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Standardizing Maternity Care Data to Improve Coordination of Care

Published:December 13, 2016DOI:https://doi.org/10.1016/j.jogn.2016.07.013

      Abstract

      The amount of data generated by health information technology systems is staggering, and using those data to make meaningful care decisions that improve patient outcomes is difficult. The purpose of this article is to describe the Maternal Health Information Initiative, a multidisciplinary group of maternity care stakeholders charged with standardizing maternity care data. Complementary strategies that practicing clinicians can use to support this initiative and improve the usability of maternity care data are provided.

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      References

        • Adler K.G.
        EHR dissatisfaction: Is it time to switch your EHR?.
        Family Practice Management. 2014; 21: 6
        • Adler-Milstein J.
        • Jha A.K.
        Sharing clinical data electronically: A critical challenge for fixing the health care system.
        Journal of the American Medical Association. 2012; 307: 1695-1696https://doi.org/10.1001/jama.2012.525
        • American College of Nurse-Midwives
        BirthTOOLS.org—Tools for optimizing the outcomes of labor safely: A framework for quality improvement.
        2016 (Retrieved from)
        • American College of Obstetricians and Gynecologists
        Executive summary: Collaboration in practice: Implementing team-based care: Report of the American College of Obstetricians and Gynecologists' task force on collaborative practice.
        Obstetrics & Gynecology. 2016; 127: 612-617https://doi.org/10.1097/AOG.0000000000001304
        • American College of Obstetricians and Gynecologists & Society for Maternal-Fetal Medicine
        Obstetric care consensus: Safe prevention of the primary cesarean delivery.
        2014 (Retrieved from)
        • American Congress of Obstetricians and Gynecologists (ACOG)
        reVITALize Obstetric Data Definitions.
        2012 (Retrieved from)
        • Amster A.
        • Jentzsch J.
        • Pasupuleti H.
        • Subramanian K.G.
        Completeness, accuracy, and computability of National Quality Forum-specified eMeasures.
        Journal of the American Medical Informatics Association. 2015; 22: 409-416https://doi.org/10.1136/amiajnl-2014-002865
        • Armijo D.
        • McDonnell C.
        • Werner K.
        Electronic health record usability: Evaluation and use case framework. AHRQ publication no. 09(10)-0091-1-EF.
        Agency for Healthcare Research and Quality, Rockville, MD2009 (Retrieved from)
        • Callaghan W.M.
        • Creanga A.A.
        • Kuklina E.V.
        Severe maternal morbidity among delivery and postpartum hospitalizations in the United States.
        Obstetrics & Gynecology. 2012; 120: 1029-1036https://doi.org/10.1097/AOG.0b013e31826d60c5
        • Charles D.
        • Gabriel M.
        • Furukawa M.F.
        Adoption of electronic health record systems among U.S. non-federal acute care hospitals: 2008–2013.
        (ONC data brief no. 16) Office of the National coordinator for Health Information Technology, Washington, DC2014 (Retrieved from)
        • Chow M.
        • Beene M.
        • O'Brien A.
        • Greim P.
        • Cromwell T.
        • DuLong D.
        • Bedecarre D.
        A nursing information model process for interoperability.
        Journal of the American Medical Informatics Association. 2015; 22: 608-614https://doi.org/10.1093/jamia/ocu026
        • Garde S.
        • Knaup P.
        • Hovenga E.
        • Heard S.
        Towards semantic interoperability for electronic health records.
        Methods of Information in Medicine. 2007; 46: 332-343https://doi.org/10.1160/me5001
        • Harris M.R.
        • Langford L.H.
        • Miller H.
        • Hook M.
        • Dykes P.C.
        • Matney S.A.
        Harmonizing and extending standards from a domain-specific and bottom-up approach: An example from development through use in clinical applications.
        Journal of the American Medical Informatics Association. 2015; 22: 545-552https://doi.org/10.1093/jamia/ocu020
        • Hawley G.
        • Jackson C.
        • Hepworth J.
        • Wilkinson S.A.
        Sharing of clinical data in a maternity setting: How do paper hand-held records and electronic health records compare for completeness?.
        BMC Health Services Research. 2014; 14: 1-9https://doi.org/10.1186/s12913-014-0650-x
        • Hayrinen K.
        • Saranto K.
        • Nykanen P.
        Definition, structure, content, use and impacts of electronic health records: A review of the research literature.
        International Journal of Medical Informatics. 2008; 77: 291-304https://doi.org/10.1016/j.ijmedinf.2007.09.001
        • Hsu W.
        • Taira R.K.
        • El-Saden S.
        • Kangarloo H.
        • Bui A.A.
        Context-based electronic health record: Toward patient specific healthcare.
        IEEE Transactions on Information Technology in Biomedicine. 2012; 16: 228-234https://doi.org/10.1109/TITB.2012.2186149
        • Hwang K.H.
        • Chung K.I.
        • Chung M.A.
        • Choi D.
        Review of semantically interoperable electronic health records for ubiquitous healthcare.
        Healthcare Informatics Research. 2010; 16: 1-5https://doi.org/10.4258/hir.2010.16.1.1
        • Integrating the Healtcare Enterprise
        Integrating the healthcare enterprise.
        2016 (Retrieved from)
        • Integrating the Healtcare Enterprise
        • Patient Care Coordination Technical Committee
        Antepartum profiles: Trial implementation.
        2011 (Retrieved from)
        • Kellermann A.L.
        • Jones S.S.
        What it will take to achieve the as-yet-unfulfilled promises of health information technology.
        Health Affairs. 2013; 32: 63-68https://doi.org/10.1377/hlthaff.2012.0693
        • Kinnunen U.M.
        • Saranto K.
        • Ensio A.
        • Iivanainen A.
        • Dykes P.
        Developing the standardized wound care documentation model: A Delphi study to improve the quality of patient care documentation.
        Journal of Wound, Ostomy, and Continence Nursing. 2012; 39: 397-407https://doi.org/10.1097/WON.0b013e318259c45b
        • Lagrew Jr., D.C.
        • Stutman H.R.
        • Sicaeros L.
        Voluntary physician adoption of an inpatient electronic medical record by obstetrician-gynecologists.
        American Journal of Obstetrics and Gynecology. 2008; 198: 6901-6906https://doi.org/10.1016/j.ajog.2008.03.022
        • Li Y.
        • Bai C.
        • Reddy C.K.
        A distributed ensemble approach for mining healthcare data under privacy constraints.
        Information Sciences. 2016; 330: 245-259https://doi.org/10.1016/j.ins.2015.10.011
        • Lim E.
        • Cheng Y.
        • Reuschel C.
        • Mbowe O.
        • Ahn H.J.
        • Juarez D.T.
        • Chen J.J.
        Risk-adjusted in-hospital mortality models for congestive heart failure and acute myocardial infarction: Value of clinical laboratory data and race/ethnicity.
        Health Services Research. 2015; 50: 1351-1371https://doi.org/10.1111/1475-6773.12325
        • March of Dimes
        Preterm birth: United States, 2003–2013.
        2016 (Retrieved from)
        • Menard M.K.
        • Main E.K.
        • Currigan S.M.
        Executive summary of the reVITALize initiative: Standardizing obstetric data definitions.
        Obstetrics & Gynecology. 2014; 124: 150-153https://doi.org/10.1097/aog.0000000000000322
        • Miller H.D.
        Transitioning to accountable care: Incremental payment reforms to support higher quality, more affordable healthcare.
        Center forHealthcare Quality and Payment Reform, Pittsburgh, PA2011 (Retrieved from)
        • Monsen K.A.
        • Finn R.S.
        • Fleming T.E.
        • Garner E.J.
        • LaValla A.J.
        • Riemer J.G.
        Rigor in electronic health record knowledge representation: Lessons learned from a SNOMED CT clinical content encoding exercise.
        Informatics for Health & Social Care. 2014; 41: 97-111https://doi.org/10.3109/17538157.2014.965302
        • Monsen K.A.
        • Peters J.
        • Schlesner S.
        • Vanderboom C.E.
        • Holland D.E.
        The gap in Big Data: Getting to wellbeing, strengths, and a whole-person perspective.
        Global advances in health and medicine. 2015; 4: 31-39https://doi.org/10.7453/gahmj.2015.040
        • National Quality Forum
        Review and Update of Guidance for Evaluating Evidence and Measure Testing - Technical Report.
        2013 (Retrieved from)
      1. Office of the National Coordinator for Health Information Technology. (2016). 2015 interoperability standards advisory. Retrieved from https://www.healthit.gov/standards-advisory

        • Office of the National Coordinator for Health Information Technology & Department of Health and Human Services
        Health information technology: Initial set of standards, implementation specifications, and certification criteria for electronic health record technology. Final rule.
        Federal Register. 2010; 75: 44589-44654
        • Pfoh E.R.
        • Abramson E.L.
        • Zandieh S.O.
        • Edwards A.
        • Kaushal R.
        Satisfaction after the transition between electronic health record systems at six ambulatory practices.
        Journal of Evaluation in Clinical Practice. 2012; 18: 1133-1139https://doi.org/10.1111/j.1365-2753.2011.01756.x
        • Simon S.R.
        • Kaushal R.
        • Cleary P.D.
        • Jenter C.A.
        • Volk L.A.
        • Orav E.J.
        • Bates D.W.
        Physicians and electronic health records: A statewide survey.
        Archives of Internal Medicine. 2007; 167: 507-512https://doi.org/10.1001/archinte.167.5.507
        • Tang P.C.
        • Ralston M.
        • Arrigotti M.F.
        • Qureshi L.
        • Graham J.
        Comparison of methodologies for calculating quality measures based on administrative data versus clinical data from an electronic health record system: Implications for performance measures.
        Journal of the American Medical Informatics Association. 2007; 14: 10-15https://doi.org/10.1197/jamia.M2198
      2. The Joint Commission. (2016). Perinatal care. Retrieved from https://www.jointcommission.org/perinatal_care

      Biography

      Catherine H. Ivory, PhD, RNC-OB, RN, BC, is an assistant professor in the School of Nursing, Vanderbilt University, Nashville, TN.

      Biography

      Maria Freytsis, CNM, MPH, is an independent consultant, Washington, DC.

      Biography

      David C. Lagrew Jr., MD, is Chief Integration and Accountability Officer, MemorialCare Health System, Fountain Valley, CA.

      Biography

      Dale Magee, MD, MS, is an associate professor of clinical obstetrics and gynecology, Massachusetts Medical School, Worcester, MA.

      Biography

      Manuel C. Vallejo, MD, DMD, is a professor and Chair of the Department of Anesthesiology, West Virginia University, Morgantown, WV.

      Biography

      Steve Hasley, MD, is Chief Medical Information Officer, American College of Obstetricians and Gynecologists, Washington, DC.

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