Effect of Electronic Health Records on Patient Satisfaction and Waiting Time at Selected Hospitals, in Addis Ababa

Background: Electronic health records provide a great potential for improving the delivery of health services and decision-making abilities for all hospital stakeholders and for prudent management of health care resources.The main objective was to assess the effect of EHR on patient satisfaction and waiting time at Selected Hospitals, Addis Ababa.Methods: An institutional-based comparative cross-sectional study was conducted. The sample size was calculated using a double population-proportion formula, which comprised 184. Statement to confirm that all methods were carried out in accordance with relevant guidelines and regulations. After receiving ethical clearance from the Institutional Ethics Review Board and the Addis Ababa Health Bureau IRB, formal letters were written to Yekatit12 Hospital and Menelik II Referral Hospital.Written consent was taken for participants. Epidata V3.1 and SPSS software V25 were used for data entry and analysis respectively. Both bivariate and multivariate logistic regression analyses were performed to assess the presence and degree of association between dependent and independent variables. Statistically significant variables were declared using an adjusted odds ratio with a 95% confidence interval.Result: The mean waiting time at Yekatit 12 HMC was 60.2 ± 48.2 minutes and 82 ± 56.8 minutes at Menelik. Similarly, 74 (83.1%) at Yekatit 12 HMC and 31.8% at Menelik II Referral Hospital were satisfied with the service. Eye contact, clear communication, accessibility of the service, explanations of the medical procedures, involving patients in clinical decisions regarding their health care, and active listening to their opinions and questions had statistical significance.Conclusion: Though patient satisfaction is not limited to those variables, overall client satisfaction and waiting time at Yekatit 12 Hospital Medical College were higher than those at Menelik II Referral Hospital, that could be attributable to the installation of EHR. As a result, the federal MOH and the respective RHBs should implement EHR in all health-care facilities.

Thermal performance of parabolic-trough solar collector using double-population LBM with single-node/curved scheme and experimental evaluation on properties of SiO2-TiO2/EG nanofluid

Purpose This paper aims to analyze the effect of absorber’s geometry and operating fluid on the thermal and hydrodynamic behaviors of a solar collector. Two different profiles are proposed for the absorber which is wavy and flat. Also, the inner tube of HTF (i.e. heat transfer fluid) is considered as single and double. The solar collector is filled with hybrid nanofluid of SiO2-TiO2/ ethylene glycol (EG) which its thermal conductivity and dynamic viscosity are measured using KD2 Pro and Brookfield LVDV III Ultra; respectively, in the temperature range of 30°C to 80°C and nanoparticle concentration in the range of 1.5% to 3.5%. Design/methodology/approach Among the solar collector, the parabolic-trough solar collector is one of the most efficient models for extracting solar thermal power. A parabolic trough solar collector with two different models of absorbers and included with two models of inner HTF tube is proposed. Findings The corresponding regression equations are derived versus temperature and volume fraction and used in the numerical process. For the numerical process, the thermal lattice Boltzmann method manipulated with a single-node curved scheme is used. Also, in the final step, the second law analysis is carried out in local and volumetric forms. The influential factors are Rayleigh number, the concentration of hybrid nano-powder and the structure of absorber profile. Originality/value The originality of the present work is combining a modern numerical method (i.e. double-population lattice Boltzmann method) with experimental observation on characteristics of SiO2-TiO2/EG nanofluid to analyze the thermal performance of parabolic trough solar collector.

Does Hypertensive Disorder and Obstetric Factors Associate with Still Birth Among Women Who Gave Birth in Selected Hospital of Southwestern, Ethiopia?

Background: The cause of stillbirth is often unknown, but can be attributable to various causes; hypertensive disorders and obstetric factors supposed to complicate pregnancy and may cost the life of the fetus. It is the series pregnancy problem not precisely known and only available few research findings are inconsistent & not well established.Objectives: The aim of this study is to assess the association between Stillbirth and hypertensive disorder and obstetric factors.Methods: Facility based unmatched case-control study design was employed from January2018 to June2019, (287 cases and 574 controls) was selected using systematic random sampling methods. Double population proportions formula with 1:2 case to control ratio was used to calculate sample size with 95% confidence interval and 80% power. The data was collected from clinical records of mother’s a using data collecting checklist. Epi data version 4.4.2.1 was used for data entry, and analysis was done by SPSS version 21 statistical software. Descriptive analysis such as frequency, percentage and chi-square test were done. For the inferential analysis, a multivariable analysis was done. Statically significant was used at a p-value <0.05 both for the univarible and multivariable analysis.Result: Women who had hypertensive disorder were 1.76 times at risk to have stillbirth than no hypertensive disorder (AOR: 1.76: 95%CI :( 1.06, 2.9). In addition, women who had first antenatal care at third trimester were 4 times at higher risk to have still birth than women, who had first antenatal care at first trimesters (AOR: 4, 95%CI: (1.54, 11). Women who had more than four children were 2.6 times at higher risk of having still birth compared with women one child (AOR: 2.6, 95%CI: (1.2, 5.7). Furthermore, the odds of having still birth was found to be higher in women, who had blood group O than blood group A (AOR: 1.7: 95%CI: (1.057, 2.8).Conclusion: According to the findings of this study, we conclude that a hypertensive disorders and obstetric factors were risk factors for stillbirth. Therefore, it is significant to give special attention to women with hypertensive disorder and multipara women.

Quasi-Affine Transformation Evolutionary with Double Excellent Guidance

The Quasi-Affine Transformation Evolutionary (QUATRE) algorithm is a swarm-based collaborative optimization algorithm, which has drawn attention from researchers due to its simple structure, easy implementation, and powerful performance. However, it needs to be improved regarding the exploration, especially in the late stage of evolution, and the problem of easy falling into a local optimal solution. This paper proposes an improved algorithm named Quasi-Affine Transformation Evolutionary with double excellent guidance (QUATRE-DEG). The algorithm uses not only the global optimal solution but also the global suboptimal solution to guide the individual evolution. We establish a model to determine the guiding force by the distance between the global optimal position and the suboptimal position and propose a new mutation strategy through the double population structure. The optimization of population structure and the improvement of operation mechanisms bring more exploration for the algorithm. To optimize the algorithm, the experiments on parameter settings were made to determine the size of the subpopulation and to achieve a balance between exploration and development. The performance of QUATRE-DEG algorithm is evaluated under CEC2013 and CEC2014 test suites. Through comparison and analysis with some ABC variants known for their strong exploration ability and advanced QUATRE variants, the competitiveness of the proposed QUATRE-DEG algorithm is validated.

Multilayered Porous Titanium-Based 3rd Generation Biomaterial Designed for Endosseous Implants

This work proposes a novel complex multi-layered material consisting of porous titanium as a substrate and a complex coating consisting of a chitosan film engulfing microsphere loaded with growth factors such as BMP2 (bone morphogenic protein 2) and IGF1 (insulin-like growth factor-1). The microspheres were obtained through deposition of dual layers of calcium cross linked pectin–chitosan/pectin polyelectrolyte onto a BSA (bovine serum albumin) gel core. The multilayer was conceived to behave like a 3rd generation biomaterial, by slow delivery of viable growth factors around implants, and to assist the healing of implantation wound and the development of new vital bone. The biologic effect of the delivery of growth factors was studied in vitro, on MSC-CD1 mesenchymal stem cells, and in vivo, on CD1 mice. Proliferation and differentiation of cells were accelerated by growth factors, especially IGF1 for proliferation and BMP2 for differentiation. In vivo tests analyzed histologically and by MicroCT show a more structured tissue around BMP2 samples. The present concept will give the best clinical results if both growth factors are delivered together by a coating film that contains a double population of microcarriers.

Member Selection for the Collaborative New Product Innovation Teams Integrating Individual and Collaborative Attributions

As the first stage of the formation of a collaborative new product innovation (CNPI) team, member selection is crucial for the effective operation of the CNPI team and the achievement of new product innovation goals. Considering comprehensively the individual and collaborative attributions, the individual knowledge competence, knowledge complementarity, and collaborative performance among candidates are chosen as the criteria to select CNPI team members in this paper. Moreover, using the fuzzy set and social network analysis method, the quantitative methods of the above criteria are proposed correspondingly. Then, by integrating the above criteria, a novel multiobjective decision model for member selection of the CNPI team is built from the view of individual and collaborative attributions. Since the proposed model is NP-hard, a double-population adaptive genetic algorithm is further developed to solve it. Finally, a real case is provided to illustrate the application and effectiveness of the proposed model and method in this paper.

Upper Openings Ventilation System Study of the Building by the Lattice Boltzmann Model

We present in this work a numerical study of a ventilation system in a room with two openings in the ceiling and a floor heating indicated by constant heat temperature. The double population thermal lattice Boltzmann method is used, with nine velocities model D2Q9 for the dynamic field and a five velocities model D2Q5 for the temperature field. The results are presented in the form of streamlines, temperature contour and velocity profile, and analysed as a function of the Richardson number.