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.
Background Often, non-clinical risk factors could affect the predisposition of an individual to diseases. Understanding these factors and their impacts helps in disease prevention and control. This study identified risk factors for malaria, yellow fever, typhoid, chickenpox, measles, hepatitis B, and urinary tract infection in a population in an African country. Methods Our study was an observational, correlational, and quantitative one that explored relationships among risk variables and disease prevalence - without modifying or controlling the variables. Data for this study was obtained through random sampling of a population of patients and physicians in the eastern/southern, western, and northern parts of Nigeria in 2015–2016. A total of 2199 patient consultation forms were returned by 102 (out of 125) physicians, and considered useful for analysis. Demographic data of patients, physicians, and diagnosis outcomes were analysed descriptively through frequency distributions, aggregate analysis, and graphs. The influence of risk factors on the disease manifestations (diagnosis outcomes) was determined using regression analysis. Results Our results show that living in a tropical climate is by far a major risk factor associated with tropical diseases (malaria: t = 19.9, typhoid: t = − 3.2, chickenpox: t = − 6.5 and typhoid: t = 12.7). The risk for contracting infections is relative to specific diseases; for example, contact with chickenpox infected person poses a high risk of contracting the virus (t = 41.8), while poor personal hygiene predisposes people to high risk of urinary tract infection (t = 23.6). On the other hand, urbanization and homelessness pose very low risks of disposing the individual to the diseases under consideration, while low fluid intake, lack of voiding, and wearing non-cotton underwear predispose individuals to few diseases. Conclusion The risk factors identified in our study exert differential and discriminating influences in the causation, predisposition, and transmission of these disease studied. It is recommended that significant effort be devoted by governments in the tropics to the mitigation of these modifiable risk factors. The most important strategy to mitigate the occurrence of these risk factors will be improving the living conditions of people and the provision of social protection measures to reduce the occurrence and burden of these diseases.
Aim: The aim of this study was to examine the impacts of different (non-clinical) risk factors on the populations’ predisposition to tropical diseases specifically Malaria, yellow fever, typhoid fever, chicken pox, measles, hepatitis B and UTI.Subject and Methods: Data for this study was obtained through patient diagnosis forms, distributed to physicians in Nigeria. A total of 2199 patient consultation forms were returned by 102 (out of 125) physicians, and considered useful for analysis. Demographic data of patients, physicians, and diagnosis outcomes were analysed descriptively through frequency distributions, aggregate analysis, and graphs, while the influence of risk factors on the disease manifestations (diagnosis outcomes) were determined using regression analysis.Results: Findings from our study demonstrated that the difficulty in diagnosing tropical disease was associated with significant increase in morbidity and mortality especially in patients with malaria, UTI and typhoid fever. Factors such as contact with an infected person and poor personal hygiene posed significant risk, while urbanization and homelessness, posed very low risks across all the diseases. Conclusion: The risk factors identified in our study exert differential and discriminating influences in the causation, predisposition, and transmission of these conditions, understanding the individual risk factors for each condition have significant socio-economic implications for people living in tropical and endemic regions, especially with respect to management and prevention of these conditions.
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