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Original Articles

Development and validation of the Neonatal Abstinence Syndrome Minimum Data Set (NAS-MDS): a systematic review, focus group discussion, and Delphi technique

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Pages 617-624 | Received 03 Jun 2019, Accepted 12 Feb 2020, Published online: 13 Oct 2020
 

Abstract

Objectives

Neonatal abstinence syndrome (NAS) is a combination of symptoms in infants exposed to any variety of substances in utero. Information systems and registries help to collect information about these patients; however, there is always a deep gap between complete and accurate information to be collected, understood, and applied in the health care system; thus, defining a minimum data sets (MDS) as one of the primarily steps of designing a registry system is essential. The aim of this study was to develop an MDS of the registry for infants with NAS in Iran.

Methods

This research is a descriptive cross-sectional study. In this study, three steps were carried out to develop the MDS including systematic review, Delphi technique, and focus group discussion. A systematic review was conducted in relevant databases to identify appropriate related data. In the second phase, a focus group discussion was used to classify the extracted data elements by contributing neonatologists. Finally, data elements were chosen through the decision Delphi technique in two distinct rounds. Collected data were analyzed using SPSS 22 (SPSS Inc., Chicago, IL).

Results

By reviewing related papers and available NAS registries in other countries, 145 essential data elements were identified. They were classified into two main categories based on the eight experts’ opinions including maternal with two sections and infant with two sections. After applying two rounds of Delphi technique, the final data elements for maternal and infant categories were 42 and 31, respectively. Thus, on completion of the survey, 73 data elements were approved.

Conclusion

The proposed MDS for NAS can help to store an accurate and comprehensive data, document medical records, integrate them with other information systems and registries, and communicate with other healthcare providers and healthcare centers. This MDS can contribute to the provision of high-quality care and better clinical decisions.

Acknowledgements

This study was part of the first author’s PhD dissertation, which was supported by a grant from Patient Registry and Health Outcome Secretariat, Deputy of Research, Tehran University of Medical Sciences. I would like to thank all neonatologists who participated in this study and played a role in the validation of the data elements. We also wish to acknowledge Dr Mostafa Mirmohammadi, Dr Habib Masoudi Farid, Dr Ardeshir Sheikhazadi, Dr Reza Jafari Sedehi, Dr Alireza Parsapour, Dr Marjan Kouhnavard, Dr Sedigheh Borna, and Dr Mahsa Asadabadi, Dr Kayvan Mirnia, Dr Razieh Sangsari, Dr Maryam Saeedi, Dr Maryam Valizadeh, Mrs. Mahrokh Gholdost, and Mrs. Maryam Bazaz Rastgar for their vital and esteemed opinion on the metrics to be included in a minimum data set.

Disclosure statement

The authors declare that there is no conflict of interest.

Additional information

Funding

Part of this work was supported by the Community Based Participatory Research Center of Tehran University of Medical Sciences, under project no. [96-03-62-36 398] and Patient Registry and Health Outcome Secretariat, Deputy of Research, Tehran University of Medical Sciences.

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