expanding data warehousing into a true management tool

Expanding Data Warehousing into a True Management Tool

Bill McCallum, CEO/PresidentAccountable AnalyticsOctober, 2014

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

With Shrinking MarginsEvery Dollar Counts

Quality of Benchmarks

Is the Benchmark representative of your population

Controls placed on the collection of the benchmark data

Understanding of benchmark calculations

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.

Extracts to Excel

Departmental Data Manipulations

Inconsistent Data Definitions

Data War Lords

Definitions are Consistent

Reports Tie Together

Performance is Defined by Best Practice

Problems are resolved quickly

Utopia

Does Your Report Development Remind You of Playing Battleship

Information Technology

End User

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

Apples and Oranges

Defining a Diabetic Cohort

PQRS - Medicare Physician Quality Reporting System

HEDIS- Healthcare Effectiveness Data

and Information Set

NQF - National Quality Forum

Practice Management System

EHR

How Big is Your World

US CensusNational Provider Identifier ListMedicare Public Use DataPatient Risk Scores CDCBerenson Eggers GroupsMGMA/AMGA BenchmarksNDC Drug Classes

Looking Beyond the Your World

Geospatial Mapping

Type of referrals and where they originate

Demographics by Financial Class

Disease Management

Marketing

Recruiting

Data

Warehouse

CompensationSupport StaffMid Levels

Revenue CycleCollectionsWrite-offs

DenialsDSO

ContractingPayer Mix

Fee Schedules

InfrastructureStaffing

IT

ProductivitySpecialty Specific

QualityCoding

Disease MgmtPQRS

Collective Data Drives Decisions

Quick Wins

Downstream Revenue Dropped Charges Leakage Modeling Proposed Contracts Case Rates

Quick Wins

Compensation / Productivity Coding Avoidable Denials Adjustments vs. ANSI Denials Fee Schedules Payer Contracts Provider Panel Size and Scheduling

The Data Model

Flat File vs Multi-dimensional

Dimension Structure

Naming Conventions

Understanding the Business Case

The Data ModelFlat File vs Multi-dimensional

Crystal / Reporting Services

Flat Highly IndexedFacilitates complex subsetsRequires expert user

Multi-Dimensional

Fast EasyDesigned for specific Task

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