Hospital Strategies for Reducing Risk-Standardized Mortality Rates in Acute Myocardial Infarction

BACKGROUND Despite recent improvements in survival after acute myocardial infarction (AMI), U.S. hospitals vary 2-fold in their 30-day risk-standardized mortality rates (RSMRs). Nevertheless, information is limited on hospital-level factors that may be associated with RSMRs. OBJECTIVE To identify hospital strategies that were associated with lower RSMRs. DESIGN Cross-sectional survey of 537 hospitals (91% response rate) and weighted multivariate regression by using data from the Centers for Medicare & Medicaid Services to determine the associations between hospital strategies and hospital RSMRs. SETTING Acute care hospitals with an annualized AMI volume of at least 25 patients. PARTICIPANTS Patients hospitalized with AMI between 1 January 2008 and 31 December 2009. MEASUREMENTS Hospital performance improvement strategies, characteristics, and 30-day RSMRs. RESULTS In multivariate analysis, several hospital strategies were significantly associated with lower RSMRs and in aggregate were associated with clinically important differences in RSMRs. These strategies included holding monthly meetings to review AMI cases between hospital clinicians and staff who transported patients to the hospital (RSMR lower by 0.70 percentage points), having cardiologists always on site (lower by 0.54 percentage points), fostering an organizational environment in which clinicians are encouraged to solve problems creatively (lower by 0.84 percentage points), not cross-training nurses from intensive care units for the cardiac catheterization laboratory (lower by 0.44 percentage points), and having physician and nurse champions rather than nurse champions alone (lower by 0.88 percentage points). Fewer than 10% of hospitals reported using at least 4 of these 5 strategies. LIMITATION The cross-sectional design demonstrates statistical associations but cannot establish causal relationships. CONCLUSION Several strategies, which are currently implemented by relatively few hospitals, are associated with significantly lower 30-day RSMRs for patients with AMI. PRIMARY FUNDING SOURCE The Agency for Healthcare Research and Quality, the United Health Foundation, and the Commonwealth Fund.

[1]  Peter Cram,et al.  Characteristics and Outcomes of America's Lowest-Performing Hospitals: An Analysis of Acute Myocardial Infarction Hospital Care in the United States , 2009, Circulation. Cardiovascular quality and outcomes.

[2]  Harlan M Krumholz,et al.  Regional variation in the treatment and outcomes of myocardial infarction: investigating New England's advantage. , 2003, American heart journal.

[3]  David A. Belsley,et al.  Regression Analysis and its Application: A Data-Oriented Approach.@@@Applied Linear Regression.@@@Regression Diagnostics: Identifying Influential Data and Sources of Collinearity , 1981 .

[4]  S. Normand,et al.  Quality of care for acute myocardial infarction at urban safety-net hospitals. , 2007, Health affairs.

[5]  E. Ellerbeck,et al.  Impact of organizational infrastructure on beta-blocker and aspirin therapy for acute myocardial infarction. , 2006, American heart journal.

[6]  S. Normand,et al.  Patterns of Hospital Performance in Acute Myocardial Infarction and Heart Failure 30-Day Mortality and Readmission , 2009, Circulation. Cardiovascular quality and outcomes.

[7]  Ingrid M. Nembhard,et al.  Qualitative and Mixed Methods Provide Unique Contributions to Outcomes Research , 2009, Circulation.

[8]  Samantha Mauck,et al.  What Distinguishes Top-performing Hospitals in Acute Myocardial Infarction Mortality Rates? A Qualitative Study , 2011 .

[9]  S. Normand,et al.  Hospital remoteness and thirty-day mortality from three serious conditions. , 2008, Health affairs.

[10]  Jonathan Fine,et al.  Use of Multidisciplinary Rounds to Simultaneously Improve Quality Outcomes, Enhance Resident Education, and Shorten Length of Stay , 2007, Journal of General Internal Medicine.

[11]  H. Krumholz,et al.  A qualitative study of increasing beta-blocker use after myocardial infarction: Why do some hospitals succeed? , 2001, JAMA.

[12]  W. W. Muir,et al.  Regression Diagnostics: Identifying Influential Data and Sources of Collinearity , 1980 .

[13]  John W. Creswell,et al.  Designing and Conducting Mixed Methods Research , 2006 .

[14]  M. Chassin Assessing strategies for quality improvement. , 1997, Health affairs.

[15]  M. Chassin Assessing Strategics For Quality Improvement , 1997 .

[16]  J. Balligand,et al.  Cardiomyocyte-specific overexpression of beta3-adrenoceptors attenuates the hypertrophic response to catecholamines in vivo , 2007 .

[17]  H. Krumholz,et al.  A Qualitative Study of Increasing β-Blocker Use After Myocardial Infarction: Why Do Some Hospitals Succeed? , 2001 .

[18]  Harlan M Krumholz,et al.  Hospital quality for acute myocardial infarction: correlation among process measures and relationship with short-term mortality. , 2006, JAMA.

[19]  Harlan M Krumholz,et al.  Research in action: using positive deviance to improve quality of health care , 2009, Implementation science : IS.

[20]  B. McNeil,et al.  Using admission characteristics to predict short-term mortality from myocardial infarction in elderly patients. Results from the Cooperative Cardiovascular Project. , 1996, JAMA.

[21]  S. Normand,et al.  Hospital volume and 30-day mortality for three common medical conditions. , 2010, The New England journal of medicine.

[22]  S. Normand,et al.  Reduction in acute myocardial infarction mortality in the United States: risk-standardized mortality rates from 1995-2006. , 2009, JAMA.

[23]  J. Ornato,et al.  2009 Focused Updates: ACC/AHA Guidelines for the Management of Patients With ST‐Elevation Myocardial Infarction (Updating the 2004 Guideline and 2007 Focused Update) and ACC/AHA/SCAI Guidelines on Percutaneous Coronary Intervention (Updating the 2005 Guideline and 2007 Focused Update) , 2009, Catheterization and cardiovascular interventions : official journal of the Society for Cardiac Angiography & Interventions.

[24]  Harlan M Krumholz,et al.  Survival after acute myocardial infarction (SAMI) study: the design and implementation of a positive deviance study. , 2011, American heart journal.

[25]  G. Ellrodt,et al.  Multidisciplinary rounds (MDR): an implementation system for sustained improvement in the American Heart Association's Get With The Guidelines program. , 2007, Critical pathways in cardiology.

[26]  S. Normand,et al.  Variation in hospital mortality rates for patients with acute myocardial infarction. , 2010, The American journal of cardiology.

[27]  M. Glickman,et al.  Statistical Methods for Profiling Providers of Medical Care: Issues and Applications , 1997 .

[28]  N. Powe,et al.  The association between hospital volume and survival after acute myocardial infarction in elderly patients. , 1999, The New England journal of medicine.

[29]  A. Rivkin,et al.  Evaluation of the role of the critical care pharmacist in identifying and avoiding or minimizing significant drug-drug interactions in medical intensive care patients. , 2011, Journal of critical care.

[30]  G. Willis,et al.  Research Synthesis: The Practice of Cognitive Interviewing , 2007 .

[31]  Harlan M Krumholz,et al.  National Patterns of Risk-Standardized Mortality and Readmission for Acute Myocardial Infarction and Heart Failure: Update on Publicly Reported Outcomes Measures Based on the 2010 Release , 2010, Circulation. Cardiovascular quality and outcomes.

[32]  H. Krumholz,et al.  Comparing AMI mortality among hospitals in patients 65 years of age and older: evaluating methods of risk adjustment. , 1999, Circulation.

[33]  S M Shortell,et al.  The Performance of Intensive Care Units: Does Good Management Make a Difference? , 1994, Medical care.

[34]  Richard F MacLehose,et al.  Quality of care for acute myocardial infarction in rural and urban US hospitals. , 2004, The Journal of rural health : official journal of the American Rural Health Association and the National Rural Health Care Association.

[35]  H. Krumholz,et al.  Hospital-Level Performance Improvement: Beta-Blocker Use After Acute Myocardial Infarction , 2004, Medical care.

[36]  M. Daniels,et al.  Hierarchical Generalized Linear Models in the Analysis of Variations in Health Care Utilization , 1999 .

[37]  Neal Krause,et al.  A comprehensive strategy for developing closed-ended survey items for use in studies of older adults. , 2002, The journals of gerontology. Series B, Psychological sciences and social sciences.

[38]  R. Centor,et al.  Relationship of hospital teaching status with quality of care and mortality for Medicare patients with acute MI. , 2000, JAMA.

[39]  S. Normand,et al.  An Administrative Claims Model Suitable for Profiling Hospital Performance Based on 30-Day Mortality Rates Among Patients With an Acute Myocardial Infarction , 2006, Circulation.