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.

© Pfizer Inc. All rights reserved

AGENDA

Introduction

What is DTEC™?

DTEC™ Reports

Examples from test sites

Potential Part D implications and applications


CHALLENGES FACING HEALTHCARE TODAY

Many Organizations Face Challenges in Identifying Gaps in the Quality of

Care for Patient Populations

Many Organizations Face Challenges in Identifying Gaps in the Quality of

Care for Patient Populations


DTEC Supports the Quality Improvement Process

Assess Baseline Performance

Assess Baseline Performance

Identify Barriers for Intervention

Identify Barriers for Intervention

Target Individuals for Intervention

Target Individuals for Intervention

Design and Implement Intervention

Design and Implement Intervention

Reassess Performance Periodically

Reassess Performance Periodically

™


WHAT IS DTEC™?

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

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


DTEC™ BENEFITS

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

Member ID PCP ID Member Gender Year of Birth Effective Date Termination Date

Member ID Claim Number Claim Line Number From Service Date To Service Date Procedure Code Principal Diagnosis Additional Diagnoses (4) Place of Service

NDC Number Member ID Prescription ID Date Filled Days Supplied Quantity

Member ID Claim Number Claim Line Number From Date To Date Principal Diagnosis Additional Diagnoses (4)

Place of Service

Professional Services InformationProfessional Services Information Drug Utilization InformationDrug Utilization Information

Facility Services InformationFacility Services InformationEnrollment InformationEnrollment Information

Analyzed Over Time Analyzed

Over Time

EMERGENCY


DTEC™ SUMMARY DATABASE

Summary Dataset

Claims and Enrollment Data Data for Population

(4 files)

Claims and Enrollment Data Data for Population

(4 files)

Demographics

Patterns

Care Improvement

DT

EC

So

ftw

are

Continuous EnrollmentContinuous Enrollment

Disease IdentificationDisease Identification

DemographicsCo-morbidities Complications

Utilization

DemographicsCo-morbidities Complications

Utilization

Quality GapsQuality Gaps


DTEC™ PATIENT IDENTIFICATION

Levels of confidence for identifying members with each targeted disease

• Lenient, Normal and Strict

Stratifications of disease severity

•Usual, Moderate and High


CONFIDENCE LEVELS FOR DISEASE IDENTIFICATION ARE INCLUSIVE

LenientLenient NormalNormal StrictStrict

(LENIENT INCLUDES MEMBERS CATEGORIZED AS NORMAL AND STRICT)


EXAMPLE: DTEC™ CRITERIA FOR IDENTIFYING MEMBERS WITH HYPERLIPIDEMIA

Hospitalization with Diagnosis or

Diagnosis on Professional Claimswith Different Dates of Service or

Rx for Lipid Lowering Agent or

Diagnosis on Professional Claimsand Rx for Lipid Lowering Agent

1

4

4

3/1

1

3

2

1/1

1

1

1

NA

Criteria StrictNormalLenient

Minimum Number of Claims Needed


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

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

Lenient Normal Strict

DM

5%

Hyperlipid

14%

HTN

16%

IHD

4%

Any CVDs

25%


DTEC™ SOFTWARE PROCESS

Care Improvement Reports

Care Improvement Reports

DTEC Phase 2Query DatabaseDTEC Phase 2

Query Database

Summary Access Database(in DTEC)

Summary Access Database(in DTEC)

DTEC Phase 1Data Audit and Summary

DTEC Phase 1Data Audit and Summary

Raw Claims Data(4 Files)

Raw Claims Data(4 Files)

Demographic Reports

Demographic Reports

Utilization Reports

Utilization Reports

PatientDrill Down

PatientDrill Down

Clinical ReportsClinical Reports


1 Care Imp. Report1 Care Imp. Report 1 Care Imp. Report1 Care Imp. Report 1 Care Imp. Report1 Care Imp. Report1 Care Imp. Report1 Care Imp. Report

HypertensionHypertension HyperlipidemiaHyperlipidemia Ischemic Heart Disease

Ischemic Heart Disease

DiabetesDiabetes

6 Reports6 Reports 6 Reports6 Reports 6 Reports6 Reports 6 Reports6 Reports

Summary ReportSummary Report

DTEC ReportsDTEC Reports

DTEC™ REPORTS

CHF Added


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

Demographics by disease severity

Comorbidities and complications (2 reports)

Hospitalizations, ER visits and medical services received

Medications / medication compliance (2 reports)

Care Improvement reports


CARE IMPROVEMENT REPORTS

Aggregate reports show the percentage of the disease population meeting the care improvement algorithm criteria

Member specific targeting reports “drill down” and produce lists of individual members for possible intervention

DTEC uses specific predefined criteria, called care improvement algorithms, that identify populations with opportunities to improve the quality of care


Sample Claims Based Quality Inferences

No renal function testing

No lipid profile

No cholesterol test after hospitalization

Thiazide or loop diuretic, no potassium check

ACE or ARB treatment

No follow up visit within 45 days of discharge

No HbA1c test

No lipid profile

No renal function testing

No urine protein test

No eye examination

No follow up visit within 45 days of hospitalization

Fewer than 2 visits during reporting period

Heart FailureHeart Failure DiabetesDiabetes


Intervention Decision Making Belongs in the Hands of the Clinician

1 Patient CI Report1 Patient CI Report

1 Care Imp. Report1 Care Imp. Report


Patient Detail ReportPatient Detail Report


1 Care Imp. Report1 Care Imp. Report


1 Care Imp. Report1 Care Imp. Report1 Care Imp. Report1 Care Imp. Report

HypertensionHypertension HyperlipidemiaHyperlipidemia Ischemic Heart Disease

Ischemic Heart Disease

DiabetesDiabetes

6 Reports6 Reports 6 Reports6 Reports 6 Reports6 Reports 6 Reports6 Reports

Summary ReportSummary Report

DTEC ReportsDTEC Reports

CI – Care Improvement

CHF Added


EXAMPLES OF DTEC DATA SUMMARIES FROM THE TEST SITES


5%

10%

16% 16%

3%4%

35%

15%

DM Hyperlipid HTN IHD

MCO Benchmark (NHANES III)

PREVALENCE OF CARDIOVASCULAR DISEASES COMPARED TO BENCHMARK DATAPercent of Members with CVD

Data on file for 200,000 member combined commercial and Medicare health plans


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

43%43%

13%13%

44%44%Usual Moderate

Severe



DIABETES COMORBIDITIES

11%

3%4%

11%

36%

51%

22%

Hyperlipidemia

Hypertension

Ischemic HD

CHF

Cerebrovascular Dis

Obesity

Acute MI

Percent of Members with Diabetes



COMPLICATIONS IN MEMBERS WITH DIABETES

10%

3%

15%

7%

1%

8%

1%

Hypoglycemia Kidney Failure

Skin Ulcer

UTI Visual Loss

Other Eye

Peripheral Neuropathy

Percent of Members



CARE IMPROVEMENT OPPORTUNITIES IN MEMBERS WITH DIABETES

23%

9%

13%

28%

12%

41%

29%

No HbA1c No Eye Exam

No Lipid Profile

w/HTN, No ACEI

or B

w/Chol, No Statin

No Hosp F/U <2 Visits/Year

Percent of Members



EXPERIENCE WITH DTEC™ SERVICE Implemented with nearly 20 health plans

• Includes 2 Medicare Advantage plans

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

Data audit and integration is automated after data input files are properly formatted

Summary dataset is retained while individual claims are processed and discarded

Pre-defined reports are based on the summary dataset, transferring analysis to the desktop

Population level reporting is linked to member level drill down reports for targeting interventions

Clinician level review of drill down patient lists is supported to verify quality improvement insights


Possible Implications for QIOs and Medicare Part D Quality Claims data can provide insight into the quality of

care for beneficiaries

The resource burden to integrate and analyze A, B, D and administrative claims data can be dramatically lowered leveraging this type of technology

Similar tools can place analytic power and targeting capabilities in the hands of Quality Improvement Organizations to work with Medicare providers

Data analytics can only support clinical decision making. Clinical decision making belongs in the hands of the clinician.

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