The principles of the tested mHealth system could be of interest during infectious disease outbreaks, such as Ebola or Lassa fever, when there might be a special need for disease-specific health information within populations.

Introduction. Tuberculosis poses a great threat to public health around the globe and affects persons mostly in their productive age, notwithstanding; everyone is susceptible to tuberculosis (TB) infection. To assess the effectiveness and performance of the tuberculosis control program activities, the percentage of cases with treatment success outcome is key. To control tuberculosis, interrupting transmission through effective treatment cannot be overemphasized. The study was conducted to determine factors associated with TB treatment outcome, in the Atwima Nwabiagya District from 2007–2017. Method. A Retrospective review of routine/standard TB registers was carried out in five directly observed therapy short-course (DOTS) centres at the Atwima Nwabiagya District from January 2007 to December 2017. Demographic characteristics, clinical characteristics, and treatment outcomes were assessed. Bivariate and multivariate logistic regression was conducted to determine the predictors of successful treatment outcome. Results. Of the 891 TB client’s data that was assessed in the district, the treatment success rate was 68.46%. Patients, aged ≤ 20 years (adjusted odds ratio aOR = 4.74 , 95 % CI = 1.75 − 12.83 ) and 51-60 years ( aOR = 1.94 , 95 % CI = 1.12 − 3.39 ), having a pretreatment weight of 35-45 kg ( aOR = 2.54 , 95 % CI = 1.32 − 4.87 ), 46-55 kg ( aOR = 2.75 , 95 % CI = 1.44 − 5.27 ) and 56-65 kg ( aOR = 3.04 , 95 % CI = 1.50 − 6.14 ) were associated with treatment success. However, retreatment patients ( aOR = 0.31 , 95 % CI = 0.11 − 0.84 ) resulted in unsuccessful treatment outcome. Conclusion. Successful treatment outcome among TB patients was about 20.00% and 30.00% lower compared to the national average treatment success rate and WHO target, respectively. Active monitoring, motivation, and counselling of retreatment patients and patients with advanced age are key to treatment success.

Background Prematurity (gestational age <37 completed weeks) accounts for the majority of neonatal deaths worldwide and most of these occur in the low-resource countries. Understanding factors that determine the best chances of preterm survival is imperative in order to enhance the care of neonates and reduce adverse outcomes in such complicated births. Aim This was to find out the proportions of preterm babies who survived at the Special Care Baby Unit (SCBU) in the Cape Coast Teaching Hospital (CCTH) and the factors which influenced their survival. Method This was a retrospective review of data on all the live preterm babies seen at the SCBU of CCTH from 2010 to 2019. Data on 2,254 babies that met the inclusion criteria were extracted. Descriptive statistics were generated and tests of association done with chi-square and multivariable logistic regression. Outcome The main outcome measure was the proportion of live preterm neonates who were discharged after SCBU admissions. Results The CCTH had a total of 27,320 deliveries from 2010 to 2019. Of these, 1,282 were live preterm births, giving a prevalence of live preterm babies over the ten-year period of 4.7% (1,282/27,320). An increasing trend in prevalence was observed with 2019 recording the highest at 9% (271/3027). Most (48.8%) of the deliveries were vaginal, 39.2% were by caesarean section (CS); the mode of birth for 12% of the women were not documented. The mean gestational age was 31.8 (±2.77) weeks. Of the birth weights documented, <1000g babies accounted for 11.9%, 1000–1499g babies made up 34.8%, while 1500g to 2499g babies accounted for 42.6%. The babies with weights >2500g made up only 3.7%. The average length of hospital stay was 8.3 (±9.88) days. Regarding the main outcome variable, 67.6% were discharged alive, 27.6% died and 4.9% were unaccounted for due to incomplete documentation. Factors which influenced survival were: birth weight (p <0.001); gestational age (p <0.001); mode and place of delivery (p <0.001 for both); APGAR scores at 1st and 5th minutes (p <0.001); and length of stay at the SCBU (p <0.001). No association was found for sex of the baby, maternal age and parity. Conclusion This study shows the possibility of achieving good preterm survival rates through the provision of specialised neonatal care, even in resource-constrained countries. This provides an updated benchmark for clinical decision-making and antenatal counselling. It also highlights the problem of inadequate data capture in our part of the world, which needs considerable improvement.

BackgroundThe aim of this study was the development and evaluation of an algorithm-based diagnosis-tool, applicable on mobile phones, to support guardians in providing appropriate care to sick children.MethodsThe algorithm was developed on the basis of the Integrated Management of Childhood Illness (IMCI) guidelines and evaluated at a hospital in Ghana. Two hundred and thirty-seven guardians applied the tool to assess their child’s symptoms. Data recorded by the tool and health records completed by a physician were compared in terms of symptom detection, disease assessment and treatment recommendation. To compare both assessments, Kappa statistics and predictive values were calculated.ResultsThe tool detected the symptoms of cough, fever, diarrhoea and vomiting with good agreement to the physicians’ findings (kappa = 0.64; 0.59; 0.57 and 0.42 respectively). The disease assessment barely coincided with the physicians’ findings. The tool’s treatment recommendation correlated with the physicians’ assessments in 93 out of 237 cases (39.2% agreement, kappa = 0.11), but underestimated a child’s condition in only seven cases (3.0%).ConclusionsThe algorithm-based tool achieved reliable symptom detection and treatment recommendations were administered conformably to the physicians’ assessment. Testing in domestic environment is envisaged.Electronic supplementary materialThe online version of this article (10.1186/s12911-018-0600-3) contains supplementary material, which is available to authorized users.

Background. Burnout among nursing professionals at the workplace and how it influences their decision to quit the profession is crucial to the delivery of quality health service. The shortage of nursing professionals has serious consequences on the healthcare system. Aim. To examine the effect of burnout on intention to quit the profession among nursing professionals. Methods. A cross-sectional study among 375 randomly selected nursing professionals in active service at a tertiary healthcare setting in Kumasi, Ghana. The Maslach Burnout Inventory was used to determine burnout, and their intention to quit the profession was assessed by asking participants whether they ever thought about quitting the profession in the past 12 months. The effect of burnout on intention to quit was analyzed using logistic regression analysis. Results. The overall prevalence of burnout among participants was 2.1% (8/375) with 10.1% (38/375), 24.0% (90/375), and 56.3% (211/375) experiencing high emotional exhaustion, depersonalisation, and low personal accomplishment, respectively. Nearly half (49.3%, 185/375) of the participants had intention to quit the profession. Emotional exhaustion (adjusted odds tatio, AOR = 5.46; 95% CI = 2.25–13.20), depersonalisation (AOR = 1.77 95% CI = 1.07–2.95), and personal accomplishment (AOR = 2.27; 95% CI = 1.30–3.96) were associated with intention to quit the profession. Conclusion. Burnout has a negative effect causing intention to quit nursing profession. It is imperative to identify strategies such as occupational health surveillance that will aim at reducing the incidence of burnout at the workplace due to its consequences, one of them being the intention to quit.