Robert L. Houchens and Nancy Schoeps
This case study investigates the relative importance of several factors in predicting the length of time young patients with asthma stay in the hospital. With the present atmosphere of cutting health care costs it is important to look at providing adequate care while at the same time reducing costs and not keeping children in the hospital longer than necessary. By looking at a sample of patients with pediatric asthma, concomitant factors to the main reason for being admitted to the hospital may shed light on different lengths of stay.
In today's healthcare environment, health insurance companies are increasingly pressuring hospitals to provide high quality health services at the lowest possible cost. The vast majority of all healthcare costs are for hospitalization. During the past decade, inpatient costs of patients in hospitals have been reduced in two primary ways. First, the less severe cases are now treated in the doctor's office or in hospital emergency rooms rather than being admitted to the hospital. Second, for cases admitted to the hospital, the lengths of hospital stays have been considerably shortened.
It is believed that some insurers have been more successful than others at minimizing hospital lengths of stay
(LOS). To test this, a sample of hospital medical records was drawn for each of several illnesses from metropolitan hospitals operating in one state. The data for this case study consists of information abstracted from the medical records of asthma patients between the ages of 2 and 18 years old.
The sample of medical records was drawn in two stages. At the first stage, 29 metropolitan hospitals were sampled with probabilities proportional to an estimate of the number of asthma admissions it had during a single year. At the second stage, 393 asthma cases insured by Insurer A were randomly selected and 396 asthma cases insured by Insurer B were randomly selected from the 29 hospitals. Information was abstracted from each patient's medical record. Aside from the main variables of interest, insurer and LOS, the additional
information falls into four categories:
patients with comorbidities.
study these variables are named bedsize and teachcat.
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