The Imperative for Patient-Centered Clinical Decision Support.

This commentary introduces the Patient-Centered Clinical Decision Support (PCCDS) Learning Network, which is collaborating with AcademyHealth to publish "Better Decisions Together" as part of eGEMs. Patient-centered clinical decision support (CDS) is an important vehicle to address broad issues in the U.S. health care system regarding quality and safety while also achieving better outcomes and better patient and provider satisfaction. Defined as CDS that supports individual patients and their care givers and/or care teams in health-related decisions and actions, PCCDS is an important step forward in advancing endeavors to move patient-centered care forward. The PCCDS Learning Network has developed a framework, referred to as the Analytic Framework for Action (AFA), to organize thinking and activities around PCCDS. A wide array of activities the PCCDS Learning Network is engaging in to inform and connect stakeholders is discussed.

Improving Identification and Diagnosis of Hypertensive Patients Hiding in Plain Sight (HIPS) in Health Centers.

BACKGROUND: Hypertension is the most prevalent chronic condition diagnosed among patients served in the safety net in the United States; however, many safety-net patients with hypertension are not formally diagnosed and may remain untreated and at increased risk for cardiovascular events. Identifying undiagnosed hypertension using algorithmic logic programmed into clinical decision support (CDS) approaches is a promising practice but has not been broadly tested in the safety-net setting. METHODS: The project used a quality improvement approach wherein information flows and actions related to blood pressure measurement were modified to include algorithm criteria to identify patients who might have undiagnosed hypertension. Identified patients were recalled for evaluation and hypertension diagnosis, if appropriate. Ten health centers in Arkansas, California, Kentucky, and Missouri were selected to participate in the project on the basis of high hypertension prevalence (compared to national average), demographic and geographic diversity, mature information systems infrastructure, and executive support. The project targeted patients from 18 to 85 years of age. RESULTS: After implementation of algorithm-based interventions, diagnosed hypertension prevalence increased significantly from 34.5% to 36.7% (p <0.05). A cohort of patients was tracked from 8 of the 10 health centers to assess follow-up evaluation and diagnosis rates; 65.2% completed a follow-up evaluation, of which 31.9% received a hypertension diagnosis. CONCLUSION: Using algorithmic logic and other CDS-enabled care process improvements appears to be an effective way health centers can identify and engage patients at risk for undiagnosed hypertension. Appropriately diagnosing all hypertensive patients ensures that hypertension control efforts yield maximal improvements in population health.

Clinical decision support models and frameworks: Seeking to address research issues underlying implementation successes and failures.

Computer-based clinical decision support (CDS) has been pursued for more than five decades. Despite notable accomplishments and successes, wide adoption and broad use of CDS in clinical practice has not been achieved. Many issues have been identified as being partially responsible for the relatively slow adoption and lack of impact, including deficiencies in leadership, recognition of purpose, understanding of human interaction and workflow implications of CDS, cognitive models of the role of CDS, and proprietary implementations with limited interoperability and sharing. To address limitations, many approaches have been proposed and evaluated, drawing on theoretical frameworks, as well as management, technical and other disciplines and experiences. It seems clear, because of the multiple perspectives involved, that no single model or framework is adequate to encompass these challenges. This Viewpoint paper seeks to review the various foci of CDS and to identify aspects in which theoretical models and frameworks for CDS have been explored or could be explored and where they might be expected to be most useful.

Implementation pearls from a new guidebook on improving medication use and outcomes with clinical decision support. Effective CDS is essential for addressing healthcare performance improvement imperatives.

Effective clinical decision support (CDS) is essential for addressing healthcare performance improvement imperatives, but care delivery organizations (CDO) typically struggle with CDS deployment. Ensuring safe and effective medication delivery to patients is a central focus of CDO performance improvement efforts, and this article provides an overview of best-practice strategies for applying CDS to these goals. The strategies discussed are drawn from a new guidebook, co-published and co-sponsored by more than a dozen leading organizations. Developed by scores of CDS implementers and experts, the guidebook outlines key steps and success factors for applying CDS to medication management. A central thesis is that improving outcomes with CDS interventions requires that the CDS five rights be addressed successfully. That is, the interventions must deliver the right information, to the right person, in the right format, through the right channel, at the right point in workflow. This paper provides further details about these CDS five rights, and highlights other important strategies for successful CDS programs.

Information management to enable personalized medicine: stakeholder roles in building clinical decision support.

BACKGROUND: Advances in technology and the scientific understanding of disease processes are presenting new opportunities to improve health through individualized approaches to patient management referred to as personalized medicine. Future health care strategies that deploy genomic technologies and molecular therapies will bring opportunities to prevent, predict, and pre-empt disease processes but will be dependent on knowledge management capabilities for health care providers that are not currently available. A key cornerstone to the potential application of this knowledge will be effective use of electronic health records. In particular, appropriate clinical use of genomic test results and molecularly-targeted therapies present important challenges in patient management that can be effectively addressed using electronic clinical decision support technologies. DISCUSSION: Approaches to shaping future health information needs for personalized medicine were undertaken by a work group of the American Health Information Community. A needs assessment for clinical decision support in electronic health record systems to support personalized medical practices was conducted to guide health future development activities. Further, a suggested action plan was developed for government, researchers and research institutions, developers of electronic information tools (including clinical guidelines, and quality measures), and standards development organizations to meet the needs for personalized approaches to medical practice. In this article, we focus these activities on stakeholder organizations as an operational framework to help identify and coordinate needs and opportunities for clinical decision support tools to enable personalized medicine. SUMMARY: This perspective addresses conceptual approaches that can be undertaken to develop and apply clinical decision support in electronic health record systems to achieve personalized medical care. In addition, to represent meaningful benefits to personalized decision-making, a comparison of current and future applications of clinical decision support to enable individualized medical treatment plans is presented. If clinical decision support tools are to impact outcomes in a clear and positive manner, their development and deployment must therefore consider the needs of the providers, including specific practice needs, information workflow, and practice environment.

Grand challenges in clinical decision support.

There is a pressing need for high-quality, effective means of designing, developing, presenting, implementing, evaluating, and maintaining all types of clinical decision support capabilities for clinicians, patients and consumers. Using an iterative, consensus-building process we identified a rank-ordered list of the top 10 grand challenges in clinical decision support. This list was created to educate and inspire researchers, developers, funders, and policy-makers. The list of challenges in order of importance that they be solved if patients and organizations are to begin realizing the fullest benefits possible of these systems consists of: improve the human-computer interface; disseminate best practices in CDS design, development, and implementation; summarize patient-level information; prioritize and filter recommendations to the user; create an architecture for sharing executable CDS modules and services; combine recommendations for patients with co-morbidities; prioritize CDS content development and implementation; create internet-accessible clinical decision support repositories; use freetext information to drive clinical decision support; mine large clinical databases to create new CDS. Identification of solutions to these challenges is critical if clinical decision support is to achieve its potential and improve the quality, safety and efficiency of healthcare.

Development, implementation, and a cognitive evaluation of a definitional question answering system for physicians.

The published medical literature and online medical resources are important sources to help physicians make patient treatment decisions. Traditional sources used for information retrieval (e.g., PubMed) often return a list of documents in response to a user's query. Frequently the number of returned documents from large knowledge repositories is large and makes information seeking practical only "after hours" and not in the clinical setting. This study developed novel algorithms, and designed, implemented, and evaluated a medical definitional question answering system (MedQA). MedQA automatically analyzed a large number of electronic documents to generate short and coherent answers in response to definitional questions (i.e., questions with the format of "What is X?"). Our preliminary cognitive evaluation shows that MedQA out-performed three other online information systems (Google, OneLook, and PubMed) in two important efficiency criteria; namely, time spent and number of actions taken for a physician to identify a definition. It is our contention that question answering systems that aggregate pertinent information scattered across different documents have the potential to address clinical information needs within a timeframe necessary to meet the demands of clinicians.

Patient-care questions that physicians are unable to answer.

OBJECTIVE: To describe the characteristics of unanswered clinical questions and propose interventions that could improve the chance of finding answers. DESIGN: In a previous study, investigators observed primary care physicians in their offices and recorded questions that arose during patient care. Questions that were pursued by the physician, but remained unanswered, were grouped into generic types. In the present study, investigators attempted to answer these questions and developed recommendations aimed at improving the success rate of finding answers. MEASUREMENTS: Frequency of unanswered question types and recommendations to increase the chance of finding answers. RESULTS: In an earlier study, 48 physicians asked 1062 questions during 192 half-day office observations. Physicians could not find answers to 237 (41%) of the 585 questions they pursued. The present study grouped the unanswered questions into 19 generic types. Three types accounted for 128 (54%) of the unanswered questions: (1) "Undiagnosed finding" questions asked about the management of abnormal clinical findings, such as symptoms, signs, and test results (What is the approach to finding X?); (2) "Conditional" questions contained qualifying conditions that were appended to otherwise simple questions (What is the management of X, given Y? where "given Y" is the qualifying condition that makes the question difficult.); and (3) "Compound" questions asked about the association between two highly specific elements (Can X cause Y?). The study identified strategies to improve clinical information retrieval, listed below. CONCLUSION: To improve the chance of finding answers, physicians should change their search strategies by rephrasing their questions and searching more clinically oriented resources. Authors of clinical information resources should anticipate questions that may arise in practice, and clinical information systems should provide clearer and more explicit answers.

A roadmap for national action on clinical decision support.

This document comprises an AMIA Board of Directors approved White Paper that presents a roadmap for national action on clinical decision support. It is published in JAMIA for archival and dissemination purposes. The full text of this material has been previously published on the AMIA Web site (www.amia.org/inside/initiatives/cds). AMIA is the copyright holder.

Recommendations for clinical decision support deployment: synthesis of a roundtable of medical directors of information systems.

BACKGROUND: Ample evidence exists that clinical decision support (CDS) can improve clinician performance. Nevertheless, additional evidence demonstrates that clinicians still do not perform adequately in many instances. This suggests an ongoing need for implementation of CDS, in turn prompting development of a roadmap for national action regarding CDS. OBJECTIVE: Develop practical advice to aid CDS implementation in order to improve clinician performance. METHOD: Structured group interview during a roundtable discussion by medical directors of information systems (N = 30), with subsequent review by participants and synthesis. RESULTS: Participant consensus was that CDS should be comprehensive and should involve techniques such as order sets and facilitated documentation as well as alerts; should be subject to ongoing feedback; and should flow from and be governed by an organization's clinical goals. CONCLUSION: A structured roundtable discussion of clinicians experienced in health information technology can yield practical, consensus advice for implementation of CDS.

Approach to leg edema of unclear etiology.

A common challenge for primary care physicians is to determine the cause and find an effective treatment for leg edema of unclear etiology. We were unable to find existing practice guidelines that address this problem in a comprehensive manner. This article provides clinically oriented recommendations for the management of leg edema in adults. We searched on-line resources, textbooks, and MEDLINE (using the MeSH term, "edema") to find clinically relevant articles on leg edema. We then expanded the search by reviewing articles cited in the initial sources. Our goal was to write a brief, focused review that would answer questions about the management of leg edema. We organized the information to make it rapidly accessible to busy clinicians. The most common cause of leg edema in older adults is venous insufficiency. The most common cause in women between menarche and menopause is idiopathic edema, formerly known as "cyclic" edema. A common but under-recognized cause of edema is pulmonary hypertension, which is often associated with sleep apnea. Venous insufficiency is treated with leg elevation, compressive stockings, and sometimes diuretics. The initial treatment of idiopathic edema is spironolactone. Patients who have findings consistent with sleep apnea, such as daytime somnolence, loud [corrected] snoring, or neck circumference >17 inches, should be evaluated for pulmonary hypertension with an echocardiogram. If time is limited, the physician must decide whether the evaluation can be delayed until a later appointment (eg, an asymptomatic patient with chronic bilateral edema) or must be completed at the current visit (eg, a patient with dyspnea or a patient with acute edema [<72 hours]). If the evaluation should be conducted at the current visit, the algorithm shown in Figure 1 could be used as a guide. If the full evaluation could wait for a subsequent visit, the patient should be examined briefly to rule out an obvious systemic cause and basic laboratory tests should be ordered for later review (complete blood count, urinalysis, electrolytes, creatinine, blood sugar, thyroid stimulating hormone, and albumin).

Clinical decision support in electronic prescribing: recommendations and an action plan: report of the joint clinical decision support workgroup.

Clinical decision support (CDS) in electronic prescribing (eRx) systems can improve the safety, quality, efficiency, and cost-effectiveness of care. However, at present, these potential benefits have not been fully realized. In this consensus white paper, we set forth recommendations and action plans in three critical domains: (1) advances in system capabilities, including basic and advanced sets of CDS interventions and knowledge, supporting database elements, operational features to improve usability and measure performance, and management and governance structures; (2) uniform standards, vocabularies, and centralized knowledge structures and services that could reduce rework by vendors and care providers, improve dissemination of well-constructed CDS interventions, promote generally applicable research in CDS methods, and accelerate the movement of new medical knowledge from research to practice; and (3) appropriate financial and legal incentives to promote adoption.

Answering physicians' clinical questions: obstacles and potential solutions.

OBJECTIVE: To identify the most frequent obstacles preventing physicians from answering their patient-care questions and the most requested improvements to clinical information resources. DESIGN: Qualitative analysis of questions asked by 48 randomly selected generalist physicians during ambulatory care. MEASUREMENTS: Frequency of reported obstacles to answering patient-care questions and recommendations from physicians for improving clinical information resources. RESULTS: The physicians asked 1,062 questions but pursued answers to only 585 (55%). The most commonly reported obstacle to the pursuit of an answer was the physician's doubt that an answer existed (52 questions, 11%). Among pursued questions, the most common obstacle was the failure of the selected resource to provide an answer (153 questions, 26%). During audiotaped interviews, physicians made 80 recommendations for improving clinical information resources. For example, they requested comprehensive resources that answer questions likely to occur in practice with emphasis on treatment and bottom-line advice. They asked for help in locating information quickly by using lists, tables, bolded subheadings, and algorithms and by avoiding lengthy, uninterrupted prose. CONCLUSION: Physicians do not seek answers to many of their questions, often suspecting a lack of usable information. When they do seek answers, they often cannot find the information they need. Clinical resource developers could use the recommendations made by practicing physicians to provide resources that are more useful for answering clinical questions.

Obstacles to answering doctors' questions about patient care with evidence: qualitative study.

OBJECTIVE: To describe the obstacles encountered when attempting to answer doctors' questions with evidence. DESIGN: Qualitative study. SETTING: General practices in Iowa. PARTICIPANTS: 9 academic generalist doctors, 14 family doctors, and 2 medical librarians. MAIN OUTCOME MEASURE: A taxonomy of obstacles encountered while searching for evidence based answers to doctors' questions. RESULTS: 59 obstacles were encountered and organised according to the five steps in asking and answering questions: recognise a gap in knowledge, formulate a question, search for relevant information, formulate an answer, and use the answer to direct patient care. Six obstacles were considered particularly salient by the investigators and practising doctors: the excessive time required to find information; difficulty modifying the original question, which was often vague and open to interpretation; difficulty selecting an optimal strategy to search for information; failure of a seemingly appropriate resource to cover the topic; uncertainty about how to know when all the relevant evidence has been found so that the search can stop; and inadequate synthesis of multiple bits of evidence into a clinically useful statement. CONCLUSIONS: Many obstacles are encountered when asking and answering questions about how to care for patients. Addressing these obstacles could lead to better patient care by improving clinically oriented information resources.