Computer-generated informational messages directed to physicians: effect on length of hospital stay.

OBJECTIVE: With the advent of hospital payment by diagnosis-related group (DRG), length of stay (LOS) has become a major issue in hospital efforts to control costs. Because the Columbia-Presbyterian Medical Center (CPMC) has had above-average LOSs for many DRGs, the authors tested the hypothesis that a computer-generated informational message directed to physicians would shorten LOS. DESIGN: Randomized clinical trial with the patient as the unit of randomization. SETTING AND STUDY POPULATION: From June 1991 to April 1993, at CPMC in New York, 7,109 patient admissions were randomly assigned to an intervention (informational message) group and 6,990 to a control (no message) group. INTERVENTION: A message giving the average LOS for the patient's admission or provisional DRG, as assigned by hospital utilization review, and the current LOS, in days, was included in the main menu for review of test results in the hospital's clinical information system, available at all nursing stations in the hospital. MAIN OUTCOME MEASURE: Hospital LOS. RESULTS: The median LOS for study patients was 7 days. After adjustment for covariates including age, sex, payor, patient care unit, and time trends, the mean LOS in the intervention group was 3.2% shorter than that in the control group (p = 0.022). CONCLUSION: Computer-generated patient-specific LOS information directed to physicians was associated with a reduction in hospital LOS.

Physician use of computers: is age or value the predominant factor?

One common explanation for the failure to achieve broad physician utilization of computer applications has been the suggestion that "We can't teach older individuals to use computers." To investigate this hypothesis, we examined utilization patterns for the Clinical Information System (CIS) at Columbia Presbyterian Medical Center (CPMC). We analyzed CIS usage for 925 attending physicians who were listed as an admitting or attending physician or surgeon for at least one patient during the year 1992. Sixty-one percent (561/925) of the attending physicians used the system at least once during the year. Sixty five percent (186/287) of the physicians who admitted at least 50 cases used the system at least 120 times during the year. The most surprising aspect of our analysis was that physicians in their late 60's and early seventies actually used the system more than their peers who were in their late 50's. Patterns of use by age group were similar for those who admitted many and few patients to the hospital. Using linear regression and chi squared analysis, we found that age is correlated (p < 0.002) with levels of physician use (inquiries per case), although age can explain (r-squared) only 3% of the observed variation in utilization patterns. We also found that there was significant variation in utilization (inquiries per case) by attendings in different departments (p < 0.007). However, the variation within departments was also large. We conclude that age and type of practice are statistically significant but not major factors in predicting which attendings will use the system. Growth rates over time (19% year to year increase in the average number of different users per day) indicate that, if present trends continue, virtually all physicians regardless of age will use the Clinical Information System for results review. We continue to feel that providing value, access and ease of use are the most important determinants for success.

A dynamic analysis of net migration and state employment change.

"The dynamic relationship of net migration and employment change is examined for ten selected states of the U.S. using a multivariate time series approach--a vector autoregression (VAR) model. Granger causality tests and dynamic multipliers provide information on the dynamic process. The results suggest a state-level process in which employment change occurs first, and net migration follows with a lag. The procedure appears promising in investigating the timing of net migration and regional employment change."