Analysis of low resource setting referral pathways to improve coordination and evidence-based services for maternal and child health in Ethiopia.


Journal

PloS one
ISSN: 1932-6203
Titre abrégé: PLoS One
Pays: United States
ID NLM: 101285081

Informations de publication

Date de publication:
2022
Historique:
received: 25 06 2021
accepted: 08 08 2022
entrez: 25 8 2022
pubmed: 26 8 2022
medline: 30 8 2022
Statut: epublish

Résumé

In low-resource settings, patient referral to a hospital is an essential part of the primary health care system. However, there is a paucity of study to explore the challenges and quality of referral coordination and communication. The purpose of this research was to analyze the existing paper-based referral registration logbook for maternal and child health in general and women of reproductive age in particular, to improve referral coordination and evidence-based services in Low-Resource Settings. This study analyzed the existing paper-based referral registration logbook (RRL) and card-sheet to explore the documentation of the referral management process, and the mechanism and quality of referrals between the health center (Jimma Health Center-case, Ethiopia) and the Hospital. A sample of 459 paper-based records from the referral registration logbook were digitized as part of a retrospective observational study. For data preprocessing, visualization, and analysis, we developed a python-based interactive referral clinical pathway tool. The data collection was conducted from August to October 2019. Jimma Health Center's RRL was used to examine how the referral decision was made and what cases were referred to the next level of care. However, the RRL was incomplete and did not contain the expected referral feedback from the hospital. Hence, we defined a new protocol to investigate the quality of referral. We compared the information in the health center's RRL with the medical records in the hospital to which the patients were referred. A total of 201 medical records of referred patients were examined. A total of 459 and 201 RRL records from the health center and the referred hospital, respectively, were analyzed in the study. Out of 459, 86.5% referred cases were between the age of 20 to 30 years. We found that "better patient management", "further patient management", and "further investigation" were the main health-center referral reasons and decisions. It accounted for 40.08%, 39.22%, and 16.34% of all 459 referrals, respectively. The leading and most common referral cases in the health center were long labor, prolonged first and second stage labor, labor or delivery complicated by fetal heart rate anomaly, preterm newborn, maternal care with breech presentation, premature rupture of membranes, malposition of the uterus, and antepartum hemorrhage. In the hospital RRL and card-sheet, the main referral-in reasons were technical examination, expert advice, further management, and evaluation. We found it overall impossible to match records from the referral logbook in the health center with the patient files in the hospital. Out of 201, only 13.9% of records were perfect matching entries between health center and referred hospital RRL. We found 84%, 14.4%, and 1.6% were appropriate, unnecessary and unknown referrals respectively. The paper illustrates the bottlenecks encountered in the quality assessment of the referrals. We analyzed the current status of the referral pathway, existing communications, guidelines and data quality, as a first step towards an end-to-end effective referral coordination and evidence-based referral service. Accessing, monitoring, and tracking the history of referred patients and referral feedback is challenging with the present paper-based referral coordination and communication system. Overall, the referral services were inadequate, and referral feedback was not automatically delivered, causing unnecessary delays.

Sections du résumé

BACKGROUND
In low-resource settings, patient referral to a hospital is an essential part of the primary health care system. However, there is a paucity of study to explore the challenges and quality of referral coordination and communication.
OBJECTIVE
The purpose of this research was to analyze the existing paper-based referral registration logbook for maternal and child health in general and women of reproductive age in particular, to improve referral coordination and evidence-based services in Low-Resource Settings.
METHODS
This study analyzed the existing paper-based referral registration logbook (RRL) and card-sheet to explore the documentation of the referral management process, and the mechanism and quality of referrals between the health center (Jimma Health Center-case, Ethiopia) and the Hospital. A sample of 459 paper-based records from the referral registration logbook were digitized as part of a retrospective observational study. For data preprocessing, visualization, and analysis, we developed a python-based interactive referral clinical pathway tool. The data collection was conducted from August to October 2019. Jimma Health Center's RRL was used to examine how the referral decision was made and what cases were referred to the next level of care. However, the RRL was incomplete and did not contain the expected referral feedback from the hospital. Hence, we defined a new protocol to investigate the quality of referral. We compared the information in the health center's RRL with the medical records in the hospital to which the patients were referred. A total of 201 medical records of referred patients were examined.
RESULTS
A total of 459 and 201 RRL records from the health center and the referred hospital, respectively, were analyzed in the study. Out of 459, 86.5% referred cases were between the age of 20 to 30 years. We found that "better patient management", "further patient management", and "further investigation" were the main health-center referral reasons and decisions. It accounted for 40.08%, 39.22%, and 16.34% of all 459 referrals, respectively. The leading and most common referral cases in the health center were long labor, prolonged first and second stage labor, labor or delivery complicated by fetal heart rate anomaly, preterm newborn, maternal care with breech presentation, premature rupture of membranes, malposition of the uterus, and antepartum hemorrhage. In the hospital RRL and card-sheet, the main referral-in reasons were technical examination, expert advice, further management, and evaluation. We found it overall impossible to match records from the referral logbook in the health center with the patient files in the hospital. Out of 201, only 13.9% of records were perfect matching entries between health center and referred hospital RRL. We found 84%, 14.4%, and 1.6% were appropriate, unnecessary and unknown referrals respectively.
CONCLUSION
The paper illustrates the bottlenecks encountered in the quality assessment of the referrals. We analyzed the current status of the referral pathway, existing communications, guidelines and data quality, as a first step towards an end-to-end effective referral coordination and evidence-based referral service. Accessing, monitoring, and tracking the history of referred patients and referral feedback is challenging with the present paper-based referral coordination and communication system. Overall, the referral services were inadequate, and referral feedback was not automatically delivered, causing unnecessary delays.

Identifiants

pubmed: 36007079
doi: 10.1371/journal.pone.0273436
pii: PONE-D-21-20872
pmc: PMC9409580
doi:

Types de publication

Journal Article Observational Study

Langues

eng

Sous-ensembles de citation

IM

Pagination

e0273436

Déclaration de conflit d'intérêts

The authors have declared that no competing interests exist.

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Auteurs

Geletaw Sahle Tegenaw (GS)

Department of Electronics and Informatics (ETRO), Vrije Universiteit Brussel (VUB), Brussel, Belgium.
Faculty of Computing, JiT, Jimma University, Jimma, Ethiopia.

Demisew Amenu (D)

Department of Obstetrics and Gynecology, College of Health Science, Jimma University, Jimma, Ethiopia.

Girum Ketema (G)

Faculty of Computing, JiT, Jimma University, Jimma, Ethiopia.

Frank Verbeke (F)

Department of Electronics and Informatics (ETRO), Vrije Universiteit Brussel (VUB), Brussel, Belgium.

Jan Cornelis (J)

Department of Electronics and Informatics (ETRO), Vrije Universiteit Brussel (VUB), Brussel, Belgium.

Bart Jansen (B)

Department of Electronics and Informatics (ETRO), Vrije Universiteit Brussel (VUB), Brussel, Belgium.
imec, Leuven, Belgium.

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Classifications MeSH