Ranking Hospitals Based on Colon Surgery and Abdominal Hysterectomy Surgical Site Infection Outcomes: Impact of Limiting Surveillance to the Operative Hospital.

Background: Hospital-specific surgical site infection (SSI) performance following colon surgery and abdominal hysterectomies can impact hospitals' relative rankings around quality metrics used to determine financial penalties. Current SSI surveillance largely focuses on SSI detected at the operative hospital. Methods: We performed a retrospective cohort study to assess the impact on hospitals' relative SSI performance rankings when SSI detected at nonoperative hospitals are included. We used data from a California statewide hospital registry to assess for evidence of SSI following colon surgery or abdominal hysterectomies performed 1 March 2011 through 30 November 2013 using previously validated claims-based SSI surveillance methods. Risk-adjusted hospital-specific rankings based on SSI detected at operative hospitals versus any California hospital were generated. Results: Among 60059 colon surgeries at 285 hospitals and 64918 abdominal hysterectomies at 270 hospitals, 5921 (9.9%) colon surgeries and 1481 (2.3%) abdominal hysterectomies received a diagnosis code for SSI within the 30 days following surgery. Operative hospital surveillance alone would have missed 7.2% of colon surgery and 13.4% of abdominal hysterectomy SSIs. The proportion of an individual hospital's SSIs detected during hospitalizations at other hospitals varied widely. Including nonoperative hospital SSIs resulted in improved relative ranking of 11 (3.9%) colon surgery and 13 (4.8%) hysterectomy hospitals so that they were no longer in the worst performing quartile, mainly among hospitals with relatively high surgical volumes. Conclusions: Standard SSI surveillance that mainly focuses on infections detected at the operative hospital causes varying degrees of SSI underestimation, leading to inaccurate assignment or avoidance of financial penalties for approximately 1 in 11-16 hospitals.

Cost savings of universal decolonization to prevent intensive care unit infection: implications of the REDUCE MRSA trial.

OBJECTIVE: To estimate and compare the impact on healthcare costs of 3 alternative strategies for reducing bloodstream infections in the intensive care unit (ICU): methicillin-resistant Staphylococcus aureus (MRSA) nares screening and isolation, targeted decolonization (ie, screening, isolation, and decolonization of MRSA carriers or infections), and universal decolonization (ie, no screening and decolonization of all ICU patients). DESIGN: Cost analysis using decision modeling. METHODS: We developed a decision-analysis model to estimate the health care costs of targeted decolonization and universal decolonization strategies compared with a strategy of MRSA nares screening and isolation. Effectiveness estimates were derived from a recent randomized trial of the 3 strategies, and cost estimates were derived from the literature. RESULTS: In the base case, universal decolonization was the dominant strategy and was estimated to have both lower intervention costs and lower total ICU costs than either screening and isolation or targeted decolonization. Compared with screening and isolation, universal decolonization was estimated to save $171,000 and prevent 9 additional bloodstream infections for every 1,000 ICU admissions. The dominance of universal decolonization persisted under a wide range of cost and effectiveness assumptions. CONCLUSIONS: A strategy of universal decolonization for patients admitted to the ICU would both reduce bloodstream infections and likely reduce healthcare costs compared with strategies of MRSA nares screening and isolation or screening and isolation coupled with targeted decolonization.

Reporting surgical site infections following total hip and knee arthroplasty: impact of limiting surveillance to the operative hospital.

BACKGROUND: Public reporting of surgical site infections (SSIs) by hospitals is largely limited to infections detected during surgical hospitalizations or readmissions to the same facility. SSI rates may be underestimated if patients with SSIs are readmitted to other hospitals. We assessed the impact of readmissions to other facilities on hospitals' SSI rates following primary total hip arthroplasty (THA) or total knee arthroplasty (TKA). METHODS: This was a retrospective cohort study of all patients who underwent primary THA or TKA at California hospitals between 1 January 2006 and 31 December 2009. SSIs were identified using ICD-9-CM diagnosis codes predictive of SSI assigned at any California hospital within 365 days of surgery using a statewide repository of hospital data that allowed tracking of patients between facilities. We used statewide data to estimate the fraction of each hospital's THA and TKA SSIs identified at the operative hospital versus other hospitals. RESULTS: A total of 91 121 THA and 121 640 TKA procedures were identified. Based on diagnosis codes, SSIs developed following 2214 (2.3%) THAs and 2465 (2.0%) TKAs. Seventeen percent of SSIs would have been missed by operative hospital surveillance alone. The proportion of hospitals' SSIs detected at nonoperative hospitals ranged from 0% to 100%. Including SSIs detected at nonoperative hospitals resulted in better relative ranking for 61% of THA hospitals and 61% of TKA hospitals. CONCLUSIONS: Limiting SSI surveillance to the operative hospital caused varying degrees of SSI underestimation and substantially impacted hospitals' relative rankings, suggesting that alternative methods for comprehensive postdischarge surveillance are needed for accurate benchmarking.

Social network analysis of patient sharing among hospitals in Orange County, California.

OBJECTIVES: We applied social network analyses to determine how hospitals within Orange County, California, are interconnected by patient sharing, a system which may have numerous public health implications. METHODS: Our analyses considered 2 general patient-sharing networks: uninterrupted patient sharing (UPS; i.e., direct interhospital transfers) and total patient sharing (TPS; i.e., all interhospital patient sharing, including patients with intervening nonhospital stays). We considered these networks at 3 thresholds of patient sharing: at least 1, at least 10, and at least 100 patients shared. RESULTS: Geographically proximate hospitals were somewhat more likely to share patients, but many hospitals shared patients with distant hospitals. Number of patient admissions and percentage of cancer patients were associated with greater connectivity across the system. The TPS network revealed numerous connections not seen in the UPS network, meaning that direct transfers only accounted for a fraction of total patient sharing. CONCLUSIONS: Our analysis demonstrated that Orange County's 32 hospitals were highly and heterogeneously interconnected by patient sharing. Different hospital populations had different levels of influence over the patient-sharing network.