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The 5 Critical Information Systems Needed to Drive ACOs
1.
© 2014 Health
Catalyst www.healthcatalyst.comProprietary. If you would like to share, we simply ask that you cite Health Catalyst © 2014 Health Catalyst www.healthcatalyst.com Proprietary. If you would like to share, we simply ask that you cite Health Catalyst 5 Critical Information Systems Needed to Drive Accountable Care Organizations By Dale Sanders
2.
© 2014 Health
Catalyst www.healthcatalyst.comProprietary. If you would like to share, we simply ask that you cite Health Catalyst Information Systems for Accountable Care Organizations (ACO) 2 Electronic Medical Record (EMR) Used in a consistent and meaningful way across the accountable care enterprise to document patients’ healthcare status and treatment and support safe, evidence based care. 1 Health Information Exchange (HIE) Enable the sharing of patients’ clinical data across disparate EMRs in the accountable care enterprise. 2 Activity Based Costing (ABC) Enables detailed, patient- specific collection of cost data. The ACO can then precisely understand cost of production and revenue margins in capitated payment models. 3 Patient Reported Outcomes (PRO) A clinical outcomes assessment system that enables the complete understanding of clinical outcomes and quality, from the patient’s perspective. 4 Enterprise Data Warehouse (EDW) Central to enabling the analysis of data collected in the information systems. the exposure and integration of the data drives ROI rates as high as 450% in two years. 5
3.
© 2014 Health
Catalyst www.healthcatalyst.comProprietary. If you would like to share, we simply ask that you cite Health Catalyst Significant focus in last 7years on EMR and HIE adoption. The inability to integrate and analyze data in an EDW is “the single most frustrating issue” those organizations face. Without integrated activity based and patient reporting data precise predictive analytics and patient risk stratification is unachievable. 3 Information Systems for Accountable Care Organizations (ACO) The EDW is the center of data collection systems,the platform that enables the analysis of clinical, financial, and patient reported data in a single database repository.
4.
© 2014 Health
Catalyst www.healthcatalyst.comProprietary. If you would like to share, we simply ask that you cite Health Catalyst Accountable Care Organization – (ACO) Background 4 ACO is simply a shift in reimbursement from procedure-based, fee-for-service towards fee-for-quality, disease, or condition-based reimbursement with capitated payments to healthcare delivery organizations on a per-case and per-capita basis.
5.
© 2014 Health
Catalyst www.healthcatalyst.comProprietary. If you would like to share, we simply ask that you cite Health Catalyst Accountable Care Organization – (ACO) Plans and Services 5 A quick assessment of the most successful U.S. healthcare systems, such as Intermountain Healthcare, reveals one very simple common trait: They offer health insurance plans and health delivery services under a single CEO who balances the economics of care with access to care and quality of care.
6.
© 2014 Health
Catalyst www.healthcatalyst.comProprietary. If you would like to share, we simply ask that you cite Health Catalyst Healthcare Industry IT Snapshot 6 • IT Investment over six years in excess of $100 billion. • Physician satisfaction with EMR products stimulated by federal incentives is only 39% and declining • 78% of public HIEs fail due to financial insolvency after federal and state grant monies removed • One-third of the organizations in the CMS Pioneer ACO Program drop out because they can not adequately quantify the quality of care and financial risk for managing patients in the ACO
7.
© 2014 Health
Catalyst www.healthcatalyst.comProprietary. If you would like to share, we simply ask that you cite Health Catalyst EDW Return on Investment 7 • Average ROI from an EDW is 431% over five years • Intermountain Healthcare enjoyed a 1,468% ROI in less than two years when implementing their EDW
8.
© 2014 Health
Catalyst www.healthcatalyst.comProprietary. If you would like to share, we simply ask that you cite Health Catalyst Healthcare Analytic Adoption Model Less than 10% of healthcare organizations with any type of EDW operate at a level 5 of the Healthcare Analytic Adoption Model 8 Level 8 Level 7 Level 6 Level 5 Level 4 Level 3 Level 2 Level 1 Level 0 Personalized Medicine & Prescriptive Analytics Clinical Risk Intervention & Predictive Analytics Population Health Management & Suggestive Analytics Waste & Care Variability Reduction Automated External Reporting Automated Internal Reporting Standardized Vocabulary & Patient Registries Enterprise Data Warehouse Fragmented Point Solutions Tailoring patient care based on population outcomes and generic data. Fee-for-quality rewards health maintenance. Organizational processes for intervention are supported with predictive risk models. Fee-for-quality includes fixed per capita payment. Tailoring patient care based on population metrics. Fee- for-quality includes bundled per case payment. Reducing variability in care processes. Focusing on internal optimization and waste reduction. Efficient, consistent production of reports & adaptability to changing requirements. Efficient, consistent production of reports & widespread availability in the organization. Relating and organizing the core data content. Collecting and integrating the core data content. Inefficient, inconsistent versions of the truth. Cumbersome internal and external reporting.
9.
© 2014 Health
Catalyst www.healthcatalyst.comProprietary. If you would like to share, we simply ask that you cite Health Catalyst Principles of Information Technology 9 As healthcare becomes a more tech-savvy, computerized industry, healthcare executives MUST understand three core principles and their impact on business.
10.
© 2014 Health
Catalyst www.healthcatalyst.comProprietary. If you would like to share, we simply ask that you cite Health Catalyst Business Moves at the Speed of Software 10 IT software is now the dominant variable in business agility and adaptability. The best software and information technology can drive unprecedented business insight and business models. The worst software can drive a business into the ground. Principles of INFORMATION TECHNOLOGY 1
11.
© 2014 Health
Catalyst www.healthcatalyst.comProprietary. If you would like to share, we simply ask that you cite Health Catalyst Big Value Comes From Big Data 11 The software and underlying technology enabling analysis of patterns in large data sets is driving extraordinary new ability for businesses to identify opportunities for greater efficiency, higher quality, lower overhead, higher margins, and new products. That is the power of the EDW. Principles of INFORMATION TECHNOLOGY 2
12.
© 2014 Health
Catalyst www.healthcatalyst.comProprietary. If you would like to share, we simply ask that you cite Health Catalyst Big Value Comes From Big Data 12 Data management maturity passes through three phases. 1. Data Collection 2. Data Sharing 3. Data Analysis Phase 3 is characterized by the implementation of the EDW. Principles of INFORMATION TECHNOLOGY 3
13.
© 2013 Health
Catalyst www.healthcatalyst.com Other Clinical Quality Improvement Resources Click to read additional information at www.healthcatalyst.com A Landmark, 12-Point Review of Population Health Management Companies (Also by Dale Sanders) Prior to his healthcare experience, Dale Sanders worked for fourteen years in the military, national-intelligence, and manufacturing sectors, specializing in analytics and decision support. In addition to his role at Health Catalyst, he continues to serve as the senior technology advisor and CIO for the National Health System in the Cayman Islands. Previously, he was CIO with the Northwestern University Medical Center, and regional director of Medical Informatics at Intermountain Healthcare where he served in a number of capacities, including chief architect of Intermountain’s enterprise data warehouse. Dale is a founder of the Healthcare Data Warehousing Association. He holds Bachelor of Science degrees in Chemistry and in Biology from Ft. Lewis College, Durango Colorado, and is a graduate of the U.S. Air Force Information Systems Engineering program.
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