Roland Gamache, Ph.D., MBA Director, State Health Data Center Indiana State Department of Health.

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Presentation transcript:

Roland Gamache, Ph.D., MBA Director, State Health Data Center Indiana State Department of Health

Purpose Provide more timely and accurate public health information. Required for essential public health functions and emergency events Improve the health resiliency of our communities Improve the quality of the health encounter More effectively deliver health care services Bi-directional health information exchange with clinicians Establish a level of trust required for health professionals to have confidence that the linked data actually represents the health information for the individual patient Continually improve the overall health status of the community

Status Methodology correctly links Over 99.8% of the birth/death records Over 99% of the hospital discharge records, Over 98% of the New Born Screening records

Not So Hidden Agenda Establish a discussion between clinical health and public health regarding matching event data related to an individual Form a workgroup in one of the CoP regarding matching records for public health Individual Environment

Topics to Cover For a child-health profile Probabilistic and Rules-based matching Exceptions SSN’s Names Matching process Summary

Child Health Profile Use Case Births Deaths New Born Screening Fetal Deaths

Probabilistic and Rules-based Matching Rules are to handle the nuances of the data to be matched Twins George Foreman Special names Rules can be applied pre-processing, during processing or post-processing Probability of a match based on “Keys”

Exceptions Multiple births – First name – Sometimes sex – Time of birth (TOB) Name change – Usually last name Name unknown – Blank – Boy or Girl – Unknown – Baby boy or Baby Girl – Infant – Male – Female

SSN Old numbers Coding Regional issues

First Three Numbers of the SSN

Pre-processing Remove spaces, punctuation Minimum data to establish identity All cap’s Remove non-sense names Infant Boy Girl (Male and Female?)

Key 1 SSN First Name (1) Last Name (6) Mothers Maiden Probability match with variation allowed on the first name

Key 2 SSN First Name (6) Maiden Name No date of birth or date incorrect Last name change

Key 3 Date of Birth SSN Name change Alias Corrupt name data Additional information should already be in the database

Key 4 Date of birth Time of birth Last name (6) First name (6) Middle name (1) Twins Similar first names

Key 5 Date of birth Time of birth First name (6) Mother’s maiden name Same as Key 4 but with name change

Key 6 Date of birth First name Maiden name To match mother’s records

Key 7 Date of birth First name (6) Last name (6) Sex Old or no SSN

Post Processing First last name (A) Second last name (B) Target last name (C) More multiple births Additional data collection C equals A+B C contains A C contains B

Summary Need for public health/health delivery discussion on record matching objectives Public health group (CoP or workgroup) to determine best practices for all of the different data streams Dissemination of “standard of business practice”

Evaluation and Quality Measures Over 3 million individuals in our database Evaluated against birth/death cohort sent to the NCHS NBS records Lead (Pb) screening Policy and Epi studies