Can telehealth expansion boost health care utilization specifically for patients with substance use disorders relative to patients with other types of chronic disease?

OBJECTIVE: Patients with substance use disorders (SUDs) exhibit low healthcare utilization despite high risk of poor outcomes. Telehealth expansion may boost utilization, but it is unclear whether telehealth can increase utilization for patients with SUDs beyond that expected for other chronic diseases amenable to remote treatment, like type 2 diabetes. This information is needed by health systems striving to improve SUD outcomes, specifically. This study compared the impact of telehealth expansion during the COVID-19 public health emergency (PHE) on utilization for patients with SUDs and diabetes. METHODS: Using Wisconsin Medicaid administrative, enrollment and claims data 12/1/2018-12/31/2020, this cohort study included nonpregnant, nondisabled adults 19-64 years with SUDs (N = 17,336) or diabetes (N = 8,499). Outcomes included having a primary care visit in the week (any, and telehealth) for any diagnosis, or a SUD or diabetes diagnosis; and the weekly fraction of visits completed by telehealth. Logistic and fractional regression examined outcomes pre- and post-PHE. Covariates included age, sex, race, ethnicity, income, geography, and comorbid medical and psychotic disorders. RESULTS: Post-PHE, patients with SUDs exhibited greater likelihood of telehealth utilization (percentage point difference (PPD) per person-week: 0.2; 95% CI: 0.001-0.003; p<0.001) and greater fractional telehealth use (PPD: 1.8; 95%CI: 0.002-0.033; p = 0.025) than patients with diabetes despite a larger overall drop in visits (PPD: -0.5; 95%CI: -0.007- -0.003; p<0.001). CONCLUSIONS: Following telehealth expansion, patients with SUDs exhibited greater likelihood of telehealth utilization than patients with diabetes. This advantage lessened the substantial PHE-induced healthcare disruption experienced by patients with SUDs. Telehealth may boost utilization for patients with SUDs.

How Does Telehealth Expansion Change Access to Healthcare for Patients With Different Types of Substance Use Disorders?

BACKGROUND: Patients with substance use disorders (SUDs) exhibit low healthcare utilization despite high medical need. Telehealth could boost utilization, but variation in uptake across SUDs is unknown. METHODS: Using Wisconsin Medicaid enrollment and claims data from December 1, 2018, to December 31, 2020, we conducted a cohort study of telemedicine uptake in the all-ambulatory and the primary care setting during telehealth expansion following the COVID-19 public health emergency (PHE) onset (March 14, 2020). The sample included continuously enrolled (19 months), nonpregnant, nondisabled adults aged 19 to 64 years with opioid (OUD), alcohol (AUD), stimulant (StimUD), or cannabis (CannUD) use disorder or polysubstance use (PSU). Outcomes: total and telehealth visits in the week, and fraction of visits in the week completed by telehealth. Linear and fractional regression estimated changes in in-person and telemedicine utilization. We used regression coefficients to calculate the change in telemedicine utilization, the proportion of in-person decline offset by telemedicine uptake ("offset"), and the share of visits completed by telemedicine ("share"). RESULTS: The cohort (n = 16 756) included individuals with OUD (34.8%), AUD (30.1%), StimUD (9.5%), CannUD (9.5%), and PSU (19.7%). Total and telemedicine utilization varied by group post-PHE. All-ambulatory: total visits dropped for all, then rose above baseline for OUD, PSU, and AUD. Telehealth expansion was associated with visit increases: OUD: 0.489, P < .001; PSU: 0.341, P < .001; StimUD: 0.160, P < .001; AUD: 0.132, P < .001; CannUD: 0.115, P < .001. StimUD exhibited the greatest telemedicine share. Primary care: total visits dropped for all, then recovered for OUD and CannUD. Telemedicine visits rose most for PSU: 0.021, P < .001; OUD: 0.019, P < .001; CannUD: 0.011, P < .001; AUD: 0.010, P < .001; StimUD: 0.009, P < .001. PSU and OUD exhibited the greatest telemedicine share, while StimUD exhibited the lowest. Telemedicine fully offset declines for OUD only. CONCLUSIONS: Telehealth expansion helped maintain utilization for OUD and PSU; StimUD and CannUD showed less responsiveness. Telehealth expansion could widen gaps in utilization by SUD type.

Telehealth Expansion, Internet Speed, and Primary Care Access Before and During COVID-19.

Importance: Primary care (PC) receipt is associated with better health outcomes. How telehealth expansion and internet speed are associated with PC use is unclear. Objective: To examine the association of telehealth and internet speed with PC use across sociodemographic determinants of health. Design, Setting, and Participants: This cohort study performed difference-in-differences regression of the change in in-person and telehealth PC visits between pre-COVID-19 public health emergency (PHE) (June 1, 2019, to February 29, 2020) and an initial (March 1, 2020, to May 31, 2020) and prolonged (March 1, 2020, to December 31, 2021) PHE period among continuously enrolled nonpregnant, nondisabled Wisconsin Medicaid beneficiaries aged 18 to 64 years. Data were analyzed from March 2022 to March 2023. Exposure: PHE-induced telehealth expansion. Main Outcomes and Measures: Change in PC telehealth (using Current Procedural Terminology codes) visits: (1) count; (2) visit share completed by telehealth; (3) percentage of PHE-induced visit decline offset by telehealth. High-speed internet (HSI) defined as living in a census block group with a median block maximum download speed of 940 megabits per second or greater (June 2020 Federal Communications Commission broadband data); other census block groups classified as low-speed internet (LSI). Results: In the total cohort of 172 387 participants, 102 989 (59.7%) were female, 103 848 (60.2%) were non-Hispanic White, 34 258 (19.9%) were non-Hispanic Black, 15 020 (8.7%) were Hispanic, 104 239 (60.5%) were aged 26 to 45 years, and 112 355 (66.0%) lived in urban counties. A total of 142 433 (82.6%) had access to HSI; 72 524 (42.1%) had a chronic condition. There was a mean (SD) of 0.138 (0.261) pre-PHE PC visits per month. In the pre-PHE period, visit rates were significantly higher for female than male participants, non-Hispanic White than non-Hispanic Black individuals, urban than rural residents, those with HSI than LSI, and patients with chronic disease than patients without. In the initial PHE period, female participants had a greater increase in telehealth visits than male participants (43.1%; 95% CI, 37.02%-49.18%; P < .001), share (2.20 percentage point difference [PPD]; 95% CI, 1.06-3.33 PPD; P < .001) and offset (6.81 PPD; 95% CI, 3.74-9.87 PPD; P < .001). Non-Hispanic Black participants had a greater increase in share than non-Hispanic White participants (5.44 PPD; 95% CI, 4.07-6.81 PPD; P < .001) and offset (15.22 PPD; 95% CI, 10.69-19.75 PPD; P < .001). Hispanic participants had a greater increase in telehealth visits than Non-Hispanic White participants (35.60%; 95% CI, 25.55%-45.64%; P < .001), share (8.50 PPD; 95% CI, 6.75-10.26 PPD; P < .001) and offset (12.93 PPD; 95% CI, 6.25-19.60 PPD; P < .001). Urban participants had a greater increase in telehealth visits than rural participants (63.87%; 95% CI, 52.62%-75.11%; P < .001), share (9.13 PPD; 95% CI, 7.84-10.42 PPD; P < .001), and offset (13.31 PPD; 95% CI; 9.62-16.99 PPD; P < .001). Participants with HSI had a greater increase in telehealth visits than those with LSI (55.23%; 95% CI, 42.26%-68.20%; P < .001), share (6.61 PPD; 95% CI, 5.00-8.23 PPD; P < .001), and offset (6.82 PPD; 95% CI, 2.15-11.49 PPD; P = .004). Participants with chronic disease had a greater increase in telehealth visits than those with none (188.07%; 95% CI, 175.27%-200.86%; P < .001), share (4.50 PPD; 95% CI, 3.58-5.42 PPD; P < .001), and offset (9.03 PPD; 95% CI, 6.01-12.04 PPD; P < .001). Prolonged PHE differences were similar. Differences persisted among those with HSI. Conclusions and Relevance: In this cohort study of Wisconsin Medicaid beneficiaries, greater telehealth uptake occurred in groups with higher pre-PHE utilization, except for high uptake among Hispanic and non-Hispanic Black individuals despite low pre-PHE utilization. HSI did not moderate disparities. These findings suggest telehealth and HSI may boost PC receipt, but will generally not close utilization gaps.

Trends in buprenorphine dosage and days supplied for new treatment episodes for opioid use disorder, 2010-2019.

BACKGROUND: Buprenorphine reduces risk of opioid overdose mortality. However, its benefits are limited by low retention, particularly in early treatment. Optimizing initial dosage may impact retention. However, little is known about the prescription characteristics of new buprenorphine treatment episodes. METHODS: In a US sample of commercial and employer-sponsored pharmacy claims, we identified new buprenorphine treatment episodes (days 1-30) from individuals ≥16 years following 90 days without buprenorphine from 2010 to 2019. Outcomes included first prescription average days supplied, first prescription average daily dosage, and average dosage on days 2, 8, 15 and 30. RESULTS: We identified 117,793 new episodes among 96,451 unique individuals. Episodes per 10,000 person-years decreased slightly over time. Stratifying by age, sex and region demonstrated decreasing episodes among individuals ≤34 years and increasing episodes among individuals ≥35 years. From 2010-2019, first prescription average days supplied and daily dosage decreased from 17.1 to 15.3 days and 13.6mg to 11.6mg, respectively. Simultaneously, the proportion of episodes without possession and with dosages <16mg increased across all days and years. By day 30, episodes without buprenorphine possession grew from 27.9% to 30.8% and episodes involving dosages of <16mg grew from 26.4% to 33.4%. CONCLUSIONS: We found that buprenorphine dosage and days supplied for new treatment episodes decreased from 2010 to 2019 while buprenorphine possession worsened. Further investigation examining the relationship between buprenorphine dosage and retention in the early treatment period is needed.

Health and Healthcare Access for Essential, Nonessential, and Nonworkers During the COVID-19 Pandemic.

OBJECTIVE: The aim of the study is to describe sociodemographic characteristics, healthcare access, and health status of low-income essential, nonessential, and nonworkers during the COVID-19 pandemic. METHODS: Using survey data (2020-2021) from Wisconsin Medicaid enrollees ( N = 2528), we compared sociodemographics, healthcare access, and health status between essential, nonessential, and nonworkers. RESULTS: Essential workers had less consistent health insurance coverage and more problems paying medical bills than nonessential and nonworkers. They reported better health than nonessential and nonworkers. They reported fewer work-limiting conditions and less outpatient healthcare utilization than nonworkers but similar rates as nonessential workers. Essential workers reported masking less frequently than nonworkers but similar frequency to nonessential workers, and lower COVID-19 vaccine willingness than nonessential and nonworkers. CONCLUSIONS: Essential workers report better health, fewer protective behaviors, and more healthcare barriers than nonessential and nonworkers. Findings indicate essential worker status may be a social determinant of health.

Differences in drug use behaviors that impact overdose risk among individuals who do and do not use fentanyl test strips for drug checking.

BACKGROUND: Opioid-involved overdose continues to rise, largely explained by fentanyl adulteration of the illicit opioid supply. Fentanyl test strips are a novel drug checking tool that can be used by people who use drugs to detect the presence of fentanyl in drug products. However, it is unclear whether fentanyl test strip use can prompt behavior changes that impact risk of overdose. METHODS: In this mixed-methods study involving a structured survey (n = 341) of syringe service program clients in southern Wisconsin, we examined the association between fentanyl test strip use and overdose risk behaviors in scenarios where the presence of fentanyl is confirmed and unknown. Individual items were transformed into summary scales representing the performance of riskier and safer behaviors. Linear regression examined the association of behaviors with FTS use. Models are adjusted for study site, race/ethnicity, age, gender, drug of choice, indicator of polysubstance use, times used per day, and lifetime overdose count. RESULTS: In response to survey questions before prompting about fentanyl risk, people who used fentanyl test strips reported an increased number of safer (p = 0.001) as well as riskier behaviors (p = 0.018) relative to people who did not use fentanyl test strips. The same held true in situations when fentanyl adulteration was suspected, though fentanyl test strip use lost significance in the fully adjusted model examining safer behaviors (safer: p = 0.143; riskier: p = 0.004). Among people who use fentanyl test strips, in unadjusted models, a positive test result was associated with more safer behaviors and fewer riskier behaviors, but these associations became nonsignificant in fully adjusted models (safer: p = 0.998; riskier: p = 0.171). Loss of significance was largely due to the addition of either polysubstance use or age to the model. CONCLUSIONS: Fentanyl test strip use is associated with behaviors that may impact overdose risk, including safer and riskier behaviors. Specifically, a positive test result may promote more risk reducing behaviors and fewer risk enhancing behaviors than a negative test result. Results suggest that while FTS may promote safer drug use behaviors, outreach and education should emphasize the need for multiple harm reduction techniques in all scenarios.

Characteristics and context of fentanyl test strip use among syringe service clients in southern Wisconsin.

BACKGROUND: Fentanyl adulteration of illicit drugs is a major driver of opioid-involved overdose in the USA. Fentanyl test strips are increasingly used by people who use drugs to check for fentanyl. However, little is known about factors that influence test strip use in this population. METHODS: In this mixed-methods study employing semi-structured open-ended interviews (n = 29) and a structured survey (n = 341), we examined characteristics associated with test strip use, characteristics of test strip use, and situational, logistical and psychosocial factors influencing test strip use. Respondents were recruited from a syringe service program in southern Wisconsin. Bivariate tests of association and multivariable logistic regression examined the relationship between respondent characteristics and test strip use. Summary statistics were used to describe how situational, logistical and psychosocial factors impact test strip use. RESULTS: Most respondents were male (59.6%), non-Hispanic white (77.4%), young (mean 35.7 years), reported heroin as their primary drug (70.7%), injection as their primary route (87.9%), and use ≥ 3 times daily (78.6%). In multivariable models, site, race and ethnicity, drug of choice, and seeking fentanyl were associated with test strip use. Among test strip users, 36.5% use them most of the time or more and 80.6% get positive results half the time or more. Among individuals reporting heroin, fentanyl, methamphetamine, or cocaine or crack cocaine at least once per month, 99.1%, 56.8%, 42.2%, and 55.7% reported testing these drugs, respectively. Test strip use is supported by information from suppliers, regular transportation, diverse distribution locations, recommendations from harm reduction staff, and having a safe or private place to use. CONCLUSIONS: We found that individuals who use fentanyl test strips are more often non-Hispanic white, use heroin, and seek drugs with fentanyl relative to individuals without test strip use. Findings confirm high fentanyl penetration in the Wisconsin drug supply. Low rates of stimulant testing suggest inadequate awareness of fentanyl penetration. Findings support outreach to key populations, increased diversity of distributing locations, efforts to correct misperceptions about drug wasting, emphasis on pre-consumption testing, and the importance of adjunct behaviors to prevent overdose given high rates of intentional fentanyl use.

Association between spine injury and opioid misuse in a prospective cohort of Level I trauma patients.

Objective: To explore patient and treatment factors explaining the association between spine injury and opioid misuse. Design: Prospective cohort study. Setting: Level I trauma center in a Midwestern city. Participants: English speaking patients aged 18 to 75 on Trauma and Orthopedic Surgical Services receiving opioids during hospitalization and prescribed at discharge. Exposure: Spine injury on the Abbreviated Injury Scale. Main outcome measures: Opioid misuse was defined by using opioids: in a larger dose, more often, or longer than prescribed; via a non-prescribed route; from someone other than a prescriber; and/or use of heroin or opium. Exploratory factor groups included demographic, psychiatric, pain, and treatment factors. Multivariable logistic regression estimated the association between spine injury and opioid misuse when adjusting for each factor group. Results: Two hundred eighty-five eligible participants consented of which 258 had baseline injury location data and 224 had follow up opioid misuse data. Most participants were male (67.8%), white (85.3%) and on average 43.1 years old. One-quarter had a spine injury (25.2%). Of those completing follow-up measures, 14 (6.3%) developed misuse. Treatment factors (injury severity, intubation, and hospital length of stay) were significantly associated with spine injury. Spine injury significantly predicted opioid misuse [odds ratio [OR] 3.20, 95% confidence interval [CI] (1.05, 9.78)]. In multivariable models, adjusting for treatment factors attenuated the association between spine injury and opioid misuse, primarily explained by length of stay. Conclusion: Spine injury exhibits a complex association with opioid misuse that predominantly operates through treatment factors. Spine injury patients may represent a subpopulation requiring early intervention to prevent opioid misuse.

Trends in Medicaid Enrollment and Disenrollment During the Early Phase of the COVID-19 Pandemic in Wisconsin.

Importance: After the federal public health emergency was declared in March 2020, states could qualify for increased federal Medicaid funding if they agreed to maintenance of eligibility (MOE) provisions, including a continuous coverage provision. The implications of MOE provisions for total Medicaid enrollment are unknown. Objective: To examine observed increases in Medicaid enrollment and identify the underlying roots of that growth during the first 7 months of the COVID-19 public health emergency in Wisconsin. Design Setting and Participants: This population-based cohort study compared changes in Wisconsin Medicaid enrollment from March through September 2020 with predicted changes based on previous enrollment patterns (January 2015-September 2019) and early pandemic employment shocks. The participants included enrollees in full-benefit Medicaid programs for nonelderly, nondisabled beneficiaries in Wisconsin from March through September 2020. Individuals were followed up monthly as they enrolled in, continued in, and disenrolled from Medicaid. Participants were considered to be newly enrolled if they enrolled in the program after being not enrolled for at least 1 month, and they were considered disenrolled if they left and were not reenrolled within the next month. Exposures: Continuous coverage provision beginning in March 2020; economic disruption from pandemic between first and second quarters of 2020. Main Outcomes and Measures: Actual vs predicted Medicaid enrollment, new enrollment, disenrollment, and reenrollment. Three models were created (Medicaid enrollment with no pandemic, Medicaid enrollment with pandemic economic circumstances, and longer Medicaid enrollment with a pandemic-induced recession), and a 95% prediction interval was used to express uncertainty in enrollment predictions. Results: The study estimated ongoing Medicaid enrollment in March 2020 for 792 777 enrollees (mean [SD] age, 20.6 [16.5] years; 431 054 [54.4%] women; 213 904 [27.0%] experiencing an employment shock) and compared that estimate with actual enrollment totals. Compared with a model of enrollment based on past data and incorporating the role of recent employment shocks, most ongoing excess enrollment was associated with MOE provisions rather than enrollment of newly eligible beneficiaries owing to employment shocks. After 7 months, overall enrollment had increased to 894 619, 11.1% higher than predicted (predicted enrollment 805 130; 95% prediction interval 767 991-843 086). Decomposing higher-than-predicted retention, most enrollment was among beneficiaries who, before the pandemic, likely would have disenrolled within 6 months, although a substantial fraction (30.4%) was from reduced short-term disenrollment. Conclusions and Relevance: In this cohort study, observed increases in Medicaid enrollment were largely associated with MOE rather than new enrollment after employment shocks. Expiration of MOE may leave many beneficiaries without insurance coverage.

Trends in Engagement With Opioid Use Disorder Treatment Among Medicaid Beneficiaries During the COVID-19 Pandemic.

Importance: Disruptions in care during the COVID-19 pandemic may have decreased access to care for patients with opioid use disorder. Objective: To examine trends in opioid use disorder treatment including buprenorphine possession, urine drug testing, and opioid treatment program services during the COVID-19 public health emergency. Design Setting and Participants: This cohort study included 6453 parent and childless adult Medicaid beneficiaries, aged 18 to 64 years, with opioid use disorder and continuous enrollment from December 1, 2018, to September 30, 2020, in Wisconsin. Logistic regression compared differences in study outcomes before, early, and later in the COVID-19 public health emergency. Analyses were conducted from January 2021 to October 2021. Exposures: Early (March 16, 2020, to May 15, 2020) and later (May 16, 2020, to September 30, 2020) in the public health emergency. Main Outcomes and Measures: Person-week outcomes included possession of buprenorphine, completion of outpatient urine drug testing, and receipt of opioid treatment program services. Results: The final cohort of 6453 participants included 3986 (61.8%) childless adults; 5741 (89%) were younger than 50 years, 3435 (53.2%) were women, 5036 (78.0%) White, and 22.0% were racial and ethnic minority groups (American Indian, 269 [4.2%]; Asian, 26 [0.4%]; Black, 458 [7.1%]; Hispanic, 292 [4.5%]; Pacific Islander, 1 [.02%]; Multiracial, 238 [3.7%]). Overall, 2858 (44.3%), 5074 (78.6%), and 2928 (45.4%) received buprenorphine, urine drug testing, or opioid treatment program services during the study period, respectively. Probability of buprenorphine possession did not change in the early or later part of the public health emergency. Probability of urine drug testing initially decreased (marginal effect [ME], -0.04; 95% CI, -0.04 to -0.03; P < .001) and then partially recovered in the later public health emergency (ME, -0.02; 95% CI, -0.03 to -0.02; P < .001). Probability of opioid treatment program services followed a similar pattern, with an early decrease (ME, -0.05; 95% CI, -0.05 to -0.04; P < .001) followed by partial recovery (ME, -0.02; 95% CI, -0.03 to -0.02; P < .001). Conclusions and Relevance: In a sample of continuously enrolled adult Medicaid beneficiaries, the COVID-19 public health emergency was not associated with decreased probability of buprenorphine possession, but was associated with decreased probability of urine drug testing and opioid treatment program services. These findings suggest patients in office-based settings retained access to buprenorphine despite decreased on-site services like urine drug tests, whereas patients at opioid treatment programs experienced greater disruption in care. Given the importance of medications for opioid use disorder in preventing overdose, policy makers should consider permanent policy changes based on lessons learned from the public health emergency to enable ongoing enhanced access to these medications.

The Affordable Care Act Medicaid Expansion Positively Impacted Community Health Centers and Their Patients.

Community health centers (CHCs) provide primary care for underserved children and adults. The Patient Protection and Affordable Care Act (ACA) aimed to strengthen the CHC network by increasing federal funds and expanding Medicaid eligibility. The ACA also aimed to boost preventive and mental health services and to reduce health and healthcare disparities. Here, we summarize our results to-date as experts in investigating the impact of ACA Medicaid expansion on CHCs and the patients they serve. We found the ACA Medicaid expansion increased access to care and preventive services, primarily in Medicaid expansion states. Rates of physical and mental health conditions rose substantially from pre- to post-ACA in expansion states, suggesting underdiagnosis pre-ACA. Disparities in health insurance coverage by race/ethnicity decreased at CHCs, yet some remain. These findings indicate that the ACA Medicaid expansion significantly helped CHCs and patients. Insurance expansion buoyed CHCs' financial viability by increasing reimbursement. Therefore, the ACA Medicaid expansion enhanced the health of underserved patients and repeal would jeopardize these advances for CHCs and their patients.