Extending Our Reach Through Partnerships June 2-6, 2013 Phoenix, Arizona

Extending Our Reach Through Partnerships June 2-6, 2013 Phoenix, Arizona

Evaluating NYC’s Fetal Death Data Quality using Neonatal Deaths as a Benchmark 2013 NAPHSIS Annual Meeting June 2, 2013 Melissa Gambatese, MPH Director, Quality Improvement Unit Bureau of Vital Statistics New York City Department of Health and Mental Hygiene

Overview Fetal Deaths in NYC Perinatal mortality Innovation – Comparing fetal deaths to neonatal deaths Research question Methods Selected Results Conclusions/Next Steps

NYC Fetal Deaths 2011 Attribute2011 Total fetal deaths # of reporting facilities52 % reported electronically>99% Gestational age <13 weeks weeks weeks ≥ 28 weeks 81% 12% 5% 2%

Perinatal Mortality Perinatal continuum Neonatal deaths Perinatal deaths BIRTH 1 st trimester 28 days 2 nd trimester 3 rd trimester Conception Late-term fetal deaths 28 weeks

Perinatal mortality Late-term fetal deaths account for: – 28% of US perinatal deaths – 25% of NYC perinatal deaths Both events occur close in time along the perinatal continuum – Causes and preventative targets likely very similar – Research/programming gap between fetal and neonatal deaths

Innovation: Fetal vs. neonatal deaths Both events captured by vital events registration systems – Viable data source: low-cost, representative Comparing fetal to neonatal deaths allows for: – Comprehensive assessment of fetal death data quality and viability for research – Insight into fetal vs. neonatal death reporting and data quality disparities

Research Question How does the completeness of late-term fetal death vital event data compare to the completeness of neonatal death vital event data in NYC?

Methods Sample events – Late-term fetal deaths (n=1930) – Neonatal deaths (n=735) matched birth and death certificates

Methods Analysis 1- Data Completeness Frequencies of missing/unknown on fetal vs. neonatal: – Maternal demographics – Maternal risk factors – Prenatal care – Infant characteristics Frequencies of ill-defined causes of death on fetal vs. neonatal Pre/post revision data completeness for fetal deaths – Electronic reporting system US Standard Report of Fetal Death Fetal death data completeness by reporting facility

Methods Analysis 2- Data provider survey Respondents: NYC medical facilities that report fetal deaths Questions on reporting requirements and barriers to reporting Responses linked to data completeness indicator – Risk ratios

SELECTED RESULTS

Percent of records with missing/unknown information, ItemNeonatalFetal Maternal demographics Race24 Ancestry410 Birthplace18 Employment during pregnancy210 Level of education222 Maternal risk factors Risk factor<15 Smoking during pregnancy<13 Pre-pregnancy weight432 Prenatal care Date of last normal menses412 Date of first prenatal care visit818 Infant characteristics Fetal weight<18 Selected Results- Data Completeness

Cause of Death Required on both death and fetal death Nosologist reviews and assigns ICD cause of death code Ill-defined causes of death Extreme immaturity (P07.2) Preterm/prematurity (P07.3) Fetal death of unspecified cause (P95) Ill-defined and unknown cause of mortality (Y34)

Selected Results: Cause of death Event type% Ill-defined, Neonatal5 Fetal67 Written causes ‘Intrauterine fetal demise’ ‘Unknown’ ‘Stillbirth’/ ‘Stillborn’

Selected Results: Pre vs. Post-revision In 2011, NYC health department implemented: – Electronic fetal death reporting system – 2003 US Standard Report of Fetal Death

Percent of fetal deaths with missing/unknown information, pre vs. post revision Item Pre-revision ( ) Post-revision (2011) Maternal demographics Race37 Ancestry725 Birthplace95 Employment during pregnancy115 Level of education22 Maternal risk factors Risk factor218 Smoking during pregnancy28 Pre-pregnancy weight3713 Prenatal care Date of last normal menses139 Date of first prenatal care visit1820 Infant characteristics Fetal weight85 Selected Results: Pre vs. Post-revision

Percent of fetal deaths with an ill-defined cause of death Item Pre-revision ( ) Post-revision (2011) Ill-defined cause of death6861 Selected Results: Pre vs. Post-revision

Selected Results: Data completeness by reporting facility “Any unknown” – Maternal risk factor – Month of last normal menses – Year of first prenatal care visit – Fetal weight

Selected Results: Data completeness by reporting facility 5.5% 4.8% 1 2

Selected Results: Data provider survey Most facilities had clear understanding of NYC reporting requirements – Example: 82% correctly responded that NYC requires fetal death reporting for all gestational ages Half (55%) considered electronic reporting easier Many reported perceived barriers – 29% difficulties with physician involvement – 26% fetal death reporting too detailed/too many questions

Selected Results: Data provider survey vs. data quality Survey responseLess likely to report unknown More likely to report unknown Risk ratio No barriers to reporting0.21 [95% CI: ] Fetal death data “very important”0.31 [95% CI: ] Difficulty with physician involvement 1.25 [95% CI: ]

Conclusions NYC late-term fetal death certificates lack maternal demographic, medical and cause of death information compared with neonatal records Variability by hospital suggests opportunities for improvement exist Implementation of electronic reporting system/revise d certificate impacted data completeness Survey results suggest a need for increased provider training, physician engagement, and reduced reporting requirements.

Limitations Unable to distinguish between “unknown” and missing/not reported – Lack of resources to conduct medical record audit Unclear whether survey respondent was person most responsible for fetal death reporting at facility. Survey respondents may have provided socially desirable responses. Could not distinguish individual effects of electronic reporting system and revised certificate. Findings limited to NYC data

Next steps Examine reasons for quality differences across hospitals Investigate differences in reporting practices between fetal and neonatal deaths. – Conference calls Create tools to assist data providers in collecting information – Parent worksheet Utilize electronic reporting system to improve data completeness – Expand data validation checks

Conclusions Jurisdictions can use neonatal deaths as a benchmark for measuring quality of late-term fetal death data Survey providers to identify barriers to reporting and link to data quality Results can inform effective fetal death data quality initiatives

Acknowledgements NYC DOHMH Bureau of Vital Statistics – Erica Lee, MPH – Elizabeth Begier, MD, MPH – Tara Das, PhD – Ann Madsen, PhD, MPH – Antonio Soto NAPHSIS NCHS

Questions?