Financial impact of introducing the Swiss-DRG reimbursement system on potentially avoidable readmissions at a university hospital.

QUESTION UNDER STUDY: Thirty-day readmissions can be classified as potentially avoidable (PARs) or not avoidable (NARs) by following a specific algorithm (SQLape®). We wanted to assess the financial impact of the Swiss-DRG system, which regroups some readmissions occurring within 18 days after discharge within the initial hospital stay, on PARs at our hospital. METHODS: First, PARs were identified from all hospitalisations recorded in 2011 at our university hospital. Second, 2012 Swiss-DRG readmission rules were applied, regrouped readmissions (RR) were identified, and their financial impact computed. Third, RRs were classified as potentially avoidable (PARRs), not avoidable (NARRs), and others causes (OCRRs). Characteristics of PARR patients and stays were retrieved, and the financial impact of PARRS was computed. RESULTS: A total of 36,777 hospitalisations were recorded in 2011, of which 3,140 were considered as readmissions (8.5%): 1,470 PARs (46.8%) and 1,733 NARs (53.2%). The 2012 Swiss-DRG rules would have resulted in 910 RRs (2.5% of hospitalisations, 29% of readmissions): 395 PARRs (43% of RR), 181 NARRs (20%), and 334 OCRRs (37%). Loss in reimbursement would have amounted to CHF 3.157 million (0.6% of total reimbursement). As many as 95% of the 395 PARR patients lived at home. In total, 28% of PARRs occurred within 3 days after discharge, and 58% lasted less than 5 days; 79% of the patients were discharged home again. Loss in reimbursement would amount to CHF 1.771 million. CONCLUSION: PARs represent a sizeable number of 30-day readmissions, as do PARRs of 18-day RRs in the 2012 Swiss DRG system. They should be the focus of attention, as the PARRs represent an avoidable loss in reimbursement.

Systems Genetics of Metabolism: The Use of the BXD Murine Reference Panel for Multiscalar Integration of Traits.

Metabolic homeostasis is achieved by complex molecular and cellular networks that differ significantly among individuals and are difficult to model with genetically engineered lines of mice optimized to study single gene function. Here, we systematically acquired metabolic phenotypes by using the EUMODIC EMPReSS protocols across a large panel of isogenic but diverse strains of mice (BXD type) to study the genetic control of metabolism. We generated and analyzed 140 classical phenotypes and deposited these in an open-access web service for systems genetics (www.genenetwork.org). Heritability, influence of sex, and genetic modifiers of traits were examined singly and jointly by using quantitative-trait locus (QTL) and expression QTL-mapping methods. Traits and networks were linked to loci encompassing both known variants and novel candidate genes, including alkaline phosphatase (ALPL), here linked to hypophosphatasia. The assembled and curated phenotypes provide key resources and exemplars that can be used to dissect complex metabolic traits and disorders.