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Data Analysis for Disease Management

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Presentation on theme: "Data Analysis for Disease Management"— Presentation transcript:

1 Data Analysis for Disease Management
presented by: Michael Mina Senior Statistical Analyst Medical Mutual of Ohio October 13, 1999

2 Presentation Overview
Brief Disease Management Overview MBSD DM Responsibilities Competitor DM Data Issues Possible Enhancements to MBSD DM Processes Disease Management Resources

3 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.

4 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

5 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

6 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

7 MBSD DM Responsibilities
* 07/16/96 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 *

8 Tools Used by MBSD DB2 / QMF / SQL SAS Access Oracle

9 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

10 DB2 Relational Database

11 DB2 (cont’d)

12 DB2 (cont’d)

13 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

14 QMF Manages queries Some reporting and formatting capabilities
Can create procedures (procs) containing instructions for running multiple queries More effective programming

15 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


17 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

18 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

19 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

20 Identify Diseases to Manage
Based on Population Analysis (SAS) Look for: High patient volume High cost

21 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

22 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

23 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

24 Determine Effectiveness - Outcomes Reporting (cont’d)
MMO outcomes reporting disease state outcomes for patients overall outcomes for patients overall outcomes for all MMO members

25 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

26 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!

27 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

28 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


30 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

31 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

32 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

33 Possible Enhancements to MBSD DM Processes (cont’d)
Data mart schema for other DM programs Evaluation of Data Mining/ Business Intelligence products

34 Disease Management Resources





39 Recap Brief Disease Management Overview MBSD DM Responsibilities
Competitor DM Data Issues Possible Enhancements to MBSD DM Processes Disease Management Resources

40 Thank you for coming!

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