Faculty Bibliography

BACKGROUND/UNASSIGNED:Schedule design may contribute to successful completion of synchronous telehealth visits by video (versus audio-only). Clustering telehealth visits on schedules may minimize workflow inefficiencies. METHODS/UNASSIGNED:We analyzed data from 21 primary care sites in an urban public health care system from March 1 to September 30, 2022. We used linear regression to test for associations between the number of consecutive telehealth visits scheduled per clinicians' half-day sessions (1 to 9+) and the proportion of telehealth visits scheduled and, separately, completed as video (versus audio-only). RESULTS/UNASSIGNED:For each additional consecutive telehealth visit scheduled, there was a 6.85% [95% confidence interval 4.80 - 8.90%] increase in the absolute percentage of visits scheduled as video visits. For each additional consecutive telehealth visit scheduled, there was a 2.88% [0.59 - 5.18%] increase in the absolute percentage of visits completed as video visits. CONCLUSIONS/UNASSIGNED:Clustered telehealth visits are positively associated with scheduling and completion of telehealth visits by video.

This study examines whether patients' telehealth experiences differed during a health system mandate for telehealth encounters due to the COVID-19 pandemic versus after the mandate was relaxed. Patient experience surveys from telehealth visits across 17 adult (age 18+) primary care sites at a large, urban public health system were analyzed during two periods: when a mandate was active (March 1, 2020-June 30, 2020) and when the mandate was relaxed and any appointment modality was available (July 1, 2020-November 30, 2021). Primary outcomes were odds ratios (ORs) comparing top-box percentages of survey responses at multiple levels: individual questions, four domains, and all questions together as a composite. Key findings: Patients had higher odds of selecting top-box answers in the elective telehealth period for the Care Provider (1.09 [95% confidence interval 1.03, 1.16]) and General Assessment (1.13 [1.02, 1.24]) domains and the survey composite (1.08 [1.04, 1.13]), but there was no difference for individual questions.Women reported more positive experiences during the elective telehealth period in the Access (1.22 [1.01, 1.47]), Care Provider (1.32 [1.17, 1.50]), and Telemedicine Technology (1.24 [1.04, 1.50]) domains.Our findings suggest that patients had better telehealth experiences when mandates were relaxed.

RATIONALE:Video visits became more widely available during the coronavirus disease (COVID-19) pandemic. However, the ongoing role and value of video visits in care delivery and how these may have changed over time are not well understood. AIMS AND OBJECTIVES:Compare the relative complexity of in-person versus video visits during the COVID-19 pandemic and describe the complexity of video visits over time. METHODS:We used billing data for in-person and video revisits from non-behavioural health specialities with the most video visit utilisation (≥50th percentile) at a large, urban, public healthcare system from 1 January 2021 to 31 March 2022. We used current procedural terminology (CPT) codes as a proxy for information gathering and decision-making complexity and time spent on an encounter. We compared the distribution of CPT codes 99211-99215 between in-person and video visits using Fisher's exact tests. We used Spearman correlation to test for trends between proportions of CPT codes over time for video visits. RESULTS:Ten specialities (adult primary care, paediatrics, adult dermatology, bariatric surgery, paediatric endocrinology, obstetrics and gynaecologist, adult haematology/oncology, paediatric allergy/immunology, paediatric gastroenterology, and paediatric pulmonology) met inclusion criteria. For each speciality, proportions of each CPT code for in-person visits and for video visits varied significantly, and patterns of variation differed by speciality. For example, in adult primary care, video visits had smaller proportions of moderate/high complexity visits (99214 and 99215) and greater proportions of lower complexity visits (99211-99213) compared with in-person visits (p < 0.001), but in paediatric endocrinology, the opposite was seen (p < 0.001). Trends in CPT codes over time for video visits in each speciality were also mixed. CONCLUSION:In-person and video visits had differing proportions of complexity codes (typically skewing towards lower complexity for video visits). The complexity of video visits changed over time in many specialities. Observed patterns for both phenomena varied by speciality.

OBJECTIVES:Patient experience and presence of evidence-based facility services are 2 dimensions of assessing quality of addiction treatment facilities. However, the relationship between these two is not well described. The objective of this study was to explore associations between patient experience measures and service offerings at addiction treatment facilities. METHODS:We used data from cross-sectional surveys of addiction treatment facilities and persons involved in treatment at corresponding facilities to identify facility services (eg, availability of medications for alcohol use disorder, assistance with obtaining social services, etc) and patient experience measures (overall facility rating, extent helped by treatment, ability to deal with daily problems after treatment), respectively. We used hierarchical multiple logistic regression to test for associations between top-box scores for each patient experience outcome and facility services. RESULTS:We analyzed 9191 patient experience surveys from 149 facilities. Assistance with obtaining social services (adjusted odds ratio [95% confidence interval], 0.43 [0.28-0.66]) was associated with lower overall treatment facility ratings. Childcare (2.00 [1.04-3.84]) was associated with top-box scores for extent helped. Availability of cognitive behavioral therapy (2.67 [1.25-5.73]) and childcare (1.77 [1.08-2.92]) were associated with top-box scores for ability to deal with daily problems after treatment. Assistance with obtaining social services (0.61 [0.41-0.90]) was associated with lower scores for ability to deal with problems after treatment. CONCLUSIONS:Few addiction treatment facility services were associated with patient experience measures. Future work should explore bridging the gap between evidence-based services and positive patient experiences.

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.

OBJECTIVE:To assess rates of breast and cervical cancer screening at student-run free clinics to understand challenges and strategies for advancing quality and accessibility of women's health screening. METHODS:The authors performed a systematic search of publications in Ovid MEDLINE, PubMed, Web of Science, and Google Scholar databases from database inception to 2020. English-language publications assessing rates of breast and cervical cancer screening in student-run free clinics were included. Structured data extraction was completed for each publication by two reviewers independently. Risk of bias was assessed using a modified Agency for Healthcare Research and Quality checklist. Results were synthesized qualitatively because of study heterogeneity. RESULTS:Of 3634 references identified, 12 references met study inclusion criteria. The proportion of patients up-to-date on breast cancer screening per guidelines ranged from 45% to 94%. The proportion of patients up-to-date on cervical cancer screening per guidelines ranged from 40% to 88%. CONCLUSION/CONCLUSIONS:Student-run free clinics can match breast and cervical cancer screening rates among uninsured populations nationally, although more work is required to bridge the gap in care that exists for the underinsured and uninsured.

IMPORTANCE:Staffing shortages in nursing homes (NHs) threaten the quality of resident care, and the COVID-19 pandemic magnified critical staffing shortages within NHs. During the pandemic, the US Congress enacted the Paycheck Protection Program (PPP), a forgivable loan program that required eligible recipients to appropriate 60% to 75% of the loan toward staffing to qualify for loan forgiveness. OBJECTIVE:To evaluate characteristics of PPP loan recipient NHs vs nonloan recipient NHs and whether there were changes in staffing hours at NHs that received a loan compared with those that did not. DESIGN, SETTING, AND PARTICIPANTS:This economic evaluation used national data on US nursing homes that were aggregated from the Small Business Administration, Nursing Home Compare, LTCFocus, the Centers for Medicare & Medicaid Services Payroll Based Journal, the Minimum Data Set, the Area Deprivation Index, the Healthcare Cost Report Information System, and the US Department of Agriculture Rural-Urban Continuum Codes from January 1 to December 23, 2020. EXPOSURE:Paycheck Protection Program loan receipt status. MAIN OUTCOME AND MEASURES:Staffing variables included registered nurse, licensed practical nurse (LPN), and certified nursing assistant (CNA) total hours per week. Staffing hours were examined on a weekly basis before and after loan receipt during the study period. An event-study approach was used to estimate the staffing total weekly hours at NHs that received PPP loans compared with NHs that did not receive a PPP loan. RESULTS:Among 6008 US NHs, 1807 (30.1%) received a PPP loan and 4201 (69.9%) did not. The median loan amount was $664 349 (IQR, $407 000-$1 058 300). Loan recipients were less likely to be part of a chain (733 [40.6%] vs 2592 [61.7%]) and more likely to be for profit (1342 [74.3%] vs 2877 [68.5%]), be located in nonurban settings (159 [8.8%] vs 183 [4.4%]), have a greater proportion of Medicaid-funded residents (mean [SD], 60.92% [21.58%] vs 56.78% [25.57%]), and have lower staffing quality ratings (mean [SD], 2.88 [1.20] vs 3.03 [1.22]) and overall quality star ratings (mean [SD], 3.08 [1.44] vs 3.22 [1.44]) (P < .001 for all). Twelve weeks after PPP loan receipt, NHs that received a PPP loan experienced a mean difference of 26.19 more CNA hours per week (95% CI, 14.50-37.87 hours per week) and a mean difference of 6.67 more LPN hours per week (95% CI, 1.21-12.12 hours per week) compared with nursing homes that did not receive a PPP loan. No associations were found between PPP loan receipt and weekly RN staffing hours (12 weeks: mean difference, 1.99 hours per week; 95% CI, -2.38 to 6.36 hours per week). CONCLUSIONS AND RELEVANCE:In this economic evaluation, a forgivable loan program that required funding to be appropriated toward staffing was associated with a significant increase in CNA and LPN staffing hours among NH PPP loan recipients. Because the PPP loans are temporary, federal and state entities may need to institute sufficient and sustainable support to mitigate NH staffing shortages.

OBJECTIVES:This study aimed to describe addiction treatment facilities by their offerings of medications for alcohol use disorder (MAUD) and/or for opioid use disorder (MOUD), and by their offering services to groups with barriers to care: uninsured and publicly insured, youth, seniors, individuals preferring to receive care in Spanish, and sexual minority individuals. METHODS:We examined addiction treatment facility survey data in 6 US states. We performed bivariate analyses comparing facilities that offered MAUD, MOUD, and both (main outcomes). We then constructed a multivariable model to identify predictors of offering MAUD, MOUD, or both, including exposures that demonstrate programming for special populations. RESULTS:Among 2474 facilities, 1228 (50%) responded between October 2019 and January 2020. Programs were offered for youth (30%), elderly (40%), Spanish-speaking (37%), and sexual minority populations (39%), with 58% providing MAUD, 67% providing MOUD, and 56% providing both. Among those providing MAUD, MOUD, or both, a majority (>60% for all exposures) offered programming to vulnerable populations. With Delaware as reference, Louisiana (adjusted odds ratio [aOR], 0.28; 95% confidence interval [CI], 0.12-0.67) and North Carolina (aOR, 0.33; 95% CI, 0.15-0.72) facilities had lesser odds of offering both MAUD and MOUD. All exposures identifying facilities offering treatment to vulnerable groups were associated with offerings of MAUD and/or MOUD except for offerings to youth; these facilities had less odds of offering MOUD (aOR, 0.31; 95% CI, 0.31-0.62). CONCLUSIONS:There are facility-level disparities in providing MAUD and MOUD by state, and facilities with youth programming have lesser odds of offering MOUD than other facilities.

Understanding patient characteristics associated with scheduling and completing telehealth visits can identify potential biases or latent preferences related to telehealth usage. We describe patient characteristics associated with being scheduled for and completing audio and video visits. We used data from patients at 17 adult primary care departments in a large, urban public healthcare system from August 1, 2020 to July 31, 2021. We used hierarchical multivariable logistic regression to generate adjusted odds ratios (aOR) for patient characteristics associated with having been scheduled for and completed telehealth (vs in-person) visits and for video (vs audio) scheduling and completion during two time periods: a telehealth transition period (N = 190,949) and a telehealth elective period (N = 181,808). Patient characteristics were significantly associated with scheduling and completion of telehealth visits. Many associations were similar across time periods, but others changed over time. Patients who were older (≥ 65 years old vs 18-44 years old: aOR for scheduling 0.53/completion 0.48), Black (0.86/0.71), Hispanic (0.76/0.62), or had Medicaid (0.93/0.84) were among those less likely to be scheduled for or complete video (vs audio) visits. Patients with activated patient portals (1.97/3.34) or more visits (≥ 3 scheduled visits vs 1 visit: 2.40/1.52) were more likely to be scheduled for or complete video visits. Variation in scheduling/completion explained by patient characteristics was 7.2%/7.5%, clustering by provider 37.2%/34.9%, and clustering by facility 43.1%/37.4%. Stable and dynamic associations suggest persistent gaps in access and evolving preferences/biases. Variation explained by patient characteristics was relatively low compared with that explained by provider and facility clustering.

OBJECTIVES/OBJECTIVE:Patient experience and presence of evidence-based facility services are 2 dimensions of assessing quality of addiction treatment facilities. However, the relationship between these two is not well described. The objective of this study was to explore associations between patient experience measures and service offerings at addiction treatment facilities. METHODS:We used data from cross-sectional surveys of addiction treatment facilities and persons involved in treatment at corresponding facilities to identify facility services (eg, availability of medications for alcohol use disorder, assistance with obtaining social services, etc) and patient experience measures (overall facility rating, extent helped by treatment, ability to deal with daily problems after treatment), respectively. We used hierarchical multiple logistic regression to test for associations between top-box scores for each patient experience outcome and facility services. RESULTS:We analyzed 9191 patient experience surveys from 149 facilities. Assistance with obtaining social services (adjusted odds ratio [95% confidence interval], 0.43 [0.28-0.66]) was associated with lower overall treatment facility ratings. Childcare (2.00 [1.04-3.84]) was associated with top-box scores for extent helped. Availability of cognitive behavioral therapy (2.67 [1.25-5.73]) and childcare (1.77 [1.08-2.92]) were associated with top-box scores for ability to deal with daily problems after treatment. Assistance with obtaining social services (0.61 [0.41-0.90]) was associated with lower scores for ability to deal with problems after treatment. CONCLUSIONS:Few addiction treatment facility services were associated with patient experience measures. Future work should explore bridging the gap between evidence-based services and positive patient experiences.