Person:

Fan, Victoria

Background: The Haiti earthquake in 2010 resulted in 1.5 million internally displaced people (IDP), yet little is known about the impact of displacement on health. In this study, we estimate the impact of displacement on infant and child mortality and key health-behavior mechanisms. Methods: We employ a difference-in-differences (DID) design with coarsened exact matching (CEM) to ensure comparability among groups with different displacement status using the 2012 Haiti Demographic and Health Survey (DHS). The participants are 21,417 births reported by a nationally representative sample of 14,287 women aged 15–49. The main independent variables are household displacement status which includes households living in camps, IDP households (not in camps), and households not displaced. The main outcomes are infant and child mortality; health status (height-for-age, anemia); uptake of public health interventions (bed net use, spraying against mosquitoes, and vaccinations); and other conditions (hunger; cholera). Results: Births from the camp households have higher infant mortality (OR = 2.34, 95 % CI 1.15 to 4.75) and child mortality (OR = 2.34, 95 % CI 1.10 to 5.00) than those in non-camp IDP households following the earthquake. These odds are higher despite better access to food, water, bed net use, mosquito spraying, and vaccines among camp households. Conclusions: IDP populations are heterogeneous and households that are displaced outside of camps may be self-selected or self-insured. Meanwhile, even households not displaced by a disaster may face challenges in access to basic necessities and health services. Efforts are needed to identify vulnerable populations to provide targeted assistance in post-disaster relief.

Background: Despite the urgent need for evidence to guide the end-of-life (EOL) care for patients with chronic kidney disease (CKD), we have limited knowledge of the costs and intensity of EOL care in this population. The present study examined patterns and predictors for EOL care intensity among elderly patients with CKD. Methods: We conducted a retrospective nationwide cohort study utilizing the Taiwan National Health Insurance (NHI) Research Database. A total of 65,124 CKD patients aged ≥ 60 years, who died in hospitals or shortly after discharge between 2002 and 2012 were analyzed. The primary outcomes were inpatient expenses and use of surgical interventions in the last 30 days of life. Utilization of intensive care unit (ICU), mechanical ventilation, resuscitation, and dialysis was also examined in a sub-sample of 2072 patients with detailed prescription data. Multivariate log-linear and logistic regression analyses were performed to assess patient-, physician-, and facility-specific predictors and the potential impact of a 2009 payment policy to reimburse hospice care for non-cancer patients. Results: During the last 30 days of life, average inpatients costs for elderly CKD patients were approximately US$10,260, with 40.9% receiving surgical interventions, 40.2% experiencing ICU admission, 45.3% undergoing mechanical ventilation, 14.7% receiving resuscitation and 42.0% receiving dialysis. Significant variability was observed in the inpatient costs and use of intensive services. Costs were lower among individuals with the following characteristics: advanced age; high income; high Charlson Comorbidity Index scores; treatment by older physicians, nephrologists, and family medicine physicians; and treatment at local hospitals. Similar findings were obtained for the use of surgical interventions and other intensive services. A declining trend was detected in the costs of EOL care, use of surgical interventions and resuscitation between 2009 and 2012, which is consistent with the impact of a 2009 NHI payment policy to reimburse non-cancer hospice care. Conclusions: Overall EOL costs and rates of intensive service use among older patients with CKD were high, with significant variability across various patient and provider characteristics. Several opportunities exist for providers and policy makers to reduce costs and enhance the value of EOL care for this population.

Summary Background: There is limited empirical evidence about the efficacy of fiscal transfers for a specific purpose, including for health which represents an important source of funds for the delivery of public services especially in large populous countries such as India. Objective: To examine two distinct methodologies for allocating specific‐purpose centre‐to‐state transfers, one using an input‐based formula focused on equity and the other using an outcome‐based formula focused on performance. Materials and Methods We examine the Twelfth Finance Commission (12FC)'s use of Equalization Grants for Health (EGH) as an input‐based formula and the Thirteenth Finance Commission (13FC)'s use of Incentive Grants for Health (IGH) as an outcome‐based formula. We simulate and replicate the allocation of these two transfer methodologies and examine the consequences of these fiscal transfer mechanisms. Results: The EGH placed conditions for releasing funds, but states varied in their ability to meet those conditions, and hence their allocations varied, eg, Madhya Pradesh received 100% and Odisha 67% of its expected allocation. Due to the design of the IGH formula, IGH allocations were unequally distributed and highly concentrated in 4 states (Manipur, Sikkim, Tamil Nadu, Nagaland), which received over half the national IGH allocation. Discussion The EGH had limited impact in achieving equalization, whereas the IGH rewards were concentrated in states which were already doing better. Greater transparency and accountability of centre‐to‐state allocations and specifically their methodologies are needed to ensure that allocation objectives are aligned to performance.

To control ever-increasing costs, global budget payment has gained attention but has unclear impacts on health care systems. We propose the CAP framework that helps navigate 3 domains of difficult design choices in global budget payment: Constraints in resources (capitation vs facility-based budgeting; hard vs soft budget constraints), Agent-principal in resource allocation (individual vs group providers in resource allocation; single vs multiple pipes), and Price adjustment. We illustrate the framework with empirical examples and draw implications for policy makers.