Table 2.
Association between health insurance and healthcare utilization amongst people with disabilities in LMICs
| Studies | Country | Health Insurance | Disability (measurement) | Healthcare utilization (recall period) | Results (insured vs uninsured) | Association (insured vs uninsured) | Risk of bias | |
|---|---|---|---|---|---|---|---|---|
| General healthcare utilization | Chen & Ning (2022) [96] | China | Long-term care insurance, Public | All types (Barthel Index – ADL function) |
1. Outpatient visit (last month) 2. Number of hospitalizations (last year) 3. Inpatient length of stay (last year) |
1. Reduced by 0.322 times (P < 0.01) 2. Reduced by 0.158 times (P < 0.01) 3. Reduced by 1.441 days (P < 0.01) |
Negative | Low |
| Mai (2022) [82] | China | Any health insurance | All types (ADL) | Access to healthcare services (unclear) | OR 1.2 (0.73–1.97) | Null | Low | |
| Palmer (2012) [74] | Vietnam | Compulsory health insurance, Public | All types (self-reported yes/no) |
1. Public inpatient services (12 months) 2. Public outpatient services (1 month) |
Regression coefficient 1. -0.002 SE 0.011 P > 0.1 2. 0.045 SE 0.014 P < 0.01 |
Positive | Medium | |
| Palmer (2014) [88] | Vietnam | Social health insurance, Public | All types (Washington Group Short Set) |
1. Inpatient (last 12 months) 2. Outpatient (last 1 month) 3. Self-treatment (last 1 month) |
Results from PSM 1. 0.093 (P < 0.01) 2. 0.034 (P > 0.1) 3. 0.033 (P > 0.1) Covariate matching 1. 0.111 (P < 0.01) 2. 0.107 (P < 0.01) 3. -0.042 (P < 0.01) |
Mixed | Low | |
| Shiwakoti et al. (2021) [89] | Ilam District, Nepal | Any health insurance, no informatio | All types (Washington Group Short Set) | Utilization of sexual and reproductive health services (unclear) | Crude OR: 1.2 (0.60 – 2.31) | Null | High | |
| Studies | Country | Health Insurance | Disability (measurement) | Healthcare utilization (recall period) | Results (insured vs uninsured) | Association (insured vs uninsured) | ||
| Disability-related healthcare utilization | Contentti (2019) | 12 Latin America countries | Any health insurance | Physical -Multiple sclerosis (clinical diagnosis) |
1. Disease-Modifying Therapy (DMT) past 12 months 2. MRI for diagnosis (lifetime) 3. Evoked Potential (lifetime) 4. Lumbar puncture (lifetime) 5. Rehabilitation (unclear) |
Uninsured vs insured 1. 90.9% vs 85.3%, P: 0.90 2. 98.7% vs 98.7%, P:1 3. 73.7% vs 76.6%, P: 0.42 4. 106 (67.9) vs 898 (68.3), P: 0.92 5. 35 (22.4%) vs 239 (18.2%), P: 0.19 |
Null | Low |
| El Sayed (2015) | 48 LMICs | Any health insurance | Mental (self-reported diagnosis) | Treatment uptake of persons with schizophrenia or depression (lifetime) |
Uninsured vs insured Schizophrenia 1. Male: 0.75 (0.51–1.11) 2. Female: 0.57 (0.47–0.69) Depression 1. Male: 0.59 (0.37–0.92) 2. Female: 0.93 (0.80–1.08) |
Positive | Low | |
| Fan (2022) | China | Long-term care insurance, Public | All types (ADL, disability defined > 1 limitation) | Unmet LTCI needs (unclear) |
PSM- Difference-in-Difference (DiD) coefficient: -0.107, SE: 0.05, P < 0.05 |
Positive | Low | |
| Guo (2015) [80] | China | Any health insurance | All types (physician diagnosis using ICD-10, ICF, WHO-DAS) | Healthcare utilization: curative care including surgeries and pharmaceutical treatments, auxiliary aids including assistive devices and services, and rehabilitation (unclear) |
Uninsured vs insured OR 0.80 (0.74–0.87) |
Positive | Medium | |
| Guo (2017) [81] | China | Medical insurance, Any health insurance | Mental (clinical diagnosis based on ICF, and ICD-10) | Mental health service utilization (lifetime) | AOR: 1.45 (1.21–1.72), P < 0.001 | Positive | Medium | |
| Li (2013) [92] | China | Medical insurance, Any health insurance | Mental (clinical diagnosis using ICD-10 and WHO-DAS 2) |
1. Any mental health services 2. Medical-pharmaceutical (unclear) 3. Rehabilitation (unclear) 4. Medical and rehabilitation (unclear) |
AOR 1. 1.39 (1.24–1.55) 2. 1.39 (1.24–1.56) 3. 1.10 (0.67–1.81) 4. 1.38 (1.12–1.70) |
Positive | Medium | |
| Machnicki (2011) [93] | Argentina | Private health insurance, Private | Mental – depression (clinical diagnosis, DSM IV and ICD-10) | Not receiving depression treatment – antidepressant (unclear) |
Uninsured vs insured AOR: 7.12 (1.88 – 26.86) |
Positive | High | |
| Medeiros (2021) [83] | Brazil | Any health insurance | All types (Self-reported yes/no) | Experience of attending at least one rehabilitation service (lifetime) | APR: 1.31 (1.15–1.49) P < 0.001 | Positive | Medium | |
| Nartey (2018) | Ghana | Social Health Insurance, Public | Mental (clinical diagnosis) | The use of mental health services as initial point of care – biomedical vs faith-based (unclear) | AOR 2.47 (0.60 – 10.11) P: 0.20 | Null | High | |
| Nattaj (2017) [94] | Iran | Public | Mental (clinical diagnosis) | Length of hospitalization – days staying at hospital (lifetime) | RR: 0.71 (0.59 – 0.84) P < 0.001 | Negative | High | |
| Shi (2019) [86] | China | Urban social insurance for workers, Public | Mental—(clinical diagnosis based on ICD-10) |
Mental health service utilization (2013–2016) Self-pay vs urban social insurance for workers 1. Community health centre vs specialty health centre 2. Secondary vs specialty hospital 3. Tertiary vs specialty hospital |
uninsured vs insured AOR (95% CI) 1. 29.49 (16.16 – 53.81) P < 0.0001 2. 3.49 (2.46 – 4.95) P < 0.0001 3. 9.82 (7.04 – 13.71) P < 0.0001 |
Positive | Medium | |
| Shi (2019) [86] | China | Urban social insurance for citizens, Public | Mental—(clinical diagnosis based on ICD-10) |
Mental health service utilization (2013–2016) 1. Community health centre vs specialty health centre 2. Secondary vs specialty hospital 3. Tertiary vs specialty hospital |
Urban social insurance for citizens vs urban social insurance for workers (more generous) 1. 4.01 (1.99 – 8.07) P < 0.0001 2. 0.99 (0.59 – 1.68) P: 0.992 3. 3.14 (1.83 – 5.37) P < 0.0001 |
Positive | Medium | |
| Zhang (2018) [95] | China | Urban Employee Basic Medical Insurance (UEBMI), Public | Mental – schizophrenia (clinical diagnosis based on ICD-10) |
Mental health service use based on claim 2010–2014 1. Total cost of service use 2. Inpatient 3. Outpatient Measured at baseline, first, second and third year follow up |
UEBMI (more generous) vs URBMI: Baseline 1. 42,543.1 vs 41,143.0 P: 0.021 2. 42,375.1 vs 40,917.3 P: 0.018 3. 168.0 vs 225.7 P: 0.031 Third year 1. 60,163.7 vs 51,875.6 P < 0.001 2. 60,145.2 vs 51,804.5 P < 0.001 3. 18.4 vs 71.1 P: 0.069 |
Positive | Low |
Abbreviations: APR Adjusted Prevalence Ratio, AOR Adjusted Odds Ratio, RR Risk Ratio, DiD Difference-in-difference, PSM Propensity Score Matching
Positive: Among people with disabilities, the insured have higher healthcare utilization than those uninsured. Mixed results of positive and null are categorized as positive
Negative: Among people with disabilities, the insured have lower healthcare utilization than those uninsured. Mixed results of negative and null are categorized as negative
Null: There is no difference in healthcare utilization between the insured and uninsured people with disabilities
Mixed: There is more than one measure showing positive and negative associations