Fourth National ACO Summit June 14, 2013 With Information from the Indiana Health Information Exchange

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Transcription:

HIEs and ACOs Fourth National ACO Summit June 14, 2013 With Information from the Indiana Health Information Exchange

Data Needs Depend Upon Structure of ACO ACOs come in many forms Patient Enrolled, locked in to attributed with free choice Limited services (what I provide) to Services Full continuum Scope Focus C Cost off care only l for f what h I provide id to Total Costs and Quality of Care Medicare like ACOs Attributed (aligned) patients Full continuum of care Responsible for Total Cost and Quality

L i ffor Responsibility Logic R ibili without ih E Enrollment ll or L Lockk IIn Providers can be held responsible for patients because: Natural networks arise from routine working relationships among providers primary care, specialty physicians and hospitals Most medical care is provided within these informal networks These care patterns are stable Seminal work on accountability Elliott Fisher et. al, D December b 2006:http://content.healthaffairs.org/content/26/1/w44.full.pd f+html?sid=3098a0fa 888d 4f5b 9ac0 748fb7bb1aab

Acute Admissions at Home Hospitals In System Admissions 80.0% 70.0% 67.6% 69.0% 68.3% 68.8% 68.7% 67.0% % of A Admissions 60 0% 60.0% 50.0% 40.0% 30.0% 20.0% 10.0% 0.0% System 1 System 2 System 3 Year 1 67.6% 68.3% 68.7% Year 2 69.0% 68.8% 67.0%

ED Visits at Home Hospitals In System ED Visits 80.0% 72 0% 72.0% 70.6% 70.0% 60.0% 69.0% 68.9% 59.0% 58.3% % of ED Visits 50.0% 40.0% 30.0% 20.0% 10.0% 0.0% System 1 System 2 System 3 Year 1 58.3% 70.6% 72.0% Year 2 59.0% 68.9% 69.0% See also: Attributing Patients to Accountable Care Organizations, Valerie Lewis, et. al, March 2013 Health Affairs

Inpatient: Completing The Data y Hospital p Necessary Connections 16 14 14 13 Numberr of Hospitals 12 11 10 8 8 7 7 6 4 2 0 System 1 System 2 System 3 90% 7 8 7 95% % 11 14 13

Health Data Sources Value Added Services Hospitals Hospitals Physician Physician Offices Physician Offices Physician Physician Labs / Imaging Centers Labs / Imaging Centers Public Health Results Delivery MU Support Clinical Quality Services Community Health Record Access Results Delivery Community Health Record System Health Information Exchange g Patient Results Delivery MU Support Public Health Integration Data Repository Network Applications Public Health Payors Payers Data Stewardship Outpatient Rx Biosurveillance Reportable p Conditions Results Delivery Quality Reporting Physician Bonus Ad i i t ti Administration De identified, longitudinal clinical data Researchers Copyright 2012 Indiana Health Information Exchange, Inc www.ihie.org

Th P The Principle i i l off LLayered d SServices i Payers/Employers/ACOs Data Payers/employers Fees Savings Hospitals Data Payers/employers Fees Savings Public Health Data Imaging Ctrs Fees Labs Savings Clinical Quality Services Patients Clinics Clinical Repository Services Hospitals Emergency Department Clinical Messaging Results Physicians Hospitals Building or layering services on top of each other squeezes more value from existing investments.

Interdependency of HIE Components Research Electronic Results Delivery Clinical Messaging Medica tion Profiling Public Health Surveillance Quality Reporting P4P and Public ED and Inpt. Abstracts and Results Review Ambulatory Results Review ADT Alerts and ACO Report ing Employer / Payer Reporting Layer III: Including Repository Services Layer II: Including Mapped/Normalized Data Layer I: Including Interface Engine, Community Trust, A layer of necessary investment Value added services that can be built upon the HIE investment

Reducing g MRSA infections byy half

HIE ACO Potentials Today ADT Alerts: especially out of ACO 1. 2. Access to Clinical Data Repository (all par institutions) 3. Inpatient admissions, discharges and transfers ED Visits Facilitate early intervention Interim facilitates communication within multi organizational ACO Clinical abstract Paper Clinical abstract real time digital access Drill down into longitudinal patient record N Normalized li d data d t in i flow fl sheets h t Reverse chronological order Not available for opt outs Cli i l iinformation Clinical f ti tto supportt ACO quality lit reporting ti LDL C, Trig, HDL etc. HgbA1c Other important results

ACO ADT Data File Daily Basis For aligned patients (excl Opt outs)

Clinical Abstract (printed)

Clinical Abstract (screen)

All Reports View View Reverse Chronological g

Flowsheet View

ACO Measures Needing Lab Values Measure Definition Diabetes Care: HgbA1c Controlled at <8% for patients with diabetes Percentage of patients 18 through75 years of age with type 1 or 2 diabetes with HgbA1c controlled at <8% on their most recent test during the previous 12 months. Diabetes Care: LDL C Controlled at <100 mg/dl for patients with diabetes Percentage of patients 18 through 75 years of age with type 1 or 2 diabetes with HgbA1c controlled at <100 mg/dl during the previous 12 months. Diabetes Care: HgbA1c Controlled at <9% for patients with diabetes Percentage of patients 18 through75 years of age with type 1 or 2 diabetes with HgbA1c controlled at <9% on their most recent test during the previous 12 months. Heart Health Ischemic Vascular Disease: Complete Lipid Profile and LDL C Control <100 mg/dl Percentage of patients aged 18 years and older with ischemic vascular disease (IVD) who received at least one lipid profile within 12 months and whose most recent LDL C level was in control (less than 100 mg/dl). Heart Health Coronary Artery Disease: Lipid Control or Lipid lowering therapy for patients with Coronary Artery Disease (CAD) Percentage of patients 18 years and older with Coronary Artery Disease (CAD) who either had an LDL C <100 mg/dl OR whose LDL C >100 and were prescribed b d a llipid lowering dl therapy. h

Developing HIE Capabilities 4. CCD Continuity of Care Document (historical clinical information) For interoperability direct to EHR 5. Leakage what and why are patients using other systems 6. Population Health Management Registries Trends in lab values improvement/not Integration with visit planners 7. Predictive modeling preventable admissions and readmissions 8. Comparative utilization and cost reporting

Thank You Contact Information David E. Kelleher Curt Sellke dave@hoi.com csellke@ihie.com