Insurance Enrollment Research Articles

Urban Trail Exposure in Winnipeg, Canada: Longitudinal Cohort Development for a 20-Year Difference-in-Differences Analysis of a Natural Experiment with Varied Duration of Exposure Times

ObjectiveDevelop a cohort to evaluate a real-world experiment of the built environment on the incidence of disease, accounting for movement of people, postal codes, incidence of disease and changing demographics. ApproachThe City of Winnipeg, Canada built multi-use trails in 2010-2012. We used the administrative data housed at the Manitoba Centre for Health Policy to evaluate the effect of this change in the built environment on the incidence of cardiovascular disease events (CVDE) and risk factors (CVDRF) before (2000-2009) and after (2012-2019) the trails were built. The Manitoba Health Insurance Registry contains postal code and demographic information on nearly all city residents and was utilized for cohort creation and person-time exposure. Individuals’ residential postal codes were linked to geo-spatial data to determine proximity to built trails at 400m, 800m and 1200m. Semi-annual postal code changes accounted for movement within/outside city limits or exclusion from the cohort. Diagnoses from hospital abstract and physician visit data and outpatient prescription dispensations were used to access prevalence and incidence of a CVDE composite measure of congestive heart failure, ischemic heart disease and stroke and a CVDRF composite measure of diabetes, dyslipidemia and hypertension. Conclusions and ImplicationsLeveraging a diverse set of administrative databases, we built a cohort evaluate the effect of building multi-use trails in Winnipeg on the reduction on CVDE and CVDRF. This demonstrates how administrative data can be used to evaluate natural, real-world experiments with minimal direct data measurement or public intrusion, resulting in actionable results to inform public policy.

The employment, retention and exit of public school teachers in New Brunswick, Canada: an analysis using linked administrative data

ObjectiveAs in many jurisdictions, New Brunswick (Canada) is facing increasing shortages of K-12 school teachers as retirements loom at the same time that the school age population of NB continues to exceed long term trends. The purpose of this retrospective study is to analyze the recruitment, retention and exit decisions of teachers in the NB public education system in order to support ongoing planning around teacher staffing. ApproachThe analysis uses a unique linked administrative data combining province-wide individual-level teacher employment data, immigration records, university graduation data and public health insurance registration on NB teachers and individuals who obtained a B.Ed. degree in NB. Data are accessed through the secure facilities of the NB Institute for Research, Data and Training. The analysis includes both descriptive statistics and econometric methods appropriate to the particular outcomes of interest. ResultsThe analysis will present results on three types of labour market transitions: 1) from NB university education to employment as a NB teacher. 2) exits from employment as a teacher, including both retirement and pre-retirement exits, and 3) decisions of ex-teachers about remaining in NB. The potential effects of a range of demographic, geographic and system-level factors on these outcomes are considered. Conclusions and ImplicationResults from the analysis of entry to and exit from K-12 teaching in NB will be vital to human resource planning for a province dealing with looming retirements, growing labour shortages and an increasing population. Future work will consider subject-specific teacher shortages in critical fields like STEM.

Emergency Medicaid enrollment after traumatic injury predicts long-term health care utilization.

Injured patients have high rates of uninsurance, which is associated with worse outcomes. Insurance linkage programs that connect patients to Medicaid coverage can prevent catastrophic costs for patients. Less is known about the long-term impact of insurance enrollment. We examined health care utilization for previously uninsured patients, hypothesizing that newly insured patients postinjury would use health care more than those remaining uninsured. We linked institutional trauma registry data to the electronic medical record to identify injured patients aged 18 to 64 years from 2017 to 2021. Patients admitted without insurance and then retroactively insured (RI) during hospitalization were compared with patients with preestablished Medicaid (Medicaid insured [MI]) and those remaining uninsured. We compared demographic and injury characteristics and future health care utilization, including hospitalizations, emergency department (ED) visits, and clinic visits, among groups at 30 days and 12 months postinjury. Patient-reported outcomes (PROs) 6 months after injury were compared by group for a subset of patients participating in an ongoing study of long-term PROs. We compared 494 RI patients with 1,706 MI and 148 uninsured patients. Retroactively insured patients were younger, more likely to have penetrating injuries, and longer hospitalization than other groups. There was a significant increase in ED and clinic visits and hospital admissions at 30 days and 12 months between RI and uninsured patients (p < 0.001). Using multivariable logistic regression, RI was associated with higher future ED utilization, hospital admissions, and specialist visits at 30 days and 12 months compared with uninsured patients. Of the 265 patients with 6-month PROs, Medicaid coverage was not associated with any significant difference in physical function or anxiety. Patients enrolled in insurance postinjury are more likely to use health care in the future than patients without insurance, but the downstream effects are less clear. Health insurance is a necessary step but not independently sufficient to optimize care and improve health outcomes. Prognostic and Epidemiological; Level IV.

Revision Surgery after Single Level Anterior Cervical Discectomy and Fusion With Plate vs Stand-Alone Cage over 2 to 5 Year Follow-Up.

retrospective study. To investigate the incidence of all-cause revision surgery between plated vs stand-alone cage constructs for single level ACDF. We retrospectively analyzed a commercial insurance claims database. Patients 18-65years-old were included if they underwent single-level inpatient ACDF (defined with CPT codes) from 2010 - 2018, with a minimum of 2-year continuous insurance enrollment. The primary independent variable was the use of anterior plating vs zero profile device or stand-alone cage. Synthetic (ie, metal, PEEK, etc.) vs allograft interbody was a secondary independent variable. The primary outcome variable was revision cervical arthrodesis after the index operation. In total, 21092 patients undergoing single-level inpatient ACDF were included. 10.0% received a stand-alone cage during the index operation. Mean follow-up duration was 4.5years. Revision arthrodesis occurred in 8.2% of patients overall, at a mean of 2.4years after the index surgery. Patients with anterior plating had a lower rate of all-cause revision surgery in unadjusted (overall rate 8.1% vs 9.6%, P = 0.0185) and adjusted analysis (OR 0.78, P = 0.0016) vs stand-alone cages. Patients with stand-alone cages had higher rates of revision with a posterior approach than did patients with plated constructs. In sub-analysis, the combination of a stand-alone interbody device with an allograft had significantly higher odds of revision than other combinations of devices. Among commercially insured patients ≤65years-old undergoing single-level ACDF, anterior plating was associated with a reduced incidence of revision surgery compared to stand-alone cages within the follow up period of our study.

Health Insurance Enrollment Among US Veterans, 2010-2021

Department of Veterans Affairs (VA) health care spending has increased in the past decade, in part due to legislative changes that expanded access to VA-purchased care. To understand how insurance coverage and enrollment in VA has changed between 2010 and 2021. This cross-sectional study used data from surveys conducted from 2010 to 2021. Participants were respondents across 4 national surveys who reported being a US veteran and reported on health insurance enrollment. Data were analyzed from October 2023 to June 2024. Self-reported health insurance coverage, reliance on VA insurance, and self-reported health. Among a total of 3 644 614 survey respondents (mean [SE] age, 60 [0.04] years; 91.3% [95% CI, 91.2%-91.5%] male) included, 52.2% (95% CI, 52.0%-52.4%) were out of the labor market and 63.1% (95% CI, 62.9%-63.3%) were married. In 2010, 94% of all veterans and 94% of veterans younger than age 65 years reported having health insurance coverage on the American Community Survey. Insurance enrollment increased over time, and by 2020, 97% of all veterans and 95% of veterans younger than 65 years reported having health insurance coverage on the American Community Survey. Insurance enrollment estimates were similar across the surveys. Approximately one-third of veterans reported being enrolled in VA health coverage. Of those who enrolled in VA insurance, more than 75% had more than 1 form of coverage, with Medicare and private insurance being the most common second insurance sources. VA insurance enrollment was negatively associated with income and health status. Veterans without insurance tended to be unemployed and younger. This study of veterans who responded to 4 national surveys found that veterans enrolled in VA health coverage had high rates of dual coverage. Further legislative efforts to increase access without recognizing the high rates of dual coverage may yield unintended consequences, such payer shifting.

Social capital, health risk avoidance, and the enrollment of health insurance: The case of rural middle-aged and elderly in China

Low enrollment intention threatens the funding pools of rural insurance schemes in developing countries. The purpose of this study is to investigate how social capital enhances the enrollment of health insurance among rural middle-aged and elderly. We propose that social capital directly increases health insurance enrollment, while indirectly influences health insurance through health risk avoidance. We used data from the China Health and Retirement Longitudinal Study (wave 4) dating the year of 2018, instrumental variable estimation was introduced to deal with the endogeneity problem, and the mediation analysis was used to examine the mechanism of social capital on insurance enrollment. The results show that social capital is positively related to social health insurance enrollment, and the relationship between social capital and social health insurance enrollment is mediated by health risk avoidance.

Impact of Government-Funded Health Insurance on Out-of-Pocket Expenditure and Quality of Hospital-Based Care in Indian States of Madhya Pradesh and Maharashtra.

With its clear focus on financial protection, government-funded health insurance (GFHI) stands out among the strategies for universal health coverage (UHC) implemented by low-to-middle income countries globally. Since 2018, India has implemented a GFHI programme called the Ayushman Bharat Pradhan Mantri Jan Arogya Yojana (AB-PMJAY), which covers 500 million individuals. The current study aims to evaluate the performance of GFHI in meeting its key objectives of improving access, quality and financial protection for hospital-based care in two large central Indian states: Madhya Pradesh and Maharashtra. The study measures access in terms of utilisation of inpatient care. Financial protection was measured in terms of catastrophic health expenditure which was defined as the incidence of out-of-pocket expenditure (OOPE) above thresholds of 10% and 25% of annual household expenditure. Patient-satisfaction with care was taken as an indicator of quality. A household survey was conducted in 2023, covering a multi-stage sample of 11,569 and 12,384 individuals in Madhya Pradesh and Maharashtra, respectively. Multi-variate analyses were conducted to find the effect of GFHI-enrolment on the desired outcomes. The instrumental variable method was applied to address potential endogeneity in insurance enrolment. Additionally, propensity score matching was done to ensure robustness. Around 71% and 63% of surveyed individuals were enrolled under GFHI in Madhya Pradesh and Maharashtra, respectively. The hospitalisation rate did not differ much between the GFHI-enrolled and non-enrolled population. The average OOPE on hospitalisation was similar for the GFHI-enrolled and non-enrolled patients. The OOPE and catastrophic health expenditure in private hospitals remained very high, irrespective of GFHI enrolment. The pattern was similar in both states. Multi-variate adjusted models showed that GFHI had no significant effect on utilisation, quality, OOPE and catastrophic health expenditure. The above results were confirmed by propensity score matching. Coverage by GFHI enrolment was ineffective in improving access, quality or financial protection for inpatient hospital care despite 5 years of implementation of the programme. Long-standing supply-side gaps and poor regulation of private providers continue to hamper the effectiveness of GFHI in India.

Prevalence and incidence measures for schizophrenia among commercial health insurance and medicaid enrollees

Given the chronic nature of schizophrenia, it is important to examine age-specific prevalence and incidence to understand the scope of the burden of schizophrenia across the lifespan. Estimates of lifetime prevalence of schizophrenia have varied widely and have often relied upon community-based data estimates from over two decades ago, while more recent studies have shown considerable promise by leveraging pooled datasets. However, the validity of measures of schizophrenia, particularly new onset schizophrenia, has not been well studied in these large health databases. The current study examines prevalence and validity of incidence measures of new diagnoses of schizophrenia in 2019 using two U.S. administrative health databases: MarketScan, a national database of individuals receiving employer-sponsored commercial insurance (N = 16,365,997), and NYS Medicaid, a large state public insurance program (N = 4,414,153). Our results indicate that the prevalence of schizophrenia is over 10-fold higher, and the incidence two-fold higher, in the NYS Medicaid population compared to the MarketScan database. In addition, prevalence increased over the lifespan in the Medicaid population, but decreased in the employment based MarketScan database beginning in early adulthood. Incident measures of new diagnoses of schizophrenia had excellent validity, with positive predictive values and specificity exceeding 95%, but required a longer lookback period for Medicaid compared to MarketScan. Further work is needed to leverage these findings to develop robust clinical outcome predictors for new onset of schizophrenia within large administrative health data systems.

Contract Termination and Insurance Enrollment Among Medicare Advantage Beneficiaries

Approximately one-fifth of Medicare Advantage (MA) contracts terminated their participation in the MA program between 2011 and 2020. Little is known about subsequent insurance choices following a termination. To examine the insurance destinations of MA enrollees and the characteristics of enrollees who switch into traditional Medicare (TM) after a contract termination. This cross-sectional study examined MA program data of MA beneficiaries in the Medicare Master Beneficiary File from 2016 to 2018. Statistical analysis was performed from June 2023 to April 2024. Beneficiary characteristics, including age, sex, race and ethnicity, dual eligibility; hospital, nursing home, and home health utilization; and contract characteristics, including plan type, vertical integration, premium, and MA star rating. The main outcome was switching to TM in the year immediately after termination. We also evaluated the characteristics of contracts among those who remained in MA. A total of 117 681 beneficiaries were included in this analysis (64 654 [54.9%] female; 409 [0.4%] American Indian or Alaska Native; 2817 [2.4%] Asian; 76 725 [16.8%] Black; 11 131 [9.5%] Hispanic; 81 226 [69.0%] White; and 2373 [2.0%] other race or ethnicity; 27 078 [23.0%] dual-eligible; mean [SD] age, 71.2 [10.4] years). Following a contract termination, 20.1% (95% CI, 19.9%-20.4%) of enrollees switched to TM, including 32.7% (95% CI, 32.4%-33.1%) of dual-eligible beneficiaries and 16.4% (95% CI, 16.2%-16.5%) of non-dual-eligible beneficiaries. In nonterminated contracts, the concurrent switch rate was 6.2% (95% CI, 6.2%-6.2%) for all, 10.4% (95% CI, 10.4%-10.4%) for dual-eligible beneficiaries and 5.1% (95% CI, 5.1%-5.1%) for non-dual-eligible enrollees. The highest switch rates to TM were among Black enrollees (32.3% [95% CI, 31.7%-32.8%]) and those with prior use of hospital (31.3% [95% CI, 30.7%-31.9%], nursing home, 41.4% [95% CI, 40.4%-42.4%], or home health care (28.3% [95% CI, 27.4%-29.2%]). Beneficiaries who stayed in MA selected higher-rated star plans (mean posttermination contract star rating of 3.8 [95% CI, 3.8-3.8] stars compared with 3.3 [95% CI, 3.3-3.3] stars in the terminated year), but did not pay more in monthly premiums with 66.5% (95% CI, 66.2%-66.8%) paying the same or lower premiums. In this cross-sectional study, 1 in 5 MA beneficiaries switched to TM after a contract termination, with Black beneficiaries and those with more intensive health needs having the highest switch rates. These findings highlight the need to examine consequences of contract terminations and subsequent insurance destinations on access to care and health outcomes, especially among those with marginalized race and ethnicity, those who are dual-eligible, and beneficiaries with higher health care needs.

Cancer information and population health resource: a resource for catchment area data and cancer outcomes research.

The University of North Carolina at Chapel Hill Lineberger Comprehensive Cancer Center has developed a novel data resource, the Cancer Information and Population Health Resource (CIPHR), for conducting catchment area evaluation and cancer population health research that links the North Carolina Central Cancer Registry (NCCCR) to medical and pharmacy claims data from Medicare, Medicaid, and private plans operating within North Carolina. This study's aim was to describe the CIPHR data and provide examples of potential cohorts available in those data. We present the underlying populations included in the NCCCR and claims data before linkage and demonstrate estimated sample sizes when these data are linked and commonly used insurance enrollment criteria are applied. Data for the years 2003-2020 are present in CIPHR and include 947 977 cancer cases from the NCCCR and 21.6 million enrollees in public and private health insurance (cancer and noncancer cases). When limited to first or only cancers (n = 672 377), 86% could be linked to insurance enrollment for at least 1 month during 2003-2020 (n = 582 638), with 62% of individuals linking to enrollment during the month of cancer diagnosis. Among all registry cancer cases, 47% (n = 317 898) had continuous insurance enrollment for at least 12 months before and after cancer diagnosis. CIPHR illustrates the utility of establishing and maintaining a statewide, comprehensive cancer population health database. This resource serves to characterize the cancer center catchment area and aids in tracking cancer outcomes and trends in care delivery as well as identifying disparities that require intervention and policy focus.

Impact of Direct Health Facility Financing on Health Insurance Enrollment and Service Quality in Dodoma Region, Tanzania

The National Health Insurance Fund (NHIF) and the Improved Community Health Fund (iCHF) are pre-payment schemes in Tanzania designed to achieve universal health coverage (UHC). Despite these efforts, public health facilities have historically struggled with poor-quality care. In response, the Direct Health Facility Financing (DHFF) mechanism was introduced in 2017, enabling health facilities to procure medicines and equipment directly from approved vendors when out-of-stock notifications are received from the Medical Store Department (MSD). This study evaluates the impact of DHFF on health insurance enrollment and service quality in the Dodoma Region. Utilizing a mixed-methods approach with an explanatory sequential design, a total of 35 respondents were involved in the proposed study, of which 30 were obtained from health insurance beneficiaries and 5 were from key informants. Results revealed increased health insurance enrollment for both NHIF and iCHF from 2018–2019 to 2019–2020, attributed to enhanced medicine availability, community education, and sensitization efforts. Beneficiaries reported significant improvements in health facilities, including better medicine availability, upgraded infrastructure, and improved attitudes from healthcare providers. Healthcare providers and authorities also noted improved service quality since DHFF's introduction. However, challenges remain, particularly with MSD's rigidity in notifying health facilities about out-of-stock items. Recommendations include enhancing the MSD's supply chain management to ensure timely notifications and deliveries. Future research should expand to multiple regions to account for cultural variations and additional factors influencing health insurance participation, enrollment, and service quality.

Metformin in Chemoprevention of Lung Cancer: A Retrospective Population-Based Cohort Study in Lithuania.

Background and Objectives: This study aimed to evaluate the potential chemopreventive effect of antidiabetic medications, specifically metformin and pioglitazone, on lung cancer in patients with type 2 diabetes mellitus (T2DM). Additionally, the potential dose-response relationship for metformin use was analyzed. Methods: We conducted a retrospective cohort study utilizing comprehensive national health insurance and cancer registry databases to gather a large cohort of T2DM patients. Cox proportional hazards regression models were used to assess the risk of lung cancer across different antidiabetic medication groups, adjusting for potential confounders such as age and gender. A dose-response analysis was conducted for metformin users. Results: Our results indicated that metformin users had a significantly lower lung cancer risk than the reference group (HR = 0.69, 95% CI [0.55-0.86], p = 0.001). The risk reduction increased with higher cumulative metformin doses: a metformin cumulative dose between 1,370,000 and 2,976,000 had an HR of 0.61 (95% CI [0.49-0.75], p < 0.001) vs. cumulative metformin dose >2,976,000 which had an HR of 0.35 (95% CI [0.21-0.59], p < 0.001). No significant association between pioglitazone use and the risk of lung cancer was found (HR = 1.00, 95% CI [0.25-4.02]). Conclusions: This study shows that metformin may have a dose-dependent chemopreventive effect against lung cancer in T2DM, while the impact of pioglitazone remains unclear and requires further investigation.

National health insurance enrolment among elderly ghanaians: the role of food security status

Older people with food insecurity in Ghana are often exposed to poor health conditions, highlighting the importance of the National health Insurance Scheme (NHIS) enrolment for ensuring they receive necessary medical attention through access to health care services. However, we know very little about the association between food insecurity and National Health Insurance Scheme enrolment among older people in Ghana. To address this void in the literature, this study uses a representative survey of adults aged 60 or older from three regions in Ghana (i.e., Upper West, Bono, and Greater Accra regions (n = 1,073)). We find that 77% of older adults reported not being enrolled into the NHIS. Results from logistic regression analysis show that older people who experienced severe household food insecurity were less likely to enroll in the National Health Insurance Scheme than those who did not experience any food insecurity (OR = 0.48 p < 0.001). Based on these findings, we argue that in addition to the traditional socioeconomic factors, addressing severe food insecurity may improve health insurance enrolment among older adults. Additionally, policymakers should also consider older people’s socioeconomic circumstances when formulating policies for them to enrol in health insurance.

Rural-urban disparity in community-based health insurance enrollment in Ethiopia: a multivariate decomposition analysis using Ethiopian Mini Demographic Health Survey 2019.

In sub-Saharan Africa, achieving universal health coverage (UHC) and protecting populations from health-related financial hardship remain challenging goals. Subsequently, community-based health insurance (CBHI) has gained interest in low and middle-income countries, such as Ethiopia. However, the rural-urban disparity in CBHI enrollment has not been properly investigated using multivariate decomposition analysis. Therefore, this study aimed to assess the rural-urban disparity of CBHI enrollment in Ethiopia using the Ethiopian Mini Demographic Health Survey 2019 (EMDHS 2019). This study used the latest EMDHS 2019 dataset. STATA version 17.0 software was used for analyses. The chi-square test was used to assess the association between CBHI enrollment and the explanatory variables. The rural-urban disparity of CBHI enrollment was assessed using the logit-based multivariate decomposition analysis. A p-value of <0.05 with a 95% confidence interval was used to determine the statistical significance. The study found that there was a significant disparity in CBHI enrollment between urban and rural households (p < 0.001). Approximately 36.98% of CBHI enrollment disparities were attributed to the compositional (endowment) differences of household characteristics between urban and rural households, and 63.02% of the disparities were due to the effect of these characteristics (coefficients). The study identified that the age and education of the household head, family size, number of under-five children, administrative regions, and wealth status were significant contributing factors for the disparities due to compositional differences between urban and rural households. The region was the significant factor that contributed to the rural-urban disparity of CBHI enrollment due to the effect of household characteristics. There were significant urban-rural disparities in CBHI enrollment in Ethiopia. Factors such as age and education of the household head, family size, number of under-five children, region of the household, and wealth status of the household contributed to the disparities attributed to the endowment, and region of the household was the contributing factor for the disparities due to the effect of household characteristics. Therefore, the concerned body should design strategies to enhance equitable CBHI enrollment in urban and rural households.

Predictive Modeling of Future Trends in US Healthcare Data and Outcomes

Predictive modeling has great potential to help guide healthcare policymaking and planning through forecasting future trends in domains such as disease prevalence, resource utilization, and costs. However, past research in this area has been limited by mostly examining small, narrow datasets that only captured specific illnesses or geographic regions. This study aimed to leverage more sophisticated predictive analytics to generate informed estimations of the most consequential healthcare trends anticipated in the United States throughout the next decade. The analysis drew upon an extensive collection of over 50 million longitudinal electronic health records spanning a 5-year timeframe, comprehensive national public health statistics from the same period, and Medicare claims encompassing 72 million beneficiaries. Advanced machine learning techniques, including neural networks and Bayesian additive regression trees, were applied to identify nonlinear relationships and temporal patterns across 500 variables related to patient demographics, medical diagnoses, therapeutic procedures, reimbursement amounts, and clinical outcomes. Models were trained using data from 2010 to 2015 then utilized to project trends and forecasts for the years 2020 to 2025. Five-fold cross-validation testing was conducted to evaluate the accuracy and generalizability of the predictive models. The model projections indicate that chronic disease prevalence nationwide will rise by approximately 40% by the conclusion of 2025, primarily fueled by growing epidemics of obesity and an increasingly aging American population. Additionally, heart disease and stroke are estimated to maintain their positioning as leading causes of death, but cases of dementia and Alzheimer's disease specifically are projected to climb even more sharply at over a 50% increase. Healthcare costs on the whole are anticipated to rise on average between 4-6% annually, and costs may potentially double for elderly patients presenting with multiple morbidities. As outpatient and home-based care options expand further, inpatient hospital facility utilization may drop marginally between 10-15%. Improved management of chronic medical conditions within local community settings could reduce preventable hospital readmissions from 25-30%. Primary care, nursing, and mental healthcare roles are likely to face looming staffing shortages as well. Telehealth adoption is forecasted to surge by approximately 45% as virtual visit formats help address access obstacles. By 2025, biologics and gene therapies could account for over 25% of total drug spending pertaining to oncology and rare disease treatment. Larger Medicaid, Medicare, and ACA commercial coverage markets may motivate higher rates of health insurance enrollment over the next few years.

Effect of Health Insurance on Inpatient Health Service Utilization among Households Affected by Non-Communicable Diseases in Busia County, Kenya

Background: Non-Communicable Diseases (NCDs) are increasingly becoming important agents of illness and premature deaths globally, killing up to 41 million people annually, most of which occur in LMICs. In Kenya, major NCDs are cardio-vascular diseases, chronic respiratory diseases, cancers and diabetes. They account for 50% of all inpatient morbidities and 39% of all hospital mortalities. Patients afflicted with NCDs go through expensive treatment regiments, restraining them from utilizing available care. NCDs deepen inequality and are major drivers of unending poverty. World leaders resolved to deal with the devastating consequences of NCDs as a developmental challenge under SDGs. Kenya successively reformed its National Health Insurer to include a package that address the blight of NCDs and transform it into a primary enabler for achieving UHC. There is however, evidence suggesting that enrolment in health insurance (HI) does not necessarily guarantee inpatient utilization of NCDs care. This study examined the effect of HI on inpatient health service utilization among households with NCDs. Methods: A quasi experimental design was conducted among eligible households with HI cover and those without, involving a representative sample of 350 households. Interviewers conducted interviews at baseline and after one year among household heads. Results: Utilization of Inpatient NCDs care improved 1.256 (95% CI= 0.965-1.634), times more among insured households, (P=0.04). Conclusion: HI improves inpatient utilization of NCDs care. To accelerate progress towards UHC, national government should expand HI program to all counties, improve awareness of cover package entitlements and remove payment preconditions for inpatient procedures. County government to ensure health systems at primary level are well equipped to tackle inpatient NCDs care needs.

The role of economic factors in shaping and constituting the household burden of neglected tropical diseases of the skin: Qualitative findings from Ghana and Ethiopia

Tracers of health system equity, neglected tropical diseases (NTDs) disproportionately affect marginalized populations. NTDs that manifest on the skin – “skin NTDs” – are associated with scarring, disfigurement, physical disability, social exclusion, psychological distress, and economic hardship. To support development and evaluation of appropriate intervention strategies, we aimed to improve understanding of the role of economic factors in shaping and constituting the burden that skin NTDs place on households. We collected data in 2021 in two predominantly rural districts: Atwima Mponua in Ghana (where Buruli ulcer, yaws, and leprosy are endemic) and Kalu in Ethiopia (where cutaneous leishmaniasis and leprosy are endemic). We conducted interviews (n = 50) and focus group discussions (n = 14) that explored economic themes with affected individuals, caregivers, and community members and analysed the data thematically using a pre-defined framework. We found remarkable commonalities across countries and diseases. We developed a conceptual framework which illustrates skin NTDs' negative economic impact, including financial costs of care-seeking and reductions in work and schooling; categorises coping strategies by their degree of risk-pooling; and clarifies the mechanisms through which skin NTDs disproportionately affect the poorest. Despite health insurance schemes in both countries, wide-ranging, often harmful coping strategies were reported. Traditional healers were often described as more accessible, affordable and offering more flexible payment terms than formal health services, except for Ethiopia's well-established leprosy programme. Our findings are important in informing strategies to mitigate the skin NTD burden and identifying key drivers of household costs to measure in future evaluations. To reduce skin NTDs' impact on households' physical, mental, and economic wellbeing, intervention strategies should address economic constraints to prompt and effective care-seeking. While financial support and incentives for referrals and promotion of insurance enrolment may mitigate some constraints, structural interventions that decentralise care may offer more equitable and sustainable access to skin NTD care.

How should regulatory schemes be optimized to enhance deterrence against medical insurance fraud by enrollees? Evidence from a discrete choice experiment in China

Medical insurance fraud (MIF) poses a substantial global financial challenge, necessitating effective regulatory strategies, especially in China, where such measures are in a critical developmental phase. This study investigates the effectiveness of various regulatory components in deterring MIF among enrollees and explores preference heterogeneity among individuals with different characteristics, utilizing a discrete choice experiment survey. Grounded in deterrence theory, our conceptual framework incorporates five attributes: intensity of economic penalties, restrictions on medical insurance benefits, deterioration of social reputation, and certainty and celerity of penalties. Employing a D-efficiency design, 24 choice sets were generated and blocked into three versions. A multistage stratified sampling method was adopted to collect data from the basic medical insurance enrollees in Shanghai. The survey was conducted from September to October 2022. The sample representativeness was further improved via the entropy balancing approach. Data from the final sample of 1034 respondents were analyzed using mixed logit models (MIXLs), incorporating interactions with individual characteristics to assess preference heterogeneity. Results reveal that escalating economic penalties, suspending insurance benefits, listing individuals as unfaithful parties, ensuring penalty certainty, and expediting enforcement significantly enhance the deterrent effect. We observed preference heterogeneity across different demographics, including age, gender, education, health status, and employment status. The study underscores the pivotal role of economic penalties in deterring MIF, while also acknowledging the significance of non-economic measures such as enforcement efficiency and social sanctions. These findings offer valuable insights for policymakers to tailor and strengthen regulatory schemes against MIF, contributing to the advancement of more effective and precise healthcare policies.

Profiles of quality of outpatient care among individuals with mental disorders based on survey and administrative data.

Though it is crucial to contribute to patient recovery through access, diversity, continuity and regularity of outpatient care, still today most of these are deemed nonoptimal. Identifying patient profiles based on outpatient service use and quality of care indicators might help formulate more personalized interventions and reduce adverse outcomes. This study aimed to identify profiles of individuals with mental disorders (MDs) patterned after their outpatient care use and quality of care received, and to link those profiles to individual characteristics and subsequent outcomes. A cohort of 5669 individuals with MDs was considered based on data from the 2013-2014 and 2015-2016 Canadian Community Health Survey, which were linked to administrative data from the Quebec health insurance registry. Latent class analysis generated profiles based on service use over the 12 months preceding each respondent's interview, and comparative analyses were used to associate profiles with sociodemographic and clinical characteristics, and health outcomes over the three following months. Four profiles were identified. Profile 1 (P-1) was labelled 'Low service use'; P-2 'Moderate general practitioner (GP) care and continuity and regularity of care'; P-3 'High GP care, continuity and regularity of care, and low psychiatrist care'; and P-4 'High psychiatrist care and regularity of care, and low GP care'. Profiles 3 and 4 (~50% of the cohort) were provided with better care, but showed worse outcomes, mainly acute care use due to more complex conditions and unmet needs. Profiles 1 and 2 had better outcomes as they showed fewer risk factors such as being younger and having better social conditions. Intensity, diversity and regularity of care were higher in profiles with more complex MDs, chronic physical illnesses, and worse perceived health conditions. Adapting specific interventions for each profile, such as assertive community treatment or intensive case management for Profile 4, is recommended.

Effectiveness of OHSAS 18001 in reducing accidents at work. A follow-up study of 13,102 workplaces

IntroductionMany organizations worldwide have adopted certified occupational health and safety management systems (COHSMSs), such as OHSAS 18001. The effectiveness of COHSMSs in improving health and safety at work has become an important question for authorities, companies, and other stakeholders. This study aims to examine whether the adoption of COHSMSs leads to reduced risk of severe accidents at work. MethodWe used a register-based longitudinal design, to compare the risk of severe accidents among adopters to non-adopters of COHSMS in the period 2010 – 2018. We linked a national register of COHSMS adopters with individual-level information on reportable accidents in the Labour Market Insurance (LMI) register to compare the risk of severe accidents at work among 805 adopters of COHSMS with a matched control group of 12,297 non-adopters of COHSMS. Multivariable Poisson regression models were used to calculate rate ratios (RR) with 95% confidence intervals (CI). ResultsThe risk of severe accidents at work was 14% lower among adopters of COHSMS compared to non-adopters already two years before the date of certification (RR 0.86, 95% CI 0.76–0.98), but no further decrease in the rate ratio could be established at three-year follow-up (RR 0.85, 95% CI 0.75–0.97). In addition, we found no decrease in the rate ratio for all reportable accidents at work at three-year follow-up. ConclusionWorkplaces with a lower risk of accidents are more likely to adopt COHSMS, indicating either a self-selection effect or that adopting workplaces have improved safety during the pre-certification phase for obtaining a certificate. Adopters of COHSMS did not reduce reportable severe work accidents further at three-year follow-up after the date of certification. This study did not find support for an effect of COHSMS on reportable severe accidents at work and nor all reportable accidents at work.