Severe Maternal Morbidity, A Tale of 2 States Using Data for Action—Ohio and Massachusetts
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Severe Maternal Morbidity, A Tale of 2 States Using Data for Action—Ohio and Massachusetts

Filetype[PDF-294.13 KB]


English

Details:

  • Alternative Title:
    Matern Child Health J
  • Personal Author:
  • Description:
    Purpose

    Describe how Ohio and Massachusetts explored severe maternal morbidity (SMM) data, and used these data for increasing awareness and driving practice changes to reduce maternal morbidity and mortality.

    Description

    For 2008–2013, Ohio used de-identified hospital discharge records and International Classification of Diseases, 9th Revision, Clinical Modification (ICD-9-CM) codes to identify delivery hospitalizations. Massachusetts used existing linked data system infrastructure to identify delivery hospitalizations from birth certificates linked to hospital discharge records. To identify delivery hospitalizations complicated by one or more of 25 SMMs, both states applied an algorithm of ICD-9-CM diagnosis and procedure codes. Ohio calculated a 2013 SMM rate of 144 per 10,000 delivery hospitalizations; Massachusetts calculated a rate of 162. Ohio observed no increase in the SMM rate from 2008 to 2013; Massachusetts observed a 33% increase. Both identified disparities in SMM rates by maternal race, age, and insurance type.

    Assessment

    Ohio and Massachusetts engaged stakeholders, including perinatal quality collaboratives and maternal mortality review committees, to share results and raise awareness about the SMM rates and identified high-risk populations. Both states are applying findings to inform strategies for improving perinatal outcomes, such as simulation training for obstetrical emergencies, licensure rules for maternity units, and a focus on health equity.

    Conclusion

    Despite data access differences, examination of SMM data informed public health practice in both states. Ohio and Massachusetts maximized available state data for SMM investigation, which other states might similarly use to understand trends, identify high risk populations, and suggest clinical or population level interventions to improve maternal morbidity and mortality.

  • Subjects:
  • Source:
  • Pubmed ID:
    31055701
  • Pubmed Central ID:
    PMC6610709
  • Document Type:
  • Funding:
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