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Using Vital Records for Public Health Surveillance: Some U.S. Examples. Mark Flotow Illinois Dept of Public Health, Center for Health Statistics NAPHSIS President 4 March 2011 Vital Statistics Summit – Ottawa, Canada. What is Public Health Surveillance?.

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using vital records for public health surveillance some u s examples

Using Vital Records for Public Health Surveillance:Some U.S. Examples

Mark Flotow

Illinois Dept of Public Health, Center for Health Statistics

NAPHSIS President

4 March 2011

Vital Statistics Summit – Ottawa, Canada

slide2

What is Public Health Surveillance?

  • Monitoring emerging infectious diseases
  • Monitoring well-established infectious diseases
  • Monitoring chronic disease
  • Monitoring morbidity and mortality agents/factors
  • Monitoring health-related behaviors
  • Monitoring newborns’ outcomes/health
  • Monitoring quality of health care
  • Monitoring food, water, drugs, dairy, etc.
  • Nota bene: monitoring = collection, analysis and sharing of surveillance information
  • Concept of public health vs. population health
slide3

Public Health Surveillance: How

  • Sentinel event reporting and monitoring
  • Screening (e.g., lab testing)
  • Registries (e.g., for cancer or vital events)
  • Administrative records (e.g., hospital discharge data)
  • Population surveys (e.g., PRAMS)
  • Direct reporting to public health programs (e.g., PHIN)
  • Direct inspection (e.g., health care facilities)
  • Anecdotal reporting (e.g., for rare events)
  • PRAMS = pregnancy risk assessment and monitoring system (CDC program)
  • PHIN = public health information network
slide4

Public Health Surveillance: When

  • Real time (or close to it; PHIN, inspections)
  • Within a week (e.g., fact of death; VR)
  • Within a month (e.g., cause of death; VR)
  • Within in a year (e.g., behaviors; BRFSS, PRAMS)
  • More than a year (e.g., chronic diseases, cancer registry)
  • VR = vital records or vital records system
  • PRAMS = pregnancy risk assessment and monitoring system (state implemented CDC program)
  • PHIN = public health information network
  • BRFSS = behavioral risk factor surveillance system (state implemented CDC program)
slide5

Public Health Surveillance: Who

  • Epidemiologists, lab staff
  • Physicians, nurses
  • Surveyors and their clients
  • Google (e.g., seasonal influenza activity by locality)
  • Statisticians, researchers
  • Registrars
  • Nota bene: many of these surveillance activities can occur at a variety of geographic levels or locations – national, state/province/territory, county/minor civil district, city, local health department, university, hospital, clinic, physician office, etc.
slide6

Vital Records as Part of Public Health Surveillance

  • What does Vital Records (VR) have to offer regarding Public Health (PH) surveillance?
  • 100% sample
  • Good data quality
  • Universal standards
  • Timely collection
  • Electronic capture (for the most part, and increasing)
  • Long time series of data
  • Trending towards GIS-compatible geocoding
  • Universal recognition and use
slide7

Vital Records as Part of Public Health Surveillance

  • Advantages/Characteristics of Electronic VR Systems: Collection
  • 100% sample needs point-of-collection input (Web-based) and dedication to training
  • Good data quality is everyone’s business: intake system, VR unit, tabulators, data users
  • Universal standards start at the national, if not international, level
  • Timely collection includes timely feedback and potentially fewer follow-back queries
slide8

Vital Records as Part of Public Health Surveillance

  • Advantages/Characteristics of Electronic VR Systems: Collection (cont.)
  • GIS-compatible geocoding relies less on geo-political boundaries for accuracy
  • Easy output and sharing, especially before a periodic file is complete
  • Sharing of system designs and standards
slide9

Vital Records as Part of Public Health Surveillance

  • Advantages of Electronic VR Systems: Tabulation/Analysis
  • Many variables for cross-tabulation (i.e., all data are entered from certificates)
  • Aggregate data quality can be done regularly as files are being built
  • Readily available time series for data quality and analysis
  • GIS geocoding allows for any geographic delineation, not just for geo-political bounded entities
  • Small-area analysis, isobars, what-ifs, etc.
slide10

Vital Records as Part of Public Health Surveillance

  • Advantages of Electronic VR Systems: Sharing/Linking
  • Web-based data query systems: everyone can be a researcher (?)
  • Data warehousing (actual or virtual)
  • EVVE (electronic verification of vital events)
  • STEVE (state and territorial exchange of vital events)
  • Combining with other survey or surveillance data
slide11

Vital Records as Part of Public Health Surveillance

  • Examples of VR Surveillance: Indirect
  • Chronic disease (premature mortality rates)
  • Infant mortality (maternal and child health), including SIDS
  • Life expectancy
  • Certain program-specific infectious diseases (e.g., influenza, diabetes)
  • Nota bene: here “indirect” means at an aggregate level
slide12

Vital Records as Part of Public Health Surveillance

  • Examples of VR Surveillance: Direct
  • Maternal mortality, case investigation
  • Adverse pregnancy outcomes reporting system (APORS)
  • Early hearing detection and intervention (EHDI) program
  • TB surveillance
  • NCI SEER (surveillance epidemiology and end results)
  • Census of fatal occupational injuries
  • in conjunction with NEDSS (disease names in VR C-o-D)
  • PRAMS
  • Nota bene: here “direct” means at an individual record level
what is prams
What is PRAMS?
  • Pregnancy Risk Assessment Monitoring System (PRAMS)
  • CDC program administered at the state level
  • Ongoing population-based surveillance system
  • Collects state-specific data
  • Self-reported data on maternal behaviors and experiences
  • Survey data merged with birth certificate data
prams objectives
PRAMS Objectives
  • To promote the collection of population-based data of high scientific quality
  • To conduct comprehensive analyses
  • To translate results into useable information for public health action
  • To assist states in building capacity for collecting, analyzing, and translating data
prams background
PRAMS Background
  • Established in 1987 as part of an Infant Health Initiative
  • Congressional funding to CDC to establish state-based programs
  • Reduce maternal and infant morbidity and mortality
      • Maternal and infant health programs
      • Health policies
      • Maternal behaviors
prams participation 2010

WA

ME

VT

MN

OR

NY

MI

RI

NYC

NE

NJ

OH

IL

UT

WV

MD

CO

NC

NM

OK

AR

SC

MS

AL

GA

LA

TX

AK

FL

HI

PRAMS Participation, 2010

MA

SDT

WI

WY

PA

DE

VA

MO

TN

Prior to 2006

Funded

in 2006

Note: PRAMS represents approximately 75% of all US live births

prams organizational structure
PRAMS Organizational Structure
  • Collaboration between CDC and funded states/sites
  • CDC provides:
    • Overall project direction
      • Standard methodology and model protocol
      • Questionnaire development coordination
      • Technical support & data management
    • Base funding
  • States/sites provide:
    • State-specific modifications to methods and questionnaire
    • Additional resources
    • Access to birth certificate variables
prams questionnaire
PRAMS Questionnaire
  • 14-pages, booklet format (self-administered)
  • Telephone version (interviewer-administered)
  • English and Spanish versions
  • Core questions common to all states
  • State specific questions
    • Bank of standard pre-tested questions that states can select from
    • State developed questions
selected topics in prams
Selected Topics in PRAMS
  • Unintended pregnancy
  • Cigarette smoking and alcohol use
  • Physical abuse
  • Multi-vitamin use
  • Breast-feeding
  • Prenatal care
  • HIV counseling and testing
  • Medicaid and WIC participation
  • Infant health and care
  • Infant sleep position
prams population of interest
PRAMS Population of Interest

Women who delivered a live-born infant

  • Residents of state
  • Birth within the calendar year of data collection

The birth certificate file (monthly) is the starting point for determining the sampling frame for the PRAMS survey.

how the birth certificate is used to implement prams
How the Birth Certificate is Used to Implement PRAMS
  • Identifying the PRAMS Sample
  • Data Collection
  • Data Weighting (both monthly and annually)
  • Data Linkage
  • Providing demographics and other information for analysis
the value of data linkage in prams
The Value of Data Linkage in PRAMS
  • Reduces respondent burden
  • Improves accuracy (better detection and measurement)
  • Reduces follow-up costs
  • Recent CDC PRAMS application package invited data linkage activities as examples of enhanced projects (beyond the basics)
exclusions to the sampling frame e g how vrs are used
Exclusions to the Sampling Frame(e.g., how VRs are used)
  • Stillbirths, fetal deaths, & induced abortions
  • Out-of-state occurrences
  • In-state births to nonresidents of the state
  • Records missing mother’s name
  • Records processed too late (> 6 months from birth)
  • Multiple gestations rules; adoptions; surrogate births; mothers under a certain age
ponder
PONDER
  • Menu-driven, web-based analysis request system
  • Accessible via Inside PRAMS
  • Includes all core and computed variables and more common standard variables
  • Data from 2000 to present
  • New years of data are available as soon as weighted
cponder
CPONDER
  • Public use version of PONDER www.cdc.gov/PRAMS/CPONDER.htm
  • Includes prevalence and trend data for selected core and standard indicators
  • Best source for cross-state comparisons and sharing data
cdc prams websites
CDC PRAMS Websites
  • CDC, Division of Reproductive Health, PRAMS page: http://www.cdc.gov/prams/
  • CPONDER PRAMS data query system; Access from PRAMS website at http://www.cdc.gov/prams/CPONDER.htm
slide29

Illinois PRAMS/VR Surveillance:

Data to Action

Paper: “Delivery hospital practices associated with breastfeeding continuation and exclusivity in Illinois” by Amanda Bennett, Dr. Deborah Rosenberg and Dr. Myrtis Sullivan (all University of Illinois – Chicago)

Data: 2000-2006 PRAMS data (n=11,987)

Results: determined which delivery hospital practices were associated with increased breastfeeding and which were not

(see next slide)

slide30

Illinois PRAMS/VR Surveillance:

Data to Action

Results (continued): increased breastfeeding associations – breastfeeding in the hospital, receiving a support phone number, rooming-in, breastfeeding in the first hour post-delivery, feeding baby only breast milk

Decreased breastfeeding associations – receiving a formula gift pack, hospital helping with breastfeeding, pacifier use

Policy: outlines practices for developing “baby-friendly” hospitals

slide31

Illinois PRAMS/VR Surveillance:

Data to Action

Evaluation: “Medicaid Family planning waiver, Illinois Healthy Woman program” (IL Dept of Healthcare and Family Services and University of Illinois – Chicago)

Data: 2001-2007 PRAMS data

Results: ongoing, being used to evaluate program effectiveness via PRAMS mothers’ experiences

slide32

Illinois PRAMS/VR Surveillance:

Data to Action

Evaluation: “Women’s Mental Health policy and program development”

Data: PRAMS data on post-partum depression

Results: post-partum treatments offered new mothers varied considerably by race category, such as medication versus receiving counseling

Policy: Illinois must take steps to ensure referral and treatment for all women and understand the factors influencing treatment selection.

example from massachusetts prams
Example from Massachusetts PRAMS

Their conclusions . . .

  • High proportion of MA women experienced postpartum depressive symptoms
  • Among those reporting depression, only 1 in 4 sought professional help
  • Improvements in screening for and appropriately managing PPD are needed
example from massachusetts prams policy impact
Example from Massachusetts PRAMS :Policy Impact

Used in drafting the bill “An Act Relative to Post Partum Depression”

  • Calls for task force to review PPD resources in MA and gather information on best practices and treatment options
  • Instructs MDPH to make PPD a priority
  • Mandates insurance companies to report to state on efforts to address PPD, including screening
  • Encourages providers, non-profits, health departments, and insurance companies to help de-stigmatize PPD and create a culture of awareness
  • Received favorable report from Joint Financial Services Committee; currently with the House Ways and Means Committee

Supported the selection of a mental health priority for MCH Block Grant

  • “Promote emotional wellness and social connectedness across lifespan”
example from massachusetts prams programmatic use
Example from Massachusetts PRAMS : Programmatic Use

MA New Parents Initiative

  • Program to improve health of new parents, infants and families across lifespan by enhancing communication between providers and new parents
  • Uses emotion-based messaging focusing on 4 topic areas
    • Improving maternal-infant mental health
    • Nurturing early care giving
    • Decreasing family violence
    • Increasing use of family planning among new parents
  • PRAMS PPD data contributed to the focus on improving maternal mental health
slide36

Automated Influenza and PneumoniaReporting in anElectronicDeathRegistrationSystem validated with Laboratory ConfirmationAlvin T. Onaka, Ph.D. Hawaii Department of HealthOffice of Health Status Monitoring

influenza deaths
Influenza Deaths
  • CDC Case Definition

Influenza listed anywhere on the death certificate (Part I or Part II)

  • Exclusions

Haemophilus influenzae

Parainfluenzae virus

weekly mortality reporting
Weekly Mortality Reporting
  • Previous Procedure
  • Deaths due to Influenza or Pneumonia manually counted by DOH staff
  • No timely means of lab confirmation from other DOH branch that electronically reports lab data (ELR)
slide39

Worksheet turned in to DOH and enters info. into system. DOH manually identifies Influenza & Pneumonia

Weekly mortality report manually run from data system

Funeral Director gives death worksheet to certifier to complete

Previous Mortality Reporting Procedure

weekly mortality reporting1
Weekly Mortality Reporting
  • New Methodology
  • New automated method of identifying Influenza or Pneumonia cases via the Hawaii Electronic Death Registration System (EDRS)
  • New electronic laboratory confirmation between EDRS and ELR
slide41

EDRS

At scheduled times, mortality reports automatically sent via email to Disease Outbreak Control Division & Vital Statistics

Internet

Internet

Certifier enters COD in EDRS

NEDSS

Later, Influenza/ Pneumonia lab results matched & results confirmed

Current Weekly/Daily Mortality Reporting Procedure

automated mortality reports
Automated Mortality Reports
  • Adjustable interval for either hourly, daily or weekly automated reporting
  • In addition to Pneumonia and Influenza case identification, custom reports are possible for future disease outbreaks (i.e., Syndromic Surveillance)
excel spreadsheet
Excel Spreadsheet

Influenza & Pneumonia Indicators

Full literal text of COD by certifier

Unique decedent ID

automated mortality reports1
Automated Mortality Reports
  • Spreadsheet allows review of Influenza & Pneumonia status & pertinent certifier information for all deaths
  • With full COD available, trained reviewers can ignore computer triggered flags and request record review of possible Influenza cases missed by computer
  • Decedent privacy protected since DOH reviewers only see a Case ID
increasing accuracy for mortality reporting and cod in general
Increasing Accuracy for Mortality Reporting and COD in general
  • Incorporation of spell checker from NCHS’s SuperMICAR
  • Spell checker reviews COD field and opens up a spell check box for certifier to accept or change possible misspelled word(s)
lessons learned from h1n1 surveillance
Lessons Learned from H1N1 Surveillance
  • Medical Examiners and Coroners often certify record with “deferred – pending lab results”.
  • The current automated reporting system will miss these Influenza cases
  • Drop to paper cases include backdated certification information
  • Automated reporting system will also miss these cases
hawaii s confirmed h1n1 influenza death cases
Hawaii’s Confirmed H1N1 Influenza Death Cases
  • 13 confirmed cases occurred in about a 1 year time period.
  • About 24% cases first identified by the automatic email mortality reporting system
  • About 38% cases first identified by Vital Statistics staff who entered in COD that was completed non-electronically
  • About 38% cases first identified by Disease Outbreak Control Division (DOCD) staff from their Electronic Laboratory Reporting system (ELRS)
slide50

In Summary . . .

VRs as Public Health Surveillance

  • Monitoring emerging infectious diseases
  • Monitoring well-established infectious diseases
  • Monitoring chronic disease
  • Monitoring morbidity and mortality agents/factors
  • Monitoring health-related behaviors
  • Monitoring newborns’ outcomes/health
  • Monitoring quality of health care
  • Monitoring food, water, drugs, dairy, etc.
  • Nota bene: monitoring = collection, analysis and sharing of surveillance information
slide51

Special thanks to . . .

  • Leslie Harrison and Martha Kapaya of CDC PRAMS
  • Theresa Sandidge, Illinois PRAMS
  • Dr. Hafsatou Diop, Massachusetts PRAMS
  • Dr. Alvin Onaka, Hawaii Dept of Health
slide52

“Merci beaucoup” for your attention and patience!

Contact information:

Mark Flotow

Illinois Center for Health Statistics/IL Dept Public Health

525 West Jefferson Street

Springfield, IL 62761

217.785.1064

mark.flotow@illinois.gov

www.naphsis.org