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息2014 MFMER | slide-1
Preventing 30-day hospital
readmissions
A systematic review and meta-analysis of
randomized trials
Aaron Leppin, MD
Knowledge and Evaluation Research Unit, Mayo Clinic
Academy Health Annual Research Meeting
San Diego, CA; June 8, 2014
息2014 MFMER | slide-2
Disclosures and Funding
 none
息2014 MFMER | slide-3
Background
 Reducing readmissions requires better
understanding of causes
 Patient appraisal of need is key
 Depends on perception of resources
 Hospital is a source of capacity
 Recently discharged patients have low capacity
for self-care1
1Krumholz, N Engl J Med. 2013.
息2014 MFMER | slide-4
The Cumulative Complexity Model
Shippee, J Clin Epidemiol., 2012
息2014 MFMER | slide-5
Hypothesis
When burdensome and
insufficiently supported
demands are placed on
patients and caregivers
post-discharge, it will
overwhelm capacity and
lead to readmission
May, Montori, and Mair; BMJ. 2009.
息2014 MFMER | slide-6
Objectives
 To synthesize RCT evidence of discharge
interventions in reducing 30-day readmissions
 To explore the characteristics of these
interventions that are most associated with their
effectiveness
息2014 MFMER | slide-7
Methods
Data Sources and Study Selection
 Database search from 1990 to April 1, 2013
 Reviewed bibliographies, expert contacts
 Eligibility Criteria
 Randomized trials of any discharge
intervention
 Assessing risk of unplanned or all-cause
readmission within 30-days with or without
out of hospital deaths
 Patients admitted >24 hours for med/surg
diagnosis and discharged to home
息2014 MFMER | slide-8
Methods
Data Extraction and Synthesis
 Extracted patient, intervention, and outcome
characteristics
 Used activity-based coding strategy to de-
bundle interventions and confirmed with
authors
 Blinded raters evaluated net intervention
descriptions to judge impact on patient
workload and capacity
息2014 MFMER | slide-9
Methods
Activity-based Coding Strategy
 Discharge planning
 Case management
 Telephone follow-up
 Telemonitoring
 Patient education
 Self-management
 Medication intervention
 Home visits
 Follow-up scheduled
 Pt-centered discharge
instructions
 Provider continuity
 Timely follow-up
 PCP communication
 Patient hotline
 Rehab intervention
 Streamlining
 Making requisite
 Other
息2014 MFMER | slide-10
Methods
Identifying Net Interventions
CONTROLINTERVENTION
Discharge planning
Telephone follow-up
Discharge planning
Telephone follow-up
Patient education
NET INTERVENTION
Patient education
息2014 MFMER | slide-11
Methods
Intervention Capacity/Workload Ratings
IncreaseDecrease No Change
息2014 MFMER | slide-12
Methods
Data Analysis
 Random effects meta-analysis of relative risks
of readmission in 30-days
 Planned, exploratory subgroup analyses of
patient, intervention, and outcome
characteristics
 Post-hoc regression model assessing value of
comprehensive support in reducing 30-day
readmissions
息2014 MFMER | slide-13
Results
Trial identification and Meta-analysis
 47 randomized trials; 18 providing previously
unpublished data
 42 reported patient-level rates
 Pooled RR: 0.82 (95% CI 0.73 to 0.91)
 P<.001
 I2=31%
 5 reported event numbers only
 Pooled RR: 0.93 (95% CI 0.72 to 1.20)
 P=.59
 I2=23%
息2014 MFMER | slide-14
Results
Subgroup analyses
Intervention characteristics with significant
interactions for reducing 30 day readmission
rates
 Rated to increase patient capacity (P=.04)
 Delivered by two or more individuals (P=.05)
 Comprised five or more activities (P=.001)
 Study published prior to 2002 (P=.01)
息2014 MFMER | slide-15
Results
Meta-regression: Comprehensive support
 Variable scores from 0 to 4; 1 point each for:
 Rated to increase patient capacity
 Five or more meaningful patient interactions
 Two or more humans involved in delivery
 Five or more intervention activities
 Summed scores3 categories
 Category 1: 0 points
 Category 2: 1-2 points
 Category 3: 3-4 points
息2014 MFMER | slide-16
Results
Regression effects of comprehensive support
Study
Characteristic
Number of
Studies
RR of
Readmission
Compared to
Reference
95%
Confidence
Interval
p value
Category 1 15 1 (reference)
Category 2 20 0.82 0.66 to 1.02 0.07
Category 3 7 0.63 0.43 to 0.91 0.02
Publication in
2002 or after
33 1.47 1.10 to 1.96 0.01
息2014 MFMER | slide-17
Results
Category 3 Interventions:
consistent and complex strategy that
emphasized the assessment and addressing of
factors related to patient context and capacity for
self-care (including the impact of comorbidities,
functional status, caregiver capabilities,
socioeconomic factors, potential for self-
management, and patient and caregiver goals for
care). These interventions coordinated care
across the inpatient-to-outpatient transition and
involved multiple patient interactions; all but 1
involved patient home visits.
Leppin, JAMA Internal Medicine, 2014
息2014 MFMER | slide-18
Strengths/Limitations
 Largest and most homogenous collection of
randomized trial evidence
 Hypothesis-generating work
 Evidence of publication bias
 Workload and capacity ratings were global
assessments; no validated or criterion-based
scale
息2014 MFMER | slide-19
Conclusions and Implications
 A comprehensive and complex strategy that
fully supports patients post-discharge has
shown consistent value (many report cost
savings)
 Recent meta-analysis in heart failure is
complementary; stresses value of home visits1
 Many interventions currently being tested do not
follow this strategy and are less effective
1Feltner, Annals of Internal Medicine, 2014
息2014 MFMER | slide-20
Acknowledgements
 Michael R. Gionfriddo,
PharmD
 Maya Kessler, MD
 Juan Pablo Brito, MBBS
 Frances S. Mair, MD
 Katie Gallacher, MBChB
 Zhen Wang, Phd
 Patricia J. Erwin, MLS
 Tanya Sylvester, BS
 Kasey Boehmer, BS
 Henry H. Ting, MD, MBA
 M. Hassan Murad, MD
 Nathan D. Shippee, PhD
 Victor M. Montori, MD
息2014 MFMER | slide-21
Thank you for your attention!
Leppin.Aaron@mayo.edu
www.minimallydisruptivemedicine.org
Leppin AL, Gionfriddo MR, Kessler M, et al. Preventing 30-Day
Hospital Readmissions: A Systematic Review and Meta-analysis of
Randomized Trials. JAMA Intern Med. Published online May 12,
2014. doi:10.1001/jamainternmed.2014.1608.

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leppina

  • 1. 息2014 MFMER | slide-1 Preventing 30-day hospital readmissions A systematic review and meta-analysis of randomized trials Aaron Leppin, MD Knowledge and Evaluation Research Unit, Mayo Clinic Academy Health Annual Research Meeting San Diego, CA; June 8, 2014
  • 2. 息2014 MFMER | slide-2 Disclosures and Funding none
  • 3. 息2014 MFMER | slide-3 Background Reducing readmissions requires better understanding of causes Patient appraisal of need is key Depends on perception of resources Hospital is a source of capacity Recently discharged patients have low capacity for self-care1 1Krumholz, N Engl J Med. 2013.
  • 4. 息2014 MFMER | slide-4 The Cumulative Complexity Model Shippee, J Clin Epidemiol., 2012
  • 5. 息2014 MFMER | slide-5 Hypothesis When burdensome and insufficiently supported demands are placed on patients and caregivers post-discharge, it will overwhelm capacity and lead to readmission May, Montori, and Mair; BMJ. 2009.
  • 6. 息2014 MFMER | slide-6 Objectives To synthesize RCT evidence of discharge interventions in reducing 30-day readmissions To explore the characteristics of these interventions that are most associated with their effectiveness
  • 7. 息2014 MFMER | slide-7 Methods Data Sources and Study Selection Database search from 1990 to April 1, 2013 Reviewed bibliographies, expert contacts Eligibility Criteria Randomized trials of any discharge intervention Assessing risk of unplanned or all-cause readmission within 30-days with or without out of hospital deaths Patients admitted >24 hours for med/surg diagnosis and discharged to home
  • 8. 息2014 MFMER | slide-8 Methods Data Extraction and Synthesis Extracted patient, intervention, and outcome characteristics Used activity-based coding strategy to de- bundle interventions and confirmed with authors Blinded raters evaluated net intervention descriptions to judge impact on patient workload and capacity
  • 9. 息2014 MFMER | slide-9 Methods Activity-based Coding Strategy Discharge planning Case management Telephone follow-up Telemonitoring Patient education Self-management Medication intervention Home visits Follow-up scheduled Pt-centered discharge instructions Provider continuity Timely follow-up PCP communication Patient hotline Rehab intervention Streamlining Making requisite Other
  • 10. 息2014 MFMER | slide-10 Methods Identifying Net Interventions CONTROLINTERVENTION Discharge planning Telephone follow-up Discharge planning Telephone follow-up Patient education NET INTERVENTION Patient education
  • 11. 息2014 MFMER | slide-11 Methods Intervention Capacity/Workload Ratings IncreaseDecrease No Change
  • 12. 息2014 MFMER | slide-12 Methods Data Analysis Random effects meta-analysis of relative risks of readmission in 30-days Planned, exploratory subgroup analyses of patient, intervention, and outcome characteristics Post-hoc regression model assessing value of comprehensive support in reducing 30-day readmissions
  • 13. 息2014 MFMER | slide-13 Results Trial identification and Meta-analysis 47 randomized trials; 18 providing previously unpublished data 42 reported patient-level rates Pooled RR: 0.82 (95% CI 0.73 to 0.91) P<.001 I2=31% 5 reported event numbers only Pooled RR: 0.93 (95% CI 0.72 to 1.20) P=.59 I2=23%
  • 14. 息2014 MFMER | slide-14 Results Subgroup analyses Intervention characteristics with significant interactions for reducing 30 day readmission rates Rated to increase patient capacity (P=.04) Delivered by two or more individuals (P=.05) Comprised five or more activities (P=.001) Study published prior to 2002 (P=.01)
  • 15. 息2014 MFMER | slide-15 Results Meta-regression: Comprehensive support Variable scores from 0 to 4; 1 point each for: Rated to increase patient capacity Five or more meaningful patient interactions Two or more humans involved in delivery Five or more intervention activities Summed scores3 categories Category 1: 0 points Category 2: 1-2 points Category 3: 3-4 points
  • 16. 息2014 MFMER | slide-16 Results Regression effects of comprehensive support Study Characteristic Number of Studies RR of Readmission Compared to Reference 95% Confidence Interval p value Category 1 15 1 (reference) Category 2 20 0.82 0.66 to 1.02 0.07 Category 3 7 0.63 0.43 to 0.91 0.02 Publication in 2002 or after 33 1.47 1.10 to 1.96 0.01
  • 17. 息2014 MFMER | slide-17 Results Category 3 Interventions: consistent and complex strategy that emphasized the assessment and addressing of factors related to patient context and capacity for self-care (including the impact of comorbidities, functional status, caregiver capabilities, socioeconomic factors, potential for self- management, and patient and caregiver goals for care). These interventions coordinated care across the inpatient-to-outpatient transition and involved multiple patient interactions; all but 1 involved patient home visits. Leppin, JAMA Internal Medicine, 2014
  • 18. 息2014 MFMER | slide-18 Strengths/Limitations Largest and most homogenous collection of randomized trial evidence Hypothesis-generating work Evidence of publication bias Workload and capacity ratings were global assessments; no validated or criterion-based scale
  • 19. 息2014 MFMER | slide-19 Conclusions and Implications A comprehensive and complex strategy that fully supports patients post-discharge has shown consistent value (many report cost savings) Recent meta-analysis in heart failure is complementary; stresses value of home visits1 Many interventions currently being tested do not follow this strategy and are less effective 1Feltner, Annals of Internal Medicine, 2014
  • 20. 息2014 MFMER | slide-20 Acknowledgements Michael R. Gionfriddo, PharmD Maya Kessler, MD Juan Pablo Brito, MBBS Frances S. Mair, MD Katie Gallacher, MBChB Zhen Wang, Phd Patricia J. Erwin, MLS Tanya Sylvester, BS Kasey Boehmer, BS Henry H. Ting, MD, MBA M. Hassan Murad, MD Nathan D. Shippee, PhD Victor M. Montori, MD
  • 21. 息2014 MFMER | slide-21 Thank you for your attention! Leppin.Aaron@mayo.edu www.minimallydisruptivemedicine.org Leppin AL, Gionfriddo MR, Kessler M, et al. Preventing 30-Day Hospital Readmissions: A Systematic Review and Meta-analysis of Randomized Trials. JAMA Intern Med. Published online May 12, 2014. doi:10.1001/jamainternmed.2014.1608.

Editor's Notes

  • #4: Other relevant models are Lazarus transactional model of stress
  • #16: I call this the touch variable