Contraceptive Access Maps

The Contraceptive Access Maps are a collaborative effort between Power to Decide and the Guttmacher Institute to re-conceptualize county-level access to low- and no-cost contraception across the United States. Informed by extensive consultations with diverse experts and stakeholders, the updated maps are grounded in the current realities of sexual and reproductive health care.

To understand contraceptive access in each county across the country, we draw on multiple data inputs to inform two distinct metrics: (1) alignment between availability of publicly funded health centers providing any contraceptive method and women’s self-defined need for this care; and (2) alignment between availability of publicly funded health centers that provide the full range of birth control methods and women’s self-defined need for contraception. These data inputs include:

1. The number of publicly-funded clinics in the county offering (a) any contraceptive method, and (b) IUDs and implants on site. For our purposes, publicly-funded clinics include sites that offer contraceptive services to the general public and receive at least some public funds (e.g., federal, state, or local funding through programs such as Title X or the federally qualified health center (FQHC) program), to provide free or reduced-fee services to qualifying patients. These sites are operated by a diverse range of providers, including public health departments, Planned Parenthood affiliates, FQHCs, and other independent organizations.

   1. Clinics in this category provide any clinic-based contraceptive method.
   2. Clinics in this category are those that provide IUDs and Implants. We use providing IUDs and implants as a proxy for providing the full range of FDA-approved methods (such as birth control pills, the shot, the ring, the patch, and emergency contraception) because health centers that can provide these more costly methods are typically able to offer a range of other methods as well.

   Data Source: Health center data is pulled from our Bedsider Clinic Finder, which compiles health centers across the country. The map includes data representing more than 7,000 health centers. The data come from multiple verified sources, including Title X clinics, Planned Parenthood affiliates, Federally Qualified Health Centers, and county and state government programs. Power to Decide manages this nationwide compilation of data, which also includes Puerto Rico. The map does not draw on data from private providers who take Medicaid or groups of clinics for specific subpopulations and can not be accessed by the general public, such as Indian Health Services, VA centers, college health centers, teen-only clinics, or school-based health centers. The Bedsider Clinic Finder was first published in 2011. Power to Decide last completed a full update of clinic information between January 2020 and March 2023 and continues to update clinic information on a rolling basis.

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2. Average patient caseloads by clinic type. We use county-specific caseload averages provided by the Guttmacher Institute to estimate the number of patients who could be served in each county. These averages reflect the typical number of patients receiving contraceptive services annually by clinic type in a given county. When county-level caseload data are not available for a specific clinic type, the value is imputed from the average caseloads of counties with similar urbanicity and population size—drawing first from counties within the same state, then from the broader DHHS/Title X region or national data, depending on how many similar counties are available at each level.

   Data Source: Data for the caseload averages come from Guttmacher’s Family Planning Census, which collected data about all of the publicly supported agencies and clinics that provided contraceptive services in 2020. Using annual patient counts, Guttmacher calculated county-specific caseload averages for 3 clinic types: Planned Parenthoods, Health Departments, and other clinics that provide contraceptive services (including FQHCs and independent organizations that receive Title X funds).  Of the 3,144 counties in the analysis, 412 (13.1%)  were missing an observed county-level patient caseload for at least one clinic type. For these counties, caseload values were imputed using a cell-based mean approach, in which each missing value is filled with the average of observed counties sharing the same urbanicity category and population-size group, at the narrowest geographic level with at least three comparable counties.

    

3. The estimates of women with a self-defined need for contraception who likely need public funding for contraceptive care in the county, calculated as the sum of women under age 20 and women ages 20-49 under 250% of the federal poverty level who indicate a self-defined need for contraceptive services—a novel measure developed by the Guttmacher Institute.

   Determination of self-defined need is based on reported recent use of contraception or contraceptive services or reporting a desire to use contraception if financial barriers were not an issue. These estimates consider the need for contraceptive services for any reason, not solely for the purpose of preventing pregnancy. To focus on those who likely need public funding to obtain contraceptive services, we limit the total number of women with a self-defined contraceptive need to those who are 20-49 with a family income below 250% of the federal poverty level (FPL; less than $62,150 for a family of three in 2023) or are younger than 20. All adolescents who have a self-defined need for contraceptive services, regardless of their family income, are assumed to have a likely need for publicly funded contraceptive care because of their heightened need for confidentiality in obtaining care (which may not be provided if they depend on their family’s resources or private insurance).

   Data source:  These data come from Guttmacher’s 2023 Self-Identified Need tables. To learn more about their methodology, you can read their report here. 

We conceptualize county-level access as the alignment between women’s needs for contraception and the availability of publicly funded clinics providing contraceptive services in the county. Specifically, we construct two distinct measures of availability—one for all health centers providing any contraceptive method and one for health centers that provide the full range of birth control methods. For each, we estimate the total patients served in a county by multiplying the number of clinics of each type by that type’s average caseload and summing across types.

To calculate preliminary alignment estimates, we divided each of these availability measures by the number of women with a self-defined need for contraception who likely need public funding for contraceptive care in the county.  We capped these preliminary alignment estimates at 1.0 and then applied a distance penalty to counties where estimated travel distance to the nearest clinic exceeded the federal standard for that county’s urbanicity type. These thresholds come from the Centers for Medicare and Medicaid Services (CMS) network adequacy standards for OB/GYN services under Medicaid managed care, which specify the maximum distance considered acceptable for patients to travel to reach OB/GYN care: 10 miles for metro counties, 20 miles for micropolitan counties, and 30 miles for rural counties. We calculated estimated distance to the nearest clinic of the relevant type within each county using a nearest-neighbor formula: Estimated distance = 0.5 × √(county land area / number of clinics). For counties where estimated distance exceeded the CMS threshold, the raw alignment score was multiplied by an exponential decay factor:exp(−(estimated distance − threshold) / threshold). Of the 2,367 counties with at least one clinic, 305 (12.9%) received a distance penalty on the all-clinics metric. Of the 1,916 counties with at least one full-range clinic, 395 (20.6%) received a distance penalty on the full-range metric.
 

The current initiative is only one way of looking at access: a county-level view of the extent to which available clinics offering either any contraceptive care or specifically the full range of birth control methods at low or no cost are aligned with women’s contraceptive needs.

The map doesn’t depict the population of people who, regardless of financial need, trust and rely on these health centers. Included in this group are people who may choose not to use their insurance for privacy reasons, travel outside their area to keep their contraceptive use private from a partner—a common situation tied to birth control sabotage or coercion—or need a provider who speaks their language or offers hours that fit their work schedule. All people should be able to access care in line with their needs and preferences without significant barriers.

In addition, our analysis of county-level access is limited in that it does not fully represent one’s proximity to a health center. For many, the presence of a clinic, even in their county, does not translate into access. In many areas of the country, a high percentage of people lack access to a vehicle or other form of transportation.

We also only count brick-and-mortar clinics and do not account for services provided via telehealth, or online birth control providers, or at pharmacies. We cannot account for contraceptive methods, like condoms or Opill, that are available over-the-counter.

Additional data limitations:

A limitation of our approach is using data from different years for the numerator and denominator. Because of the effort and time involved in collecting and analyzing data from health centers across the country, 2020 is the most recent data we have on caseload averages.   Given the rapidly shifting nature of care, our caseload averages from 2020 may no longer reflect clinic service availability.

There may be limitations to our patient caseload averages. To calculate the caseload averages, we grouped clinics into three categories to align Power to Decide and Guttmacher’s data: Planned Parenthoods, Health Departments, and other clinics that provide contraceptive services (this includes all other clinics in our database such as FQHCs and independent organizations that receive Title X funds). In particular, the “other” category may over- or underestimate network availability. We have tried to alleviate this concern by drawing on county-specific caseload averages to more closely estimate availability specific to county contexts.

Finally, our distance adjustment is an approximation with notable limitations. We estimate the distance to the nearest clinic from a county's land area and clinic count rather than from actual clinic locations, so the adjustment captures the general relationship between clinic density and travel burden rather than any individual's true travel distance. It also assumes a single federal distance standard for each urbanicity type and does not account for variation in road networks, terrain, or the distribution of clinics within a county.