Browsing by Author "Kayemba, Frank"

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    Factors associated with longer hospital stay following caesarean section birth at a tertiary hospital in Eastern Uganda.
    (Research Square, 2025) Thaddeus, Jude Mulowooza; Tweheyo, Ronald; Babuya, Jonathan; Atuhairwe, Irene; Makoko, Brian Tonny; Waako, Paul; Twineamatsiko, Andrew; Agaba, Brian; Stephen, Obbo; Kavuma, Pontian Kiwanuka; Kibuule, Dan; Kayemba, Frank; Kagoya, Enid Kawala
    Background. Caesarean Section(C/S) is a lifesaving procedure for both the mother and the baby but it is associated with various post-operative complications and longer hospital stays. Prolonged Hospitalization after a Caesarean section can be stressful for both the healthcare providers and the mothers while also risking them acquiring hospital acquired infections. Factors related to longer hospital stays among mothers delivered by C/S have not been well explored. This study aimed to determine the factors associated with longer (> 4 days) hospital stay following Caesarean birth at Mbale Regional Referral Hospital. Methods This was a retrospective cross-sectional study carried out at Mbale Regional Referral Hospital (MRRH) between December 2023 and May 2024 accessed in June 2024. A total of 536 patient files of women who underwent Caesarean section were randomly selected and reviewed. Data on social demographics, obstetric characteristics and other surgical details including outcomes was extracted and recorded using an online data collection tool. Descriptive analysis to summarise the data and logistic regression to identify factors associated with longer hospital stays were done, and P-values < 0.05 significance level at a 95% confidence interval were considered. Results The mean hospital stay was 4.02 days (SD ± 2.87). Nearly half of the women (47.6%) were referred from other health facilities with most caesarean sections (70.9%) sanctioned by junior house officers. Preoperative prophylactic antibiotics were administered in 85.4% and spinal anaesthesia was used in 98.5% of the Csections. In multivariable analysis, lack of a complete blood count, vaginal preparation, intravenous fluids before surgery and a patient undergoing general anesthesia were significantly related to longer hospital stays. Conclusion Multiple factors are associated with longer hospital stays at Mbale Regional Referral Hospital. Improvement of evidence-based practices such as the intravenous fluids, vaginal preparation and basic laboratory investigations before surgery and use of spinal anesthesia can help to reduce hospital stay and its associated risks. Keywords: Caesarean section, longer hospital stay, postoperative complications
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    “I can no longer give take-home exams”: health professionals educators’ experiences and perceptions regarding the use of artificial intelligence in health professions education in Uganda.
    (BMC, 2025) Mukunya, David; Nantale, Ritah; Paungholi, Kennedy; Epuitai, Joshua; Kayemba, Frank; Jemba, Brian; Ajalo, Elizabeth; Afodun, Adam; Musaba, Milton W.; Munabi, Ian G.; Kiguli, Sarah; Mubuuke, A. G.
    Introduction: Artificial intelligence (AI) tools offer immense opportunities and challenges for medical education. However, there is limited information about the use of AI among health professional educators, particularly in low and middle-income countries. We aimed to explore the experiences and perceptions regarding AI use in health professional education. Methods and materials: We collected qualitative data using in-depth interviews with 19 health professional educators. The interviews were audio-recorded and transcribed verbatim. We used Atlas Ti version 9.1 to organise the data. We used Braun and Clarke’s six-step thematic analysis for data analysis. The study was approved by the Busitema University Research and Ethics Committee (BUFHS-2023-79). Results: Three major themes were identified from the data: uptake and use of AI, perceived benefits of AI in health professional education, and concerns regarding AI use. We noted initial reluctance to support AI use, while its use varied from no or infrequent use to frequent use. Health professional educators used AI for various reasons, such as for teaching, student assessment, research, and personal work. AI was perceived to be beneficial in improving the clarity of writing, providing access to individual-tailored information, teaching, learning, and assessment, and research purposes. The barriers to AI use included a lack of institutional policies to guide AI use, limited capacity to afford paid AI versions, and reluctance to use AI. AI was seen to have inherent limitations, which included inaccurate information and a lack of contextual information for resource-limited settings. The fears of AI use included the risk of over-reliance on AI, academic misconduct, examination malpractice, ethical conflicts, and integrity. Conclusion: AI use in health professional education was perceived to have some benefits, amidst concerns that may derail its use in health professional education. The lack of policy and guidelines to govern the use of AI in health professions education underscores the need to develop policies and guidelines that safeguard and promote responsible and ethical use of AI. Keywords Health professional education, Artificial intelligence, Educators, Uganda
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    Utilisation of ChatGPT and other Artificial Intelligence tools among medical faculty in Uganda : a cross-sectional study.
    (MedEdPublish, 2025) Mukunya, David; Nantale, Ritah; Kayemba, Frank; Ajalo, Elizabeth; Pangholi, Kennedy; Babuya, Jonathan; Akuu, Suzan Langoya; Namiiro, Amelia Margaret; Tweheyo, Ronald; Ekak, Steven; Nakitto, Brenda; Nantongo, Kirsten; Mpagi, Joseph Luwaga; Musaba, Milton W.; Oguttu, Faith; Kuteesa, Job; Mubuuke, Aloysius Gonzaga; Munabi, Ian Guyton; Kiguli, Sarah
    Background ChatGPT is a large language model that uses deep learning techniques to generate human-like texts. ChatGPT has the potential to revolutionize medical education as it acts as an interactive virtual tutor and personalized learning assistant. We assessed the use of ChatGPT and other Artificial Intelligence (AI) tools among medical faculty in Uganda. Methods We conducted a descriptive cross-sectional study among medical faculty at four public universities in Uganda from November to December 2023. Participants were recruited consecutively. We used a semi-structured questionnaire to collect data on participants’ sociodemographics and the use of AI tools such as ChatGPT. Our outcome variable was the use of ChatGPT and other AI tools. Data were analyzed in Stata version 17.0. Results We recruited 224 medical faculty, majority [75% (167/224)] were male. The median age (interquartile range) was 41 years (34–50). Almost all medical faculty [90% (202/224)] had ever heard of AI tools such as ChatGPT. Over 63% (120/224) of faculty had ever used AI tools. The most commonly used AI tools were ChatGPT (56.3%) and Quill Bot (7.1%). Fifty-six faculty use AI tools for research writing, 37 for summarizing information, 28 for proofreading work, and 28 for setting exams or assignments. Forty faculty use AI tools for nonacademic purposes like recreation and learning new skills. Faculty older than 50 years were 40% less likely to use AI tools compared to those aged 24 to 35 years (Adjusted Prevalence Ratio (aPR):0.60; 95% Confidence Interval (CI): [0.45, 0.80]). Conclusion The use of ChatGPT and other AI tools was high among medical faculty in Uganda. Older faculty (>50 years) were less likely to use AI tools compared to younger faculty. Training on AI use in education, formal policies, and guidelines are needed to adequately prepare medical faculty for the integration of AI in medical education. Keywords ChatGPT, medical faculty, Bing, Bard, Uganda, generative AI, medical education
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    Watching over life : practices and meanings of postpartum vital signs monitoring in eastern Uganda.
    (medRxiv, 2025) Babuya, Jonathan; Kayemba, Frank; Waiswa, Sinani; Nsubuga, Allan G.; Ewing, Helen; Atuhairwe, Irene; Ijangolet, Esther; Otim, Eric; Ronald, Kibuuka; Jesca, Atugonza; Okello, Francis; Nakattudde, Prossy; Nyangoma, Faith; Nakawuka, Betty; Kabahinda, Nichola; Kamwesigye, Assen; Apoya, Jill; Waako, Paul; Wandabwa, Julius; Musaba, Milton; Bonaventure, Ahaisibwe; Aeby, Tod; Nandutu, Sarah; Mugabe, Kenneth; Pangholi, Kennedy; Nahurira, Doreck; Agaba, Brian; Mbwali, Immaculate; Bahati, Johnson; Kagoya, Enid Kawala
    Introduction Postnatal deaths account for about one-third of maternal mortality in Low- and middle-income countries (LMICs). Nearly half occur within the first 24 hours and are preventable through continuous inpatient monitoring. This study assessed maternal mortality within the first 24 postnatal hours; and the current postpartum monitoring practices, including the availability of monitoring charts and the frequency of vital sign assessments in eastern Uganda. Methods This cross-sectional study reviewed the medical records of all postpartum women admitted at Mbale Regional Referral Hospital, Eastern Uganda, between August 2022 and February 2023. A semi-structured data extraction form was used. The outcome variable was postpartum monitoring; categorized as "No" for women with no vital signs monitored and "Yes" for those with at least one vital sign monitored. Descriptive analysis was performed using Stata Version 17.0, and Poisson regression was employed to explore the association between various factors and postpartum monitoring. Results Medical records of 2,717 postpartum mothers were reviewed. The median (interquartile range) age was 25(20-30) years. A minority (34%; 910/2717) of mothers had vital sign observation charts in their medical records and very few (4%; 110/2717) had a fluid balance chart. About 49 24% (651/2717) of mothers had at least one vital sign recorded. Blood pressure was the most (16.8%; 456/2717) recorded vital sign followed by pulse rate (13.6%; 369/2717). Respiratory rate and temperature were the least monitored vital signs with 1.2% and 1.1% records respectively. Mothers who delivered by C-section had a 151% higher prevalence of postpartum monitoring compared to those who had a vaginal delivery (aPR: 2.51; 95% CI: 2.19–2.89). Maternal mortality rate on the first postpartum day was 8.8 per 1000, with postpartum hemorrhage accounting for 61%. Conclusion Postpartum vital signs monitoring was low. LMICs need to devise means of automating the monitoring process.
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    Widespread use of ChatGPT and other Artificial Intelligence tools among medical students in Uganda : a cross-sectional study.
    (PLOS One, 2025) Ajalo, Elizabeth; Mukunya, David; Nantale, Ritah; Kayemba, Frank; Pangholi, Kennedy; Babuya, Jonathan; Akuu, Suzan Langoya; Namiiro, Amelia Margaret; Nsubuga, Yakobo Baddokwaya; Mpagi, Joseph Luwaga; Musaba, Milton W.; Oguttu, Faith; Kuteesa, Job; Mubuuke, Aloysius Gonzaga; Munabi, Ian Guyton; Kiguli, Sarah
    Background Chat Generative Pre-trained Transformer (ChatGPT) is a 175-billion-parameter natural language processing model that uses deep learning algorithms trained on vast amounts of data to generate human-like texts such as essays. Consequently, it has introduced new challenges and threats to medical education. We assessed the use of ChatGPT and other AI tools among medical students in Uganda. Methods We conducted a descriptive cross-sectional study among medical students at four public universities in Uganda from 1st November 2023 to 20th December 2023. Participants were recruited by stratified random sampling. We used a semi-structured questionnaire to collect data on participants’ socio-demographics and use of AI tools such as ChatGPT. Our outcome variable was use of AI tools. Data were analyzed descriptively in Stata version 17.0. We conducted a modified Poisson regression to explore the association between use of AI tools and various exposures. Results A total of 564 students participated. Almost all (93%) had heard about AI tools and more than two-thirds (75.7%) had ever used AI tools. Regarding the AI tools used, majority (72.2%) had ever used ChatGPT, followed by SnapChat AI (14.9%), Bing AI (11.5%), and Bard AI (6.9%). Most students use AI tools to complete assignments (55.5%), preparing for tutorials (39.9%), preparing for exams (34.8%) and research writing (24.8%). Students also reported the use of AI tools for nonacademic purposes including emotional support, recreation, and spiritual growth. Older students were 31% less likely to use AI tools compared to younger ones (Adjusted Prevalence Ratio (aPR):0.69; 95% CI: [0.62, 0.76]). Students at Makerere University were 66% more likely to use AI tools compared to students in Gulu University (aPR:1.66; 95% CI:[1.64, 1.69]). Conclusion The use of ChatGPT and other AI tools was widespread among medical students in Uganda. AI tools were used for both academic and non-academic purposes. Younger students were more likely to use AI tools compared to older students. There is a need to promote AI literacy in institutions to empower older students with essential skills for the digital age. Further, educators should assume students are using AI and adjust their way of teaching and setting exams to suit this new reality. Our research adds further evidence to existing voices calling for regulatory frameworks for AI in medical education.