Recent policy actions and proposals in Medicaid have renewed focus on the problem of churn, or temporary loss of coverage in which enrollees disenroll and then re-enroll within a short period of time. The Families First Coronavirus Response Act (FFCRA) passed during the coronavirus pandemic requires states to provide continuous coverage to Medicaid enrollees until the end of the month in which the public health emergency (PHE) ends to receive enhanced federal funding. During this time, people did not churn on and off Medicaid, but churn may resurface when the continuous enrollment requirement ends. The Build Back Better reconciliation bill under consideration in Congress would begin to phase out the continuous enrollment requirement and the enhanced match beginning April 1, 2022. Additionally, the bill would require states to provide 12-month continuous coverage for children and for postpartum individuals in Medicaid and the Children’s Health Insurance Program (CHIP), which could reduce churn for those groups. Currently more than half of states already provide 12-month continuous coverage for children on an optional basis.

To help inform the current policy discussion, this brief provides estimates of churn for people enrolled in Medicaid in 2018. We use 2017 and 2019 as look-back and look-ahead years, respectively, so we can examine what happens to people a full year before and after an enrollment date or disenrollment date in 2018. We also provide estimates of churn by eligibility group and compare rates in Medicaid expansion versus non-expansion states. Overall, we find that 10% of full-benefit enrollees have a gap in coverage of less than a year, and rates are higher for children and adults compared to aged and people with disabilities. Churn rates also vary substantially by state, ranging from 5% or less in some states to 15% or more in others. Churn has implications for access to care as well as administrative costs faced by states. Detail on the data and methods underlying this analysis are in the Methods section at the end of the brief.

Background

The temporary loss of Medicaid coverage in which enrollees disenroll and then re-enroll within a short period of time, often referred to as “churn,” occurs for a several reasons. Enrollees may experience short-term changes in income or circumstances that make them temporarily ineligible. Alternatively, some people who remain eligible may face barriers to maintaining coverage due to renewal processes and periodic eligibility checks. Eligible individuals are at risk for losing coverage if they do not receive or understand notices or forms requesting additional information to verify eligibility or do not respond to requests within required timeframes.

Some enrollees may be at higher risk of churn than others. Working individuals whose monthly income fluctuates may be more likely to experience churn in states that have adopted frequent electronic data matches during the year. For example, adult enrollees without disabilities, most of whom are working, may have irregular work hours, overtime, or multiple part-time jobs that can lead to month-to-month changes in income. In contrast, elderly adults and people with disabilities, particularly those who qualify for Supplemental Security Income (SSI), are less likely to experience monthly income changes or other changes in circumstances. Most states conduct data matches on a periodic basis to identify changes in circumstances between annual renewal periods. If the data checks identify changes in income or other factors that affect eligibility and the individual is unable to resolve the discrepancy within the specified timeframe (often limited to within 10 days from the date of the notice), the person can be disenrolled from coverage.

Churn can result in access barriers as well as additional administrative costs. When individuals who remain eligible for coverage are disenrolled, they may experience gaps in coverage that could limit access to care and lead to delays in getting needed care. Research indicates that enrollees who experience fluctuations in coverage are more likely to report difficulties getting medical care and are more likely to end up in the hospital with a preventable condition. In addition, there are administrative costs associated with disenrolling an enrollee and then subsequently processing a new application.

What are the rates of churn in Medicaid?

Among full-benefit beneficiaries enrolled at any point in 2018, 10.3% had a gap in coverage of less than a year. About 4.2% were disenrolled and then re-enrolled within three months and 6.9% within six months (Figure 1).

Rates of churn were higher for children and adults compared to aged adults and people with disabilities (Figure 2). We estimate that 11.2% of full-benefit children and 12.1% of adults were disenrolled and then subsequently re-enrolled within one year. Analysis also shows that rates of churn are higher for enrollees with partial benefit packages, but there are similar churn rates across expansion and non-expansion states (Appendix Table 1). However, there is considerable variation in churn rates across states, with 4 states (HI, AZ, DC, and NC) having 5% of enrollees or fewer disenrolling and then re-enrolling within a year, and 4 states (TX, WI, NH, and PA) having 15% of enrollees or more disenrolling and re-enrolling within a year.

What are current policy issues related to churn?

The continuous enrollment requirement related to the coronavirus pandemic has all but halted Medicaid churn for the past year and a half, but disenrollments are expected resume once the requirement ends. In part due to the continuous enrollment requirement, Medicaid/CHIP enrollment has increased from February 2020 to May 2021 by 11.5 million (or 16.2%) to 82.8 million individuals. However, when the continuous enrollment requirement ends, states will begin processing renewals and individuals may lose coverage if they are no longer eligible or face barriers during the redetermination process, such as providing required documentation.

The Build Back Better Act (BBBA) that is currently being debated in Congress would phase out the continuous enrollment requirement beginning April 1, 2022. To continue receiving a phased-down enhanced federal match rate, states would be required to follow rules about disenrolling people that could help to reduce rates of churn. For example, states could only disenroll individuals who have been enrolled at least 12 consecutive months and must limit eligibility redeterminations to a set proportion of enrollees each month through September 2022. States could not disenroll individuals based on returned mail unless there were at least two failed attempts to contact the individual through at least two modalities (e.g., mail and text messages). States would also have to report monthly data on call center statistics (average volume, wait times, and abandonment rates) as well as rates of eligibility renewals, redeterminations, and coverage terminations due to changes in circumstances (e.g., increased income) or due to administrative reasons (e.g., failing to provide required documentation).

Prior to the pandemic, some states had adopted policies and processes to reduce churn and promote continuous coverage. For example, as of January 2020, 35 states account for anticipated income changes, such as recurring seasonable employment or a job change, when determining eligibility at renewal. Some states also use projected annual income for the remainder of the calendar year when determining ongoing eligibility at renewal or when an individual has a potential change in circumstances between renewal periods. States can also implement processes that improve communications with enrollees to help prevent them from losing coverage because they do not receive or respond to notices from the state. Such actions include conducting regular data matches with the U.S. Postal Service National Change of Address Database, working with managed care plans and providers to update enrollees’ address information, and calling enrollees or sending email or text notifications when returned mail from a notice sent to an enrollee is received.

The BBBA would require states to implement 12-month continuous coverage for children and postpartum individuals. States have the option to provide 12 months of continuous coverage for children. Under this option, states allow a child to remain enrolled for a full year unless the child ages out of coverage, moves out of state, voluntarily withdraws, or does not make premium payments. As such, 12-month continuous eligibility eliminates coverage gaps due to fluctuations in income over the course of the year. A recent MACPAC analysis found that states with 12-month continuous coverage for children had lower rates of churn among children enrolled in Medicaid and CHIP compared to states without this policy. Currently, 34 states provide 12-month continuous eligibility to at least some children in either Medicaid or CHIP. The Build Back Better Act would require states to extend 12-month continuous coverage for children in Medicaid and CHIP and would also require 12-month continuous coverage for postpartum individuals, a change from the current requirement of 60-day postpartum coverage.

Data Source and Linkage

Our analysis is based on the Transformed Medicaid Statistical Information System (T-MSIS) Analytic Files (TAF) Research Identifiable Files (RIF). We include beneficiaries who were enrolled at any point in 2018. We use the 2018 Demographic Eligibility (DE) Base file to determine eligibility pathway based on last-best eligibility data. We draw enrollment dates from the 2017-2019 DE Dates files. Our analysis uses enrollment dates from 2017 and 2019 for look-back and look-ahead years, respectively, so that we can examine what happens to enrollees a full year before and after an enrollment start date or disenrollment date in 2018. Data for 2019 are from the preliminary version of the T-MSIS RIF. All other DE Base and DE Dates files are final versions (Release 1).

State Exclusion Criteria

We use 41 states in our analysis. We exclude 10 states (FL, IN, KY, ME, MS, NE, OK, OR, UT, and WY) due to missing or inconsistent data based on state-level information available at the DQ Atlas as well as our own analysis. We relied on data quality assessments from DQ Atlas to exclude states that have a “medium concern”, “high concern”, or “unusable” data quality assessment for: (1) the average monthly Medicaid/CHIP enrollment compared to an external enrollment benchmark (Medicaid/CHIP Performance Indicator Data) (five states (IN, KY, ME, MS, NE)); (2) the average length of enrollment gaps, and (3) the percent of beneficiaries with overlapping Medicaid and S-CHIP enrollment spans (no states were excluded based on measures 2 or 3). We further excluded states based on: (4) the percent of beneficiaries missing an eligibility group code (threshold of >=10%, excluded OR); (5) the percent of beneficiaries with only one enrollment span (threshold of >=99.5, excluded FL, KY, and WY); and (6) the percent of beneficiaries with three or more enrollment spans in a year (threshold of >=5%, excluded OK). Notably, our exclusion criteria for related to the number of enrollment spans in a year are less restrictive than that in the DQ Atlas because we did not want to make assumptions about the number of enrollment spans in our analysis, but did want to remove extreme cases that are the most likely to represent inaccurate enrollment dates.

For analysis that includes restricted benefit enrollees, we further excluded two states (CA and ND) due to large amounts of missing data among restricted benefit enrollees. CA was excluded because roughly 75% of observations coded with restricted benefits in the DE Base file were missing a federal identifier (BENE_ID). ND was excluded due to large amounts of missing enrollment data in the DE Dates files and, after merging the DE Dates and DE Base files, more than half (53%) of restricted benefit enrollees in the DE Base file did not have a matching BENE_ID in the DE Dates file and were dropped from the analysis.

Beneficiary Linking, Eligibility Classification, and Exclusion

We linked individuals across years using BENE_ID, which are unique enrollee identifiers created by the Chronic Conditions Warehouse and are recommended for use when combining data for multiple years. We also use BENE_ID to link the DE Base and DE Dates files. We assigned restricted benefit status and eligibility group code using a last-best approach for 2018, which assigns eligibility based on the most recent eligibility code in 2018. We classified eligibility groups using a hierarchy that first checked if the eligibility group code was missing, then for medically needy eligibility, disability (under age 65), and expansion adult. Any enrollees in the DE Base file that had a non-missing eligibility code and had not been assigned an eligibility group through this hierarchy were then were assigned by age to children (ages 20 and under), adults (ages 21 to 64), and aged (ages 65 and over).

The 2018 DE Base files for 41 states in our analysis contained 82.9 million observations after removing a small number of “dummy” records that represent enrollees who have claims data but no eligibility data provided by the states. We removed observations missing eligibility codes or restricted benefit status codes (624,000 observations), people qualifying through a medically needy pathway (1.7 million observations), people missing a BENE_ID for linking files (3.1 million observations), and people with duplicated BENE_ID (262,000 observations). After merging with the DE Dates files, there were less than 5,000 enrollees who did not have a matching BENE_ID in the DE Dates and DE Base files and were dropped from the final sample. Our final sample included 77.2 million unduplicated enrollees. Of these, 71.3 million were full-benefit enrollees. Our analysis of restricted benefit enrollees included 5.4 million people in the 39 states included in that component of the analysis.

Calculating Churn

The DE Dates files provide a start and end date for every enrollment span in our time period. As noted above, our analysis uses enrollment dates from 2017 and 2019 for look-back and look-ahead years for a more complete picture of churning. Before calculating churn rates, we first merged all overlapping and contiguous enrollment spans for enrollees, which we defined as enrollment spans that are separated by one day or less. For example, if a person has two enrollment spans with an end date and a start date that are one day apart (i.e., the person disenrolled and re-enrolled the next day), we considered these spans to be contiguous and merged them into one enrollment span. After merging overlapping and contiguous spans, we identified enrollment gaps, which we defined as the number of days between two enrollment spans for an enrollee. To be counted as “churn” in our analysis, a person would have had (1) an enrollment gap of 365 days or less and (2) and enrollment gap that started or ended in 2018. For example, a person that disenrolled in 2017 but then re-enrolled within 365 days in 2018 would be included in our churn estimates. Similarly, a person who disenrolled in 2018 and then re-enrolled in less than 365 days would also be counted in our churn estimates. Sensitivity analyses that only included gaps longer than 31 days showed a marginal decrease in churn rates (approximately 1 percentage point); while shorter gaps could reflect data reporting errors, they also could be true disenrollments followed by relatively quick re-enrollment.

Previous studies have estimated Medicaid churn rates at around 10%. There is some variation across studies due to use of different data sources, national versus state-specific estimates, and the focus on different populations (e.g., children versus adults). A recent analysis from MACPAC, which used the same data source but different methods as our analysis found that 8% of Medicaid and CHIP enrollees re-enrolled in coverage within one year of disenrolling. The most significant difference in our methods from MACPAC analysis was that the MACPAC analysis only utilized a look-ahead year, while our analysis includes a look-ahead year and a look-back year. There are other differences in methods from MACPAC’s analysis, but those likely have a smaller impact than the use of a look-back year. Our estimate of a 10% churn rate overall is also similar to estimates of 9% and 11% from studies of churn in specific states.

Introduction

The Build Back Better Act (BBBA) includes several prescription drug provisions; while much of the focus has been on Medicare and private insurance, the bill includes a number of provisions with implications for Medicaid prescription drug spending. Before the pandemic, Medicaid outpatient prescription drug utilization, measured in terms of the number of prescriptions, was decreasing while Medicaid gross spending on prescription drugs was increasing. COVID-19 and social distancing practices changed health care needs and utilization, in turn impacting Medicaid prescription drug utilization and spending in 2020. Further, Medicaid enrollment has increased throughout the pandemic, which could influence Medicaid prescription drug trends. This issue brief describes Medicaid prescription drug utilization and spending trends in calendar year 2020 compared to previous years to explore how the pandemic impacted Medicaid prescription drug utilization and spending. This brief builds on a previous KFF analysis of Medicaid prescription drug trends using the most recent data available.

Utilization Trends

Medicaid outpatient prescription drug utilization decreased during the pandemic. Overall, there were a total of 703.6 million Medicaid outpatient prescriptions in 2020, which is down from 734.1 million prescriptions in 2019 (Figure 1). While outpatient prescription drug utilization started to decline even before the pandemic, the decline from 2019 to 2020 (4.2%) was greater than the decline from 2018 to 2019 (0.8%). Immediately following the onset of the COVID-19 pandemic, Medicaid prescription drug utilization dropped in the second quarter (April – June) of 2020, experiencing a 10.1% decrease in prescription drug utilization compared to the same quarter in 2019 (Figure 2). Utilization was higher in the third and fourth quarters of 2020, but still below 2018 and 2019 levels. This decrease in outpatient drug utilization occurred as Medicaid enrollment increased by 12.5% between February 2020, right before the pandemic began, and December 2020.

Prescription drug utilization trends varied across drug groups in 2020. The same drug groups comprise the top ten most prescribed drug groups in 2019 and 2020, but the order changed (Table 1). Among the top ten most prescribed drug groups in 2020, seven experienced declines in utilization and three experienced increases. Drug groups that saw large utilization declines from 2019 to 2020 compared to 2018 to 2019 included antibiotics, allergy immunotherapy and antihistamines, sympathomimetic agents, and adrenals and combinations. Further, analgesics/antipyretics, which include opioids, were declining before the pandemic and continued to decline in 2020. On the other hand, three drug groups, psychotherapeutics, anticonvulsants, and antidiabetic agents, saw increases in drug utilization from 2019 to 2020, which could be due to the routine nature of the drugs that comprise these groups. Psychotherapeutic agents were the most prescribed drug group in 2020 and experienced a 4% increase in utilization, which mirrors national trends and the increase in mental health challenges throughout the pandemic.

Gross Spending Trends

While utilization declined, Medicaid spending on outpatient prescription drugs before rebates¹  increased in 2020. Overall, Medicaid paid $73.4 billion before rebates for outpatient prescription drugs in 2020, which is up from $69.1 billion in 2019 (Figure 3). Medicaid gross spending on prescription drugs increased 9.8% from 2018 to 2019 compared to 6.2% from 2019 to 2020, indicating spending increases may have slowed somewhat due to the pandemic. Immediately following the onset of the COVID-19 pandemic, the second quarter (April – June) of 2020 saw the lowest spending, which mirrors the dip in utilization in the same quarter, though Q2 2020 spending was still above Q2 spending in previous years (Figure 4). Gross spending rebounded and was higher in the third and fourth quarters of 2020 than in the first quarter of 2020.

Gross Medicaid spending continued to increase for almost all of the most costly drug groups before rebates in 2020. The same drug groups comprise the top ten most costly drug groups before rebates in 2019 and 2020, but the order changed (Table 2). Antivirals were consistently the most costly drug group in Medicaid before rebates from 2015 to 2019, driven by spending for drugs used to treat HIV and hepatitis C drugs; however, antiviral spending declined from 2019 to 2020 and antidiabetic agents became the most costly drug group before rebates in 2020. While not in the top 10 most costly drug groups, respiratory agents, a drug group used to relieve and treat respiratory diseases such as COVID-19, experienced a 61% increase in gross spending and a 44% increase in utilization from 2019 to 2020.² 

Despite remaining stable in prior years, net Medicaid prescription drug spending, or spending after rebates, increased in federal fiscal year 2020. While gross Medicaid spending on outpatient prescription drugs increased from 2015 to 2019, rebates also increased during the period, leaving Medicaid net spending in 2019 almost the same as net spending in 2015. However, recent data for the federal fiscal year (FFY) 2020 (October 1, 2019 – September 30, 2020) shows rebates for Medicaid prescription drugs increased by $2.1 billion from FFY 2019 while Medicaid gross spending increased by $3.6 billion, leading to an increase in net Medicaid spending in FFY 2020.³ 

Discussion

There are many factors that may have contributed to the decline in prescription drug utilization during the pandemic, including decreases in service utilization, drug adherence, and the diminished spread of illnesses other than COVID-19. Following the onset of the pandemic, there was a drop in emergency department visits, hospital admissions, preventive service utilization, and elective health services. The use of telemedicine increased, but it did not increase enough to make up for the decline in in-person visits. Declines in health care utilization likely led to fewer clinicians writing prescriptions, thus contributing to the decline in Medicaid prescription drug utilization. Additionally, a recent study found US patients were more likely to discontinue use of chronic medications during the pandemic and less likely to begin new medications, signaling changes in drug adherence could have contributed to the decline. Declines across specific drug groups also likely reflects the decline medical service utilization during the pandemic and the impact of COVID-19 mitigation measures. Social distancing lessened the spread of other illnesses, such as the flu, which saw sharp declines in cases and deaths during the pandemic. Antibiotics saw the largest decline (-23%) in utilization from 2019 to 2020 (Table 1), likely due in part to fewer bacterial infections during the pandemic.

Medicaid prescription drug utilization declined at time when Medicaid enrollment was increasing. Administrative data for Medicaid show that after declines in enrollment from 2017 through 2019, total enrollment nationwide began to grow after February 2020, right before the pandemic began. By December 2020, enrollment had increased by 8.9 million, or 12.5%, from actual enrollment in February 2020. The overall number of prescriptions per enrollee per year decreased from approximately ten prescriptions per person in 2019 down to nine in 2020.⁴ 

While prescription drug utilization decreased during the pandemic, Medicaid spending before rebates increased. Overall, 2020 continued with the same utilization and spending trends seen before the pandemic in 2019, but utilization decreased to a larger degree and spending increased to a smaller degree in 2020 compared to 2019. All drug groups in both the top 10 for utilization and gross spending, saw larger growth in their gross spending than in utilization from 2019 to 2020, which contributes to the increase in spending despite declines in utilization overall. Further, increases in gross spending despite decreases in utilization in 2020 may be due in part to decreased use of less costly drugs. For example, antibiotics experienced a 23% decline in use from 2019 to 2020 (Table 1), but antibiotics only made up 2% of gross spending in 2020. Also, despite the pandemic, the number of new drug approvals remained high in 2020, likely contributing to the increase in spending despite decreases in utilization.

Looking Ahead

Medicaid prescription drug policy is likely to remain an issue at both the federal and state levels due to budgetary constraints and the entry of new, high-cost drugs to the market. States remain concerned about specialty and high-cost drugs and report developing strategies and policies to address these drugs. Though much of the focus on the Build Back Better Act (BBBA), recently passed by the House of Representatives and currently being debated in the Senate, has been on Medicare and private insurance prescription drug provisions, the BBBA includes a number of provisions that affect Medicaid prescription drug spending. The BBBA would require retail community pharmacy participation in the National Average Drug Acquisition Cost (NADAC) survey, which could better align pharmacy reimbursement rates with pharmacy actual costs. The BBBA prohibits the implementation of a rule issued by the Trump Administration estimated to increase federal and state Medicaid spending. The rule would have eliminated rebates negotiated between drug manufacturers and pharmacy benefit managers (PBMs) or health plan sponsors in Medicare Part D by eliminating the safe harbor protection under the federal anti-kickback law. The BBBA also proposes to apply the Medicaid Drug Rebate Program to separate state CHIP programs, likely allowing state CHIP programs to receive larger rebates. Lastly, there may be implications for Medicaid prescription drug spending resulting from Medicare proposals in the BBBA that allow the federal government to negotiate prices for some high-cost drugs and implement an inflationary rebate for some drugs under Medicare Part B and Part D.

Methodology

This analysis of Medicaid prescription drug utilization and spending trends builds on a previous KFF analysis of Medicaid prescription drug trends using the most recent data available. This analysis uses 2017 through 2020 State Drug Utilization Data (SDUD), downloaded in November 2021, merged with data from IBM Micromedex RED BOOK. The SDUD is publicly available data provided as part of the Medicaid Drug Rebate Program. It provides data on the number of prescriptions, Medicaid spending before rebates, and cost-sharing for rebate-eligible Medicaid outpatient drugs. The RED BOOK data is from September 2021. The use of RED BOOK data does not represent and should not be characterized as a RED BOOK endorsement of any data, findings, or other content presented in this report. The SDUD and the RED BOOK data were merged at the NDC-level to incorporate the therapeutic/pharmacologic category of the product.

Limitations

The SDUD provides spending and utilization data by NDC, quarter, managed care or fee-for-service, and state. It also provides this data summarized for the whole country. CMS has suppressed data cells with fewer than 11 prescriptions, citing the Federal Privacy Act and the HIPAA Privacy Rule. This analysis used the national data because less data is suppressed at the national versus state level.

This analysis uses gross Medicaid spending because rebate data is unavailable to the public at the NDC level. Rebates have a considerable effect on Medicaid drug spending overall, lowering net spending, but this effect varies at the drug level as different drugs receive different rebates. We do include analysis of the Medicaid Budget and Expenditure System’s (MBES) FMR net expenditure data, available for the federal fiscal year, to understand overall Medicaid rebate trends. Additionally, although Medicaid beneficiaries largely self-administer drugs that are prescribed in an outpatient setting, medical practitioners must administer some drugs. Although states are instructed to collect drug rebates on physician-administered outpatient drugs that are not billed as a bundled service, physician-administered drugs subject to a rebate can vary from state to state. Because specialty drugs are often physician-administered, it is possible that the data reflects lower Medicaid spending and utilization of certain drugs of this kind.

1. Under the Medicaid Drug Rebate Program, manufacturers that want their drugs covered by Medicaid must sign an agreement with the Secretary of Health and Human Services stating that they will rebate a specified portion of the Medicaid payment for the drug to the states, who in turn share the rebates with the federal government. In addition to federal statutory rebates, most states negotiate supplemental rebates. Both statutory and supplemental rebates account for a sizeable share of prescription drug spending, lowering aggregate drug spending by about 55% in 2019. Rebates are not included in this analysis due to lack of data availability (see Appendix for details). While rebates have implications for net Medicaid spending, understanding trends in gross spending and utilization provides important context for pharmacy benefit policy by highlighting underlying cost factors. ↩︎
2. KFF analysis of 2019-2020 State Drug Utilization Data, November 2021; IBM Micromedex RED BOOK, September 2021. ↩︎
3. KFF analysis of Medicaid Budget and Expenditure System (MBES) FMR net expenditure data as of September 2021; 2018-2020 State Drug Utilization Data, November 2021; IBM Micromedex RED BOOK, September 2021. ↩︎
4. KFF analysis of CMS, Medicaid & CHIP: Monthly Application and Eligibility Reports, last updated October 26, 2021; 2019-2020 State Drug Utilization Data, November 2021; IBM Micromedex RED BOOK, September 2021.   ↩︎

Overview

This report, Donor Government Funding for Family Planning in 2020, tracks funding levels of the donor governments that collectively provide the bulk of international assistance for family planning activities. The new report provides the latest data available on donor funding disbursements based on data provided by governments. It presents their bilateral assistance to low- and middle-income countries as well as contributions to UNFPA.

December 2021 (.pdf)

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November 2013 (.pdf)

This report provides an analysis of donor government funding to address family planning in low- and middle-income countries in 2020, the most recent year available, as well as trends over time. It is part of an effort by KFF (the Kaiser Family Foundation) to track such funding that began after the London Summit on Family Planning in 2012. Importantly, the current findings largely reflect political funding decisions made before the COVID-19 pandemic and therefore likely precede any major effects on donor government spending for family planning. Key findings include:

• AFTER THREE YEARS OF INCREASES, DONOR GOVERNMENT FUNDING FOR BILATERAL FAMILY PLANNING DECLINED. In 2020, family planning funding from donor governments totaled US$1.40 billion, a decline of US$114 million compared to the 2019 level (US$1.52 billion).¹ 
• THE DECLINE IN 2020 WAS LARGELY DUE TO DECREASED FUNDING FROM U.K., THE WORLD’S SECOND LARGEST DONOR, LARGELY OFFSETTING ITS PRIOR YEAR INCREASE. K. bilateral funding for family planning activities declined by more than US$100 million in 2020. The decline was partly due to the timing of U.K. disbursements (funding increased significantly in 2019, but then returned to near prior year levels in 2020), as well as an overall decline in its ODA due to the effect of COVID-19 on the U.K.’s gross national income (GNI).^2 ,3 
• THREE DONORS INCREASED BILATERAL FUNDING IN 2020 WHILE ALL OTHER DONORS EITHER DECLINED OR REMAINED FLAT. Among the ten donor governments profiled, three increased funding (Canada, France, and Sweden), three remained essentially flat (Australia, Netherlands, and U.S.), and four decreased (Denmark, Germany, Norway, and U.K.); these trends were the same after adjusting for inflation and exchange rate fluctuations, except for the Netherlands, which increased in currency of origin.
• THE U.S. CONTINUES TO BE THE LARGEST DONOR TO BILATERAL FAMILY PLANNING EFFORTS. The U.S. provided $592.5 million or 42% of total bilateral funding from governments in 2020.⁴  The U.K. (US$266.5 million, 19%) was the second largest donor, followed by the Netherlands (US$202.3 million, 14%), Sweden (US$129.3 million, 9%), and Canada (US$94.0 million, 7%).
• DESPITE THE DECLINE IN 2020, FUNDING HAS GENERALLY INCREASED SINCE THE CALL FOR MORE FUNDING MADE AT THE LONDON SUMMIT IN 2012. Funding from donor governments in 2020 was approximately US$215 million above the 2012 level (US$1.2 billion). In 2020, six donor governments provided higher funding than in 2012, including Canada, Denmark, the Netherlands, Norway, Sweden, and the U.K. Since funding from the U.S., the world’s largest donor over the period has been relatively flat, the overall trends have been largely driven by other donors.
• FUNDING TO UNFPA INCREASED IN 2020, EVEN WITHOUT U.S. SUPPORT. In addition to bilateral funding for family planning, the donor governments profiled provided US$411.7 million in core contributions to UNFPA in 2020, an increase of more than US$40 million compared to 2019 (US$367.6 million).^5 ,6  The ranking of donor government support for UNFPA differs from that of their bilateral funding. Germany provided the largest core contribution (US$78.8 million), followed by Sweden (US$65.9 million), Norway (US$55.1 million), the Netherlands (US$36.8 million), and Denmark (US$34.1 million).The U.S. did not provide any funding to UNFPA in 2020 due to the Trump Administration’s invoking of the Kemp-Kasten amendment to withhold funding from UNFPA between 2017 and 2020. The Biden administration has moved to restore funding, expected in 2021.⁷ 
• FUTURE FUNDING WILL LIKELY DEPEND ON THE IMPACT OF COVID-19 ON COUNTRY BUDGETS AND FAMILY PLANNING SERVICES AS WELL AS CHANGES IN U.S. ADMINISTRATION PRIORITIES. Donor government funding decisions for 2020 were largely determined prior to the COVID-19 pandemic, before most governments saw their GDPs fall. Funding for family planning activities in 2021, which will largely reflect decisions made in 2020, and beyond will depend on the trajectory of the COVID-19 pandemic, particularly vaccination roll-out, but also the continued economic stresses on country budgets (both donor and recipient) as well as changing needs in recipient countries resulting from impacts on family planning services. At the same time, funding from the U.S. may rise as the Biden Administration and current Congress have expressed support for increased funding for family planning activities.

Introduction

This report provides data on donor government funding for family planning activities in low- and middle-income countries in 2020, the most recent year available, as well as trends over time. It is part of an effort by KFF that began after the London Summit on Family Planning in 2012 and includes data from all 30 members of the Organisation for Economic Co-operation and Development (OECD)’s Development Assistance Committee (DAC), as well as non-DAC members where data are available.⁸  Data are collected directly from donors and supplemented with data from the DAC. Direct data collection was carried out for ten donor governments that account for 98% of total funding for family planning. Both bilateral assistance and core contributions to UNFPA are included. For more detail, see methodology.

Findings

Bilateral Funding

In 2020, donor governments provided US$1.40 billion in bilateral funding for family planning activities (see Figure 1, Table 1, & Appendix), a decline of US$114 million compared to the 2019 level (US$1.52 billion).¹ The decline in 2020 followed three years of increases, which, in 2019, resulted in the highest level of funding since the London Summit in 2012.

The decline in 2020 was largely due to decreased funding from the U.K., the world’s second largest donor. It is important to note, however, that the U.K. decline was due to a complex set of factors including the timing of disbursements (funding increased significantly in 2019, but then returned to almost prior year levels in 2020) and the overall decline in ODA resulting from the effect of COVID-19 on GNI.²

Among the ten donors for which direct data collection was conducted, three increased funding in 2019 (Canada, France, and Sweden), three remained essentially flat (Australia, Netherlands, and U.S.), and four decreased (Denmark, Germany, Norway, and U.K.). These trends were the same after adjusting for inflation and exchange rate fluctuations, except for the Netherlands, which increased in currency of origin.

The U.S. was the largest donor to bilateral family planning efforts in 2020, accounting for 42% of donor government funding (see Figure 2). Despite a decline, the U.K. remained the second largest donor (19%) followed by the Netherlands (14%), Sweden (9%), and Canada (7%).

Donor government funding for family planning has generally risen since the London Summit in 2012, although totals have fluctuated over the period. Funding in 2020 (US$1.40 billion) was approximately US$215 million above the 2012 level (US$1.19 billion). In 2020, six donors provided higher funding than in 2012, including Canada, Denmark, the Netherlands, Norway, Sweden, and the U.K. Since funding from the U.S., which has been the largest donor each year over the period, has been relatively flat, the overall trends have largely been driven by the other donors (see Figure 3).

Donor Contributions to UNFPA

While the majority of donor government assistance for family planning is provided bilaterally, donors also provide support for family planning activities through contributions to the United Nations Population Fund (UNFPA). Most of UNFPA’s funding is from donor governments, which provide funding in two ways: 1) donor directed or earmarked contributions for specific activities (e.g. donor contributions to the UNFPA Supplies), which are included as part of bilateral funding above; and 2) general contributions to “core” activities that are untied and meant to be used for both programmatic activities (e.g. family planning, population and development, HIV/AIDS, gender, and sexual and reproductive health and rights) and operational support as determined by UNFPA.⁹ 

In 2020, the donor governments profiled provided US$411.7 million in core contributions to UNFPA, an increase of more than US$40 million compared to the 2019 level (US$367.6 million). The increase was largely attributable to Germany, which more than doubled its core contribution (from US$37.0 million in 2019 to US$78.8 million in 2020), mostly in support of UNFPA’s efforts to address the impacts of COVID-19.¹⁰  In addition to Germany, one other donor increased funding (Sweden), while five remained flat (Australia, Canada, France, the Netherlands, and the U.K.), and two declined (Denmark and Norway); these trends were the same after adjusting for inflation and exchange rate fluctuations, except for Norway, which remained flat in currency of origin.

The ranking of donor contributions to UNFPA differs from that of their bilateral family planning funding. Germany provided the largest core contribution to UNFPA in 2020 (US$78.8 million), followed by Sweden (US$65.9 million), Norway (US$55.1 million), the Netherlands (US$36.8 million), and Denmark (US$34.1 million), (see Figure 4 and Table 2). Three donors – Denmark, Germany, and Norway – provided larger contributions to UNFPA’s core resources than their total bilateral funding for family planning.

Due to the Trump administration’s decision to invoke the Kemp-Kasten amendment to withhold funding – both core and non-core - from UNFPA, the U.S. did not provide a contribution to UNFPA between 2017-2020. The Biden Administration has moved to restore funding, which is expected in 2021. Still, these amounts, and historical UNFPA contributions, place the U.S below other donors as the U.S. directs almost all of its support for family planning through bilateral channels.

Looking Ahead

Donor government funding decisions for 2020 largely occurred prior to the COVID-19 pandemic. However, the decline in family planning funding in 2020 was partially due to the impact of COVID-19 on the U.K. GNI. Whether this trend continues for the U.K. or other donor governments in 2021 and beyond will largely depend on the trajectory of the COVID-19 pandemic, particularly the rollout of vaccinations globally, as the pandemic put significant stresses on both donor and recipient country budgets as well as the delivery of family planning services globally.¹¹  At the same time, funding from the U.S. could potentially increase in 2021 as the Biden Administration requested additional resources, and Congress has indicated it may support an increase (although, final funding decisions have not been made). Given that the U.S. is the largest donor to global family planning efforts, any changes would have an outsized impact on the overall amount and trends over time.

Methodology

Bilateral and multilateral data on donor government assistance for family planning (FP) in low- and middle-income countries were collected from multiple sources. The research team collected the latest bilateral assistance data directly for 10 governments: Australia, Canada, Denmark, Germany, France, the Netherlands, Norway, Sweden, the United Kingdom, and the United States during 2021. Data represent the fiscal year 2020 period. Direct data collection from these donors was desirable because they represent the preponderance of donor government assistance for family planning and the latest official statistics – from the Organisation for Economic Co-operation and Development (OECD) Creditor Reporting System (CRS) (see: http://www.oecd.org/dac/stats/data) – which are from 2019 and do not include all forms of international assistance (e.g., funding to countries such as Russia and the Baltic States that are no longer included in the CRS database). In addition, the CRS data may not include certain funding streams provided by donors, such as FP components of mixed-purpose grants to non-governmental organizations. Data for all other OECD DAC member governments – Austria, Belgium, Czech Republic, the European Union, Finland, Greece, Hungary, Iceland, Ireland, Italy, Japan, Korea, Luxembourg, New Zealand, Poland, Portugal, the Slovak Republic, Slovenia, Spain, and Switzerland – which collectively accounted for approximately 2 percent of bilateral family planning disbursements, were obtained from the OECD CRS and are from calendar year 2019.

For purposes of this analysis, funding was counted as family planning if it met the OECD CRS purpose code definition: “Family planning services including counselling; information, education and communication (IEC) activities; delivery of contraceptives; capacity building and training.”  Where it was possible to identify funding amounts, family-planning-related activities funded in the context of other official development assistance sectors (e.g. education, civil society) are included in this analysis. Project-level data were reviewed for Canada, Denmark, France, Germany, the Netherlands, Norway, and Sweden to determine whether all or a portion of the funding could be counted as family planning. Family-planning-specific funding totals for the United States were confirmed through communication with government representatives. Funding attributed to Australia and the United Kingdom is based on a revised Muskoka methodology as agreed upon by donors at the London Summit on Family Planning in 2012. Funding totals presented in this analysis should be considered preliminary estimates based on data provided by representatives of the donor governments who were contacted directly.

It was difficult in some cases to disaggregate bilateral family planning funding from broader population, reproductive and maternal health totals, as the two are sometimes represented as integrated totals. In addition, family-planning-related activities funded in the context of other official development assistance sectors (e.g. education, civil society) have in the past remained largely unidentified. For purposes of this analysis, we worked closely with the largest donors to family planning to identify such family-planning-specific funding where possible. In some cases (e.g. Canada), specific FP percentages were recorded for mixed-purpose projects. In other cases, it was possible to identify FP-specific activities by project titles in languages of origin, notwithstanding less-specific financial coding. In still other cases, detailed project descriptions were analyzed (see Appendix for detailed data table).

Bilateral funding is defined as any earmarked (FP-designated) amount and includes family planning-specific contributions to multilateral organizations (e.g. non-core contributions to UNFPA Supplies). UNFPA contributions from all governments correspond to amounts received during the 2020 calendar year, regardless of which contributor’s fiscal year such disbursements pertain to.

With some exceptions, bilateral assistance data were collected for disbursements. A disbursement is the actual release of funds to, or the purchase of goods or services for, a recipient. Disbursements in any given year may include disbursements of funds committed in prior years and in some cases, not all funds committed during a government fiscal year are disbursed in that year. In addition, a disbursement by a government does not necessarily mean that the funds were provided to a country or other intended end-user. Enacted amounts represent budgetary decisions that funding will be provided, regardless of the time at which actual outlays, or disbursements, occur. In recent years, most governments have converted to cash accounting frameworks, and present budgets for legislative approval accordingly; in such cases, disbursements were used as a proxy for enacted amounts.

For the U.S., funding represents final, Congressional appropriations (firm commitments that will be spent) to the U.S. Agency for International Development (USAID), rather than disbursements, which can fluctuate from year-to-year due to the unique nature of the U.S. budget process (unlike most other donors, U.S. foreign assistance funding may be disbursed over a multi-year period). U.S. totals also include some funding originally appropriated by Congress for UNFPA that is transferred to the USAID family planning & reproductive health (FP/RH) account due to specific provisions in U.S. law including the Kemp-Kasten amendment (see KFF “UNFPA Funding & Kemp-Kasten: An Explainer”). Prior reports presented disbursements. For this report, all prior-year amounts have been changed from disbursements to appropriations. This change in methodology does not alter the overall trend in total funding from donor governments over time.

UNFPA core contributions were obtained from United Nations Executive Board documents. UNFPA estimates of total family planning funding provided from both core and non-core resources were obtained through direct communications with UNFPA representatives. Other than core contributions provided by governments to UNFPA, un-earmarked core contributions to United Nations entities, most of which are membership contributions set by treaty or other formal agreement (e.g., United Nations country membership assessments), are not identified as part of a donor government’s FP assistance even if the multilateral organization in turn directs some of these funds to FP. Rather, these would be considered as FP funding provided by the multilateral organization, and are not considered for purposes of this report.

The fiscal year period varies by country. The U.S. fiscal year runs from October 1-September 30. The Australian fiscal year runs from July 1-June 30. The fiscal years for Canada and the U.K. are April 1-March 31. Denmark, France, Germany, the Netherlands, Norway, and Sweden use the calendar year. The OECD uses the calendar year, so data collected from the CRS for other donor governments reflect January 1-December 31. Most UN agencies use the calendar year and their budgets are biennial.

All data are expressed in US dollars (USD). Where data were provided by governments in their currencies, they were adjusted by average daily exchange rates to obtain a USD equivalent, based on foreign exchange rate historical data available from the U.S. Federal Reserve (see: http://www.federalreserve.gov/) or in some cases from the OECD. Data obtained from UNFPA were already adjusted by UNFPA to represent a USD equivalent based on date of receipts.

1. Totals represent funding specifically designated by donor governments for family planning as defined by the OECD DAC (see methodology), and include: standalone family planning projects; family planning-specific contributions to multilateral organizations (e.g., contributions to UNFPA Supplies); and, in some cases, projects that include family planning within broader reproductive health activities. ↩︎
2. U.K. official development assistance (ODA) is directly tied by law to the gross national income (GNI). Therefore, a decline in the U.K. GNI in 2020 resulted in a subsequent decline in ODA. For more information see “Reduction in the UK’s 0.7 percent ODA target”, June 2021. ↩︎
3. Direct communication, U.K. Foreign, Commonwealth & Development Office (FCDO). November 2021. ↩︎
4. This year’s report also includes an update to the methodology for reporting U.S. funding totals (see methodology for more information). ↩︎
5. Includes core-contributions from members of the OECD DAC only; core contributions from non-DAC donors are not included in this total. ↩︎
6. UNFPA, “Delivering In A Pandemic: Annual Report 2020”, 2020. See also UNFPA Donor Contributions portal. ↩︎
7. In 2016, US contributions to UNFPA had totaled US$69 million, including US$30.7 million in core resources and an additional US$38.3 million in non-core resources for other project activities. (See KFF’s “UNFPA Funding & Kemp-Kasten: An Explainer.”). ↩︎
8. Includes funding from 29 DAC member countries and the European Union (EU). ↩︎
9. In 2020, UNFPA spent approximately US$451.6 million (42.3% of UNFPA’s total programme expenses) on family planning activities (US$76.6 million from core resources and US$375.0 million from non-core resources). This includes US$297.6 million for family-planning specific activities such as enabling environments for family planning, contraceptives and related supplies, provision of services and family planning systems strengthening, and US$154.0 million for activities with an impact on family planning results in other areas of work under UNFPA’s mandate. Direct communication, UNFPA, October 2021. ↩︎
10. At this time, it is unclear whether future core contributions from Germany will continue at the 2020 amount. ↩︎
11. FP2030, “FP2030: Measurement Report, 2021”, December 2021. ↩︎