Motivating example
NB, illness
REGRESSION, SECONDARY
Telemedicine (TM) is an emerging platform for the delivery of health-related services and medical information via telecommunication technology such as computers and smartphones. The COVID-19 pandemic heightened the importance and value of these contactless healthcare services. Previuosly [In this current study, the primary outcome of interest is the number of serious illness episodes. A serious illness episode was defined as a case in which a patient either had a hospital stay > 7 days was admitted to the pediatric intensive care unit (PICU) or died during the same hospitalization. Approximately 72.7% of the primary outcome values were zero (70% and 75.6% in the CC alone and CC + TM groups, respectively). Here, we also include two secondary outcomes: (1) days in the hospital and (2) care days outside the home. The distribution of days in hospital is similar to the primary outcome, with the exception of a few extreme observations (median 0, interquartile range 0–6, maximum 92). The distribution of care days outside the home differs because the percentage of zero counts is only 5.2%. The characteristics of the three observed outcomes are shown in Table Characteristics of the observed outcomes (Var., variance, % of 0’s, percentage of zero counts) and a list of covariates for adjustmentSimilar to the original analyses of these outcomes, we include three variables as predictors: (1) treatment group (CC alone = 0; CC + TM = 1); (2) age strata (< 2 years; ≥ 2), (3) baseline risk (risk level 1 [mechanical ventilation], risk level 2 [equal to or above the expected median risk but not ventilator-dependent], and risk level 3 [below the expected median risk]). Length of follow-up (in days) is included as an offset. Using the three outcomes and observed predictors, we performed a NB and ZINB regression analysis. The regression coefficients from the NB and ZINB models were then used as 