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.

Kori Krueger, MD, MBA Has no real or apparent conflicts of interest to report.

© HIMSS 2015

Kate Konitzer, MMI Salary: Yes Receipt of Intellectual Property Rights/Patent Holder: Pending

© HIMSS 2015

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

• 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

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

Attribution

Define Population

Identify Care Gaps

Stratify Risks

Engage Patients

Manage Care

Measure Outcomes

Feedback Loop

Define Population

HTN

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

Data Mart

Transactional Data Sources

Atomic Level Data Warehouse

Staging Area

Data Mart

Portal

Extr

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DW Development DW Analytics

Analytics Environment

Attribution

Primary Care and Specialty

Care

Define Population

HTN

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

Attribution

Blood Pressure Control

Primary Care and Specialty

Care

Define Population

HTN

Identify Care Gaps

Blood Pressure Control

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

Attribution

Blood Pressure Control

Primary Care and Specialty

Care

Define Population

HTN

Identify Care Gaps

Blood Pressure Control

Stratify Risks

HTN/DM, At Risk

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

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

• 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

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

• 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

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

• 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

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

• 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

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%

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

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

• 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

Kori Krueger, M.D., M.B.A. Medical Director Institute for Quality, Innovation & Patient Safety Office 715-389-3188 krueger.kori@marshfieldclinic.org

Kate Konitzer, MMI Chief Informaticist Office 715-221-8311 kate.konitzer@mcis.com