Reducing Rehospitalization: Policy, Ecology and Culture
Luke Hansen, MD MHSAssistant Professor, Northwestern University
Feinberg School of Medicine, SSOM ‘03
National Health Expenditures per Capita, 1960-2010
Notes: According to CMS, population is the U.S. Bureau of the Census resident-based population, less armed forces overseas.
Source: Centers for Medicare and Medicaid Services, Office of the Actuary, National Health Statistics Group, at http://www.cms.hhs.gov/NationalHealthExpendData/ (see Historical; NHE summary including share of GDP, CY 1960-2010; file nhegdp10.zip).
5.2% 7.2% 9.2% 12.5% 13.8% 14.5% 15.4% 15.9% 16.0% 16.1% 16.2% 16.4% 16.8% 17.9% 17.9%
NHE as a Share of GDP
Cumulative Percent Change in National Health Expenditures, by Selected Sources of Funds, 2000-2010
Notes: This figure omits national health spending that belongs in the categories of Other Public Insurance Programs, Other Third Party Payers and Programs, Public Health Activity, and Investment, which together represent about 20% of total national health spending in 2010. Medicare and Medicaid were enacted in 1965; by January 1970, all states but two were participating in Medicaid.
Source: Kaiser Family Foundation calculations using NHE data from Centers for Medicare and Medicaid Services, Office of the Actuary, National Health Statistics Group, at http://www.cms.hhs.gov/NationalHealthExpendData/ (see Historical; National Health Expenditures by type of service and source of funds, CY 1960-2010; file nhe2010.zip).
Distribution of National Health Expenditures, by Type of Service (in Billions), 2010
Note: Other Personal Health Care includes, for example, dental and other professional health services, durable medical equipment, etc. Other Health Spending includes, for example, administration and net cost of private health insurance, public health activity, research, and structures and equipment, etc.
Source: Kaiser Family Foundation calculations using NHE data from Centers for Medicare and Medicaid Services, Office of the Actuary, National Health Statistics Group, at http://www.cms.hhs.gov/NationalHealthExpendData/ (see Historical; National Health Expenditures by type of service and source of funds, CY 1960-2010; file nhe2010.zip).
NHE Total Expenditures: $2,593.6 billion
Nursing Care Facilities & Continuing Care Retirement
Communities, $143.1 (5.5%)
•19% rehospitalized in 30 days•$17.4 billion annually
MedPAC and the federal response to high rates of readmission
• MedPAC estimates annual cost of all avoidable readmission $12 Billion
• June 2007: Recommends public reporting of risk‐adjusted readmission
• Summer 2009: Public reporting of readmission outcomes goes live
• www.hospitalcompare.hhs.gov
“Beginning 2013, [Affordable Care Act(ACA)] imposes penalties on hospitals for so‐called ‘excess’ readmissions based on ‘expected’ 30‐day readmission rates for heart attack, heart failure, and pneumonia”
Starts in FY ’13 based on FY ’12 (starts Oct ’11). Payments for all Medicare patients will be reduced by up to 1% and increase to 3% by 2015, at which time COPD, CABG, PCI and others will be added.
PPACA, 2010, Section 3025
What can be done to reduce readmission rates?
• Why do readmissions occur?• What are patient risk factors for readmission?• What has been tested to reduce readmission?
Why do readmissions occur?
Healthcare Quality
Medical Co-morbidity
Incidence of post‐discharge adverse events
• 19% of patients had a post discharge AE• ⅓ preventable and ⅓ ameliorable
Ann Intern Med 2003; Vol. 138
• ¼ of discharged patients require additional outpatient work‐ups
• > ⅓ of these are not completed• Increased time to post‐discharge f/u associated with lack of work‐up completion
• Availability of discharge summary increased likelihood of work‐up being done
Arch Intern Med. 2007;167:1305‐1311
Loose ends at discharge
“quicker and sicker”?
• 6,955,461 Medicare FFS hospitalizations for HF between 1993 and 2006, with 30‐day f/u.
• LOS 8.8 days down to 6.3 days• In‐hospital mortality from 8.5% to 4.3%• 30‐day mortality from 12.8% to 10.7%• Discharges to SNF increased from 13% to 20%• 30 day readmission increased from 17.2% to 20.1%
What can be done to reduce readmission rates?
• Why do readmissions occur?• What are patient risk factors for readmission?
• What has been tested to reduce readmission?
Home
Recovery
Rehospitalization
Risks of Readmission
Repeated admitsMedical co‐morbidityDepressionMaleInsuranceAge
RaceSelf perceived QOLMarriedRegular physicianPolypharmacy
Three approaches to risk assessment:• Calculated, Externally developed • Calculated, Internally developed• Not Calculated
Two approaches to targeting:• Proactive• Reactive
A statistical prelude:Discriminative Strength
The ROC curve and the C Statistic
Kansagara, D., H. Englander, et al. (2011). "Risk Prediction Models for Hospital Readmission." JAMA: The Journal of the American Medical Association 306(15): 1688-1698.
• 7843 articles reviewed• 30 studies included in the review
• 7 models could be used to risk stratify on admission
• C statistic 0.56-0.72
“Variables independently associated with [readmission and death] (from which we derived the mnemonic “LACE”) included length of stay (“L”); acuity of the admission (“A”); comorbidity of the patient (measured with the Charlson comorbidity index score) (“C”); and emergency department use (measured as the number of visits in the six months before admission) (“E”).
“The LACE index was discriminative (C statistic 0.684)”
Three approaches to risk assessment:• Calculated, Externally developed • Calculated, Internally developed• Not Calculated
Two approaches to targeting:• Proactive• Reactive
Development of a single hospital empiric readmission risk prediction model
ID Risks Develop scores Measure characteristics
Variable OR# admissions in previous year 1.32Male Sex 1.11Subjective weight loss 1.04# Chronic Conditions 1.03Age 0.93African American Race 0.92
• Initial model also considered marital status, insurance status• C statistic 0.68
ID Risks Develop scores Measure characteristics
Risk Factor Categories PointsAge
<20 -320-29 030-39 040-49 050-59 060-69 -170-79 -180-89 -1≥90 -1
SexMale 0Female 1
Non Black RaceBlack 0Non Black 1
Risk Factor Categories PointsAdmissions, past year
0 01 32 53 84 11≥5 19
Subjective Wt LossNo 0Yes 3
Comorbidity Count0 to 2 03 to 6 27 to 9 4>9 6
Development of a single hospital empiric readmission risk prediction model
ID Risks Develop scores Clinical Application
Readmitted? Risk Score<4 5-9 10-14 15-18 >19 Total
No 86.01% 78.44% 71.07% 64.56% 52.94% 76.32%
Yes 13.99% 21.56% 28.93% 35.44% 47.06% 23.68%
Development of a single hospital empiric readmission risk prediction model
Three approaches to risk assessment:• Calculated, Externally developed • Calculated, Internally developed• Not Calculated
Two approaches to targeting:• Proactive• Reactive
• Methods– aged ≥65, 550-bed tertiary care
academic medical center. – Staff estimated the chance of
unscheduled readmission within 30 days
• Results (as AUC) – 0.50 for case managers– 0.55 for RNs– 0.59 for interns– 0.58 for attendings– 0.56 for calculated index
JGIM 2011
The “8P” Risk Assessment
• Problem medications (insulin, warfarin, narcotics [see Budnitz NEJM 2011])
• Psychological Comorbidity
• Principal dx (CA, DM, COPD, CHF, CVA)
• Polypharmacy
• Poor health literacy
• Patient support lacking
• Prior hospitalizations
• Palliative care
Assumption 1: All Measurable Risk is Meaningful
“On logistic regression, a decreasing temperature was significantly associated with rehospitalization within 180 days (odds ratio, 4.01; 95% confidence interval, 1.63‐10.02; P < .003).”
Assumption 2:The ecology of rehospitalization
Community
Hospital
Family
patient
Assumption 2:The ecology of rehospitalization
Healthcare Quality
Medical Co-morbidity
Assumption 2:The ecology of rehospitalization
Hospital Quality
Physician Quality
Medical Co-morbidity
Assumption 2:The ecology of rehospitalization
Hospital Quality
Physician Quality
Medical Co-morbiditySocial Support
NeighborhoodEnvironment
Assumption 2:The ecology of rehospitalization
Arbaje, A., Wolff, J., Yu, Q., Powe, N., Anderson, G., & Boult, C. (2008). Postdischarge environmental and socioeconomic factors and the likelihood of early hospital readmission among community-dwelling Medicare beneficiaries. The Gerontologist, 48(4), 495.
Model 1 includes age aloneModel 2 includes model 1 plus patient comorbiditiesModel 3 includes model 2 plus discharge dispositionModel 4 includes model 3 plus hospital characteristics (size,
membership in a system, teaching status, ownership, location, region)
Model 5 includes model 4 plus percent Medicaid at each hospital and each hospital’s Disproportionate Share Index
Joynt, K. et al, JAMA, 2011
Assumption 2:The ecology of rehospitalization
What is the effect of “risk-adjustment” that does not account for all determinants of readmission?
The DC PROMIS Study
Prospective survey of hospitalized, non‐demented elders being discharged to home regarding self‐reported function in diverse domains:
– Physical function– Cognitive function– Emotional function– Social function
Not Readmitted (n=50)
Readmitted (n=18)
P value*
LACE Score 6.96 (±2.94) 8.00 (±2.32) 0.2901Social and functional variables, prior to discharge, mean T score (SD)
Physical function 39.99 (±10.10)
31.75 (±8.17) 0.0028
Applied cognitive ability 48.06 (±7.14)
45.91 (±6.17) 0.2622
Depressive symptoms 51.10 (±8.49)
52.03 (±4.75) 0.5765
Ability to access social support 49.44 (±10.12)
40.25 (±8.53) 0.0014
Social isolation 44.04 (±8.59)
49.05 (±5.97) 0.0301
*significance calculated using t-test for continuous variables and Fisher’s exact test for categorical variables
Assumption 3: Reduced Rehospitalization is improved health
Feng et al, Health Affairs 2012
Assumption 3: Reduced Rehospitalization is improved health
Krumholz, H. M., et al (2013). Relationship Between Hospital Readmission and Mortality Rates for Patients Hospitalized With Acute Myocardial Infarction, Heart Failure, or Pneumonia Hospital Performance and Readmission/Mortality Rates. JAMA, 309(6), 587‐593.
Quality
Assumption 3: Reduced Rehospitalization is improved health
Cost
(Quality)(Access)↑Value =
Assumption 3: Reduced Rehospitalization is improved value?
What can be done to reduce readmission rates?
• Why do readmissions occur?• What are the risk factors for readmission?• What has been tested to reduce readmission?
• Literature between 1970 and January 2011• 4013 articles identified• Full text of 386 studies or reviews examined by
four physician team• 43 studies were included in final review which
reported a 30 day readmission outcome and interventions were not disease specific
Effectiveness Characteristic #1: Multifaceted intervention
Pre-Discharge Intervention
Post-DischargeIntervention
Patient educationPCP communicationDischarge planning
Medication reconciliation
Home visitFollow-up phone call
Patient hotlineEarly follow-up
Intervention Bridging the TransitionTransition coach
Patient-centered discharge instructionsIntegration of inpatient and outpatient care
Effectiveness Characteristic #2:Bridging Interventions
Facets PopulationSetting (nation)
Study design Control n
Intervention N
Absolute risk reduction (%)
Jack BW, et al. Project RED 6 wards USA RCT 368 370 6.0 (S)
Naylor M, et al. Transitional Care Intervention
5
≥65 yocardiac
medical and surgical DRG
USA RCT 70 72 12 (NS at 2 weeks)
Coleman EA et al.Care Transitions Intervention
4 ≥65 yo USA RCT 371 379 3.6 (S)
Interventions including a “bridging” component were significantly associated with a finding of statistically significant benefit.
The PASS: A Patient-centered discharge instruction
• Simple• Problem focused• Appropriate literacy• Robust Medication
Reconciliation– New meds– Stopped meds– Changed meds
NEW CONCEPT: Health information, advice,
instructions, or change in management
Explain new concept / Demonstrate new skill
Patient recalls and comprehends / Demonstrates
skill mastery
Assess patient comprehension / Ask patient to demonstrate
Clarify and tailor explanation
Re‐assess recall and comprehension /Ask
patient to demonstrate
The Teach Back Method
Modified from Schillinger, D. et al. Arch Intern Med 2003;163:83‐90
Effectiveness analysis of sites participating in Project BOOST
• Readmission outcomes presented from 11 of 30 pilot sites
• Average rate of 30-day rehospitalization in BOOST units was 14.7% prior to implementation and 12.7% 12 months later (P=0.010)
• Absolute reduction of 2% • Relative reduction of 13.6%
Implementation Caveat 1: Will it play in Peoria?
Boston Medical Center
Proctor Medical Center
Location Boston, MA (pop 645,169)
Peoria, IL (pop 115,007)
Licensed beds 639 299
Medicare FFS HF admissions (7/1/06 to 6/30/09)
488 379
Teaching Hospital Yes No
Active NIH-funding FY 2010
$46,187,521 $0
Implementation Caveat 2: Context is critical
Ideas and products and messages and behaviors spread just like viruses do.
--Malcolm Gladwell, The Tipping Point
Project BOOST units in Pilot Cohort
5%
10%
15%
20%
Pre‐Implementation 1y Post‐Implementation
Readmission Ra
te
Project BOOST units in Pilot Cohort
5%
10%
15%
20%
Pre‐Implementation 1y Post‐Implementation
Readmission Ra
te
Contextual elements of the organization
Strategic environment• What are the organization’s strategic goals?• What is the organization’s financial status?• What is the competition doing?• How is the hospital perceived locally?
Organizational culture• Senior leadership engagement• How has change occurred previously in the organization?• What is the organization’s safety culture?
What is culture?
• An academic definition:“The integrated pattern of human knowledge, belief, and behavior that depends upon the capacity for learning and transmitting knowledge to succeeding generations.”
• An easy definition: “It’s how we do things here.”
What is Safety Culture?“The accident can be said to have
flowed from deficient safety culture, not only at the Chernobyl plant, but throughout the Soviet design, operating and regulatory organizations for nuclear power that existed at the time.”
‐‐International Atomic Energy Agency (IAEA)
What is Safety Culture?“BP has harnessed impressive scientific and technological experience…and you have to wonder why they hadn't harnessed similar science and technology to anticipate failure, to install redundancy to prevent failure…[they] cast doubt on whether the company has the commitment to the practice and the culture of safety necessary to protect the public.”Rep. James L. Oberstar (D‐Minn.), chairman of the House Transportation and Infrastructure Committee
0
5
10
15
20
25
% Problem
atic Respo
nse
(mean of 16 ite
ms)
VA hospitals (shaded) US hospitals (unshaded) and Naval aviation average (line)
Room for Improvement?
One US hospital from a sample of 97 performed better than the naval aviation average
Singer, et al. Health Mgmt Review 2010
Association between readmission and safety climate
AMI HF
Org
.
Senior Management Engagement 0.0804* 0.0744Organizational Resources 0.0642 0.0705Overall Emphasis on Safety 0.0968** 0.1130**Problem Responsiveness 0.0853* 0.0903
Clin
. uni
t
Unit Safety Norms 0.1860** 0.2590**Unit Recognition and Support 0.0345 0.0599Unit Manager Support 0.0506 0.0344Collective Learning 0.1160* 0.1600**Psychological Safety 0.0644 0.0602
Indi
v. Fear of Shame 0.0126 -0.0827Fear of Blame 0.0510 0.1060**Provision of Safe Care -0.0138 0.0067Summary Measure 0.1230* 0.1600*
**p<0.01, *p<.05, Regression models include region, hospital tax status, nurse staffing ratios
Take home points
• Communication at discharge, particularly regarding medications, is important
• Effectiveness is not efficacy• Frontline safety culture is a necessary although insufficient component of a high performing healthcare system
James Cassidy SSOM ‘48
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