The association of inpatient blood utilization and diagnosis‐related group weight: implications for risk‐adjusted benchmarking

Abstract

BACKGROUND Risk‐adjusted benchmarking could be useful to compare blood utilization between hospitals or individual groups, such as physicians, while accounting for differences in patient complexity. The aim of this study was to analyze the association of red blood cell (RBC) use and diagnosis‐related group (DRG) weights across all inpatient hospital stays to determine the suitability of using DRGs for between‐hospital risk‐adjusted benchmarking. Specific hierarchical organizational units (surgical vs. nonsurgical patients, departments, and physicians) were also evaluated. STUDY DESIGN AND METHODS We studied blood use among all adult inpatients, and within organizational units, over 4 years (May 2014 to March 2018) at an academic center. Number of RBCs transfused, all patient refined (APR)‐DRGs, and other variables were captured over entire hospital stays. We used multilevel generalized linear modeling (zero‐inflated negative binomial) to study the relationship between RBC utilization and APR‐DRG. RESULTS A total of 97,955 hospital stays were evaluated and the median APR‐DRG weight was 1.2. The association of RBCs transfused and APR‐DRG weight was statistically significant at all hierarchical levels (incidence rate ratio = 1.22; p < 0.001). The impact of APR‐DRG on blood use, measured by the incidence rate ratio, demonstrated an association at the all‐patient and surgical levels, at several department and physician levels, but not at the medical patient level. The relationship between RBCs transfused and APR‐DRG varied across organizational units. CONCLUSION Number of RBCs transfused was associated with APR‐DRG weight at multiple hierarchical levels and could be used for risk‐adjusted benchmarking in those contexts. The relationship between RBC use and APR‐DRG varied across organizational units.

Development and validation of a machine learning method to predict intraoperative red blood cell transfusions in cardiothoracic surgery

“…Most patients received zero intraoperative allogeneic RBC transfusions, while about one quarter used 1–3 units and 6% used 4 or more units. This right-skewed distribution is typical for plots showing the frequency of transfusion volumes amongst a cohort of patients 18 , 19 . While most patients were male, the percentage of female patients increased in higher blood use categories.…”

Better than ‘normal’: Describing the distribution of and outliers in RBC usage

“…Lumping these heterogenous groups together is sensible for total daily RBC usage from the perspective of inventory management, but analyzing blood usage at the individual patient level for this amalgamated group is not as helpful. Further work in this area could include fitting theoretical distributions to the empirical usage of select groups of patients and should include patients that used zero red cells as well 5 …”

“…Further work in this area could include fitting theoretical distributions to the empirical usage of select groups of patients and should include patients that used zero red cells as well. 5 When relating individual users to daily RBC usage, days with the top percentile of RBC usage were more likely to have at least one ultramassively transfused patient as compared to the bottom 99 percent of days. This finding is intuitive in that days with large amounts of RBC usage tended to have at least one large individual blood user.…”

“…[1][2][3] Blood usage can be partially estimated by patient volume and complexity, though the bias of this estimate is difficult to quantify. [4][5][6] Daily blood use is a random variable that fits some sampling distribution with associated parameters. 7…”

Sanguine: Visual analysis for patient blood management

“…For example, if one surgeon transfuses more blood on average than others in the peer group, the surgeon may rightly complain that the comparison is not fair if they tend to see sicker or more complex patients. Previous work 38 has shown that diagnosis related group (DRG) billing code weights are associated with transfusion volumes in surgical populations. In other words, more complex patients will have a higher DRG weight and would be expected to receive more blood on average.…”