title: Capturing the context of maternal deaths from verbal autopsies: a reliability study of the maternal data extraction tool (M-DET).
abstract: BACKGROUND
  The availability of quality data to inform policy is essential to reduce maternal deaths. To characterize maternal deaths in settings without complete vital registration systems, we designed and assessed the inter-rater reliability of a tool to systematically extract data and characterize the events that precede a nationally representative sample of maternal deaths in India.
  
  
  RESULTS
  Of 1017 nationally representative pregnancy-related deaths, which occurred between 2001 and 2003, we randomly selected 105 reports. Two independent coders used the maternal data extraction tool (questions with coding guidelines) to collect information on antenatal care access, final pregnancy outcome; planned place of birth and care provider; community consultation, transport, admission, hospital referral; and verification of cause of death assignment. Kappa estimated inter-rater agreement was calculated and classified as poor (K≤0.4), moderate (K = 0.4≤0.6), substantial (K = 0.6≤ 0.8) and high (K>0.8) using the criteria from Landis & Koch. The data extraction tool had high agreement for gestational age, pregnancy outcome, transport, death en route and admission to hospital; substantial agreement for receipt of antenatal care, planned place of birth, readmission and referral to higher level hospital, and whether or not death occurred in the intrapartum period; moderate to substantial agreement for classification of deaths as direct or indirect obstetric deaths or incidental deaths; moderate agreement for classification of community healthcare consultation and total number of healthcare contacts; and poor agreement for the classification of deaths as sudden deaths and other/unknown cause of death. The ability of the tool to identify the most-responsible-person in labour varied from moderate agreement to high agreement.
  
  
  CONCLUSIONS
  This data extraction tool achieved good inter-rater reliability and can be used to collect data on events surrounding maternal deaths and for verification/improvement of underlying cause of death.
authors.affiliation: Centre for Global Health Research, Li Ka Shing Knowledge Institute, St. Michael's Hospital, Toronto, Canada. cghr@smh.toronto.on.ca
authors.forename: Ann L
authors.initials: AL
authors.lastname: Montgomery
authors.forename: Shaun K
authors.initials: SK
authors.lastname: Morris
authors.forename: Rajesh
authors.initials: R
authors.lastname: Kumar
authors.forename: Raju
authors.initials: R
authors.lastname: Jotkar
authors.forename: Prem
authors.initials: P
authors.lastname: Mony
authors.forename: Diego G
authors.initials: DG
authors.lastname: Bassani
authors.forename: Prabhat
authors.initials: P
authors.lastname: Jha
mesh_terms: D000028:Abortion, Induced / Q000379:methods / Q000401:mortality / Q000706:statistics & numerical data; D001344:Autopsy / Q000379:methods; D002423:Cause of Death; D003627:Data Interpretation, Statistical; D016208:Databases, Factual / Q000592:standards* / Q000706:statistics & numerical data; D005260:Female; D006285:Health Planning / Q000458:organization & administration / Q000706:statistics & numerical data; D006297:Health Services Accessibility / Q000706:statistics & numerical data; D006801:Humans; D008428:Maternal Mortality; D008499:Medical Records / Q000592:standards / Q000706:statistics & numerical data; D033262:Narration; D011247:Pregnancy; D011256:Pregnancy Outcome / Q000453:epidemiology; D011295:Prenatal Care / Q000706:statistics & numerical data; D015203:Reproducibility of Results