Transcript Can Give Managed Care Organizations

Data Mining:
Opportunities for Healthcare
Quality Improvement & Cost Control
Joseph A. Welfeld, FACHE
Long Island University
845.359.7200 x 5410
[email protected]
March 7, 2005
The Health Information Technology Summit West
Data Mining: Opportunities for Healthcare
Quality Improvement & Cost Control
 Speaker Profile
 Data Mining
 Quality Improvement – Changing Behavior
with Incentives
 Cost Control – Targeting Key Areas
 Data Mining Software
 Practical Applications – A Case Study
 Questions
Speaker Profile – Joseph A. Welfeld
 Regional Operations Director: NY - RelayHealth
 Program Director: Graduate Program in Health
Administration: LIU – Rockland Graduate Campus
 30 years of healthcare experience
 CEO - Ocean State Physicians Health Plan
 Regional VP – United Healthcare
 10 years in strategy consulting for IPAs, PHOs &
Hospital Networks
 MBA Healthcare Administration – CUNY/Mt. Sinai
School of Medicine
Data Mining: Definition
 An information extraction activity whose goal is
to discover hidden facts contained in databases.
 True data mining software doesn't just change
the presentation, but actually discovers
previously unknown relationships among the
data.
The Healthcare Database Minefield
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Hospital claims data – billing systems
Medical claims data – billing systems
Pharmacy claims data – PBMs
Lab data systems
Aggregators:
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Managed Care Organizations
Third Part Administrators
Medical Groups/IPAs
None of the above
Data Mining:
Obstacles in Healthcare Organizations
Deer in the headlights look
Data what?
We don’t have any more money to buy software
We have all the software we need
We just spent $__million on a new system
Our IT staff can produce anything we want from
our in-house data system
 Our data analysis could not be better
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Quality Improvement – The Challenge
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Finding acceptable standards
Combining data from multiple sources
Limited financial incentives to promote change
Until recently, no financial incentives to change
Goal – physician “behavior” change
Quality Improvement – The Opportunities
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HEDIS Standards
Leapfrog Group
Bridges to Excellence
MCO Performance Incentives
Sample HEDIS Report Activity:
Beta Blocker Treatment After Heart Attack
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Members age 35 and older who where
discharged with an AMI and were prescribed
beta-blockers within 7 days of discharge.
Numerator: Members who received an
ambulatory prescription for a beta-blocker
within 7 days of discharge
Denominator: Members with an AMI between
Jan 1 and Dec 24 of the measurement year
Problem Faced: Linking admission/discharge
and prescribing data
Beta Blockers Prescribed after MI Diagnosis:
ATENOLOL
COREG
INDERAL
LABETOLOL
SOTALOL
BETAPACE
PROPRANOLOL
NORMODYNE
Use of Appropriate Medications:
People with Asthma
 Numerator: Members age 5-56 who received a
prescription for a long term control asthma
medication such as inhaled cortico-steroids
 Denominator: Members age 5-56 are identified
as having asthma using pharmaceuticals and
diagnostic data during the year prior to the
measurement year
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Four dispensing events
One ER visit with a principle diagnosis of asthma
One acute inpatient discharge with a principal
diagnosis of asthma
At least four outpatient visits with a diagnosis of
asthma and two dispensing events
Cost Control – The Challenge
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Payer – Provider “ trust chasm”
The “my patients are sicker” debate
Combining data from multiple sources into
coherent and logical reports
Cost Control – The Opportunities
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The ability to merge medical claims, hospital
claims, drug claims, medical records and clinical
outcomes data
The ability to analyze episodes of care including
drug utilization
The ability to rapidly create contract models by
user-defined resource and provider categories
Ability to drill down into individual patient claims
Ability to target high cost trends
Cost Control: Targeting High Cost Trends
 Puts up to 3 datasets side-by-side.
 Can compare performance against benchmarks.
 Unlimited number of resource categories and
user-defined resource utilization models allowed
 Tracks in-patient, professional, lab, pharmacy
and other cost categories automatically
 See example:
Cost Control: Drilling Down to Specifics
 Isolate a resource category and quickly find
highest cost by any factor (disease risk group,
age, sex, plan, doctor, etc.)
 Then drill down to get more information on
those results
 Drill down further to see treatment line items
for those specific patients
 Example on following screens shows disease
groups with highest lab costs
ACRG2 Metastatic Category: 5 episodes with very high costs
Those 5 Patient Episodes in the ACRG2 Metastatic Group
Cost Control: Age/Sex Analysis
 Creates unlimited number of age distribution
models to apply against data
 Select specific resource categories to view
 Cross-tab against specific values of any factor,
i.e., disease group, specialty, etc.
 The following slide shows the utilization of
selected resources by Age/Sex for patients in the
Asthma-Diabetes-CHF CRG categories:
Cost Control: Physician Profiling
 Functions designed to monitor physician activity
 Monitor ICD9 and CPT code utilization patterns
 Cross-tab against specific values of any factor,
i.e., disease group, specialty, etc.
 Summarizes all costs by provider and compares
on one screen.
ER Utilization Costs by PCP:
•Outliers shown above dotted line on graph
•Highest outlier on graph highlighted on chart
CPT Codes for Gastroenterologists: Ranked by Frequency
PCP Utilization Cost Summary by Major Resource Category
Detailed 3M CRG (Clinical Risk Groups)
Disease/Severity Cost Distribution
Detailed 3M CRG (Clinical Risk Groups) Disease/Severity Cost Distribution
Hudson IPA – A Case Study
 Strategic Question – How to deliver real value to
managed care organizations?
 Replace capitated agreement with performancebased model
 Provide managed care organizations data
analysis capabilities they don’t really have
 Assist with HEDIS performance monitoring and
communications – a key MCO objective
Data Mining Software – Bringing Value
Gave IPA:
 Ability to merge medical claims, hospital claims,
drug claims, medical records and clinical
outcomes data
 Ability to analyze episodes of care including drug
utilization to meet agreed-upon goals
 Ability to rapidly create contract models by userdefined resource and provider categories
 Ability to drill down into individual patient claims
 Ability to analyze HEDIS performance criteria
including diabetes and cardiology care
Data Mining Software Characteristics
 Powerful disease state management and risk
contract functionality
 Data warehouse designed to merge all types of
healthcare data.
 Physician profiling and resource tracking features
 Drill down into individual patient claims from
either financial or clinical perspectives and
retrieve both types of information together
Data Mining Software Characteristics
 SmartCare – Developed by VantagePoint Health
Information Systems, Inc.
 Loads claims data at a rate of 100,000 claims/hr
 Links pharmacy (PBM), hospital & medical claims
 Automatically creates episodes of care
 Computes PM/PM ratios in less than five seconds
 Powerful graphing & statistical tools
 No programming/data analysis skills/staff needed
 Open database for addition of other clinical or
administrative fields – lab, blood pressure, etc.
Data Mining Applications Summary
Gives Physician Organizations:
 Ability to develop quality indicators,
performance improvement programs and
incentive-based compensation programs.
 Ability to analyze HEDIS performance criteria
including diabetes and cardiology care.
 Ability to analyze formulary compliance activity.
 Tool for additional revenue resources including
comprehensive market research, clinical
outcomes and pharmaco-economic studies.
 Ability to monitor risk-contract progress.
Data Mining Applications Summary
Can Give Managed Care Organizations:
 A tool to develop true partnership relationships
with provider organizations seeking incentive
compensation or risk relationships
 Ability to develop comprehensive HEDIS analysis
and performance reports
 Ability to combine multiple claims data bases into
a single data reporting and analysis system at
the contracting level
 Ability to do rapidly model the impact of fee
schedule changes on provider costs and contract
performance.
Questions??