統計分析案例 5

Comparison of hospital length of stay between two insurers for patients with

pediatric asthma

Introduction

This case study investigates the relative importance of several factors in predicting the length of time young patients with asthma stay in the hospital.

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.

Sampling scheme

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.

Recorded variables

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.

A. Patient Severity Variables describe the severity of the patient’s condition at admission to the hospital.

B. Demographic Variables describe the patient’s age, sex, race. C. Hospital level variables describe aspects of the characteristics of

the hospital in which the patient was treated. D. treatment Variables describe aspects of the patient’s treatment

during hospitalization.

Variables

The Pediatric Asthma data found in the file Case05.txt can be read by the SAS input statement file

INPUT LOS 1-2 HOSPITAL 4-6 PATIENT 8-12 INSURER 14-15 SUMCOMRB 17-18 CMPL11 21 CMPL12 23 SEVMOD 25 SEVSEV 27 HISTF01 29-30 HISTF02 32 HISTF03 34-35 AGE 37-38 FEMALE 40 RACE 42 SUMSERV 44-46 BEDSIZE 48 OWNER 50 TEACHCAT 52 ANYCOMP 54 HIGHPOC 56 MEDPOC 58 LOWPOC 60 DIAGTSTS 62-63 @65 FTETOBED 7.4 @73 PCTINS1 7.4;

A, B, C, D

Questions of interest

Are there differences in LOS between the insurers? Do the differences hold up once you have

accounted for differences in hospital and patient characteristics?

What are the differences in patient severity characteristics, demographics, hospital characteristics, and treatment variables between the two insurers?

Analysis

Frequency of the Variables: FREQ Descriptive of Variables: MEANS Correlation b/w LOS and Variables: CORR Contingency table: FREQ; TABLES Regression: REG