Article

Methods for Analyzing Health Care Utilization and Costs

Boston University, Boston, Massachusetts, United States
Annual Review of Public Health (Impact Factor: 6.47). 02/1999; 20(1). DOI: 10.1146/annurev.publhealth.20.1.125
Source: OAI

ABSTRACT

Important questions about health care are often addressed by studying health care utilization. Utilization data have several characteristics that make them a challenge to analyze. In this paper we discuss sources of information, the statistical properties of utilization data, common analytic methods including the two-part model, and some newly available statistical methods including the generalized linear model. We also address issues of study design and new methods for dealing with censored data. Examples are presented.

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Available from: Paula Katherine Hagedorn Diehr
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    • "Costs are skewed right, with high costs driven largely by inpatient hospitalizations[5]. Hospitalizations are relatively rare and can be an important indicator of disease acuity; however, they may also occur as a result of non condition related events such as physical injuries, adding noise to the model[5]. Most first principle based approaches, typically adopted in healthcare research, are not well-tailored to handle such complex dependencies[6]. "
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    • "Costs are skewed right, with high costs driven largely by inpatient hospitalizations[9]. Hospitalizations are relatively rare and can be an important indicator of disease acuity; however, they may also occur as a result of non condition related events such as physical injuries, adding noise to the model[9]. Most first principle based approaches, typically adopted in healthcare research, are not well-tailored to handle such complex dependencies[10]. "
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    Full-text · Conference Paper · Oct 2015
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    • "consider the ICER as the additional cost of ICD for saving one year of life. Our approach utilizes the projected survival curve and monthly costs for survivors to obtain the projected overall mean costs. It has beenobserved that The health care costs tend to rise dramatically in the period prior to an individual's death (Scitovsky and Capron 1986; Diehretal. 1999). A common practice when people model the cost data is that the last month's costisd is carded (e.g., Liu et al. 2008), which affect the estimate of monthly cost. Our proposed method will take into consideration the death cost in our modeling for cost data. From the economic point of view, today's cost in dollars and health benefit in l"

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