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Winning at Care Coordination Using Data-Driven Partnerships
Session #166, February 22, 2017
Steven Littlehale, MS, GCNS-BC
EVP & Chief Clinical Officer
Idriz Limaj, LNHA, RN
Chief Operating Officer
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Speaker Introduction
Idriz Limaj, LNHA, RN
Chief Operating Officer
LifeBridge Health
Steven Littlehale, MS, GCNS-BC
EVP & Chief Clinical Officer
PointRight Inc.
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Conflict of Interest
Idriz Limaj, LNHA, RN
Has no real or apparent conflicts of interest to report.
Steven Littlehale, MS, GCNS-BC
Has no real or apparent conflicts of interest to report.
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Agenda
• What’s going on in the post-acute world?
• What data is available from post-acute care?
• What are the steps for building and managing a high-performing post-acute provider network?
• How can predictive analytics play a role in managing the network?
• How can this advance population health management?
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Learning Objectives
• Recognize the depth and breadth of available LTPAC data and what it can do for you – public domain data, MDS data, OASIS
• Evaluate the critical components of a data-driven strategy for building and managing a ‘smart’ network of LTPAC providers
• Discuss how predictive analytics can directly impact care coordination, reduce readmissions and optimize placements
• Develop the necessary steps for integrating LTPAC data into population health management programs
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STEPS™ to ValueAn introduction to the benefits realized for the value of Health IT
• The value STEPS™ impacted were:
– Treatment/Clinical
– Patient Engagement & Population Management
– Savings
• Improved the Hospital discharge and admission process
• Improved the Nursing Home to Hospital transfer process
• Reduced overall risk-adjusted rehospitalization rate by 1.06 percentage points
• Improved LifeBridge Quality Score by 6.81%
• Improved overall Five-Star by 4.45%
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What’s Going On in the Post-Acute World? The journey to value-based care
HVBP NewMeasures
SNFVBP
NewMeasures
NewData
HHVBP
NewMeasures
NewData
IMPACT Act
NewMeasures
NewData
Five-Star
NewMeasures
NewData
AffordableCare Act
NewData
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There is an Alignment…
HRRP
NewMeasures
SNFVBP
NewMeasures
NewData
HHVBP
NewMeasures
NewData
IMPACT Act
NewMeasures
NewData
Five-Star
NewMeasures New
Data
NewData
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HHS Payment ReformHHS announced targets to increase the number of payments that are linked to quality outcomes by 2018.
We are setting clear goals – and establishing a clear timeline – for moving from volume to valuein Medicare payments.
“Our first goal is for 30% of all Medicare provider payments to be in alternative payment models that are tied to how well providers care for their patients, instead of how much care they provide – and to do it by 2016.Our goal would then be to get to 50% by 2018.”
Our second goal is for virtually all Medicare fee-for-service payments to be tied to quality and value; at least 85% in 2016 and 90% in 2018.- HHS Secretary BurwellJan. 26, 2015
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Focus on Quality
Payment is now aligning with quality.
The Administration has set measurable goals and a
timeline to move the Medicare program, and the
health care system at large, toward paying
providers based on the quality, rather than the
quantity of care they give patients. The final rule
includes policies that advance that vision and
support building a health care system that delivers
better care, spends health care dollars more wisely
and results in healthier people.
CMS 8/3/2015
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Understanding post-acute data
And knowing what it can do for you
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Available Data: Home Health Agencies (HHAs)
• The Outcome and Assessment Information Set (OASIS)
– Home health quality measures (both outcome and process measures)
• Medicare claims
– Medicare claims data is used to calculate certain utilization-based home health quality measures.
• The patient experience of care survey uses the Home Health Consumer Assessment of Healthcare Providers and Systems (HHCAHPS) instrument.
• Medicare.gov/HomeHealthCompare
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Available Data: Skilled Nursing Facilities (SNFs)
• CMS’s health inspection database
– Nursing home characteristics and health deficiencies issued and data about staffing and penalties
• The Minimum Data Set (MDS)
– Clinical data for quality measures come from the MDS Repository
• Medicare claims
– Medicare claims data is used to calculate certain utilization-based home health quality measures
• Medicare.gov/NursingHomeCompare
• Many states have unique data sets/report cards
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Available Data: Metrics in the Future
• IMPACT Act – QRP Measures and C-CDA files
– Long-Term Care Hospitals (LTCHs): LTCH Care Data Set (LCDS)
– Skilled Nursing Facilities (SNFs): Minimum Data Set (MDS)
– Home Health Agencies (HHAs): OASIS
– Inpatient Rehabilitation Facilities (IRFs): IRF-Patient Assessment Instrument (IRF-PAI)
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The critical components of a data-driven strategyBuilding and managing ‘Smart’ LTPAC provider networks
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Building a Narrow vs. “Smart Network”
NARROW NETWORKS• Efficient
• Geared toward the stakeholderSMART NETWORKS• Customized to fit patients’ needs
• High Performance/Data-driven
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Three Keys to Success
StandardizedTransparent
Operational
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LifeBridge Health OverviewLeading provider of hospital services in northwestern Baltimore and all of Carroll County, Maryland
• $1.8B health system
• 4 hospitals
• 249 nursing home beds (1 free-standing, 1 TCU)
• ~550 employed physicians │~2,000 employed nurses
• 100+ locations
• 22 urgent care sites
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SNF Collaborative – A Preferred Network
The SNF Collaborative was developed to:
• Create a network that is focused on quality and patient experience
• Enhance patient outcomes while reducing the cost of care
• Standardize and share best practices across systems
• Enhance problem-solving and collective navigation within today’s healthcare landscape
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Continuum of Care
PRIMARY
CARE,
PREVENTION,
WELLNESS
AMBULATORY
CARE
ACUTE CARE,
TERTIARY CAREPOST-ACUTE
CARE
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Ongoing Performance MonitoringMetrics
• Quality
• Rehospitalization
• Patient and family satisfaction
Goals
Improve scores by 10% annually if below state average
Improve scores by 20% annually if above state average
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The Collaborative Dashboard
Transparency. Standardization. Operational.
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™
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Pro30™ Rehospitalization for Collaborative
18.6%
19.0% 19.1%
18.6% 18.7%18.3% 18.2% 18.2%
17.5%17.1% 17.3%
17.1%18.1%
18.5% 18.5%
18.1% 18.2%
17.8% 17.8% 17.8%
17.0%16.8% 17.0%
16.8%
15%
16%
17%
18%
19%
20%
Sep-15 Oct-15 Nov-15 Dec-15 Jan-16 Feb-16 Mar-16 Apr-16 May-16 Jun-16 Jul-16 Aug-16
Observed Adjusted
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SNF Outcomes to DateTransparency and data exchange drive change:
– Improved the Hospital discharge and admission process
– Improved the Nursing Home to Hospital transfer process
– Reduced overall adjusted rehospitalization rate by 1.06 percentage points
– Improved quality metrics by 6.81%
– Improved overall Five-Star by 4.45%
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Next Steps for the SNF Collaborative
• Leverage a ‘Smart’ network for discharge planning Discharge patients to the right setting based on outcomes
• Standardized clinical pathways based on best practices CHF, UTI, COPD, Pneumonia, Diabetes
• Reduce costs Monitor length of stay and quality outcomes
• Investigate acute care end of life admissions
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The power of predictive analytics
Knowing what to look for so you can better prepare for what lies ahead
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Choose the Right BenchmarksWhen it comes to using your data, it’s not just about choosing the right outcomes…
it’s about choosing the right benchmarks…
AND proper risk adjustment.
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Risk Adjusted Rehospitalization Rates – Nation
Source: Original PointRight®
Research © 2016
15% and below
15% to 18%
18% and above
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Observed vs. Risk Adjusted Rehospitalization Rates – California
Risk-AdjustedObserved
12% and below
12% to 20%
20% and above
Source: Original PointRight®
Research © 2016
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Predictive Analytics = Better PartnershipsPointRight Post-Acute Grades vs. the CMS Five-Star Ratings
Post-Operative Care (All Procedures)
CMS 5 Star
Ranking
5 4 3 2 1
18.2% 19.1% 20.0% 19.1% 20.0%
PointRight
Grade
A B C D E
14.1% 17.0% 18.4% 20.8% 24.4%
Chronic Obstructive Pulmonary Disease (COPD)
CMS 5 Star
Ranking
5 4 3 2 1
19.0% 19.3% 19.5% 20.0% 21.1%
PointRight
Grade
A B C D E
16.0% 17.3% 19.0% 21.3% 24.9%
2% Points
Difference
9% Points
Difference
2% Points
Difference
10% Points
Difference
1 and 2 Star SNFs Might be Best Choice in Some Markets
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Care Processes at One SNFCARE PROCESSES AND OUTCOMES Measure Group State National
Pain Management: % of Patients 50% 33% 38% 51%
Advanced Directives: % of Patients 2% 20% 20% 59%
Behavior Management Ratio 5% 40% 42% 80%
Diagnosed with Depression: % of Patients 17% 35% 38% 41%
Facility Acquired Contractors: % of Patients 6% 5% 6% 2%
Hospice Care Utilization 8% 5% 5% 4%
Respiratory Therapy: % of Patients 13% 7% 9% 13%
Observed Drug Administration Errors No
Source: Original PointRight ® Research © 2016
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Average Length of Stay (ALOS)
Year State Median
2012 Nation 24
2013 Nation 24
2014 Nation 24
2015 Nation 22
Year State Median
2015 Nation 22
2015 AL 20
2015 FL 22
2015 MD 27
2015 MA 19
2015 MS 29
2015 TX 25
Source: Original PointRight ® Research © 2016
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What Impacts Average Length of Stay?
State Cognitive
Impairment
Median
Nation No 22
Nation Yes 25
State Incontinence Median
Nation No 21
Nation Yes 28
State Depression Median
Nation No 22
Nation Yes 27
State Pain Median
Nation No 22
Nation Yes 24
Source: Original PointRight ® Research © 2016
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What’s next for LTPAC data?
Accelerating population health management
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Performance by Clinical Cohort™
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COPD at One SNF
Source:
Source:
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Summary
Data is abundant; turning
it into action requires an
extra layer of intelligence
DATA
INTELLIGENCE
ACTION
Partnerships are best
achieved through metrics
that are:
TRANSPARENT
STANDARDIZED
OPERATIONAL
Alignment and
communication improve
outcomes
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STEPS™ to ValueA summary of the benefits realized for the value of Health IT
• The value STEPS™ impacted were:
– Treatment/Clinical
– Patient Engagement & Population Management
– Savings
• Improved the Hospital discharge and admission process
• Improved the Nursing Home to Hospital transfer process
• Reduced overall risk-adjusted rehospitalization rate by 1.06 percentage points
• Improved LifeBridge Quality Score by 6.81%
• Improved overall Five-Star by 4.45%
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Questions
Idriz Limaj, LNHA, RN
Chief Operating Officer
Steven Littlehale, MS, GCNS-BC
EVP & Chief Clinical Officer
@SteveLittlehale
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