BRIDGING THE GAP BETWEEN CONFUSION AND CLARITY IN HEALTHCARE

National Physician Advisor ConferenceNPAC2019

Readmissions: The Good, the Bad, and the Unclear

Daniel J. Brotman, MD, FACP, MHMProfessor of MedicineDirector, Hospitalist Program, Johns Hopkins HospitalBaltimore, MD

Thanks to…Amy DeutschendorfErik HoyerMelissa RichardsonDiane LepleyCurtis LeungScott Berkowitz

Jason MillerSumit BhatiaRos StewartHannah MillerDawn SaglianiNancy SullivanPatty BrownFred BrancatiKostas LyketsosSteve MandellPeter GreeneTony BoonyasaiGary Gerstenblith

Meghan DavlinLeigh EfirdModupe SavageCindy RutledgeMaggie NeelyCarol SylvesterMary MyersLinda DunbarMike WeisfeldtSteve SissonSanjay DesaiEric HowellJudy ReitzHunter Young

The rest of the J-CHiP team

Disclosures:

• CMMI (research funding): J-CHiP was supported by Funding Opportunity Number CMS-1C1-12-0001 from Centers for Medicare and Medicaid Services, Center for Medicare and Medicaid Innovation. Its contents are solely the responsibility of the authors and do not necessarily represent the official views of HHS or any of its agencies.

Personal Disclosures

I have watched all episodes of the original Star Trek series, most episodes > 4 times

Undergarment preference: Boxers

• Not briefs

Readmissions, circa 2009

Medicare data 2003-4

• Overall readmissions 19.6% at 30 days

• Estimated annual cost to Medicare $17.4B

Readmission risk factors

Variable Hazard Ratio (95% CI)

Hospital observed-to-expected (O/E) hospitalizations 1.10 (1.096-1.098)

National rehospitalization rate for DRG 1.27 (1.267-1.270)

Number hospitalizations in prior year0123+

1.001.38 (1.37-1.38)1.75 (1.75-1.76)2.50 (2.50-2.51)

Length-of-Stay>2 times DRG-expected LOS0.5-2 times DRG-expected LOS<0.5 times DRG-expected LOS

1.27 (1.26-1.27)1.00

0.87 (0.87-0.88)

Black race 1.06 (1.05-1.06)

End-stage renal disease 1.42 (1.41-1.43)

Readmission risk, Cont.

Variable Hazard Ratio (95% CI)

Age (years)<5555-6465-6970-7475-7980-8485-89>89

1.00.98 (0.98-0.99)1.00 (0.99–1.01)1.02 (1.01-1.04)1.07 (1.06-1.08)1.10 (1.09-1.11)1.12 (1.11-1.34)1.12 (1.11-1.13)

Male 1.06 (1.05-1.06)

On disability 1.13 (1.12-1.14)

On supplemental security income 1.12 (1.11-1.12)

Pubmed citations with “Readmission(s)” or “Rehospitalization(s)”, 1960 to 2018

0

1000

2000

3000

4000

5000

1960 1970 1980 1990 2000 2010 2020

CMS policy:Hospital Readmissions Reduction Program: Conditions

• FY 2012 inpatient prospective payment system final rule:

• Acute Myocardial Infarction

• Heart Failure

• Pneumonia

• Added in 2015

• Hip and Knee arthroplasty

• COPD

• Added in 2017

• CABG

All-cause readmissions:

• Publically reported but no penalties yet

IMPLICATION$• CMS identified hospitals whose readmission rates are

higher than expected (observed/expected significantly > 1.0)

• Penalties started in October, 2012• Increasing over time:

• 1% of Medicare payments in FY13

• 2% in FY14

• 3% in FY15 (and moving forward)

Measuring readmissions

• Raw readmission rate vs risk adjusted?• What do you adjust for?

• All-cause vs “potentially preventable”?

• Focused conditions vs “hospital-wide”?

• Intra-hospital vs all readmissions?

• Purpose of measurement (financial penalties at institution level vs local QI)?

“Expected Readmissions”” There’s an app for that!

National penalties for ALL-CAUSE readmissions?

• No financial penalties yet

• But DO show up in the CMS Star Report

A side note: What makes Maryland Different?

• “Waiver” state; fees controlled by HSCRC (state agency)

• 1977: Exempted from federal reimbursement rules provided that costs are kept lower than expected for the Maryland population.

• 4 other states originally had waivers, but dropped out

• To maintain waiver, Readmission rates need to go down to national rates

• HSCRC’s readmission strategy

• Hospital-Wide readmissions

• Risk adjusted for APRDRG-SOI

Using APRDRG-SOI allows for calculating EXPECTED readmissions on a PATIENT LEVEL for adjustment in CLINICAL CARE, Research, and QI

Actual JHH Readmission rate

Predicted readmission rate using historical APRDRG-SOI combinations

Higher complexity diagnosis / SOI

INTER-hospital readmissions?

• Do you know whether your patients were readmitted elsewhere if it is not a Medicare patient?

• Do good readmission reduction approaches create hospital brand loyalty?• Scheduled follow-up at your institution

• Grateful, impressed patients

• “Why would I go anywhere else?”

24

All-Cause UnadjustedReadmissions (Maryland Hospital A)

3/12/2019

12.0%

12.5%

13.0%

13.5%

14.0%

14.5%

15.0%

Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2

2012 2013 2014

Approximately 9% increase over 10 quarters

25

BUT… What about readmissions to other hospitals in Maryland?

3/12/2019

70%

72%

74%

76%

78%

80%

Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2

CY2012 CY2013 CY2014

Intra-hospital readmission proportion

Proportion of Intra Readmissions

Approximately 9% increase over same 10 quarters

26

Intra-hospital readmission proportion vs Readmission Rate

3/12/2019

69%

70%

71%

72%

73%

74%

75%

76%

77%

78%

10.0%

10.5%

11.0%

11.5%

12.0%

12.5%

13.0%

Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2

CY2012 CY2013 CY2014

Intra Readmission Rate Proportion of Intra Readmissions

27

Overall vs intra-hospital readmissions (Maryland Hospital A)

3/12/2019

Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2

2012 2013 2014

12.5%

13.0%

13.5%

14.0%

14.5%

15.0%

15.5%

16.0%

16.5%

30

-Day

Re

adm

issi

on

Rat

e

30-Day Intra-Readmission Rate 30-Day Overall Readmission Rate

Preventing Readmissions

• A paucity of high quality trials

• Conclusions: Isolated interventions may have small effects… Bundled interventions may realize an additive effect or additional value through organizational or culture changes.

JHHS Care Coordination “Bundle”

• ED care management

• Risk screening

• Patient and family education (disease specific)

• Interdisciplinary care planning (Multi-D rounds)

• Provider handoffs

• Medication management

• Patient/family support during the care transition (phone or in person)

Early risk screen

View of referring providers?

Outcomes for PAL and Transitions GuidesTransitions Guides:• N= eligible 5634 patients• Those who did not get converted for TG

services (N=2066) had a 77% increased odds of readmission compared to those who received TG services

Patient Access Line Intervention:• N=8969 eligible patients• Those who did not get connected

(N= 3650) had a 35% increased odds of readmission compared to those who did get connected

19.0%

30.8%

0.0%

5.0%

10.0%

15.0%

20.0%

25.0%

30.0%

35.0%

Convert No convert

TG Conversion Status and Readmission Rates

Controlled for: Age, Race, Sex,

Payer, Service, Co-morbidity, LOS,

HSCRC Expected Readmission Rate

Hoyer et al, JGIM (in press)

After Care Clinic (ACC)

9/14/2011 10/12/2011 21

ONYIKE,

CHIADIKAOBI

UCHENDU MEY6208615880 31209849 MEY6-625-B Geriatric (GER ) DEPRESSION/NOS

MEDICARE A

(MC11)

ROSENBLATT,

ADAM 208544817

208601039 10/24/2011 10/26/2011 7 HIROSE, KENZO WGC4

HEM4

208591701 53954524 WGA3-320-P

Oncology/Endocrino

logy Surgery (SOE )

155.1 -

CHOLANGIOCARCIN

OMA

MEDICARE A

(MC11)

SCHULICK,

RICHARD DAVID

GERBER,

JONATHAN

MICHAEL 208576272 10/12/2011 10/16/2011 17

BRODSKY,

ROBERT ALAN

GORE, STEVEN

DAVID HEM4

208608422 54350000

Ipop Oncology Bone

Marrow Transplant

(IPO )

CHEMO

ANTINEOPLASTIC

CHEMO(V5811)

MEDICARE A

(MC11)

MEDICARE A

(MC11)

GERBER,

JONATHAN

MICHAEL 208596395 10/19/2011 10/21/2011 12208608422 54350000

Ipop Oncology Bone

Marrow Transplant

(IPO )

CHEMO

ANTINEOPLASTIC

CHEMO(V5811)

10/20/2011 10/25/2011 8

SCHULMAN,

STEVEN P CCP5208615674 84394066 CCU5-017-I Cardiology (CRD )

AORTIC VALVE

STENOSIS

CAREFIRST

BLUE CR/SH

(BX19)

SCHULMAN,

STEVEN P 208589028

208544478 10/6/2011 10/27/2011 6

YANG, STEPHEN

CLYDE WGA4

WGD5

208616524 24861149 NEL6-673-P

Adult Surgery,

Thoracic (THO ) PNEUMOTHORAX

BLUE CR/SH

OUT-OF-

STATE (BXOS)

YANG, STEPHEN

CLYDE

ARMSTRONG,

DEBORAH 208599886 10/21/2011 10/25/2011 8

ANTONARAKIS,

EMMANUEL

STYLIAN

Previous

AttendingPhys

Previous

Location ERAdmit

208616201 83067611 WGB5-512-P

Medical Oncology

(MON ) HEART FAILURE

PRIORITY

PTNR

MCO/SPEC

(P17H)

Insurer

Readmit

AttendingPhys

Previous

Patcom

Previous

AdmDate

Previous

DisDate

DaysSinc

e LastDCPatcom Medrec

Loc-Room-

Bed AdmitServ AdmitComplaint

Daily Readmission Report“Please comment on the readmission in terms of preventability.” -Daniel J. Brotman, MD

Time for skepticism…

Big Step Back:Is readmission rate a valid quality measure?If so, what number is our target?

• Optimizing door to balloon time:

• 100% in <90 minutes

• Optimizing central line infections:

• 0%

• Optimizing readmissions:

• 0%? 10%? 15%?

Concerns about penalizing hospitals for readmissions

• Exacerbating disparities:• Penalizing under-resourced communities? Socioeconomic variables initially

excluded from CMS model.

• NEW CMS POLICY IN FY19: Adjustment for SES using dual eligible percent (5 groupings)

• If we do well keeping patients out of the hospital then the ones admitted are sicker (with higher readmission rates)

Hoyer et al, JGIM (in press)

• QI intervention: Education, handoffs, clinical pathways

• Outcomes:

• Increased readmissions (OR 1.65, 95% CI 1.1-2.5)

• Trend toward decreased mortality (OR 0.68, 95% CI 0.44-1.07)

• Intervention: Education, phone calls to patients, home health, provider education

• Results: Stopped early for safety reasons• No significant difference in readmissions

• More deaths in intervention group (Hazard Ratio 3.00 [CI, 1.46 to 6.17]; P = 0.003).

BASELINE REPORTING PLUS PENALITY

REPORTING ONLY

HOWEVER: hospitals that reduced their readmission rates tended to also improve their mortality rates very slightly (R2 = 0.004)

• Coding may have driven the “performance” changes

HRRP excludes critical access hospitals, rehab hospitals, psych hospitals, children’s hospitals, PPS-exempt cancer hospitals,...

HRRP excludes critical access hospitals, rehab hospitals, psych hospitals, children’s hospitals, PPS-exempt cancer hospitals,...

SUMMARY

The Good• Focusing on readmissions forces us to:

• Own care transitions and communicate better

• Educate patients and families

• Get into details on specific patients (eg, “frequent fliers”) to ask ourselves what we might be missing

• Invest in new programs that safely allow traditionally inpatient services (eg, blood transfusions) to be done in outpatient setting

The Bad• Not all care is safe in the outpatient setting (Sometimes

hospitals save lives.)

• Financial penalties may favor hospitals serving affluent communities with better primary care at the expense of those serving the poor (regressive taxation) – May improve with new CMS policies

• Perverse incentive to turn away more complicated patients

• System may be getting gamed

The Unclear: Financial incentives to reduce readmissions may be “sexy” now, but will they stand the test of time?

Never, ever think outside the box

www.acpadvisors.org

63

brotman@jhmi.edu

Readmissions: The Good, the Bad, and the Unclear

Thank you!