DATA DETECTIVES: PROMISING STRATEGIES TO IDENTIFY …

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DATA DETECTIVES: PROMISING STRATEGIES TO IDENTIFY SUSPECT CLIENT RECORDS IN OREGON'S IMMUNIZATION INFORMATION SYSTEM (ALERT IIS) Andrew Osborn, Oregon Sentinel Project Coordinator Deborah Richards, Oregon ALERT IIS Data Quality Coordinator

Transcript of DATA DETECTIVES: PROMISING STRATEGIES TO IDENTIFY …

Page 1: DATA DETECTIVES: PROMISING STRATEGIES TO IDENTIFY …

DATA DETECTIVES: PROMISING

STRATEGIES TO IDENTIFY SUSPECT CLIENT

RECORDS IN OREGON'S IMMUNIZATION

INFORMATION SYSTEM (ALERT IIS)

Andrew Osborn, Oregon Sentinel Project Coordinator

Deborah Richards, Oregon ALERT IIS Data Quality Coordinator

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Background

� ALERT Immunization Information System (IIS)

� Started in 1996 as statewide childhood registry

� Lifespan in 2008

� ~6 million client records

� ~350k new in 2014

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It’s Raining Data

ALERT IIS

Public Health

Other IIS

CCOs & HealthPlans

Pharmacies

Clinics & Hospitals

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Record Merging

� Goal: Minimize duplicate records in system by proactively merging records

DATA IN

DEDUPLICATION

AFTER MERGE

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Record Merging

� Automatic client and immunization record merging

� Targeted Manual Merging

� Future Enhancements of match algorithms and processes

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Data Scene Investigation

Fragmentation Data Quality

Sparse Data

Complex Names

Move away

Death

Content

Frequency

Accuracy

Migration

� ~8% more clients over population estimates

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CDC NCIRD* Sentinel Program

� Project supported by Center for Disease Control and Prevention

� Six contiguous counties

� Monitor vaccine trends

� Conduct evaluations

* National Center for Immunization and Respiratory Diseases

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CDC Sentinel Program

� Oregon one of six CDC Sentinel sites across US

� Leading national data quality improvement effort

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There’s a Method for that…

� Statistical methods exist…

…but are they enough?

� The purpose of investigating records:

� To enhance existing statistical methods

� To enhance overall ALERT IIS data quality

� To make record resolution more efficient and effective

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And more help is on the way…

� Major improvements in demographic field population:

� More fields are populated

� Populated more frequently

� Populated more accurately

� Of interest today:

� Numeric fields

� Address field

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Leverage Numeric Data Fields

Table 1: Likelihood that selected fields were populated among client records that were

successfully merged (Oregon Sentinel data, n=2,876)

Odds Ratio

Traditional Merging Fields

Mother’s First Name 1.23

Mother’s Maiden Name 1.20

Client's Middle Name 1.01

Odds Ratio

Numerical fields

Medicaid ID 3.78

Encrypted Social Security Number 2.99

Phone Number 2.15

Names are good… numbers are better

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Leverage Address Field

0.00%

1.00%

2.00%

3.00%

4.00%

5.00%

6.00%

7.00%

8.00%

9.00%

10.00%

0.00%

1.00%

2.00%

3.00%

4.00%

5.00%

6.00%

7.00%

8.00%

9.00%

10.00%

Percent of clients with only one vaccination recorded in ALERT IIS

Ages 4-12

Complete

Address

Complete

Address

Bad

Address

Bad

Address

Kids with bad addresses: it starts out bad… and gets worse

Ages 13-17

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Leverage Migration Patterns

Every year, some kids move out of Oregon…

… and every year, some kids’ shots stop showing up in ALERT IIS…

…coincidence???

What else?

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Leverage Migration Patterns

Discount Rate

Calculate discount rate by comparing last update figures with known state migration patterns

Years since update

Determine years since last update for each record

Difference between date record entered system vs. since last update date

National Standards

Utilize National DQ Standards Recommendations on record inactivation following period of inactivity, other factors

Match pattern of moving to vaccination pattern:

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Leverage Migration Patterns

7.2

5.8

5.2

4.4

3.0

0.0

1.0

2.0

3.0

4.0

5.0

6.0

7.0

8.0

Perc

en

tage o

ver

Cen

sus

How close can we get to Census population estimates? It depends on which method(s) we use.

Discount Rate National

Standards

Subtract Number of

Clients Moved From

Each Years

Discount Rate +

National Standards

National

Standards +

Subtract by Year

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Sentinel Next Steps

� All methods presented promise to improve accuracy of rates calculations using ALERT IIS data, and can help target suspect records for resolution

� Project in its infancy but momentum is building

� National white paper on IIS data quality will result

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Thank you

Deborah RichardsALERT IIS Data Quality Coordinator

[email protected]

Andrew OsbornOregon Sentinel Project [email protected]