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Overview of General Prevalence Estimates

CDC Site Visit at Emory CHD Surveillance Cooperative Agreement Prevalence Estimates September 25, 2013 Carol Hogue, PhD, MPH Cheryl Raskind-Hood, MS, MPH. Overview of General Prevalence Estimates. 5 counties* within Metropolitan Atlanta Population in 2010, ages 18 – 64: ~ 3 million**

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Overview of General Prevalence Estimates

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  1. CDC Site Visit at EmoryCHD Surveillance Cooperative Agreement Prevalence EstimatesSeptember 25, 2013Carol Hogue, PhD, MPHCheryl Raskind-Hood, MS, MPH

  2. Overview of General Prevalence Estimates • 5 counties* within Metropolitan Atlanta • Population in 2010, ages 18 – 64: ~ 3 million** • 51% non-Hispanic White, 40% non-Hispanic Black • Living in same house > 1 year ~ 80% • Resident who meets case definition with at least one encounter , 2008-2010 • Hospital • Outpatient clinic • Medicaid (ResDAC) • Presumed alive on January 1, 2010 and in age range (11-64) • GA Vital Records (Mortality 2008 – 2010) * The five counties are within the Metropolitan Atlanta area and include Fulton, Cobb, Dekalb, Gwinnett, & Clayton. ** U.S. Census 2010.

  3. Map of Five Counties

  4. Planned Strategy1: Population-Based Estimate MACDP Not Linked to Data Sources includes GA Vital Records

  5. Data Sources for Population-based Prevalence • Hospitals and Clinics Included • Emory Healthcare: Emory HC (EHC) • Children’s Healthcare of Atlanta: CHOA • Sibley Heart Center: Sibley • Grady Health • Selected private providers: • Pediatric Cardiology Services (PCS) • To-date: Deduplicated CHOA & Sibley (2008-2010) • Merged by Last Name, First Name, DOB, Sex & County • Retained all CHD Dx Codes • ~4700 after adolescent merge • Few county differences • Use of LexisNexis for validation

  6. Variables Used to Link Various Data Sources * May receive SSN to Bene_ID crosswalk from ResDAC

  7. Linkage for Population-based CHD Adolescents & Adults Step 1. Link GA death records to sources to determine survivors. Deduplicate. DATA SOURCES Step 2. Create datasets & identify survivors & non-survivors. Step 4. Upload limited dataset to CDC via SAMS. Step 3. Create limited datasets with specific core vars & PHI removed. Emory HC 2008-2010 Adult CHD Dataset Grady Health 2008-2010 Adolescent& Adult CHD Datasets Adolescent& Adult CHD Datasets ResDAC 2008-2009 Adolescent& Adult CHD Datasets GA Death Records 2008-2010 Adolescent CHD Dataset CHOA 2008-2018 Sibley 2008-2018 Constrain to specific vars and remove PHI Select Private Providers 2008-2018

  8. Deduplicating & Matching Protocol • Sibley • CHOA • Emory Clinics* • Emory Hospitals • Medicaid (ResDAC) • Others as Available Used as example for all datasets * Including archived Heart Failure database at Emory HC.

  9. Flowchart: Deduplicating Adolescent EHC Clinic Datasets CHOA 2 SIBLEY CHOA 1 Sibley extracted Name, DOB, Gender & CHD ICD-9s for 2008-2010 CHOA extracted Name, DOB, Gender & CHD ICD-9s for 5/1/2009-12/31/2010 Sibley extracted Name, DOB, Gender & CHD ICD-9s for 2008-2010 CHOA extracted Name, DOB, Gender & CHD ICD-9s for 1/1/2008-4/30/2009 Concatenated multiple rows into a single row for each patient Concatenated multiple rows into a single row for each patient Cross-walked county in by zip; Concatenated multiple rows into a single row for each patient De-duplicate patients De-duplicate patients Deduplicated patients Merge & de-duplicate both datasets Merge & de-duplicate patients

  10. Five-county EstimatesPossible Over-estimate Because: • Multiple data sources may not be completely deduplicated • Name changes • Inaccurate county of residence coded (e.g., Grady free clinics serve only Fulton & DeKalb residents) • Imprecision of some ICD-9CM codes / diagnoses

  11. Five-county EstimatesPossible Under-estimate Because: • Persons living with CHDs may not access the healthcare system in time frame (2008-2010) (clinical data supports this) • You would think that • those with mild to moderate CHD defects would be less likely to access care, BUT not so • Those with unsuccessful surgeries would be less likely to access care, BUT according to clinical data, the complex severe defects are equally at risk (25%) • Imprecision of some ICD9-CM codes / diagnoses • Missing the uninsured

  12. Population-based Estimate Adolescent & Adult CHD in Five-Counties: Issues and Limitations • Not an issue -> Moved out of state before 2008 • Data errors leading to non-match, e.g., incomplete dates, misspelled names, changed names (less an issue if MACDP is included in matching process) • Didn’t seek care in Georgia during 2008-2010 • Received care outside of data sources

  13. Should We Add 41 Counties?

  14. Map of 46 counties Atlanta Augusta

  15. Should We Add 41 Counties? • Arguments in favor of including them • Additional data collection effort is minimal • Clinical Penetration in these counties are high for our Network Consortium • Healthcare settings for the 5-county area also serve the vast majority of the 46-county area • ResDAC will be reported for all of Georgia • Population of rural and semi-urban areas in the South may have different CHD prevalence (e.g., because of migration closer to care) • Different demographics for urban vs. rural outside and inside metro Atlanta limits

  16. Should We Add 41 Counties? • Arguments against including them • 46-county prevalence estimates will be more affected by missing cases that are seen outside of Georgia • ResDAC only for GA – GA residents can’t go out of state (out-of-pocket cost) • Some specialized care in border areas in Alabama, Florida, and South Carolina

  17. And the Answer Is. . . .?

  18. Yes

  19. Planned Strategy2:MACDP-based EstimateLink MACDP to Data Sources includes NDI & GA Vital Records

  20. Relationship of Presumed MACDP Survivors to Clinical & Medicaid Datasets Presumed ALIVE, But NOT Found in Lexis/Nexis MEDICAID 2008-2009 Seen in MCAID within 5 counties Seen in clinics & MCAID & living within 5 counties Seen in MCAID but living outside the 5 counties Seen in clinics & living within 5 counties Seen in clinics & MCAID but living outside 5 counties Seen in clinics but living outside 5 counties CLINICS 2008-2010 Note. Encounters occurred between 2008-2010 for EHC & between 2008-2009 for Medicaid; 2010 Medicaid data available soon.

  21. Summary of Data Sources

  22. Flowchart: To Obtain Dataset for Presumed MACDP Survivors (To be completed by CDC contractors?) Original MACDP Dataset YES FOUND IN GA DC ? Remove from MACDP Survivors NO YES Remove from MACDP Survivors FOUND IN NDI ? NO PRESUMED SURVIVORS

  23. FLOWCHART: Bringing Merged Sibley & CHOA Adolescent Dataset into CDC for MACDP MATCHING Emory HC Deduplicated Dataset MACDP 1967-1999 Add to repository matched file & deduplicate Exact Match With Last Name, First Name, DOB, & Gender YES NO Add to repository matched file & deduplicate Matches with Additional Approaches * YES NO Residual MACDP temporary file * Protocol for additional matching approaches to be discussed with CDC & consortium partners.

  24. Linkage with MACDP: CHD Adolescents & Adults Step 1. Link MACDP with GA death records & NDI to determine survivors. Merge with adult & adolescent sources. Deduplicate. Step 2. Create datasets & identify survivors & non-survivors. Step 4. Upload limited dataset to CDC via SAMS. Step 3. Create limited datasets with specific core vars & PHI removed. DATA SOURCES Emory HC 2008-2010 Grady Health 2008-2010 ResDAC 2008-2009 Linked MACDP Adult CHD Dataset Adolescent& Adult CHD Datasets Adolescent& Adult CHD Datasets MACDP with or without NDI Adolescent& Adult CHD Datasets CHOA 2008-2018 Linked MACDP Adolescent CHD Dataset Sibley 2008-2018 Select Private Providers 2008-2018 Constrain to specific vars and remove PHI • Remove PHI from MACDP not found in other sources. GA Death Records 2008-2010

  25. Assumptions & Issues of MACDP Matching Process: Multiple Reasons for Lack of Matching • Moved out of state before 2008 • Data errors leading to non-match, e.g., incomplete dates, misspelled names, changed names • Didn’t seek care in Georgia during 2008-2010 • Received care outside of data sources • Underestimate number of uninsured patients who may have sought care elsewhere • Fulton & DeKalb covered through Grady Health • Emory HC does not turn anyone away Note. 50-64 year olds will not be matched as they were born before the MACDP began collecting data.

  26. What Does the Cooperative Agreement Gain with MACDP in the Emory Project? • This is NOT a population-based prevalence estimate. It’s an estimate of MACDP survivors who are living in the 5-county area sometime in 2008-2010 and who accessed the healthcare system during that period. • Can also be estimate of MACDP survivors who are living in GA (but outside the 5-county area) who accessed care through consortium or Medicaid. • And an estimate of survivors who didn’t “hit the system” in Georgia. • Can also serve to help develop a ‘correction factor’ for those who are still alive and who did not hit the HC system

  27. Benefits of Linking MACDP Data to the Population-based Estimate • A population-based estimate allows for: • Estimating age-specific prevalence in five-county area • Modeling the dispersion by age to estimate MACDP movement out of area and out of the state of Georgia • Modeling missed care between the MACDP and the population-based estimate by differences in prevalence rates by severity of diagnosis • (there will be MACDP cases that did not match & some will be due to lack of accessing care during the 2008-2010 period; hypothesis - less severe cases are less likely to seek health care)

  28. Prevalence Measures for Comparisons • Determine age-specific prevalence (by decade) of those living insidethe 5-county area sometime between 1/1/08-12/31/10 • Determine age-specific prevalence (by decade) of those living outside the 5-county area sometime between 1/1/08-12/31/10 • GA Population-based • Five-County Prevalence (inside) • 41-County Prevalence (outside) • 46-County Prevalence • MACDP Survivors • Five-County Prevalence (inside) • 41-County Prevalence (outside) • 46-County Prevalence Note. GMH & Pediatric Cardiology Services data will not be linked to MACDP per recent DUA agreement, October 2013.

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