Faculty Bibliography

OBJECTIVE:We examined drive times to outpatient substance use disorder treatment providers that provide contingency management (CM) and those that integrate CM with medication for opioid use disorder (MOUD) services in 6 US states. METHODS:We completed cross-sectional geospatial analysis among census tracts in Delaware, Louisiana, Massachusetts, North Carolina, New York, and West Virginia. We excluded census tracts with a population of zero. Using data from the 2020 Shatterproof substance use treatment facility survey, our outcome was the minimum drive time in minutes from the census tract mean center of population to the nearest outpatient CM provider, outpatient CM provider with MOUD services, and federally qualified health centers (FQHC). We stratified census tracts by 2010 Rural-Urban Commuting Area codes and by state. RESULTS:The population was greater than zero in 11,719 of 11,899 census tracts. The median drive time to the nearest CM provider was 12.2 [interquartile range (IQR), 7.0-23.5) minutes and the median drive time to the nearest CM provider increased from 9.7 (IQR, 6.0-15.0) minutes in urban census tracts to 38.8 (IQR, 25.4-53.0) minutes in rural (H = 3683, P < 0.001). The median drive time increased to the nearest CM provider with MOUD services [14.2 (IQR, 7.9-29.5) minutes, W = 18,877, P < 0.001] and decreased to the nearest FQHC [7.9 (IQR, 4.3-13.6) minutes, W = 11,555,894, P < 0.001]. CONCLUSIONS:These results suggest limited availability of CM, particularly within rural communities and for patients needing concurrent CM and MOUD treatment. Our results suggest greater adoption of CM within FQHCs could reduce urban-rural disparities in CM availability.

INTRODUCTION/OBJECTIVE:Previous studies have evaluated the implementation of standardized social determinants of health (SDOH) screening within healthcare settings, however, less is known about where screening gaps may exist following initial implementation based on facility characteristics. The objective of this study is to assess differences in screening rates for SDOH at a large, urban healthcare system. METHODS:We used electronic health record data obtained from NYC Health + Hospitals primary care sites from 2019 to 2022. We calculated the mean number of visits that were SDOH screened by visit type, facility size, and the percentages of community characteristics. We conducted 4 logistic regression models predicting the odds of screening for any SDOH and for specific SDOH needs (housing, food, and medical cost assistance) based on facility type, facility size, and the socioeconomic characteristics of the surrounding community. RESULTS:Among the 3 212 650 visits included, 16.90% were SDOH screened. Across all 4 multivariate logistic regression models predicting SDOH screening, a visit had significantly lower odds of being screened if based at a midsize or small facility, if it was a telemedicine visit, or based at a facility located in a zip-code with a higher percentage of SDOH needs. CONCLUSIONS:Our study found important differences in SDOH screening rates at a large, NYC-based health system based on size, visit type, and community level characteristics. In particular, our findings point to barriers related to facility size and telemedicine workflow that should be addressed to increase uptake of SDOH screening within different visits and facility types.

RATIONALE/BACKGROUND:During the coronavirus disease pandemic, audio-only and video telehealth visits became more widely available, but the relative patient satisfaction between telehealth and in-person modalities is not well-described. AIMS AND OBJECTIVES/OBJECTIVE:Our objective was to compare patient satisfaction with audio-only, video, and in-person adult primary care visits at a large, urban public healthcare system. METHODS:In this cross-sectional study, we used aggregated data from Press Ganey patient satisfaction surveys at 17 primary care facilities at New York City Health + Hospitals for visits between 1 June 2021 to 30 November 2021. We compared mean scores for questions common to surveys for each modality in domains of Access, Care Provider, and Overall Assessment using pairwise comparisons with two-tailed t-tests. RESULTS:There were 7,183/79,562 (9.0%) respondents for in-person visits and 1,009/15,092 (6.7%) respondents for telehealth visits. Compared to respondents for in-person visits, respondents for telehealth visits were more likely to be aged 35-64 years, Asian, and speak English as their primary language, and less likely to be ≥65 years old, Black or other race, and speak Spanish or another language as their primary language (p < 0.001). Patients reported higher mean satisfaction for Access measures for telehealth visits than in-person visits (p < 0.001). For Care Provider satisfaction questions, video visits generally had higher mean scores than in-person and, in turn, audio-only visits. For Overall Assessment questions, video visits had higher mean scores than in-person and, subsequently, audio-only visits. CONCLUSION/CONCLUSIONS:Of the visit modalities, video visits had the highest mean satisfaction scores across all domains. Telehealth may improve experiences with access, but audio-only visits may provide poorer visit experiences.

BACKGROUND:Appointment non-attendance has clinical, operational, and financial implications for patients and health systems. How telehealth services are associated with non-attendance in primary care is not well-described, nor are patient characteristics associated with telehealth non-attendance. OBJECTIVE:We sought to compare primary care non-attendance for telehealth versus in-person visits and describe patient characteristics associated with telehealth non-attendance. DESIGN/METHODS:An observational study of electronic health record data. PARTICIPANTS/METHODS:Patients with primary care encounters at 23 adult primary care clinics at a large, urban public healthcare system from November 1, 2019, to August 31, 2021. MAIN MEASURES/METHODS:We analyzed non-attendance by modality (telephone, video, in-person) during three time periods representing different availability of telehealth using hierarchal multiple logistic regression to control for patient demographics and variation within patients and clinics. We stratified by modality and used hierarchal multiple logistic regression to assess for associations between patient characteristics and non-attendance in each modality. KEY RESULTS/RESULTS:There were 1,219,781 scheduled adult primary care visits by 329,461 unique patients: 754,149 (61.8%) in-person, 439,295 (36.0%) telephonic, and 26,337 (2.2%) video visits. Non-attendance for telephone visits was initially higher than that for in-person visits (adjusted odds ratio 1.04 [95% CI 1.02, 1.07]) during the early telehealth availability period, but decreased later (0.82 [0.81, 0.83]). Non-attendance for video visits was higher than for in-person visits during the early (4.37 [2.74, 6.97]) and later (2.02 [1.95, 2.08]) periods. Telephone visits had fewer differences in non-attendance by demographics; video visits were associated with increased non-attendance for patients who were older, male, had a primary language other than English or Spanish, and had public or no insurance. CONCLUSIONS:Telephonic visits may improve access to care and be more easily adoptable among diverse populations. Further attention to implementation may be needed to avoid impeding access to care for certain populations using video visits.

LEARNING OBJECTIVES:After studying this article, the participant should be able to: 1. Understand the autologous graft options available to the rhinoplasty surgeon, including septal cartilage, auricular cartilage, costal cartilage, and bone. 2. Understand the autograft and allograft options available to the rhinoplasty surgeon, including cadaveric costal cartilage, silicone, Medpor, and Gore-Tex. 3. Identify the ideal situations to use each of these implant materials. 4. Understand the advantages and disadvantages of the different autografts, allografts, and implants in rhinoplasty. SUMMARY:This review focuses on the graft options available to the modern rhinoplasty surgeon. Autologous options are varied in the quality of cartilage harvested and the morbidity of the donor site. In addition, surgeons should understand the allograft options should autologous grafting be unfeasible or undesirable. New technological advances in processing of allograft cartilage makes this an attractive secondary option.

BACKGROUND:Hospitalist physicians' workload-the total number of patients they care for daily-is rising in the U.S. Hospitalists report that increased workload negatively affects patients care. OBJECTIVE:Measure the associations between hospitalist physicians' workload and clinical outcomes. DESIGN, SETTINGS, AND PARTICIPANTS/METHODS:Observational study, using electronic health record (EHR) data, of adults hospitalized on the hospitalist service at Yale-New Haven Hospital from 2015-2018. MAIN OUTCOME AND MEASURES/METHODS:We defined hospitalists' workload as the number of patients they cared for on the first full hospital day of a given patient's encounter. We used multilevel Poisson and logistic regression to examine associations between workload and length of stay (LOS), return to the Emergency Department (ED), and readmission. We adjusted for sociodemographic factors, patient complexity and severity of illness, and weekend admission (for LOS) or discharge (for ED visits or readmission). RESULTS:We analyzed 38,141 hospitalizations. Median patient age was 64 years (IQR 51-78 years), 53% were female, and 34% were nonwhite. Mean workload was 15 patients (SD 3 patients; range 10-34 patients). LOS was prolonged by 0.05 days (95% CI 0.02, 0.08; p(0.001) when comparing the 75th workload percentile (16 patients) to the 25th workload percentile (13 patients). There were no associations between workload and ED visits or readmission within 7 and 30 days. CONCLUSIONS:There was a statistically significant but modest relationship between workload and LOS; workload was not associated with ED visits or readmissions.Given clinical reports of the deleterious effects of increased hospitalist workload, there is a need for prospective research assessing a range of outcomes, beyond those measurable in contemporary EHR data.

Although the Affordable Care Act requires nonprofit hospital organizations to report how they identify and invest in community health needs, the utility of mandated reporting documents for tracking investments in the social determinants of health has been questioned. Using public reporting documents and focusing on housing as a social determinant of health, we describe how nonprofit hospital organizations in 5 communities with the highest rates of homelessness document needs and investments related to housing on their Community Health Needs Assessments, Implementation Strategies, and Schedule H (990H) tax forms. Of 47 organizations, 55% identified housing as a health need, 36% described housing-related implementation strategies, and 26% reported relevant 990H spending. Overall concordance among identified needs, strategies, and spending was low, with only 15% of organizations addressing housing across all 3 documents. Regulatory reform could help promote accountability and transparency in organizations' efforts to address housing and other health-related social needs.

Telehealth services may improve access to care, but there are concerns around whether availability of telehealth may increase care utilization. We assessed whether usage of telehealth was associated with differential primary care utilization at a large, urban public healthcare system. Using electronic health record data from 23 primary care clinics, we categorized patients as telehealth users and non-users. Then, we compared the number of visits per patient between groups using Welch's t-tests while stratifying by comorbidity count. We used multivariable Poisson regression to test for associations between telehealth usage and visit count while controlling for other demographic factors. Compared with telehealth non-users, telehealth users had approximately 1 more primary care visit per patient over the year regardless of comorbidity count or other patient characteristics. Availability of telehealth services may be associated with increased primary care utilization in a safety-net setting, though further research on outcomes, costs of care, and patient and clinician experiences is needed to better inform decisions regarding provision and reimbursement of telehealth services.