Katharina Hauck

How dangerous is a day in hospital? A model of adverse events and length of stay for medical inpatients.

Background:Despite extensive research into adverse events, there is no quantitative estimate for the risk of experiencing adverse events per day spent in hospital. This is important information for hospital managers, because they may consider discharging patients earlier to alternative care providers if this is associated with lower risk, but other costs and benefits are similar. Methods:We model adverse events as a function of patient risk factors, hospital fixed effects, and length of stay. Potential endogeneity of length of stay is addressed with instrumental variable methods, using days and months of discharge as instruments. We use administrative hospital episode data for 206,489 medical inpatients in all public hospitals in the state of Victoria, Australia, for the year 2005/2006. Results:A hospital stay carries a 5.5% risk of an adverse drug reaction, 17.6% risk of infection, and 3.1% risk of ulcer for an average episode, and each additional night in hospital increases the risk by 0.5% for adverse drug reactions, 1.6% for infections, and 0.5% for ulcers. Length of stay is endogenous in models of adverse events, and risks would be underestimated if length of stay was treated as exogenous. Conclusions:The results of our research contribute to assessing the benefits and costs of hospital stays—and their alternatives—in a quantitative manner. Instead of discharging patients early to alternative care, it would be more desirable to address underlying causes of adverse events. However, this may prove costly, difficult, or impossible, at least in the short run. In such situations, our research supports hospital managers in making informed treatment and discharge decisions.

Priority setting in health a political economy perspective

Most countries face high demands on their health care systems and have limited resources with which to meet them. Priority setting seeks to address these problems by proposing rules to decide which groups of patients or disease areas should secure favoured access to limited health care resources. The economic approach towards priority setting, particularly in the form of cost-effectiveness analysis, is commonly advocated. However, despite many decades of refinement of the technical and methodological issues arising from the use of economic evaluation in priority setting, decision makers continue to diverge frequently from the principles of economic evaluation. Our approach in this paper is to highlight the potential contribution of models of political economy to understanding what constitutes rational behaviour when agents operate within political and institutional constraints. We argue that there may be potentially greater benefits to be gained from exploration and analysis of priority setting using models based on concepts such as median voter and competing interest groups, than from further efforts to refine the techniques of economic evaluation.

HPTN 071 (PopART): A Cluster-Randomized Trial of the Population Impact of an HIV Combination Prevention Intervention Including Universal Testing and Treatment: Mathematical Model

Background The HPTN 052 trial confirmed that antiretroviral therapy (ART) can nearly eliminate HIV transmission from successfully treated HIV-infected individuals within couples. Here, we present the mathematical modeling used to inform the design and monitoring of a new trial aiming to test whether widespread provision of ART is feasible and can substantially reduce population-level HIV incidence. Methods and Findings The HPTN 071 (PopART) trial is a three-arm cluster-randomized trial of 21 large population clusters in Zambia and South Africa, starting in 2013. A combination prevention package including home-based voluntary testing and counseling, and ART for HIV positive individuals, will be delivered in arms A and B, with ART offered universally in arm A and according to national guidelines in arm B. Arm C will be the control arm. The primary endpoint is the cumulative three-year HIV incidence. We developed a mathematical model of heterosexual HIV transmission, informed by recent data on HIV-1 natural history. We focused on realistically modeling the intervention package. Parameters were calibrated to data previously collected in these communities and national surveillance data. We predict that, if targets are reached, HIV incidence over three years will drop by >60% in arm A and >25% in arm B, relative to arm C. The considerable uncertainty in the predicted reduction in incidence justifies the need for a trial. The main drivers of this uncertainty are possible community-level behavioral changes associated with the intervention, uptake of testing and treatment, as well as ART retention and adherence. Conclusions The HPTN 071 (PopART) trial intervention could reduce HIV population-level incidence by >60% over three years. This intervention could serve as a paradigm for national or supra-national implementation. Our analysis highlights the role mathematical modeling can play in trial development and monitoring, and more widely in evaluating the impact of treatment as prevention.

THE EFFECTS OF TAXING SUGAR-SWEETENED BEVERAGES ACROSS DIFFERENT INCOME GROUPS

This paper investigates the impact of sugar-sweetened beverages (SSB) taxes on consumption, bodyweight and tax burden for low-income, middle-income and high-income groups using an Almost Ideal Demand System and 2011 Household level scanner data. A significant contribution of our paper is that we compare two types of SSB taxes recently advocated by policy makers: A 20% flat rate sales (valoric) tax and a 20 cent/L volumetric tax. Censored demand is accounted for using a two-step procedure. We find that the volumetric tax would result in a greater per capita weight loss than the valoric tax (0.41 kg vs. 0.29 kg). The difference between the change in weight is substantial for the target group of heavy purchasers of SSBs in low-income households, with a weight reduction of up to 3.20 kg for the volumetric and 2.06 kg for the valoric tax. The average yearly per capita tax burden on low-income households is

The Impact of Severe Obesity on Hospital Length of Stay

17.87 (0.21% of income) compared with

The influence of health care organisations on health system performance.

15.17 for high-income households (0.07% of income) for the valoric tax, and

Adverse event rates as measures of hospital performance

13.80 (0.15%) and

Employment, work hours and weight gain among middle-aged women.

10.10 (0.04%) for the volumetric tax. Thus, the tax burden is lower, and weight reduction is higher under a volumetric tax.

Evidence for scaling up HIV treatment in sub-Saharan Africa: A call for incorporating health system constraints

Background:The excess health care costs caused by obesity are a concern in many countries, yet little is known about the additional resources required to treat obese patients in hospitals. Objective:To estimate differences in hospital resource use, measured by length of stay, between severely obese and other patients, conditioning on a range of patient and hospital characteristics. Research Design:Administrative patient-level hospital data for 122 Australian public hospitals over the financial year 2005/06 (Victorian Admitted Episodes Data). Subjects:Episodes (435,147) for patients above 17 years of age and with a stay of one night or more. Measures:Quantile Regression analysis is used to generate 19 estimates of the difference between severely obese and other patients across the whole range of length of stay, from very short to very long staying patients. Separate estimates for 17 hospital specialties and for medically and surgically treated patients are generated. Results:There are significant differences in average length of stay for almost all specialties. For some, differences are less than 1 day, but for others, severely obese patients stay up to 4 days longer. For a number of specialties, obese patients have significantly shorter length of stay. Overall, medically managed obese patients stay longer, whereas surgically treated patients stay shorter than other patients. Differences tend to increase with length of stay. Conclusions:Differences in length of stay may arise because severely obese patients are medically more complex. The observed shorter stays for obese patients in some specialties may result from their observed greater likelihood of being transferred to another hospital.

Departures from Cost-Effectiveness Recommendations: The Impact of Health System Constraints on Priority Setting

Objectives: The governments of many countries are undertaking initiatives to assess the extent to which health care organisations fulfil important objectives of health care, such as health improvement, fair access and efficiency. However, the extent to which these health care organisations can influence these objectives is unclear. The purpose of this study is to examine the potential influence of English National Health Service territorial health authorities on 14 indicators of system performance. Methods: The study uses performance data relating to approximately 5000 small geographical areas with average populations of 10 000. Multi-level statistical models are used to attribute variation in the indicators to three hierarchical levels - small areas, district health authorities and regional health authorities - after controlling for socio-demographic characteristics. Variations in indicators attributable to district or regional level give an indication of the extent to which health authorities may influence performance. Results: After adjusting for socio-demographic characteristics, the proportion of variation in performance attributable to district health authorities varies from about 8% (for standardised mortality ratios) to about 76% (for waiting time for elective surgery). Variation at the regional level is smaller than at the district level. Conclusions: There appear to be very large variations between indicators in the extent to which health care organisations can influence health system performance. Choice of performance indicators and the managerial incentive regime based on the indicators should recognise this variability, as it is highly dysfunctional to hold managers accountable for measures of performance that are beyond their control.