Factors Influencing Show Rates of Emergency Department Referrals to Primary Care Safety Net Clinics.

BACKGROUND: Utilization of emergency departments for non-urgent conditions has been a longstanding problem leading to excessive health care spending, unnecessary testing, and missed opportunities for patients to form longitudinal relationships with primary care clinicians. The Milwaukee Health Care Partnership established the Emergency Department Care Coordination program to decrease avoidable emergency department visits and connect high-risk individuals with primary care medical homes. Emergency department providers from 8 hospitals schedule patients to safety net clinics to establish follow-up care. During 2018 and 2019, there were 5,035 appointments scheduled, with a 43% show rate. This project aimed to identify factors influencing the show rate to follow-up appointments and to develop program interventions. METHODS: This project utilized a database of deidentified patient and referral information and performed logistic regressions to determine factors that influence show rates. RESULTS: There was a significant difference in show rates when looking at days between the emergency department visit and follow-up appointment, age, receiving clinic, and insurance status (all P > 0.001). Patients seen within 5 days of emergency department visit, patients 65 and older, and uninsured patients had increased likelihood of attending follow-up appointments. CONCLUSION: These results demonstrate that older adults are more likely to attend appointments, and more efforts are needed to engage younger people. The analysis shows the need to schedule patients with follow-up primary care quickly, as a short number of days from emergency department visit to primary care appointment was strongly correlated with a higher show rate. In addition, uninsured patients are good candidates for Emergency Department Care Coordination program referrals.

Analysis of Clinician and Patient Factors and Completion of Telemedicine Appointments Using Video.

Importance: Telemedicine provides patients access to episodic and longitudinal care. Policy discussions surrounding future support for telemedicine require an understanding of factors associated with successful video visits. Objective: To assess patient and clinician factors associated with successful and with failed video visits. Design, Setting, and Participants: This was a quality improvement study of 137 846 scheduled video visits at a single academic health system in southeastern Wisconsin between March 1 and December 31, 2020, supplemented with patient experience survey data. Patient information was gathered using demographic information abstracted from the electronic health record and linked with block-level socioeconomic data from the US Census Bureau. Data on perceived clinician experience with technology was obtained using the survey. Main Outcomes and Measures: The primary outcome of interest was the successful completion of a scheduled video visit or the conversion of the video visit to a telephone-based service. Visit types and administrative data were used to categorize visits. Mixed-effects modeling with pseudo R2 values was performed to compare the relative associations of patient and clinician factors with video visit failures. Results: In total, 75 947 patients and 1155 clinicians participated in 137 846 scheduled video encounters, 17 190 patients (23%) were 65 years or older, and 61 223 (81%) patients were of White race and ethnicity. Of the scheduled video encounters, 123 473 (90%) were successful, and 14 373 (10%) were converted to telephone services. A total of 16 776 patients (22%) completed a patient experience survey. Lower clinician comfort with technology (odds ratio [OR], 0.15; 95% CI, 0.08-0.28), advanced patient age (66-80 years: OR, 0.28; 95% CI, 0.26-0.30), lower patient socioeconomic status (including low high-speed internet availability) (OR, 0.85; 95% CI, 0.77-0.92), and patient racial and ethnic minority group status (Black or African American: OR, 0.75; 95% CI, 0.69-0.81) were associated with conversion to telephone visits. Patient characteristics accounted for systematic components for success; marginal pseudo R2 values decreased from 23% (95% CI, 21.1%-26.1%) to 7.8% (95% CI, 6.3%-9.4%) with exclusion of patient factors. Conclusions and Relevance: As policy makers consider expanding telehealth coverage and hospital systems focus on investments, consideration of patient support, equity, and friction should guide decisions. In particular, this quality improvement study suggests that underserved patients may become disproportionately vulnerable by cuts in coverage for telephone-based services.