Electronic clinical decision support for management of depression in primary care: a prospective cohort study

Benefits of Clinical Decision Support Systems for the Management of Noncommunicable Chronic Diseases: Targeted Literature Review

BACKGROUND

Clinical decision support systems (CDSSs) are designed to assist in health care delivery by supporting medical practice with clinical knowledge, patient information, and other relevant types of health information. CDSSs are integral parts of health care technologies assisting in disease management, including diagnosis, treatment, and monitoring. While electronic medical records (EMRs) serve as data repositories, CDSSs are used to assist clinicians in providing personalized, context-specific recommendations derived by comparing individual patient data to evidence-based guidelines.

OBJECTIVE

This targeted literature review (TLR) aimed to identify characteristics and features of both stand-alone and EMR-integrated CDSSs that influence their outcomes and benefits based on published scientific literature.

METHODS

A TLR was conducted using the Embase, MEDLINE, and Cochrane databases to identify data on CDSSs published in a 10-year frame (2012-2022). Studies on computerized, guideline-based CDSSs used by health care practitioners with a focus on chronic disease areas and reporting outcomes for CDSS utilization were eligible for inclusion.

RESULTS

A total of 49 publications were included in the TLR. Studies predominantly reported on EMR-integrated CDSSs (ie, connected to an EMR database; n=32, 65%). The implementation of CDSSs varied globally, with substantial utilization in the United States and within the domain of cardio-renal-metabolic diseases. CDSSs were found to positively impact "quality assurance" (n=35, 69%) and provide "clinical benefits" (n=20, 41%), compared to usual care. Among CDSS features, treatment guidance and flagging were consistently reported as the most frequent elements for enhancing health care, followed by risk level estimation, diagnosis, education, and data export. The effectiveness of a CDSS was evaluated most frequently in primary care settings (n=34, 69%) across cardio-renal-metabolic disease areas (n=32, 65%), especially in diabetes (n=13, 26%). Studies reported CDSSs to be commonly used by a mixed group (n=27, 55%) of users including physicians, specialists, nurses or nurse practitioners, and allied health care professionals.

CONCLUSIONS

Overall, both EMR-integrated and stand-alone CDSSs showed positive results, suggesting their benefits to health care providers and potential for successful adoption. Flagging and treatment recommendation features were commonly used in CDSSs to improve patient care; other features such as risk level estimation, diagnosis, education, and data export were tailored to specific requirements and collectively contributed to the effectiveness of health care delivery. While this TLR demonstrated that both stand-alone and EMR-integrated CDSSs were successful in achieving clinical outcomes, the heterogeneity of included studies reflects the evolving nature of this research area, underscoring the need for further longitudinal studies to elucidate aspects that may impact their adoption in real-world scenarios.

Unmet need in major depressive disorder and acute suicidal ideation or behavior: findings from a longitudinal electronic health record data analysis

AIMS

Using a national electronic health records (EHR) database, the current study describes treatments, depression severity, and health care resource utilization (HRU) among patients with major depressive disorder (MDD) and acute suicidal ideation or behavior (MDSI) prior to, during, and following a suicide-related event in the United States.

MATERIALS AND METHODS

This retrospective matched cohort study used data collected from the Optum EHR de-identified database for patients with diagnosis codes for MDD and acute suicidal ideation or behavior and a propensity score-matched cohort of patients without MDD or a suicide-related event. The study period was 31 October 2015-30 September 2019. MDD-related treatments and 9-item Patient Health Questionnaire (PHQ-9) scores, when available, were assessed at the first health care encounter for a suicide-related event (index period), 12 months before (pre-period), and 6 months after (post-period). All-cause and MDD-related HRU were assessed during the post-period.

RESULTS

The mean (standard deviation) age of patients with MDSI was 39 (16) years; 55.0% were female. Index events occurred as follows: inpatient stay, 38.9%; observation unit stay, 4.6%; emergency department (ED) visit, 46.5%; and outpatient visit, 10.1%. Antidepressants and psychotherapy were the most common pharmacologic and nonpharmacologic treatments, respectively, prescribed during the pre- (31.3%, 9.5%, respectively) and index (41.2%, 18.7%, respectively) periods. Post-period data (n = 40,261) revealed only 43.4% received an antidepressant and 20.5% had psychotherapy after the suicide-related event. Few patients had PHQ-9 scores recorded during the pre- (4.4%), index (1.3%), and post- (7.6%) periods. During the post-period, 11.8%, 5.0%, and 33.1% of patients had ≥1 all-cause inpatient stay, observation unit stay, and ED visit, respectively; 61.0% had ≥1 all-cause and 33.4% ≥1 MDD-related outpatient visit. Most patients with MDSI and an inpatient encounter or ED visit were discharged to home or self-care (65.4%). Odds of an all-cause hospital encounter during the post-period were higher for patients with versus without MDSI (by 30.1, 33.5, and 33.9 times for inpatient stay, ED visit, and observation unit stay, respectively).

CONCLUSION

This analysis highlights an opportunity to improve outcomes for this vulnerable population. More complete data on patient outcomes is needed to inform strategies designed to optimize screening and treatment.

Effect of a novel pharmacist-led reporting system on appropriate use of direct-acting oral anticoagulants (DOACs) in a patient-centered medical home

Recent analyses demonstrate roughly 16-24% of patients taking direct-acting oral anticoagulants (DOACs) are prescribed an inappropriate dose, exposing patients to increased risk of thrombosis or bleeding. The use of reporting systems in the outpatient setting can efficiently identify potential medication errors and safety concerns. The purpose of this study was to evaluate the effect of a novel pharmacist-driven reporting system on appropriate prescribing of DOACs in the outpatient setting. This single-center qualitative study was conducted within a patient-centered medical home (PCMH). Reports were generated monthly to include all new DOAC prescriptions. Branching logic and filters were utilized within a secure web application to make the reporting process more efficient and identify regimens needing an intervention. Pharmacists reviewed the regimens populated by filters and made recommendations to prescribers as appropriate. The number of interventions proposed was captured as the primary outcome. Secondary outcomes include the nature of drug therapy problems identified and number of interventions accepted by prescribers. A total of 107 patients were analyzed for appropriateness from November 2017 to February 2019. Of the regimens included for review, 15 regimens were identified as potentially inappropriate. The nature of drug therapy problems identified include under dosing (4.25%), overdosing (2.13%), correction of documentation (2.13%), clarification of indication (3.19%), and ordering laboratory studies (3.19%). Of the interventions recommended, fourteen (93%) were accepted. Pharmacists integrated in a PCMH are well positioned to monitor and resolve DOAC drug therapy problems using local clinical reports.

Use of the 9-Item Patient Health Questionnaire for Depression Assessment in Primary Care Patients With Type 2 Diabetes

The purpose of the current study was to assess the frequency and distribution of the 9-Item Patient Health Questionnaire (PHQ-9) among individuals with type 2 diabetes with and without depression. The current case-control study used electronic medical record data from two primary care institutions. The sample was divided into cases with coexisting depression and type 2 diabetes and controls without depression. Data included demographics, biomarkers, number of services delivered, and clinic visits in 2013. Similar PHQ-9 use was seen between unique primary care practices. However, less than one third of patients at either site received depression screening with the PHQ-9 in 2013. Male and older adult patients were less likely to receive assessment. Guideline ambiguity and lack of accountability in primary care practice has made the use of depression metrics arbitrary in diabetic populations at risk for depression. To assure adequate care provision, it is imperative that proven tools for assessing depressive symptoms are used.

Mental health collaborative care and its role in primary care settings

Collaborative care models (CCMs) provide a pragmatic strategy to deliver integrated mental health and medical care for persons with mental health conditions served in primary care settings. CCMs are team-based intervention to enact system-level redesign by improving patient care through organizational leadership support, provider decision support, and clinical information systems, as well as engaging patients in their care through self-management support and linkages to community resources. The model is also a cost-efficient strategy for primary care practices to improve outcomes for a range of mental health conditions across populations and settings. CCMs can help achieve integrated care aims underhealth care reform yet organizational and financial issues may affect adoption into routine primary care. Notably, successful implementation of CCMs in routine care will require alignment of financial incentives to support systems redesign investments, reimbursements for mental health providers, and adaptation across different practice settings and infrastructure to offer all CCM components.

Furthering the reliable and valid measurement of mental health screening, diagnoses, treatment and outcomes through health information technology

INTRODUCTION

Measurement of mental health is challenging; however, many solutions may be found through the use of health information technology.

METHOD

This article reviews current approaches to measuring mental health, focusing on screening, diagnosis, treatment, and outcomes. It then identifies several key areas in which health information technology may advance the field and provide reliable and valid measurements that are readily available to and manageable for providers, as well as acceptable, feasible, and sustainable for selected populations.

RESULT AND CONCLUSIONS

Although new technologies must overcome many challenges, including privacy, efficiency, cost, and scalability, it is an exciting and fast-growing field with many potential applications and clinical benefit.