The Maryland Department of Health (MDH) has asked The Hilltop Institute to determine the predictive value of questions present on the Minimum Data Set (MDS) assessment for subsequent hospitalization during a Medicare Skilled Nursing Facility (SNF) stay. To do this, we analyzed the most recent assessment from 202,839 SNF stays in Maryland that began between January 1, 2013, and December 31, 2016. We found that 48,582 of these stays ended in a discharge to a hospital. We then calculated the amount of time between the nursing home admission and the subsequent hospitalization for each case. Finally, we loaded the resulting data set into a proportional hazard regression model in order to calculate the value of selected MDS assessment responses on assessing the risk of an individual's discharge to a hospital during a SNF post-acute care stay.
Of the 35 MDS elements initially considered for the model, 22 were statistically significant at the 0.05 level. Of these, shortness of breath and fever had by far the highest hazard ratios. Individuals displaying signs of shortness of breath while sitting were 84 percent more likely to be hospitalized during their SNF stay than other individuals,