Alyssa Shell Tilhou

The use of stimulants like cocaine and methamphetamine is a growing health threat in the United States. Between 2013 and 2019, deaths involving cocaine use tripled and deaths involving methamphetam...

Introduction: Buprenorphine (BUP) is an effective treatment for opioid use disorder (OUD) that may create opportunities to expand access to preventive services for patients with OUD when implemented in the primary care setting. HIV prevention, particularly pre-exposure prophylaxis (PrEP), represents a vital service for persons with OUD due to HIV risk associated with injection drug use and condomless sex. Evaluating the existing integration of BUP treatment and HIV prevention is an important step to further optimize comprehensive care for patients with OUD. Methods: This retrospective cohort study used pharmacy claims from the Merative™ MarketScan ^® Research Databases, 2014 – 2022, to examine use of PrEP among new BUP treatment episodes over the first 63 days of treatment. We excluded BUP episodes from individuals with probable HIV (based on diagnosis or medications indicated for HIV in the past 365 day). Clinical indications for PrEP were identified based on past 365-day diagnosis of sexually transmitted infections (STIs) or serious injection-related infections (SIRIs). Results: Of 123,740 BUP episodes representing 76,377 individuals, 104 (0.1%) involved PrEP during BUP treatment. Most of these episodes (71%) involved PrEP in the 30 days prior to BUP initiation. Only 6% of the sample exhibited diagnoses indicating risk for HIV. Of these, only 0.2% involved PrEP during the BUP treatment episode. BUP episodes involving PrEP tended to be disproportionately male (89% compared with 63%) and from the Northeast (27% vs. 18%) or West (30% vs. 16%). Conclusions: Findings from this retrospective cohort study identify a major gap in PrEP use for individuals with OUD and documented HIV risk. Aligning HIV prevention and BUP treatment is an important opportunity to enhance health for patients with OUD.

Among the many harmful consequences of opioid use disorder (OUD), two outcomes are particularly critical: opioid overdose and HIV infection. Fortunately, two interventions—medications for OUD (MOUD) and pre-exposure prophylaxis (PrEP) for HIV–effectively reduce the risk of opioid overdose and HIV, respectively. Despite the safety and availability of MOUD and PrEP, their uptake remains quite low. Efforts to increase use of MOUD and PrEP have occurred largely independently, yet these interventions integrate well in the setting of office-based treatment of OUD. To develop strategies that promote utilization of both medications, an integrated framework is needed. The OUD care cascade, a model describing treatment stages through which a patient may progress, has been increasingly used to facilitate monitoring and strategically expand MOUD services. Integrating PrEP into this framework could bring increased attention to PrEP utilization and strengthen efforts to enhance uptake of both medications. While real-world challenges exist along the continuum from diagnosis to retention, integrated measurement frameworks such as dashboards can help track progress, identify gaps, and optimize treatment strategies. To accelerate progress in the fight against HIV and opioid overdose, it is time to integrate monitoring and research of MOUD and PrEP.

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.

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.

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.