Multi-criteria decision analysis method for differential diagnosis of tropical febrile diseases.

This paper employs the Analytical Hierarchy Process (AHP) to enhance the accuracy of differential diagnosis for febrile diseases, particularly prevalent in tropical regions where misdiagnosis may have severe consequences. The migration of health workers from developing countries has resulted in frontline health workers (FHWs) using inadequate protocols for the diagnosis of complex health conditions. The study introduces an innovative AHP-based Medical Decision Support System (MDSS) incorporating disease risk factors derived from physicians' experiential knowledge to address this challenge. The system's aggregate diagnostic factor index determines the likelihood of febrile illnesses. Compared to existing literature, AHP models with risk factors demonstrate superior prediction accuracy, closely aligning with physicians' suspected diagnoses. The model's accuracy ranges from 85.4% to 96.9% for various diseases, surpassing physicians' predictions for Lassa, Dengue, and Yellow Fevers. The MDSS is recommended for use by FHWs in communities lacking medical experts, facilitating timely and precise diagnoses, efficient application of diagnostic test kits, and reducing overhead expenses for administrators.

Lessons learned on data collection for a digital health intervention-insights and challenges from Nigeria.

Objectives: This article delves into the challenges of medical data collection during the COVID-19 pandemic in developing countries, using Nigeria as a case study. It emphasizes how data collection impacts research quality, reliability, and validity. Methods: Qualitative research utilizing purposive sampling was employed to explore experiences in designing a diagnostic tool for febrile diseases in Nigeria. A questionnaire with selectable and open-ended questions was utilized for data collection, and 23 respondents participated. Results: Among 74 potential participants, 23 valid responses were gathered, revealing significant themes related to experiences and challenges in medical data collection. A multidisciplinary team approach proved beneficial, fostering collaboration, enhancing knowledge, and promoting positive experiences. Despite challenges with paper questionnaires, most participants preferred them for ease of use. Connectivity issues hindered timely data uploading and disrupted virtual meetings. Conclusion: Innovative and flexible strategies, such as a blended data collection approach and well-coordinated teams, were vital in overcoming challenges. Electronic data collection tools, reminders, and effective communication played key roles, leading to positive outcomes. This study provides valuable insights for researchers and practitioners involved in data collection, particularly in developing countries like Nigeria.

Modelling Differential Diagnosis of Febrile Diseases with Fuzzy Cognitive Map.

The report of the World Health Organization (WHO) about the poor accessibility of people living in low-to-middle-income countries to medical facilities and personnel has been a concern to both professionals and nonprofessionals in healthcare. This poor accessibility has led to high morbidity and mortality rates in tropical regions, especially when such a disease presents itself with confusable symptoms that are not easily differentiable by inexperienced doctors, such as those found in febrile diseases. This prompted the development of the fuzzy cognitive map (FCM) model to serve as a decision-support tool for medical health workers in the diagnosis of febrile diseases. With 2465 datasets gathered from four states in the febrile diseases-prone regions in Nigeria with the aid of 60 medical doctors, 10 of those doctors helped in weighting and fuzzifying the symptoms, which were used to generate the FCM model. Results obtained from computations to predict diagnosis results for the 2465 patients, and those diagnosed by the physicians on the field, showed an average of 87% accuracy for the 11 febrile diseases used in the study. The number of comorbidities of diseases with varying degrees of severity for most patients in the study also covary strongly with those found by the physicians in the field.

Adoption of electronic medical records in developing countries-A multi-state study of the Nigerian healthcare system.

Electronic medical records (EMR) are extensively used in developed countries to manage patient records and facilitate consultations and follow-up of treatment. This has resulted in centralised databases where different services and clinicians can quickly access patient data to support healthcare delivery. However, adoption and usage of EMR in developing countries is not common and, in most cases, non-existent. Clinicians are dependent on patients keeping their own records manually with no centralised database to manage and control the patient medical history. The key objective of this study was to investigate the propensity of clinicians and senior management personnel in healthcare facilities to adopt EMR and evaluate the contextual factors that impact or impede adoption. Using Davis's technology adoption model extended with other factors, this study determined if contextual or situational factors are associated with barriers that impede adoption of EMRs in developing countries. Using a cross-sectional quantitative research approach, a questionnaire was designed to collect data across four states in the Niger Delta region of Nigeria. Stratified random sampling was used to select healthcare facilities that participated in the survey and selection of respondents from each healthcare facility. Data was collected by trained research assistants and a total of 1,177 valid responses were received and analysed using factor analysis and multiple regression analysis. The results from the analysis show that usefulness, critical success factors, awareness and relative advantage significantly influence clinicians' intention to adopt EMRs. Surprisingly, infrastructure availability was not statistically significant. Meanwhile, risk and data security both negatively influence adoption, indicating that user perception of risk and safety of their data decreases their propensity to adopt EMRs. The results from this study suggests that usefulness and anticipated success factors in facilitating operations within healthcare facilities have a great influence on user adoption of EMRs. Awareness, training and education of users on the effectiveness of EMRs and their usefulness will increase adoption. The results will be beneficial in helping government and healthcare leaders formulate policies that will guide and support adoption of EMR. Other policy recommendations and suggestions for future research were also proffered.

An Assessment of Antihypertensive Medication Adherence among Hypertensive Patients Attending the Outpatient Clinics in the University of Uyo Teaching Hospital, Uyo.

CONTEXT: Hypertension is a global cause of significant morbidity, ranking top as a cause of increased disability-adjusted life years. Patients who do not take their prescribed medication show almost a fourfold increase in the risk of dying from stroke by the second year after being prescribed treatment and a nearly threefold increased risk in the 10th year when compared to patients who take their prescribed medication. Medication adherence is a key factor in the control of high blood pressure. OBJECTIVE: The objective of the study was to assess the antihypertensive medication adherence rate of patients attending the outpatient clinics at the University of Uyo Teaching Hospital (UUTH) and to explore factors that affect their adherence to the medications. MATERIALS AND METHODS: This was a descriptive cross-sectional study of adult hypertensive patients attending the outpatient clinics at UUTH, from May to July 2018, who had been placed on antihypertensive medication(s) for at least 6 months. A standardized Morisky Medication Adherence 8 Questionnaire for assessing medication adherence was modified and used for the data collection. The questionnaires were administered by trained interviewers. Data were analyzed using SPSS 20.0. RESULTS: A total of 379 hypertensive patients took part in the study; 85.2% were adherent to antihypertensive medication(s), but only 14.2% showed good adherence. Four of the five dimensions considered in the Morisky Assessment greatly affected antihypertensive medication adherence. The mean age of the study participants was 60.8 ± 1.8 years, and 75% were male. CONCLUSION: Good adherence to antihypertensive medication was quite low in this study population, and it was affected by all dimensions of the Morisky Assessment; health-care providers should pay more attention to their patient's drug adherence, educate them on medication adherence, and get them involved in their care.