Onpoint Health Data, Minnesota Health Care Claims …€¦ · ME101 Subscriber Last Name MC101 Subscriber Last Name PC101 Subscriber Last Name ... •Group name –tracking movement

9/30/2014

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Title XxSubtitle Xx

Presenter, TitleDate

1Proprietary and Confidential 1

Minnesota Health Care Claims Reporting System MN APCD Stakeholder Workgroup

Minnesota Department of Health09/30/2014

Formed in 1976 as an independent, nonprofit

Based in Portland, ME

Record of innovation

1980s. Data organization supporting Dr. J. Wennbergs small-area variation studies

1995. Built first-of-its-kind, multi-payer claims database for ME statewide business coalition

2002. Developed APCD for State of Maine

2006. First to integrate Medicare claims data into APCD

2010. 3-state APCD integration for landmark variation study

2013. Data organization behind Dartmouth Institutes Pediatric Atlas & Total Cost of Care studies

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About Onpoint Health Data

MN APCD Stakeholder Workgroup 2014

9/30/2014

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About Onpoint Health Data

Depth of health data integration expertise

35 years experience working with healthcare data

20 years experience integrating, analyzing claims data

Extensive Medicare and Medicaid integration experience

Dental claims, provider data integration experience

Extensive data linkage expertise: EHR, clinical registry, public health registry

Expert in data enhancements designed to support analytics: claim consolidation, disease flags, i/p stay identifiers, diagnostic and procedure groupers, provider attribution, risk scoring, HEDIS and other performance measures

3MN APCD Stakeholder Workgroup 2014

About Onpoint Health DataSolution: Onpoint CDM

Scalable, efficient, in production for 10+ years

Continuous enhancement over six statewide APCD implementations

Rigorous QA procedures

More than 200 carriers submitting monthly

More than 10M lives and 10TB of data

Data encrypted in motion and at rest, zero data breaches in more than 30 years and 9 billion records

Best of breed COTS and open-source technologies


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Dartmouth Pediatric AtlasBased on Onpoints Integration of APCDs from ME, NH, & VT

MN APCD Stakeholder Workgroup 2014 5


Diagnostic Imaging & Prescription Drug Use From the APCD-based Dartmouth Pediatric Atlas

Map 32. Percent of children

filling at least one prescription

for an ADHD medication

among hospital service areas

(2007-10)

Map 25. Head CT scans per

1,000 children among hospital

service areas (2007-10)

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Potentially Avoidable ED Use From the APCD-based Tri-State Variation Study

Burlington(16.1)

Caribou(136.3)

Across 67 hospital service areas in northern New England, population-based rates varied8-fold for the commercial population.



Medical Home EvaluationVermont Blueprint for Health

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Primary Care Practice Profiles

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Dartmouth Total Cost of Care Study


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Understanding MHCCRSAPCDs versus MPCDs


State Commercial TPAs/Self-Funded Medicaid Medicare

All-Payer Claims Databases (APCDs)

MA Y Y Y Y

MD Y Y Y Y

ME Y Y Y Y

MN Y Y Y Y

NH Y Y Y Y

RI Y Y Y Y

VT Y Y Y Y

Multi-Payer Claims Databases (MPCDs)

CO Y N Y N

KS Y N Y N

UT Y Y N N

CA Y Y N Y

WI Y Y Y N

WA Y Y Y N

TN Y Y Y N

Understanding MHCCRS Data Submitters

Payer registration

All health plans, TPAs, and PBMs covering MN residents

Annual registration each April 1

2014: 241 registered payers

Submitters

Paid at least $3M in institutional, professional, and/or pharmacy claims

$300K if PBM

Evaluated annually during registration

2014: 90 submitters


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Understanding MHCCRS APCD statistics

In production for 5+ years

Data from 2008 onward

Collection of enrollment data, medical claims, and pharmacy claims files

Defined by statutes and finalized through the public rule making process

More than 18,600 submissions

Almost 4.5 billion records submitted


Number of Submitters

Count Total Eligibility Data Medical Claims Pharmacy Claims

Cumulative 111 100 84 77

Current 90 85 66 64

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Our Solution: Onpoint CDMwww.onpointcdm.org


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Data Quality and Validation - Intake

Onpoint uses over 500 DQ checks

Data element level

Within a file, across data elements

Across files

Trending


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Data Quality and Validation - IntakeLoad Threshold Reporting


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Data Quality and Validation - IntakeData Quality Reporting


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Data Quality and Validation - IntakeTrend Reporting


Dashboard

Membership Detail

Module

Claims Paid Detail

Module

Total Claims Supported

by Eligibility Module

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Data Quality and Validation - IntakePercent of required resubmissions - MHCCRS


2009 2010 2011 2012 2013

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

one submission

resubmissions

Protecting Patient PrivacyHashing data

Per the administrative rule, PII (personally identifiable information) is required to be de-identified

Hashing versus encryption

Hashing: one-way, permanent, and nonreversible

Encryption: two-way, usually need a key to decrypt

Hashing using SHA-512 transforms any data element into a 128-character string

Performed by submitters prior to submission to Onpoint

Validations ensure designated fields are hashed prior to load


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Protecting Patient PrivacyHashed Data Elements


Eligibility File Medical Claims Pharmacy Claims

ME009 Plan-Specific Contract # MC008 Plan-Specific Contract # PC008 Plan-Specific Contract #

ME014 Member Date of Birth MC013 Member Date of Birth PC013 Member Date of Birth

ME101 Subscriber Last Name MC101 Subscriber Last Name PC101 Subscriber Last Name

ME102 Subscriber First Name MC102 Subscriber First Name PC102 Subscriber First Name

ME103 Subscriber Middle Initial MC103 Subscriber Middle Initial PC103 Subscriber Middle Initial

ME104 Member Last Name MC104 Member Last Name PC104 Member Last Name

ME105 Member First Name MC105 Member First Name PC105 Member First Name

ME106 Member Middle Initial MC106 Member Middle Initial PC106 Member Middle Initial

Data Standardization and Processing

Creating a unique patient ID

Creating a unique provider ID

Standardization

Consolidation of claims


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Data Standardization and ProcessingCreating a Unique Patient ID an example


Method First Name Last Name SSN DOB Contract # Unique ID

Direct Identifiers

John Smith 3/15/1964 BCBS456 123

Jon Smith JR 3/15/1964 AETNA123 123

Hashed Identifiers

A1G584DD KU5D4S3R K8G5D3D2 L5B2HJJF 123

TH2SS5F31 H5D3D15W K8G5D3D2 W5RF2GH7 456

Collection of SSN

A1G584DD KU5D4S3R JT3S1V58 K8G5D3D2 L5B2HJJF 123

TH2SS5F31 H5D3D15W JT3S1V58 K8G5D3D2 W5RF2GH7 123

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Data Standardization and ProcessingUnique Patient ID Medical enrollment survival analysis


100%

93%

100%

87%

93%

100%

79%83%

89%

0

1,000,000

2,000,000

3,000,000

4,000,000

5,000,000

6,000,000

2009 2010 2011

2009 2010 2011 2012

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Data Standardization and ProcessingCreating a Unique Provider ID

Data Standardization and ProcessingStandardization


NCPDP Standards Relationship (Pharmacy)

Description Code

Self 01

Spouse 02

Child 03

Other 04

X12 Standards Relationship (Medical & Eligibility)

Code Description

18 Self

01 Spouse

19 Child

G8 Other

Data elements are standardized across all data sources for consistency in analysis and reporting

All crosswalks are stored in reference tables (e.g., relationship codes, dependency status, product codes, gender codes, etc.)

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Data Standardization and ProcessingConsolidation example simple aggregation


Claim # Claim Status Paid Date CPT Code Charge Paid

ABC Primary 02/03/2014 99214 250.00 135.00

ABC Reversal 03/24/2014 99214 -250.00 -135.00

ABC Primary 03/24/2014 99214 250.00 155.00

ABC Primary 03/24/2014 99214 250.00 155.00

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Value adds

Claim type

Inpatient discharge grouping

Reference tables / referential integrity

Additional post-consolidation quality assurance

Groupers

APCs for outpatient hospital

DRGs for inpatient hospital

MS-DRGs

APR-DRGs

Data Enhancements and DeliveryExtracts


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Challenges and Recommendations

Additional patient identifiers (SSN) Unique Patient ID

Group name tracking movement of large groups

Primary insurance indicator coordination of benefits (COB)

Discharge date hospital stays, readmissions

Present on admission improved MS-DRG assignment

Claim status (medical)- COB, denials

Pharmacy Location in/out of state


Data Quality Reporting

Due for completion November 2014

Collaborative effort MDH & Onpoint

Includes overview of Onpoints data quality assurance steps

Includes trending and data quality analysis for enrollment, medical claims and pharmacy claims

Analysis based on most current extract

Will update semi-annually with delivery of extracts

QA cannot be static


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Documents

Onpoint Health Data, Minnesota Health Care Claims …€¦ · ME101 Subscriber Last Name MC101 Subscriber Last Name PC101 Subscriber Last Name ... •Group name –tracking movement