統計分析案例 5

1. 統計分析案例5 Comparison of hospital length of stay between two insurers for patients with pediatric asthma

2. 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.

3. 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.

4. 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.

5. 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 14-15SUMCOMRB 17-18 CMPL11 21 CMPL12 23 SEVMOD 25 SEVSEV 27 HISTF01 29-30 HISTF02 32 HISTF03 34-35AGE 37-38 FEMALE 40 RACE 42SUMSERV 44-46 BEDSIZE 48 OWNER 50 TEACHCAT 52ANYCOMP 54 HIGHPOC 56 MEDPOC 58 LOWPOC 60 DIAGTSTS 62-63@65 FTETOBED 7.4 @73 PCTINS1 7.4; • A, B, C, D

6. 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?

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