Methodology for sampling women at high maternal risk in administrative data

Abstract Background In population level studies, the conventional practice of categorizing women into low and high maternal risk samples relies upon ascertaining the presence of various comorbid conditions in administrative data. Two problems with the conventional method include variability in the recommended comorbidities to consider and inability to distinguish between maternal and fetal risks. High maternal risk sample selection may be improved by using the Obstetric Comorbidity Index (OCI), a system of risk scoring based on weighting comorbidities associated with maternal end organ damage. The purpose of this study was to compare the net benefit of using OCI risk scoring vs the conventional risk identification method to identify a sample of women at high maternal risk in administrative data. Methods This was a net benefit analysis using linked delivery hospitalization discharge and vital records data for women experiencing singleton births in Georgia from 2008-2012. We compared the value identifying a sample of women at high maternal risk using the OCI score to the conventional method of dichotomous identification of any comorbidities. Value was measured by the ability to select a sample of women designated as high maternal risk who experienced severe maternal morbidity or mortality. Results The high maternal risk sample created with the OCI had a small but positive net benefit (+ 0.6), while the conventionally derived sample had a negative net benefit indicating the sample selection performed worse than identifying no woman as high maternal risk. Conclusions The OCI can be used to select women at high maternal risk in administrative data. The OCI provides a consistent method of identification for women at risk of maternal morbidity and mortality and avoids confounding all obstetric risk factors with specific maternal risk factors. Using the OCI may help reduce misclassification as high maternal risk and improve the consistency in identifying women at high maternal risk in administrative data.

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Methodology for sampling women at high maternal risk in administrative data

BMC Pregnancy and Childbirth ◽

10.1186/s12884-019-2500-7 ◽

2019 ◽

Vol 19 (1) ◽

Author(s):

Jennifer Vanderlaan ◽

Anne Dunlop ◽

Roger Rochat ◽

Bryan Williams ◽

Susan E. Shapiro

Keyword(s):

Risk Factors ◽

Administrative Data ◽

Conventional Method ◽

Maternal Morbidity ◽

Sample Selection ◽

Population Level ◽

Risk Identification ◽

Net Benefit ◽

Maternal Risk ◽

Risk Scoring

Abstract Background In population level studies, the conventional practice of categorizing women into low and high maternal risk samples relies upon ascertaining the presence of various comorbid conditions in administrative data. Two problems with the conventional method include variability in the recommended comorbidities to consider and inability to distinguish between maternal and fetal risks. High maternal risk sample selection may be improved by using the Obstetric Comorbidity Index (OCI), a system of risk scoring based on weighting comorbidities associated with maternal end organ damage. The purpose of this study was to compare the net benefit of using OCI risk scoring vs the conventional risk identification method to identify a sample of women at high maternal risk in administrative data. Methods This was a net benefit analysis using linked delivery hospitalization discharge and vital records data for women experiencing singleton births in Georgia from 2008 to 2012. We compared the value identifying a sample of women at high maternal risk using the OCI score to the conventional method of dichotomous identification of any comorbidities. Value was measured by the ability to select a sample of women designated as high maternal risk who experienced severe maternal morbidity or mortality. Results The high maternal risk sample created with the OCI had a small but positive net benefit (+ 0.6), while the conventionally derived sample had a negative net benefit indicating the sample selection performed worse than identifying no woman as high maternal risk. Conclusions The OCI can be used to select women at high maternal risk in administrative data. The OCI provides a consistent method of identification for women at risk of maternal morbidity and mortality and avoids confounding all obstetric risk factors with specific maternal risk factors. Using the OCI may help reduce misclassification as high maternal risk and improve the consistency in identifying women at high maternal risk in administrative data.

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Methodology for sampling women at high maternal risk in administrative data

10.21203/rs.2.11606/v1 ◽

2019 ◽

Author(s):

Jennifer Vanderlaan ◽

Anne Dunlop ◽

Roger Rochat ◽

Bryan Williams ◽

Susan E. Shapiro

Keyword(s):

Risk Factors ◽

Administrative Data ◽

Conventional Method ◽

Maternal Morbidity ◽

Sample Selection ◽

Population Level ◽

Risk Identification ◽

Net Benefit ◽

Maternal Risk ◽

Risk Scoring

Abstract Background In population level studies, the conventional practice of categorizing women into low and high maternal risk samples relies upon ascertaining the presence of various comorbid conditions in administrative data. Two problems with the conventional method include variability in the recommended comorbidities to consider and inability to distinguish between maternal and fetal risks. High maternal risk sample selection may be improved by using the Obstetric Comorbidity Index (OCI), a system of risk scoring based on weighting comorbidities associated with maternal end organ damage. The purpose of this study was to compare the net benefit of using OCI risk scoring vs the conventional risk identification method to identify a sample of women at high maternal risk in administrative data. Methods This was a net benefit analysis using linked delivery hospitalization discharge and vital records data for women experiencing singleton births in Georgia from 2008-2012. We compared the value identifying a sample of women at high maternal risk using the OCI score to the conventional method of dichotomous identification of any comorbidities. Value was measured by the ability to select a sample of women designated as high maternal risk who experienced severe maternal morbidity or mortality. Results The high maternal risk sample created with the OCI had a small but positive net benefit (+ 0.6), while the conventionally derived sample had a negative net benefit indicating the sample selection performed worse than identifying no woman as high maternal risk. Conclusions The OCI can be used to select women at high maternal risk in administrative data. The OCI provides a consistent method of identification for women at risk of maternal morbidity and mortality and avoids confounding all obstetric risk factors with specific maternal risk factors. Using the OCI may help reduce misclassification as high maternal risk and improve the consistency in identifying women at high maternal risk in administrative data.

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Methodology for sampling women at high maternal risk in administrative data

10.21203/rs.2.11606/v4 ◽

2019 ◽

Author(s):

Jennifer Vanderlaan ◽

Anne Dunlop ◽

Roger Rochat ◽

Bryan Williams ◽

Susan E. Shapiro

Keyword(s):

Risk Factors ◽

Administrative Data ◽

Conventional Method ◽

Maternal Morbidity ◽

Sample Selection ◽

Population Level ◽

Risk Identification ◽

Net Benefit ◽

Maternal Risk ◽

Risk Scoring

Abstract Background In population level studies, the conventional practice of categorizing women into low and high maternal risk samples relies upon ascertaining the presence of various comorbid conditions in administrative data. Two problems with the conventional method include variability in the recommended comorbidities to consider and inability to distinguish between maternal and fetal risks. High maternal risk sample selection may be improved by using the Obstetric Comorbidity Index (OCI), a system of risk scoring based on weighting comorbidities associated with maternal end organ damage. The purpose of this study was to compare the net benefit of using OCI risk scoring vs the conventional risk identification method to identify a sample of women at high maternal risk in administrative data. Methods This was a net benefit analysis using linked delivery hospitalization discharge and vital records data for women experiencing singleton births in Georgia from 2008-2012. We compared the value identifying a sample of women at high maternal risk using the OCI score to the conventional method of dichotomous identification of any comorbidities. Value was measured by the ability to select a sample of women designated as high maternal risk who experienced severe maternal morbidity or mortality. Results The high maternal risk sample created with the OCI had a small but positive net benefit (+ 0.6), while the conventionally derived sample had a negative net benefit indicating the sample selection performed worse than identifying no woman as high maternal risk. Conclusions The OCI can be used to select women at high maternal risk in administrative data. The OCI provides a consistent method of identification for women at risk of maternal morbidity and mortality and avoids confounding all obstetric risk factors with specific maternal risk factors. Using the OCI may help reduce misclassification as high maternal risk and improve the consistency in identifying women at high maternal risk in administrative data.

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Severe Maternal Morbidity: A Comparison of Definitions and Data Sources

American Journal of Epidemiology ◽

10.1093/aje/kwab077 ◽

2021 ◽

Author(s):

Jonathan M Snowden ◽

Audrey Lyndon ◽

Peiyi Kan ◽

Alison El Ayadi ◽

Elliott Main ◽

...

Keyword(s):

Administrative Data ◽

Maternal Morbidity ◽

Claims Data ◽

Birth Certificate ◽

Population Level ◽

Kappa Statistic ◽

Data Sources ◽

Severe Maternal Morbidity ◽

Fine Grained ◽

Control And Prevention

Abstract Severe maternal morbidity (SMM) is a composite outcome measure that indicates serious, potentially life-threatening maternal health problems. There is great interest in defining SMM using administrative data for surveillance and research. In the US, one common way of defining SMM at the population level is an index developed by the Centers for Disease Control and Prevention. Modifications have been proposed to this index (e.g., excluding maternal transfusion); some research defines SMM using an index introduced by Bateman et al. Birth certificate data are also increasingly being used to define SMM. We compared commonly used US definitions of SMM to each other among all California births, 2007-2012, using the Kappa statistic and other measures. We also evaluated agreement between maternal morbidity fields on the birth certificate compared to claims data. Concordance was generally low between the 7 definitions of SMM analyzed (i.e., κ < 0.4 for 13 of 21 two-way comparisons), Low concordance was particularly driven by presence/absence of transfusion and claims data versus birth certificate definitions. Low agreement between administrative data-based definitions of SMM highlights that results can be expected to differ between them. Further research is needed on validity of SMM definitions, using more fine-grained data sources.

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Peripartum Embolism

10.1093/med/9780190226459.003.0046 ◽

2017 ◽

Author(s):

Elizabeth M. S. Lange ◽

Paloma Toledo

Keyword(s):

Risk Factors ◽

Amniotic Fluid ◽

Maternal Morbidity ◽

Clinical Presentation ◽

Air Embolism ◽

Common Type ◽

Amniotic Fluid Embolism ◽

Maternal Risk ◽

Venous Air Embolism ◽

Maternal Morbidity And Mortality

Embolic disease during pregnancy is a significant contributor to maternal morbidity and mortality. The most common type of embolism is venous air embolism, but this is rarely symptomatic or hemodynamically significant. However, both thromboembolism and amniotic fluid embolism (AFE) are associated with significant maternal risk, and in the case of AFE, frequent major hemodynamic sequelae and fatal results ensue. As each class of embolic disease has slightly different risk factors, pathophysiology, clinical presentation, and treatment, they will each be discussed in separate sections in this chapter with an overview of these components.

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Evaluating Iowa Severe Maternal Morbidity Trends and Maternal Risk Factors: 2009–2014

Maternal and Child Health Journal ◽

10.1007/s10995-017-2301-4 ◽

2017 ◽

Vol 21 (9) ◽

pp. 1834-1844 ◽

Cited By ~ 2

Author(s):

Brittni N. Frederiksen ◽

Catherine J. Lillehoj ◽

Debra J. Kane ◽

Dave Goodman ◽

Kristin Rankin

Keyword(s):

Risk Factors ◽

Maternal Morbidity ◽

Severe Maternal Morbidity ◽

Maternal Risk Factors ◽

Maternal Risk ◽

Morbidity Trends

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Maternal Risk Factors for Lactation Mastitis: A Meta-analysis

Western Journal of Nursing Research ◽

10.1177/0193945920967674 ◽

2020 ◽

pp. 019394592096767

Author(s):

Yuan Deng ◽

Yan Huang ◽

Ping Ning ◽

Se-Ge Ma ◽

Pei-Yu He ◽

...

Keyword(s):

Risk Factors ◽

Meta Analysis ◽

Significant Risk ◽

Risk Identification ◽

Cochrane Library ◽

Maternal Risk Factors ◽

Case Control Studies ◽

Maternal Risk ◽

Newcastle Ottawa Scale ◽

Lactational Mastitis

This meta-analysis was conducted to identify maternal risk factors for lactational mastitis. Studies published in English or Chinese were retrieved from Medline (PubMed), Embase, Cochrane Library, Web of Science, CNKI, WANFANG, and VIP databases according to predefined inclusion and exclusion criteria. Study quality was assessed by the Newcastle–Ottawa Scale. A random-effects model was used for data pooling and I2 tests to assess study heterogeneity. Pooled data from 8 cohorts and 10 case–control studies identified previous mastitis during breastfeeding (P<0.00001), cesarean section (P=0.001), breast trauma (P<0.001), anemia (P=0.0001), latch problems ≤ 8 weeks post-delivery (P=0.003), milk overproduction (P=0.002), blocked duct (P<0.0001), cracked nipple (especially ≤ 4 weeks post-delivery) (P=0.0001), use of nipple shields (P<0.00001), nipple cream (P<0.0001), brassieres (P<0.0001), and breast pumps (P<0.00001), and breastfeed duration > 30 min (P=0.008) as significant risk factors. Washing nipples before breastfeeding decreased lactational mastitis risk. Identification of these risk factors may facilitate the development of nursing care protocols for reducing lactational mastitis.

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NEONATAL SEPSIS AND IDENTIFICATION OF RISK FACTORS: STUDY IN AVBRH HOSPITAL SAWANGI

International Journal of Medical and Biomedical Studies ◽

10.32553/ijmbs.v3i6.1215 ◽

2019 ◽

Vol 3 (6) ◽

Author(s):

Pramod P. Singhavi

Keyword(s):

Risk Factors ◽

Neonatal Sepsis ◽

Early Onset ◽

Late Onset ◽

Signs And Symptoms ◽

Premature Rupture ◽

Maternal Risk ◽

Late Onset Sepsis ◽

Early Onset Sepsis ◽

Meconium Stained Amniotic Fluid

Introduction: India has the highest incidence of clinical sepsis i.e.17,000/ 1,00,000 live births. In Neonatal sepsis septicaemia, pneumonia, meningitis, osteomyelitis, arthritis and urinary tract infections can be included. Mortality in the neonatal period each year account for 41% (3.6 million) of all deaths in children under 5 years and most of these deaths occur in low income countries and about one million of these deaths are due to infectious causes including neonatal sepsis, meningitis, and pneumonia. In early onset neonatal sepsis (EOS) Clinical features are non-specific and are inefficient for identifying neonates with early-onset sepsis. Culture results take up to 48 hours and may give false-positive or low-yield results because of the antenatal antibiotic exposure. Reviews of risk factors has been used globally to guide the development of management guidelines for neonatal sepsis, and it is similarly recommended that such evidence be used to inform guideline development for management of neonatal sepsis. Material and Methods: This study was carried out using institution based cross section study . The total number neonates admitted in the hospital in given study period was 644, of which 234 were diagnosed for neonatal sepsis by the treating pediatrician based on the signs and symptoms during admission. The data was collected: Sociodemographic characteristics; maternal information; and neonatal information for neonatal sepsis like neonatal age on admission, sex, gestational age, birth weight, crying immediately at birth, and resuscitation at birth. Results: Out of 644 neonates admitted 234 (36.34%) were diagnosed for neonatal sepsis by the paediatrician based on the signs and symptoms during admission. Of the 234 neonates, 189 (80.77%) infants were in the age range of 0 to 7 days (Early onset sepsis) while 45 (19.23%) were aged between 8 and 28 days (Late onset sepsis). Male to female ratio in our study was 53.8% and 46% respectively. Out of total 126 male neonates 91(72.2%) were having early onset sepsis while 35 (27.8%) were late onset type. Out of total 108 female neonates 89(82.4%) were having early onset sepsis while 19 (17.6%) were late onset type. Maternal risk factors were identified in 103(57.2%) of early onset sepsis cases while in late onset sepsis cases were 11(20.4%). Foul smelling liquor in early onset sepsis and in late onset sepsis was 10(5.56%) and 2 (3.70%) respectively. In early onset sepsis cases maternal UTI, Meconium stained amniotic fluid, Multipara and Premature rupture of membrane was seen in 21(11.67%), 19 (10.56%), 20(11.11%) and 33 (18.33%) cases respectively. In late onset sepsis cases maternal UTI, Meconium stained amniotic fluid, Multipara and Premature rupture of membrane was seen in 2 (3.70%), 1(1.85%), 3 (5.56%) and 3 (5.56%) cases respectively. Conclusion: Maternal risk identification may help in the early identification and empirical antibiotic treatment in neonatal sepsis and thus mortality and morbidity can be reduced.

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Population level risk factors associated with childhood obesity

Obesity Abstracts ◽

10.1530/obabs.01.rfc2.6 ◽

2019 ◽

Author(s):

Claire Beynon ◽

Nora Pashyan ◽

Elizabeth Fisher ◽

Dougal Hargreaves ◽

Linda Bailey ◽

...

Keyword(s):

Risk Factors ◽

Childhood Obesity ◽

Population Level ◽

Factors Associated

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