Impact of Health Insurance Patterns on Chronic Health Conditions Among Older Patients

Nathalie Huguet; Tahlia Hodes; Shuling Liu; Miguel Marino; Teresa D. Schmidt; Robert W. Voss; Katherine D. Peak; Ana R. Quiñones

doi:10.3122/jabfm.2023.230106R1

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Figure 1.
Longitudinal insurance patterns from pre- to post-Medicare age eligibility among 45,527 patients from community health centers.
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Figure 2.
Multimorbidity patterns from pre- to post-Medicare age eligibility among 45,527 patients from community health centers.
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Figure 3.
Multimorbidity patterns from pre- to post-Medicare age eligibility by longitudinal insurance patterns among 45,527 patients from community health centers.
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Figure 4.
Change in rates of chronic conditions per patient from pre- to post-Medicare age eligibility by insurance patterns among 45,527 patients from community health centers.

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Table 1.

Characteristics of Patients by Longitudinal Insurance Patterns, 990 Community Health Centers

	Overall (n = 45,527)	Continuously Insured (n = 32,722)	Continuously Uninsured (n = 3,117)	Discontinuously Insured (n = 2,246)	Gained Insurance (n = 6,374)	Lost Insurance (n = 1,068)
Sex, n (%)
Woman	26,168 (57.5)	18,758 (57.3)	1,782 (57.2)	1,257 (56.0)	3,786 (59.4)	585 (54.8)
Man	19,359 (42.5)	13,964 (42.7)	1,335 (42.8)	989 (44.0)	2,588 (40.6)	483 (45.2)
Race and ethnicity, n (%)
Hispanic	14,438 (31.7)	9,658 (29.5)	1,608 (51.6)	760 (33.8)	2,024 (31.8)	388 (36.3)
Non-Hispanic Black	7,242 (15.9)	4,787 (14.6)	505 (16.2)	452 (20.1)	1,314 (20.6)	184 (17.2)
Non-Hispanic White	18,531 (40.7)	14,204 (43.4)	729 (23.4)	792 (35.3)	2,463 (38.6)	343 (32.1)
Other	2,809 (6.2)	2,199 (6.7)	130 (4.2)	137 (6.1)	274 (4.3)	69 (6.5)
Unknown	2,507 (5.5)	1,874 (5.7)	145 (4.7)	105 (4.7)	299 (4.7)	84 (7.9)
Federal poverty level, n (%)
Some or all ≥138%	12,851 (28.2)	9,374 (28.6)	549 (17.6)	601 (26.8)	2,044 (32.1)	283 (26.5)
Never Documented	6,502 (14.3)	5,620 (17.2)	274 (8.8)	174 (7.7)	362 (5.7)	72 (6.7)
All <138%	26,174 (57.5)	17,728 (54.2)	2,294 (73.6)	1,471 (65.5)	3,968 (62.3)	713 (66.8)
Geographic location, n (%)
Rural	4,843 (10.6)	3,823 (11.7)	152 (4.9)	176 (7.8)	628 (9.9)	64 (6.0)
Unknown	2,693 (5.9)	2,063 (6.3)	178 (5.7)	131 (5.8)	238 (3.7)	83 (7.8)
Urban	37,991 (83.4)	26,836 (82.0)	2,787 (89.4)	1,939 (86.3)	5,508 (86.4)	921 (86.2)
# Visits pre-period, mean (SD)	3.50 (3.96)	3.89 (4.36)	2.36 (2.70)	4.54 (3.83)	2.36 (2.37)	2.14 (2.86)
% Preventive visit	4.4	4.6	4.1	3.7	3.4	2.4
% Mental health visit	4.4	3.9	2.3	8.6	5.9	6.2
% Medicare wellness	0	0	0	0	0	0
% Other ambulatory visits	91.2	91.5	93.6	87.7	90.6	89.4
# Visits post-period, mean (SD)	9.03 (14.27)	9.18 (12.86)	6.52 (23.47)	10.47 (21.13)	8.50 (9.11)	4.93 (10.70)
% Preventive visit	2.7	2.5	3.4	4.2	2.5	4.4
% Mental health visit	0.7	3.4	1.7	5.1	5.8	9.5
% Medicare wellness	3.7	0.8	0.5	0.0	0.5	0.1
% Other ambulatory visits	92.9	93.3	94.5	90.7	91.2	88.0
≥2 Chronic conditions, n (%)
At Pre-period	35,118 (77.1)	25,944 (79.3)	2,053 (65.9)	1,679 (74.8)	4,716 (74.0)	726 (68.0)
At Post-period	39,077 (85.8)	28,543 (87.2)	2,350 (75.4)	1,920 (85.5)	5,474 (85.9)	790 (74.0)

Abbreviation: SD, Standard deviation.
Note: Sample included patient aged 62–68 years with at least one visit before and after Medicare age eligibility and insurance type recorded for every visit.

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Table 2.

Covariate-Adjusted Changes in the Relative Rate of Chronic Conditions pre- versus post-Medicare Age Eligibility by Longitudinal Insurance Patterns

	Adjusted Rate Ratio (95% CI)
*Time*
Pre-period	Reference
Post-period	1.20 (1.20,1.21)
*Longitudinal Insurance Pattern*
Continuously Insured	Reference
Continuously Uninsured	0.76 (0.73,0.78)
Discontinuously Insured	0.93 (0.90,0.96)
Gained Insurance	0.88 (0.84,0.88)
Lost Insurance	0.82 (0.79,0.87)
*Time and Longitudinal Insurance Pattern Interaction terms*
Post-Period * Continuously Uninsured	0.99 (0.98,1.01)
Post-Period * Discontinuously Insured	1.02 (1.00,1.03)
Post-Period * Gained Insurance	1.06 (1.05,1.07)
Post-Period * Lost Insurance	0.93 (0.91,0.94)

Abbreviation: CI, confidence interval.
Notes: Bolded estimates were significant at P < .05. Adjusted rates were computed using Poisson GEE models with an exchangeable correlation structure clustered on primary clinic. Estimates adjusted for sex, race and ethnicity, federal poverty level, and geographic location.