Topical Corticosteroid Clinical Decision Support for Primary Care Providers: There’s an App for That!

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.

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Live Usability Testing of Two Complex Clinical Decision Support Tools: Observational Study (Preprint)

10.2196/preprints.12471 ◽

2018 ◽

Author(s):

Safiya Richardson ◽

David Feldstein ◽

Thomas McGinn ◽

Linda S Park ◽

Sundas Khan ◽

...

Keyword(s):

Primary Care ◽

Decision Support ◽

Observational Study ◽

Clinical Decision Support ◽

Usability Testing ◽

Clinical Decision ◽

Primary Care Providers ◽

Chief Complaint ◽

Care Providers ◽

Clinical Environment

BACKGROUND Potential of the electronic health records (EHR) and clinical decision support (CDS) systems to improve the practice of medicine has been tempered by poor design and the resulting burden they place on providers. CDS is rarely tested in the real clinical environment. As a result, many tools are hard to use, placing strain on providers and resulting in low adoption rates. The existing CDS usability literature relies primarily on expert opinion and provider feedback via survey. This is the first study to evaluate CDS usability and the provider-computer-patient interaction with complex CDS in the real clinical environment. OBJECTIVE This study aimed to further understand the barriers and facilitators of meaningful CDS usage within a real clinical context. METHODS This qualitative observational study was conducted with 3 primary care providers during 6 patient care sessions. In patients with the chief complaint of sore throat, a CDS tool built with the Centor Score was used to stratify the risk of group A Streptococcus pharyngitis. In patients with a chief complaint of cough or upper respiratory tract infection, a CDS tool built with the Heckerling Rule was used to stratify the risk of pneumonia. During usability testing, all human-computer interactions, including audio and continuous screen capture, were recorded using the Camtasia software. Participants’ comments and interactions with the tool during clinical sessions and participant comments during a postsession brief interview were placed into coding categories and analyzed for generalizable themes. RESULTS In the 6 encounters observed, primary care providers toggled between addressing either the computer or the patient during the visit. Minimal time was spent listening to the patient without engaging the EHR. Participants mostly used the CDS tool with the patient, asking questions to populate the calculator and discussing the results of the risk assessment; they reported the ability to do this as the major benefit of the tool. All providers were interrupted during their use of the CDS tool by the need to refer to other sections of the chart. In half of the visits, patients’ clinical symptoms challenged the applicability of the tool to calculate the risk of bacterial infection. Primary care providers rarely used the incorporated incentives for CDS usage, including progress notes and patient instructions. CONCLUSIONS Live usability testing of these CDS tools generated insights about their role in the patient-provider interaction. CDS may contribute to the interaction by being simultaneously viewed by the provider and patient. CDS can improve usability and lessen the strain it places on providers by being short, flexible, and customizable to unique provider workflow. A useful component of CDS is being as widely applicable as possible and ensuring that its functions represent the fastest way to perform a particular task.

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Genomic decision support needs in pediatric primary care

Journal of the American Medical Informatics Association ◽

10.1093/jamia/ocw184 ◽

2017 ◽

Vol 24 (4) ◽

pp. 851-856 ◽

Cited By ~ 4

Author(s):

Jeffrey W Pennington ◽

Dean J Karavite ◽

Edward M Krause ◽

Jeffrey Miller ◽

Barbara A Bernhardt ◽

...

Keyword(s):

Primary Care ◽

Decision Support ◽

Clinical Decision Support ◽

Clinical Decision ◽

Primary Care Providers ◽

Pediatric Primary Care ◽

Care Providers ◽

Further Development

Abstract Clinical genome and exome sequencing can diagnose pediatric patients with complex conditions that often require follow-up care with multiple specialties. The American Academy of Pediatrics emphasizes the role of the medical home and the primary care pediatrician in coordinating care for patients who need multidisciplinary support. In addition, the electronic health record (EHR) with embedded clinical decision support is recognized as an important component in providing care in this setting. We interviewed 6 clinicians to assess their experience caring for patients with complex and rare genetic findings and hear their opinions about how the EHR currently supports this role. Using these results, we designed a candidate EHR clinical decision support application mock-up and conducted formative exploratory user testing with 26 pediatric primary care providers to capture opinions on its utility in practice with respect to a specific clinical scenario. Our results indicate agreement that the functionality represented by the mock-up would effectively assist with care and warrants further development.

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A pilot study of the functionality and clinician acceptance of a clinical decision support tool to improve primary care of opioid use disorder

Addiction Science & Clinical Practice ◽

10.1186/s13722-021-00245-7 ◽

2021 ◽

Vol 16 (1) ◽

Author(s):

Rebecca C. Rossom ◽

JoAnn M. Sperl-Hillen ◽

Patrick J. O’Connor ◽

A. Lauren Crain ◽

Laurel Nightingale ◽

...

Keyword(s):

Primary Care ◽

Decision Support ◽

Clinical Decision Support ◽

Clinical Decision ◽

Primary Care Providers ◽

Opioid Use Disorder ◽

Care Providers ◽

Opioid Use ◽

Convenience Sample ◽

Increased Risk

Abstract Objective Most Americans with opioid use disorder (OUD) do not receive indicated medical care. A clinical decision support (CDS) tool for primary care providers (PCPs) could address this treatment gap. Our primary objective was to build OUD-CDS tool and demonstrate its functionality and accuracy. Secondary objectives were to achieve high use and approval rates and improve PCP confidence in diagnosing and treating OUD. Methods A convenience sample of 55 PCPs participated. Buprenorphine-waivered PCPs (n = 8) were assigned to the intervention. Non-waivered PCPs (n = 47) were randomized to intervention (n = 24) or control (n = 23). Intervention PCPs received access to the OUD-CDS, which alerted them to patients at potentially increased risk for OUD or overdose and guided diagnosis and treatment. Control PCPs provided care as usual. Results The OUD-CDS was functional and accurate following extensive multi-phased testing. PCPs used the OUD-CDS in 5% of encounters with at-risk patients, far less than the goal of 60%. OUD screening confidence increased for all intervention PCPs and OUD diagnosis increased for non-waivered intervention PCPs. Most PCPs (65%) would recommend the OUD-CDS and found it helpful with screening for OUD and discussing and prescribing OUD medications. Discussion PCPs generally liked the OUD-CDS, but use rates were low, suggesting the need to modify CDS design, implementation strategies and integration with existing primary care workflows. Conclusion The OUD-CDS tool was functional and accurate, but PCP use rates were low. Despite low use, the OUD-CDS improved confidence in OUD screening, diagnosis and use of buprenorphine. NIH Trial registration NCT03559179. Date of registration: 06/18/2018. URL: https://clinicaltrials.gov/ct2/show/NCT03559179

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Sustaining Use of a Clinical Decision Support Tool for Primary Care Providers

Journal of Patient-Centered Research and Reviews ◽

10.17294/2330-0698.1141 ◽

2015 ◽

Vol 2 (2) ◽

pp. 116

Author(s):

A. L. Crain ◽

JoAnn M Sperl-Hillen ◽

Heidi L Ekstrom ◽

Patrick J O'Connor ◽

Karen L Margolis ◽

...

Keyword(s):

Primary Care ◽

Decision Support ◽

Clinical Decision Support ◽

Decision Support Tool ◽

Clinical Decision ◽

Primary Care Providers ◽

Care Providers ◽

Support Tool ◽

Clinical Decision Support Tool

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Effects of computer-aided clinical decision support systems in improving antibiotic prescribing by primary care providers: a systematic review

Journal of the American Medical Informatics Association ◽

10.1136/amiajnl-2014-002886 ◽

2014 ◽

Vol 22 (1) ◽

pp. 236-242 ◽

Cited By ~ 42

Author(s):

Jakob Holstiege ◽

Tim Mathes ◽

Dawid Pieper

Keyword(s):

Primary Care ◽

Decision Support ◽

Clinical Decision Support Systems ◽

Clinical Decision ◽

Primary Care Providers ◽

Antibiotic Prescribing ◽

Care Providers ◽

Prescribing Behavior ◽

Computer Aided ◽

Prescribing Practice

Abstract Objective To assess the effectiveness of computer-aided clinical decision support systems (CDSS) in improving antibiotic prescribing in primary care. Methods A literature search utilizing Medline (via PubMed) and Embase (via Embase) was conducted up to November 2013. Randomized controlled trials (RCTs) and cluster randomized trials (CRTs) that evaluated the effects of CDSS aiming at improving antibiotic prescribing practice in an ambulatory primary care setting were included for review. Two investigators independently extracted data about study design and quality, participant characteristics, interventions, and outcomes. Results Seven studies (4 CRTs, 3 RCTs) met our inclusion criteria. All studies were performed in the USA. Proportions of eligible patient visits that triggered CDSS use varied substantially between intervention arms of studies (range 2.8–62.8%). Five out of seven trials showed marginal to moderate statistically significant effects of CDSS in improving antibiotic prescribing behavior. CDSS that automatically provided decision support were more likely to improve prescribing practice in contrast to systems that had to be actively initiated by healthcare providers. Conclusions CDSS show promising effectiveness in improving antibiotic prescribing behavior in primary care. Magnitude of effects compared to no intervention, appeared to be similar to other moderately effective single interventions directed at primary care providers. Additional research is warranted to determine CDSS characteristics crucial to triggering high adoption by providers as a perquisite of clinically relevant improvement of antibiotic prescribing.

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

10.21203/rs.3.rs-499725/v1 ◽

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

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

Diabetes ◽

10.2337/db21-859-p ◽

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

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Direct and Electronic Health Record Access to the Clinical Decision Support for Immunizations in the Minnesota Immunization Information System

Biomedical Informatics Insights ◽

10.4137/bii.s40208 ◽

2016 ◽

Vol 8s2 ◽

pp. BII.S40208

Author(s):

Sripriya Rajamani ◽

Aaron Bieringer ◽

Stephanie Wallerius ◽

Daniel Jensen ◽

Tamara Winden ◽

...

Keyword(s):

Decision Support ◽

Clinical Decision Support ◽

Health Care Providers ◽

Clinical Decision ◽

Population Based ◽

Direct Access ◽

Care Providers ◽

Study Objective ◽

Vaccination Rates ◽

Electronic Health

Immunization information systems (IIS) are population-based and confidential computerized systems maintained by public health agencies containing individual data on immunizations from participating health care providers. IIS hold comprehensive vaccination histories given across providers and over time. An important aspect to IIS is the clinical decision support for immunizations (CDSi), consisting of vaccine forecasting algorithms to determine needed immunizations. The study objective was to analyze the CDSi presentation by IIS in Minnesota (Minnesota Immunization Information Connection [MIIC]) through direct access by IIS interface and by access through electronic health records (EHRs) to outline similarities and differences. The immunization data presented were similar across the three systems examined, but with varying ability to integrate data across MIIC and EHR, which impacts immunization data reconciliation. Study findings will lead to better understanding of immunization data display, clinical decision support, and user functionalities with the ultimate goal of promoting IIS CDSi to improve vaccination rates.

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

10.21203/rs.3.rs-64077/v2 ◽

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.

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