Applying Analytics to Population Health...
Transcript of Applying Analytics to Population Health...
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Applying Analytics to Population Health Management
April 15, 2015
Kori Krueger, MD, MBA / Marshfield Clinic
Kate Konitzer, MMI / Marshfield Clinic Information Services
DISCLAIMER: The views and opinions expressed in this presentation are those of the author and do not necessarily represent official policy or position of HIMSS.
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Kori Krueger, MD, MBA Has no real or apparent conflicts of interest to report.
© HIMSS 2015
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Kate Konitzer, MMI Salary: Yes Receipt of Intellectual Property Rights/Patent Holder: Pending
© HIMSS 2015
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Explain the Population Health Management lifecycle
Demonstrate the use of analytics applied to population health
Discuss concepts applied throughout the lifecycle
Analyze gaps for population health advancement
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• Satisfaction from providers in better understanding their patient panels.
• Treatment is based on evidenced based medicine guidelines and measured to the guidelines.
• Electronic information is key to understand your patient populations and using the data to define new strategies.
• Prevention is assessed by improving compliance rates and encouraging screening tests for early detection. Managing patient outcomes prevents adverse events associated with the disease states.
• Savings are being demonstrated by improving quality, and lowering utilization by better managed care.
Value Steps
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Marshfield Clinic Health System
• Formed 1916
• Physician led – 501(c)3
• 750 physicians in 86 specialties
• 6,450 employees
• 56 regional sites
• 375,000 unique patients/year
• 3.7 million patient encounters/year
• >$1 billion in annual revenue
• Security Health Plan 228,000 member HMO
• Division of Laboratory Medicine
• Education Foundation
• Research Foundation
• Family Health Center – FQHC (76,000 patients, 443,000 encounters/ year)
• Integrated Dental Clinics in underserved areas
• An Academic Campus of UW School of Medicine and Public Health
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Attribution
Define Population
Identify Care Gaps
Stratify Risks
Engage Patients
Manage Care
Measure Outcomes
Feedback Loop
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Define Population
HTN
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Objective – Ability to identify any population cohort
Challenges – Extract information from your EHR – Terminologies/Codes
Implementation – Enterprise Data Warehouse – Structured data collection – Terminology groupers
Results – Reliable, longitudinal cohort
Gaps Strategy – QA of problem lists – Care plans attached to problem lists
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Data Mart
Transactional Data Sources
Atomic Level Data Warehouse
Staging Area
Data Mart
Portal
Extr
act,
Tran
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m, L
oad
Extr
act,
Tran
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m, L
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DW Development DW Analytics
Analytics Environment
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Attribution
Primary Care and Specialty
Care
Define Population
HTN
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Objective – Identify patient / provider relationship
Challenges – Self-reported data – Place of service visits
Implementation – Self-reported – Attribution rules
Results – Accountability – Actionable
Gaps Strategy – Quality Assurance – track at time of care
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Attribution
Blood Pressure Control
Primary Care and Specialty
Care
Define Population
HTN
Identify Care Gaps
Blood Pressure Control
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Objective – Identify gaps given evidenced based care guidelines
Challenges – Conflicting guidelines – Lack of evidenced based care – Accurate data (device, home monitoring, place of service)
Implementation – Consistent specifications – Instrumentation of devices
Results – Governance of best practices – Patient level detail
Gaps Strategy – Guideline consensus
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Attribution
Blood Pressure Control
Primary Care and Specialty
Care
Define Population
HTN
Identify Care Gaps
Blood Pressure Control
Stratify Risks
HTN/DM, At Risk
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Objective – Identify risk
Challenges – Determine risk categories – Risk assessment – Determine future risk
Implementation – Multiple co-morbidities – Predictive modeling
Results – Defined populations
Gaps Strategy – Revision and refinement of risk model
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Attribution
Blood Pressure Control
Primary Care and Specialty
Care
Define Population
HTN
Identify Care Gaps
Blood Pressure Control
Stratify Risks
HTN/DM, At Risk
Engage Patients
Patient Portal Secure
Messaging
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• Objective – Engage patient activation
• Challenges – Differing levels of patient engagement – Disparity and access to resources – Care management programs under-funded or not funded
• Implementation – EMR and patient care tools – Identification of the ‘At Risk’ population
• Results – Informed consumer of healthcare
• Gaps Strategy – Engage community
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Attribution
Blood Pressure Control
Primary Care and Specialty
Care
Define Population
HTN
Identify Care Gaps
Blood Pressure Control
Stratify Risks
HTN/DM, At Risk
Engage Patients
Patient Portal Secure
Messaging
Manage Care
Care Plans
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• Objective – Develop multi-faceted approach
• Challenges – Adherence to care plan – Communication outside of visit between patient and provider – Variation of care
• Implementation – Care management programs – Evidence based care guidelines
• Results – Improved outcomes
• Gaps Strategy – Integration of best practices with EMR
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Attribution
Blood Pressure Control
Primary Care and Specialty
Care
Define Population
HTN
Identify Care Gaps
Blood Pressure Control
Stratify Risks
HTN/DM, At Risk
Engage Patients
Patient Portal Secure
Messaging
Manage Care
Care Plans
Feedback Loop
Dashboard
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• Objective – Provide consistent and timely feedback
• Challenges – Accessible, meaningful, timely results
• Implementation – PDSA’s – Dashboard – Actionable information
• Result – Dashboard utilization – Departmental meetings
• Next Steps – Point of care integration
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Attribution
Primary Care and Specialty
Care
Define Population
HTN
Identify Care Gaps
Blood Pressure Control
Stratify Risks
HTN/DM, At Risk
Engage Patients
Patient Portal Secure
Messaging
Manage Care
Care Plans
Measure Outcomes
Feedback Loop
Dashboard
Reduce Strokes
and Heart Attacks
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• Objective – Develop consistent approach to measuring outcomes (stroke, heart
attacks)
• Challenges – Manage variation – Incomplete data
• Implementation – Quality/Process improvement – Integrated clinical / claims data
• Results – Number needed to treat - NNT
• Gaps Strategy – Proactive vs. Reactive approach
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Measure 2004 2014
HTN blood pressure control 49.8% 77.3%
Pneumococcal vaccination 57.4% 89.1%
Asked if use tobacco 11.7% 97%
Diabetic LDL control 37.1% 62.6%
Diabetic foot exam N/A 77%
All-cause hospitalizations per 1,000 diabetes patients 399 365
Breast cancer screening 60.8% 76.1%
Colorectal cancer screening 49% 71.3%
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Hypertension Example:
– BP control rate has increased from 49.8% controlled to 77.3% of patients controlled
– Resulting in additional 15,182 patients now at goal that would not have been at goal in past
– Need to treat 18 patients for 5 years to goal in order to prevent one heart attack or stroke
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Results: • Additional 674 heart attacks avoided
– Savings over 10 years (2010 $): $56,953,000 • 169 strokes avoided
– Savings over 10 years (2010 $): $31,045,000 – Total Savings*: $87,998,000
*Estimated using the CDC Chronic Disease Cost Calculator for State of Wisconsin including only direct medical expenses, not indirect societal costs
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• Clinical and Analytic teams partnering • Clinical
– Manage what you can measure – Optimize resource allocations – Develop regional teams – Define processes to share with clinical teams
• Toolkits – PDSA’s – Care Plan development
• Analytics – Define processes with the Clinical teams – Provide insights into delivery of care
• Dashboards • Predictive modeling
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Kori Krueger, M.D., M.B.A. Medical Director Institute for Quality, Innovation & Patient Safety Office 715-389-3188 [email protected]
Kate Konitzer, MMI Chief Informaticist Office 715-221-8311 [email protected]