Analyzing health outcomes measured as bounded counts

This paper assesses analytical strategies that respect the bounded-count nature of health outcomes encountered often in empirical applications. Absent in the literature is a comprehensive discussion and critique of strategies for analyzing and understanding such data. The paper's goal is to provide an in-depth consideration of prominent issues arising in and strategies for undertaking such analyses, emphasizing the merits and limitations of various analytical tools empirical researchers may contemplate. Three main topics are covered. First, bounded-count health outcomes' measurement properties are reviewed and their implications assessed. Second, issues arising when bounded-count outcomes are the objects of concern in evaluations are described. Third, the (conditional) probability and moment structures of bounded-count outcomes are derived and corresponding specification and estimation strategies presented with particular attention to partial effects. Many questions may be asked of such data in health research and a researcher's choice of analytical method is often consequential.

Using measures of race to make clinical predictions: Decision making, patient health, and fairness

The use of race measures in clinical prediction models is contentious. We seek to inform the discourse by evaluating the inclusion of race in probabilistic predictions of illness that support clinical decision making. Adopting a static utilitarian framework to formalize social welfare, we show that patients of all races benefit when clinical decisions are jointly guided by patient race and other observable covariates. Similar conclusions emerge when the model is extended to a two-period setting where prevention activities target systemic drivers of disease. We also discuss non-utilitarian concepts that have been proposed to guide allocation of health care resources.

The Relative Importance of Hospital Discharge and Patient Composition in Changing Post-Acute Care Utilization and Outcomes Among Medicare Beneficiaries

Background

The COVID-19 pandemic changed care delivery. But the mechanisms of changes were less understood.

Objectives

Examine the extent to which the volume and pattern of hospital discharge and patient composition contributed to the changes in post-acute care (PAC) utilization and outcomes during the pandemic.

Research design

Retrospective cohort study. Medicare claims data on hospital discharges in a large healthcare system from March 2018 to December 2020.

Subjects

Medicare fee-for-service beneficiaries, 65 years or older, hospitalized for non-COVID diagnoses.

Measures

Hospital discharges to Home Health Agencies (HHA), Skilled Nursing Facilities (SNF), and Inpatient Rehabilitation Facilities (IRF) versus home. Thirty- and ninety-day mortality and readmission rates. Outcomes were compared before and during the pandemic with and without adjustment for patient characteristics and/or interactions with the pandemic onset.

Results

During the pandemic, hospital discharges declined by 27%. Patients were more likely to be discharged to HHA (+4.6%, 95% CI [3.2%, 6.0%]) and less likely to be discharged to either SNF (-3.9%, CI [-5.2%, -2.7%]) or to home (-2.8% CI [-4.4%, -1.3%]). Thirty- and ninety-day mortality rates were significantly higher by 2% to 3% points post-pandemic. Readmission were not significantly different. Up to 15% of the changes in discharge patterns and 5% in mortality rates were attributable to patient characteristics.

Conclusions

Shift in discharge locations were the main driver of changes in PAC utilization during the pandemic. Changes in patient characteristics explained only a small portion of changes in discharge patterns and were mainly channeled through general impacts rather than differentiated responses to the pandemic.

Embracing Uncertainty: The Value of Partial Identification in Public Health and Clinical Research

INTRODUCTION

This paper describes the methodology of partial identification and its applicability to empirical research in preventive medicine and public health.

METHODS

The authors summarize findings from the methodologic literature on partial identification. The analysis was conducted in 2020-2021.

RESULTS

The applicability of partial identification methods is demonstrated using 3 empirical examples drawn from published literature.

CONCLUSIONS

Partial identification methods are likely to be of considerable interest to clinicians and others engaged in preventive medicine and public health research.

Discovering treatment effectiveness via median treatment effects-Applications to COVID-19 clinical trials

Comparing median outcomes to gauge treatment effectiveness is widespread practice in clinical and other investigations. While common, such difference-in-median characterizations of effectiveness are but one way to summarize how outcome distributions compare. This paper explores properties of median treatment effects (TEs) as indicators of treatment effectiveness. The paper's main focus is on decisionmaking based on median TEs and it proceeds by considering two paths a decisionmaker might follow. Along one, decisions are based on point-identified differences in medians alongside partially identified median differences; along the other decisions are based on point-identified differences in medians in conjunction with other point-identified parameters. On both paths familiar difference-in-median measures play some role yet in both the traditional standards are augmented with information that will often be relevant in assessing treatments' effectiveness. Implementing either approach is straightforward. In addition to its analytical results the paper considers several policy contexts in which such considerations arise. While the paper is framed by recently reported findings on treatments for COVID-19 and uses several such studies to explore empirically some properties of median-treatment-effect measures of effectiveness, its results should be broadly applicable.

Likelihood of hospital readmission in Medicare Advantage and Fee-For-Service within same hospital

OBJECTIVE

To assess the extent to which all-cause 30-day readmission rate varies by Medicare program within the same hospitals.

STUDY DESIGN

We used conditional logistic regression clustered by hospital and generalized estimating equations to compare the odds of unplanned all-cause 30-day readmission between Medicare Fee-for-Service (FFS) and Medicare Advantage (MA).

DATA COLLECTION

Wisconsin Health Information Organization collects claims data from various payers including private insurance, Medicare, and Medicaid, twice a year.

PRINCIPAL FINDINGS

For 62 of 66 hospitals, hospital-level readmission rates for MA were lower than those for Medicare FFS. The odds of 30-day readmission in MA were 0.92 times lower than Medicare FFS within the same hospital (odds ratio, 0.93; 95 percent confidence interval, 0.89-0.98). The adjusted overall readmission rates of Medicare FFS and MA were 14.9 percent and 11.9 percent, respectively.

CONCLUSION

These findings provide additional evidence of potential variations in readmission risk by payer and support the need for improved monitoring systems in hospitals that incorporate payer-specific data. Further research is needed to delineate specific care delivery factors that contribute to differential readmission risk by payer source.

Individual results may vary: Inequality-probability bounds for some health-outcome treatment effects

While many results from the treatment-effect and related literatures are familiar and have been applied productively in health economics evaluations, other potentially useful results from those literatures have had little influence on health economics practice. With the intent of demonstrating the value and use of some of these results in health economics applications, this paper focuses on one particular class of parameters that describe probabilities that one outcome is larger or smaller than other outcomes ("inequality probabilities"). While the properties of such parameters have been exposited in the technical literature, they have scarcely been considered in informing practical questions in health evaluations. This paper shows how such probabilities can be used informatively, and describes how they might be identified or bounded informatively given standard sampling assumptions and information only on marginal distributions of outcomes. The logic of these results and the empirical implementation thereof-sampling, estimation, and inference-are straightforward. Derivations are provided and several health-related applications are presented.

Considering mean and inequality health outcomes together: the population health performance index

Background

The purpose was to develop and test a population health measure that combines mean health outcomes and inequalities into a single GDP-like metric to help policymakers measure population health performance on both dimensions in one metric.

Methods

The Population Health Performance Index is a weighted average of a mean index and an inequality index according to the user’s inequality aversion. We deploy this methodology for two combinations of health outcome and disparity domain: infant mortality by race and unhealthy days by education.

Results

The PHPI is bounded between 0 and 1, and is comprised of a weighted average of two separate indices: a mean index and an inequality index, with 1 representing the ideal state of no ill health and no inequality and 0 representing the worst state in the U.S. PHPI values across states (neutral 50:50 weighting) vary between 0.60 (Massachusetts) to 0.17 (Delaware) for infant mortality by race and between 0.65 (North Dakota) to 0.00 (West Virginia) for unhealthy days by education. For some states, the choice of inequality aversion significantly impacts their PHPI value and state rank.

Conclusions

Mean and inequality health outcomes can be combined into a single Population Health Performance Index for use by public and private policy makers, like the GDP is used as a summary metric to measure economic output. The index can allow for varying degrees of inequality aversion, an individual’s or jurisdiction’s value choice that can substantially impact the value of this new summary population health metric.

Marginal Effects in Multivariate Probit Models

Estimation of marginal or partial effects of covariates x on various conditional parameters or functionals is often a main target of applied microeconometric analysis. In the specific context of probit models, estimation of partial effects involving outcome probabilities will often be of interest. Such estimation is straightforward in univariate models, and results covering the case of quadrant probability marginal effects in bivariate probit models for jointly distributed outcomes y have previously been described in the literature. This paper's goals are to extend Greene's results to encompass the general M≥2 multivariate probit (MVP) context for arbitrary orthant probabilities and to extended these results to models that condition on subvectors of y and to multivariate ordered probit data structures. It is suggested that such partial effects are broadly useful in situations wherein multivariate outcomes are of concern.

Estimation of Multivariate Probit Models via Bivariate Probit

This paper suggests the utility of estimating multivariate probit (MVP) models using a chain of bivariate probit estimators. The proposed approach is based on Stata's biprobit and suest procedures and is driven by a Mata function. Two potential advantages over Stata's mvprobit procedure are suggested: significant reductions in computation time; and essentially unlimited dimensionality of the outcome set. The time savings arise because the proposed approach does not rely simulation methods; the dimension advantage arises because only pairs of outcomes are considered at each estimation stage. Importantly, the proposed approach provides a consistent estimator of all the MVP model's parameters under the same assumptions required for consistent estimation via mvprobit, and simulation exercises reported below suggest no loss of estimator precision relative to mvprobit.

The effectiveness-efficiency trade-off in health care: The case of hospitals in Lombardy, Italy

We study the presence and the magnitudes of trade-offs between health outcomes and hospitals' efficiency using a data set from Lombardy, Italy, for the period 2008-2011. Our goal is to analyze whether the pressures for cost containment may affect hospital performance in terms of population health status. Unlike previous work in this area, we analyze hospitals at the ward level so comparisons can be made across more homogeneous treatments. We focus on two different health outcomes: mortality and readmission rates. We find that there is a trade-off between mortality rates and efficiency, as more efficient hospitals have higher mortality rates. We also find, however, that more efficient hospitals have lower readmission rates. Moreover, we show that focusing the analysis at the ward level is essential, since there is evidence of higher mortality rates in general medicine and surgery, while in oncology mortality is lower in more efficient hospitals. Furthermore, we find that consideration of spatial processes is important since mortality rates are higher for hospitals subject to high degree of horizontal competition, but lower for those hospitals having strong competition but high efficiency. This implies that the interplay of efficient resource allocation and hospital competition is important for the sustainability and effectiveness of regional health care systems.

Development of a novel, objective measure of health care-related financial burden for U.S. families with children

OBJECTIVE

To develop and validate a theoretically based and empirically driven objective measure of financial burden for U.S. families with children.

DATA SOURCES

The measure was developed using 149,021 families with children from the National Health Interview Survey, and it was validated using 18,488 families with children from the Medical Expenditure Panel Survey.

STUDY DESIGN

We estimated the marginal probability of unmet health care need due to cost using a bivariate tensor product spline for family income and out-of-pocket health care costs (OOPC; e.g., deductibles, copayments), while adjusting for confounders. Recursive partitioning was performed on these probabilities, as a function of income and OOPC, to establish thresholds demarcating levels of predicted risk.

PRINCIPAL FINDINGS

We successfully generated a novel measure of financial burden with four categories that were associated with unmet need (vs. low burden: midlow OR: 1.93, 95 percent CI: 1.78-2.09; midhigh OR: 2.78, 95 percent CI: 2.49-3.10; high OR: 4.38, 95 percent CI: 3.99-4.80). The novel burden measure demonstrated significantly better model fit and less underestimation of financial burden compared to an existing measure (OOPC/income ≥ 10 percent).

CONCLUSION

The newly developed measure of financial burden establishes thresholds based on different combinations of family income and OOPC that can be applied in future studies of health care utilization and expenditures and in policy development and evaluation.

Sleep behavior and unemployment conditions

Recent research has reported that habitually short sleep duration is a risk factor for declining health, including increased risk of obesity, diabetes and coronary heart disease. In this study we investigate whether macroeconomic conditions are associated with variation in mean sleep time in the United States, and if so, whether the effect is procyclical or countercyclical. We merge state unemployment rates from 2003 through 2012 with the American Time Use Survey, a nationally representative sample of adults with 24h time diaries. We find that higher aggregate unemployment is associated with longer mean sleep duration, with each additional point of state unemployment associated with an additional average 0.83 min of sleep (p<0.001), after adjusting for a secular trend of increasing sleep over the time period. Despite a national poll in 2009 that found one-third of Americans reporting losing sleep over the economy, we do not find that higher state unemployment is associated with more sleeplessness. Instead, we find that higher state unemployment is associated with less frequent time use described as "sleeplessness" (marginal effect=0.05 at 4% unemployment and 0.034 at 14% unemployment, p<0.001), after controlling for a secular trend.

MULTIVARIATE FRACTIONAL REGRESSION ESTIMATION OF ECONOMETRIC SHARE MODELS

This paper describes and applies econometric strategies for estimating regression models of economic share data outcomes where the shares may take boundary values (zero and one) with nontrivial probability. The main focus of the paper is on the conditional mean structures of such data. The paper proposes an extension of the fractional regression methodology proposed by Papke and Wooldridge, 1996, 2008, in univariate cross-sectional and panel contexts. The paper discusses the stochastic aspects of share definition and measurement, and summarizes important features of the existing literature on econometric strategies for share model estimation. The paper then goes on to discuss the univariate fractional regression estimation strategies proposed by Papke and Wooldridge and to extend the fractional regression approach to estimation of and inference about regression models describing the multivariate share data. Some issues involving outcome aggregation/disaggregation are considered, as is a full likelihood estimation approach based on Dirichlet-multinomial models. The paper demonstrates the workings of these various empirical strategies by estimating models of financial asset portfolio shares using data from the 2001, 2004, and 2007 U.S. Surveys of Consumer Finances.

Cumulative social risk exposure, infant birth weight, and cognitive delay in infancy

OBJECTIVE

To determine the effect of exposure to multiple social risks on cognitive delay at 9 months of age; and whether obstetric factors mediate the relationship between cumulative social risk and cognitive delay.

METHODS

Data were from 8950 mother-child dyads participating in the first wave of the Early Childhood Longitudinal Study, Birth Cohort. Cognitive delay was defined as falling in the lowest 10% of mental scale scores from the Bayley Short Form-Research Edition. Five social risk factors were combined and categorized into a social risk index. Staged multivariable logistic regressions were used to investigate whether obstetric factors mediated the impact of social risk on the odds of cognitive delay.

RESULTS

Infants with cognitive delay were more likely to live with social risks than infants without cognitive delay. The percentage of infants with cognitive delay increased with the number of social risks. In adjusted analyses, exposure to multiple social risk factors was associated with higher odds of cognitive delay at 9 months of age (adjusted odds ratio 2.11; 95% confidence interval 1.18-3.78 for 4 or more risks vs no risks). Accounting for birth weight attenuated this relationship (P < .001).

CONCLUSIONS

This population-based study investigated the independent and cumulative effects of social risk factors on cognitive delay in infancy. Findings revealed a significant cumulative relationship between exposure to social risk and cognitive delay, which was partly mediated by birth weight. Programs that address the social context of US infants are needed to improve their developmental trajectories.

The association between motor vehicle injuries and health-related quality of life: a longitudinal study of a population-based sample in the United States

PURPOSE

As many as 3 million US residents are injured in traffic-related incidents every year leaving many victims with disabling conditions. To date, limited numbers of studies have examined the effects of traffic-related injuries on self-reported health. This study aims to examine the association between health-related quality of life (HRQOL) and traffic-related injuries longitudinally in a nationally representative sample of US adult population.

METHODS/APPROACH

This is a longitudinal study of adult participants (age ≥18) from seven panels (2000-2007) of the Medical Expenditure Panel Survey. The dependent variables included the physical and mental components of the SF-12, a measure of self-reported health. The outcome was assessed twice during the follow-up period: round 2 (~4-5 months into the study) and round 4 (~18 months into the study) for 62,298 individuals. Two methods estimate the association between traffic-related injuries and HRQOL: a within person change using paired tests and a between person change using multivariable regression adjusting for age, sex, income and educational level.

RESULTS

Nine hundred and ninety-three participants reported traffic-related injuries during the follow-up period. Compared to their pre-crash HRQOL, these participants lost 2.7 of the physical component score while their mental component did not change. Adjusted results showed significant deficits in the physical component (-2.84, p value = <.001) but not the mental component (-0.07, p value = .83) of HRQOL after controlling for potential confounders.

CONCLUSION

Traffic injuries were significantly associated with the physical component of HRQOL. These findings highlight the individual and societal burden associated with motor vehicle crash-related disability in the United States.

Understanding socioeconomic and racial differences in adult lung function

RATIONALE

The contribution of socioeconomic factors to racial differences in the distribution of lung function is not well understood.

OBJECTIVES

We investigated the contribution of socioeconomic factors to racial differences in FEV₁ using statistical tools that allow for examination across the population distribution of FEV₁.

METHODS

We compared FEV₁ for white and African-American participants (aged 20-80 yr) in NHANES III with greater than or equal to two acceptable maneuvers to a restricted sample following the routine exclusion criteria used to derive population reference equations. Ordinary least squares and quantile regression analyses using spirometric, anthropometric, and socioeconomic data (high school completion) were performed separately by sex for both data sets.

MEASUREMENTS AND MAIN RESULTS

In the entire sample with acceptable spirometry (n ¼ 9,658), high school completion was associated with a mean 69.13-ml increase in FEV₁ for males (P , 0.05) and a mean 50.75-ml increase in FEV₁ for females (P , 0.01). In quantile regression analysis, we observed a significant racial difference in the association of high school completion with FEV₁ among both sexes that varied across the distribution; college completion was associated with an additional increase in FEV₁ for white males (70.36-250.76 ml) and white females (57.87-317.77 ml). Routine exclusion criteria differentially excluded individuals by age, race, and education. In the restricted sample (n ¼ 2,638), the association with high school completion was not significant.

CONCLUSIONS

High school completion is associated with racially patterned improvements in the FEV₁ of adults in the general population. The application of routine exclusion criteria leads to underestimates of the role of high school completion on FEV₁.

For-profit hospital status and rehospitalizations at different hospitals: an analysis of Medicare data

BACKGROUND

About one quarter of rehospitalized Medicare patients are admitted to hospitals different from their original hospital. The extent to which this practice is related to for-profit hospital status and affects payments and mortality is unknown.

OBJECTIVE

To describe and examine predictors of and payments for rehospitalization at a different hospital among Medicare patients rehospitalized within 30 days at for-profit and nonprofit or public hospitals.

DESIGN

Cohort study of patients discharged and rehospitalized from January 2005 to November 2006.

SETTING

Medicare fee-for-service hospitals throughout the United States.

PARTICIPANTS

A 5% random national sample of Medicare patients with acute care rehospitalizations within 30 days of discharge (n = 74,564).

MEASUREMENTS

30-day rehospitalizations at different hospitals and total payments or mortality over the subsequent 30 days. Multivariate logistic and quantile regression models included index hospital for-profit status, discharge counts, geographic region, rural-urban commuting area, and teaching status; patient sociodemographic characteristics, disability status, and comorbid conditions; and a measure of risk adjustment.

RESULTS

16 622 patients (22%) in the sample were rehospitalized at a different hospital. Factors associated with increased risk for rehospitalization at a different hospital included index hospitalization at a for-profit, major medical school-affiliated, or low-volume hospital and having a Medicare-defined disability. Compared with patients rehospitalized at the same hospital, patients rehospitalized at different hospitals had higher adjusted 30-day total payments (median additional cost, $1308 per patient; P < 0.001) but no statistically significant differences in 30-day mortality, regardless of index hospital for-profit status.

LIMITATION

The database lacked detailed clinical information about patients and did not include information about specific provider practice motivations or the role of patient choice in hospitalization venues.

CONCLUSION

Rehospitalizations at different hospitals are common among Medicare patients, are more likely among those initially hospitalized at a for-profit hospital, and are related to increased overall payments without improved mortality.

PRIMARY FUNDING SOURCE

University of Wisconsin Hartford Center of Excellence in Geriatrics, National Institutes of Health.

For-profit hospital status and rehospitalizations at different hospitals: an analysis of Medicare data

BACKGROUND

About one quarter of rehospitalized Medicare patients are admitted to hospitals different from their original hospital. The extent to which this practice is related to for-profit hospital status and affects payments and mortality is unknown.

OBJECTIVE

To describe and examine predictors of and payments for rehospitalization at a different hospital among Medicare patients rehospitalized within 30 days at for-profit and nonprofit or public hospitals.

DESIGN

Cohort study of patients discharged and rehospitalized from January 2005 to November 2006.

SETTING

Medicare fee-for-service hospitals throughout the United States.

PARTICIPANTS

A 5% random national sample of Medicare patients with acute care rehospitalizations within 30 days of discharge (n = 74,564).

MEASUREMENTS

30-day rehospitalizations at different hospitals and total payments or mortality over the subsequent 30 days. Multivariate logistic and quantile regression models included index hospital for-profit status, discharge counts, geographic region, rural-urban commuting area, and teaching status; patient sociodemographic characteristics, disability status, and comorbid conditions; and a measure of risk adjustment.

RESULTS

16 622 patients (22%) in the sample were rehospitalized at a different hospital. Factors associated with increased risk for rehospitalization at a different hospital included index hospitalization at a for-profit, major medical school-affiliated, or low-volume hospital and having a Medicare-defined disability. Compared with patients rehospitalized at the same hospital, patients rehospitalized at different hospitals had higher adjusted 30-day total payments (median additional cost, $1308 per patient; P < 0.001) but no statistically significant differences in 30-day mortality, regardless of index hospital for-profit status.

LIMITATION

The database lacked detailed clinical information about patients and did not include information about specific provider practice motivations or the role of patient choice in hospitalization venues.

CONCLUSION

Rehospitalizations at different hospitals are common among Medicare patients, are more likely among those initially hospitalized at a for-profit hospital, and are related to increased overall payments without improved mortality.

PRIMARY FUNDING SOURCE

University of Wisconsin Hartford Center of Excellence in Geriatrics, National Institutes of Health.

Understanding the production of population health and the role of paying for population health

This article considers 2 related themes that address population health outcomes and the contributions to those outcomes by time, place, individual behaviors and choices, and activities of various social sectors. First, what does it mean to "produce" population health, and how can the production of health be understood empirically? Second, through what processes can incentives be modified to improve population health? Among the issues that arise are understanding the mechanisms through which paying for population health works and how the health-producing incentives materialize in various sectors, especially those whose primary functions are not generally viewed as fostering better population health.

Hospital costs for treatment of acute heart failure: economic analysis of the REVIVE II study

BACKGROUND

Acute heart failure (AHF) is the leading cause of hospital admission among older Americans. The Randomized EValuation of Intravenous Levosimendan Efficacy (REVIVE II) trial compared patients randomly assigned to a single infusion of levosimendan (levo) or placebo (SOC), each in addition to local standard treatments for AHF. We report an economic analysis of REVIVE II from the hospital perspective.

METHODS

REVIVE II enrolled patients (N = 600) hospitalized for treatment of acute decompensated heart failure (ADHF) who remained dyspneic at rest despite treatment with intravenous diuretics. Case report forms documented index hospital treatment (drug administration, procedures, days of treatment by care unit), as well as subsequent hospital and emergency department admissions during follow-up ending 90 days from date of randomization. These data were used to impute cost of admission based on an econometric cost function derived from >100,000 ADHF hospital billing records selected per REVIVE II inclusion criteria.

RESULTS

Index admission mean length of stay (LOS) was shorter for the levo group compared with standard of care (SOC) (7.03 vs 8.96 days, P = 0.008) although intensive care unit (ICU)/cardiac care unit (CCU) days were similar (levo 2.88, SOC 3.22, P = 0.63). Excluding cost for levo, predicted mean (median) cost for the index admission was levo US $13,590 (9,458), SOC $19,021 (10,692) with a difference of $5,431 (1,234) favoring levo (P = 0.04). During follow-up through end of study day 90, no significant differences were observed in numbers of hospital admissions (P = 0.67), inpatient days (P = 0.81) or emergency department visits (P = 0.41). Cost-effectiveness was performed with a REVIVE-II sub-set conforming to current labeling, which excluded patients with low baseline blood pressure. Assuming an average price for levo in countries where currently approved, there was better than 50% likelihood that levo was both cost-saving and improved survival. Likelihood that levo would be cost-effective for willingness-to-pay below $50,000 per year of life gained was about 65%.

CONCLUSIONS

In the REVIVE II trial, patients treated with levo had shorter LOS and lower cost for the initial hospital admission relative to patients treated with SOC. Based on sub-group analysis of patients administered per the current label, levo appears cost-effective relative to SOC.

Surgical work output: is there room for increase? An analysis of surgical work effort from 1999 to 2003

OBJECTIVE

To analyze physician work production over a 5-year period to discover trends in productivity.

SUMMARY BACKGROUND DATA

Surgical workforce calculations over the past 25 years have projected major oversupply as well as looming shortages. Recent studies indicate that demand for surgical services will increase over the next two decades as the population ages and develops age related chronic diseases. This study examines actual physician productivity to determine whether there is capacity for increased work output in response to projected increases in demand.

METHODS

Physician productivity data as measured by relative value units were obtained from the Medical Group Management Association Physician Compensation Reports for a 5-year period. Surgeons were compared with nonsurgeons and across subspecialties.

RESULTS

Surgeon and nonsurgeon productivity in terms of relative value units remained relatively stable over the study period; surgical:nonsurgical productivity per provider was 1.30-1.46:1.

CONCLUSIONS

Surgeons produce a significant amount of the total work in multi-specialty medical groups. These results may indicate that the surgical and general surgical workforce has reached a plateau with respect to clinical productivity. Predicted increases in demand for procedure-based work to care for the aging population are likely to be difficult to meet with the available workforce.

Willingness to pay for reducing fatal risk by improving air quality: a contingent valuation study in Chongqing, China

In China, 76% of all energy comes from coal consumption, which is the major cause of air pollution. One of the major barriers to developing sound policies for controlling air pollution is the lack of information related to the value of the health consequences of air pollution. We conducted a willingness-to-pay (WTP) study using contingent valuation (CV) methods in Chongqing, China to estimate the economic value of saving one statistical life through improving air quality. A sample of 500residents was chosen based on multistage sampling methods. A face-to-face household interview was conducted using a series of hypothetical, open-ended scenarios followed by bidding game questions designed to elicit the respondents' WTP for air pollution reduction. The Two-Part Model was used for estimations. The results show that 96% of respondents were able to express their WTP. Their mean annual income is $490. Their WTP to save one statistical life is $34,458. Marginal increases for saving one statistical life is $240 with 1year age increase, $14,434 with 100yuan monthly income increase, and $1590 with 1year education increase. Unlike developed country, clean air may still be considered as a "luxury" good in China based on the estimation of income elasticity.

Generalized modeling approaches to risk adjustment of skewed outcomes data

There are two broad classes of models used to address the econometric problems caused by skewness in data commonly encountered in health care applications: (1) transformation to deal with skewness (e.g., ordinary least square (OLS) on ln(y)); and (2) alternative weighting approaches based on exponential conditional models (ECM) and generalized linear model (GLM) approaches. In this paper, we encompass these two classes of models using the three parameter generalized Gamma (GGM) distribution, which includes several of the standard alternatives as special cases-OLS with a normal error, OLS for the log-normal, the standard Gamma and exponential with a log link, and the Weibull. Using simulation methods, we find the tests of identifying distributions to be robust. The GGM also provides a potentially more robust alternative estimator to the standard alternatives. An example using inpatient expenditures is also analyzed.

Variation in Chinese population health related quality of life: Results from a EuroQol study in Beijing, China

The purpose of this study is to measure Chinese population health related quality of life (HRQoL) using European quality of life (EQ-5D) instrument, to examine the validity of EQ-5D in measuring Chinese population HRQoL, to explore the relationships between EQ-5D and other health determinants, and to display the similarities and differences of HRQoL between the Chinese population and the populations of other countries. The data used in this study includes 2994 respondents whose age are 12 years and older, which is from the 2000 Beijing Household Health Survey. Univariate and bivariate analyses have been used to examine the level of HRQoL and the relationships between HRQoL and other variables. Multi-variate analyses have been used to explore the relationships between the EQ-5D Visual Analogue Scale (VAS) and the EQ-5D five dimension indicators. There are four principal findings from this study. First, the EQ-5D instrument is a valid measure for Chinese HRQoL, but with a significant ceiling effect. Second, Pain/ Discomfort and Anxiety/Depression are the major Chinese HRQoL problems and the extents of these problems differ in subgroup populations. Third, typically mean scores are lower for older age group; this is observed at lower ages in the Chinese population than in populations from developed countries. Fourth, Chinese HRQoL has strong association relationship with population socio-economic status (SES), which might imply that issues brought on by the rapid economic transition have both positive and negative impacts on Chinese HRQoL.

Comparing alternative models: log vs Cox proportional hazard?

Health economists often use log models (based on OLS or generalized linear models) to deal with skewed outcomes such as those found in health expenditures and inpatient length of stay. Some recent studies have employed Cox proportional hazard regression as a less parametric alternative to OLS and GLM models, even when there was no need to correct for censoring. This study examines how well the alternative estimators behave econometrically in terms of bias when the data are skewed to the right. Specifically we provide evidence on the performance of the Cox model under a variety of data generating mechanisms and compare it to the estimators studied recently in Manning and Mullahy (2001). No single alternative is best under all of the conditions examined here. However, the gamma regression model with a log link seems to be more robust to alternative data generating mechanisms than either OLS on ln(y) or Cox proportional hazards regression. We find that the proportional hazard assumption is an essential requirement to obtain consistent estimate of the E(y|x) using the Cox model.

Services integration and cost-effectiveness

Alcohol treatment services are increasingly combined with other health and social services to address the needs of multiple-problem clients. Hence, it has been of growing policy interest to find the most effective and the most cost-effective ways of linking these services. This symposium presents some recent studies in this area. The small but growing body of studies in this area has great potential to inform public policy debates.

Factors influencing decisions regarding influenza vaccination and treatment: a survey of healthcare workers

Surveys conducted in our healthcare facility evaluated factors associated with acceptance of influenza vaccination and opinions regarding influenza prevention and treatment and willingness to pay. Avoiding lost work and low risk were primary reasons for vaccine recipients and non-recipients, respectively. One-third of vaccine recipients would refuse vaccination if asked to pay at least $10.

Live long, live well: quantifying the health of heterogeneous populations

Various health, quality, utility and disability adjusted life years or life expectancy (HALY, QALY, DALY; HALE, QALE, DALE) measures have become gold standards for defining outcomes in technology evaluation, population health monitoring, and other evaluative efforts. As such, the analytical framework within which these measures are used for descriptive and evaluative purposes should be theoretically consistent and statistically rigorous. For instance, widely accepted definitions of cost-effectiveness ratios and other technology evaluation criteria that are based on expectations of the respective cost and outcome measures must, as such, be defined in terms of expected HALYs or QALYs. Similarly, measures like HALEs or QALEs used for population health monitoring are typically concerned with population expectations of such measures (or their corresponding totals). This paper demonstrates that estimation of such expectations necessitates consideration of the population variation in, and covariation between, quality and longevity. From the perspective of several different environments characterizing such heterogeneity, quantification or estimation of measures like QALYs is reconsidered. An empirical example of the central issues is provided by means of an analysis of the years of healthy life (YHL) measure drawn from the US National Health Interview Survey.

Estimating log models: to transform or not to transform?

Health economists often use log models to deal with skewed outcomes, such as health utilization or health expenditures. The literature provides a number of alternative estimation approaches for log models, including ordinary least-squares on ln(y) and generalized linear models. This study examines how well the alternative estimators behave econometrically in terms of bias and precision when the data are skewed or have other common data problems (heteroscedasticity, heavy tails, etc.). No single alternative is best under all conditions examined. The paper provides a straightforward algorithm for choosing among the alternative estimators. Even if the estimators considered are consistent, there can be major losses in precision from selecting a less appropriate estimator.

It'll only hurt a second? Microeconomic determinants of who gets flu shots

Appreciating how the propensity to be immunized against the flu depends on individual characteristics and environments is essential for policies regarding influenza control to be formulated sensibly. To this point, the literature has offered little documentation on the determinants of influenza immunization. Beyond epidemiology, there are important economic issues that must be addressed to understand this form of preventive care. One concerns the relationship between labour supply and immunization propensity: While it is relatively costly (in terms of time costs) for workers to obtain immunizations, workers also have relatively more to lose from being ill with the flu. Another concern not generally appreciated is the extent to which individuals' perceived risks of infection may affect their propensities to be immunized. The paper also attempts to shed light on these issues. The analysis uses data from the 1991 National Health Interview Survey. Immunization propensity displays expected patterns by age and health status, while the results with respect to race, household structure, income and insurance are somewhat more surprising and/or novel. The estimated labour supply and perceived risk effects suggest that some aspects of the economics of preventive care generally not considered in empirical work are important and merit further consideration.

Drinking, problem drinking, and productivity

This chapter surveys and critiques the recent economic literature dealing with the relationships between labor market productivity and alcohol use and misuse. The focus here is twofold. First is to present and discuss the relevant conceptual issues that must be appreciated in assessing such relationships. Second is to summarize and assess the empirical findings that have been offered in the literature.

Much ado about two: reconsidering retransformation and the two-part model in health econometrics

In health economics applications involving outcomes (y) and covariates (x), it is often the case that the central inferential problems of interest involve E[y/x] and its associated partial effects or elasticities. Many such outcomes have two fundamental statistical properties: y > or = 0; and the outcome y = 0 is observed with sufficient frequency that the zeros cannot be ignored econometrically. This paper (1) describes circumstances where the standard two-part model with homoskedastic retransformation will fail to provide consistent inferences about important policy parameters; and (2) demonstrates some alternative approaches that are likely to prove helpful in applications.

Linking the health utilities index to National Medical Expenditure Survey data

Measures of health-related quality of life (HR-QOL) are becoming increasingly important in assessing the effects of chronic illness and healthcare interventions designed to treat them. Obtaining measures of HR-QOL for a nationally representative sample of individuals would enhance understanding of health status in the US, and promote further study of the economic causes and effects of health status. This study reports on our efforts to link a prominent HR-QOL scale, the Health Utilities Index Mark I (HUI), to the National Medical Expenditure Survey (NMES). Six distinct algorithms were constructed for linking the HUI to NMES. These alternative linkage algorithms yielded HUI measures that were highly intercorrelated (p = 93 to 99%). Multivariate regression analyses performed to predict variations in HR-QOL revealed that the HUI exhibited good predictive validity--the HUI demonstrated lower quality of life for a variety of chronic illnesses, and wealthier individuals and better educated individuals had a higher quality of life. In contrast to some previous HR-QOL research, the present analysis demonstrates that: (i) cancer is negatively and significantly related to quality of life; and (ii) smoking is negatively and significantly related to quality of life. Overall, the results suggest that the HUI linkages to NMES provide reliable and valid measures of quality of life. As such, items from the NMES can be grouped and linked in such a way as to obtain health state utility values. These values should be of use to those who wish to understand the global health of the US population for policy-making efforts.

Net health benefits: a new framework for the analysis of uncertainty in cost-effectiveness analysis

In recent years, considerable attention has been devoted to the development of statistical methods for the analysis of uncertainty in cost-effectiveness (CE) analysis, with a focus on situations in which the analyst has patient-level data on the costs and health effects of alternative interventions. To date, discussions have focused almost exclusively on addressing the practical challenges involved in estimating confidence intervals for CE ratios. However, the general approach of using confidence intervals to convey information about uncertainty around CE ratio estimates suffers from theoretical limitations that render it inappropriate in many situations. The authors present an alternative framework for analyzing uncertainty in the economic evaluation of health interventions (the "net health benefits" approach) that is more broadly applicable and that avoids some problems of prior methods. This approach offers several practical and theoretical advantages over the analysis of CE ratios, is straightforward to apply, and highlights some important principles in the theoretical underpinnings of CE analysis.

Women and work: tipplers and teetotalers

We seek to understand better the puzzling finding that, for women, alcoholism appears to be positively associated with the probability of being employed. Using the 1988 Alcohol Survey of the National Health Interview Survey, we find that this association holds for white women only. For white women, alcoholism and early drinking are associated with higher educational attainment, a smaller family size and a lower probability of being married. In turn, these human capital indicators are associated with greater labour supply, thus helping to explain the curious positive relationship between alcoholism and employment for women. An advance in this paper over our previous work is to examine life-time abstention from alcohol and its association with employment and human capital variables. We find that lifetime abstention is associated with lower employment, unemployment and education and greater propensity to be married for both white and non-white women.

Alcohol screening and brief intervention: where research meets practice

Numerous studies have consistently shown that quick screening instruments can identify people whose drinking is likely to present health risks and that low-cost, brief interventions are effective in reducing drinking among many such at-risk drinkers. This article describes the results of a one-year policy analysis that explored how alcohol screening and brief intervention (SBI) can be moved to widespread clinical applications in the United States. It introduces the concept of risky drinking and considers the potential of this new technology to reduce it. The research evidence behind this approach is reviewed, and a description of current programs in this and other countries beginning to apply SBI is provided. Economic issues attendant to applications are identified and discussed. The potential for applications in health care is analyzed and summary conclusions from market research are set forth. Recommendations are offered for immediate action.