David D. McManus|Jane S. Saczynski|Darleen Lessard|Molly E. Waring|Jeroan J. Allison|David C. Parish|Robert J. Goldberg|Arlene S. Ash|Catarina I. Kiefe
Reliability of Predicting Early Hospital Readmission After Discharge for an Acute Coronary Syndrome Using Claims-Based Data
University of Massachusetts Chan Medical School|University of Massachusetts Chan Medical School|University of Massachusetts Chan Medical School|University of Massachusetts Chan Medical School|University of Massachusetts Chan Medical School|Mercer University|University of Massachusetts Chan Medical School|University of Massachusetts Chan Medical School|University of Massachusetts Chan Medical School
early rehospitalization discharge acute coronary syndrome including acute myocardial infarction ami generally considered undesirable centers medicare medicaid services cms base hospital financial incentives riskadjusted readmission rates ami using claims data adjustment models little known contribution readmission risk factors captured claims 804 consecutive patients 65 years discharged 2011 2013 6 hospitals massachusetts georgia acute coronary syndrome compared cmslike readmission prediction model enhanced model incorporating additional clinical psychosocial sociodemographic characteristics principal components analysis mean age 73 years 38 women 25 college educated 32 previous ami allcause rehospitalization occurred within 30 days 13 enhanced model previous coronary intervention odds ratio 205 95 confidence interval ci 134 316 chronic kidney disease 189 95 ci 115 310 low health literacy 175 95 ci 114 269 lower serum sodium levels current nonsmoker status positively associated readmission discriminative ability enhanced versus claimsbased model higher without evidence overfitting example patients highest deciles readmission likelihood observed readmissions occurred 24 claimsbased model 33 enhanced model conclusion readmission may influenced measurable factors cms claimsbased models controllable hospitals incorporating additional factors riskadjusted readmission models may improve accuracy validity use indicators hospital quality early rehospitalization discharge acute coronary syndrome including acute myocardial infarction ami generally considered undesirable centers medicare medicaid services cms base hospital financial incentives riskadjusted readmission rates ami using claims data adjustment models little known contribution readmission risk factors captured claims 804 consecutive patients 65 years discharged 2011 2013 6 hospitals massachusetts georgia acute coronary syndrome compared cmslike readmission prediction model enhanced model incorporating additional clinical psychosocial sociodemographic characteristics principal components analysis mean age 73 years 38 women 25 college educated 32 previous ami allcause rehospitalization occurred within 30 days 13 enhanced model previous coronary intervention odds ratio 205 95 confidence interval ci 134 316 chronic kidney disease 189 95 ci 115 310 low health literacy 175 95 ci 114 269 lower serum sodium levels current nonsmoker status positively associated readmission discriminative ability enhanced versus claimsbased model higher without evidence overfitting example patients highest deciles readmission likelihood observed readmissions occurred 24 claimsbased model 33 enhanced model conclusion readmission may influenced measurable factors cms claimsbased models controllable hospitals incorporating additional factors riskadjusted readmission models may improve accuracy validity use indicators hospital quality