Abstract

Background: A contextual error occurs when failure to consider a patient’s life situation and behavior results in a care plan that while evidence-based, is nevertheless unlikely to achieve its intended aims. For instance, increasing the dosage of insulin to address an elevated Hgb A1c when a patient’s underlying challenge is deteriorating vision limiting their ability to read their syringe would constitute a contextual error. Prescribing such a patient prefilled syringes would constitute a contextualized care plan. Over nearly 20 years, our research team has documented many such errors, demonstrating that they are common and adversely impact health care outcomes. In a recent non-VA study, we developed clinical decision support (CDS) tools for the Oracle Cerner electronic health record (EHR) system, that reduce contextual error rates. [The purpose of this study is to import them into the VHA Oracle Cerner system and rigorously test them in a simulation study and collect preliminary data on facilitators and barriers to implementation.] Significance: The VHA Electronic Health Record Modernization is at a critical phase in its implementation. There is a consensus that VHA is overdue for modernization; however, the unique environment of VHA has proven challenging. Hence there is a critical need for research on Cerner in VHA. The VHA Office of Health Informatics is supporting this study because the CDS tools we propose to test are grounded in research on contextualization of care within VHA, and a recent non-VA study showing evidence of effectiveness. Innovation & Impact: To date CDS systems have been primarily clinical, and not sensitive to variations in patient life context. We have demonstrated that incorporating contextual information into the CDS knowledge base helps clinicians prevent contextual errors. This study will employ standardized patients portraying scenarios in which contextual factors are essential to decision making, randomized to clinicians with vs without contextualized CDS tools built in a non-production domain of the Cerner EHR that is a replica of the production domain. This novel experimental design will isolate the effect of contextualized CDS on clinical decision making to determine whether it prevents contextual errors in Veterans’ care. Specific Aims: 1. H1: Clinicians are more likely to adapt care to contextual factors with compared to without contextualized CDS support. 2. H2: Clinicians are less likely to order unnecessary or inappropriate clinical studies or treatment interventions with compared to without contextualized CDS support, with a concomitant reduction in costs. [3. Implementation: Employ a CDS user experience survey instrument and Consolidated Framework for Implementation Research (CFIR) guided semi-structured interviews with clinicians to assess feasibility and acceptability, and to identify barrier and facilitators to the introduction of novel EHR tools that alert them to contextual factors and pre-write orders for interventions, in the new VA Cerner work environment.] Methodology: First, the contextualized CDS tools will be built into a non-production environment of the VHA Cerner/Oracle system using Discern, the Cerner CDS programming language. Then, standardized patients portraying four scripts will visit 16 clinicians in person and 16 via telehealth. The scripts will be organized into four counterbalanced sets in which two scripts are presented with CDS active and two without CDS active, and block randomized. [Participating clinician subjects who use Oracle Cerner EHR will also provide feedback on user experience to inform implementation both through semi-structured interviews and through completion of the Questionnaire for User Interaction Satisfaction (QUIS).] Next Steps/Implementation: The VHA Office of Health Informatics, a close partner in this study, will decide whether to implement the CDS technology in the live EHR environment based on the findings.

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DRA: Health Systems Science

DRE: TRL - Applied/Translational, Data Science

Keywords: None at this time.

MeSH Terms: None at this time.