Data Analysis for Disease Management

presented by:

Michael Mina

Senior Statistical Analyst

Medical Mutual of Ohio

October 13, 1999

Presentation Overview

• Brief Disease Management Overview

• MBSD DM Responsibilities

• Competitor DM Data Issues

• Possible Enhancements to MBSD DM Processes

• Disease Management Resources

Brief Disease Management Overview

• Disease management is the process of coordinating and managing members who have chronic conditions and health management services along the full spectrum of health care delivery while striving to improve both clinical and economic outcomes through altering patient and provider behavior.

Brief Disease Management Overview (cont’d)

• Population based - different levels of severity

• Education, Assistance

• Help patients control their own disease

• Concerned with quality of life, not cost alone

Brief Disease Management Overview (cont’d)

• Insurance companies usually understaffed for this purpose

• Disease Management programs often vendor-based, with vendors focused on a specific disease

Brief Disease Management Overview (cont’d)

• MMO DM programs include:– Breathe Easy (Asthma, COPD)– Heart Sense (Congestive heart failure)– Transplanting Health (Organ transplant)– BabyLink (Perinatal education)– Outpatient Diabetic Education

MBSD DM Responsibilities

• Identify diseases to manage

• Process information for vendor usage

• Invite providers to participate

• Determine effectiveness of DM efforts– Outcomes reporting– Over/underutilization measures

Tools Used by MBSD

• DB2 / QMF / SQL

• SAS

• Access

• Oracle

DB2 / QMF / SQL

• Above terms often used interchangeably

• DB2 - Relational Database Management System (RDBMS)

• QMF - Query Management Facility

• SQL - Structured Query Language

• Easy access to data

DB2

• Relational Database

DB2 (cont’d)

DB2 (cont’d)

DB2

• Production systems - PReview, CMS, CPIMS

• Data storage - claims, premium, dependents

• Standard RDBMS for MMO data warehousing / data mart efforts– Note: In the industry as a whole, outcomes

reporting is a force behind data warehousing

• DB2 used widely inside and outside MMO - BP pay-at-pump

QMF

• Manages queries

• Some reporting and formatting capabilities

• Can create procedures (procs) containing instructions for running multiple queries

• More effective programming

SQL

• Queries - mini computer programs

• “The most difficult area of data warehousing is the translation of simple business analyses into SQL” - Ralph Kimball Ph.D., CEO Red Brick Systems

SQL (cont’d)

• SELECT DISTINCT SUB_ID, DEP_NBR FROM CORP.INPAT WHERE YR_MO=199909 AND PAT_AGE>=65 AND SPEC_CD=‘C1’ ORDER BY 1, 2

SAS

• SAS is a company with many products

• Very powerful statistical analysis software

• MMO has about 10 SAS programmers

• Goodyear has over 700 SAS programmers and a SAS data warehouse

• SAS is used by GE Card Services with an Oracle data warehouse

Access

• Microsoft database

• Very versatile– Easy to create reports with downloaded

mainframe data– Very widely used– Small business database of choice– But also used by NCB ($80 billion bank) for

Sales & Incentive program

Oracle

• Very powerful, very widely used RDBMS

• Uses PL/SQL version of SQL

• MMO uses Oracle for HEDIS reporting

• Used by Yahoo! and other database-driven web sites

Identify Diseases to Manage

• Based on Population Analysis (SAS)

• Look for:– High patient volume– High cost

Process Information for Vendor Usage

• Initial and subsequent targetings

• Standardized methodology based on DB2– Select claims related to disease state

• BabyLink: by Rx; Others: medical claims by dx

– Identify distinct members from claims– Select all claims for those members

(comorbidities)– Get member, provider, PCP information

• Methodology documented and flowcharted

Invite Providers to Participate

• Problems with provider address quality

• DB2/QMF/SQL and Access programming used to improve information quality– DB2: standard in-network provider addressing– Access: “smart” formatting of mailing labels– “Clean” and “proper” addresses still an issue

Determine Effectiveness- Outcomes Reporting

• Vendor outcomes reporting - based upon enrolled population

• MMO outcomes reporting– Days/1000, Cases/1000– ER visits/1000, Office visits/1000– coming soon: Readmissions/1000

Determine Effectiveness- Outcomes Reporting (cont’d)

• MMO outcomes reporting– disease state outcomes for patients– overall outcomes for patients– overall outcomes for all MMO members

Determine Effectiveness- Outcomes Reporting (cont’d)

• Breathe Easy: Started with SAS, ran out of space

• Met deadline with a workaround

• Change in specifications

• Tried DB2 this time, still ran out of space

Determine Effectiveness- Outcomes Reporting (cont’d)

• Vertical partitioning– Another way to organize data– 85% space savings over previous process– Process enabler

• Data mart• DB2 + Vertical Partitioning + Data Mart +

Access = Success!

Determine Effectiveness- Outcomes Reporting (cont’d)

• Process still under development

• New specifications easier to implement– Disease assignment module (5 SQL queries)– Separate BH outcomes from Medical

Determine Effectiveness- Over/Underutilization Measures

• What is a readmission? Ask me in a month!

• Developed in DB2 using claims, not PReview

• Access reports used to test methodology– Process: review results > modify SQL query > rerun

query > import results into Access > review results

• Can ultimately be run from data mart

Competitor DM Data Issues- Aetna

• Managed care data warehouse since 1996

• Combines some functions of PReview, HEDIS

• Standard reports, member mailings

• Chronic disease registry

• Data warehouse soon to have web browser front end

Competitor DM Data Issues- Anthem BCBS

• Data warehouse since 1991• Excellence in Business Information Award• Outcomes reporting, HEDIS reporting, fraud• “We did this not just to get into a leadership

position but as a matter of survival” - Joe Bruscato, Chief Data Warehousing Architect, Anthem BCBS

Possible Enhancements to MBSD DM Processes

• Currently use FFS inpatient, outpatient, professional claims for targeting, outcomes– exception: BabyLink

• Likely inclusions– Rx claims (major medical, freestanding)– encounters

• Redundancy to ensure validity– e.g., asthma dx and one Rx and one refill

Possible Enhancements to MBSD DM Processes (cont’d)

• Data mart schema for other DM programs

• Evaluation of Data Mining/ Business Intelligence products

Disease Management Resources

Recap

• Brief Disease Management Overview

• MBSD DM Responsibilities

• Competitor DM Data Issues

• Possible Enhancements to MBSD DM Processes

• Disease Management Resources

Thank you for coming!