{
    "abstract": "Many severe maternal morbidities (SMMs) are preventable, and understanding circumstances in which complications occur is crucial. The objective was to evaluate a framework for SMM benchmarking and quality improvement opportunities. Building upon metrics defined by the Centers for Disease Control and Prevention on the basis of an inpatient sample, analysis included indicators across 5 domains (Hemorrhage/Transfusion, Preeclampsia/Eclampsia, Cardiovascular, Sepsis, and Thromboembolism/Cerebrovascular). Morbidity rates per 10 000 deliveries were calculated using de-identified administrative claims in commercially insured women in the United States. Longitudinal data linked inpatient delivery episodes and 6-week postpartum period, and SMMs were assessed for present on admission and geographic variation. This retrospective analysis of 356 838 deliveries identified geographic variation in SMMs. For example, hemorrhage rates per 10 000 varied 3-fold across states from 279.7 in Alabama to 964.69 in Oregon. Administrative claims can be used to calculate SMM rates, identify geographic variations, and assess problems locally, nationally, and across payers. Identifying conditions present on admission and a postpartum window is valuable in differentiating events occurring during preadmission, inpatient stay, and postpartum periods. Targeting preventable SMMs through local and hospital-level interventions and limiting SMM progression through postdischarge monitoring may reduce the prevalence of SMM and postpartum complications.",
    "authors": [
        {
            "affiliation": "OptumLabs, Eden Prairie, Minnesota (Ms Chaisson and Drs Ameli and Thayer); Ariadne Labs, Boston, Massachusetts (Ms Paterson and Dr Weiseth); and ProgenyHealth, Plymouth Meeting, Pennsylvania (Dr Genen).",
            "firstname": "Christine E",
            "initials": "CE",
            "lastname": "Chaisson"
        },
        {
            "affiliation": null,
            "firstname": "Omid",
            "initials": "O",
            "lastname": "Ameli"
        },
        {
            "affiliation": null,
            "firstname": "Victoria J",
            "initials": "VJ",
            "lastname": "Paterson"
        },
        {
            "affiliation": null,
            "firstname": "Amber",
            "initials": "A",
            "lastname": "Weiseth"
        },
        {
            "affiliation": null,
            "firstname": "Linda",
            "initials": "L",
            "lastname": "Genen"
        },
        {
            "affiliation": null,
            "firstname": "Sarah",
            "initials": "S",
            "lastname": "Thayer"
        }
    ],
    "conclusions": null,
    "copyrights": "Copyright \u00a9 2021 The Authors. Published by Wolters Kluwer Health, Inc.",
    "doi": "10.1097/JPN.0000000000000580",
    "journal": "The Journal of perinatal & neonatal nursing",
    "keywords": [],
    "methods": null,
    "publication_date": "2021-06-26",
    "pubmed_id": "34171882",
    "results": null,
    "title": "Using a Claims-Based Framework to Identify Severe Maternal Morbidities in a Commercially Insured US Population.",
    "xml": "<Element 'PubmedArticle' at 0x78850615ecf0>"
}