Reducing Readmission

Transcription

1 Reducing Readmission Sharon Weber, MD Tim and MaryAnn McKenzie Chair of Surgical Oncology Vice Chair of Academic Affairs, General Surgery Director of Surgical Oncology, UW Carbone Cancer Center University of Wisconsin School of Medicine and Public Health

2 Readmission and the ACA 2010: Patient Protection and Affordable Care Act Pay for performance through hospital value based purchasing 2012: Hospital Readmission Reduction Project (HRRP) initiated by CMS Hospitals penalized for readmissions for patients with acute MI, CHF and pneumonia Benchmark rate July June HRRP 2015: Now includes surgical procedures Total hip/knee arthroplasty Hospital-wide reporting: All-cause Concerns: Number of hospitals impacted Disproportional impact on at-risk population SES not included in calculation» Safety net hospitals and minority-serving hospitals disproportionately impacted Weber SM Surgery 2014;156(5): Merkow, JAMA, 2015;313:483-95

3 Hospital Compare

4 Hospital Compare

5 Is The Focus on Readmission Working? Medicare data 100,000 fewer readmissions from Surgery specific data Jencks, et al CMS data: 15.6% of surgical patients readmitted Tsai, et al CMS data: 13.1% MedPAC Mar Jencks SF et al. NEJM 2009;360: Tsai et al. NEJM 2013;369:

6 Defining The Extent and Cause of Problem Nearly 500,000 patients Bariatrics, colectomy/proctectomy, hysterectomy, total hip or knee replacement, ventral hernia repair, LE vascular bypass Unplanned readmission 5.7% Only 2.3% due to complication that occurred in hospital Most were due to post-discharge complications Most common SSI 20% Delayed return of bowel function 10% Bleeding 5% Merkow, JAMA, 2015;313:483-95

7 A Valid Surgical Quality Metric? What does readmission measure in surgical patients? Post-discharge complications drive readmission Patient-specific socio-demographic factors play important role Insurance, poverty, race Not well measured in administrative databases Are readmissions a valid marker of poor quality? Likely enhance the quality of care for complications Patients do not see readmission as an issue Merkow, JAMA, 2015;313: Tsai et al. NEJM 2013;369: Revolving Door: Report on US Hosp Readmission, RWJ Foundation, 2013

8 Preventable Readmissions What readmissions are preventable? MedPAC definition: Readmission could have been prevented by Provision of quality care in the hospital Adequate discharge planning Adequate follow up Improved care coordination

9 Readmission Reduction Strategies Decrease post-discharge complication rates Manage complications as outpatient Focus on preventable readmissions Quality care in hospital Discharge planning Adequate follow-up Care coordination/enhanced transitional care Emphasis on high risk patients: Risk prediction

10 Interventions No study in surgical patients exclusively Medical data: Systemic review, 2011 and trials Minor representation of surgical patients No analysis of differences between medical and surgical patients Leppin, JAMA Int Med, 2014;174: Hansen, Ann Int Med 2011;155:520-8

11 Targets In Existing Intervention Trials Inpatient Stay Predischarge Interventions Patient education Med reconciliation D/C planning Discharge Postdischarge Interventions Follow-up call Patient activated hotlines Timely follow-up visit Readmission Bridging Interventions Transition coach MD continuity (Inpt/outpt) Patient-centered discharge instructions Hansen, Ann Int Med 2011;155:520-8

12 Intervention Trials Simple (single) interventions not effective Complex interventions needed Multiple components Involving more individuals in care process Supporting patient capacity for self-care Tested interventions effective at decreasing readmissions RR 0.82 (95% CI ) Trials published before 2002 more effective Likely reflecting institutional efforts aimed at reducing readmission over time Changing culture Leppin, JAMA Int Med, 2014;174: Hansen, Ann Int Med 2011;155:520-8

13 Risk Prediction Systemic review: 26 trials Mixed medical and surgical patients n: Trials Data Source Timing C-statistic Risk Prediction 14 Retrospective administrative data 7 Realtime admin data/ primary data collection Early during hospitalization POOR MODERATE 5 At discharge MODERATE Overall, poor performance for risk prediction Models that included functional and social variables improved model discrimination Kansagara, JAMA, 2011;306:

14 Surgical Models: Risk Prediction 2011 NSQIP Data Complex and parsimonious data set: equal performance Parsimonious: LOS/2 + ASA class Lucas, Ann Surg, 2013;258:430-39

15 The Identification of High Risk Patients at the Time of Discharge Single Institutional Data Tevis, JAMA Surg, 2015;Apr 22

16 Predictive Nomogram Developed Tevis, JAMA Surg, 2015;Apr 22

17 Negative Predictive Value High Study Population Retrospective Validation Group Prospective Validation Group Predicted Readmission Risk PPV NPV PPV NPV PPV NPV 6% 12.2% 94.8% 12.9% 94.3% 11.5% 96.9% Can exclude patients who have low risk of readmission Less possible to focus on a truly high risk population Tevis, JAMA Surg, 2015;Apr 22

18 Surgical Risk Prediction: Limitations Limited sociodemographic information Social support, insurance status, self-efficacy, caregiver availability missing NSQIP: 30d postoperative readmission rate

19 What is Unique to Surgical Patients? Post-hospitalization syndrome Sleep deprivation, stress, poor nutrition, pain, physical deconditioning Contributes to altered sensorium Post-operative cognitive dysfunction Deficits in Short-term memory Attention span Level of consciousness Occurs in up to 50-60% of patients Vulnerable Patients!! Moller, Lancet, 1998;351: Krumholz, NEJM 2013;368:100-2

20 Possible Strategies Must involve the caregiver!! No single best approach

21 Improved Transitional Care Active issues at time of discharge New patient education NOT part of chronic medical illness Unpredictable Patient vulnerable Problems with seamless transition Intake discontinuity Inadequate information to local providers Unfamiliar with complex surgical care Planned/elective surgery: opportunity for pre-op education

22 Discharge Planning Patient-centered discharge instructions Assure caregiver is present Multiple opportunities for teaching Planned, methodical strategy Remembering patient s altered cognition

23 Manage Complications as Outpatients Enhanced Transitional Care Many are result of expected complications Dehydration after ileostomy Early postoperative follow up visit For regional patients, provide residential bridge (eg hotel) to allow for close FU visits Wound care clinic New ostomy: protocolized care with IVF as needed

24 Follow-Up Early post-operative clinics, flexible availability, managed by APP s High risk patients may need more frequent monitoring Recruit PCP s or patients themselves for enhanced monitoring Orthostatics Wound check

25 Conclusions Readmission prevention is a complex undertaking Culture change is occurring Decreased readmissions Focus on: Prevention of postdischarge complications Managing complications outside of the hospital Involve caregivers Discharge planning Pre- and post-op education Ensuring patient safety essential

26

27 Validated Retro- and Prospectively OR 95% CI P value C statistic Retrospective Validation Prospective Validation < Tevis, JAMA Surg, 2015;Apr 22

28 Readmission Nomogram: PPV & NPV Patients Readmission Risk Cutoff (decile) Positive Predictive Value Negative Predictive Value 4.83% (10) 10.8% 96.1% 5.37% (20) 11.8% 95.7% 6.08% (30) 12.2% 94.8% 6.98% (40) 14.6% 94.5% 7.55% (50) 14.9% 94.6% 9.51% (60) 15.9% 93.6% 11.6%(70) 17.4% 92.9% 14.4%(80) 19.4% 92.3% 19.1% (90) 25.2% 91.4% PPV = TP/(TP+FP) NPV = TN/(TN+FN) Tevis, JAMA Surg, 2015;Apr 22