Abstract
States have turned to novel Medicaid financing to pay for community health worker (CHW) programs, often through fee-for-service or capitated payments. We sought to estimate Medicaid payment rates to ensure CHW program sustainability. A microsimulation model was constructed to estimate CHW salaries, equipment, transportation, space, and benefits costs across the U.S. Fee-for-service rates per 30-min CHW visit (code 98960) and capitated rates were calculated for financial sustainability. The mean CHW hourly wage was $23.51, varying from $15.90 in Puerto Rico to $31.61 in Rhode Island. Overhead per work hour averaged $43.65 nationwide, and was highest for transportation among other overhead categories (65.1% of overhead). The minimum fee-for-service rate for a 30-min visit was $53.24 (95% CI $24.80, $91.11), varying from $40.44 in South Dakota to $70.89 in Washington D.C. The minimum capitated rate was $140.18 per member per month (95% CI $105.94, $260.90), varying from $113.55 in South Dakota to $176.58 in Washington D.C. Rates varied minimally by metro status but more by panel size. Higher Medicaid fee-for-service and capitated rates than currently used may be needed to support financial viability of CHW programs. A revised payment estimation approach may help state officials, health systems and plans discussing CHW program sustainability.
Similar content being viewed by others
Avoid common mistakes on your manuscript.
Introduction
Community health worker (CHW) programs have demonstrated improvements in health outcomes, especially for low-income or otherwise marginalized populations who face significant barriers to receiving quality healthcare services [1,2,3]. CHWs are generally people from the same community as a patient, who provide critical social and emotional support, health education, and/or navigation assistance that supplements the work of other healthcare providers to assist in improving access to or quality of healthcare services for a patient [4]. CHW program evaluations have included randomized controlled trials among diverse populations, showing improvements of health outcomes and healthcare costs, particularly among Medicaid beneficiaries [5, 6].
CHW programs have faced considerable financing challenges despite the evidence of their benefits to health outcomes and healthcare costs. Many CHW programs have been financed under temporary grants, which has posed challenges for their long-term viability [7]. Recently, CHW programs have been included among states’ Medicaid 1115 waivers and related demonstration programs that aim to direct Medicaid dollars to CHW services [8]. CHW programs funded by Medicaid financing are either paid through fee-for-service (FFS) payments for visits between CHWs and patients, or capitated per-member-per-month (PMPM) payments to CHWs caring for a population panel of patients as part of a Medicaid managed care organization or a healthcare practice that has entered into value-based contracting. What remains unclear is how much financing should be allotted in FFS or PMPM payments to enable CHW programs to be financially sustainable. CHW programs, unlike standard medical care in clinics or hospitals, often require considerable transportation time, mobile equipment, and associated expenses, alongside flexible systems for supervision and support to ensure safety of CHWs and effectiveness in delivering roving, within-community services.
In the current study, we seek to establish and apply a rigorous approach to estimating the levels of Medicaid FFS or PMPM payments necessary to support the financial viability of CHW programs across all 50 US states, Washington D.C. and Puerto Rico. We develop and implement a microsimulation model that synthesizes data on CHW salaries, supervision, equipment, transportation, benefits and related costs across the US. We use the model to estimate the levels of financing needed to cover CHW program costs across different geographies, while maintaining patient volume or panel sizes that are consistent with the randomized trials showing benefits of CHWs on patient outcomes and healthcare costs.
Methods
Methods Overview
We constructed a microsimulation model (Fig. 1), which is a type of simulation that accounts for the covariation among input variables to estimate variations in output variables across locations (e.g., capturing how wages or transportation costs may be higher, and therefore subsequent payments may need to be higher in a given location). In our prespecified economic analysis plan (see “Data Availability”), we chose microsimulation because wages and costs related to CHW programs are expected to be highly variable across geographies, and hence we judged that capturing variations through a microsimulation, rather than only using national average estimates for cost, would be important to ensure the financial viability of CHW programs that are typically susceptible to local variations in labor and overhead expenditure. Our methods and reporting corresponded to the Consolidated Health Economic Evaluation Reporting Standards (see Appendix for checklist) [9].
Input Variables and Data Sources
Input variables and data sources for the model are summarized in Table 1, and further detailed in the Appendix by state (including Washington D.C. and Puerto Rico) and by metropolitan or non-metropolitan statistical area within states. The study population was defined as US-based CHW programs serving Medicaid patients.
The first set of input variables were labor costs (Fig. 1). CHW and CHW supervisor wages from the Bureau of Labor Statistics Occupational Employment and Wage Statistics (OEWS) database, which provides wage estimates from 82 million people (62% of total national employment) working at 1.1 million non-farm employer establishments surveyed through six semiannual panels collected over a 3-year period (2018–2021) [10]. In the main analysis, we used CHW supervisor wages for Registered Nurse (RN) care managers, to correspond to a common supervision structure reported in systematic reviews, accounting for a typical 1:8 ratio of RN supervisors to CHWs; in a sensitivity analysis (detailed further below), we varied the CHW supervisor to correspond to a Master’s-level Medical Social Worker (MSW) with a 1:6 ratio of MSW to CHW, to address another commonly-reported supervisor profile [11, 12]. Both the mean and standard deviations around the mean for CHW and CHW supervisor salaries were obtained from the OEWS database, for each state and each metropolitan or non-metropolitan statistical area within states (see Appendix).
The second set of input variables were overhead expenditures (Fig. 1). Based on prior accounting efforts to estimate costs among CHW programs, the overhead expenditure categories we considered in the model included equipment, software, transportation, space, and benefits. For equipment, we gathered the cost of annual mobile phone plan with unrestricted text, call and data including mobile Wi-Fi hotspot; the annualized cost of a Chromebook laptop over a typical four-year lifecycle; and costs of ongoing Information Technology (IT) support [13,14,15]. For software, we incorporated costs of CHW and CHW supervisor accounts on the most popular patient care management software systems incorporating records management, panel management, telehealth functionalities and billing [16]. For transportation, we gathered the typical time and associated mileage and gasoline expenses required for transportation from a CHW home to a patient home or CHW workspace, based on commute times by location [17]. The transportation time was included to account for both the costs of transportation itself (fuel costs, maintenance, insurance and depreciation) and opportunity costs (the wage costs to support CHWs for their time in transit, which would need to be indirectly compensated by visit-based FFS or panel-based PMPM payments) [18, 19]. For space, we computed the average cost of office space per person in the locale from a national real estate database [20]. For benefits, we assessed the overhead costs of initial and continuing CHW education based on a review of state education requirements associated with CHW certification, along with provision and administration of employer-sponsored healthcare insurance coverage (medical, dental, and vision) with a health maintenance organization or preferred-provider organization plan based on the average benefit expenditure rate reported among healthcare organizations in a national employer-sponsored benefits survey [21, 22].
Outcome Definitions
We calculated two outcomes, estimating the threshold value for each outcome to cover the total annual expenses for a CHW, after incorporating the above costs. The two outcomes were: (i) the Medicaid FFS payment rate per a 30-min visit between a CHW and an individual patient (typically Medicaid billing code 98960, which most states use as the basis for CHW payment [21]), either in person or virtually (telephone or video); or (ii) the Medicaid PMPM payment rate for every patient on the CHW’s panel at a given time.
For both outcomes, we computed the payment rates for a full-time CHW with 2080 h of work per year, with a mean patient panel of 65 patients at a given moment, and a mean 6-month duration of service per patient (varied in sensitivity analyses detailed below) [12]. All costs were summed from a CHW service provider perspective (accounting for labor and overhead including opportunity cost) over a one-year time horizon, and updated to undiscounted 2023 US Dollars using the Consumer Price Index to account for inflation [23].
Computation Methods
We estimated each outcome separately, assuming each CHW would be paid under either a Medicaid FFS or capitated PMPM contract. For each outcome, we first computed the total monthly cost to support each CHW each month by summing the total costs listed above and detailed in Table 1, scaling the estimate to a cost per CHW per month including overhead costs associated with that CHW. We then estimated the time left for visits and the associated transportation time to estimate the typical visit rate per CHW per month, with a ratio of 1:3 of in-person to virtual (phone or video) visits [24]. Finally, we estimated each of the outcome variables by estimating what threshold for payment would be the minimum amount to meet the total monthly costs given the visit rate or typical patient panel size per CHW (65 patients per CHW, each enrolled for 6 months) [12]. We completed the calculations for each state and for each sub-state metropolitan or non-metropolitan area. For validation, we compared our estimates to the program costs available from CHW program costs in two states (Virginia and Washington state) for which independent and complete wage and overhead expenditure data were available [25].
Sensitivity and Uncertainty Analysis
For each outcome, we sampled 10,000 times with replacement from normal distributions constructed around the mean and standard deviation of each input variable (Appendix) to estimate the mean and 95% credible interval (CI) around each outcome estimate [26].
We performed two sensitivity analyses. In the first sensitivity analysis, we swapped out the salary and overhead expenditures for an RN care manager supervisor for each team of eight CHWs for the salary and overhead expenditures for an MSW supervisor for each team of six CHWs [11, 12]. In the second sensitivity analysis, we varied the size of the patient panel associated with each CHW from a low of 15 to a high of 100 to understand the implications of widely varying panel size among CHW programs.
Results
Descriptive Statistics on the Input Variables
CHW wages estimated in the Bureau of Labor Statistics OEWS database had a mean national hourly wage of $23.51 (varying from $15.90 in Puerto Rico to $31.61 in Rhode Island; Fig. 2), with wages averaging $22.54 in metropolitan areas and $21.13 in non-metro areas. CHW supervisor wages when including RN care managers as supervisors had a mean national hourly wage of $39.88 (varying from $17.96 in Puerto Rico to $64.10 in California, and averaging $40.87 in metro and $38.93 in non-metro areas), where MSW supervisors had a mean national hourly wage of $29.37 (varying from $16.22 in Puerto Rico to $42.49 in California; Fig. 2).
Overhead expenditures (equipment, software, transportation, space, and benefits) per CHW work hour averaged $43.65 nationwide (varying from $19.21 in North Dakota to $196.41 in New York, and averaging $43.84 in metro and $43.46 in non-metro areas). Among the varied overhead expenditures, the highest sub-cost was universally for transportation, which constituted a mean of 65.1% of the overhead expenditure nationally (varying from 21.0% in Hawaii to 94.2% in Arkansas). In our face validity checks, wage and overhead expenditure data did not differ between model estimates and independent program data available from two states (Appendix).
Fee-for-Service Payment Rate Minimums
The minimum Medicaid fee-for-service payment rate for a 30-min CHW visit (Medicaid billing code 98960), after considering the wages and overhead costs for CHWs, was estimated to be a mean of $53.24 nationwide (95% CI $24.80, $91.11). Among states, the minimum varied from $40.44 in South Dakota (95% CI $17.65, $71.09) to $70.89 in Washington D.C. (95% CI $32.08, $120.25) due to the combination of wages and overhead costs (Table 2, Fig. 3).
Among sub-state metropolitan or non-metropolitan areas, the minimum fee-for-service payment rate for a 30-min CHW visit varied from $40.24 in the Las Cruces, New Mexico area (95% CI $17.60, $69.89) to $78.08 in the Napa, California area (95% CI $33.85, $136.93; see Appendix). Fee-for-service minimums were typically higher in metropolitan than in non-metropolitan areas but with overlapping credible intervals ($52.38 in metro, 95% CI $24.34, $89.77; $49.82 in non-metro, 95% CI $23.29, $81.15).
Capitated Payment Rate Minimums
The minimum Medicaid capitated payment rate per member per month (PMPM), after considering the same overhead costs as above, was estimated to be a mean of $140.18 nationwide (95% CI $105.94, $260.90). Among states, the minimum varied from $113.55 in South Dakota (95% CI $84.58, $229.03) to $176.58 in Washington D.C. (95% CI $132.83, $298.64; Table 2, Fig. 3).
Among sub-state metropolitan or non-metropolitan areas, the minimum PMPM rate varied from $111.76 in the Las Cruces, New Mexico area (95% CI $83.37, $223.62) to $196.08 in the Napa, California area (95% CI $156.88, $326.14). Capitated minimums were typically higher in metropolitan than in non-metropolitan areas but with overlapping credible intervals ($138.41 in metro, 95% CI $104.51, $258.02; $132.78 in non-metro, 95% CI $99.54, $250.80).
Sensitivity Analyses
In the first sensitivity analysis, when we swapped out the expenditures for an RN care manager supervisor (1 for each 8 CHWs) for an MSW supervisor (1 for each six CHWs), the minimum fee-for-service payment rate for a 30-min CHW visit was estimated as a mean of $52.80 nationwide (95% CI $24.78, $90.08), while the minimum capitated PMPM rate was estimated as a mean of $139.02 nationwide (95% CI $104.87, $258.13; see Appendix for data across states).
In the second sensitivity analysis, we varied the size of the patient panel associated with each CHW from a low of 15 to a high of 100. At the lowest panel size of 15, the minimum fee-for-service payment rate rose to a mean of $230.72 (95% CI $107.45, $394.83), and capitated PMPM to a mean of $607.45 (95% CI $459.09, $1130.55; see Appendix). At the highest panel size of 100, the minimum fee-for-service payment rate declined to a mean of $34.61 (95% CI $16.12, $59.22) and capitated PMPM to a mean of $91.12 (95%CI $68.88, $169.58; see Appendix).
Discussion
As state Medicaid agencies seek to provide sustainable funding for CHW programs, we established and applied a rigorous approach to estimating the levels of Medicaid FFS or PMPM payments to support the financial viability of CHW programs across all 50 US states, Washington D.C. and Puerto Rico. In the past, payments for services outside of face-to-face medical encounters in hospitals or clinic settings have lacked a systematic approach to establishing their basis, and CHW programs particularly face numerous challenges that differ from traditional medical visits—such as potentially meaningful transportation time to patient locations.
We found that the threshold minimum levels of both Medicaid FFS and PMPM payments estimated through our microsimulation model to sustain CHW programs were typically much higher than those currently publicly disclosed by Medicaid officials. For example, whereas the estimates in our main analysis indicated a minimum FFS rate of $53.24 nationally for a 30-min Medicaid billing code 98960, publicly-accessible Medicaid state plan amendments and waivers lack clarity on how their rates were established and indicate variations from $9.60 in Indiana to $30.89 in South Dakota [27, 28]—all much lower than the threshold to achieve financial sustainability, per our estimates. Similarly, while our minimum capitated rate estimate was $140.18 PMPM, capitated rates that are publicly disclosed appear lower, on the order of $1.65 in Maine and $9.65 in Idaho [29, 30], though such data are not systematically publicly disclosed per recent reviews of the subject [31]. Additionally, our findings indicate that meaningful accounting of overhead expenditure and local wage rates is important to account for when computing the funding levels necessary to sustain a CHW program. Overall overhead expenditures did not differ markedly between metro and non-metro areas, as transport time was higher in non-metro areas but was counterbalanced by higher employee benefit and space costs in metro areas.
As with any study based on simulations, our study is subject to limitations associated with model assumptions. First, we considered two common types of supervisor types for CHWs, but did not consider all possibilities; CHW programs vary widely in their regulation and implementation. Secondly, we consciously focused on a suite of expenditures including standard employee benefits at the overhead rates seen in the healthcare sector generally, although some CHW programs do not offer such employee benefits to CHWs. We chose to include benefit overhead expenditures intentionally, as we did not want to compute minimum thresholds for payment that did not consider the need for sustainable, long-term career potential for CHWs, and particularly wanted to ensure consideration of providing healthcare coverage to employees who themselves are providing healthcare services. Third, our study revealed that the threshold estimates for Medicaid fee-for-service and capitated rates could be sensitive to the panel size adopted by CHWs; while we adopted panel sizes from published research articles reporting successful CHW programs, it is possible that higher and lower panel sizes may be successful among varied patient populations, and associated payments would need to be adjusted accordingly. Finally, while our study focused on patients receiving Medicaid, for whom CHW programs have been carefully studied, CHW services are increasingly available to uninsured, Medicare, and commercially-insured patients who have a different burden of illness and potentially different cost structure for their infrastructure.
We believe future research on the subject of CHW payment would benefit from the broader disclosure of payment levels, as publicly-available listings for CHW payment rates were limited to a few states with Medicaid state plan amendments or waivers requiring such disclosure. Additionally, further study may be required into the intangible opportunity costs facing CHWs and affecting program sustainability, such as the availability and affordability of childcare, and of tools and data technologies needed to ensure safety when performing community-based home visits.
While such opportunities for further research may be present in coming years, our current study synthesized available data on CHW salaries, supervision, equipment, transportation, benefits and related costs across the US to provide estimates of the levels of financing needed to cover CHW program costs across different geographies. We found that to maintain patient volume or panel sizes that are consistent with the randomized trials showing benefits of CHWs on patient outcomes and healthcare costs, levels of fee-for-service and capitated program payment for CHW programs would likely need to be considerably higher than current publicly-available data sources suggest are offered for Medicaid-covered CHW services.
Data Availability
All data used for this study are publicly available, and statistical/modeling code are also available at https://github.com/sanjaybasu/chw_payment.
References
Kim, K., Choi, J. S., Choi, E., et al. (2016). Effects of community-based health worker interventions to improve chronic disease management and care among vulnerable populations: A systematic review. American Journal of Public Health, 106(4), e3–e28. https://doi.org/10.2105/AJPH.2015.302987
Berini, C. R., Bonilha, H. S., & Simpson, A. N. (2022). Impact of community health workers on access to care for rural populations in the United States: A systematic review. Journal of Community Health, 47(3), 539–553. https://doi.org/10.1007/s10900-021-01052-6
Jack, H. E., Arabadjis, S. D., Sun, L., Sullivan, E. E., & Phillips, R. S. (2017). Impact of community health workers on use of healthcare services in the united states: A systematic review. Journal of General Internal Medicine, 32(3), 325–344. https://doi.org/10.1007/s11606-016-3922-9
Olaniran, A., Smith, H., Unkels, R., Bar-Zeev, S., & van den Broek, N. (2017). Who is a community health worker? – a systematic review of definitions. Global Health Action, 10(1), 1272223. https://doi.org/10.1080/16549716.2017.1272223
Gibbons, M. C., & Tyus, N. C. (2007). Systematic review of U.S.-based randomized controlled trials using community health workers. Progress in Community Health Partnerships: Research, Education and Action, 1(4), 371–381. https://doi.org/10.1353/cpr.2007.0035
Trump, L. J., & Mendenhall, T. J. (2017). Community health workers in diabetes care: A systematic review of randomized controlled trials. Families, Systems, & Health, 35(3), 320.
Kangovi, S., Grande, D., & Trinh-Shevrin, C. (2015). From rhetoric to reality—community health workers in post-reform US health care. The New England Journal of Medicine, 372(24), 2277.
Higgins, E. (2021). State community health worker models. NASHP. Retrieved 18 Apr 2023 from https://nashp.org/state-community-health-worker-models/
Husereau, D., Drummond, M., Augustovski, F., et al. (2022). Consolidated health economic evaluation reporting standards 2022 (CHEERS 2022) statement: Updated reporting guidance for health economic evaluations. BMJ, 376, e067975. https://doi.org/10.1136/bmj-2021-067975
Division of Occupational Employment and Wage Statistics. (2022). Technical notes for May 2021 OEWS estimates. U.S. Bureau of Labor Statistics. Retrieved 18 April 2023 from https://www.bls.gov/oes/current/oes_tec.htm
Westgate, C., Musoke, D., Crigler, L., & Perry, H. B. (2021). Community health workers at the dawn of a new era: 7. Recent advances in supervision. Health Research Policy System, 19(Suppl 3), 114. https://doi.org/10.1186/s12961-021-00754-6
Kangovi, S., Mitra, N., Grande, D., Long, J. A., & Asch, D. A. (2020). Evidence-based community health worker program addresses unmet social needs and generates positive return on investment. Health Affairs, 39(2), 207–213. https://doi.org/10.1377/hlthaff.2019.00981
Shields, C. (2023). How Much Outsourced IT Support Costs in 2023. Ntiva. Retrieved 15 May 2023 from https://www.ntiva.com/blog/outsourced-it-services-benefits-and-cost
Brant, T., Westover, B. (2023). The best Chromebooks for 2023. ZiffDavis. Retrieved 15 May 2023 from https://www.pcmag.com/picks/the-best-chromebooks
Griffith, E. (2023). Business choice 2023: The best mobile phones and carriers in North America. ZiffDavis. Retrieved 15 May 2023 from https://www.pcmag.com/news/business-choice-2023-mobile-phones-and-service-providers
Kaur, B. (2023). A guide to healthcare software pricing models. Software Advice. Retrieved 15 May 2023 from https://www.softwareadvice.com/resources/healthcare-software-pricing-models/
US Census Bureau. (2023) American community survey data tables. US Census Bureau. Retrieved 15 May 2023 from https://www.census.gov/programs-surveys/acs/data/data-tables.html
Internal Revenue Service. (2023). Standard mileage rates. US Department of Treasury. Retrieved 15 May 2023 from https://www.irs.gov/tax-professionals/standard-mileage-rates
Edmunds. (2010). Depreciation infographic: How fast does my new car lose value? On edmunds.Com. CarMax. Retrieved 15 May 2023 from https://www.edmunds.com/car-buying/how-fast-does-my-new-car-lose-value-infographic.html
National Real Estate Investor. (2023). Commercial office trends. InformaConnect. Retrieved 15 May 2023 from https://www.nreionline.com/office/#menu
Rush, C., Higgins, E., Wilkniss, S. (2022). State approaches to community health worker financing through Medicaid state plan amendments. National Academy for State Health Policy. Retrieved 24 Apr 2023 from https://nashp.org/state-approaches-to-community-health-worker-financing-through-medicaid-state-plan-amendments/
US Bureau of Labor Statistics. (2023). Employer costs for employee compensation. US Department of Labor.
US Bureau of Labor Statistics. (2023). CPI inflation calculator. US Department of Treasury. Retrieved 15 May 2023 from https://www.bls.gov/data/inflation_calculator.htm
Shah, M. K., Gibbs, A. C., Ali, M. K., Narayan, K. M. V., & Islam, N. (2021). Overcoming the digital divide in the Post–COVID-19 “reset”: Enhancing group virtual visits with community health workers. Journal of Medical Internet Research, 23(7), e27682. https://doi.org/10.2196/27682
Basu, S. (2023). Waymark evidence / clinical trials. University of California San Francisco. Retrieved 16 May 2023 from https://digital.health/product-detail/waymark
Basu, S. (2015). Microsimulation. In: Systems science and population health. Oxford University Press.
Hughes, R. (2018) TN 18–005:Transmittal and notice of approval of state plan material. Family Social Services Administration. https://www.medicaid.gov/sites/default/files/State-resource-center/Medicaid-State-Plan-Amendments/Downloads/IN/IN-18-005.pdf
Snyder, W. (2019). TN 19–005: Transmittal and notice of approval of state plan material. South Dakota Department of Social Services. https://www.medicaid.gov/sites/default/files/State-resource-center/Medicaid-State-Plan-Amendments/Downloads/SD/SD-19-005.pdf
Maine Department of Health and Human Services. (2023). MaineMOM. Maine Department of Health and Human Services. Retrieved 16 May 2023 from http://www.maine.gov/dhhs/oms/about-us/projects-initiatives/mainemom
Idaho Departmetn of Health and Welfare. (2022). HC PCMH tier program proposal. Idaho Department of Health and Welfare. Retrieved 16 May 2023 from https://publicdocuments.dhw.idaho.gov/WebLink/DocView.aspx?id=14290&dbid=0&repo=PUBLIC-DOCUMENTS&cr=1
Haldar, S., Hinton, E. (2023). State policies for expanding medicaid coverage of community health worker (CHW) Services. Kaiser Family Foundation. Retrieved 31 Jan 2023 from https://www.kff.org/medicaid/issue-brief/state-policies-for-expanding-medicaid-coverage-of-community-health-worker-chw-services/
Funding
SB receives funding in part by the National Institute of Diabetes and Digestive and Kidney Diseases of the National Institutes of Health under Award Numbers R01DK125406, P30 DK092924, U18 DP006526 and R01DK116852.
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Conflict of interest
Sanjay Basu receives Grants from the National Institutes of Health and Centers for Disease Control and Prevention, personal fees from the University of California San Francisco, salary support from HealthRight360 and Waymark, has stock options in Collective Health and Waymark, and has a patents pending for ‘Multi-modal system for patient communication,’ ‘Predicted changes in risk based on interventions’ and ‘Operationalizing predicted changes in risk based on interventions’, outside the submitted work. All authors receive salary and stock options from Waymark, which trains and deploys community health workers to serve patients receiving Medicaid and their primary care providers.
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
About this article
Cite this article
Basu, S., Patel, S.Y., Robinson, K. et al. Financing Thresholds for Sustainability of Community Health Worker Programs for Patients Receiving Medicaid Across the United States. J Community Health 49, 606–634 (2024). https://doi.org/10.1007/s10900-023-01290-w
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10900-023-01290-w