Appl Clin Inform 2017; 08(02): 412-429
DOI: 10.4338/ACI-2016-04-RA-0068
Research Article
Schattauer GmbH

Development and use of a clinical decision support tool for behavioral health screening in primary care clinics

Timothy E. Burdick
1  Department of Community and Family Medicine, Geisel School of Medicine, Hanover, NH, USA
2  Department of Biomedical Data Science, Geisel School of Medicine, Hanover, NH, USA
3  Department of Medical Informatics and Clinical Epidemiology, Oregon Health and Science University, Portland, OR, USA
,
Rodger S Kessler
4  Department of Family Medicine, University of Vermont, Burlington, VT, USA
5  Center for Clinical and Translational Science, University of Vermont, Burlington, VT, USA
› Author Affiliations
Funding This research was made possible in part by a grant from the Vermont Health Improvement Program at the University of Vermont (PI: Dr. Thomas Peterson).
Further Information

Publication History

08 July 2016

16 February 2017

Publication Date:
21 December 2017 (online)

Summary

Objective: Screening, brief intervention, and referral for treatment (SBIRT) for behavioral health (BH) is a key clinical process. SBIRT tools in electronic health records (EHR) are infrequent and rarely studied. Our goals were 1) to design and implement SBIRT using clinical decision support (CDS) in a commercial EHR; and 2) to conduct a pragmatic evaluation of the impact of the tools on clinical outcomes.

Methods: A multidisciplinary team designed SBIRT workflows and CDS tools. We analyzed the outcomes using a retrospective descriptive convenience cohort with age-matched comparison group. Data extracted from the EHR were evaluated using descriptive statistics.

Results: There were 2 outcomes studied: 1) development and use of new BH screening tools and workflows; and 2) the results of use of those tools by a convenience sample of 866 encounters. The EHR tools developed included a flowsheet for documenting screens for 3 domains (depression, alcohol use, and prescription misuse); and 5 alerts with clinical recommendations based on screening; and reminders for annual screening. Positive screen rate was 21% (≥1 domain) with 60% of those positive for depression. Screening was rarely positive in 2 domains (11%), and never positive in 3 domains. Positive and negative screens led to higher rates of documentation of brief intervention (BI) compared with a matched sample who did not receive screening, including changes in psychotropic medications, updated BH terms on the problem list, or referral for BH intervention. Clinical process outcomes changed even when screening was negative.

Conclusions: Modified workflows for BH screening and CDS tools with clinical recommendations can be deployed in the EHR. Using SBIRT tools changed clinical process metrics even when screening was negative, perhaps due to conversations about BH not captured in the screening flowsheet. Although there are limitations to the study, results support ongoing investigation.

Citation: Burdick TE, Kessler RS. Development and use of a clinical decision support tool for behavioral health screening in primary care clinics. Appl Clin Inform 2017; 8: 412–429 https://doi.org/10.4338/ACI-2016-04-RA-0068

Clinical Relevance

Implementing clinical decision support requires partnerships between EHR managers and clinical leaders, and it must account for workflow and content redesign. Access to results of validated behavioral health (BH) screening tools, incorporated into the EHR, increased screening substantially. The screening process seems to increase provider documentation of BH problems in the medical record and increases access to behavioral care through brief intervention by medication management and referrals – even in cases when screening is negative.


Ethics approval

The study was performed in compliance with the World Medical Association Declaration of Helsinki on Ethical Principles for Medical Research Involving Human Subjects and was reviewed by the University of Vermont Institutional Review Board.