A Comparison of Alternative Models for the Demand for Medical Care

Duan, Naihua; Manning, Willard G.; Morris, Carl N.; Newhouse, Joseph P.

doi:10.1080/07350015.1983.10509330

Cited by 614 publications

(501 citation statements)

References 14 publications

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“…Similar issues in the risk-adjustment literature were raised in relation to estimating costs in the RAND insurance experiment in the early 1980s [9,10], where log transformation was found to yield better compliance with modelling assumptions, but where prediction on the untransformed scale was the ultimate goal. This requirement led Duan to propose the 'smearing estimator' that could be used to correct for the bias that occurs if expectations on the transformed scale are back transformed [11].…”

Section: Introductionmentioning

confidence: 88%

Parametric modelling of cost data: some simulation evidence

et al. 2005

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SummaryRecently, commentators have suggested that the distributional form of cost data should be explicitly modelled to gain efficiency in estimating the population mean. We perform a series of simulation experiments to evaluate the usual sample mean and the mean estimator of a lognormal distribution, in the context of both theoretical distributions and three large empirical datasets. The sample mean is always unbiased, but is somewhat less efficient when the population distribution is truly lognormal. However the lognormal estimator can perform appallingly when the true distribution is not lognormal. In practical situations, where the true distribution is unknown, the sample mean generally remains the estimator of choice, especially when limited sample size prohibits detailed modelling of the cost data distribution. Copyright

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Section: Introductionmentioning

confidence: 88%

Parametric modelling of cost data: some simulation evidence

et al. 2005

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“…We estimated the incremental contribution of AORC to total expenditures by a 4-stage model, which has also been described by Duan et al (45). The first stage uses a logistic regression to predict the probability of any medical expenditures.…”

Section: Methodsmentioning

confidence: 99%

Medical care expenditures and earnings losses of persons with arthritis and other rheumatic conditions in the United States in 1997: Total and incremental estimates

Yelin¹,

Cisternas²,

Pasta³

et al. 2004

Arthritis & Rheumatism

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Objective. To provide estimates of the total medical care expenditures and earnings losses associated with arthritis and other rheumatic conditions (AORC), as well as the increment in such costs specifically attributable to these conditions, in the US in 1997.Methods. The estimates were derived from the 1997 Medical Expenditures Panel Survey (MEPS), a national probability sample of 14,147 households including 34,551 persons, of whom 4,776 self-reported arthritis. After weighting, those who self-reported AORC represent 38.4 million persons. We tabulated all medical care expenditures of the adult MEPS respondents, stratified by arthritis and comorbidity status, and then used regression techniques to estimate the increment in health care expenditures attributable to AORC, after taking comorbidity, demographic characteristics, and insurance status into account. Using the same methods, we also estimated the magnitude of the earnings losses sustained by persons of working ages (18-64 years) who had AORC.Results. Persons with AORC incurred mean total medical care expenditures of $4,865 (total $186.9 billion). The largest components of these expenditures were inpatient care (39%), ambulatory care (29%), and prescriptions (14%). The mean increment in medical care expenditures specifically attributable to AORC among those ages 18 years and older was $1,391 (total ϳ$51.1 billion). Persons with AORC ages 18-64 years earned $3,812 less on average than did other persons of these ages (total $82.4 billion). Of this average, $1,579 was attributable to the AORC (total $35.1 billion).Conclusion. In 1997, persons with AORC incurred direct and indirect costs of $269.3 billion, of which $86.2 billion was attributable to these conditions. Information about the economic impact of illness has become central to health policy debates, affecting the allocation of research funding among conditions and the choice of therapies for specific conditions. Because of the growing importance of cost of illness studies in health policy, the literature concerning the cost of all forms of musculoskeletal conditions for the US as a whole (1-8) and for other nations (9-13), as well as the cost of specific musculoskeletal conditions, including various forms of arthritis and other rheumatic conditions (AORC) (14-37), has been expanding rapidly.In general, the studies of the economic impact of all forms of musculoskeletal conditions have been derived from population-based surveys, but not directly observed individual-level medical care expenditures or employment status and earnings. In contrast, studies that have tracked the actual costs or expenditures for individuals have used clinical-based samples and are, thus, not representative of the general population. In the present study, we used the results of the Medical Expen-

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“…The two part model assumes that the zero values and the positive values are generated by different independent mechanisms. Duan et al [25] and Jones [26] provide more in-depth discussion of the merits of the two part model.…”

Section: Econometric Specificationmentioning

confidence: 99%

The Importance of Proximity to Death in Modelling Community Medication Expenditures for Older People: Evidence From New Zealand

Moore

Bennett

Normand

2014

Appl Health Econ Health Policy

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BackgroundConcerns about the long term sustainability of health care expenditures and in particular prescribing expenditures has become an important policy issue in most developed countries. Previous studies suggest that proximity to death (PTD) has a significant effect on total health care expenditures, with its exclusion leading to an overestimation of likely growth. There are limited studies of pharmaceutical expenditures taking PTD into account. ObjectiveThis paper presents an empirical analysis of public medication expenditure on older individuals in New Zealand (NZ). The aim of the study is to examine the individual effects of age and proximity to death (PTD) using individual level data. MethodsThis study uses individual level dispensing data from 2008/2009 covering the whole population of medication users age 70 years or more and resident in New Zealand. A case control methodology is used to examine individual cost and medication use for a 12 month period for decedents (cases) and survivors (controls). A random effects two part model, with a Probit and Generalized Linear Model (GLM) is used to explore the effect of age and proximity to death on expenditures. ResultsThe impact of proximity to death on prescription expenditure is not as dramatic as studies reporting on Acute and/or long term care. The 12 month decedent to survivor mean expenditure ratio was 1.95, 2 2.09 for males and 1.82 for females. The additional cost of dying in terms of prescription drugs decreases with age, with those who die at 90 years of age or older consuming fewer drugs on average and having a lower mean expenditure than those who died in their 70s and 80s. The following variables were found to have a decreasing effect on the mean monthly prescription expenditures, a reduction of 2.2% for each additional year of age, 4.2% being in the Mãori ethnic group and 7.8% for Pacific Islanders. Increases in monthly expenditure were associated with being a decedent 32.1%-62.6% (depending on month), being of Asian origin 16.2% or a male 12.6%. ConclusionsGiven the variance reported between survivors and decedents, to improve accuracy future projections should include PTD in their models. Policies targeted at reducing expenditures should not focus on age but on ensuring appropriate and cost effective prescribing especially towards the end of life. Key points for decision makers: Despite prescription medications being the most common medical intervention there is limited evidence on how proximity to death and ageing affect prescribing expenditures for older people. In terms of expenditure on prescription medications, proximity to death would appear to be a more important driver than ageing and should therefore be considered in any future expenditure projections.

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A Comparison of Alternative Models for the Demand for Medical Care

Cited by 614 publications

References 14 publications

Parametric modelling of cost data: some simulation evidence

Parametric modelling of cost data: some simulation evidence

Medical care expenditures and earnings losses of persons with arthritis and other rheumatic conditions in the United States in 1997: Total and incremental estimates

The Importance of Proximity to Death in Modelling Community Medication Expenditures for Older People: Evidence From New Zealand

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