Adam Wright

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.

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.

Cardiac-Myocyte-Specific Excision of the Vinculin Gene Disrupts Cellular Junctions, Causing Sudden Death or Dilated Cardiomyopathy

ABSTRACT Vinculin is a ubiquitously expressed multiliganded protein that links the actin cytoskeleton to the cell membrane. In myocytes, it is localized in protein complexes which anchor the contractile apparatus to the sarcolemma. Its function in the myocardium remains poorly understood. Therefore, we developed a mouse model with cardiac-myocyte-specific inactivation of the vinculin (Vcl) gene by using Cre-loxP technology. Sudden death was found in 49% of the knockout (cVclKO) mice younger than 3 months of age despite preservation of contractile function. Conscious telemetry documented ventricular tachycardia as the cause of sudden death, while defective myocardial conduction was detected by optical mapping. cVclKO mice that survived through the vulnerable period of sudden death developed dilated cardiomyopathy and died before 6 months of age. Prior to the onset of cardiac dysfunction, ultrastructural analysis of cVclKO heart tissue showed abnormal adherens junctions with dissolution of the intercalated disc structure, expression of the junctional proteins cadherin and β1D integrin were reduced, and the gap junction protein connexin 43 was mislocalized to the lateral myocyte border. This is the first report of tissue-specific inactivation of the Vcl gene and shows that it is required for preservation of normal cell-cell and cell-matrix adhesive structures.

Relationship between use of electronic health record features and health care quality: results of a statewide survey.

Background:Electronic health records (EHRs) are widely viewed as useful tools for supporting the provision of high quality healthcare. However, evidence regarding their effectiveness for this purpose is mixed, and existing studies have generally considered EHR usage a binary factor and have not considered the availability and use of specific EHR features. Objective:To assess the relationship between the use of an EHR and the use of specific EHR features with quality of care. Research Design:A statewide mail survey of physicians in Massachusetts conducted in 2005. The results of the survey were linked with Healthcare Effectiveness Data and Information Set (HEDIS) quality measures, and generalized linear regression models were estimated to examine the associations between the use of EHRs and specific EHR features with quality measures, adjusting for physician practice characteristics. Subjects:A stratified random sample of 1884 licensed physicians in Massachusetts, 1345 of whom responded. Of these, 507 had HEDIS measures available and were included in the analysis (measures are only available for primary care providers). Measure:Performance on HEDIS quality measures. Results:The survey had a response rate of 71%. There was no statistically significant association between use of an EHR as a binary factor and performance on any of the HEDIS measure groups. However, there were statistically significant associations between the use of many, but not all, specific EHR features and HEDIS measure group scores. The associations were strongest for the problem list, visit note and radiology test result EHR features and for quality measures relating to womens health, colon cancer screening, and cancer prevention. For example, users of problem list functionality performed better on womens health, depression, colon cancer screening, and cancer prevention measures, with problem list users outperforming nonusers by 3.3% to 9.6% points on HEDIS measure group scores (all significant at the P < 0.05 level). However, these associations were not universal. Conclusions:Consistent with past studies, there was no significant relationship between use of EHR as a binary factor and performance on quality measures. However, availability and use of specific EHR features by primary care physicians was associated with higher performance on certain quality measures. These results suggest that, to maximize health care quality, developers, implementers and certifiers of EHRs should focus on increasing the adoption of robust EHR systems and increasing the use of specific features rather than simply aiming to deploy an EHR regardless of functionality.

Clinical Decision Support Capabilities of Commercially-available Clinical Information Systems

BACKGROUND The most effective decision support systems are integrated with clinical information systems, such as inpatient and outpatient electronic health records (EHRs) and computerized provider order entry (CPOE) systems. Purpose The goal of this project was to describe and quantify the results of a study of decision support capabilities in Certification Commission for Health Information Technology (CCHIT) certified electronic health record systems. METHODS The authors conducted a series of interviews with representatives of nine commercially available clinical information systems, evaluating their capabilities against 42 different clinical decision support features. RESULTS Six of the nine reviewed systems offered all the applicable event-driven, action-oriented, real-time clinical decision support triggers required for initiating clinical decision support interventions. Five of the nine systems could access all the patient-specific data items identified as necessary. Six of the nine systems supported all the intervention types identified as necessary to allow clinical information systems to tailor their interventions based on the severity of the clinical situation and the users workflow. Only one system supported all the offered choices identified as key to allowing physicians to take action directly from within the alert. Discussion The principal finding relates to system-by-system variability. The best system in our analysis had only a single missing feature (from 42 total) while the worst had eighteen.This dramatic variability in CDS capability among commercially available systems was unexpected and is a cause for concern. CONCLUSIONS These findings have implications for four distinct constituencies: purchasers of clinical information systems, developers of clinical decision support, vendors of clinical information systems and certification bodies.

Creating and sharing clinical decision support content with Web 2.0

Clinical decision support is a powerful tool for improving healthcare quality and patient safety. However, developing a comprehensive package of decision support interventions is costly and difficult. If used well, Web 2.0 methods may make it easier and less costly to develop decision support. Web 2.0 is characterized by online communities, open sharing, interactivity and collaboration. Although most previous attempts at sharing clinical decision support content have worked outside of the Web 2.0 framework, several initiatives are beginning to use Web 2.0 to share and collaborate on decision support content. We present case studies of three efforts: the Clinfowiki, a world-accessible wiki for developing decision support content; Partners Healthcare eRooms, web-based tools for developing decision support within a single organization; and Epic Systems Corporations Community Library, a repository for sharing decision support content for customers of a single clinical system vendor. We evaluate the potential of Web 2.0 technologies to enable collaborative development and sharing of clinical decision support systems through the lens of three case studies; analyzing technical, legal and organizational issues for developers, consumers and organizers of clinical decision support content in Web 2.0. We believe the case for Web 2.0 as a tool for collaborating on clinical decision support content appears strong, particularly for collaborative content development within an organization.

Coxsackievirus and adenovirus receptor (CAR) mediates atrioventricular-node function and connexin 45 localization in the murine heart

The coxsackievirus and adenovirus receptor (CAR) is a transmembrane protein that belongs to the family of adhesion molecules. In the postnatal heart, it is localized predominantly at the intercalated disc, where its function is not known. Here, we demonstrate that a first degree or complete block of atrioventricular (AV) conduction developed in the absence of CAR in the adult mouse heart and that prolongation of AV conduction occurred in the embryonic heart of the global CAR-KO mouse. In the cardiac-specific CAR-KO (CAR-cKO) mouse, we observed the loss of connexin 45 localization to the cell-cell junctions of the AV node but preservation of connexin 40 and 43 in contracting myocardial cells and connexin 30.2 in the AV node. There was also a marked decrease in beta-catenin and zonula occludens-1 (ZO-1) localization to the intercalated discs of CAR-cKO mouse hearts at 8 weeks before the mice developed cardiomyopathy at 21 weeks of age. We also found that CAR formed a complex with connexin 45 via its PSD-95/DigA/ZO-1-binding (PDZ-binding) motifs. We conclude that CAR expression is required for normal AV-node conduction and cardiac function. Furthermore, localization of connexin 45 at the AV-node cell-cell junction and of beta-catenin and ZO-1 at the ventricular intercalated disc are dependent on CAR.

A four-phase model of the evolution of clinical decision support architectures

BACKGROUND A large body of evidence over many years suggests that clinical decision support systems can be helpful in improving both clinical outcomes and adherence to evidence-based guidelines. However, to this day, clinical decision support systems are not widely used outside of a small number of sites. One reason why decision support systems are not widely used is the relative difficulty of integrating such systems into clinical workflows and computer systems. PURPOSE To review and synthesize the history of clinical decision support systems, and to propose a model of various architectures for integrating clinical decision support systems with clinical systems. METHODS The authors conducted an extensive review of the clinical decision support literature since 1959, sequenced the systems and developed a model. RESULTS The model developed consists of four phases: standalone decision support systems, decision support integrated into clinical systems, standards for sharing clinical decision support content and service models for decision support. These four phases have not heretofore been identified, but they track remarkably well with the chronological history of clinical decision support, and show evolving and increasingly sophisticated attempts to ease integrating decision support systems into clinical workflows and other clinical systems. CONCLUSIONS Each of the four evolutionary approaches to decision support architecture has unique advantages and disadvantages. A key lesson was that there were common limitations that almost all the approaches faced, and no single approach has been able to entirely surmount: (1) fixed knowledge representation systems inherently circumscribe the type of knowledge that can be represented in them, (2) there are serious terminological issues, (3) patient data may be spread across several sources with no single source having a complete view of the patient, and (4) major difficulties exist in transferring successful interventions from one site to another.

The state of the art in clinical knowledge management: An inventory of tools and techniques

PURPOSE To explore the need for, and use of, high-quality, collaborative, clinical knowledge management (CKM) tools and techniques to manage clinical decision support (CDS) content. METHODS In order to better understand the current state of the art in CKM, we developed a survey of potential CKM tools and techniques. We conducted an exploratory study by querying a convenience sample of respondents about their use of specific practices in CKM. RESULTS The following tools and techniques should be priorities in organizations interested in developing successful computer-based provider order entry (CPOE) and CDS implementations: (1) a multidisciplinary team responsible for creating and maintaining the clinical content; (2) an external organizational repository of clinical content with web-based viewer that allows anyone in the organization to review it; (3) an online, collaborative, interactive, Internet-based tool to facilitate content development; (4) an enterprise-wide tool to maintain the controlled clinical terminology concepts. Even organizations that have been successfully using computer-based provider order entry with advanced clinical decision support features for well over 15 years are not using all of the CKM tools or practices that we identified. CONCLUSIONS If we are to further stimulate progress in the area of clinical decision support, we must continue to develop and refine our understanding and use of advanced CKM capabilities.

Early Results of the Meaningful Use Program for Electronic Health Records

The HITECH Act created incentives to encourage adoption of electronic health records. As of May 2012, only 12.2% of 62,226 eligible professionals had attested to meaningful use, including 9.8% of specialists and 17.8% of primary care providers.