1. Ryan Kelly Dr. Nicolas Shammas Christine Beuthin Jackie Carlson Marti Cox Kathy Lenaghan Dr. Ram Niwas Dr. Jon Lemke 06/18/15 ASSESSMENT OF TIME TO HOSPITAL READMISSIONS AND NUMBER OF HOSPITAL PATIENT DAYS AFTER AN INITIAL HOSPITALIZATION FOR HEART FAILURE Genesis Research Summit WITH DISCUSSION ADDENDUM

2.  The phases of this project include:  Identify patient population  Gather and consolidate patient information  Use Medicare models to determine relevant risk factors  Assess effects of risk factors on time to readmission and hospitalized days after index visit PROJECT PHASES Kelly, R. et al. June 18, 2015

3.  Included Patients  Medicare Patients  500 Admissions for Heart Failure 10/1/2011 – 9/30/2013  Index Diagnosis of Heart Failure in Study Time Frame  GMC-Davenport or GMC-Silvis  Reside in 17 County Service Area  Results in 166 Patients in Final Population  Record all Patient Hospital Visits (Inpatient, Outpatient, Outpatient Observation, ED) from Index Hospitalization until 12/31/2013  Censor Patient Upon Death, Readmission Outside GHS, Elective Procedure, or AMA STUDY DESIGN Kelly, R. et al. June 18, 2015

4. Mean Age79.3 Years Sex Women: 76 (46%) Men: 90 (54%) Type of Heart Failure Diastolic: 55 (33%) Systolic: 55 (33%) Both: 11 (7%) Unspecified: 45 (27%) Site of Index Visit Davenport: 102 (61%) Silvis: 64 (39%) PATIENT DEMOGRAPHICS Kelly, R. et al. June 18, 2015

8.  Can we use PoA diagnoses at index visit to predict readmission and hospitalized days?  CMS – Yale Models (30 day readmissions)  34 Groupers of Related ICD-9 Codes, Plus Age and Sex  Does the type of Heart Failure and the medications given significantly affect patient outcomes?  Univariate Analysis  Split population based on inclusion in one of 34 groupers  For example, compare 46 anemic patients vs. 112 non-anemic patients  Multivariate Analysis  Utilize all diagnoses, age, sex, and other predictors to create comprehensive model RISK FACTORS AND MODELING Kelly, R. et al. June 18, 2015

9. GrouperOdds Ratio Renal failure1.20 Severe hematological disorders 1.18 Chronic obstructive pulmonary disease 1.17 Metastatic cancer or acute leukemia 1.16 Congestive heart failure1.13 Disorders of fluid, electrolyte, acid-base 1.13 Acute coronary syndrome1.12 End stage renal disease or dialysis 1.12 Cardio-respiratory failure or shock 1.11 MEDICARE 30 DAY READMISSION MODEL (YALE) GrouperOdds Ratio Pneumonia1.11 Diabetes or DM complications1.10 Iron deficiency or other anemias and blood disease 1.10 Drug/alcohol abuse/dependence/psychosis 1.10 Protein-calorie malnutrition1.09 Decubitus ulcer or chronic skin ulcer 1.09 Liver or biliary disease1.08 Nephritis1.08 Vascular or circulatory disease1.07 Peptic ulcer, hemorrhage, other specified GI disorders 1.07 Kelly, R. et al. June 18, 2015

10. GrouperOdds Ratio Other psychiatric disorders1.07 Other urinary tract disorders1.07 Coronary atherosclerosis or angina 1.06 Specified arrhythmias1.06 Major psychiatric disorders1.06 Other GI disorders1.05 Fibrosis of lung or other chronic lung disorders 1.05 Valvular or rheumatic heart disease 1.04 Other or unspecified heart disease 1.04 MEDICARE 30 DAY READMISSION MODEL (YALE) GrouperOdds Ratio Hemiplegia, paraplegia, paralysis, functional disability 1.04 Stroke1.03 Dementia or other specified brain disorders 1.02 Depression1.02 Asthma1.01 Male1.01 Cancer1.00 Age > 651.00 Kelly, R. et al. June 18, 2015

13.  Time to Readmission Model including risk factors  Model 30-Day Readmission Rate  Probability of 30-Day readmission from the CMS model  All encounters, and Inpatient Readmissions only  Poisson regression for number of hospitalized days after index  Weighted by number of days at risk, and controlled for age and sex  Ultimate goal to reduce cost per covered life through use of accurate models MULTIVARIATE MODELING Kelly, R. et al. June 18, 2015

14. RESULTS Kelly, R. et al. June 18, 2015

15. RESULTS Kelly, R. et al. June 18, 2015

16.  Model for Hospitalized Days with Age, Sex, Type of Heart Failure, Medication, and Each of 34 groupers  Explained variation  Lung Fibrosis and Eligibility for ACEI/ARB were both significant RESULTS Indicated Eligible ACEI/ARB? With Lung Fibrosis? Hospitalized Days Days at Risk Rate Yes 3310631.1 per 100 YesNo219.5159021.4 per 100 NoYes0.52510.2 per 100 No 311.589333.5 per 100 Kelly, R. et al. June 18, 2015

17.  Genesis announced they would begin CMS HF Bundled Payments on July 1 st of this year  These bundled payments include the index admission, as well as all costs during 90 day episodes of care  A brief summary of our 166 patient population showed  287 follow up visits (1.7 per patient)  1158 Total Hospitalized Days  2.6 per visit  7.0 per patient  8.6 hospitalized days per 100 at risk  21 deaths (12.7%) CMS HF BUNDLED PAYMENTS Kelly, R. et al. June 18, 2015

18. 90-DAY EPISODES OF CARE Kelly, R. et al. June 18, 2015

19. 90-DAY EPISODES OF CARE Kelly, R. et al. June 18, 2015

20.  Further explore the potential differences in outcomes between patients with diastolic or systolic heart failure  Fine tune multivariate models used to predict readmissions  Develop graphical representations of the final models. WHAT IS NEXT Kelly, R. et al. June 18, 2015