AGE RATE MODELS Inpatient AGE Model AGE rates for the inpatient setting was specified using a Poisson model for weighted counts of AGE cases. \[w_{a,t} \sim ( n_{a,t})\] where \(\lambda\) is the rate, \(n\) is the subgroup population size and \(w\) is the weighted count of AGE patients. Subscripts \(a,y\) identify age and year subgroups, respectively. To account for imperfect observation of the AGE inpatient population, the observed cases \(y\) were weighted according to a binomial relationship: \[y_{a,t} \sim (w_{a,t}, \pi_y)\] where \(\pi\) is the weighting factor, and is the product of two quantities: (1) monitoring rate \(m\) of the inpatient hospital setting, in days per week; (2) VUMC market share \(s_t\) of Davidson county during year \(t\): \[\pi_t = m \times s_t\] The market shares were assumed to be 0.94, 0.9 and 0.83 for years 2012, 2013 and 2014, respectively and the monitoring rate was 1 (_i.e._ 7 days out of 7). Thus, this model accounts for two sources of stochastic uncertainty, one related to the appearance of cases in the sample, via the binomial sampling model, and another related to the disease process itself, via the Poisson count model. Outpatient AGE Model The AGE model for the outpatient setting is similar, except the population from which we are sampling is the total number of outpatients seen, rather than the population served by VUMC. Since monitoring intensity was 4 days per week for outpatients, the outpatient sample is correspondingly weighted by \(m=0.57\) (_i.e._ 4/7). Hence, the sample is modeled directly as a Poisson random variable: \[y_{a,t} \sim ( n_{a,t})\] ED AGE Model The AGE model for the ED setting is identical to that of the inpatient setting, save for an additional factor in the weighting term. This factor accounts for the expected relative number of patients enrolled in 8-hour monitoring relative to full 24-hour monitoring. Using available information regarding ED visits, we were able to estimate that our 8-hour surveillance period accounts for 55% of the expected number enrolled under 24-hour surveillance. This additional scaling factor \(\delta=0.55\) was added to the weighting for the observed sample: \[\pi_t = m \times s_t \times \delta\] The ED monitoring rate was \(m=0.57\) and market shares for all years were \(s_1=0.60, s_2=0.59, s_30.62\).
