Accelerating the Pace of Surgical Quality Improvement

Campbell, Darrell A.; Englesbe, Michael J.; Kubus, James; Phillips, Laurel R. S.; Shanley, Charles J.; Velanovich, Vic; Lloyd, Larry R.; Hutton, Max; Arneson, Wallace; Share, David

doi:10.1001/archsurg.2010.220

Cited by 136 publications

(101 citation statements)

References 20 publications

Supporting

Mentioning

101

Contrasting

Order By: Relevance

“…Data for the mSqC are rigorously recorded by trained and certified clinical nurse reviewers at each participating ACS nSqiP hospital in michigan, and the validity and reliability of this comprehensive tool for quality improvement has been previously demonstrated. 18,19 Data collected include demographic characteristics, comorbidities, laboratory values, intraoperative events, and 30-day postoperative outcomes of patients undergoing general and vascular surgery. in addition to the more than 200 variables identical to ACS nSqiP, the mSqC's "colectomy project" records more specific pre-, intra-, and postoperative data on certain types of colectomies.…”

Section: Methodsmentioning

confidence: 99%

Risk Factors for Anastomotic Leakage After Colectomy

Leichtle

Mouawad

Welch

et al. 2012

Diseases of the Colon &Amp; Rectum

View full text Add to dashboard Cite

show abstract

Section: Methodsmentioning

confidence: 99%

Risk Factors for Anastomotic Leakage After Colectomy

Leichtle

Mouawad

Welch

et al. 2012

Diseases of the Colon &Amp; Rectum

View full text Add to dashboard Cite

show abstract

“…The MSQC represents a partnership between two entities-Blue Cross and Blue Shield of Michigan and 52 Michigan hospitals. This project followed standard data definitions and collection protocols as we have previously described [15, 16]. In brief, data collection occurs at the hospital level by specific MSQC data-collection nurses.…”

Section: Methodsmentioning

confidence: 99%

Improving Mortality Following Emergent Surgery in Older Patients Requires Focus on Complication Rescue

et al. 2013

Self Cite

View full text Add to dashboard Cite

Structured Abstract Objective To determine if a hospital’s ability to rescue patients from major complications underlies variation in outcomes for elderly patients undergoing emergency surgery. Summary Background Data Perioperative mortality rates in elderly patients undergoing emergent general/vascular operations are high and vary widely across Michigan hospitals. Methods We identified 23,224 patients undergoing emergent general/vascular surgery procedures at 41 hospitals within the Michigan Surgical Quality Collaborative (MSQC) between 2006–2011. Hospitals were ranked by risk- and reliability-adjusted 30-day mortality and grouped into tertiles. We stratified patients by age (<75 and ≥75). Risk-adjusted major complication and failure to rescue (i.e., mortality following major complication) rates were determined for each tertile of hospital mortality. Results Risk-adjusted mortality rates in elderly patients varied 2-fold across all hospitals. Complication rates correlated poorly with mortality. Failure-to-rescue rates, however, were markedly higher in high mortality hospitals (29% lowest tertile vs. 41% highest tertile, p<0.01). When compared to younger patients, overall failure to rescue rates were almost 2-fold greater in the elderly (36.1% ≥75 vs. 18.7% <75, p<0.01). Conclusions Hospitals’ failure to rescue patients from major complications seems to underlie the variation in mortality across Michigan hospitals following emergent surgery. While higher failure to rescue rates in the elderly may signify their diminished physiological reserve for surviving critical illness, the wide variation across hospitals also highlights the importance of systems aimed at the early recognition and effective management of major complications in this vulnerable population.

show abstract

“…MSQC data abstraction and data quality assurance details have been described elsewhere. [9][10][11][12] In brief, specially trained data abstractors prospectively collect patient characteristics, intraoperative processes of care, and 30-day postoperative outcomes for patients undergoing specified general and vascular surgical operations utilizing a sampling algorithm that minimizes selection bias. This algorithm divides each calendar year into 46 8-day cycles, from which the first 25 consecutive surgical operations that meet MSQC inclusion criteria are selected.…”

Section: Data Sourcesmentioning

confidence: 99%