Eng

DTEC ™

IMPROVING THE QUALITY OF
CARE THROUGH CLAIMS DATA
ANALYSIS
Benjamin Eng, MD, MA

AHQA 2005 Fall Meeting
Quality Measurement and
Improvement in the New
Medicare Prescription Drug
Benefit
November 17, 2005
Washington, D.C.

AGENDA

s Introduction

s What is DTEC™?

s DTEC™ Reports

s Examples from test sites

s Potential Part D implications and applications

© Pfizer Inc. All rights reserved

CHALLENGES FACING
HEALTHCARE TODAY

Many Organizations Face Challenges in
Identifying Gaps in the Quality of
Care for Patient Populations


™
DTEC Supports the Quality Improvement Process
Assess Baseline
Performance

Identify Barriers for
Intervention

Target Individuals for
Intervention

Design and Implement
Intervention

Reassess Performance
Periodically


WHAT IS DTEC™?

s DTEC is a service offered by Pfizer that:
• Uses the customer’s claims data to identify their member populations
with targeted diseases

– First module covers CV diseases (hyperlipidemia, hypertension,
diabetes, ischemic heart disease, congestive heart failure)

• Produces aggregate and member-specific reports

• Provides analysis of the aggregate reports

s DTEC is HIPAA-compliant because no member-specific data
leaves the customer or is viewed by Pfizer


DTEC™ BENEFITS

s DTEC
• Lowers the barriers to improving the quality of care members receive

• Leverages existing data resources to develop reports that facilitate use
of appropriate interventions for targeted groups of members


DATA FIELDS UTILIZED BY DTEC™ SOFTWARE
Professional Services Information Drug Utilization Information

s Member ID s NDC Number
s Claim Number s Member ID
s Claim Line Number s Prescription ID
s From Service Date s Date Filled
s To Service Date s Days Supplied
s Procedure Code s Quantity
s Principal Diagnosis Analyzed
s Additional Diagnoses (4) Over Time
s Place of Service

Enrollment Information Facility Services Information

s Member ID s Member ID
s PCP ID s Claim Number
s Member Gender s Claim Line Number
s Year of Birth s From Date
EMERGENCY

s Effective Date s To Date
s Termination Date s Principal Diagnosis
s Additional Diagnoses (4)
s Place of Service


DTEC™ SUMMARY DATABASE
Claims and Enrollment Data
Data for Population
(4 files)

Continuous Enrollment
DTEC Software

Disease Identification
Summary Dataset
s Demographics
Demographics
s Patterns
Co-morbidities
Complications s Care Improvement
Utilization

Quality Gaps


DTEC™ PATIENT IDENTIFICATION

s Levels of confidence for identifying members with each
targeted disease
• Lenient, Normal and Strict

s Stratifications of disease severity
• Usual, Moderate and High


CONFIDENCE LEVELS FOR DISEASE
IDENTIFICATION ARE INCLUSIVE
(LENIENT INCLUDES MEMBERS CATEGORIZED AS NORMAL AND STRICT)

Lenient Normal Strict


EXAMPLE:
DTEC™ CRITERIA FOR IDENTIFYING
MEMBERS WITH HYPERLIPIDEMIA
Minimum Number of Claims Needed
Criteria Lenient Normal Strict

Hospitalization with Diagnosis or 1 1 1
Diagnosis on Professional Claims
with Different Dates of Service or 1 3 4
Rx for Lipid Lowering Agent or 1 2 4
Diagnosis on Professional Claims
and Rx for Lipid Lowering Agent NA 1/1 3/1


PERCENT OF MEMBERS IN COMMERCIAL HEALTH
PLAN POPULATION IDENTIFIED BY DTEC™ AS
HAVING CV DISEASE
25%

16%
14%

5%
4%

DM Hyperlipid HTN IHD Any CVDs

Lenient Normal Strict
Data on file for 100,000 member commercial health plan
Note: The Lenient category includes members classified as Normal and Strict


DTEC™ SOFTWARE PROCESS
Raw Claims Data
(4 Files)

DTEC Phase 1
Data Audit and Summary

Summary Access Database
(in DTEC)

DTEC Phase 2
Query Database

Demographic Utilization Clinical Care Improvement
Reports Reports Reports Reports

Patient
Drill Down


DTEC™ REPORTS
DTEC Reports CHF
Added
Summary Report

Hypertension Hyperlipidemia Ischemic Heart Diabetes
Disease

6 Reports 6 Reports 6 Reports 6 Reports

1 Care Imp. Report 1 Care Imp. Report 1 Care Imp. Report 1 Care Imp. Report


DTEC™ AGGREGATE DISEASE
POPULATION REPORTS
s Disease prevalence by level of confidence

s Demographics by disease severity

s Comorbidities and complications (2 reports)

s Hospitalizations, ER visits and medical services received

s Medications / medication compliance (2 reports)

s Care Improvement reports


CARE IMPROVEMENT REPORTS

DTEC™ uses specific predefined criteria, called
care improvement algorithms, that identify populations
with opportunities to improve the quality of care
s Aggregate reports show the percentage of the disease
population meeting the care improvement algorithm criteria
s Member specific targeting reports “drill down” and produce
lists of individual members for possible intervention


Sample Claims Based Quality Inferences
Heart Failure Diabetes

s No renal function testing s No HbA1c test

s No lipid profile s No lipid profile

s No cholesterol test after s No renal function testing
hospitalization
s No urine protein test
s Thiazide or loop diuretic, no
s No eye examination
potassium check
s No follow up visit within 45
s ACE or ARB treatment
days of hospitalization
s No follow up visit within 45
s Fewer than 2 visits during
days of discharge
reporting period


Intervention Decision Making Belongs in the
Hands of the Clinician
DTEC Reports CHF
Added
Summary Report

Hypertension Hyperlipidemia Ischemic Heart Diabetes
Disease

6 Reports 6 Reports 6 Reports 6 Reports

1 Care Imp. Report 1 Care Imp. Report 1 Care Imp. Report 1 Care Imp. Report

1 Patient CI Report 1 Patient CI Report 1 Patient CI Report 1 Patient CI Report

Patient Detail Report

CI – Care Improvement

EXAMPLES OF DTEC™
DATA SUMMARIES
FROM THE TEST SITES


PREVALENCE OF CARDIOVASCULAR DISEASES
COMPARED TO BENCHMARK DATA
Percent of Members with CVD
35%

16% 16% 15%
10%
4% 5%
3%

DM Hyperlipid HTN IHD

MCO Benchmark (NHANES III)
Data on file for 200,000 member combined commercial and Medicare health plans


CLASSIFICATION OF MEMBERS WITH
DIABETES BY SEVERITY (N=5,629)

Usual 44% 43% Moderate

13%

Severe



DIABETES COMORBIDITIES
Percent of Members with Diabetes

51%

36%

22%

11% 11%

4% 3%

Hyperlipidemia Ischemic HD Cerebrovascular Dis Acute MI
Hypertension CHF Obesity



COMPLICATIONS IN MEMBERS
WITH DIABETES
Percent of Members
15%

10%

8%
7%

3%
1% 1%

Hypoglycemia Kidney Skin UTI Visual Other Peripheral
Failure Ulcer Loss Eye Neuropathy



CARE IMPROVEMENT OPPORTUNITIES IN
MEMBERS WITH DIABETES
Percent of Members
41%

29% 28%
23%

12% 13%
9%

No HbA1c No Eye No Lipid w/HTN, w/↑Chol, No Hosp F/U <2 Visits/
Exam Profile No ACEI No Statin Year
or βB



EXPERIENCE WITH DTEC™ SERVICE
s Implemented with nearly 20 health plans
• Includes 2 Medicare Advantage plans

s Purpose of DTEC implementation has included
• To measure baseline CV assessment data

• To determine whether to start a CV quality initiative

• To identify patients for a case management quality improvement
program
• To identify patients for a pilot Diabetes intervention program

• To identify patients for a patient CV education program

• To document quality trends over multiple years

• To identify a population of high risk patients to conduct an
adherence study on

Unique Features of DTEC’s Design
s Data audit and integration is automated after data input
files are properly formatted
s Summary dataset is retained while individual claims are
processed and discarded
s Pre-defined reports are based on the summary dataset,
transferring analysis to the desktop
s Population level reporting is linked to member level drill
down reports for targeting interventions
s Clinician level review of drill down patient lists is
supported to verify quality improvement insights


Possible Implications for QIOs and
Medicare Part D Quality
s Claims data can provide insight into the quality of care for
beneficiaries
s The resource burden to integrate and analyze A, B, D and
administrative claims data can be dramatically lowered
leveraging this type of technology
s Similar tools can place analytic power and targeting
capabilities in the hands of Quality Improvement
Organizations to work with Medicare providers
s Data analytics can only support clinical decision making.
Clinical decision making belongs in the hands of the
clinician.


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