Effectiveness of clinical decision support to enhance delivery of family planning services in primary care settings

Contraception ◽  
2020 ◽  
Vol 101 (3) ◽  
pp. 199-204
Author(s):  
Silpa Srinivasulu ◽  
Seema D. Shah ◽  
Clyde B. Schechter ◽  
Linda Prine ◽  
Susan E. Rubin
Keyword(s):  
Primary Care ◽  
Decision Support ◽  
Family Planning ◽  
Clinical Decision Support ◽  
Clinical Decision ◽  
Family Planning Services ◽  
Primary Care Settings

scholarly journals Clinical Decision Support for Worker Health: A Five-Site Qualitative Needs Assessment in Primary Care Settings

2020 ◽  
Vol 11 (04) ◽  
pp. 635-643
Author(s):  
Joan S. Ash ◽  
Dian Chase ◽  
Sherry Baron ◽  
Margaret S. Filios ◽  
Richard N. Shiffman ◽  
...  
Keyword(s):  
Primary Care ◽  
Decision Support ◽  
Clinical Decision Support ◽  
Clinical Decision ◽  
Primary Care Providers ◽  
Care Providers ◽  
Technical Feasibility ◽  
Primary Care Settings ◽  
Worker Health ◽  
Operational Issues

Abstract Background Although patients who work and have related health issues are usually first seen in primary care, providers in these settings do not routinely ask questions about work. Guidelines to help manage such patients are rarely used in primary care. Electronic health record (EHR) systems with worker health clinical decision support (CDS) tools have potential for assisting these practices. Objective This study aimed to identify the need for, and barriers and facilitators related to, implementation of CDS tools for the clinical management of working patients in a variety of primary care settings. Methods We used a qualitative design that included analysis of interview transcripts and observational field notes from 10 clinics in five organizations. Results We interviewed 83 providers, staff members, managers, informatics and information technology experts, and leaders and spent 35 hours observing. We identified eight themes in four categories related to CDS for worker health (operational issues, usefulness of proposed CDS, effort and time-related issues, and topic-specific issues). These categories were classified as facilitators or barriers to the use of the CDS tools. Facilitators related to operational issues include current technical feasibility and new work patterns associated with the coordinated care model. Facilitators concerning usefulness include users' need for awareness and evidence-based tools, appropriateness of the proposed CDS for their patients, and the benefits of population health data. Barriers that are effort-related include additional time this proposed CDS might take, and other pressing organizational priorities. Barriers that are topic-specific include sensitive issues related to health and work and the complexities of information about work. Conclusion We discovered several themes not previously described that can guide future CDS development: technical feasibility of the proposed CDS within commercial EHRs, the sensitive nature of some CDS content, and the need to assist the entire health care team in managing worker health.

scholarly journals Assessing the implementation of a clinical decision support tool in primary care for diabetes prevention: a qualitative interview study using the Consolidated Framework for Implementation Science

2022 ◽  
Vol 22 (1) ◽  
Author(s):  
Rebekah Pratt ◽  
Daniel M. Saman ◽  
Clayton Allen ◽  
Benjamin Crabtree ◽  
Kris Ohnsorg ◽  
...  
Keyword(s):  
Primary Care ◽  
Decision Support ◽  
Clinical Decision Support ◽  
Clinical Decision ◽  
Care Team ◽  
Trial Registration ◽  
Web Based ◽  
Primary Care Clinics ◽  
Primary Care Settings ◽  
Qualitative Interview Study

Abstract Background In this paper we describe the use of the Consolidated Framework for Implementation Research (CFIR) to study implementation of a web-based, point-of-care, EHR-linked clinical decision support (CDS) tool designed to identify and provide care recommendations for adults with prediabetes (Pre-D CDS). Methods As part of a large NIH-funded clinic-randomized trial, we identified a convenience sample of interview participants from 22 primary care clinics in Minnesota, North Dakota, and Wisconsin that were randomly allocated to receive or not receive a web-based EHR-integrated prediabetes CDS intervention. Participants included 11 clinicians, 6 rooming staff, and 7 nurse or clinic managers recruited by study staff to participate in telephone interviews conducted by an expert in qualitative methods. Interviews were recorded and transcribed, and data analysis was conducted using a constructivist version of grounded theory. Results Implementing a prediabetes CDS tool into primary care clinics was useful and well received. The intervention was integrated with clinic workflows, supported primary care clinicians in clearly communicating prediabetes risk and management options with patients, and in identifying actionable care opportunities. The main barriers to CDS use were time and competing priorities. Finally, while the implementation process worked well, opportunities remain in engaging the care team more broadly in CDS use. Conclusions The use of CDS tools for engaging patients and providers in care improvement opportunities for prediabetes is a promising and potentially effective strategy in primary care settings. A workflow that incorporates the whole care team in the use of such tools may optimize the implementation of CDS tools like these in primary care settings. Trial registration Name of the registry: Clinicaltrial.gov. Trial registration number: NCT02759055. Date of registration: 05/03/2016. URL of trial registry record: https://clinicaltrials.gov/ct2/show/NCT02759055 Prospectively registered.

scholarly journals Availability and usage of clinical decision support systems (CDSSs) in office-based primary care settings in the USA

2019 ◽  
Vol 26 (1) ◽  
pp. e100015
Author(s):  
Xia Jing ◽  
Lina Himawan ◽  
Timothy Law
Keyword(s):  
Primary Care ◽  
Drug Interaction ◽  
Decision Support ◽  
Clinical Decision Support ◽  
Clinical Decision Support Systems ◽  
Preventive Services ◽  
Clinical Decision ◽  
Primary Care Settings ◽  
The Usa ◽  
Usage Rates

BackgroundA clinical decision support system (CDSS) covers a broad spectrum of applications, for example, screening reminders, can reduce malpractice, improve preventive services and enable better management of chronic conditions. CDSSs have traditionally been used successfully in large hospitals. The availability (ie, whether the function is provided by the software) and usage (ie, actual use) of a CDSS in office-based primary care settings, however, are less well studied.ObjectiveTo establish a benchmark of CDSS availability and usage in office-based primary care settings, particularly given the large volume of visits in such settings.MethodsWe used the 2015 Centers for Disease Control and Prevention’s National Ambulatory Medical Care Survey to conduct secondary data analysis. We selected preventive services reminders and drug interaction alerts, along with several other variables as examples of a CDSS.ResultsCDSS usage rates ranged from 68.5% to 100% among solo or non-solo primary care practices owned by physicians or physician groups that have electronic medical records (EMRs)/electronic health records (EHRs) and 44.7% to 96.1%, regardless of EMR/EHR status. According to proportion tests, solo practices had significantly lower CDSS usage and availability rates on several measures if the practice is entirely EMR/EHR based and significantly lower (16.3%–28.9%) CDSS usage rates than did non-solo practices on each measure, regardless of EMR/EHR status.ConclusionIn the USA, a CDSS, especially under the categories of basic preventive reminders and drug interaction alerts, is used routinely between 68% and 100% in primary care if a practice is entirely EMR/EHR based. More work is needed, however, to determine the reasons for large usage gaps between solo and non-solo practices and to reduce such gaps.

Computerized Clinical Decision Support Systems for Prescribing in Primary Care: Main Characteristics and Implementation Impact. Protocol of an Evidence and Gap Map.

2021 ◽  
Author(s):  
Hector Acosta-Garcia ◽  
Ingrid Ferrer-López ◽  
Juan Ruano-Ruiz ◽  
Bernardo Santos-Ramos ◽  
Teresa Molina-López
Keyword(s):  
Primary Care ◽  
Decision Support ◽  
Decision Support Systems ◽  
Clinical Decision Support ◽  
Literature Search ◽  
Support Systems ◽  
Grey Literature ◽  
Clinical Decision Support Systems ◽  
Clinical Decision ◽  
Cochrane Library

Abstract Background Computerized clinical decision support systems are used by clinicians at the point-of-care to improve quality of healthcare processes (prescribing error prevention, adherence to clinical guidelines...) and clinical outcomes (preventive, therapeutic, and diagnostics). Attempts to summarize results of computerized clinical decision support systems to support prescription in primary care have been challenging, and most systematic reviews and meta-analyses failed due to an extremely high degree of heterogeneity present among the included primary studies. The aim of our study will be to synthesize the evidence, considering all methodological factors that could explain these differences, and to build an evidence and gap map to identify important remaining research questions. Methods A literature search will be conducted from January 2010 onwards in Medline, Embase, The Cochrane Library and Web of Science databases. Two reviewers will independently screen all citations, full-text and abstract data. The study methodological quality and risk of bias will be appraised using appropriate tools if applicable. A flow diagram with the screened studies will be presented, and all included studies will be displayed using interactive evidence and gap maps. Results will be reported in accordance with recommendations from The Campbell Collaboration on the development of evidence and gap maps. Discussion Evidence behind computerized clinical decision support systems to support prescription use in primary care, has so far been difficult to be synthesized. Evidence and gap maps represent an innovative approach that has emerged and is increasingly being used to address a broader research question, where multiple types of intervention and outcomes reported may be evaluated. Broad inclusion criteria have been chosen with regards to study designs, in order to collect all available information. Regarding the limitations we will only include English and Spanish language studies from the last 10 years, we will not perform a grey literature search, and we will not carry out a meta-analysis due to the predictable heterogeneity of available studies. Systematic Review registration: This study is registered in Open Science Framework https://bit.ly/2RqKrWp

859-P: Impact of a Prediabetes Clinical Decision Support System on CV Risk Factor Control in Primary Care: Randomized Trial

Diabetes ◽  
2021 ◽  
Vol 70 (Supplement 1) ◽  
pp. 859-P
Author(s):  
JAY R. DESAI ◽  
A. LAUREN CRAIN ◽  
DANIEL SAMAN ◽  
JOANN M. SPERL-HILLEN ◽  
CLAYTON ALLEN ◽  
...  
Keyword(s):  
Primary Care ◽  
Risk Factor ◽  
Decision Support ◽  
Decision Support System ◽  
Randomized Trial ◽  
Clinical Decision Support ◽  
Support System ◽  
Clinical Decision Support System ◽  
Clinical Decision ◽  
Risk Factor Control

scholarly journals Clinical decision support improves the appropriateness of laboratory test ordering in primary care without increasing diagnostic error: the ELMO cluster randomized trial

2020 ◽  
Author(s):  
Nicolas Delvaux ◽  
Veerle Piessens ◽  
Tine De Burghgraeve ◽  
Pavlos Mamouris ◽  
Bert Vaes ◽  
...  
Keyword(s):  
Primary Care ◽  
Decision Support ◽  
Laboratory Test ◽  
Clinical Decision Support ◽  
Clinical Decision ◽  
Diagnostic Error ◽  
Order Sets ◽  
Cluster Randomized ◽  
Physician Order Entry ◽  
Test Ordering

Abstract Background Inappropriate laboratory test ordering poses an important burden for healthcare. Clinical decision support systems (CDSS) have been cited as promising tools to improve laboratory test ordering behavior. The objectives of this study were to evaluate the effects of an intervention that integrated a clinical decision support service into a computerized physician order entry (CPOE) on the appropriateness and volume of laboratory test ordering, and on diagnostic error in primary care.Methods This study was a pragmatic, cluster randomized, open label, controlled clinical trial. Setting 280 general practitioners (GPs) from 72 primary care practices in Belgium. Patients Patients aged ≥18 years with a laboratory test order for at least one of 17 indications; cardiovascular disease management, hypertension, check-up, chronic kidney disease (CKD), thyroid disease, type 2 diabetes mellitus, fatigue, anemia, liver disease, gout, suspicion of acute coronary syndrome (ACS), suspicion of lung embolism, rheumatoid arthritis, sexually transmitted infections (STI), acute diarrhea, chronic diarrhea, and follow-up of medication. Interventions The CDSS was integrated into a computerized physician order entry (CPOE) in the form of evidence-based order sets that suggested appropriate tests based on the indication provided by the general physician. Measurements The primary outcome of the ELMO study was the proportion of appropriate tests over the total number of ordered tests and inappropriately not-requested tests. Secondary outcomes of the ELMO study included diagnostic error, test volume and cascade activities.Results CDSS increased the proportion of appropriate tests by 0.21 (95% CI 0.16 - 0.26, p<.0001) for all tests included in the study. GPs in the CDSS arm ordered 7 (7.15 (95% CI 3.37 - 10.93, p=.0002)) tests fewer per panel. CDSS did not increase diagnostic error. The absolute difference in proportions was a decrease of 0.66% (95% CI 1.4% decrease - 0.05% increase) in possible diagnostic error.Conclusions A CDSS in the form of order sets, integrated within the CPOE improved appropriateness and decreased volume of laboratory test ordering without increasing diagnostic error. Trial Registration Clinicaltrials.gov Identifier: NCT02950142, registered on October 25, 2016Funding source This study was funded through the Belgian Health Care Knowledge Centre (KCE) Trials Programme agreement KCE16011.

scholarly journals Using normalisation process theory to understand workflow implications of decision support implementation across diverse primary care settings

2019 ◽  
Vol 26 (1) ◽  
pp. e100088
Author(s):  
Rebecca G Mishuris ◽  
Joseph Palmisano ◽  
Lauren McCullagh ◽  
Rachel Hess ◽  
David A Feldstein ◽  
...  
Keyword(s):  
Primary Care ◽  
Decision Support ◽  
Clinical Decision ◽  
Process Theory ◽  
Normalisation Process Theory ◽  
Implementation Barriers ◽  
Clinical Workflow ◽  
Primary Care Settings ◽  
Registration Number

BackgroundEffective implementation of technologies into clinical workflow is hampered by lack of integration into daily activities. Normalisation process theory (NPT) can be used to describe the kinds of ‘work’ necessary to implement and embed complex new practices. We determined the suitability of NPT to assess the facilitators, barriers and ‘work’ of implementation of two clinical decision support (CDS) tools across diverse care settings.MethodsWe conducted baseline and 6-month follow-up quantitative surveys of clinic leadership at two academic institutions’ primary care clinics randomised to the intervention arm of a larger study. The survey was adapted from the NPT toolkit, analysing four implementation domains: sense-making, participation, action, monitoring. Domains were summarised among completed responses (n=60) and examined by role, institution, and time.ResultsThe median score for each NPT domain was the same across roles and institutions at baseline, and decreased at 6 months. At 6 months, clinic managers’ participation domain (p=0.003), and all domains for medical directors (p<0.003) declined. At 6 months, the action domain decreased among Utah respondents (p=0.03), and all domains decreased among Wisconsin respondents (p≤0.008).ConclusionsThis study employed NPT to longitudinally assess the implementation barriers of new CDS. The consistency of results across participant roles suggests similarities in the work each role took on during implementation. The decline in engagement over time suggests the need for more frequent contact to maintain momentum. Using NPT to evaluate this implementation provides insight into domains which can be addressed with participants to improve success of new electronic health record technologies.Trial registration numberNCT02534987.

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