| Literature DB >> 32275654 |
Stephanie S Chan1, Andre R Chappel1, Karen E Joynt Maddox2, Karen W Hoover3, Ya-Lin A Huang3, Weiming Zhu3, Stacy M Cohen4, Pamela W Klein4, Nancy De Lew1.
Abstract
BACKGROUND: In 2015, there were approximately 40,000 new HIV diagnoses in the United States. Pre-exposure prophylaxis (PrEP) is an effective strategy that reduces the risk of HIV acquisition; however, uptake among those who can benefit from it has lagged. In this study, we 1) compared the characteristics of patients who were prescribed PrEP with individuals newly diagnosed with HIV infection, 2) identified the specialties of practitioners prescribing PrEP, 3) identified metropolitan statistical areas (MSAs) within the US where there is relatively low uptake of PrEP, and 4) reported median amounts paid by patients and third-party payors for PrEP. METHODS ANDEntities:
Year: 2020 PMID: 32275654 PMCID: PMC7147726 DOI: 10.1371/journal.pmed.1003072
Source DB: PubMed Journal: PLoS Med ISSN: 1549-1277 Impact factor: 11.069
Fig 1PrEP patient algorithm applied to IDV database, September 2015–August 2016.
Dx, diagnosis; IDV, Integrated Dataverse; PrEP, pre-exposure prophylaxis; Rx, prescription.
Number of PrEP patients, number of newly diagnosed HIV infections in 2015, and ratio of relative uptake by MSA for the 20 MSAs with the lowest and highest uptake.
| MSA | Number of PrEP Patients | Number of People with Newly Diagnosed HIV Infection, 2015 | Ratio of Number of PrEP Patients to Number of Newly Diagnosed HIV Infections | Ranking of Ratio |
|---|---|---|---|---|
| Twenty MSAs by Lowest Uptake | Lowest 20 MSAs | |||
| McAllen–Edinburg–Mission, TX | 9 | 82 | 0.11 | 1 |
| Virginia Beach–Norfolk–Newport News, VA–NC | 53 | 293 | 0.18 | 2 |
| Baton Rouge, LA | 54 | 265 | 0.20 | 3 |
| Deltona–Daytona Beach–Ormond Beach, FL | 22 | 78 | 0.28 | 4 |
| San Juan–Carolina–Caguas, PR | 144 | 399 | 0.36 | 5 |
| Palm Bay–Melbourne–Titusville, FL | 21 | 57 | 0.37 | 6 |
| Augusta–Richmond County, GA–SC | 41 | 104 | 0.39 | 7 |
| Bakersfield, CA | 49 | 121 | 0.40 | 8 |
| Lakeland–Winter Haven, FL | 43 | 106 | 0.41 | 9 |
| Memphis, TN–MS–AR | 127 | 312 | 0.41 | 10 |
| Stockton–Lodi, CA | 28 | 68 | 0.41 | 11 |
| El Paso, TX | 48 | 116 | 0.41 | 12 |
| Jacksonville, FL | 131 | 315 | 0.42 | 13 |
| Youngstown–Warren–Boardman, OH–PA | 15 | 35 | 0.43 | 14 |
| Columbia, SC | 81 | 164 | 0.49 | 15 |
| Greenville–Anderson–Mauldin, SC | 39 | 78 | 0.50 | 16 |
| Greensboro–High Point, NC | 67 | 131 | 0.51 | 17 |
| San Antonio–New Braunfels, TX | 200 | 386 | 0.52 | 18 |
| Richmond, VA | 135 | 227 | 0.59 | 19 |
| Fresno, CA | 61 | 102 | 0.60 | 20 |
| Twenty MSAs by Highest Uptake | Highest 20 MSAs | |||
| Madison, WI | 204 | 21 | 9.71 | 1 |
| Seattle–Tacoma–Bellevue, WA | 2,877 | 334 | 8.61 | 2 |
| San Francisco–Oakland–Hayward, CA | 5,625 | 722 | 7.79 | 3 |
| Boston–Cambridge–Newton, MA–NH | 2,876 | 456 | 6.31 | 4 |
| Portland–Vancouver–Hillsboro, OR–WA | 897 | 165 | 5.44 | 5 |
| Des Moines–West Des Moines, IA | 169 | 32 | 5.28 | 6 |
| Salt Lake City, UT | 384 | 75 | 5.12 | 7 |
| Minneapolis–St. Paul–Bloomington, MN-WI | 1,212 | 265 | 4.57 | 8 |
| Albany–Schenectady–Troy, NY | 223 | 50 | 4.46 | 9 |
| Rochester, NY | 375 | 87 | 4.31 | 10 |
| Chicago–Naperville–Elgin, IL–IN–WI | 5,347 | 1,380 | 3.87 | 11 |
| Providence–Warwick, RI–MA | 405 | 107 | 3.79 | 12 |
| Pittsburgh, PA | 622 | 165 | 3.77 | 13 |
| Boise City, ID | 72 | 20 | 3.60 | 14 |
| New York–Jersey City, NY–NJ–PA | 12,402 | 3,563 | 3.48 | 15 |
| Durham–Chapel Hill, NC | 279 | 81 | 3.44 | 16 |
| Columbus, OH | 826 | 240 | 3.44 | 17 |
| San Jose–Sunnyvale–Santa Clara, CA | 534 | 156 | 3.42 | 18 |
| Washington–Arlington–Alexandria, DC–VA–MD–WV | 3,941 | 1,233 | 3.20 | 19 |
| Denver–Aurora–Lakewood, CO | 789 | 272 | 2.90 | 20 |
Source: Authors’ analysis of the IDV data from September 2015 to August 2016 and the CDC’s 2015 annual HIV Surveillance Report. Abbreviations: CDC, Centers for Disease Control and Prevention; IDV, Integrated Dataverse; MSA, metropolitan statistical area; PrEP, pre-exposure prophylaxis.
Demographic characteristics of individuals prescribed PrEP in IDV database and adults and adolescents diagnosed with HIV infection reported to the CDC in 2015.
| Number of Individuals Prescribed PrEP, September 2015–August 2016 | % | Number of Individuals with Newly Diagnosed HIV Infection, 2015 | % | |||
|---|---|---|---|---|---|---|
| Total | 75,839 | 100.0 | 39,741 | 100.0 | ||
| Age | <0.001 | |||||
| 13–14 | Not Available | 26 | 0.1 | |||
| 15–34 | 34,935 | 46.1 | 22,010 | 55.4 | ||
| 35–44 | 18,753 | 24.7 | 7,669 | 19.3 | ||
| 45–54 | 15,088 | 19.9 | 6,306 | 15.9 | ||
| 55–64 | 5,781 | 7.6 | 2,883 | 7.3 | ||
| ≥65 | 1,282 | 1.7 | 847 | 2.1 | ||
| Ethnicity | <0.001 | |||||
| Black/African American | 5,944 | 7.8 | 17,345 | 43.6 | ||
| Hispanic/Latino | 6,523 | 8.6 | 9,682 | 24.4 | ||
| White/Caucasian | 34,427 | 45.4 | 10,447 | 26.3 | ||
| Other | 2,230 | 2.9 | 2,267 | 5.7 | ||
| Unknown | 26,715 | 35.2 | Not Available | |||
| Geography—Census Region | <0.001 | |||||
| Midwest | 12,298 | 16.2 | 5,198 | 13.1 | ||
| Northeast | 20,243 | 26.7 | 6,478 | 16.3 | ||
| South | 22,550 | 29.7 | 20,377 | 51.3 | ||
| West | 20,132 | 26.6 | 7,688 | 19.3 | ||
| Other/unknown | 616 | 0.8 | Not Available | |||
| Sex | <0.001 | |||||
| Male | 71,349 | 94.1 | 32,306 | 81.3 | ||
| Female | 4,490 | 5.9 | 7,435 | 18.7 | ||
| Educational Attainment | N/A | |||||
| HS graduate or less | 13,447 | 17.7 | Not Available | |||
| Some college | 16,790 | 22.1 | Not Available | |||
| Associate degree/bachelor degree or more | 19,885 | 26.2 | Not Available | |||
| Unknown | 25,717 | 33.9 | Not Available | |||
| Household Income | N/A | |||||
| Under 30,000 | 4,571 | 6.0 | Not Available | |||
| 30,000–49,000 | 8,158 | 10.8 | Not Available | |||
| 50,000–74,000 | 11,412 | 15.1 | Not Available | |||
| 75,000–99,000 | 8,704 | 11.5 | Not Available | |||
| 100,000+ | 15,523 | 20.5 | Not Available | |||
| Unknown | 27,471 | 36.2 | Not Available | |||
Source: Authors’ analysis of the IDV data from September 2015 to August 2016.
***p-value for chi-squared tests.
^Age categories for PrEP patients are 16–35, 36–45, 46–55, 55–65, over 65.
Abbreviations: CDC, Centers for Disease Control and Prevention; IDV, Integrated Dataverse; N/A, not applicable; PrEP, pre-exposure prophylaxis.
Fig 2Relative uptake of PrEP by MSA for MSAs with populations of 500,000 or greater.
Source: Authors’ analysis of the IDV data from September 2015 to August 2016 and CDC’s 2015 Annual HIV Surveillance Report. The authors used a shapefile, rather than a basemap, of the US with state borders from the US Census Bureau, https://www.census.gov/geographies/mapping-files/time-series/geo/tiger-line-file.html. CDC, Centers for Disease Control and Prevention; IDV, Integrated Dataverse; MSA, metropolitan statistical area; PrEP, pre-exposure prophylaxis.
Payment methods of PrEP patients, September 2015 through August 2016, and type of health insurance of coverage for antiretroviral medications for PLWH.
| Payment Methods | Number of PrEP Patients | Proportion of All PrEP Patients (%) | Proportion of Individuals Living with Diagnosed HIV (%) |
|---|---|---|---|
| Commercial | 60,580 | 79.88% | 34.90% |
| Medicaid | 8,970 | 11.83% | 44.80% |
| Medicare | 3,224 | 4.25% | 27.50% |
| TRICARE/CHAMPUS or VA (VA not included in PrEP patient data) | 428 | 0.56% | 4.80% |
| Gilead | 9,487 | 12.51% | n/a |
| Cash | 2,851 | 3.76% | n/a |
| Other assistance | 1,672 | 2.20% | n/a |
| Ryan White | n/a | n/a | 44.90% |
| Other public insurance | n/a | n/a | 12.50% |
| Insurance type unknown | n/a | n/a | 1.50% |
| No health insurance or coverage | n/a | n/a | 1.90% |
Source: Authors’ analysis of the IDV data from September 2015 to August 2016.
Each payment method is not mutually exclusive; i.e., patients may use more than one type of payment method and appear in more than one row in this table. The number of individuals prescribed PrEP in Table 3 adds up to more than 75,839. The percent of individuals prescribed PrEP does not sum to 100% for the same reason. There are very few patients who are dually eligible for Medicare and Medicaid. Gilead is parsed out from “Other assistance.” “TRICARE” is parsed out from commercial insurance. We identified 4 patients with payments for PrEP made by the VA and are not reporting on them due to the small sample size. Abbreviations: IDV, Integrated Dataverse; PLWH, people living with diagnosed HIV; PrEP, pre-exposure prophylaxis; VA, Veterans Administration.
Median patient and TPP payments for PrEP by payment method category, September 2015 through August 2016.
| Payment Method | Number of PrEP User-Months | Patient and TPP | Median Monthly Payment | 25th Percentile Monthly Payment | 75th Percentile Monthly Payment | TPP Share of Monthly Payment (Median) | Projected Yearly Payment (Median) |
|---|---|---|---|---|---|---|---|
| Any Insurance | 264,929 | Patient | $6 | $0 | $0 | $72 | |
| TPP | $1,458 | $1,379 | $1,498 | >99% | $17,496 | ||
| Commercial | 187,148 | Patient | $30 | $0 | $50 | $360 | |
| TPP | $1,464 | $1,389 | $1,509 | 98% | $17,568 | ||
| Medicaid | 30,580 | Patient | $0 | $0 | $3 | $0 | |
| TPP | $1,468 | $1,396 | $1,483 | >99% | $17,616 | ||
| Medicare | 13,487 | Patient | $1 | $0 | $10 | 0% | $12 |
| Low-Income Subsidy | 10,185 | Patient | $0 | $0 | $4 | 0% | $0 |
| Other | 3,302 | Patient | $74 | $50 | $474 | 5% | $888 |
| TPP | $1,462 | $1,379 | $1,494 | >99% | $17,544 | ||
| Tricare | 2,013 | Patient | $20 | $0 | $24 | $240 | |
| TPP | $1,429 | $1,358 | $1,445 | 99% | $17,148 | ||
| Gilead | 27,737 | Patient | $0 | $0 | $0 | $0 | |
| TPP | $75 | $35 | $1,480 | >99% | $900 | ||
| Cash Only | 118 | Patient | $1,791 | $1,716 | $1,945 | $21,492 | |
| TPP | $0 | $0 | $0 | 0% | $0 | ||
| Other Assistance | 3,281 | Patient | $0 | $0 | $0 | $0 | |
| TPP | $1,399 | $74 | $1,510 | >99% | $16,788 |
Source: Authors’ analysis of the IDV data from September 2015 to August 2016.
Notes: Each payment method category is not mutually exclusive, except for the category “Cash Only.” That is, patients may have more than one type of insurance and appear in more than one row in this table. The exception is “Cash Only”; patients in this category only paid for PrEP using cash. The number of individuals prescribed PrEP in Table 4 adds up to more than 75,839. The percent of individuals prescribed PrEP does not sum to 100% for the same reason. “TRICARE” is parsed out from commercial insurance. We identified 4 patients with payments for PrEP made by the VA and are not reporting on them due to the small sample size. There are very few patients in this database who are dually eligible for Medicare and Medicaid. Abbreviations: IDV, Integrated Dataverse; PrEP, pre-exposure prophylaxis; TPP, third-party payor; VA, Veterans Administration.