Medical Meteorology: Whether Weather Influences Admissions

Abstract

To the Editor: Senior residents routinely petition Mother Nature for adverse weather conditions with the hope of reducing their workload by decreasing the number of hospital admissions. To our knowledge, no study to date has challenged the validity of this assumption. Wright-Patterson Medical Center is a US Air Force Regional Medical Center that provides primary and tertiary care to active-duty and retired military members and their dependents. The Wright-Patterson Air Force Base Weather Center is located less than 1 mile from the hospital. All weather data for this study were obtained from this weather center. We collected and compared admission and weather data over 13 noncontinuous months, representing all seasons. We measured the effect of the presence of any rainfall, snowfall, lightning, poor visibility (<5/8 mile), or extreme temperatures (<20°F/>90°F) and weekend/weekday numbers of admissions. For the months studied, the average number of admissions per day to the internal medicine service was 5.9 patients. The univariate analysis of the 6 independent weather variables done with t tests to determine the difference between the presence and absence of the weather variable on admissions is given in Table 1. Admissions were increased when rain was present, and the number was higher on weekdays than on weekends. Admissions were decreased when snow and lightning were present.Table 1Noncontinuous Adverse Conditions and Number of Admissions*Expressed as sample size (mean ± SD number of admissions).ConditionVisibility < 5/8mileRain†P<.01.Snow†P<.01.Lightning†P<.01.Temperature <20°F/>90°FWeekday†P<.01.Present42 (5.92±3.27)66 (6.50±3.40)15 (5.00±2.59)13 (5.00±2.89)23 (5.96±2.92)186 (6.56±1.66)Absent217 (5.91±2.81)193 (5.72±2.58)244 (5.97±2.84)246 (5.96±2.82)236 (5.91±2.82)73 (4.27±2.93)* Expressed as sample size (mean ± SD number of admissions).† P<.01. Open table in a new tab The results of the multiple regression analysis to determine what combinations of variables significantly predict admissions are shown in Table 2. When “weekend” was entered on step 1 with “snowfall” on step 2, the predicted variance was 14.7%. None of the remaining variables entered was significantly predictive. When all variables were forced into the equation, a total of 18.5% of the variance was explained.Table 2Multiple Regression With Admissions per Day as Dependent Variable*Final R2=0.157.R2R changeP valueStep 1: weekend0.1330.133<.001Step 2: snowfall0.1470.014<.001* Final R2=0.157. Open table in a new tab We found that weekends and snowfall together were important predictors of fewer admissions at our institution. While rain and lightning were significant in the univariate analysis, neither entered the prediction equation significantly in the multivariate analysis. The other variables studied did not affect admissions. Our study suggests that adverse weather conditions, with the exception of snowfall, may not reduce the senior resident's admission workload, but an open clinic is likely to increase it. The views expressed in this article are those of the authors and do not reflect the official policy of the Department of Defense or other departments of the US government.