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Journal of the American Board of Family Medicine logoLink to Journal of the American Board of Family Medicine
. 2025 May 12;38(1):154–164. doi: 10.3122/jabfm.2024.240186R1

Insurance Instability Among Community-Based Health Center Patients with Diabetes Post-Affordable Care Act Medicaid Expansion

Leo Lester 1, Dang Dinh 1, Annie E Larson 1, Andrew Suchocki 1, Miguel Marino 1, Jennifer DeVoe 1, Nathalie Huguet 1,
PMCID: PMC12096389  PMID: 40185641

Abstract

Background:

To evaluate insurance instability (churn) among adults with diabetes receiving care at community-based health centers (CHCs).

Methods:

Retrospective cohort study using patients’ electronic health records data for 300,158 adults aged 19 to 64 with ≥3 ambulatory visits between 2014 and 2019 of which 39,542 churned out of insurance. Generalized estimating equation-based (GEE) logistic regression models were fitted to assess the odds of churning.

Results:

Among CHC patients, those with diabetes had 1.25 greater odds of churning than those without diabetes (aOR = 1.25; 95%CI = 1.18, 1.33). Among CHC patients with diabetes, the odds of churning were higher for those with uncontrolled diabetes, more complex medication regimens, and acute diabetes complication.

Conclusions:

CHC patients with diabetes are more likely to experience insurance instability than those without diabetes. Outreach efforts to reduce the impact of the postpandemic Medicaid disenrollment among patients with diabetes and lower income will be critical to reduce harmful health consequences.

Keywords: Access to Care, Community Health Centers, Diabetes, Health Insurance, Insurance Coverage, Low-Income Population, Medicaid, Primary Health Care, Secondary Data Analysis, Social Determinants of Health

Introduction

In March 2020, states received funding for their Medicaid programs if they allowed beneficiaries to remain enrolled – referred to continuous enrollment - until the end of the public health emergency, which expired May 2023. 1 As Medicaid continuous enrollment unwinds, millions of Americans have lost, and will continue to lose, insurance coverage – over 21 million as of May 2024. 2,3 Evidence shows that up to 65% of people who disenroll from Medicaid experience a period of uninsurance during the following year. 4 This pattern of short-term disenrollment has been associated with difficulty accessing care or medication, unmet health care needs, discontinuity of care, 58 and poor health outcomes. 810 Health insurance instability may be particularly challenging for patients with diabetes needing regular chronic care management to reduce the risk of diabetes complications. Yet little is known about the frequency of insurance instability (churning) among patients with diabetes and what factors may be associated with churning. Understanding churning among patients with diabetes could provide critical information for clinics serving patients at risk for Medicaid disenrollment.

Patients receiving care in community-based health centers (CHCs) may be at particularly high risk for insurance instability following unwinding of Medicaid continuous enrollment. CHCs serve over 30 million patients yearly and provide services regardless of patients’ ability to pay. A substantial proportion of CHC patients have low income, are more likely to belong to racial and ethnic minority groups, and have multimorbidity. 11,12 Further, a large proportion of CHC patients do not have health insurance or are Medicaid beneficiaries. 11 Therefore, this study estimates the prevalence of, and factors associated with, churning out of health insurance coverage (lost Medicaid or lost Private insurance) among patients with diabetes receiving care in CHCs.

Methods

This retrospective cohort study uses electronic health records (EHR) data from the Accelerating Data Value Across a National Community Health Center Network (ADVANCE) of CHCs. 13 ADVANCE data are from OCHIN and Health Choice Network (HCN). OCHIN offers a fully hosted and tailored instance of OCHIN Epic practice management and EHR solutions. Similarly, HCN consists of a group of CHCs on a single EHR system. The data from OCHIN and HCN are centralized and standardized in the ADVANCE data warehouse using the PCORnet common data model.

We extracted data for 1,713,977 patients aged 19 to 64 seen in 354 clinics across 20 states, including Medicaid expansion and nonexpansion states, between January 2014 and December 2019 (the study period). We excluded patients who were pregnant between 2012 and 2019 or had Medicare coverage (n = 350,804) as they have different health care needs and access options. To determine longitudinal health insurance and churning status, we restricted the sample to patients with multiple ambulatory visits. Patients included had a baseline insured visit between 2014 and 2017, with ≥3 ambulatory visits occurring within the subsequent 3-year period, and ≥12 months separating the first and last of these visits (n = 300,158). Our sample included 44,864 patients with a diagnosis of diabetes (4.7% with type 1 and 95.3% with type 2 diabetes) at any time between 2012 and 2019 who were identified using ICD-9-CM and ICD-10-CM codes from problem list and encounter diagnoses, and 255,294 patients who did not have diabetes (no diagnosis, HbA1c ≥9 or insulin prescription during the study period).

Our primary outcome was a binary indicator distinguishing patients who churned out of insurance coverage vs those who did not. Those who churned (n = 39,542) were defined as having ≥2 consecutive uninsured visits. Those who did not churn included patients who had every visit insured (217,894) or a single uninsured visit (42,722). Among this last group, the uninsured visit could have been in between insured visits, possibly due to delay in enrollment (n = 30,910), or as their last visit (n = 11,812). Among the 30,910 group, 89% had their next insured visit within 12 months of the uninsured one. Insured visits were mostly paid for by Medicaid (55%), followed by Private insurance (29%), then a mix of payors (16%). Health insurance status from the EHR data are primarily based on information collected at each visit for billing purposes, 14 represent a reliable source of information on insurance status and services received at each visit, and demonstrated to have excellent agreement with Medicaid data in CHC settings. 15

Characteristics of patients include sex, age, race and ethnicity, federal poverty level, and patient rural/urban residential classification. We assessed multimorbidity status (2+ conditions excluding diabetes diagnosis), baseline payor type (Medicaid or Private), and the average number of ambulatory visits during the study period. For patients with diabetes, we evaluated glycohemoglobin (HbA1c) following Centers for Medicare & Medicaid Services quality metric 16 to determine uncontrolled status (HbA1c >9.0 averaged over 3 years from the baseline visit); whether insulin was ever prescribed during the study period; and whether other diabetes medications were prescribed over the entire study period, categorized by the complexity of the medication regimen (eg, prior authorization, demonstrated nonresponse to prior medication). Acute diabetes-related complications (abnormal blood glucose, acute kidney failure, cardiac arrest, cardiac arrythmias, congestive heart failure, diabetic ulcer, glaucoma, hyperkalemia, hypertensive emergency, hypotension or shock, infections or closely related conditions, myocardial infarction, neuropathy, noncardiac, noncerebral artery complications, stroke, transient neurological deficit, or cerebral artery occlusion) were identified using ICD-9-CM and ICD-10-CM code classifications, had to occur on or after the first diagnosis of diabetes, and were counted as distinct complications if the interval between diagnostic encounters was at least 10 days. 17

Statistical Analysis

We conducted descriptive statistics to examine characteristics and health-related factors of the study population, both overall and stratified by churning and diabetes status and compared those who churn out of insurance with those who did not using χ2 tests and t test. First, we evaluated the odds of churning by diabetes status using a generalized estimating equation-based (GEE) logistic regression model. This GEE model included an indicator denoting if a patient had diabetes (yes vs no) while controlling for demographic and health-related covariates. Second, we restricted our sample to patients with a diabetes diagnosis and further evaluated the associations between demographic/health-related factors and churning. All GEE models accounted for clustering of patients within clinics using an exchangeable working correlation and robust standard errors. All analyses were 2-sided with statistical significance set at type I error of 5%. Analyses were conducted using R Core Team (2021) and Stata version 17.0 (StataCorp 2021). The University’s Institutional Review Board approved the study.

Results

Among the 300,158 patients in the cohort, 17.0% (n = 7,954) of patients with diabetes experienced churning, while 12.0% (n = 31,588) of patients without diabetes experienced churning. Overall, among those who experience churning, 58% lost Medicaid coverage and 42% lost private insurance. The median number of visits following churning over the study period was 4 visits (range 0 to 201). The rate of patients with diabetes experiencing churning varied by state of residence from 5.0% in Massachusetts to 48.2% in Texas (Appendix Tables 1). Among patients with diabetes who lost Medicaid coverage, 46% remained uninsured, 11% switched to private insurance, and 42% regained Medicaid. Among patients with diabetes who lost private coverage, 61% remained uninsured, 8% gained Medicaid insurance, and 31% reenrolled into private insurance. The multivariate analysis shows that patients with diabetes had 1.25 greater odds of insurance churning than patients without diabetes [adjusted odd ratio (aOR) = 1.25; 95%CI = 1.18, 1.33], after adjusting for demographic and health-related factors (Table 1).

Appendix Table 1.

Number and Percent of Insurance Churning Among Patients with Diabetes Seen in Community-Based Health Centers by State from 2014 to 2019*

State Patients with Diabetes N Patients with Diabetes who Churn out of Insurance N (%)
AK** <150 <30 (17.9)
CA 6,588 892 (13.5)
FL 10,779 2,529 (23.5)
HI 441 43 (9.8)
IN 767 125 (16.3)
KS 248 69 (27.8)
MA 1,001 50 (5.0)
MD 899 120 (13.3)
MN 356 60 (16.9)
MO 706 184 (26.1)
MT 333 55 (16.5)
NC 1,756 437 (24.9)
NM 3,454 382 (11.1)
NV** <50 <10 (17.0)
OH 2,334 383 (16.4)
OR 10,374 2,041 (19.7)
RI 2,238 195 (8.7)
TX 137 66 (48.2)
WA 1,372 158 (11.5)
WI 894 132 (14.8)

*Sample included non-pregnant patients aged 19-64 without Medicare coverage who had a baseline insured visit between 2014 and 2017, with ≥3 ambulatory visits occurring within the subsequent 3-year period, and at least 12 months separating the first and last of these visits between 2014 and 2019. Those who churned were defined as having ≥2 consecutive uninsured visits. **Numbers <10 are masked to protect patients’ identities.

Table 1.

Percent and Adjusted Odds of Insurance Churning Among Patients Seen in Community-Based Health Centers from 2014 to 2019*

Total N = 300,158 Churned out of
Insurance
N = 39,542
Did Not Churn out of
Insurance
N = 260,616
aOR
of Churning
(95% CI)
N Col % N Row % N Row %
Diabetes diagnosis
 Yes 44,864 14.9 7,954 17.7 36,910 82.3 1.25 (1.18, 1.33)
 No 255,294 85.1 31,588 12.4 223,706 87.6 Reference
Sex          
 Female 184,675 61.5 26,990 14.6 157,685 85.4 Reference
 Male 115,483 38.5 12,552 10.9 102,931 89.1 0.76 (0.71, 0.82)
Age at baseline visit          
 19 to 44 166,869 55.6 21,819 13.1 145,050 86.9 Reference
 45 to 64 133,289 44.4 17,723 13.3 115,566 86.7 0.86 (0.81, 0.90)
Race/Ethnicity          
 Non-Hispanic White 129,756 43.2 11,940 9.2 117,816 90.8 Reference
 Hispanic 94,817 31.6 16,986 17.9 77,831 82.1 1.87 (1.58, 2.22)
 Non-Hispanic Black 46,497 15.5 7,742 16.7 38,755 83.3 1.73 (1.50, 1.99)
 Non-Hispanic Other 13,880 4.6 1,183 8.5 12,697 91.5 0.85 (0.75, 0.98)
 Missing 15,208 5.1 1,691 11.1 13,517 88.9 1.24 (1.09, 1.41)
Federal poverty level          
 ≤138% 211,177 70.4 30,672 14.5 180,505 85.5 1.31 (1.17, 1.47)
 >138% 54,467 18.1 6,662 12.2 47,805 87.8 Reference
 Missing 34,514 11.5 2,208 6.4 32,306 93.6 0.59 (0.46, 0.76)
Patients’ residence          
 Rural 81,695 27.2 8,548 10.5 73,147 89.5 Reference
 Urban 218,463 72.8 30,994 14.2 187,469 85.8 1.16 (0.93, 1.46)
Baseline payor type          
 Medicaid 194,208 64.7 22,863 11.8 171,345 88.2 Reference
 Private insurance 105,950 35.3 16,679 15.7 89,271 84.3 1.68 (1.47, 1.92)
Comorbidities excluding diabetes          
 Mental health disorder only 37,487 12.5 4,582 12.2 32,905 87.8 1.06 (0.99, 1.14)
 Physical comorbidity only 76,575 25.5 12,009 15.7 64,566 84.3 1.16 (1.10, 1.24)
 Mental health and physical comorbidity 44,404 14.8 5,741 12.9 38,663 87.1 1.00 (0.91, 1.09)
 None 141,692 47.2 17,210 12.1 124,482 87.9 Reference
 Mean ambulatory visits, N (SD) 12.6 11.4 15.4 13.7 12.2 11.0 1.02 (1.01, 1.03)

Abbreviations: aOR, Adjusted odds ratio; CI, Confidence interval; SD, Standard deviation.

*Sample included non-pregnant patients aged 19-64 without Medicare coverage who had a baseline insured visit between 2014 and 2017, with ≥3 ambulatory visits occurring within the subsequent 3-year period, and at least 12 months separating the first and last of these visits between 2014 and 2019. Those who churned were defined as having ≥2 consecutive uninsured visits. Those who did not churn included those who had every visit insured or those who had one single uninsured. χ2 tests for categorical variables and t test for continuous variables were used to test for differences between churning groups, except for age groups, all were significant at P < .001.

Bolded estimates are significant at P < .05.

Among patients with diabetes, those who were female, aged 19 to 44, non-Hispanic Black, or Hispanic had higher odds of churning than their counterparts (Table 2). Patients with diabetes who had private insurance before churning, had more ambulatory visits, or had both physical and mental health comorbidities also had higher odds of churning than their counterparts. Patients with uncontrolled diabetes had greater likelihood of churning (aOR = 1.33; 95%CI = 1.24, 1.43). Those with more complex diabetes medication regimens (aOR = 1.33; 95%CI = 1.19, 1.49) or with an acute diabetes complication (aOR = 1.20; 95%CI = 1.08, 1.33) had higher odds of churning. Having a prescription of insulin was not associated with churning likelihood.

Table 2.

Percent and Adjusted Odds of Insurance Churning Among Patients with Diabetes Seen in Community-Based Health Centers from 2014 to 2019*

Churned out of Insurance (n = 7954) Did Not Churn out of Insurance (n = 36,910) aOR of Churning (95% CI)
N Row % N Row %
Sex          
 Female 4,970 19.7 20,235 80.3 Reference
 Male 2,984 15.2 16,675 84.8 0.78 (0.72, 0.84)
Age      
 19 to 44 2,421 18.3 10,832 81.7 Reference
 45 to 64 5,533 17.5 26,078 82.5 0.87 (0.81, 0.93)
Race/Ethnicity      
 Non-Hispanic White 1,694 12.1 12,296 87.9 Reference
 Hispanic 3,897 22.1 13,725 77.9 1.81 (1.50, 2.19)
 Non-Hispanic Black 1,803 19.8 7,305 80.2 1.58 (1.35, 1.85)
 Non-Hispanic Other 266 12.4 1,872 87.6 0.96 (0.81, 1.14)
 Missing 294 14.7 1,712 85.3 1.21 (1.04, 1.42)
Federal poverty level      
 ≤138% 6,354 18.7 27,595 81.3 1.33 (1.15, 1.54)
 >138% 1,276 16.9 6,283 83.1 Reference
 Missing 324 9.7 3,032 90.3 0.68 (0.45, 1.03)
Patients’ residence      
 Rural 1,566 15.6 8,496 84.4 Reference
 Urban 6,388 18.4 28,414 81.6 1.12 (0.87, 1.44)
Baseline payor type      
 Medicaid 4,464 15.0 25,306 85.0 Reference
 Private insurance 3,490 23.1 11,604 76.9 1.94 (1.68, 2.25)
Comorbidities excluding diabetes      
 Mental health disorder only 310 16.1 1,616 83.9 0.99 (0.83, 1.18)
 Physical comorbidity only 4,423 19.1 18,708 80.9 1.08 (0.99, 1.17)
 Mental health and physical comorbidity 1,864 15.7 10,002 84.3 0.93 (0.84, 1.04)
 None 1,357 17.1 6,584 82.9 Reference
 Mean ambulatory visits, N (SD) 19.5 15.7 16.9 12.8 1.01 (1.00, 1.01)
HbA1c control      
 ≤9 5,343 16.4 2,7182 83.6 Reference
 >9 2,465 21.9 8,782 78.1 1.33 (1.24, 1.43)
 Missing 146 13.4 946 86.6 1.10 (0.87, 1.39)
Diabetes medication regimen complexity      
 No medication 946 12.7 6,498 87.3 Reference
 Lower complexity 4,874 18.0 22,155 82.0 1.35 (1.24, 1.47)
 High complexity 2,134 20.5 8,257 79.5 1.33 (1.19, 1.49)
Ever with insulin      
 Yes 3,496 19.6 14,360 80.4 1.06 (0.98, 1.13)
 No 4,458 16.5 22,550 83.5 Reference
Acute complications during study period      
 0  6,614 17.2 31,764 82.8 Reference
 1 807 21.6 2,922 78.4 1.20 (1.08, 1.33)
 ≥ 2 533 19.3 2,224 80.7 1.00 (0.87, 1.15)

Abbreviations: aOR, Adjusted odds ratio, CI, Confidence interval.

*Sample included non-pregnant patients aged 19-64 without Medicare coverage who had a baseline insured visit between 2014 and 2017, with ≥3 ambulatory visits occurring within the subsequent 3-year period, and at least 12 months separating the first and last of these visits between 2014 and 2019. Those who churned were defined as having ≥2 consecutive uninsured visits. Those who did not churn included those who had every visit insured or those who had one single uninsured. χ2 tests for categorical variables and t test for continuous variables were used to test for differences between churning groups, except for age groups, all were significant at P <.001. Bolded estimates are significant at P < .05.

We conducted a sensitivity analysis removing 42,722 patients with a single uninsured visit from the nonchurning group and found the same pattern of results (Appendix Tables 2 and 3).

Appendix Table 2.

Percent and Adjusted Odds of Insurance Churning Among Patients Seen in Community-Based Health Centers from 2014 to 2019* - Excluding 42,722 Patients with a Single Uninsured from Those Who Did Not Churn

Total N = 257,436 Churned out
of Insurance
N = 39,542 
Did not Churn out
of Insurance
N = 217,894 
aOR
of Churning
(95% Cl)
  N Col % N Row % N Row %
Diabetes diagnosis          
 Yes 37,775 14.7 7,954 21.1 29,821 78.9 1.27 (1.19, 1.35)
 No 219,661 85.3 31,588 14.4 188,073 85.6 Reference
Sex          
 Female 158,031 61.4 26,990 17.1 131,041 82.9 Reference
 Male 99,405 38.6 12,552 12.6 86,853 87.4 0.76 (0.71, 0.82)
Age at baseline visit          
 19-44 143,124 55.6 21,819 15.2 121,305 84.8 Reference
 45-64 114,312 44.4 17,723 15.5 96,589 84.5 0.85 (0.80, 0.90)
Race/Ethnicity          
 Non-Hispanic White 112,487 43.7 11,940 10.6 10,0547 89.4 Reference
 Hispanic 81,149 31.5 16,986 20.9 64,163 79.1 1.93 (1.61, 2.31)
 Non-Hispanic Black 38,512 15 7,742 20.1 30,770 79.9 1.85 (1.59, 2.16)
 Non-Hispanic Other 12,019 4.7 1,183 9.8 10,836 90.2 0.85 (0.73, 0.98)
 Missing 13,269 5.2 1,691 12.7 11,578 87.3 1.25 (1.09, 1.43)
Baseline payor type          
 Medicaid 165,417 64.3 22,863 13.8 142,554 86.2 Reference
 Private 92,019 35.7 16,679 18.1 75,340 81.9 1.71 (1.49, 1.96)
Federal poverty level          
 ≤138% 179,246 69.6 30,672 17.1 148,574 82.9 1.34 (1.19, 1.51)
 >138% 47,195 18.3 6,662 14.1 40,533 85.9 Reference
 Missing 30,995 12 2,208 7.1 28,787 92.9 0.56 (0.44, 0.73)
Patients’ residence          
 Rural 70,817 27.5 8,548 12.1 62,269 87.9 Reference
 Urban 186,619 72.5 30,994 16.6 155,625 83.4 1.18 (0.92, 1.51)
Comorbidities excluding diabetes          
 Mental health disorder only 32,046 12.4 4,582 14.3 27,464 85.7 1.06 (0.98, 1.14)
 Physical comorbidity only 65,421 25.4 12,009 18.4 53,412 81.6 1.16 (1.09, 1.23)
 Mental health and physical comorbidity 37,704 14.6 5,741 15.2 31,963 84.8 0.98 (0.89, 1.08)
 None 122,265 47.5 17,210 14.1 105,055 85.9 Reference
 Mean ambulatory visits, (SD) 12.4 10.9 15.4 13.7 11.8 10.3 1.03 (1.02, 1.03)

Abbreviations: aOR, Adjusted odds ratio, CI, Confidence interval; SD, standard deviation.

*Sample included non-pregnant patients aged 19-64 without Medicare coverage who had a baseline insured visit between 2014 and 2017, with ≥3 ambulatory visits occurring within the subsequent 3-year period, and at least 12 months separating the first and last of these visits between 2014 and 2019. Those who churned were defined as having ≥2 consecutive uninsured visits. Those who did not churn included those who had every visit insured. Those with one uninsured visit among those who did not churn were excluded Chi-square tests for categorical variables and t-tests for continuous variables were used to test for differences between churning groups, except for age groups, all were significant at p < .001.

Bolded estimates are significant at p < .05.

Appendix Table 3.

Percent and Adjusted Odds of Insurance Churning Among Patients With Diabetes Seen in Community-Based Health Centers from 2014 to 2019* - Excluding 42,722 Patients with a Single Uninsured from Those Who Did Not Churn

  Churned out
of Insurance
(N = 7,954)
Did not Churn out of
Insurance (N = 29,821)
aOR
of Churning
(95% Cl)
  N Row % N Row %
Sex      
 Female 4,970 23.4 16,277 76.6 Reference
 Male 2,984 18.1 13,544 81.9 0.78 (0.72, 0.85)
Age      
 19-44 2,421 21.6 8,782 78.4 Reference
 45-64 5,533 20.8 21,039 79.2 0.88 (0.82, 0.94)
Race/Ethnicity      
 Non-Hispanic White 1,694 14.3 10,155 85.7 Reference
 Hispanic 3,897 26.1 11,037 73.9 1.84 (1.51, 2.25)
 Non-Hispanic Black 1,803 24.1 5,675 75.9 1.67 (1.41, 1.99)
 Non-Hispanic Other 266 14.8 1,536 85.2 0.97 (0.81, 1.16)
 Missing 294 17.2 1,418 82.8 1.21 (1.03, 1.43)
Baseline payor type      
 Medicaid 4,464 17.9 20,502 82.1 Reference
 Private 3,490 27.2 9,319 72.8 2.00 (1.71, 2.33)
Federal poverty level      
 ≤138% 6,354 22.3 22,091 77.7 1.37 (1.17, 1.59)
 >138% 1,276 20 5,109 80 Reference
 Missing 324 11 2,621 89 0.65 (0.42, 0.99)
Patients’ residence      
 Rural 1,566 18.3 6,970 81.7 Reference
 Urban 6,388 21.8 22,851 78.2 1.14 (0.86, 1.51)
Comorbidities excluding diabetes      
 Mental health disorder only 310 19.3 1,298 80.7 0.99 (0.82, 1.20)
 Physical comorbidity only 4,423 22.7 15,093 77.3 1.06 (0.97, 1.15)
 Mental health and physical comorbidity 1,864 18.7 8,128 81.3 0.91 (0.81, 1.02)
 None 1,357 20.4 5,302 79.6 Reference
 Mean ambulatory visits, (SD) 19.5 15.7 16.4 12.2 1.02 (1.01, 1.02)
HbA1c control      
 ≤9 5,343 19.4 22,168 80.6 Reference
 >9 2,465 26.5 6,850 73.5 1.40 (1.30, 1.50)
 Missing 146 15.4 803 84.6 1.12 (0.88, 1.43)
Diabetes medication regimen complexity      
 No medication 146 15.4 803 84.6 Reference
 Lower complexity 4,874 21.3 1,7979 78.7 1.38 (1.26, 1.51)
 High complexity 2,134 24.9 6,431 75.1 1.39 (1.23, 1.58)
Ever with insulin      
 Yes 3,496 23.5 11,411 76.5 1.05 (0.97, 1.13)
 No 4,458 19.5 18,410 80.5 Reference
Acute complications during study period      
 0 6,614 20.5 25,713 79.5 Reference
 1 807 25.7 2,327 74.3 1.19 (1.06 1.33)
 ≥2 533 23 1,781 77 0.97 (0.84, 1.13)

Abbreviations: aOR, Adjusted odds ratio, CI, Confidence interval.

*Sample included non-pregnant patients aged 19-64 without Medicare coverage who had a baseline insured visit between 2014 and 2017, with ≥3 ambulatory visits occurring within the subsequent 3-year period, and at least 12 months separating the first and last of these visits between 2014 and 2019. Those who churned were defined as having ≥2 consecutive uninsured visits. Those who did not churn included those who had every visit insured. Those with one uninsured visit among those who did not churn were excluded. Chi-square tests for categorical variables and t-tests for continuous variables were used to assess differences between churning groups, except for age groups, all were significant at p < .001.

Bolded estimates are significant at p < .05.

Discussion

Overall, our findings suggest that, among patients who receive care at CHCs, those with diabetes are more likely to experience insurance instability than those without diabetes. This finding could be an artifact of visit data because patients with diabetes typically have more frequent visits and may be more likely to continue to visit their clinic during a period of uninsurance. In contrast, patients without diabetes may forgo care during a period of uninsurance leading to an underestimated rate of churning in this group. Future research is needed to evaluate the prevalence of churning among patients with other chronic health conditions to determine whether this result is specific to diabetes or not.

Notably, this analysis shows association and not causation; the methods used here do not demonstrate that churning leads to higher HbA1c, or the inverse. Future research is needed to assess the nature of the association between churning and diabetes outcomes. Further, our sample was restricted to patients with at least 3 ambulatory visits and does not capture those who exited the health system within the network. This restriction likely underestimates the rate of churning; however, a previous study showed that patient attrition within CHCs over a 3-year period is less than 20%. 18 Lastly, among those who did not churn, 5% had their last encounter as uninsured and may have been misclassified; although the sensitivity analysis (Appendix Tables 2 and 3) removing these patients from the sample did not alter the results.

It is worrisome that patients with poorer diabetes outcomes, such as uncontrolled diabetes and acute complications, seem more likely to experience insurance instability than those with better diabetes management. As millions of Americans are disenrolled from Medicaid following the end of the public health emergency, CHCs must prepare for an influx of patients with diabetes experiencing insurance instability. 19 In addition, private insurance premiums are expected to increase which could lead to more patients becoming uninsured. 20 Fortunately, CHCs provide care regardless of patients’ insurance coverage, but Medicaid is an important source of revenue for CHCs. In addition, while it may be expected that people churning out of Medicaid would enroll in marketplace plans, our study suggests that a large proportion will become and remain uninsured (51%) and few enroll in private insurance (11%). The Centers for Medicare and Medicaid Services have suggested strategies states can implement to reduce the impact of disenrollment on beneficiaries. 21 These strategies focus on reducing administrative burden and assisting beneficiaries with renewal efforts, but does not include patients who lose eligibility and are at risk of being uninsured. CHCs can provide limited assistance to help patients enroll in marketplace insurance but the increased demand may be prohibitive. State efforts should emphasize outreach and assistance to facilitate marketplace insurance enrollment and not focus exclusively on Medicaid re-enrollment and/or create state-sponsored insurance programs for people who are unable to afford or are ineligible for marketplace coverage.

Acknowledgments

The authors acknowledge the significant contributions to this study provided by collaborating investigators in the NEXT-D3 (Natural Experiments in Translation for Diabetes 3.0) Study. The research reported in this work was powered by PCORnet®. PCORnet has been developed with funding from the Patient-Centered Outcomes Research Institute® (PCORI®) and conducted with the Accelerating Data Value Across a National Community Health Center Network (ADVANCE) Clinical Research Network (CRN). ADVANCE is a Clinical Research Network in PCORnet® led by OCHIN in partnership with Health Choice Network, Fenway Health, University of Washington, and Oregon Health & Science University. ADVANCE’s participation in PCORnet® is funded through the PCORI Award RI-OCHIN-01-MC.

Footnotes

This article was externally peer reviewed.

Conflict of interest: The authors have no conflicts of interest to declare.

Funding: Research reported in this publication was jointly supported by the Centers for Disease Control and Prevention (CDC) and National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK), grant (U18DP006536). The content is solely the responsibility of the authors and does not necessarily represent the official views of the CDC or NIDDK.

To see this article online, please go to: http://jabfm.org/content/38/1/154.full.

References


Articles from Journal of the American Board of Family Medicine are provided here courtesy of American Board of Family Medicine

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