expanding data warehousing into a true management tool
TRANSCRIPT
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Expanding Data Warehousing into a True Management Tool
Bill McCallum, CEO/PresidentAccountable AnalyticsOctober, 2014
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Operating Costs rising more rapidly than revenues
Maintaining Physician Comp against declining…
Collecting self-pay and high-deductible patients
Managing finances with the uncertainty of…
Recruiting physicians
Negotiating contracts with payers
Selecting and implementing a new EMR
Modifying physician compensation methodology
Participating in PQRI
Hiring and retaining quality staff
Top 10 Challenges Physician Response
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With Shrinking MarginsEvery Dollar Counts
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Quality of Benchmarks
Is the Benchmark representative of your population
Controls placed on the collection of the benchmark data
Understanding of benchmark calculations
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MGMA Encounter Definition
A documented, face-to-face contact between a patient and a provider who exercises independent judgment in the provision of services to the individual. If a patient sees multiple providers on the same day for the same set of problems/diagnoses, it is considered one encounter. If a patient with multiple problems/diagnoses sees multiple providers on the same day and each provider manages a different set of problems/diagnoses, then it can be considered as multiple encounters.
Do not include: 1. Ambulatory encounters attributed to nonphysician providers;2. Encounters for the physician specialties of pathology or diagnostic radiology. (see #2 under “Include” above);3. Encounters that include procedures from the surgery chapter (CPT codes 10021-69979) or anesthesia chapter (CPT codes 00100-01999);4. Number of procedures, since a single encounter can generate multiple procedures;5. Visits where there is not an identifiable contact between a patient and a physician or nonphysicianprovider such as when the patient comes into the practice solely for an injection, vein puncture, EKG, or EEG administered by an RN or technician;6. Administration of chemotherapy drugs; or7. Administration of immunizations.
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Extracts to Excel
Departmental Data Manipulations
Inconsistent Data Definitions
Data War Lords
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Definitions are Consistent
Reports Tie Together
Performance is Defined by Best Practice
Problems are resolved quickly
Utopia
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Does Your Report Development Remind You of Playing Battleship
Information Technology
End User
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PM System Specialty Cardiology
MGMA Specialty Cardiology: Electrophysiology
Cardiology: Invasive
Cardiology: Invasive-Interventional
Cardiology: Noninvasive
Surgery: Cardiovascular
Surgery: Cardiovascular-Pediatric
Surgery: Thoracic (Primary)
Surgery: Vascular (Primary)
Medicare Specialty 06 – Cardiology
78 – Cardiac Surgery
33 – Thoracic Surgery
Apples and Oranges
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Apples and Oranges
Defining a Diabetic Cohort
PQRS - Medicare Physician Quality Reporting System
HEDIS- Healthcare Effectiveness Data
and Information Set
NQF - National Quality Forum
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Practice Management System
EHR
How Big is Your World
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US CensusNational Provider Identifier ListMedicare Public Use DataPatient Risk Scores CDCBerenson Eggers GroupsMGMA/AMGA BenchmarksNDC Drug Classes
Looking Beyond the Your World
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Geospatial Mapping
Type of referrals and where they originate
Demographics by Financial Class
Disease Management
Marketing
Recruiting
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Data
Warehouse
CompensationSupport StaffMid Levels
Revenue CycleCollectionsWrite-offs
DenialsDSO
ContractingPayer Mix
Fee Schedules
InfrastructureStaffing
IT
ProductivitySpecialty Specific
QualityCoding
Disease MgmtPQRS
Collective Data Drives Decisions
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Quick Wins
Downstream Revenue Dropped Charges Leakage Modeling Proposed Contracts Case Rates
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Quick Wins
Compensation / Productivity Coding Avoidable Denials Adjustments vs. ANSI Denials Fee Schedules Payer Contracts Provider Panel Size and Scheduling
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The Data Model
Flat File vs Multi-dimensional
Dimension Structure
Naming Conventions
Understanding the Business Case
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The Data ModelFlat File vs Multi-dimensional
Crystal / Reporting Services
Flat Highly IndexedFacilitates complex subsetsRequires expert user
Multi-Dimensional
Fast EasyDesigned for specific Task
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Your dimensions and their hierarchy determine the success of your deployment
Know what business cases . To many dimensions become overwhelming for the user
The Data ModelDimension Structure