Factors Affecting Healthcare Provider Referral to Heart Function Clinics: A Mixed-Methods Study

Factors Influencing Primary Care Physicians' Intent to Refer Patients With Hypertension to a Digital Remote Blood Pressure Monitoring Program: Mixed Methods Study

BACKGROUND

Primary care physicians' (PCP) referral rates to digital health programs are highly variable. This study explores whether knowledge of the digital remote blood pressure monitoring (RBPM) program and information on referral patterns influence PCPs' intention to refer patients.

OBJECTIVE

This study aims to examine the relationship between PCPs' knowledge of the digital RBPM program and information on their own prior referral rates versus their own with their peers' referral rates and their likelihood to refer patients to the digital RBPM program.

METHODS

This is a mixed methods study integrating quantitative analysis of electronic health record data regarding the frequency of PCPs' referrals of patients with hypertension to a digital health program and quantitative and qualitative analyses of survey data about PCPs' knowledge of the program and their intention to refer patients. PCPs responded to a clinical vignette featuring an eligible patient. They were randomized to either receive their own referral rate or their own plus their peers' referral rate. They were assessed on their intent to refer eligible future patients. Descriptive and multivariable linear regression analyses examined participant characteristics and the factors associated with their intent to refer patients. Narrative reasons for their intention to refer were thematically analyzed.

RESULTS

Of the 242 eligible PCPs invited to participate, 31% (n=70) responded to the survey. From electronic health record data, the mean referral rate of patients per PCP was 11.80% (SD 13.30%). The mean self-reported knowledge of the digital health program was 6.47 (SD 1.81). The mean likelihood of referring an eligible patient (on a scale of 0 to 10, with 0 being not at all, and 10 being definitely) based on a vignette was 8.54 (SD 2.12). The own referral data group's mean likelihood to refer was 8.91 (SD 1.28), whereas the own plus peer prior referral data group was 8.35 (SD 2.19). Regression analyses suggested the intention to refer the vignette patient was significantly associated with their knowledge (coefficient 0.46, 95% CI 0.20-0.73; P<.001), whereas the intention to refer future patients was significantly associated with their intent to refer the patient in the vignette (coefficient 0.62, 95% CI 0.46-0.78; P<.001). No evidence of association was found on receiving own plus peer referral data compared with own referral data and intent to refer future patients (coefficient 0.23, 95% CI -0.43 to 0.89; P=.48).

CONCLUSIONS

Physicians' intention to refer patients to a novel digital health program can be extrapolated by examining their intention to refer an eligible patient portrayed in a vignette, which was found to be significantly influenced by their knowledge of the program. Future efforts should engage PCPs to better inform them so that more patients can benefit from the digital health program.

Heart failure clinic inclusion and exclusion criteria: cross-sectional study of clinic's and referring provider's perspectives

OBJECTIVES

There are substantial variations in entry criteria for heart failure (HF) clinics, leading to variations in whom providers refer for these life-saving services. This study investigated actual versus ideal HF clinic inclusion or exclusion criteria and how that related to referring providers' perspectives of ideal criteria.

DESIGN, SETTING AND PARTICIPANTS

Two cross-sectional surveys were administered via research electronic data capture to clinic providers and referrers (eg, cardiologists, family physicians and nurse practitioners) across Canada.

MEASURES

Twenty-seven criteria selected based on the literature and HF guidelines were tested. Respondents were asked to list any additional criteria. The degree of agreement was assessed (eg, Kappa).

RESULTS

Responses were received from providers at 48 clinics (37.5% response rate). The most common actual inclusion criteria were newly diagnosed HF with reduced or preserved ejection fraction, New York Heart Association class IIIB/IV and recent hospitalisation (each endorsed by >74% of respondents). Exclusion criteria included congenital aetiology, intravenous inotropes, a lack of specialists, some non-cardiac comorbidities and logistical factors (eg, rurality and technology access). There was the greatest discordance between actual and ideal criteria for the following: inpatient at the same institution (κ=0.14), congenital heart disease, pulmonary hypertension or genetic cardiomyopathies (all κ=0.36). One-third (n=16) of clinics had changed criteria, often for non-clinical reasons. Seventy-three referring providers completed the survey. Criteria endorsed more by referrers than clinics included low blood pressure with a high heart rate, recurrent defibrillator shocks and intravenous inotropes-criteria also consistent with guidelines.

CONCLUSIONS

There is considerable agreement on the main clinic entry criteria, but given some discordance, two levels of clinics may be warranted. Publicising evidence-based criteria and applying them systematically at referral sources could support improved HF patient care journeys and outcomes.