Midwifery Data Collection: Options and Opportunities

Accuracy in Reporting of Kentucky Certified Nurse-Midwives as Attendants in Birth Registration Data

INTRODUCTION

Birth certificate data are used nationally to determine health care policy and health care reimbursement and to demonstrate the legitimacy and value of certified nurse-midwives (CNMs) and certified midwives (CMs) in perinatal and neonatal outcomes. However, the validity of birth certificate data is questionable, in part because of the data collection process. These data are particularly crucial for midwife-attended births because the correct birth attendant is not always accurately identified on the birth certificate. The purpose of this project was to examine the actual number of CNM-reported births compared with those recorded by the Kentucky Office of Vital Statistics and to examine the process used by birth registrars to complete the birth certificate.

METHODS

CNMs attending births in hospitals in Kentucky in 2017 logged their birth statistics. These numbers were compared with the 2017 Kentucky Vital Statistics Birth Certificate data of CNM-attended births. Kentucky birth registrars (50%) who work in facilities where CNMs attend births completed a 32-question survey to describe their process of collecting birth certificate data.

RESULTS

The comparison data revealed that CNM-attended births in Kentucky are underrepresented in the state vital statistics by as much as 19.2%. Birth registrars identified barriers to collecting accurate data including lack of training, multiple sources of data, incomplete prenatal records, and absence of systems to help ensure accuracy.

DISCUSSION

CNMs/CMs should keep personal and practice birth logs and routinely compare these with hospital data kept by the birth registrar. The state office of vital statistics and hospitals should target training to specific facilities that have the most inaccurate data. The Improving Midwifery Birth Numbers Initiative through the American College of Nurse-Midwives Division of Research Data Management Section should continue to encourage midwifery students to complete this research in all 50 states.

National Minimum Data Set for Antimicrobial Resistance Management: Toward Global Surveillance System

BACKGROUND

Success of infection treatment depends on the availability of accurate, reliable, and comprehensive data, information, and knowledge at the point of therapeutic decision-making. The identification of a national minimum data set will support the development and implementation of an effective surveillance system. The goal of this study was to develop a national antimicrobial resistance surveillance minimum data set.

METHODS

In this cross-sectional and descriptive study, data were collected from selected pioneering countries and organizations which have national or international antimicrobial resistance surveillance systems. A minimum data set checklist was extracted and validated. The ultimate data elements of the minimum data set were determined by applying the Delphi technique.

RESULTS

Through the Delphi technique, we obtained 80 data elements in 8 axes. The resistance data categories comprised basic, clinical, electronic reporting, infection control, microbiology, pharmacy, World Health Organization-derived, and expert-recommended data. Relevance coding was extracted based on the Iranian electronic health record coding system.

CONCLUSION

This study provides a set of data elements and a schematic framework for the implementation of an antimicrobial resistance surveillance system. A uniform minimum data set was created based on key informants' opinions to cover essential needs in the early implementation of a global antimicrobial resistance surveillance system in Iran.

The American College of Nurse-Midwives Clarity in Collaboration Project: Describing Midwifery Care in Interprofessional Collaborative Care Models

In 2014, the American College of Nurse-Midwives (ACNM) launched a project called Clarity in Collaboration to develop data definitions related to midwifery and maternity care delivery processes. These definitions are needed to ensure midwifery care delivered in collaborative care models is accurately and consistently captured in clinical documentation systems, data registries, and systems being developed as part of health care restructuring and payment reform. The Clarity in Collaboration project builds on the efforts of the Women's Health Registry Alliance (WHRA), which was recently established by the American College of Obstetricians and Gynecologists. Clarity in Collaboration mirrored the process used by ReVITALize, WHRA's first maternity data standardization project, which focused on establishing standardized clinical data definitions for obstetrics. The ACNM Clarity in Collaboration project brought together maternity and midwifery care experts to complete a year-long consensus process, including a period of public comment, resulting in development of 20 concept definitions. These definitions can be used to describe midwifery care within the context of collaborative care models. This article provides a summary of the ACNM Clarity in Collaboration process with discussion of implications for maternity data collection.

A modified Delphi consensus study to identify UK osteopathic profession research priorities

There is an increasing emphasis to take an evidence-based approach to healthcare. To obtain evidence relevant to the osteopathic profession a clear research direction is required based on the views of stakeholders in the osteopathic profession. A modified Delphi consensus approach was conducted to explore the views of osteopaths and patients regarding research priorities for osteopathy. Osteopaths and patients were invited to complete an online questionnaire survey (n = 145). Round 1 requested up to 10 research priority areas and the rationale for their selection. All of the themes from Round 1 were fed back verbatim, and in Round 2 participants were asked to rank the importance of the research priorities on a 5-point Likert scale. Finally, in Round 3 participants were asked to rank the importance of a refined list of research topics which had reached consensus. Descriptive analysis and use of Kendall's coefficient of concordance enabled interpretation of consensus. The response rate for Round 1 was 87.9% and identified 610 research priority areas. Round 2 identified 69 research themes as important, and Round 3 identified 20 research priority topic areas covering four themes: effectiveness of osteopathic treatment (7 areas prioritised), role of osteopathy: the management of four conditions were prioritised, risks with osteopathic treatment (two areas prioritised) and outcomes of osteopathic treatment (two areas prioritised). The findings will be taken forward to develop the research strategy for osteopathy.