Optimizing data collection for obstetrical ultrasound research at the primary health care level in rural Uganda
Background Neonatal and maternal mortality remains high in low- and middle-income countries (LMIC), especially in sub-Saharan Africa. Quality data collection is crucial to understand the magnitude of these problems and to measure the impact of interventions aimed at improving neonatal and maternal m...
Saved in:
| Main Authors: | , , , , , , , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2024-12-01
|
| Series: | Global Health Action |
| Subjects: | |
| Online Access: | http://dx.doi.org/10.1080/16549716.2024.2436715 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1832096716266930176 |
|---|---|
| author | Renny Ssembatya Abimbola Leslie Kristen DeStigter Erika M. Edwards Joyce Nayiga Samalie Nakibirango Julian P. Arapa Nicholas Bahati Blandina Busingye Thomas Eremu Mary Nakafeero Micheal F. Ssenoga Frank B. Williams Delia Horn |
| author_facet | Renny Ssembatya Abimbola Leslie Kristen DeStigter Erika M. Edwards Joyce Nayiga Samalie Nakibirango Julian P. Arapa Nicholas Bahati Blandina Busingye Thomas Eremu Mary Nakafeero Micheal F. Ssenoga Frank B. Williams Delia Horn |
| author_sort | Renny Ssembatya |
| collection | DOAJ |
| description | Background Neonatal and maternal mortality remains high in low- and middle-income countries (LMIC), especially in sub-Saharan Africa. Quality data collection is crucial to understand the magnitude of these problems and to measure the impact of interventions aimed at improving neonatal and maternal mortality. However, data collection in the low-income country setting, especially in rural areas, has been a challenge for researchers, policy makers, and public health officials. Here, we describe the methodology, experience and lessons learned while collecting data at lower-level primary health care facilities in rural Uganda. Methods Data collection was performed at Health Center III sites in rural Uganda, in partnership with Imaging the World and its affiliate Imaging the World Africa. The primary purpose of the data collection was to study the efficacy and clinical effect of introducing prenatal ultrasound services at these sites. Local data clerks were hired to perform the data collection through a combination of intensive training and on-the-ground support. Frequent oversight was used to support data collection. Results Of 2,397 enrolled pregnant women, 1,977 (82.5%) had complete outcome data. Upon independent expert audit, the data were >80% accurate for 10/11 variables and >90% accurate for 6/11 variables. Overall, the data collected at the rural HCs were 90% accurate. Discussion Accurate and complete data collection is possible in an LMIC setting if appropriate training and oversight are employed. |
| format | Article |
| id | doaj-art-fb674375bf264dc6954869c46d4f924b |
| institution | Kabale University |
| issn | 1654-9880 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | Global Health Action |
| spelling | doaj-art-fb674375bf264dc6954869c46d4f924b2025-02-05T12:46:14ZengTaylor & Francis GroupGlobal Health Action1654-98802024-12-0117110.1080/16549716.2024.24367152436715Optimizing data collection for obstetrical ultrasound research at the primary health care level in rural UgandaRenny Ssembatya0Abimbola Leslie1Kristen DeStigter2Erika M. Edwards3Joyce Nayiga4Samalie Nakibirango5Julian P. Arapa6Nicholas Bahati7Blandina Busingye8Thomas Eremu9Mary Nakafeero10Micheal F. Ssenoga11Frank B. Williams12Delia Horn13Imaging the World AfricaUniversity of Vermont Medical CenterThe University of VermontThe University of VermontMakerere University College of Health SciencesImaging the World Consortium for Health LimitedData ClerkData ClerkData ClerkData ClerkMakerere UniversityImaging the World Center for Health and InnovationOchsner Baptist Medical CenterThe University of Vermont, University of Vermont Medical CenterBackground Neonatal and maternal mortality remains high in low- and middle-income countries (LMIC), especially in sub-Saharan Africa. Quality data collection is crucial to understand the magnitude of these problems and to measure the impact of interventions aimed at improving neonatal and maternal mortality. However, data collection in the low-income country setting, especially in rural areas, has been a challenge for researchers, policy makers, and public health officials. Here, we describe the methodology, experience and lessons learned while collecting data at lower-level primary health care facilities in rural Uganda. Methods Data collection was performed at Health Center III sites in rural Uganda, in partnership with Imaging the World and its affiliate Imaging the World Africa. The primary purpose of the data collection was to study the efficacy and clinical effect of introducing prenatal ultrasound services at these sites. Local data clerks were hired to perform the data collection through a combination of intensive training and on-the-ground support. Frequent oversight was used to support data collection. Results Of 2,397 enrolled pregnant women, 1,977 (82.5%) had complete outcome data. Upon independent expert audit, the data were >80% accurate for 10/11 variables and >90% accurate for 6/11 variables. Overall, the data collected at the rural HCs were 90% accurate. Discussion Accurate and complete data collection is possible in an LMIC setting if appropriate training and oversight are employed.http://dx.doi.org/10.1080/16549716.2024.2436715imaging the worldimaging the world africalow- and middle-income countriesprenatal ultrasoundneonatal mortalitymaternal mortalitydata accuracydata completeness |
| spellingShingle | Renny Ssembatya Abimbola Leslie Kristen DeStigter Erika M. Edwards Joyce Nayiga Samalie Nakibirango Julian P. Arapa Nicholas Bahati Blandina Busingye Thomas Eremu Mary Nakafeero Micheal F. Ssenoga Frank B. Williams Delia Horn Optimizing data collection for obstetrical ultrasound research at the primary health care level in rural Uganda Global Health Action imaging the world imaging the world africa low- and middle-income countries prenatal ultrasound neonatal mortality maternal mortality data accuracy data completeness |
| title | Optimizing data collection for obstetrical ultrasound research at the primary health care level in rural Uganda |
| title_full | Optimizing data collection for obstetrical ultrasound research at the primary health care level in rural Uganda |
| title_fullStr | Optimizing data collection for obstetrical ultrasound research at the primary health care level in rural Uganda |
| title_full_unstemmed | Optimizing data collection for obstetrical ultrasound research at the primary health care level in rural Uganda |
| title_short | Optimizing data collection for obstetrical ultrasound research at the primary health care level in rural Uganda |
| title_sort | optimizing data collection for obstetrical ultrasound research at the primary health care level in rural uganda |
| topic | imaging the world imaging the world africa low- and middle-income countries prenatal ultrasound neonatal mortality maternal mortality data accuracy data completeness |
| url | http://dx.doi.org/10.1080/16549716.2024.2436715 |
| work_keys_str_mv | AT rennyssembatya optimizingdatacollectionforobstetricalultrasoundresearchattheprimaryhealthcarelevelinruraluganda AT abimbolaleslie optimizingdatacollectionforobstetricalultrasoundresearchattheprimaryhealthcarelevelinruraluganda AT kristendestigter optimizingdatacollectionforobstetricalultrasoundresearchattheprimaryhealthcarelevelinruraluganda AT erikamedwards optimizingdatacollectionforobstetricalultrasoundresearchattheprimaryhealthcarelevelinruraluganda AT joycenayiga optimizingdatacollectionforobstetricalultrasoundresearchattheprimaryhealthcarelevelinruraluganda AT samalienakibirango optimizingdatacollectionforobstetricalultrasoundresearchattheprimaryhealthcarelevelinruraluganda AT julianparapa optimizingdatacollectionforobstetricalultrasoundresearchattheprimaryhealthcarelevelinruraluganda AT nicholasbahati optimizingdatacollectionforobstetricalultrasoundresearchattheprimaryhealthcarelevelinruraluganda AT blandinabusingye optimizingdatacollectionforobstetricalultrasoundresearchattheprimaryhealthcarelevelinruraluganda AT thomaseremu optimizingdatacollectionforobstetricalultrasoundresearchattheprimaryhealthcarelevelinruraluganda AT marynakafeero optimizingdatacollectionforobstetricalultrasoundresearchattheprimaryhealthcarelevelinruraluganda AT michealfssenoga optimizingdatacollectionforobstetricalultrasoundresearchattheprimaryhealthcarelevelinruraluganda AT frankbwilliams optimizingdatacollectionforobstetricalultrasoundresearchattheprimaryhealthcarelevelinruraluganda AT deliahorn optimizingdatacollectionforobstetricalultrasoundresearchattheprimaryhealthcarelevelinruraluganda |