Comparative effectiveness of generic commercial versus locally customized clinical decision support tools to reduce prescription of nonsteroidal anti-inflammatory drugs for patients with heart failure.

OBJECTIVE: To compare the effectiveness of 2 clinical decision support (CDS) tools to avoid prescription of nonsteroidal anti-inflammatory drugs (NSAIDs) in patients with heart failure (HF): a "commercial" and a locally "customized" alert. METHODS: We conducted a retrospective cohort study of 2 CDS tools implemented within a large integrated health system. The commercial CDS tool was designed according to third-party drug content and EHR vendor specifications. The customized CDS tool underwent a user-centered design process informed by implementation science principles, with input from a cross disciplinary team. The customized CDS tool replaced the commercial CDS tool. Data were collected from the electronic health record via analytic reports and manual chart review. The primary outcome was effectiveness, defined as whether the clinician changed their behavior and did not prescribe an NSAID. RESULTS: A random sample of 366 alerts (183 per CDS tool) was evaluated that represented 355 unique patients. The commercial CDS tool was effective for 7 of 172 (4%) patients, while the customized CDS tool was effective for 81 of 183 (44%) patients. After adjusting for age, chronic kidney disease, ejection fraction, NYHA class, concurrent prescription of an opioid or acetaminophen, visit type (inpatient or outpatient), and clinician specialty, the customized alerts were at 24.3 times greater odds of effectiveness compared to the commercial alerts (OR: 24.3 CI: 10.20-58.06). CONCLUSION: Investing additional resources to customize a CDS tool resulted in a CDS tool that was more effective at reducing the total number of NSAID orders placed for patients with HF compared to a commercially available CDS tool.

Clinician challenges to evidence-based prescribing for heart failure and reduced ejection fraction: A qualitative evaluation.

BACKGROUND: Reasons for suboptimal prescribing for heart failure with reduced ejection fraction (HFrEF) have been identified, but it is unclear if they remain relevant with recent advances in healthcare delivery and technologies. This study aimed to identify and understand current clinician-perceived challenges to prescribing guideline-directed HFrEF medications. METHODS: We conducted content analysis methodology, including interviews and member-checking focus groups with primary care and cardiology clinicians. Interview guides were informed by the Cabana Framework. RESULTS: We conducted interviews with 33 clinicians (13 cardiology specialists, 22 physicians) and member checking with 10 of these. We identified four levels of challenges from the clinician perspective. Clinician level challenges included misconceptions about guideline recommendations, clinician assumptions (e.g., drug cost or affordability), and clinical inertia. Patient-clinician level challenges included misalignment of priorities and insufficient communication. Clinician-clinician level challenges were primarily between generalists and specialists, including lack of role clarity, competing priorities of providing focused versus holistic care, and contrasting confidence regarding safety of newer drugs. Policy and system/organisation level challenges included insufficient access to timely/reliable patient data, and unintended care gaps for medications without financially incentivized metrics. CONCLUSION: This study presents current challenges faced by cardiology and primary care which can be used to strategically design interventions to improve guideline-directed care for HFrEF. The findings support the persistence of many challenges and also sheds light on new challenges. New challenges identified include conflicting perspectives between generalists and specialists, hesitancy to prescribe newer medications due to safety concerns, and unintended consequences related to value-based reimbursement metrics for select medications.

EHR-Integrated Clinical Pathways Promote Education, Confidence, and Save Time for Primary Care Providers.

Computerized clinical decision support tools are increasingly necessary and widespread in primary care due to rapidly evolving evidence and shifting clinical guidelines. Clinical pathways are a subtype of clinical decision support tool which aim to link evidence to practice and which require evaluation of benefits and barriers to use to inform user-centered design. The objective was to describe the use and perceived benefits and barriers to evidence-based, disease-specific electronic health record pathways for clinical decision support. Primary care providers at a large integrated health system were surveyed about their use of clinical pathways using an online questionnaire distributed via email in November 2021. Descriptive statistics were estimated and differences in the characteristics and responses by pathway use were assessed using chi-square or Fisher exact tests. The survey response rate was 26% (153/593). There were differences in the response rates between providers by practice type (42% academic versus 54% community; P < 0.001). No difference was found in the demographics of those that used the pathways versus those that did not according to role, age, or length of time in practice. Providers in the academic practice were more likely than those in community practices to have used the pathways. Among providers who used the pathways, 98% agree they have evidence-based information, 98% agree they allow them to take better care of patients, 88% agree they guide clinical-decisions, and 85% agree they save time. The main barrier for those who had used pathways was that they forget about them. Among those who had not used pathways, 35% were unaware that pathways existed. This analysis demonstrates that primary care providers who adopt clinical pathways perceive benefits in several domains. The largest barriers to adoption were that users forgot about pathways or were unaware of them. Future work should focus on dissemination and education, improving tool accessibility, and content optimization to balance complexity with efficiency.

PATHWEIGH, pragmatic weight management in adult patients in primary care in Colorado, USA: study protocol for a stepped wedge cluster randomized trial.

BACKGROUND: Despite the overwhelming prevalence and health implications of obesity, it is rarely adequately addressed in a health care setting. PATHWEIGH is a pragmatic approach to weight management that uses tools built into the electronic medical record to overcome barriers and guide care. Implementation strategies are employed to facilitate adoption and use of the PATHWEIGH tools and processes. The current study will compare the effectiveness of PATHWEIGH versus standard of care (SOC) on patient weight loss in primary care and explore factors for its successful implementation. METHODS: A stepped wedge cluster randomized trial design will be used within an effectiveness-implementation hybrid study. Adult patient weight loss and weight loss maintenance will be compared in PATHWEIGH versus SOC in 57 family and internal medicine clinics in a large health system in Colorado, USA. Effectiveness will be evaluated using generalized linear mixed models to determine statistical differences in weight loss and weight loss maintenance at 6, 12, and 18 months. Patient-, provider-, and clinic-level predictors will be identified using mediator and moderator analyses. Conceptually guided by the Practical, Robust, Implementation and Sustainability Model (PRISM), a mixed methods approach including quantitative (practice surveys, use tracking) and qualitative (interviews, observations) data collection will be used to determine factors impeding and facilitating adoption, implementation, and maintenance of PATHWEIGH and evaluate specified implementation strategies. A cost analysis of the practice and system costs and resources required by PATHWEIGH relative to the reimbursement collected will be performed. DISCUSSION: The effectiveness and implementation of PATHWEIGH, and their interrelatedness, for patient weight loss are collectively the focus of the current trial. Findings from this study are expected to serve as a blueprint for available and effective weight management in primary care medical practice. TRIAL REGISTRATION: ClinicalTrials.gov NCT04678752 . Registered on December 21, 2020.

Development and Validation of a Clinical Prognostic Stage Group System for Nonmetastatic Prostate Cancer Using Disease-Specific Mortality Results From the International Staging Collaboration for Cancer of the Prostate.

Importance: In 2016, the American Joint Committee on Cancer (AJCC) established criteria to evaluate prediction models for staging. No localized prostate cancer models were endorsed by the Precision Medicine Core committee, and 8th edition staging was based on expert consensus. Objective: To develop and validate a pretreatment clinical prognostic stage group system for nonmetastatic prostate cancer. Design, Setting, and Participants: This multinational cohort study included 7 centers from the United States, Canada, and Europe, the Shared Equal Access Regional Cancer Hospital (SEARCH) Veterans Affairs Medical Centers collaborative (5 centers), and the Cancer of the Prostate Strategic Urologic Research Endeavor (CaPSURE) registry (43 centers) (the STAR-CAP cohort). Patients with cT1-4N0-1M0 prostate adenocarcinoma treated from January 1, 1992, to December 31, 2013 (follow-up completed December 31, 2017). The STAR-CAP cohort was randomly divided into training and validation data sets; statisticians were blinded to the validation data until the model was locked. A Surveillance, Epidemiology, and End Results (SEER) cohort was used as a second validation set. Analysis was performed from January 1, 2018, to November 30, 2019. Exposures: Curative intent radical prostatectomy (RP) or radiotherapy with or without androgen deprivation therapy. Main Outcomes and Measures: Prostate cancer-specific mortality (PCSM). Based on a competing-risk regression model, a points-based Score staging system was developed. Model discrimination (C index), calibration, and overall performance were assessed in the validation cohorts. Results: Of 19 684 patients included in the analysis (median age, 64.0 [interquartile range (IQR), 59.0-70.0] years), 12 421 were treated with RP and 7263 with radiotherapy. Median follow-up was 71.8 (IQR, 34.3-124.3) months; 4078 (20.7%) were followed up for at least 10 years. Age, T category, N category, Gleason grade, pretreatment serum prostate-specific antigen level, and the percentage of positive core biopsy results among biopsies performed were included as variables. In the validation set, predicted 10-year PCSM for the 9 Score groups ranged from 0.3% to 40.0%. The 10-year C index (0.796; 95% CI, 0.760-0.828) exceeded that of the AJCC 8th edition (0.757; 95% CI, 0.719-0.792), which was improved across age, race, and treatment modality and within the SEER validation cohort. The Score system performed similarly to individualized random survival forest and interaction models and outperformed National Comprehensive Cancer Network (NCCN) and Cancer of the Prostate Risk Assessment (CAPRA) risk grouping 3- and 4-tier classification systems (10-year C index for NCCN 3-tier, 0.729; for NCCN 4-tier, 0.746; for Score, 0.794) as well as CAPRA (10-year C index for CAPRA, 0.760; for Score, 0.782). Conclusions and Relevance: Using a large, diverse international cohort treated with standard curative treatment options, a proposed AJCC-compliant clinical prognostic stage group system for prostate cancer has been developed. This system may allow consistency of reporting and interpretation of results and clinical trial design.