Reducing burnout and enhancing work engagement among clinicians: The Minnesota experience.

Background: The Minnesota Hospital Association (MHA) recognized the impact that burnout and disengagement had on the clinician population. A clinician task force developed a conceptual framework, followed by annual surveys and a series of interventions. Features of the job demands-resources model were used as the conceptual underpinning to this analysis.

Adding Laboratory Data to Hospital Claims Data to Improve Risk Adjustment of Inpatient/30-Day Postdischarge Outcomes.

Numerical laboratory data at admission have been proposed for enhancement of inpatient predictive modeling from administrative claims. In this study, predictive models for inpatient/30-day postdischarge mortality and for risk-adjusted prolonged length of stay, as a surrogate for severe inpatient complications of care, were designed with administrative data only and with administrative data plus numerical laboratory variables. A comparison of resulting inpatient models for acute myocardial infarction, congestive heart failure, coronary artery bypass grafting, and percutaneous cardiac interventions demonstrated improved discrimination and calibration with administrative data plus laboratory values compared to administrative data only for both mortality and prolonged length of stay.

Admission Laboratory Results to Enhance Prediction Models of Postdischarge Outcomes in Cardiac Care.

Predictive modeling for postdischarge outcomes of inpatient care has been suboptimal. This study evaluated whether admission numerical laboratory data added to administrative models from New York and Minnesota hospitals would enhance the prediction accuracy for 90-day postdischarge deaths without readmission (PD-90) and 90-day readmissions (RA-90) following inpatient care for cardiac patients. Risk-adjustment models for the prediction of PD-90 and RA-90 were designed for acute myocardial infarction, percutaneous cardiac intervention, coronary artery bypass grafting, and congestive heart failure.

Incorporating the Last Four Digits of Social Security Numbers Substantially Improves Linking Patient Data from De-identified Hospital Claims Databases.

Objective: Assess algorithms for linking patients across de-identified databases without compromising confidentiality.

Data Sources/study Setting: Hospital discharges from 11 Mayo Clinic hospitals during January 2008-September 2012 (assessment and validation data). Minnesota death certificates and hospital discharges from 2009 to 2012 for entire state (application data).

Harnessing the power of enhanced data for healthcare quality improvement: lessons from a Minnesota Hospital Association Pilot Project.

The imperative to achieve quality improvement and cost-containment goals is driving healthcare organizations to make better use of existing health information. One strategy, the construction of hybrid data sets combining clinical and administrative data, has strong potential to improve the cost-effectiveness of hospital quality reporting processes, improve the accuracy of quality measures and rankings, and strengthen data systems. Through a two-year contract with the Agency for Healthcare Research and Quality, the Minnesota Hospital Association launched a pilot project in 2007 to link hospital clinical information to administrative data.

Promoting collaboration and transparency in patient safety.

Background: The Minnesota Alliance for Patient Safety (MAPS) collaborative was founded in 2000 by the Minnesota Hospital Association (MHA), the Minnesota Medical Association, and the Minnesota Department of Health.

Creating A Culture Of Learning, Justice, And Accountability: MAPS made it a priority to make the health care workplace one that encourages learning from adverse events. MAPS is pioneering a statewide model of a "just" culture--one that supports learning yet holds individuals accountable for errors.