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Barriers and Facilitators to Implementation of Medication Decision Support Systems in Electronic Medical Records: Mixed Methods Approach Based on Structural Equation Modeling and Qualitative Analysis.

ABSTRACT: BACKGROUND:Adverse drug events (ADEs) resulting from medication error are some of the most common causes of iatrogenic injuries in hospitals. With the appropriate use of medication, ADEs can be prevented and ameliorated. Efforts to reduce medication errors and prevent ADEs have been made by implementing a medication decision support system (MDSS) in electronic health records (EHRs). However, physicians tend to override most MDSS alerts. OBJECTIVE:In order to improve MDSS functionality, we must understand what factors users consider essential for the successful implementation of an MDSS into their clinical setting. This study followed the implementation process for an MDSS within a comprehensive EHR system and analyzed the relevant barriers and facilitators. METHODS:A mixed research methodology was adopted. Data from a structured survey and 15 in-depth interviews were integrated. Structural equation modeling was conducted for quantitative analysis of factors related to user adoption of MDSS. Qualitative analysis based on semistructured interviews with physicians was conducted to collect various opinions on MDSS implementation. RESULTS:Quantitative analysis revealed that physicians' expectations regarding ease of use and performance improvement are crucial. Qualitative analysis identified four significant barriers to MDSS implementation: alert fatigue, lack of accuracy, poor user interface design, and lack of customizability. CONCLUSIONS:This study revealed barriers and facilitators to the implementation of MDSS. The findings can be applied to upgrade MDSS in the future.

SUBMITTER: Jung SY

PROVIDER: S-EPMC7407246 | biostudies-literature | 2020 Jul

REPOSITORIES: biostudies-literature

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Barriers and Facilitators to Implementation of Medication Decision Support Systems in Electronic Medical Records: Mixed Methods Approach Based on Structural Equation Modeling and Qualitative Analysis.

Jung Se Young SY Hwang Hee H Lee Keehyuck K Lee Ho-Young HY Kim Eunhye E Kim Miyoung M Cho In Young IY

JMIR medical informatics 20200722 7

<h4>Background</h4>Adverse drug events (ADEs) resulting from medication error are some of the most common causes of iatrogenic injuries in hospitals. With the appropriate use of medication, ADEs can be prevented and ameliorated. Efforts to reduce medication errors and prevent ADEs have been made by implementing a medication decision support system (MDSS) in electronic health records (EHRs). However, physicians tend to override most MDSS alerts.<h4>Objective</h4>In order to improve MDSS functiona ...[more]

PMID: 32706717

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Project description:BackgroundDespite the rapid adoption of electronic health records (EHRs) resulting from the reimbursement program of the US government, EHR adoption in behavioral hospitals is still slow, and there remains a lack of evidence regarding barriers and facilitators to the implementation of mental health care EHRs.ObjectiveThe aim of this study is to analyze the experience of mental health professionals to explore the perceived barriers, facilitators, and critical ideas influencing the implementation and usability of a mental health care EHR.MethodsIn this phenomenological qualitative study, we interviewed physicians, nurses, pharmacists, mental health clinicians, and administrative professionals separately at 4 behavioral hospitals in the United States. We conducted semistructured interviews (N=43) from behavioral hospitals involved in the adoption of the mental health care EHR. Purposeful sampling was used to maximize the diversity. Transcripts were coded and analyzed for emergent domains. An exploratory data analysis was conducted.ResultsContent analyses revealed 7 barriers and 4 facilitators. The most important barriers to implementing the mental health care EHR were the low levels of computer proficiency among nurses, complexity of the system, alert fatigue, and resistance because of legacy systems. This led to poor usability, low acceptability, and distrust toward the system. The major facilitators to implementing the mental health care EHR were well-executed training programs, improved productivity, better quality of care, and the good usability of the mental health care EHR.ConclusionsHealth care professionals expected to enhance their work productivity and interprofessional collaboration by introducing the mental health care EHR. Routine education for end users is an essential starting point for the successful implementation of mental health care EHR electronic decision support. When adopting the mental health care EHR, managers need to focus on common practices in behavioral hospitals, such as documenting structured data in their organizations and adopting a seamless workflow of mental health care into the system.

Project description:BACKGROUND:Primary care needs to be patient-centered, integrated, and interprofessional to help patients with complex needs manage the burden of medication-related problems. Considering the growing problem of polypharmacy, increasing attention has been paid to how and when medication-related decisions should be coordinated across multidisciplinary care teams. Improved knowledge on how integrated electronic health records (EHRs) can support interprofessional shared decision-making for medication therapy management is necessary to continue improving patient care. OBJECTIVE:The objective of our study was to examine how physicians and pharmacists understand and communicate patient-focused medication information with each other and how this knowledge can influence the design of EHRs. METHODS:This study is part of a broader cross-Canada study between patients and health care providers around how medication-related decisions are made and communicated. We visited community pharmacies, team-based primary care clinics, and independent-practice family physician clinics throughout Ontario, Nova Scotia, Alberta, and Quebec. Research assistants conducted semistructured interviews with physicians and pharmacists. A modified version of the Multidisciplinary Framework Method was used to analyze the data. RESULTS:We collected data from 19 pharmacies and 9 medical clinics and identified 6 main themes from 34 health care professionals. First, Interprofessional Shared Decision-Making was not occurring and clinicians made decisions based on their understanding of the patient. Physicians and pharmacists reported indirect Communication, incomplete Information specifically missing insight into indication and adherence, and misaligned Processes of Care that were further compounded by EHRs that are not designed to facilitate collaboration. Scope of Practice examined professional and workplace boundaries for pharmacists and physicians that were internally and externally imposed. Physicians decided on the degree of the Physician-Pharmacist Relationship, often predicated by colocation. CONCLUSIONS:We observed limited communication and collaboration between primary care providers and pharmacists when managing medications. Pharmacists were missing key information around reason for use, and physicians required accurate information around adherence. EHRs are a potential tool to help clinicians communicate information to resolve this issue. EHRs need to be designed to facilitate interprofessional medication management so that pharmacists and physicians can move beyond task-based work toward a collaborative approach.

Project description:BackgroundA high proportion of patients with severe mental illness relapse due to nonadherence to psychotropic medication. In this paper, we use the normalization process theory (NPT) to describe the implementation of a web-based clinical decision support system (CDSS) for Community Mental Health Services (CMHS) called Actionable Intime Insights or AI2. AI2 has two distinct functions: (1) it provides an overview of medication and treatment history to assist in reviewing patient adherence and (2) gives alerts indicating nonadherence to support early intervention.ObjectiveOur objective is to evaluate the pilot implementation of the AI2 application to better understand the challenges of implementing a web-based CDSS to support medication adherence and early intervention in CMHS.MethodsThe NPT and participatory action framework were used to both explore and support implementation. Qualitative data were collected over the course of the 14-month implementation, in which researchers were active participants. Data were analyzed and coded using the NPT framework. Qualitative data included discussions, meetings, and work products, including emails and documents.ResultsThis study explores the barriers and enablers of implementing a CDSS to support early intervention within CMHS using Medicare data from Australia's national electronic record system, My Health Record (MyHR). The implementation was a series of ongoing negotiations, which resulted in a staged implementation with compromises on both sides. Clinicians were initially hesitant about using a CDSS based on MyHR data and expressed concerns about the changes to their work practice required to support early intervention. Substantial workarounds were required to move the implementation forward. This pilot implementation allowed us to better understand the challenges of implementation and the resources and support required to implement and sustain a model of care based on automated alerts to support early intervention.ConclusionsThe use of decision support based on electronic health records is growing, and while implementation is challenging, the potential benefits of early intervention to prevent relapse and hospitalization and ensure increased efficiency of the health care system are worth pursuing.

Project description:BackgroundMenu labelling is continuing to gather public and legislative support as one of the potential environmental strategies for addressing the obesity pandemic. However, issues relating to implementation have been reported in countries where menu labelling has been introduced on a voluntary or mandatory basis. The aim of this mixed methods systematic review is to synthesise the empirical evidence on the barriers and facilitators to implementation of menu labelling interventions to support healthy food choices.MethodsThis review will use the 'best fit' framework synthesis approach to synthesise qualitative, quantitative and mixed methods evidence. Peer-reviewed publications will be accessed through PubMed, EMBASE, CINAHL, PsycINFO, Web of Science and Scopus. Grey literature will be accessed through Google Scholar, OpenGrey, RIAN, EThOS, ProQuest, WorldCat, Networked Digital Library of Theses and Dissertations, Open Access Theses and Dissertations, and public health organisation websites. Screening reference lists, citation chaining and contacting authors of all included studies will be undertaken. There will be no restriction on menu labelling scheme or format, publication year or language; however, only primary research studies relevant to supply-side stakeholders will be eligible for inclusion. Study quality will be assessed using the Mixed Methods Appraisal Tool. At least two independent reviewers will perform study selection, data extraction and quality appraisal; if consensus is required, another independent reviewer will be consulted. A combination of deductive coding, using the Consolidated Framework for Implementation Research as the a priori framework, and inductive analysis, using secondary thematic analysis, will be used. The overall process will assist in the construction of a new evidence-based conceptual model regarding the implementation of menu labelling interventions. The new model will be assessed for bias and a sensitivity analysis performed.DiscussionGiven the growing consensus that a systemic, sustained portfolio of obesity prevention strategies, delivered at scale, is needed to address the obesity epidemic, greater understanding of the practical issues relating to implementation of such strategies is required. Findings from this review will be used to develop a set of best-practice guidelines to enhance the adoption, implementation and sustainability of menu labelling interventions across countries worldwide.Systematic review registrationPROSPERO CRD42017083306.

Project description:BACKGROUND:Unnecessary healthcare utilization, non-adherence to current clinical guidelines, or insufficient personalized care are perpetual challenges and remain potential major cost-drivers for healthcare systems around the world. Implementing decision support systems into clinical care is promised to improve quality of care and thereby yield substantial effects on reducing healthcare expenditure. In this article, we evaluate the economic impact of clinical decision support (CDS) interventions based on electronic health records (EHR). METHODS:We searched for studies published after 2014 using MEDLINE, CENTRAL, WEB OF SCIENCE, EBSCO, and TUFTS CEA registry databases that encompass an economic evaluation or consider cost outcome measures of EHR based CDS interventions. Thereupon, we identified best practice application areas and categorized the investigated interventions according to an existing taxonomy of front-end CDS tools. RESULTS AND DISCUSSION:Twenty-seven studies are investigated in this review. Of those, twenty-two studies indicate a reduction of healthcare expenditure after implementing an EHR based CDS system, especially towards prevalent application areas, such as unnecessary laboratory testing, duplicate order entry, efficient transfusion practice, or reduction of antibiotic prescriptions. On the contrary, order facilitators and undiscovered malfunctions revealed to be threats and could lead to new cost drivers in healthcare. While high upfront and maintenance costs of CDS systems are a worldwide implementation barrier, most studies do not consider implementation cost. Finally, four included economic evaluation studies report mixed monetary outcome results and thus highlight the importance of further high-quality economic evaluations for these CDS systems. CONCLUSION:Current research studies lack consideration of comparative cost-outcome metrics as well as detailed cost components in their analyses. Nonetheless, the positive economic impact of EHR based CDS interventions is highly promising, especially with regard to reducing waste in healthcare.

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Barriers and Facilitators to Implementation of Medication Decision Support Systems in Electronic Medical Records: Mixed Methods Approach Based on Structural Equation Modeling and Qualitative Analysis.

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Barriers and Facilitators to Implementation of Medication Decision Support Systems in Electronic Medical Records: Mixed Methods Approach Based on Structural Equation Modeling and Qualitative Analysis.

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