Abstract
BACKGROUND:
Medication nonadherence diminishes the benefits of preexposure prophylaxis (PrEP) for the 1.2 million Americans at risk for HIV exposure.
OBJECTIVE:
To describe HIV PrEP treatment patterns among Medicare Advantage Prescription Drug (MAPD) plan and commercially insured beneficiaries.
METHODS:
This retrospective cohort study identified patients aged 16 to 89 years with at least 1 dispensing of emtricitabine-tenofovir disoproxil fumarate from July 2012, through December 2020, or emtricitabine-tenofovir alafenamide from October 2019 through December 2020, and who were continuously enrolled at least 12 months prior to and following the earliest PrEP claim. Outcomes were HIV PrEP adherence measured by proportion of days covered (PDC) using 2 binary thresholds of 0.60 (4 doses/week) and 0.80 (5-6 doses/week) and duration of index treatment episode, total time on treatment, and total number of prescription fills.
RESULTS:
The study cohort of 707 (292 MAPD plan, 415 commercial) was predominantly made up of male patients (90.0%) and resided in the South (78.9%) with a mean age of 46.2 years (MAPD plan: 54.5, commercial: 40.4). Both populations engaged in high-risk sexual behavior (All: 18.7%, MAPD plan: 16.8%, commercial: 20.0%) and experienced sexually transmitted infections (All: 3.3%, MAPD plan: 2.1%, commercial: 4.1%). The mean index treatment episode length was 297.0 days (MAPD plan: 283.6, commercial: 306.5). Total time on treatment was 477.3 days (MAPD plan: 450.7, commercial 496.0). At 3 months, 84.9% (MAPD plan: 83.6%, commercial: 85.8%) and at 12 months, 58.7% (MAPD plan: 57.2, commercial: 59.8) of patients achieved a PDC of at least 0.80. At 3 months, 100.0% (MAPD plan: 100.0%, commercial: 100.0%), and at 12 months, 74.3% (MAPD plan: 70.2%, commercial: 76.9%) of patients achieved a PDC of at least 0.60. The cohort had a mean of 16.4 fills of 30 days (MAPD plan: 16.4, commercial: 16.3) supply.
CONCLUSIONS:
There is an opportunity for clinical programs to focus on improving longer-term PrEP adherence among individuals at risk for HIV exposure.
Plain language summary
Being adherent to a medication means taking that medication as prescribed. For this study, patients were considered adherent to HIV preexposure prophylaxis (PrEP) medication if they had enough pills to cover 4 out of every 5 days. After 3 months, 85% of patients were adherent to their PrEP medication prescription. After 1 year, more than half of patients were PrEP adherent. Future programs should focus on increasing long-term adherence to PrEP.
Implications for managed care pharmacy
Variable rates of medication adherence to HIV PrEP were found across Medicare Advantage Prescription Drug plan and commercial beneficiaries short term vs long term. Study results may inform design of PrEP clinical programs to improve long-term adherence among patients at risk of acquiring HIV. Future research should identify barriers to adherence, such as affordability, access, and intolerance because of side effects, and should evaluate the real-world association between HIV PrEP treatment patterns and incidence of HIV infections.
The Centers for Disease Control and Prevention estimates that as of 2020, approximately 1.2 million Americans were at substantial risk for HIV exposure and had an indication for preexposure prophylaxis (PrEP) which the US Food and Drug Administration (FDA) defines as at-risk adults and adolescents weighing at least 35 kg without evidence of renal impairment.1-3 Two forms of PrEP, emtricitabine-tenofovir disoproxil fumarate (FTC/TDF, brand name Truvada) and emtricitabine-tenofovir alafenamide (FTC/TAF, brand name Descovy), are approved in the United States as once daily oral regimens for HIV primary prevention in adults and adolescents.4,5 FTC/TDF received FDA approval July 16, 2012, and FTC/TAF was approved October 3, 2019. In December 2021, a new extended-release injectable suspension of cabotegravir (Apretude) also has the same FDA high-risk designation6 as FTC/TDF and FTC/TAF and received FDA approval for HIV PrEP.7
The efficacy of PrEP combined with safe-sex practices has been demonstrated in multiple randomized-control trials and real-world settings, and the majority of published literature on PrEP focuses on younger age groups.8 PrEP reduces the risk of acquiring HIV through sexual transmission by more than 90% when taken as prescribed.9,10 It reduces the risk of HIV infection through injection drug use by 74% in people with detectable medication levels and by 49% overall.11,12 A systematic review found a 70% relative risk reduction of acquiring HIV because of sexual exposure or injection drug use among those with highest PrEP adherence8; yet, studies in community settings indicate that around a quarter of individuals discontinue the medication within the first few months.13 Further, when confirmed by plasma drug concentrations, adherence to PrEP ranges widely from 30% to 100%.8 Real-world PrEP adherence and HIV risk factors also vary. The open label extension trial of men and transgender women who have sex with men, iPrEX OLE, found HIV incidence of 4.7 infections per 100 person-years for patients when no PrEP medication was detected in dried blood spot samples compared with 0.0 infections per 100 person-years for patients with an estimated adherence of 4 or more doses per week.14 A cohort study of 3,121 individuals in a Los Angeles federally qualified health center demonstrated that HIV incidence was 0.1 per 100 person-years among active PrEP patients compared with 2.1 per 100 person-years among patients who discontinued PrEP therapy.13 It is estimated that the medical cost saved by avoiding 1 HIV infection is $229,800 (in 2012 US dollars) over a lifetime,15 making PrEP a cost-effective option for disease prevention.16,17 Despite these documented benefits, retrospective data also demonstrate that individuals in certain geographic regions are less likely to be prescribed PrEP even though these areas carry a significant proportion of disease burden. The South accounted for about 27% of PrEP users in 2016, while experiencing roughly 50% of annual HIV incidence.8,18,19
In 2019, the US Department of Health and Human Services established goals of reducing incident HIV infections in the United States by 75% within 5 years and then by 90% within 10 years.20 This will require additional study of current PrEP treatment patterns in a variety of settings and patient populations to fully understand opportunities for and barriers to successful PrEP use and reduction in HIV incidence. The majority of published literature on PrEP adherence focuses on younger age groups,8 and it is not known if these results are generalizable to older populations. The objective of this study was to describe real-world HIV PrEP treatment patterns among older Medicare Advantage Prescription Drug (MAPD) plans and commercially insured beneficiaries in a national health plan population with significant representation from the Southern states—an area disproportionately burdened with HIV.
Methods
STUDY DESIGN, DATA SOURCE, AND PATIENT SELECTION
This retrospective cohort study used the Humana Research Database to identify MAPD plan or commercially insured beneficiaries aged 16 to 89 years with at least 1 dispensing of greater than 30 days’ duration of FTC/TDF from July 16, 2012, to December 31, 2020, or FTC/TAF from October 3, 2019, through December 31, 2020. The index date was the date of first prescription fill for either drug, and the index treatment episode was calculated as days supply plus a 21-day grace period, selected to reflect the period during which a person can maintain 4 doses per week with a 30-day prescription.13 Eligible patients had at least 12 months of continuous health plan enrollment prior to and following the index date. Follow-up included the 12 months of continuous enrollment plus the time until HIV diagnosis, disenrollment, death, or December 31, 2021 (end of study period). Continuous enrollment was defined as having no gaps in enrollment more than 45 days during the study period. All measures for the time period given (3 months or 12 months follow-up) used data from the index date and the appropriate follow-up time for those measures. Patients with pre-index evidence of PrEP therapy were excluded. Patients with a diagnosis of or treatment of HIV or hepatitis B during the 12-month pre-index period (inclusive of index date) through 30 days post-index, to account for a seroconversion period, were also excluded. Patients with postexposure prophylaxis therapy, which is defined as having an index treatment episode less than 30 days, were excluded from analysis. Diagnosis of HIV (International Classification of Diseases, Ninth Revision, Clinical Modification [ICD-9-CM]: 042, 07953, 79571, V08; ICD-10-CM: B20, B9735, R75, Z21) and Hepatitis B (ICD-9-CM: 07020-07023, 07030-07033; ICD-10-CM: B160-B162, B169, B180-B181, B1910-B1911) was determined by the presence of at least 1 medical diagnosis code or a positive laboratory result.
ETHICAL APPROVAL
The Humana Healthcare Research Human Subject Protection Office used the US Department of Health and Human Services regulations 45 CFR 46 and the Office of Human Research Protections Guidance on Coded Private Information or Specimens Use in Research, Guidance (2008) to determine this study did not constitute human participants research and did not require institutional review board oversight. The decision was based on the determination that the research involved only analysis of coded information, and the researchers could not readily identify the individuals from which the information was derived.
STUDY MEASURES
Baseline demographic and clinical characteristics were measured for all eligible patients, stratified by insurance status. Demographic characteristics included age, sex, race, region, low income subsidy (LIS)/dual Medicare/Medicaid eligibility status, and population density (urban, suburban, rural, unknown) assigned by matching patient ZIP codes at index date to Rural-Urban Commuting Area codes.21-23 LIS provides premium and cost-share assistance and is available to Medicare Part D beneficiaries whose income falls below 150% of the federal poverty line. For dually eligible beneficiaries, Medicare is the primary payer for most services, and Medicaid covers benefits not offered by Medicare. Dually eligible beneficiaries may have higher disease burden and different health care use patterns compared with other Medicare beneficiaries.24,25 The clinical characteristics measured were the Deyo-Charlson Comorbidity Index score,26-29 RxRisk-V score,30 indicators of behavioral risk (ICD-9 V69.2 and ICD-10 Z72.5x codes), and diagnosis of at least 1 sexually transmitted disease/infection (STD/STI). The RxRisk-V score is a pharmacy-based composite score developed by the Veterans Health Administration to assess comorbidity burden. The score, which ranges from 0 to 43 (originally it ranged from 0 to 45, however as urinary catheters and colostomy supplies are not present in administrative pharmacy claims, the current score is from 0 to 43), sums the number of condition categories, and higher scores indicate higher burden.
Characterization of HIV PrEP treatment patterns included index treatment episode duration and total time on treatment. Adherence to HIV PrEP was measured using proportion of days covered (PDC) at 2 binary thresholds of 0.60 (corresponding to 4.2 doses/week)31-33 and 0.80 (reflecting a potential threshold for a clinical adherence intervention).31 PDC is a continuous measure with values between 0.0 and 1.0, representing the proportion of time a person is theoretically in possession of medication. It is calculated by dividing the number of days on which the medication was available (based on filled prescriptions days supply field) by the duration of the post-index period. PDC was assessed at 3 and 12 months during the post-index period.
STATISTICAL ANALYSIS
Baseline population characteristics and HIV PrEP treatment patterns were reported using summary statistics. Means and SD were used for continuous variables and counts and frequencies (%) for categorical variables. PDC is reported based on the percentage of individuals who achieve the PDC thresholds at each time point.
Results
Of the 13,459 people with at least 1 pharmacy claim for FTC/TDF or FTC/TAF during the identification period, 707 individuals (292 MAPD plan, 415 commercial) met all of the criteria required for study inclusion (Supplementary Figure 1 (124.6KB, pdf) , available in online article) The most common reason for exclusion was pre-index HIV treatment (58%). These individuals were excluded to ensure patients in the study population were receiving medication only for PrEP, not for preexisting HIV infection, as some of the same medications used for PrEP also can be used in HIV treatment.
Demographic and clinical characteristics are reported in Table 1. Overall, the majority of the cohort was male (90.0%) and resided in the South (78.9%), with a mean (SD) length of follow-up in days of 772.9 (422.2) for the overall cohort, and 789.5 (459.2) and 761.2 (394.2) for MAPD plan and commercial beneficiaries, respectively. The overall mean age was 46.2 (13.8) years. When stratified by insurance status, patients with an MAPD plan were older than commercial patients, with mean (SD) ages of 54.5 (SD 12.3) and 40.4 (11.6) years, respectively. Patients generally had low comorbidity burden as observed by Deyo-Charlson Comorbidity Index scores, with a mean of 0.99 (± 1.45) for MAPD plan and 0.14 (± 0.14) for commercial populations. Race data were not uniformly available and were classified as other/unknown for 98.8% of commercial patients. In the MAPD plan cohort, 63.4% were White, 25.7% were Black, and 10.9% were Other/Unknown. Approximately 72% of the MAPD plan cohort was LIS and/or dually eligible. Indicators of behavioral risk were evident across the cohort, with 18.7% identified as having high-risk sexual behavior and 3.3% being diagnosed with at least 1 STD/STI (gonorrhea, syphilis, and/or chlamydia).
TABLE 1.
Demographic and Clinical Characteristics Among Patients With PrEP Treatment From 2012 to 2020
| Characteristic | All N = 707 | MAPD plan n = 292 | Commercial n = 415 |
|---|---|---|---|
| Treatment | |||
| Descovy | 87 (12.3) | 44 (15.1) | 43 (10.4) |
| Truvada | 620 (87.7) | 248 (84.9) | 372 (89.6) |
| Age, years, mean (SD) | 46.2 (13.8) | 54.5 (12.3) | 40.4 (11.6) |
| Age category, years, n (%) | |||
| 19 to 44 | 328 (46.4) | 65 (22.2) | 263 (63.4) |
| 45 to 54 | 156 (22.1) | 69 (23.6) | 87 (—) |
| 55 to 64 | 140 (19.8) | 77 (26.4) | (—)a |
| 65 to 89 | 83 (11.7) | (—)a | <11 (—) |
| Sex, n (%) | |||
| Female | 70 (9.9) | 45 (15.4) | 25 (6.0) |
| Male | 637 (90.1) | 247 (84.6) | 390 (94.0) |
| Race, n (%) | |||
| White | 201 (28.4) | (—)a | <11 (—) |
| Black | 78 (11.0) | 78 (—) | 0 (—) |
| Other | 14 (2.0) | 14 (—) | 0 (—) |
| Unknown | 414 (58.6) | <11 (—) | (—)a |
| Geographic region | |||
| Northeast | 11 (—) | <11 (—) | <11 (—) |
| Midwest | 86 (—) | 40 (—) | 46 (—) |
| South | 558 (—) | 217 (—) | 341 (—) |
| West | 50 (—) | 25 (—) | 25 (—) |
| Unknown | <11 (—) | <11 (—) | 0 (—) |
| Population density | |||
| Urban | 614 (—) | 227 (—) | 387 (—) |
| Suburban | 63 (—) | 46 (—) | 17 (—) |
| Rural | 20 (—) | (—)a | <11 (—) |
| Unknown | <11 (—) | <11 (—) | <11 (—) |
| Plan type | |||
| FFS | <11 (—) | <11 (—) | 0 (—) |
| HMO | 437 (—) | 115 (—) | 322 (—) |
| Other | 95 (—) | (—)a | <11 (—) |
| PPO/POS | 173 (—) | 82 (—) | 91 (—) |
| LIS or dual eligibility, n (%) | |||
| LIS only | 23 (—) | 23 (—) | 0 (0) |
| Dual eligibility only | <11 (—) | <11 (—) | 0 (0) |
| LIS and dual eligibility | 186 (—) | 186 (—) | 0 (0) |
| No LIS or dual eligibility | 497 (—) | 82 (—) | 415 (100) |
| DCCI, mean (SD)b | 0.49 (±1.10) | 0.99 (±1.45) | 0.14 (±0.52) |
| RxRisk-V score,c mean (SD) | 4.01 (±3.35) | 5.82 (±3.50) | 2.57 (±2.40) |
| Any STD/STI, n (%) | 23 (3.3) | <11 (—) | (—)a |
| Any chlamydia, n (%) | <11 (—) | 0 (0) | <11 (—) |
| Any gonorrhea, n (%) | <11 (—) | 0 (0) | <11 (—) |
| Any syphilis, n (%) | 17 (2.4) | <11 (—) | (—)a |
| Any high-risk sexual behavior, n (%) | 132 (18.7) | 49 (16.8) | 83 (20.0) |
| Any HIV tests, n (%) | 82 (11.6) | 24 (8.2) | 58 (14.0) |
| Count of HIV tests among testers, mean (SD) | 1.44 (0.82) | 1.58 (0.93) | 1.38 (0.77) |
a It is not permissible to report percentages and select values because of CMS cell suppression guidelines for n < 11 and this applies to data (commercial) that could be used to calculate the numbers for the CMS population; US Department of Health & Human Services. Guidance Portal. CMS Cell Suppression Policy. January 1, 2020. Accessed February 28, 2023. https://www.hhs.gov/guidance/document/cms-cell-suppression-policy.
b The DCCI uses ICD-10 diagnosis and procedure codes within 17 categories of comorbidities to represent overall patient health risk on a scale of 0 to 33.
c The RxRisk-V Score is a pharmacy-based comorbidity index comprising 45 distinct medical condition categories in which a higher number indicates greater comorbidity burden. For this study, the range is 0-43 as we do not capture neurogenic bladder and ostomy products in outpatient pharmacy claims.
CMS = Centers for Medicare & Medicaid Services; DCCI = Deyo-Charlson Comorbidity Index; FFS = fee-for-service; HMO = health maintenance organization; ICD = International Classification of Diseases, Tenth Revision; LIS = low-income subsidy; MAPD = Medicare Advantage Prescription Drug; PPO/POS = preferred provider organization/point of service; PrEP = preexposure prophylaxis; STD/STI = sexually transmitted disease/sexually transmitted infection.
HIV PrEP adherence was observed at 3 and 12 months post-index. At 3 months post-index, 84.9% of patients reached a PDC of 0.80 (83.6% MAPD plan, 85.8% commercial) and 100% of patients reached a PDC of 0.60 (100% MAPD plan, 100% commercial). Adherence decreased across both cohorts at 12 months, with 58.7% reaching PDC 0.80 (57.2% MAPD plan, 59.8% commercial) and 74.3% reaching PDC 0.60 (70.5% MAPD plan, 76.9% commercial).
HIV PrEP was used with a mean (SD) index treatment episode of 297.0 (263.9) days (283.6 [253.8] days MAPD plan, 306.5 [279.7] days commercial) and total time on treatment of 477.3 (338.7) days (450.7 [341.6] days MAPD plan, 496.0 [335.7] days commercial). Patients had a mean (SD) of 16.4 (11.5) fills (16.4 [11.9] MAPD plan, 16.3 [11.2] commercial) of 30 days supply (Table 2) over the mean 773-day follow-up period.
TABLE 2.
Treatment Patterns Among Patients With PrEP Treatment From 2012 to 2020
| Characteristic | Overall, N = 707mean (SD) | MAPD plan, n = 292 mean (SD) | Commercial, n = 415 mean (SD) |
|---|---|---|---|
| Length of follow-up, daysa,b | 772.85 (422.20) | 789.47 (459.24) | 761.16 (394.22) |
| Index Rx days supply | 33.23 (13.78) | 30.50 (6.21) | 35.15 (16.96) |
| Length of index treatment episode, days | 297.03 (263.91) | 283.63 (253.84) | 306.45 (270.68) |
| Average days supply across episodes | 33.13 (10.36) | 30.19 (3.56) | 35.21 (12.80) |
| Total number of fills | 16.36 (11.52) | 16.41 (11.93)) | 16.33 (11.24) |
| Length of index treatment episode, days | 297.03 (263.91) | 283.63 (253.84) | 306.45 (270.68) |
| Number of treatment episodes | 1.98 (0.93) | 1.93 (0.81) | 2.02 (1.01) |
| Length of all treatment episodes, days | 477.29 (338.65) | 450.70 (341.61) | 496.00 (335.71) |
| Total time on treatment, daysc | 627.64 (377.65) | 606.03 (384.06) | 642.84 (372.79) |
| PDCd | |||
| PDC 3-months post-index | 0.93 (0.11) | 0.93 (0.12) | 0.93 (0.11) |
| PDC 12-months post-index | 0.76 (0.24) | 0.75 (0.25) | 0.77 (0.23) |
| PDC 3-months post-index | |||
| By threshold, n (%) | |||
| ≥0.60e | 707 (100) | 292 (100) | 415 (100) |
| ≥0.80f | 600 (84.9) | 244 (83.6) | 356 (85.8) |
| PDC 12-months post-index, n (%) | |||
| ≥0.60e | 525 (74.3) | 206 (70.5) | 319 (76.9) |
| >0.80 | 415 (58.7) | 167 (57.2) | 248 (59.8) |
a Does not include time from the end of the last treatment episode through the end of follow-up, where applicable; only includes patients with at least 1 treatment gap.
b Patients with at least 1 treatment gap [n (%)] = 550 (77.8%), 239 (81.8%), and 311 (74.9%) in overall, MAPD plan, and commercial, respectively.
c Includes all time from the index date through the end of the last treatment episode, regardless of treatment gaps.
d PDC calculations by interval include all patients with at least as many months follow-up.
e PDC ≥60% = approximately 4 doses per week.
f PDC ≥80% = approximately 5-6 doses per week.
MAPD = Medicare Advantage Prescription Drug; PDC = proportion of days covered; PrEP = preexposure prophylaxis; Rx = prescription.
Discussion
This study describes HIV PrEP treatment patterns among new users of PrEP in a real-world setting. In this study, 85% of patients achieved a PDC of at least 0.80 at 3 months, and 55% achieved a PDC of at least 0.80 at 12 months. This lower percent of patients achieving a PDC of at least 0.80 at 1 year aligns with existing data. For example, in 1 study of 7,148 PrEP users filling prescriptions with a national pharmacy chain, persistence, another measure of medication adherence, was 56% and 63% in years 1 and 2, respectively, and was 41% overall when considering the entire time from initiation to year 2.34 The Pharmacy Quality Alliance uses a PDC greater than 0.80 for most chronic medications but sets a PDC greater than 0.90 for antiretroviral medication adherence assessments.35 Other PrEP adherence studies have used PDC cut points of at least 0.85, corresponding to 6 days per week, or at least 0.57, corresponding to 4 days per week and have had the majority of their cohort (>70%) aged under 35 years.32 Regardless of the PDC threshold used to consider treatment effective, the observed decline over time in the numbers of patients meeting at least a 0.80 PDC represents an opportunity to address long-term adherence issues.
Medication adherence continues to be an area of concern for PrEP for patients at sustained risk of acquiring HIV. Medication adherence can be impacted by socioeconomic, therapy-related, disease-related, patient-related, and health care system-related domains.36 Although this study focused on medication adherence measured by PDC through proof of administrative claims, individual evidence for nonadherence and information on high-risk behavior was not available. Adherence-related factors including knowledge and awareness of PrEP, cost, stigma, ability to access PrEP-dispensing providers/clinics, prescription side effects/interactions, and understanding one’s sexual risk could potentially affect individuals’ ability to maintain PrEP adherence.37-39 Although some work has been done to investigate underlying reasons for PrEP nonadherence such as substance use disorder,40 copay amount,34,40 smoking,40 hypertension, and diabetes,41 further research should investigate how these change over time to impact adherence. For the minority of individuals who discontinue PrEP because of treatment side effects,42-44 more information is needed to determine how best to support these patients and increase adherence. One option for possibly improving adherence is the newer, injectable, extended-release PrEP medication cabotegravir. This study only focused on the 2 oral medications because cabotegravir was approved after our data collection period.7 Future research could compare the oral medications vs the injectable option to determine whether the form of medication delivery has a significant impact on adherence in the short and long term.
The strengths of this study include a real-world analysis of both pharmacy and medical claims in a national health plan, an extended study identification period, follow-up data for at least 12 months, and availability of PrEP use trends among an older population. The MAPD plan cohort had a mean age of 54.5 years and was 90.1% male sex, 86.8% urban, and 61.8% on a health maintenance organization plan. The majority of published literature on PrEP adherence focuses on younger age groups,8 and it is not known if these results are generalizable to older populations. Our cohort provides valuable insight into PrEP use among older individuals. Additionally, 78.9% of our study cohort resided in the South. A large Southern population may limit overall generalizability but provides unique insights into a population with a potentially high need for PrEP interventions. The highest rates of new HIV diagnoses occur in the South.45
LIMITATIONS
This study has a small sample size and was subject to limitations of using administrative claims data. Claims data may be subject to errors in coding and lack of availability of certain clinical information, such as complete laboratory measures and non-STI infections. Lack of information on behavioral risk factors means it is not possible to determine if variable treatment patterns represent true increases in the risk of acquiring HIV or may represent a time of lower risk because of decreases in the behaviors associated with HIV acquisition. The missing, incomplete, or inaccurate data within the health care information technology system poses a limitation to the use of secondary data. Coding errors and inaccurate entry may lead to underestimates of behavioral risk or overestimates of adherence, as possession of a filled prescription may not reflect true adherence rates. It is possible that individuals assigned to the Medicare Advantage or commercial insurance plans may have changed insurance at some point during the study, which has the potential to affect use. We opted for an intention-to-treat method with regard to insurance plan type. Racial disparities in PrEP access persist, but the lack of race data in the commercial cohort precluded analyzing results by race. Given that Black and Latino men who have sex with men are disproportionately affected by HIV and far less likely to be prescribed PrEP,8,46 future studies using real-world data can help address this gap by examining differences in PrEP access and use by race.
Conclusions
These results may be used in the design of HIV PrEP clinical programs, with a focus on improving longer-term adherence and addressing variable treatment patterns among patients at risk. Future research should evaluate the real-world association between HIV PrEP treatment patterns and incidence of HIV infection and their intersection with other factors, such as health related social needs, socioeconomic status, geographic location, and race.
ACKNOWLEDGMENTS
The authors wish to thank Insiya Poonawalla for review and editorial oversight.
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