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Steven J. Korzeniewski, PhD-Candidate, MSc, MA, Director, Statistical Analysis Resource Group (SARG) & Chief Scientific Officer [email protected] Epidemiology of Readmissions Across the Lifespan & Evidence of Intervention Effectiveness

Steven J. Korzeniewski, PhD-Candidate, MSc, MA, Director, Statistical Analysis Resource Group (SARG) & Chief Scientific Officer [email protected]

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Page 1: Steven J. Korzeniewski, PhD-Candidate, MSc, MA, Director, Statistical Analysis Resource Group (SARG) & Chief Scientific Officer skorzeniewski@mpro.org

Steven J. Korzeniewski, PhD-Candidate, MSc, MA,Director, Statistical Analysis Resource Group (SARG) & Chief Scientific Officer

[email protected]

Epidemiology of Readmissions Across the Lifespan & Evidence of Intervention

Effectiveness

Page 2: Steven J. Korzeniewski, PhD-Candidate, MSc, MA, Director, Statistical Analysis Resource Group (SARG) & Chief Scientific Officer skorzeniewski@mpro.org

Overview:Objective: Describe the distribution of readmissions across the lifespan, focusing on Michigan data where possible

Outline:• Brief History of Readmissions (since 1960)• Readmissions Across the lifespan• Michigan Data

• ReWaRD Provisional Data• Medicare FFS

• Prevention Literature (controversies)• Encouraging Evidence of Intervention Impact• Preliminary findings of the MPRO Care Transitions Project

Please note that slides are intentionally ‘rich’ with text, oral presentation will emphasize key points.

Page 3: Steven J. Korzeniewski, PhD-Candidate, MSc, MA, Director, Statistical Analysis Resource Group (SARG) & Chief Scientific Officer skorzeniewski@mpro.org

Early Literature

• Early readmission literature focused almost universally on psychiatric patients.

• Studies published in the 1960s focused on: Family therapy in preventing readmissions, (Berman 1966)

Alternatives to mental patient rehospitalization (Miller, 1966)

Social process and readmission to mental hospital (Rapheal, 1966)

Marital status and interpersonal dynamics and readmission (Gynther, 1967)

Ex-mental patient readmissions (Maisel, 1967)

Correlates of psychiatric readmissions (Tuckman, 1967; Arthur 1968)

Page 4: Steven J. Korzeniewski, PhD-Candidate, MSc, MA, Director, Statistical Analysis Resource Group (SARG) & Chief Scientific Officer skorzeniewski@mpro.org

National AttentionReadmissions did not capture widespread national attention until the 1980s

• Zook and Moore reported:• hospitalizations accounted for nearly half of all healthcare expenses in the

United States

• estimated that 13% of inpatients used half of all hospital resources through repeated admissions. Zook CJ, Moore FD. High Cost Users of Medical Care. N Engl J Med. 1980;302:996-1002.

• Medicare moved from a FFS to a prospective payment system, based reimbursement on average lengths of stay given a patient’s diagnosis

• caused concern that financial incentive for earlier and perhaps premature discharges would increase readmission rates.

Page 5: Steven J. Korzeniewski, PhD-Candidate, MSc, MA, Director, Statistical Analysis Resource Group (SARG) & Chief Scientific Officer skorzeniewski@mpro.org

Seminal Study1984, Anderson and Steinberg published their seminal study of 270,266 randomly selected Medicare beneficiaries, revealed:

• 22% of Medicare hospitalizations from 1974-1977 were followed by a readmission within 60 days of discharge,

• Estimated annual cost to Medicare of $2.5 billion. [i] Anderson GF, Steinberg EP. Hospital Readmissions in the Medicare Population. N Engl J Med. 1984 Nov 22;311(21):1349-53.

Page 6: Steven J. Korzeniewski, PhD-Candidate, MSc, MA, Director, Statistical Analysis Resource Group (SARG) & Chief Scientific Officer skorzeniewski@mpro.org

MedPAC Follow-up measurement of the overall Medicare population rehospitalization rate did not occur until the 2007 and 2008 Medicare Payment Advisory Commission (MedPAC) reports

Noted that 17.6% of Medicare patients discharged from a hospital in 2005 were readmitted within 30 days. “Medicare Payment Advisory Commission. Payment Policy for Inpatient Readmissions,” from: Report to the Congress: Promoting Greater Efficiency in Medicare. Washington, DC; June 2007:103-120. Available at: www.medpac.gov/documents/Jun07_EntireReport.pdf.

Page 7: Steven J. Korzeniewski, PhD-Candidate, MSc, MA, Director, Statistical Analysis Resource Group (SARG) & Chief Scientific Officer skorzeniewski@mpro.org

Jencks et al. 2009• Medicare population 60-day readmission rate

increased by 40% compared to Anderson and Steinberg’s findings published 25 years prior. one of five (19.6%) Medicare beneficiaries

discharged from a hospital from 2003-2004 were rehospitalized within 30 days,

estimated annual unplanned rehospitalization cost of $17.4 billion for Medicare alone. Jencks SF, Williams MV, Coleman EA. Rehospitalizations Among Patients in the Medicare Fee-for-service Program. N Engl J Med. 2009;360:1418-1428.

Page 8: Steven J. Korzeniewski, PhD-Candidate, MSc, MA, Director, Statistical Analysis Resource Group (SARG) & Chief Scientific Officer skorzeniewski@mpro.org

Jencks et al. 2009Medicare rehospitalization rate was 45% greater in the five states with the highest rates than in the five states with the lowest rates.

Extreme variation is likely indicative of differences in healthcare quality and patient population characteristics across the US.

As noted by Jenck’s et al., further study is necessary to understand these differences and discern whether prevention strategies in low-risk settings are exportable to high-risk settings.

Figure: Rates of Rehospitalization within 30 Days of Hospital Discharge, Medicare Fee-For-Service Beneficiaries Discharged 10/1/2003-9/30/2004, United States

Page 9: Steven J. Korzeniewski, PhD-Candidate, MSc, MA, Director, Statistical Analysis Resource Group (SARG) & Chief Scientific Officer skorzeniewski@mpro.org

SNFs & Readmissions40% of Medicare beneficiaries are discharged from an acute care hospital stay to a post-acute care setting; of those, roughly half enter a nursing home for skilled nursing care or rehabilitation services. HCUPnet. 2009 [cited 2009 July 21]; Available from: http://hcupnet.ahrq.gov.

Mor et al. (2010) report that on average 23.5% of SNF residents are rehospitalized within 30 days of an acute care hospital discharge amounting to a total annual cost of $4.35 billion for Medicare alone based on analysis of CMS data from 2000-2006; their study further noted a 29% increase in rehospitalizations during this time period.

Michigan has the sixth greatest SNF resident readmission rate (25.8%) in the US, accounting for an estimated $175 million Medicare expenditure annually. Michigan also has the fifth greatest rate of prior nursing home use among rehospitalized residents.

Figure 1: Rehospitalization Rates in Total and by Prior Nursing Home Use among Medicare Beneficiaries, 2000-2006 (Mor, V., et al., The Revolving Door Of Rehospitalization From Skilled Nursing Facilities. Health Affairs, 2010. 29(1): p. 57-64)

Page 10: Steven J. Korzeniewski, PhD-Candidate, MSc, MA, Director, Statistical Analysis Resource Group (SARG) & Chief Scientific Officer skorzeniewski@mpro.org

Across the Lifespan:

• Readmissions are not isolated among the Medicare population, they are prevalent across the lifespan.

About 15% of preterm infants require at least one rehospitalization within the first year of life; average cost per readmission $8468, average annual cost in excess of $41 million. (Underwood et al.)

16.7% of the 186,856 pediatric patients discharged from 38 US children’s hospitals from 2003-2005 were readmitted within one year. (Feudtner et al.)

Page 11: Steven J. Korzeniewski, PhD-Candidate, MSc, MA, Director, Statistical Analysis Resource Group (SARG) & Chief Scientific Officer skorzeniewski@mpro.org

Pediatric PQI Conditions

Ages 0-18 Ages 19-64 Ages 65+0%

5%

10%

15%

20%

25%

30%

35%

40%

45%

22.4%

32.5%

40.1%

Figure 2: All-Cause Six Month Readmission Rate by Age Among Patients Residing in NY, PA, TN, or WI Admitted for a PQI Condition and Discharged January-June, 1999

• after admission for a PQI condition were rehospitalized within six months;• readmission rates increased linearly with age.

1 of 5 Pediatric Patients PQI Conditions Diabetes short-term complication admission ratePerforated appendix admission rateDiabetes long-term complication admission rateChronic obstructive pulmonary disease admission rateHypertension admission rateCongestive heart failure admission rateLow Birth WeightDehydration admission rateBacterial pneumonia admission rateUrinary tract infection admission rateAngina admission without procedureUncontrolled diabetes admission rate Adult asthma admission rateRate of lower-extremity amputation among patients with diabetes

Page 12: Steven J. Korzeniewski, PhD-Candidate, MSc, MA, Director, Statistical Analysis Resource Group (SARG) & Chief Scientific Officer skorzeniewski@mpro.org

Preventable Readmissions:

Goldfield et al. applied definition of ‘preventable readmissions’ to greater than four million admissions from 234 Florida hospitals from 2004-2005

-14.4% were followed by a potentially preventable readmission within 15 days.

-preventable readmission rates were linearly associated with age.

0-5 Years

6-18 Years

18-35 Years

36-55 Years

56-75 Years

76-85 Years

85+ Years

0%

2%

4%

6%

8%

10%

12%

Figure 3: All-Cause 15 Day Potentially Preventable Readmission Rate by Age Group, Florida Inpatient Hospital Data, 2005-2006

Readmissions are not only prevalent across the lifespan, many are preventable.

Page 13: Steven J. Korzeniewski, PhD-Candidate, MSc, MA, Director, Statistical Analysis Resource Group (SARG) & Chief Scientific Officer skorzeniewski@mpro.org

Michigan Data

Provisional Multi-Payer Data, 2008

Page 14: Steven J. Korzeniewski, PhD-Candidate, MSc, MA, Director, Statistical Analysis Resource Group (SARG) & Chief Scientific Officer skorzeniewski@mpro.org

Reporting Template:

14

30-Day All Cause Readmissions- Time Period: CY2008- PROVISIONAL DATA

Payers: HAP, Health Plus, Medicaid, Priority Health, Medicare, BCN, BCBSM

PRODUCT Line

See Data Definitions for Column Descriptions

a b c d e f g h I

AGE GROUP

Type of Index Admission

Discharges at Risk

RA to the Same Hospital RA to a Different Hospital RA to Any Hospital

    N N % N % N %

Commercial

AdultM 81,735 8,659 10.6% 2,844 3.5% 11,505 14.1%S 84,878 4,480 5.3% 1,123 1.3% 5,603 6.6%O 41,667 997 2.4% 174 0.4% 1,171 2.8%

PediatricM 11,260 774 6.9% 194 1.7% 968 8.6%S 3,537 181 5.1% 32 0.9% 213 6.0%O 547 20 3.7% 6 1.1% 26 4.8%

Post-neonatal M 3,173 196 6.2% 58 1.8% 254 8.0%S 878 52 5.9% 24 2.7% 76 8.7%

Neonatal M 24,935 286 1.1% 149 0.6% 435 1.7%S 386 26 6.7% 10 2.6% 36 9.3%

Total 252,996 15,671 6.2% 4,614 1.8% 20,287 8.0%

Medicaid FFS (managed care data not shown for presentation

purposes)

AdultM 64,017 5,234 8.2% 2,134 3.3% 7,368 11.5%S 18,513 1,013 5.5% 317 1.7% 1,330 7.2%O 31,200 940 3.0% 203 0.7% 1,143 3.7%

PediatricM 7,039 1,406 20.0% 104 1.5% 1,510 21.5%S 1,296 131 10.1% 13 1.0% 144 11.1%O 1,151 35 3.0% 13 1.1% 48 4.2%

Post-neonatal M 2,472 233 9.4% 86 3.5% 319 12.9%S 355 51 14.4% 11 3.1% 62 17.5%

Neonatal M 31,498 347 1.1% 403 1.3% 750 2.4%S 73 5 6.9% 5 6.9% 10 13.7%

Total 157,614 9,395 6.0% 3,289 2.1% 12,684 8.1%

Medicare (FFS)Adult M 280,012 45,250 16.2% 11,657 4.2% 56,907 20.3%

S 117,311 9,797 8.4% 2,712 2.3% 12,509 10.7%Total 398,836 55,419 13.90% 14,573 3.7% 69,992 18.0%

Total by Age Group Adult 737,544 78,696 10.7% 21,884 3.0% 100,583 13.6%Pediatric 26,378 2,591 9.8% 369 1.4% 2,960 11.2%Post-neonatal 7,365 553 7.5% 183 2.5% 736 10.0%Neonatal 58,481 702 1.2% 581 1.0% 1,283 2.2%

Grand Total 829,768 82,542 9.9% 23,017 2.8% 105,562 12.7%

Adult Medical Discharges

Pediatric Medical Discharges

Overall Rate

Page 15: Steven J. Korzeniewski, PhD-Candidate, MSc, MA, Director, Statistical Analysis Resource Group (SARG) & Chief Scientific Officer skorzeniewski@mpro.org

MI Medicare FFS,

Michigan Medicare FFS Patient 30-Day All Cause Readmission Rates (%) by County, 2010

CMS 7.2 Care Transitions Counties Readmission Rate=18%

Statewide Medicare FFS Patient Readmission Rate= ~19%

Readmission Rates are Greatest in Southeast Michigan

Medicare FFS Inpatient Data, ISAT Database, Not for General Distribution, Provisional Data

Page 16: Steven J. Korzeniewski, PhD-Candidate, MSc, MA, Director, Statistical Analysis Resource Group (SARG) & Chief Scientific Officer skorzeniewski@mpro.org

Mi Medicare FFS

F

M

>74

65-74

<65

Other

Black

White

Sex

Age

Rac

e

0 5 10 15 20 25 30

30-Day All-Cause Readmission Rate

30-Day All Cause Readmission Rate by Age, Race & Sex, Michigan Medicare (FFS) Beneficiaries Discharged from a Michigan hospital from January 1, 2008 through June 30, 2010

Page 17: Steven J. Korzeniewski, PhD-Candidate, MSc, MA, Director, Statistical Analysis Resource Group (SARG) & Chief Scientific Officer skorzeniewski@mpro.org

Mi Medicare FFS

Other

Mental Health (Secondary Dx)

COPD

PNE

AMI

CHF

Dia

gnos

is (

Dx)

0 5 10 15 20 25 30

30 Day All Cause Readmission Rate (%)

30-Day All Cause Readmission Rate by Selected Diagnoses, Michigan Medicare (FFS) Beneficiaries Discharged from a Michigan hospital from January 1, 2008 through June 30, 2010

Page 18: Steven J. Korzeniewski, PhD-Candidate, MSc, MA, Director, Statistical Analysis Resource Group (SARG) & Chief Scientific Officer skorzeniewski@mpro.org

Mi Medicare FFS

Rural

Urban

Urb

anic

ity o

f H

ospi

tal

0 5 10 15 20 25

30 Day All Cause Readmission Rate (%)

Urban vs. Rural Hospital 30-Day All Cause Readmission Rate, Michigan Medicare (FFS) Beneficiaries Discharged from a Michigan hospital from January 1, 2008 through June 30, 2010

Page 19: Steven J. Korzeniewski, PhD-Candidate, MSc, MA, Director, Statistical Analysis Resource Group (SARG) & Chief Scientific Officer skorzeniewski@mpro.org

Mi Medicare FFS

No Yes0

5

10

15

20

25

30

Physician Follow-up

30 D

ay a

ll C

ause

Rea

dm

issi

on

R

ate

(%)

30-Day All Cause Readmission Rate by Physician Follow-up Prior to Readmission or 30 days, Michigan Medicare (FFS) Beneficiaries Discharged from a Michigan hospital from January 1, 2008 through June 30, 2010

Adjusted for time to

readmission

Page 20: Steven J. Korzeniewski, PhD-Candidate, MSc, MA, Director, Statistical Analysis Resource Group (SARG) & Chief Scientific Officer skorzeniewski@mpro.org

Care Transitions Project: Descriptive Characteristics and Rate of 30-day All-Cause Readmission among Medicare FFS Beneficiaries Admitted to an Acute Care Hospital in Central Michigan, 1/1/08 - 3/31/10 (NOT FOR GENERAL DISTRIBUTION)

Population SegmentTotal Discharges Eligible for

ReadmissionReadmission Within 30-days

of Discharge

N % N %

RaceWhite* 25562 86.37 4634 18.13Black 3210 10.85 768 23.93Other 823 2.78 146 17.74

Age<65 6847 23.14 1633 23.8565-74 8397 28.37 1376 16.39>75* 14351 48.49 2539 17.69

SexM 13037 44.05 2563 19.66F* 16558 55.95 2985 18.03

Length of Stay< 4 days* 14399 48.65 2150 14.934 - 8 days 10922 36.90 2242 20.53> 8 days 4274 14.44 1156 27.05

Diagnosis

CHF 1477 4.99 385 26.07AMI 598 2.02 134 22.41PNE 1116 3.77 189 16.94COPD 1123 3.79 280 24.93OTHER* 25281 85.42 4560 18.04

Physician Follow-up within 30 days of discharge or prior to readmission

No 8526 28.81 2419 28.37

Yes* 21069 71.19 3129 14.85

Number of Admissions in 180 Days Prior to Index Admission

0* 17664 59.69 2249 12.731 6566 22.19 1433 21.822 2788 9.42 791 28.37≥ 3 2577 8.71 1075 41.72

Post Discharge Care

Self* 15055 50.87 2427 16.12HHA 6403 21.64 1320 20.62SNF 4003 13.53 956 23.88Other 4134 13.97 845 20.44

Total 29595   5548 18.75

Recent Admission history was by far the most significant predictor of readmission; adjusted HR 3.18 (CI: 2.94-3.44)

Patients having >3 admissions in the past 6 months accounted for 40% fewer admissions, yet 8% more readmissions than patients admitted for CHF, AMI, PNE or COPD

COMBINED…..

Page 21: Steven J. Korzeniewski, PhD-Candidate, MSc, MA, Director, Statistical Analysis Resource Group (SARG) & Chief Scientific Officer skorzeniewski@mpro.org

Care Transitions Project:

Baseline Qtr. 2 Qtr. 3 Qtr. 4 Qtr. 5 Qtr. 6 Qtr. 7 Qtr. 8 Qtr. 910

12

14

16

18

20

22

16.72

15.31

13.85

14.63

16.22

14.4

12.7813.33

13.65

20.11

18.6518.16

18.67

19.84

18.54

17.59

18.2318.66

30-Day All Cause Readmission Rate Denominated Per 1,000 El-igible Medicare FFS Beneficiaries and Separately to Eligible Discharges by Quarter , Michigan Care Transitions Project

Number per 1,000 Beneficiaries Linear (Number per 1,000 Beneficiaries)

Per Eligible Discharges (%) Linear (Per Eligible Discharges (%))30

-Da

y A

ll C

au

se

Re

ad

mis

sio

n R

ate

Declining number of admissions resulted in less improvement when rates were

denominated to eligible readmissions.

When denominated to eligible Medicare FFS beneficiaries, we observed an 18% RIR.

Page 22: Steven J. Korzeniewski, PhD-Candidate, MSc, MA, Director, Statistical Analysis Resource Group (SARG) & Chief Scientific Officer skorzeniewski@mpro.org

Care Transitions Project:

If the number of admissions declines at the same ‘pace’ as

readmissions, the rate denominated to discharges

appears constant.

Page 23: Steven J. Korzeniewski, PhD-Candidate, MSc, MA, Director, Statistical Analysis Resource Group (SARG) & Chief Scientific Officer skorzeniewski@mpro.org

Prevention Literature:

Debate continues about the degree of preventability; To date, there is no accepted case definition for ‘preventable’ readmission.

• Ashton and Wray’s systematic (1996) review draw attention to limitations of past studies concluding that it is impossible to say with confidence that early readmission is or is not a valid and useful quality indicator based on current evidence.

• Reported relationship is confounded by:• improper study design, • omission of important variables, and • mis-specification of variables.

• Ashton et al.’s meta-analysis (1997) and Benbassat and Taragin’s review (2000) report that approximately 9%-55% of readmissions are preventable.

• The latter study further noted that findings from prospective randomized trials suggest that 12%-75% of all readmissions can be prevented.

• More recently (2010), LaMantia et al.’s systematic review of interventions to improve transitional care between nursing homes and hospitals also reported that further research is necessary to better define target populations and outcome measures for high-quality transitional care.

Page 24: Steven J. Korzeniewski, PhD-Candidate, MSc, MA, Director, Statistical Analysis Resource Group (SARG) & Chief Scientific Officer skorzeniewski@mpro.org

Review:

• Readmissions have been studied for over fifty years; early studies focused on psychiatric patients

• Anderson and Steinberg’s seminal study and Medicare payment reform created widespread national attention readmissions during the 1980s.

• MedPAC & Jencks et al.’s studies reinvigorated attention towards readmissions.

• Much has yet to be learned about how to prevent readmissions based on past literature, although much encouraging evidence exists.

• The MPRO CT project findings suggest that patients with greater numbers of past admissions account for fewer admissions yet more readmissions than patients admitted for CHF, AMI, PNE or COPD COMBINED.

Page 25: Steven J. Korzeniewski, PhD-Candidate, MSc, MA, Director, Statistical Analysis Resource Group (SARG) & Chief Scientific Officer skorzeniewski@mpro.org

Acknowledgment:

This material was prepared by MPRO, the Medicare Quality Improvement Organization for Michigan, which is under contract with the Centers for Medicare & Medicaid Services (CMS), an agency of the U.S. Department of Health and Human Services.

The contents presented do not necessarily reflect CMS policy. 

9SOW-MI-7.2-11-117

Page 26: Steven J. Korzeniewski, PhD-Candidate, MSc, MA, Director, Statistical Analysis Resource Group (SARG) & Chief Scientific Officer skorzeniewski@mpro.org

CTI & INTERACT:

While past findings per intervention impact are heterogeneous overall, encouraging evidence exists.

• 2strategies stand out for having undergone significant evaluation over the past decade that resulted in encouraging evidence of impact on readmissions:

• Care Transitions Intervention (CTI sm)• CTI sm basically consists of cross-site communication tools, engagement of patients in their

care, and implementation of transition coaches; studies suggest that these strategies nearly halve the readmission rate, increase appropriate medication use and reduce healthcare costs among chronically ill and high-risk Medicare patients.(Coleman, Smith et al. 2004; Coleman, Parry et al. 2006; Parry, Min et al. 2009)

• INTERACT (Interventions to reduce Acute Care Transfers).• INTERACT is a set of strategies focused on communication across care settings, care

paths and advance care planning developed by CMS and the QIO for Georgia to reduce potentially avoidable acute care transfers from nursing homes. Ouslander et al.’s pilot study in three nursing homes characterized by high readmission rates reported a 50% reduction in the overall rate of potentially avoidable hospitalizations during a six month intervention period relative to baseline.(Ouslander, Perloe et al. 2009)

Page 27: Steven J. Korzeniewski, PhD-Candidate, MSc, MA, Director, Statistical Analysis Resource Group (SARG) & Chief Scientific Officer skorzeniewski@mpro.org

Care Transitions Project:

• In 2009, CMS initiated the Care Transitions Project to reduce community-wide rates of rehospitalizations among 14 selected communities, including one in central Michigan.

• Findings to date include:

• an 18.4% decrease in the number of 30-day all-cause readmissions per 1,000 eligible Medicare FFS beneficiaries residing in the target area weighted for days of observation in the 9th quarter relative to baseline.

• Regression analysis revealed a marginally significant reduction in the hazard of readmission by calendar year quarter during the study period (p=0.11), suggesting that the decline would not necessarily be expected by chance alone.

• While a strong association was observed between post discharge physician visit and readmission, 25% of patients lacking a claim for post discharge physician visit were readmitted within 3 days meaning many had little time to enact the visit.