Economic burden of bacteremic melioidosis in eastern and northeastern, Thailand.

Melioidosis is among the most common causes of septicemia in Thailand, but data on economic burden are limited. We describe the economic impact of bacteremic melioidosis hospitalizations in two Thailand provinces during 2006-2008. Costs are presented in US dollars ($1 = 30.49 Thai Baht). The average annual incidence of bacteremic melioidosis cases per 100,000 persons in Sa Kaeo and Nakhon Phanom was 4.6 and 14.4, respectively. The annual cost of bacteremic melioidosis hospitalizations from the societal perspective, including direct and indirect costs, was $152,159 in Sa Kaeo and $465,303 in Nakhon Phanom. The average cost per fatal case was $14,182 and $14,858 in Sa Kaeo and Nakhon Phanom, respectively. In addition to the high morbidity and mortality, the substantial economic burden of melioidosis further supports the need for investments to identify improved prevention and control strategies for melioidosis.

Infectious disease mortality rates, Thailand, 1958-2009.

To better define infectious diseases of concern in Thailand, trends in the mortality rate during 1958-2009 were analyzed by using data from public health statistics reports. From 1958 to the mid-1990s, the rate of infectious disease-associated deaths declined 5-fold (from 163.4 deaths/100,000 population in 1958 to 29.5/100,000 in 1997). This average annual reduction of 3.2 deaths/100,000 population was largely attributed to declines in deaths related to malaria, tuberculosis, pneumonia, and gastrointestinal infections. However, during 1998-2003, the mortality rate increased (peak of 70.0 deaths/100,000 population in 2003), coinciding with increases in mortality rate from AIDS, tuberculosis, and pneumonia. During 2004-2009, the rate declined to 41.0 deaths/100,000 population, coinciding with a decrease in AIDS-related deaths. The emergence of AIDS and the increase in tuberculosis- and pneumonia-related deaths in the late twentieth century emphasize the need to direct resources and efforts to the control of emerging and re-emerging infectious diseases.

Using health technology assessment for informing coverage decisions in Thailand.

This article aims to illustrate and critically analyze the results from the 1-year experience of using health technology assessment (HTA) in the development of the Thai Universal Coverage health benefit package. We review the relevant documents and give a descriptive analysis of outcomes resulting from the development process in 2009-2010. Out of 30 topics nominated by stakeholders for prioritization, 12 were selected for further assessment. A total of five new interventions were recommended for inclusion in the benefit package based on value for money, budget impact, feasibility and equity reasons. Different stakeholders have diverse interests and capabilities to participate in the process. In conclusion, HTA is helpful for informing coverage decisions for health benefit packages because it enhances the legitimacy of policy decisions by increasing the transparency, inclusiveness and accountability of the process. There is room for improvement of the current use of HTA, including providing technical support for patient representatives and civic groups, better communication between health professionals, and focusing more on health promotion and disease prevention.

Capacity of Thailand to contain an emerging influenza pandemic.

Southeast Asia will likely be the epicenter of the next influenza pandemic. To determine whether health system resources in Thailand are sufficient to contain an emerging pandemic, we mapped health system resources in 76 provinces. We used 3 prepandemic scenarios of clustered cases and determined resource needs, availability, and gaps. We extended this analysis to a scenario of a modest pandemic and assumed that the same standards of clinical care would be required. We found that gaps exist in many resource categories, even under scenarios in which few cases occur. Such gaps are likely to be profound if a severe pandemic occurs. These gaps exist in infrastructure, personnel and materials, and surveillance capacity. Policy makers must determine whether such resource gaps can realistically be closed, ideally before a pandemic occurs. Alternatively, explicit assumptions must be made regarding allocation of scarce resources, standards of care, and priority setting during a pandemic.

The cost of influenza in Thailand.

The cost of influenza in less wealthy tropical countries is needed to inform national vaccine policy decisions. Between September 2003 and August 2004, we prospectively identified hospitalized pneumonia cases and outpatients with laboratory confirmed influenza in a Thai province. Disease incidence, patient interviews, medical record reviews, and data from a national health survey were used to calculate direct and indirect costs which were extrapolated to the Thai population. Influenza was identified in 80 (11%) of 761 hospitalized pneumonia inpatients with projected annual incidence of 18-111/100,000 population. Influenza was confirmed in 23% of 1092 outpatients with an estimated annual incidence of 1420/100,000 population. Influenza was estimated to cause between US dollar 23.4 and US dollar 62.9 million in economic losses with lost productivity accounting for 56% of all costs. The burden of influenza in Thailand is greater than previously appreciated, particularly in young children and the elderly. The impact and cost-effectiveness of influenza vaccination for high-risk groups merits further investigation.

Capacity in Thai public hospitals and the production of care for poor and nonpoor patients.

OBJECTIVE: To assess the capacity of Thai public hospitals to proportionately expand services to both the poor and the nonpoor. This is accomplished by measuring the production of services provided to poor, relative to nonpoor, patients and the plant capacity of individual public hospitals to care for the patient load. STUDY SETTING: Thai public hospitals operating in 1999, following the economic crisis when public hospitals were required to treat all patients irrespective of ability to pay. STUDY DESIGN AND DATA COLLECTION: Input and output data for 68 hospitals were collected using databases and questionnaire surveys. A distinction was made between inpatient and outpatient services to both poor and nonpoor patients and the data were assessed statistically. DATA ANALYSIS: Congestion and capacity indices to measure poor/nonpoor service trade-offs and capacity utilization were estimated. The analysis was undertaken by data envelopment analysis (DEA), a nonparametric linear programming approach used to derive efficiency and productivity estimates. Principal Findings. Increases in the amount of services provided to poor patients did not reduce the amount of services to nonpoor patients. Overall, hospitals are producing services relatively close to their capacity given fixed inputs. Possible increases in capacity utilization amounted to 5 percent of capacity. CONCLUSIONS: Results suggest that some increased public hospital care can be accomplished by reallocation of resources to less highly utilized hospitals, given the budgetary constraints. However, further expansion and increase in access to health services will require plant investments. The study illustrates how DEA methodologies can be used in planning health services in data constrained settings.