Comparing Resource Use in Medical Admissions of Children With Complex Chronic Conditions

Abstract

Background: Children with complex chronic conditions (CCCs) utilize a disproportionate share of hospital resources.

Objective: We asked whether some hospitals display a significantly different pattern of resource utilization than others when caring for similar children with CCCs admitted for medical diagnoses.

Research design: Using Pediatric Health Information System data from 2009 to 2013, we constructed an inpatient Template of 300 children with CCCs, matching these to 300 patients at each hospital, thereby performing a type of direct standardization.

Subjects: Children with CCCs were drawn from a list of the 40 most common medical principal diagnoses, then matched to patients across 40 Children's Hospitals.

Measures: Rate of intensive care unit admission, length of stay, resource cost.

Results: For the Template-matched patients, when comparing resource use at the lower 12.5-percentile and upper 87.5-percentile of hospitals, we found: intensive care unit utilization was 111% higher (6.6% vs. 13.9%, P<0.001); hospital length of stay was 25% higher (2.4 vs. 3.0 d/admission, P<0.001); and finally, total cost per patient varied by 47% ($6856 vs. $10,047, P<0.001). Furthermore, some hospitals, compared with their peers, were more efficient with low-risk patients and less efficient with high-risk patients, whereas other hospitals displayed the opposite pattern.

Conclusions: Hospitals treating similar patients with CCCs admitted for similar medical diagnoses, varied greatly in resource utilization. Template Matching can aid chief quality officers benchmarking their hospitals to peer institutions and can help determine types of their patients having the most aberrant outcomes, facilitating quality initiatives to target these patients.

Figure 1.. Template Creation and Matching Process:

The template was constructed by creating 2,000 random samples of 300 patients from the PHIS data set of study eligible patients, and selecting that template that had the smallest Mahalanobis distance to the patients admitted for a top 40 principal diagnosis. This created a representative template of CCC patients across study hospitals. The template was used to create strata of similar patients across the study hospitals.

Figure 2.. Risk Synergy Plots for Selected Hospitals:

The x-axis of each graph represents the risk, estimated by predicted length of stay on admission, for each template patient strata. The y-axis for the Hospitals AA and O represents the relative difference in log cost (focal minus control) inside each matched pair. The y-axis for Hospitals S and E represents the difference in ICU utilization (focal minus control). A point falling on the horizontal line at 0 represents no difference in cost (or ICU utilization) between the 2 patients in the matched pair, and a point falling below the line suggests a lower cost (or ICU utilization) for the focal vs control patient. The solid lines represent the locally weighted scatterplot smoothing (LOWESS) line. LOWESS 95% CI bands (shaded areas) for the central tendency line were produced using the bootstrap method. A box plot at the bottom of each graph denotes the 5%, 25%, 50%, 75%, and 95% values of the predicted risk over all strata. Each graph illustrates an individual hospital. Note, all 4 slopes (risk synergy plots) were statistically significant (see Supplemental Table 11).