Differences in Telehealth During COVID-19 Between Commercial and Medicaid Enrollees

Objectives: To compare how in-person evaluation and management (E&M) visits and telehealth use differed during the COVID-19 pandemic between commercially insured and Medicaid enrollees, and to assess how insurance plan type—fee-for-service (FFS) vs managed care (MC)—and enrollee characteristics contributed to these differences. Study Design: Retrospective cohort analysis of 2019 and 2020 data from the commercially insured California Public Employees' Retirement System (CalPERS) and the California Medicaid program (Medi-Cal). Am J Manag Care. 2023;29(1):In Press _____ Takeaway Points * Increased use of telehealth during the COVID-19 pandemic has raised concerns about equitable access among lower-resourced populations, but few direct comparisons of telehealth use exist. * Compared with enrollees in a large, commercially insured managed care plan, Medicaid managed care enrollees had lower use of telehealth. * However, compared with enrollees in a large, commercially insured fee-for-service plan, Medicaid fee-for-service enrollees had higher use of telehealth. * Both insurer and plan type interact to affect uptake of telehealth, indicating heterogeneity that policy makers may wish to address when writing future telehealth policies. _____ The COVID-19 pandemic prompted a large shift to the provision of telehealth, due to benefits that include reduced risks of COVID-19 transmission and more convenient access to care. CalPERS enrollees select their insurance plan from several options, including a fully integrated health plan offered by Kaiser Permanente, several non-Kaiser health maintenance organization (HMO) plans, and preferred provider organization (PPO) plans.

Differences in telehealth during COVID-19 between commercial and Medicaid enrollees.

OBJECTIVES: To compare how in-person evaluation and management (E&M) visits and telehealth use differed during the COVID-19 pandemic between commercially insured and Medicaid enrollees, and to assess how insurance plan type-fee-for-service (FFS) vs managed care (MC)-and enrollee characteristics contributed to these differences. STUDY DESIGN: Retrospective cohort analysis of 2019 and 2020 data from the commercially insured California Public Employees' Retirement System (CalPERS) and the California Medicaid program (Medi-Cal). METHODS: We conducted unadjusted comparisons of per capita E&M visits and the share of visits conducted via telehealth by payer (CalPERS vs Medi-Cal) and plan type (FFS vs MC). We estimated linear regressions of telehealth use that adjusted for patient demographics, rurality, and internet access. Among Medi-Cal enrollees, we examined telehealth use differences based on race, language, and citizenship status. RESULTS: Regression-adjusted share of telehealth visits as a proportion of all E&M visits was 22.6% for CalPERS FFS patients (the reference group), 38.2% for Medi-Cal FFS patients, 46.0% for Medi-Cal MC patients, and 53.5% for CalPERS MC patients. Among Medi-Cal enrollees, telehealth use as a share of all E&M visits was higher among Spanish speakers, female enrollees, and rural enrollees. Across most demographic characteristics, Medi-Cal patients enrolled in FFS were less likely to receive telehealth compared with those enrolled in MC. CONCLUSIONS: During the first year of the COVID-19 pandemic, California MC enrollees had higher rates of telehealth use compared with FFS enrollees, regardless of insurer. Among FFS enrollees, those enrolled in Medicaid had higher rates of telehealth use compared with those insured by CalPERS. Telehealth policies should be aware of this heterogeneity, as well as its implications for equity of telehealth access.

Mental Health Service Utilization Rates Among Commercially Insured Adults in the US During the First Year of the COVID-19 Pandemic.

Importance: The COVID-19 pandemic has been associated with an elevated prevalence of mental health conditions and disrupted mental health care throughout the US. Objective: To examine mental health service use among US adults from January through December 2020. Design, Setting, and Participants: This cohort study used county-level service utilization data from a national US database of commercial medical claims from adults (age >18 years) from January 5 to December 21, 2020. All analyses were conducted in April and May 2021. Main Outcomes and Measures: Per-week use of mental health services per 10 000 beneficiaries was calculated for 5 psychiatric diagnostic categories: major depressive disorder (MDD), anxiety disorders, bipolar disorder, adjustment disorders, and posttraumatic stress disorder (PTSD). Changes in service utilization rates following the declaration of a national public health emergency on March 13, 2020, were examined overall and by service modality (in-person vs telehealth), diagnostic category, patient sex, and age group. Results: The study included 5 142 577 commercially insured adults. The COVID-19 pandemic was associated with more than a 50% decline in in-person mental health care service utilization rates. At baseline, there was a mean (SD) of 11.66 (118.00) weekly beneficiaries receiving services for MDD per 10 000 enrollees; this declined by 6.44 weekly beneficiaries per 10 000 enrollees (ß, -6.44; 95% CI, -8.33 to -4.54). For other disorders, these rates were as follows: anxiety disorders (mean [SD] baseline, 12.24 [129.40] beneficiaries per 10 000 enrollees; ß, -5.28; 95% CI, -7.50 to -3.05), bipolar disorder (mean [SD] baseline, 3.32 [60.39] beneficiaries per 10 000 enrollees; ß, -1.81; 95% CI, -2.75 to -0.87), adjustment disorders (mean [SD] baseline, 12.14 [129.94] beneficiaries per 10 000 enrollees; ß, -6.78; 95% CI, -8.51 to -5.04), and PTSD (mean [SD] baseline, 4.93 [114.23] beneficiaries per 10 000 enrollees; ß, -2.00; 95% CI, -3.98 to -0.02). Over the same period, there was a 16- to 20-fold increase in telehealth service utilization; the rate of increase was lowest for bipolar disorder (mean [SD] baseline, 0.13 [16.72] beneficiaries per 10 000 enrollees; ß, 1.40; 95% CI, 1.04-1.76) and highest for anxiety disorders (mean [SD] baseline, 0.20 [9.28] beneficiaries per 10 000 enrollees; ß, 9.12; 95% CI, 7.32-10.92). When combining in-person and telehealth service utilization rates, an overall increase in care for MDD, anxiety, and adjustment disorders was observed over the period. Conclusions and Relevance: In this cohort study of US adults, we found that the COVID-19 pandemic was associated with a rapid increase in telehealth services for mental health conditions, offsetting a sharp decline in in-person care and generating overall higher service utilization rates for several mental health conditions compared with prepandemic levels.

The Health Plan Environment In California Contributed To Differential Use Of Telehealth During The COVID-19 Pandemic.

The COVID-19 pandemic has led to substantial increases in the use of telehealth and virtual care in the US. Differential patient and provider access to technology and resources has raised concerns that existing health disparities may be extenuated by shifts to virtual care. We used data from one of the largest providers of employer-sponsored insurance, the California Public Employees' Retirement System, to examine potential disparities in the use of telehealth. We found that lower-income, non-White, and non-English-speaking people were more likely to use telehealth during the period we studied. These differences were driven by enrollment in a clinically and financially integrated care delivery system, Kaiser Permanente. Kaiser's use of telehealth was higher before and during the pandemic than that of other delivery models. Access to integrated care may be more important to the adoption of health technology than patient-level differences.

Spatial modeling of vaccine deserts as barriers to controlling SARS-CoV-2.

BACKGROUND: COVID-19 vaccine distribution is at risk of further propagating the inequities of COVID-19, which in the United States (US) has disproportionately impacted the elderly, people of color, and the medically vulnerable. We sought to measure if the disparities seen in the geographic distribution of other COVID-19 healthcare resources were also present during the initial rollout of the COVID-19 vaccine. METHODS: Using a comprehensive COVID-19 vaccine database (VaccineFinder), we built an empirically parameterized spatial model of access to essential resources that incorporated vaccine supply, time-willing-to-travel for vaccination, and previous vaccination across the US. We then identified vaccine deserts-US Census tracts with localized, geographic barriers to vaccine-associated herd immunity. We link our model results with Census data and two high-resolution surveys to understand the distribution and determinates of spatially accessibility to the COVID-19 vaccine. RESULTS: We find that in early 2021, vaccine deserts were home to over 30 million people, >10% of the US population. Vaccine deserts were concentrated in rural locations and communities with a higher percentage of medically vulnerable populations. We also find that in locations of similar urbanicity, early vaccination distribution disadvantaged neighborhoods with more people of color and older aged residents. CONCLUSION: Given sufficient vaccine supply, data-driven vaccine distribution to vaccine deserts may improve immunization rates and help control COVID-19.

COVID-19 has affected the elderly, people of color, and individuals with chronic illnesses more than the general population. Large barriers to accessing the COVID-19 vaccine could make this problem worse. We used a website called VaccineFinder, which has information on the location of most COVID-19 vaccine doses in the US, to measure vaccine accessibility in early 2021. We then identified vaccine deserts, defined as small US regions with poor access to the COVID-19 vaccine. We found that over 10% of the US lived in a vaccine desert. Overall, we found that vaccines were less available to people in rural areas, people of color, and individuals with chronic illnesses. It will be important to reverse this pattern and ensure enough vaccines are sent to these communities to help reduce the spread of COVID-19.

The association of strained ICU capacity with hospital patient racial and ethnic composition and federal relief during the COVID-19 pandemic.

OBJECTIVE: To identify the association between strained intensive care unit (ICU) capacity during the COVID-19 pandemic and hospital racial and ethnic patient composition, federal pandemic relief, and other hospital characteristics. DATA SOURCES: We used government data on hospital capacity during the pandemic and Provider Relief Fund (PRF) allocations, Medicare claims and enrollment data, hospital cost reports, and Social Vulnerability Index data. STUDY DESIGN: We conducted cross-sectional bivariate analyses relating strained capacity and PRF award per hospital bed with hospital patient composition and other characteristics, with and without adjustment for hospital referral region (HRR). DATA COLLECTION: We linked PRF data to CMS Certification Numbers based on hospital name and location. We used measures of racial and ethnic composition generated from Medicare claims and enrollment data. Our sample period includes the weeks of September 18, 2020 through November 5, 2021, and we restricted our analysis to short-term, general hospitals with at least one intensive care unit (ICU) bed. We defined "ICU strain share" as the proportion of ICU days occurring while a given hospital had an ICU occupancy rate ≥ 90%. PRINCIPAL FINDINGS: After adjusting for HRR, hospitals in the top tercile of Black patient shares had higher ICU strain shares than did hospitals in the bottom tercile (30% vs. 22%, p < 0.05) and received greater PRF amounts per bed ($118,864 vs. $92,407, p < 0.05). Having high versus low ICU occupancy relative to pre-pandemic capacity was associated with a modest increase in PRF amounts per bed after adjusting for HRR ($107,319 vs. $96,627, p < 0.05), but there were no statistically significant differences when comparing hospitals with high versus low ICU occupancy relative to contemporaneous capacity. CONCLUSIONS: Hospitals with large Black patient shares experienced greater strain during the pandemic. Although these hospitals received more federal relief, funding was not targeted overall toward hospitals with high ICU occupancy rates.

US Health Care Workforce Changes During the First and Second Years of the COVID-19 Pandemic.

This article quantifies changes in employment and average wages of employees of 6 key health care organizations during the COVID-19 pandemic.

US Health Care Workforce Changes During the First and Second Years of the COVID-19 Pandemic

This article quantifies changes in employment and average wages of employees of 6 key health care organizations during the COVID-19 pandemic.

The impact of the COVID-19 pandemic and policy response on health care utilization: Evidence from county-level medical claims and cellphone data.

The COVID-19 pandemic has forced federal, state, and local policymakers to respond by legislating, enacting, and enforcing social distancing policies. However, the impact of these policies on healthcare utilization in the United States has been largely unexplored. We examine the impact of county-level shelter in place ordinances on healthcare utilization using two unique datasets-employer-sponsored insurance for over 6 million people in the US and cell phone location data. We find that introduction of these policies was associated with reductions in the use of preventive care, elective care, and the number of weekly visits to physician offices, hospitals and other health care-related industries. However, controlling for county-level exposure to the COVID-19 pandemic as a way to account for the endogenous nature of policy implementation reduces the impact of these policies. Our results imply that while social distancing policies do lead to reductions in healthcare utilization, much of these reductions would have occurred even in the absence of these policies.

The Impact of the COVID-19 Pandemic and Policy Responses on Excess Mortality

As a way of slowing COVID-19 transmission, many countries and U.S. states implemented shelter-in-place (SIP) policies. However, the effects of SIP policies on public health are a priori ambiguous as they might have unintended adverse effects on health. The effect of SIP policies on COVID-19 transmission and physical mobility is mixed. To understand the net effects of SIP policies, we measure the change in excess deaths following the implementation of SIP policies in 43 countries and all U.S. states. We use an event study framework to quantify changes in the number of excess deaths after the implementation of a SIP policy. We find that following the implementation of SIP policies, excess mortality increases. The increase in excess mortality is statistically significant in the immediate weeks following SIP implementation for the international comparison only and occurs despite the fact that there was a decline in the number of excess deaths prior to the implementation of the policy. At the U.S. state-level, excess mortality increases in the immediate weeks following SIP introduction and then trends below zero following 20 weeks of SIP implementation. We failed to find that countries or U.S. states that implemented SIP policies earlier, and in which SIP policies had longer to operate, had lower excess deaths than countries/U.S. states that were slower to implement SIP policies. We also failed to observe differences in excess death trends before and after the implementation of SIP policies based on pre-SIP COVID-19 death rates.

The Impact of the COVID-19 Pandemic and Policy Response on Health Care Utilization: Evidence from County-level Medical Claims and Cellphone data

The COVID-19 pandemic has forced federal, state and local policymakers to respond by legislating, enacting, and enforcing social distancing policies. However, the impact of these policies on healthcare utilization in the United States has been largely unexplored. We examine the impact of county-level shelter in place ordinances on healthcare utilization using two unique datasets—employer-sponsored insurance for over 6 million people in the US and cell phone location data. We find that introduction of these policies was associated with reductions in the use of preventive care, elective care, and the number of weekly visits to physician offices and hospitals. However, controlling for county-level exposure to the COVID-19 pandemic reduces the impact of these policies. Our results imply that while social distancing policies do lead to reductions in healthcare utilization, much of these reductions would have occurred even in the absence of these policies.

Back to School: The Effect of School Visits During COVID-19 on COVID-19 Transmission

Schools across the United States and the world have been closed in an effort to mitigate the spread of COVID-19. However, the effect of school closure on COVID-19 transmission remains unclear. We estimate the causal effect of changes in the number of weekly visits to schools on COVID-19 transmission using a triple difference approach. In particular, we measure the effect of changes in county-level visits to schools on changes in COVID-19 diagnoses for households with school-age children relative to changes in COVID-19 diagnoses for households without school-age children. We use a data set from the first 46 weeks of 2020 with 130 million household-week level observations that includes COVID-19 diagnoses merged to school visit tracking data from millions of mobile phones. We find that increases in county-level in-person visits to schools lead to an increase in COVID-19 diagnoses among households with children relative to households without school-age children. However, the effects are small in magnitude. A move from the 25th to the 75th percentile of county-level school visits translates to a 0.3 per 10,000 household increase in COVID-19 diagnoses. This change translates to a 3.2 percent relative increase. We find larger differences in low-income counties, in counties with higher COVID-19 prevalence, and at later stages of the COVID-19 pandemic.

Association Between COVID-19 Relief Funds and Hospital Characteristics in the US.

Importance: In response to financial stress created by the reduction in care during the COVID-19 pandemic, hospitals received financial assistance through the Coronavirus Aid, Relief, and Economic Security (CARES) Act program. To date, the allocation of CARES Act funding is not well understood. Objective: To examine the disbursement of the High-Impact Distribution CARES Act funds and the association between financial assistance and hospital-level financial resources prior to the COVID-19 pandemic. Design Setting and Participants: This cross-sectional analysis of US-based hospitals and health systems assesses the hospital characteristics associated with CARES Act funding with linear regression models using linked hospital and health system-level information on CARES Act funding with hospital characteristics from Hospital Cost Report data. Exposures: Hospital and health system CARES Act financial assistance. Main Outcomes and Measures: Hospital and health system affiliation, status, and financial health prior to the COVID-19 pandemic. Data analysis took place from December 2020 through June 2021. Results: The analysis included 952 hospital-level entities with an average payment of $33.6 million, most of which was received during the first payment round. Wide ranges existed in CARES Act funding, with 24% of matched hospitals receiving less than $5 million in funding and 8% receiving more than $50 million. Academic-affiliated hospitals, hospitals with higher pre-COVID-19 assets and hospitals with higher COVID-19 cases received higher levels of funding, while critical access hospitals received lower levels of financial assistance. A 10% increase in hospital assets, endowment size, and COVID-19 cases was associated with 1.4% (95% CI, 0.8% to 2.0%; P = .003), 0.2% (95% CI, 0.1% to 0.3%; P < .001), and 3.5% (95% CI, 2.8% to 4.2%; P < .001) increases in CARES Act funding, respectively. Conclusions and Relevance: In this cross-sectional study of US hospitals and health systems, findings suggest that High-Impact Distribution CARES Act funds may have disproportionately gone to hospitals that were in a stronger financial situation prior to the pandemic compared with those that were not, but funds also went disproportionately to those that eventually had the most cases.

Vaccinations Against COVID-19 May Have Averted Up To 140,000 Deaths In The United States.

COVID-19 vaccination campaigns continue in the United States, with the expectation that vaccines will slow transmission of the virus, save lives, and enable a return to normal life in due course. However, the extent to which faster vaccine administration has affected COVID-19-related deaths is unknown. We assessed the association between US state-level vaccination rates and COVID-19 deaths during the first five months of vaccine availability. We estimated that by May 9, 2021, the US vaccination campaign was associated with a reduction of 139,393 COVID-19 deaths. The association varied in different states. In New York, for example, vaccinations led to an estimated 11.7 fewer COVID-19 deaths per 10,000, whereas Hawaii observed the smallest reduction, with an estimated 1.1 fewer deaths per 10,000. Overall, our analysis suggests that the early COVID-19 vaccination campaign was associated with reductions in COVID-19 deaths. As of May 9, 2021, reductions in COVID-19 deaths associated with vaccines had translated to value of statistical life benefit ranging between $625 billion and $1.4 trillion.

Assessing the Association Between Social Gatherings and COVID-19 Risk Using Birthdays.

Importance: Many policies designed to stop the spread of COVID-19 address formal gatherings, such as workplaces and dining locations. Informal social gatherings are a potentially important mode of SARS-CoV-2 transmission, but studying their role in transmission is challenged by data and methodological limitations; birthdays offer an opportunity to empirically quantify the potential role of small social gatherings in COVID-19 spread. Objective: To assess the association between social gatherings and SARS-CoV-2 transmission by studying whether COVID-19 rates increase after birthdays in a household. Design, Setting, and Participants: This cross-sectional study used nationwide data from January 1 to November 8, 2020, from 2.9 million US households with private insurance to compare COVID-19 infections between households with and without a birthday in the preceding 2 weeks, stratified according to county-level COVID-19 prevalence in that week and adjusting for household size and both week- and county-specific differences. The study also compared how birthday-associated infection rates differed by type of birthday (eg, child vs adult birthday, or a milestone birthday such as a 50th birthday), county-level precipitation on the Saturday of each week (which could move gatherings indoors), political leanings in the county, and state shelter-in-place policies. Main Outcomes and Measures: Household-level COVID-19 infection. Results: Among the 2.9 million households in the study, in the top decile of counties in COVID-19 prevalence, households with a birthday in the 2 weeks prior had 8.6 more diagnoses per 10 000 individuals (95% CI, 6.6-10.7 per 10 000 individuals) compared with households without a birthday in the 2 weeks prior, a relative increase of 31% above the county-level prevalence of 27.8 cases per 10 000 individuals, vs 0.9 more diagnoses per 10 000 individuals (95% CI, 0.6-1.3 per 10 000 individuals) in the fifth decile (P < .001 for interaction). Households in the tenth decile of COVID-19 prevalence had an increase in COVID-19 diagnoses of 15.8 per 10 000 persons (95% CI, 11.7-19.9 per 10 000 persons) after a child birthday, compared with an increase of 5.8 per 10 000 persons (95% CI, 3.7-7.9 per 10 000 persons) among households with an adult birthday (P < .001 in a test of interactions). No differences were found by milestone birthdays, county political leaning, precipitation, or shelter-in-place policies. Conclusions and Relevance: This cross-sectional study suggests that birthdays, which likely correspond with social gatherings and celebrations, were associated with increased rates of diagnosed COVID-19 infection within households in counties with high COVID-19 prevalence.

Trends in visits to substance use disorder treatment facilities in 2020.

OBJECTIVE: To describe weekly changes in the number of substance use disorder treatment (SUDT) facility visits in 2020 compared to 2019 using cell phone location data. METHODS: We calculated the percentage weekly change in visits to SUDT facilities from the week of January 5 through the week of October 11, 2020, relative to the week of January 6 through the week of October 13, 2019. We stratified facilities by county COVID-19 incidence per 10,000 residents in each week and by 2018 fatal drug overdose rate. Finally, we conducted a multivariable linear regression analysis examining percent change in visits per week as a function of county-level COVID-19 tercile, a series of calendar month indicators, and the interaction of county-level COVID-19 tercile and month. We repeated the regression analysis replacing COVID-19 tercile with overdose tercile. RESULTS: Beginning the eleventh week of 2020, the number of visits to SUDT facilities declined substantially, reaching a nadir of 48% of 2019 visits in early July. In contrast to January, there were significantly fewer visits in 2020 compared to 2019 in all subsequent months (p < 0.01 in all months). Multivariable regression results found that facilities in the tercile of counties experiencing the most COVID-19 cases had a significantly greater reduction in the number of SUDT visits in 2020 for the months of June through August than facilities in counties with the fewest COVID-19 rates (p < 0.05). The study found no statistically significant difference in the change in the number of visits by facilities in counties with historically different overdose rates. DISCUSSION: Our findings support the hypothesis that a reduction has occurred in the average weekly number of visits to SUDT facilities. The size of the effect differs based on the number of COVID-19 cases but not on historical overdose rate.

Use of buprenorphine for those with employer-sponsored insurance during the initial phase of the COVID-19 pandemic.

OBJECTIVE: To quantify weekly rates of use of buprenorphine for those with employer-based insurance and whether the rate differs based on county-level measures of race, historical fatal drug overdose rate, and COVID-19 case rate. METHODS: We used 2020 pharmaceutical claims for 4.8 million adults from a privately insured population to examine changes in the use of buprenorphine to treat opioid use disorder in 2020 during the onset of the COVID-19 pandemic. We quantified variation by examining changes in use rates across counties based on their fatal drug overdose rate in 2018, number of COVID-19 cases per capita, and percent nonwhite. RESULTS: Weekly use of buprenorphine was relatively stable between the first week of January (0.6 per 10,000 enrollees, 95%CI = 0.2 to 1.1) and the last week of August (0.8 per 10,000 enrollees, 95%CI = 0.4 to 1.3). We did not find evidence of any consistent change in use of buprenorphine by county-level terciles for COVID-19 rate as of August 31, 2020, age-adjusted fatal drug overdose rate, and percent nonwhite. Use was consistently higher for counties in the highest tercile of county age-adjusted fatal drug overdose rate when compared to counties in the lowest tercile of county age-adjusted fatal drug overdose rate. DISCUSSION: Our results provide early evidence that new federal- and state-level policies may have steadied the rate of using buprenorphine for those with employer-based insurance during the pandemic.