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Assessing the accuracy of survey reports of health insurance coverage using enrollment data.

ABSTRACT: OBJECTIVE:To measure the accuracy of survey-reported data on features and type of health insurance coverage. DATA SOURCE:Enrollment records from a private insurer were used as sample for primary survey data collection in spring of 2015 using the Current Population Survey health insurance module. STUDY DESIGN:A reverse record check study where households with individuals enrolled in a range of public and private health insurance plans (including the marketplace) were administered a telephone survey that included questions about general source of coverage (eg, employer), program name (eg, Medicaid), portal, premium, and subsidies. DATA COLLECTION/EXTRACTION METHODS:Survey data were matched back to enrollment records, which indicated coverage status at the time of the survey. Concordance between the records and survey data was assessed. PRINCIPAL FINDINGS:Correct reporting of general source of coverage ranged from 77.8 percent to 98.3 percent across coverage type, premium ranged from 91.6 percent to 96.4 percent, and subsidy ranged from 83.0 percent to 91.0 percent. Using a conceptual algorithm to categorize coverage type resulted in sensitivity of 98.3 percent for employer-sponsored enrollees, and 70.6 percent-77.6 percent for the other coverage types, while specificity ranged from 93.9 percent to 99.4 percent across coverage types. CONCLUSIONS:Survey reports of features of coverage suggest they are viable items to include in an algorithm to categorize coverage type. Findings have implications beyond the CPS, particularly for marketplace enrollees.

SUBMITTER: Pascale J

PROVIDER: S-EPMC6736923 | biostudies-literature | 2019 Oct

REPOSITORIES: biostudies-literature

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Assessing the accuracy of survey reports of health insurance coverage using enrollment data.

Pascale Joanne J Fertig Angela R AR Call Kathleen Thiede KT

Health services research 20190709 5

<h4>Objective</h4>To measure the accuracy of survey-reported data on features and type of health insurance coverage.<h4>Data source</h4>Enrollment records from a private insurer were used as sample for primary survey data collection in spring of 2015 using the Current Population Survey health insurance module.<h4>Study design</h4>A reverse record check study where households with individuals enrolled in a range of public and private health insurance plans (including the marketplace) were adminis ...[more]

PMID: 31287571

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Project description:BackgroundHealth insurance enrollment is a difficult financial decision with large health impacts. Challenges such as low health insurance literacy and lack of knowledge about choosing a plan further complicate this decision-making process. Therefore, to support consumers in their choice of a health insurance plan, it is essential to understand how individuals go about making this decision.ObjectiveThis study aims to understand the sources of information used by individuals to support their employer-provided health insurance enrollment decisions. It seeks to describe how individual descriptive factors lead to choosing a particular type of information source.MethodsAn introduction was presented on health insurance plan selection and the sources of information used to support these decisions from the 1980s to the present. Subsequently, an electronic survey of 151 full-time faculty and staff members was conducted. The survey consisted of four sections: demographics, sources of information, health insurance literacy, and technology acceptance. Descriptive statistics were used to show the demographic characteristics of the 126 eligible respondents and to study the response behaviors in the remaining survey sections. Proportion data analysis was performed using the Cochran-Armitage trend test to understand the strength of the association between our variables and the types of sources used by the respondents.ResultsIn terms of demographics, most of the respondents were women (103/126, 81.7%), represented a small household (1-2 persons; 87/126, 69%), and used their insurance 3-12 times a year (52/126, 41.3%). They assessed themselves as having moderate to high health insurance literacy and high acceptance of technology. The most selected and top-ranked sources were Official employer or state websites and Official Human Resources Virtual Benefits Counselor Alex. From our data analysis, we found that the use of official primary sources was constant across age groups and health insurance use groups. Meanwhile, the use of friends or family as a primary source slightly decreased as age and use increased.ConclusionsIn this exploratory study, we identified the main sources of health insurance information among full-time employees from a large state university and found that most of the respondents needed 2-3 sources to gather all the information that they desired. We also studied and identified the relationships between individual factors (such as age, gender, and literacy) and 2 dependent variables on the types of primary sources of information. We encountered several limitations, which will be addressed in future studies.

Project description:BackgroundVision health is an important aspect of health worldwide. Visual impairment (VI) is associated with poor quality of life and is usually more prevalent in rural areas. To help rural populations obtain vision care, health insurance policies have emerged throughout the world. However, some existing literatures show that health insurance enrollment's impact on the overall physical health of rural population has been minimal. Focusing on vision health among adults in rural China, our study aims to investigates the impact of health insurance on vision health, heterogeneity of the effect, and the moderating effect of health insurance enrollment on the impact of chronic physical diseases and basic eye diseases on vision health.MethodsPrimary data were collected through a nation-wide epidemiological survey of vision health conducted in rural China in 2018, with a sample size of 28,787 used in our statistical analysis. Instrumental variables regression and Heckman selection models were conducted to examine the impact of health insurance enrollment and reimbursement ratio adults' vision health outcomes. Subsample regressions by sex, age, education level, and whether with eye diseases were further conducted to explore the heterogeneity in our results. We then examined whether health insurance enrollment moderates the impact of chronic physical diseases and basic eye diseases on vision health through the method of introducing interaction terms.ResultsParticipating in health insurance reduced the probability of VI by 2.15 %. The reimbursement rate increasing by 1 % point may reduce the probability of worsening VI by 6.12 %. Men (-0.0235, P = 0.0002) benefit more from insurance enrollment than women (-0.0201, P = 0.0082) with respect to vision health. From the young adult group to the oldest group, the marginal effect of health insurance increased from - 0.0068 (P = 0.0394) to -0.0753 (P < 0.0001). The marginal effect on VI was most significant in people with lower education levels and weakened with increased education levels. People with basic eye diseases (-0.0496, P = 0.0033) benefit more from participating insurance than the people without basic eye diseases (-0.0196, P = 0.0001) with respect to vision health. The moderating effects of health insurance enrollment on the impacts of cerebral infarction (-0.1225, P < 0.0001), diabetes (-0.0398, P = 0.0245), hyperlipidemia (-0.1364, P = 0.0271), mental illness (-0.1873, P = 0.0010), glaucoma (-0.1369, P = 0.0073), diabetic retinopathy (-0.1560, P = 0.0043), and retinal vein obstruction (-0.2018, P = 0.0155) on vision health were significantly negative.ConclusionsThe results suggest that participation in health insurance and higher health insurance reimbursement ratios reduced the risk of VI in the sampled adults. Health insurance has the most significant effect in in vulnerable groups. Heath insurance enrollment moderates the impacts of several chronic physical and basic eye conditions on vision health. Our findings have potential implications for reforming health insurance policies to improve vision health conditions in rural areas of developing countries.

Project description:BACKGROUND: China has one of the world's largest health insurance systems, composed of government-run basic health insurance and commercial health insurance. The basic health insurance has undergone system-wide reform in recent years. Meanwhile, there is also significant development in the commercial health insurance sector. A phone call survey was conducted in three major cities in China in July and August, 2011. The goal was to provide an updated description of the effect of health insurance on the population covered. Of special interest were insurance coverage, gross and out-of-pocket medical cost and coping strategies. RESULTS: Records on 5,097 households were collected. Analysis showed that smaller households, higher income, lower expense, presence of at least one inpatient treatment and living in rural areas were significantly associated with a lower overall coverage rate. In the separate analysis of basic and commercial health insurance, similar factors were found to have significant associations. Higher income, presence of chronic disease, presence of inpatient treatment, higher coverage rates and living in urban areas were significantly associated with higher gross medical cost. A similar set of factors were significantly associated with higher out-of-pocket cost. Households with lower income, inpatient treatment, higher commercial insurance coverage, and living in rural areas were significantly more likely to pursue coping strategies other than salary. CONCLUSIONS: The surveyed cities and surrounding rural areas had socioeconomic status far above China's average. However, there was still a need to further improve coverage. Even for households with coverage, there was considerable out-of-pocket medical cost, particularly for households with inpatient treatments and/or chronic diseases. A small percentage of households were unable to self-finance out-of-pocket medical cost. Such observations suggest possible targets for further improving the health insurance system.

Project description:BackgroundNationally representative household surveys are the gold standard for tracking progress in coverage of life-saving maternal and child interventions, but often do not provide timely information on coverage at the local and health facility level. Electronic routine health information system (RHIS) data could help provide this information, but there are currently concerns about data quality. This analysis seeks to improve the usability of and confidence in electronic RHIS data by using adjustments to calculate more accurate numerators and denominators for essential interventions.MethodsData from three sources (Ugandan Demographic and Health (UDHS) survey, electronic RHIS, and census) were used to provide estimates of essential maternal (> 4 antenatal care visits (ANC), skilled delivery, and postnatal care visit (PNC)) and child health interventions (diphtheria, pertussis, tetanus, and hepatitis B and Haemophilus influenzae type b and polio vaccination series, measles vaccination, and vitamin A). Electronic RHIS data was checked for quality and both numerators and denominators were adjusted to improve accuracy. Estimates were compared between the three sources.ResultsEstimates of maternal health interventions from adjusted electronic RHIS data were lower than those of the UDHS, while child intervention estimates were typically higher. Adjustment of electronic RHIS data generally improved accuracy compared with no adjustment. There was considerable agreement between estimates from adjusted, electronic RHIS data, and UDHS for skilled delivery and first dose of childhood vaccination series, but lesser agreement for ANC visits and second and third doses of childhood vaccinations.ConclusionsNationally representative household surveys will likely continue being the gold standard of coverage estimates of maternal and child health interventions, but this analysis shows that current approaches to adjusting health facility estimate works better for some indications than others. Further efforts to improve accuracy of estimates from RHIS sources are needed.

Project description:ObjectivesTo analyse the relationship between health need, insurance coverage, health service availability, service use, insurance claims and out-of-pocket spending on health across Indonesia.DesignSecondary analysis of nationally representative quantitative data. We merged four national data sets: the National Socioeconomic Survey 2018, National Census of Villages 2018, Population Health Development Index 2018 and National Insurance Records to end 2017. Descriptive analysis and linear regression were performed.SettingIndonesia has one of the world's largest single-payer national health insurance schemes. Data are individual and district level; all are representative for each of the country's 514 districts.ParticipantsAnonymised secondary data from 1 131 825 individual records in the National Socioeconomic Survey and 83 931 village records in the village census. Aggregate data for 220 million insured citizens.Primary outcome measuresHealth service use and out-of-pocket payments, by health need, insurance status and service availability. Secondary outcome: insurance claims.ResultsSelf-reported national health insurance registration (60.6%) is about 10% lower compared with the insurer's report (71.1%). Insurance coverage is highest in poorer areas, where service provision, and thus service use and health spending, are lowest. Inpatient use is higher among the insured than the uninsured (OR 2.35, 95% CI 2.27 to 2.42), controlling for health need and access), and poorer patients are most likely to report free inpatient care (53% in wealth quintile 1 vs 41% in Q5). Insured patients spend US$ 3.14 more on hospitalisation than the uninsured (95% CI 1.98 to 4.31), but the difference disappears when controlled for wealth. Lack of services is a major constraint on service use, insurance claims and out-of-pocket spending.ConclusionsThe Indonesian public insurance system protects many inpatients, especially the poorest, from excessive spending. However, others, especially in Eastern Indonesia cannot benefit because few services are available. To achieve health equity, the Indonesian government needs to address supply side constraints and reduce structural underfunding.

Project description:IntroductionThe provision of non-contributory public health insurance (NPHI) to marginalised populations is a critical step along the path to universal health coverage. We aimed to assess the extent to which Ayushman Bharat-Pradhan Mantri Jan Arogya Yojana (PM-JAY)-potentially, the world's largest NPHI programme-has succeeded in raising health insurance coverage of the poorest two-fifths of the population of India.MethodsWe used nationally representative data from the National Family Health Survey on 633 699 and 601 509 households in 2015-2016 (pre-PM-JAY) and 2019-2021 (mostly, post PM-JAY), respectively. We stratified by urban/rural and estimated NPHI coverage nationally, and by state, district and socioeconomic categories. We decomposed coverage variance between states, districts, and households and measured socioeconomic inequality in coverage. For Uttar Pradesh, we tested whether coverage increased most in districts where PM-JAY had been implemented before the second survey and whether coverage increased most for targeted poorer households in these districts.ResultsWe estimated that NPHI coverage increased by 11.7 percentage points (pp) (95% CI 11.0% to 12.4%) and 8.0 pp (95% CI 7.3% to 8.7%) in rural and urban India, respectively. In rural areas, coverage increased most for targeted households and pro-rich inequality decreased. Geographical inequalities in coverage narrowed. Coverage did not increase more in states that implemented PM-JAY. In Uttar Pradesh, the coverage increase was larger by 3.4 pp (95% CI 0.9% to 6.0%) and 4.2 pp (95% CI 1.2% to 7.1%) in rural and urban areas, respectively, in districts exposed to PM-JAY and the increase was 3.5 pp (95% CI 0.9% to 6.1%) larger for targeted households in these districts.ConclusionThe introduction of PM-JAY coincided with increased public health insurance coverage and decreased inequality in coverage. But the gains cannot all be plausibly attributed to PM-JAY, and they are insufficient to reach the goal of universal coverage of the poor.

Dataset Information

Assessing the accuracy of survey reports of health insurance coverage using enrollment data.

Publications

Assessing the accuracy of survey reports of health insurance coverage using enrollment data.

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