Clinical Decision Support to Reduce Opioid Prescriptions for Dental Extractions using SMART on FHIR: Implementation Report.

BACKGROUND: Clinical decision support (CDS) has the potential to improve clinical decision-making consistent with evidence-based care. CDS can be designed to save health care providers time and help them provide safe and personalized analgesic prescribing. OBJECTIVE: The aim of this report is to describe the development of a CDS system designed to provide dentists with personalized pain management recommendations to reduce opioid prescribing following extractions. The use of CDS is also examined. METHODS: This study was conducted in HealthPartners, which uses an electronic health record (EHR) system that integrates both medical and dental information upon which the CDS application was developed based on SMART (Substitutable Medical Applications and Reusable Technologies) on FHIR (Fast Healthcare Interoperability Resources). The various tools used to bring relevant medical conditions, medications, patient history, and other relevant data into the CDS interface are described. The CDS application runs a drug interaction algorithm developed by our organization and provides patient-specific recommendations. The CDS included access to the state Prescription Monitoring Program database. IMPLEMENTATION (RESULTS): The pain management CDS was implemented as part of a study examining opioid prescribing among patients undergoing dental extraction procedures from February 17, 2020, to May 14, 2021. Provider-level use of CDS at extraction encounters ranged from 0% to 87.4% with 12.1% of providers opening the CDS for no encounters, 39.4% opening the CDS for 1%-20% of encounters, 36.4% opening it for 21%-50% of encounters, and 12.1% opening it for 51%-87% of encounters. CONCLUSIONS: The pain management CDS is an EHR-embedded, provider-facing tool to help dentists make personalized pain management recommendations following dental extractions. The SMART on FHIR-based pain management CDS adapted well to the point-of-care dental setting and led to the design of a scalable CDS tool that is EHR vendor agnostic. TRIAL REGISTRATION: ClinicalTrials.gov NCT03584789; https://clinicaltrials.gov/study/NCT03584789.

Adapting a clinical decision support system to improve identification of pediatric hypertension in a rural health system: Design of a pragmatic trial.

BACKGROUND: Identifying hypertension (HTN) early is crucial in preventing and lowering the long-term risk of heart disease, yet HTN in children often goes undiagnosed. An electronic health record linked, web-based clinical decision support (CDS) called PedsBP can help address this care gap and has been previously shown to increase recognition of HTN by primary care clinicians. OBJECTIVES: To adapt the PedsBP tool for use in a mostly rural health system and then to evaluate the effectiveness of PedsBP for repeat of hypertensive level blood pressure (BP) measurements and HTN recognition among youth 6-17 years of age in primary care settings, comparing low-intensity and high-intensity implementation approaches. METHODS AND DESIGN: PedsBP was evaluated through a pragmatic, clinic-randomized trial. The tool was piloted in 2 primary care clinics and modified prior to the full trial. Forty community-based, primary care clinics (or clusters of clinics) were randomly allocated in a 1:1:1 ratio to usual care, low-intensity implementation (CDS only), or high-intensity implementation (CDS plus in-person training, monthly use reports, and ongoing communication between study staff and clinics). Accrual of eligible patients started on August 1, 2022 and will continue for 18 months. Primary outcomes include repeating hypertensive level BP measurements at office visits and clinical recognition of HTN. Secondary outcomes include lifestyle counseling, dietician referral, and BP at follow-up. CONCLUSION: This report focuses on the design and feasibility of adapting and implementing PedsBP in a rural primary care setting. The trial and analysis are ongoing with main results expected in mid-2024.

Effect of Clinical Decision Support at Community Health Centers on the Risk of Cardiovascular Disease: A Cluster Randomized Clinical Trial.

Importance: Management of cardiovascular disease (CVD) risk in socioeconomically vulnerable patients is suboptimal; better risk factor control could improve CVD outcomes. Objective: To evaluate the impact of a clinical decision support system (CDSS) targeting CVD risk in community health centers (CHCs). Design, Setting, and Participants: This cluster randomized clinical trial included 70 CHC clinics randomized to an intervention group (42 clinics; 8 organizations) or a control group that received no intervention (28 clinics; 7 organizations) from September 20, 2018, to March 15, 2020. Randomization was by CHC organization accounting for organization size. Patients aged 40 to 75 years with (1) diabetes or atherosclerotic CVD and at least 1 uncontrolled major risk factor for CVD or (2) total reversible CVD risk of at least 10% were the population targeted by the CDSS intervention. Interventions: A point-of-care CDSS displaying real-time CVD risk factor control data and personalized, prioritized evidence-based care recommendations. Main Outcomes and Measures: One-year change in total CVD risk and reversible CVD risk (ie, the reduction in 10-year CVD risk that was considered achievable if 6 key risk factors reached evidence-based levels of control). Results: Among the 18 578 eligible patients (9490 [51.1%] women; mean [SD] age, 58.7 [8.8] years), patients seen in control clinics (n = 7419) had higher mean (SD) baseline CVD risk (16.6% [12.8%]) than patients seen in intervention clinics (n = 11 159) (15.6% [12.3%]; P < .001); baseline reversible CVD risk was similarly higher among patients seen in control clinics. The CDSS was used at 19.8% of 91 988 eligible intervention clinic encounters. No population-level reduction in CVD risk was seen in patients in control or intervention clinics; mean reversible risk improved significantly more among patients in control (-0.1% [95% CI, -0.3% to -0.02%]) than intervention clinics (0.4% [95% CI, 0.3% to 0.5%]; P < .001). However, when the CDSS was used, both risk measures decreased more among patients with high baseline risk in intervention than control clinics; notably, mean reversible risk decreased by an absolute 4.4% (95% CI, -5.2% to -3.7%) among patients in intervention clinics compared with 2.7% (95% CI, -3.4% to -1.9%) among patients in control clinics (P = .001). Conclusions and Relevance: The CDSS had low use rates and failed to improve CVD risk in the overall population but appeared to have a benefit on CVD risk when it was consistently used for patients with high baseline risk treated in CHCs. Despite some limitations, these results provide preliminary evidence that this technology has the potential to improve clinical care in socioeconomically vulnerable patients with high CVD risk. Trial Registration: ClinicalTrials.gov Identifier: NCT03001713.