Faculty Bibliography

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.

PURPOSE/UNASSIGNED:Hospital at home (HaH) is a means of providing inpatient-level care at home. Selection of admissions potentially suitable for HaH in oncology is not well studied. We sought to create a predictive model for identifying admissions of patients with cancer, specifically solid-tumor malignancies, potentially suitable for HaH. METHODS/UNASSIGNED:In this observational study, we analyzed admissions of patients with solid-tumor malignancies and unplanned admissions (January 1, 2015, to June 12, 2019) at an academic, urban cancer hospital. Potential suitability for HaH was the primary outcome. Admissions were considered potentially suitable if they did not involve escalation of care, rapid response evaluation, in-hospital death, telemetry, surgical procedure, consultation to a procedural service, advanced imaging, transfusion, restraints, and nasogastric tube placement. Admission source, patient demographics, vital signs, laboratory test results, comorbidities, admission and active cancer diagnoses, and recent hospital utilization were included as candidate variables in a multivariable logistic regression model. RESULTS/UNASSIGNED:Of 3,322 admissions, 905 (27.2%) patients were potentially suitable for HaH. After variable selection in the derivation cohort (n = 1,097), thirteen factors predicted potential suitability: admission source; temperature and respiratory rate at presentation; hemoglobin; breast cancer, GI cancer, or malignancy of secondary or ill-defined origin; admission for genitourinary, musculoskeletal, or neurologic symptoms, intestinal obstruction or ileus, or evaluation of secondary malignancy; and emergency department visit in prior 90 days. Model c-statistics were 0.71 (95% CI, 0.68 to 0.75) and 0.63 (0.59 to 0.67) in the derivation and validation (n = 1,095) cohorts. CONCLUSION/UNASSIGNED:Hospital admissions of patients potentially suitable for HaH may be identifiable using data available at admission.