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Application of Predictive Modeling to Identify, Stratify, and Triage Members in Care Management Programs: A Health Plan Case Study Soyal Momin, MS, MBA Sylvia Sherrill, RN, MS Lelis Welch, RNC, CCM Judy Slagle, RN, MPA Terence Shea, PharmD Steven Coulter, MD

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Page 1: Application of Predictive Modeling to Identify, Stratify, and Triage Members in Care Management Programs: A Health Plan Case Study Soyal Momin, MS, MBA

Application of Predictive Modeling to Identify, Stratify, and Triage Members in

Care Management Programs: A Health Plan Case Study

Soyal Momin, MS, MBA

Sylvia Sherrill, RN, MS

Lelis Welch, RNC, CCM

Judy Slagle, RN, MPA

Terence Shea, PharmD

Steven Coulter, MD

Page 2: Application of Predictive Modeling to Identify, Stratify, and Triage Members in Care Management Programs: A Health Plan Case Study Soyal Momin, MS, MBA

Outline

• Historical View: Case Management at BCBST

• Concept: Next Generation Care Management (NGCM)

• Implementation and Evaluation of NGCM

• Enhancements/Improving Process Efficiency

Page 3: Application of Predictive Modeling to Identify, Stratify, and Triage Members in Care Management Programs: A Health Plan Case Study Soyal Momin, MS, MBA

History• Identifying Members for Case Management

– Referrals from• Internal Sources• External Sources• An internally developed ICD9 Trigger list

– The ICD9 Trigger list included Asthma, Diabetes, High Risk OB, AIDs, Cancer, CHF, COPD etc

• Case managers workload– 103/CM/Month

• DCG implementation validation revealed missed opportunities for case management

Page 4: Application of Predictive Modeling to Identify, Stratify, and Triage Members in Care Management Programs: A Health Plan Case Study Soyal Momin, MS, MBA

Base Year and Year-2 Risk Profile of Members Referred to Case ManagementCommercial Line of Business

2,1201,926

2,087

4,124

6,170

4,2444,117

2,683

4,543

840

0

1,000

2,000

3,000

4,000

5,000

6,000

7,000

Risk Level 1 ($0-1K) Risk Level 2 ($1K-$5K) Risk Level 3 ($5K-$10K) Risk Level 4 ($10K-$25K) Risk Level 5 (>25K)

Base Year (04/01-03/02) Year-2 (04/02-03/03)

Current methodology of identifying members for case management (Trigger List) seems to be working

Page 5: Application of Predictive Modeling to Identify, Stratify, and Triage Members in Care Management Programs: A Health Plan Case Study Soyal Momin, MS, MBA

Year-2 Detailed Risk Profile of Members NOT Referred to Case Management Commercial Line of Business

907

303

88

27 24

872

0

100

200

300

400

500

600

700

800

900

1000

$25,000-$30,000 $30,000-$40,000 $40,000-$50,000 $50,000-$60,000 $60,000-$70,000 $70,000-$9,999,999

Year-2 (04/02-03/03)

Light Touch

Page 6: Application of Predictive Modeling to Identify, Stratify, and Triage Members in Care Management Programs: A Health Plan Case Study Soyal Momin, MS, MBA

Year-2 Case Mix Index of Members NOT Referred to Case ManagementCommercial Line of Business

0.24

1.13

17.04

6.87

3.23

0

2

4

6

8

10

12

14

16

18

20

22

24

Risk Level 1 ($0-1K) Risk Level 2 ($1K-$5K) Risk Level 3 ($5K-$10K) Risk Level 4 ($10K-$25K) Risk Level 5 (>25K)

Year-2 (04/02-03/03)

Page 7: Application of Predictive Modeling to Identify, Stratify, and Triage Members in Care Management Programs: A Health Plan Case Study Soyal Momin, MS, MBA

Next Generation Care Management: One size does not fit all

Segmentation % Members % Cost

Healthy Group 40% 0%

Worried Well 52% 45%

Chronically Ill 7% 30%

Catastrophic 1% 25%

Page 8: Application of Predictive Modeling to Identify, Stratify, and Triage Members in Care Management Programs: A Health Plan Case Study Soyal Momin, MS, MBA

Next Generation Care Management:Triage Guidelines

Segmentation DxCG Risk Level

Management Type

Healthy Group; Worried Well

1 – 2

Lifestyle/Health

Counseling

Chronically Ill 3 – 4 Refer to Care Coordination Unit

Catastrophic

5

Refer to Catastrophic Case Management

Page 9: Application of Predictive Modeling to Identify, Stratify, and Triage Members in Care Management Programs: A Health Plan Case Study Soyal Momin, MS, MBA

Lifestyle/Health Counseling for Healthy and Worried Well:

• Information on disease/condition– Web resources– Pamphlets– Telephonic health library

• Encouragement to take more active role/accountability

Page 10: Application of Predictive Modeling to Identify, Stratify, and Triage Members in Care Management Programs: A Health Plan Case Study Soyal Momin, MS, MBA

Care Coordinationfor Chronically Ill

• Telephonic coordination with members and their providers

• Ensures appropriate treatments and pharmaceuticals

• Six different programs included in this model

Page 11: Application of Predictive Modeling to Identify, Stratify, and Triage Members in Care Management Programs: A Health Plan Case Study Soyal Momin, MS, MBA

Care Coordination Programs

• Pharmacy Care Management

• Emergency Room (ER) Visits Management

• Centers of Excellence (COE)

• Transition of Care

• Condition Specific Care Coordination

• Disease Management

Page 12: Application of Predictive Modeling to Identify, Stratify, and Triage Members in Care Management Programs: A Health Plan Case Study Soyal Momin, MS, MBA

Care Coordination Program # 1

• Pharmacy Care Management for Specialty Populations

– Pharmacy Case Management Programs:• Hepatitis C• AMI-Beta Blocker• Migraine• Polypharmacy

Page 13: Application of Predictive Modeling to Identify, Stratify, and Triage Members in Care Management Programs: A Health Plan Case Study Soyal Momin, MS, MBA

Care Coordination Program # 2

• Emergency Room (ER) Visits Management Program

– Monthly report identify ER “frequent flyers”– Contacted by a nurse with psychiatric

training– Clinical counseling and guidance– Discuss options of care with goal to reduce

ER Visits

Page 14: Application of Predictive Modeling to Identify, Stratify, and Triage Members in Care Management Programs: A Health Plan Case Study Soyal Momin, MS, MBA

Care Coordination Program # 3

• Centers of Excellence (COE) Program– Identify providers based on utilization and quality of

care indicators (CQI using ETGs) and input from regional staff

• Asthma• Diabetes• CHF• COPD• CAD

– Can be used to refer/steer members to providers considered COE

Page 15: Application of Predictive Modeling to Identify, Stratify, and Triage Members in Care Management Programs: A Health Plan Case Study Soyal Momin, MS, MBA

Care Coordination Program # 4

• Transition of Care Program– Formerly known as discharge planning, make

sure members are in appropriate setting for treatment

– Assist facility, physician, and member with transition

• Lower ALOS for per diem admissions• Better outcome for DRG admissions• Reduce re-admissions• Smooth transition of care

Page 16: Application of Predictive Modeling to Identify, Stratify, and Triage Members in Care Management Programs: A Health Plan Case Study Soyal Momin, MS, MBA

Care Coordination Program # 5

• Condition Specific Care Coordination– Assess and advise program with one time

follow-up• CAD• CHF• COPD• Asthma• Diabetes• Hypertension• GI disorders

Page 17: Application of Predictive Modeling to Identify, Stratify, and Triage Members in Care Management Programs: A Health Plan Case Study Soyal Momin, MS, MBA

Care Coordination Program # 6

• Disease Management programs– Carved out to LifeMasters Supported

SelfCare, Inc.• CAD• CHF• COPD• Asthma• Diabetes

Page 18: Application of Predictive Modeling to Identify, Stratify, and Triage Members in Care Management Programs: A Health Plan Case Study Soyal Momin, MS, MBA

Next Generation Care Management:Catastrophic Case Management

• Directed to members with– Terminal illness– Major trauma– Cognitive/physical disability– High-risk condition– Complicated care needs

• Systematic process of assessing, planning, coordinating, implementing, and evaluation of care

Page 19: Application of Predictive Modeling to Identify, Stratify, and Triage Members in Care Management Programs: A Health Plan Case Study Soyal Momin, MS, MBA

Next Generation Care Management:Implementation

• MCSource

• Predictive Modeling Using– DCG– ETG

• Rolling 12 Months DCG Explanation Prospective Model

• ETG Cost to Supplement DCG Prediction

Page 20: Application of Predictive Modeling to Identify, Stratify, and Triage Members in Care Management Programs: A Health Plan Case Study Soyal Momin, MS, MBA

Better Understanding of Predictive Modeling

• Do Predictive models work like a crystal

ball?

• Models do not predict a disease (ICD-9)

• Helps quantify a disease

• Provides early warning for certain

diseases with high future resource

requirements

Page 21: Application of Predictive Modeling to Identify, Stratify, and Triage Members in Care Management Programs: A Health Plan Case Study Soyal Momin, MS, MBA

• Clinical Profile of Member XYZ

• Diagnosed with CHF (Date: 10/01/2002)

• Diagnosed with Diabetes (Date: 10/30/2002)

• Our traditional methods might refer this member for Case

Management (CM) some time in 2003

• DCG/ETG approach will identify this member for CM in

11/2002 or 12/2002

Example of Predictive Modeling

Page 22: Application of Predictive Modeling to Identify, Stratify, and Triage Members in Care Management Programs: A Health Plan Case Study Soyal Momin, MS, MBA

Next Generation Care Management:Program Evaluation

• Medication cost avoidance and members’ compliance

– Hepatitis C ($1.5M/Year)– Beta Blockers post AMI ($1.3M/Year)– Migraine care management

• Member and provider satisfaction

• CM staff turnover

• Triaging efficiencies

Page 23: Application of Predictive Modeling to Identify, Stratify, and Triage Members in Care Management Programs: A Health Plan Case Study Soyal Momin, MS, MBA

Next Generation Care Management:Program Evaluation

Total Number of Members

(04/03 - 03/04)

• Lifestyle/Health Counseling - 1,555

• Care Coordination - 7,229

• Catastrophic Case Mgmt. - 13,622

• Number of Cases/CM/Month=76/CM/Month

Page 24: Application of Predictive Modeling to Identify, Stratify, and Triage Members in Care Management Programs: A Health Plan Case Study Soyal Momin, MS, MBA

Next Generation Care Management:Program Enhancements

• Developed SQL database containing DCG and ETG information

– Improved processes/workflow– Easy and continuous access– Better documentation

Page 25: Application of Predictive Modeling to Identify, Stratify, and Triage Members in Care Management Programs: A Health Plan Case Study Soyal Momin, MS, MBA

Next Generation Care Management:Program Enhancements

Page 26: Application of Predictive Modeling to Identify, Stratify, and Triage Members in Care Management Programs: A Health Plan Case Study Soyal Momin, MS, MBA

Next Generation Care Management:Program Enhancements

Page 27: Application of Predictive Modeling to Identify, Stratify, and Triage Members in Care Management Programs: A Health Plan Case Study Soyal Momin, MS, MBA

Conclusions

• More scientific/standardized approach• Able to touch more lives efficiently• Well accepted by our case managers• NGCM has helped

– streamline our processes– better manage case managers case load

• Provide “Peace of Mind” to our members and clients