decisions for a patient with severe AD. It led her to recognize the importance of factors she had not previously considered. In each of the three cases, the intensive process of decision analysis appears to have improved the subject's decision.

The application of medical decision analysis to genetic testing: an introduction.

The availability of genetic tests to diagnose or predict Alzheimer disease (AD) causes a shift in the way people think about the condition and how they assess the options available to them. Decision analysis in a quantitative approach for dealing with the uncertainties inherent in many medical decisions, including decisions about genetic testing. Decision analysis does not guarantee a good outcome, but aims to yield better overall average results by providing a framework for people to evaluate their options and minimize cognitive biases. We provide an overview of the decision analysis process, including the terms and tools commonly associated with it. We also use a recent example to demonstrate one way decision analysis has been applied to genetics in the medical literature. This paper is an introduction to subsequent papers that explore the specific question of whether decision analysis is a helpful tool for understanding the uncertainty inherent in probabilistic information about genetic risk for AD.

Postoperative complications in Parkinson's disease.

BACKGROUND: Although Parkinson's disease is relatively common in America, with an average annual incidence of 20 cases per 100,000 population, little information exists about postoperative morbidity and mortality in those Parkinson's patients who undergo elective surgery. METHODS: We performed a retrospective cohort study using the Veterans Affairs (VA) Austin database system (a cumulative index of admissions and discharges from all US VA Medical Centers) to identify 41,213 patients who underwent elective bowel resection, cholecystectomy, or radical prostatectomy between January 1, 1990, and December 31, 1995. We examined the study population using univariate analysis, acute length of stay with multivariate analysis, and postoperative complications with logistic regression. RESULTS: The selected surgeries were performed on 234 patients with a diagnosis of Parkinson's disease and 40,979 with no such diagnosis. In univariate analysis, patients with Parkinson's disease had significantly longer acute hospital stays than non-Parkinson's patients (11.4 +/- 15.9 days vs 8.8 +/- 9.0 days, P < .001). In addition, Parkinson's patients had a higher in-hospital mortality than non-Parkinson's patients (7.3% vs 3.8%, P = .006). After we adjusted for coexisting morbidity, age, admitting location, and gender, patients with Parkinson's disease had an average acute hospital stay 2.34 days longer than that of non-Parkinson's patients (P < .001). However, the mortality difference did not reach statistical significance in multivariate analysis (P = .098). Finally, Parkinson's patients had significantly increased incidences of urinary-tract infection (odds ratio 2.045, P < .001), aspiration pneumonia (odds ratio 3.825, P < .001), and bacterial infections (odds ratio 1.682, P < .001). CONCLUSIONS: Patients with Parkinson's disease are at greater risk for specific complications and longer hospital stay after elective bowel resection, cholecystectomy, or radical prostatectomy. Awareness of these complications may help caregivers to reduce postoperative mortality and morbidity and to decrease the length of hospitalization.