Journal of Health Management and Informatics
Volume:9 Issue: 4, Dec 2022

This study aimed to identify the clinical features and predictors of mortality in patients hospitalized with Coronavirus disease 2019 (COVID-19) in southern Iran. This cross-sectional study was performed on patients with COVID-19 admitted to Ali Asghar Hospital in Shiraz, Iran, in 2021. All patients with a definitive diagnosis of COVID-19 were included in the study. The required information was extracted from the patient's medical records. In this study, 619 patients with COVID-19 were included. Sixty-four patients (10.3%) died due to COVID-19, and 555 (89.7%) patients recovered. The clinical signs of breath shortness, muscle pain, low Oxygen saturation, and intubation were statistically significant between the two groups (P<0.05). The results of the multivariate logistic model showed that age >52 years, diabetes, and SaO2 level less than 90% significantly increased the risk of death in COVID-19 hospitalized patients. The results of the study showed that patients with SaO2 levels less than 90% and over the age of 52 and those with diabetes had a higher risk of mortality from COVID-19. Therefore, identifying COVID-19 risk factors and deaths will have important implications for clinical management and disease reduction strategies.

Health information technology (HIT) can facilitate informed decisions regarding health conditions. This study aimed to examine the predisposing factors, enabling factors, and need factors associated with the use of HIT for personal health management. Individuals with chronic conditions might further need to use HIT tools to improve their health outcomes.
This study used secondary data with a sample size of 3,865 from the 4th cycle of 2020 Health Information National Trends Survey (HINTS) 5. Using multivariable logistic regression, we used four regression models to examine the association between the dependent and independent variables, such as multiple chronic conditions and sociodemographic characteristics. The dependent variables representing the use of HIT were “looked for health or medical information for yourself”, “used e-mail or the Internet to communicate with a doctor or doctor’s office”, “looked up medical test results”, and “made appointments with a healthcare provider.”
Adults with 3 or more chronic conditions had higher odds of looking for health or medical information for themselves (Adjusted Odds Ratio AOR= 1.9; Confidence Interval CI:1.09-3.32), using e-mail or the Internet to communicate with a doctor or doctor’s office (AOR= 1.84; CI, 1.20-2.81), and looking up medical test results (AOR= 2.04; CI, 1.19-3.50) when compared to those with no chronic conditions. Compared to individuals who had less than a high school degree, those with a college degree were more likely to look for health or medical information for themselves (Adjusted Odds Ratio AOR= 7.21; Confidence Interval CI, 2.34-22.23), use e-mail or the Internet to communicate with a doctor or doctor’s office (AOR=3.01; CI, 1.47-6.17), look up medical test results (AOR=4.34; CI, 2.46-7.65), and make appointments with a healthcare provider (AOR= 2.84; CI, 1.40-5.76). Enabling factors strongly associated with HIT use were having a regular provider and having access to the Internet.
This study provides evidence about the factors that influence the use of health information technology for personal health management.

The "family physician" program is one of the plans which aimed at expanding the coverage of insurance, overcoming the barriers to the health system of the country, and solving the public health problems in Iran. This study was conducted to identify the strengths and weaknesses of the urban family physician program from the viewpoint of policymakers, administrators, and recipients of services in the city of Shiraz during 2012-2016, using corrective strategies.

This is a qualitative study, and the data were collected through focus group discussions and semi-structured interviews. A total of six focus group discussion sessions and 40 interviews were conducted, and the target sampling was done.

A total of 9 basic concepts and 46 sub-concepts were identified to explain the strengths and weaknesses of the family physician program. The main concepts included: 1- Culture-making and community preparation, 2- Structure and deployment facilities of the program, 3- Manpower training, 4. Service coverage, concept 5. Resources (financial, human, and equipment), 6. Stewardship and monitoring of the program, 7. Insurance system, tariffs, and compensation of services, 8. Clarity of the guidelines and regulations, and 9. Satisfaction with the implementation of the plan.

According to the results of the study, educational planning for public culture-making through the media and newspapers, proportion of the number of people covered by each doctor, aggregation of insurance, and legal requirements for specialists to cooperate effectively are recommended to improve the program.

In this study, we analyze the optimal intervention strategies that lead to reducing the effects of the COVID-19 pandemic by artificial neural networks (ANNs). Our aim is to investigate the effects of optimal control strategies, such as the implementation of government intervention, testing, and vaccination policies during outbreaks. We utilized a controlled SIDAREV model to study the progression of the COVID-19 pandemic. Using Pontryagin's minimum principle (PMP) for the SIDAREV model, we defined an unconstrained minimization problem. Applying the Hamiltonian conditions, we approximated the obtained ordinary differential equations (ODE) using ANNs. We utilized the multilayer perceptron (MLP) to obtain the approximate solution of the states and co-states functions. We observed the effects of optimal control strategies, and to show the efficiency of the proposed method, we compared it with the Runge-Kutta method through some examples. Using a mathematical model that simulates the behavior of the Covid-19 disease, we can examine the effects of controllers such as government interventions, tests and vaccinations with the neural network method. The results show that this method is useful in solving the problem of optimal control of infectious diseases.

All managers should strive to make the most of the available facilities to avoid wasting resources. This study aimed to estimate the direct financial burden of unnecessary admissions and stay days in the Internal and Surgical Wards of Teaching Hospitals in Yazd City. A total of 272 cases were selected using the stratified sampling method in 2021, and each hospital was considered as a statistical classctedcity:2021. Protocol Evaluation Appropriateness was used to collect the data. Multiple logistic regression analysis was used to determine the impact of demographic variables on the type of admission and also on the type of stay day through SPSS22. The results showed that 5.5% of admissions and 19.4% of stay day were deemed unnecessary, and the chance of unnecessary admission in the surgical ward compared to the internal ward was about 75% (p = 0.037, OR 0.25) and in patients with basic insurance was about 74% lower than those without basic insurance. The cost of unnecessary admission and stay was estimated at 310.294.000 IR Rials. There is a need to establish interaction between the health insurance organization and other basic insurance organizations with managers and officials of hospitals and monitor the cases, so that admissions and inappropriate hospital days are reduced.

This study aimed to identify the essential information needs in the rapid response team (RRT) electronic records of hospitals.

 This cross-sectional study was conducted among 71 RRT members of Abu Ali Sina Organ Transplant Center in Shiraz, Iran. Data were collected using a researcher-made questionnaire by trained researchers. Descriptive (mean, frequency, and percentage) and analytic (Mann Whitney U and Kruskal Wallis) statistics were used to analyze the data.

  The three data elements with the highest mean scores were blood pressure (4.8), heart rate (4.7), and respiratory rate (4.6). Among the top ten data elements according to Nursing Supervisor “Investigations (Most recent chest x-Ray)”, “Investigations (EF)”, and “Investigations (pulmonary function test)”; according to Head nurse “Investigations (EF)”, “Laboratory (Arterial blood gas)” and “Laboratory (Hb)”; and according to RRT ICU Nurse “Laboratory (Hb)”, “Laboratory (O2 saturation)” and “Laboratory (K)” were the most important data elements. Also, by opening the RRT Registered anesthesia nurse, “Physiology (BP)”, “Physiology (RR)”, and “Physiology (body temperature)” were the most important data elements. There was a statistically significant difference between different clinical roles in the relationship between important data elements (P <0.05). Also, there was a statistically significant difference between the registered group of RRT anesthesia nurses and other clinical role groups (P <0.008).

The identified information needs in this study can be used to inform the development and design of user-centered EMRs for nurse-led RRTs.

Coronavirus has become a global pandemic since early 2019. More than180 countries around the world are involved with COVID-19. One of the effective methods to monitor, detect, warn early, prevent, and control is Information Technology. This study is a  scoping review. This study aimed to describe the novel information technologies used during the COVID-19 pandemic. The literature was searched for types of information technologies on COVID-19 with the help of libraries, electronic databases (Scopus, PubMed, and Web of sciences), and search engines available at Google. In this study, three groups of telemedicine technologies including telediagnosis, telemonitoring, and teleconsultation were selected. In addition, several unique technologies such as artificial intelligence, smart wearable devices, big data, neural networks, robots, chatbots, close contact detectors, Internet of Things (IoT), smart drones, Electronic Health Records, and thermal scanners were included. More than 150 resources were collected, 68 of whom were selected based on their relevancy during 2021. The results showed that the role of modern technologies in healthcare systems monitoring was crucial during the COVID-19 pandemic. Therefore, telemedicine is one of the solutions that has been equivalent to or even better than face-to-face medicine, and governments should better learn about the experiences of different countries in the use and their branches such as Telemonitoring, Teleconsultation, Telediagnosis along with enforcing laws to follow the protocols and vaccination of different groups of society to prevent the spread of the disease.

With the advancement of science, the role of employees and human relations (human capital) in the development of the organization and society has become more apparent, drawing more attention to the discussion of social capital and intellectual capital, as well as their constructive role in the development and top organizational performance. As a result, the current study was designed at Mashhad University of Medical Sciences to create a quantitative model of intellectual capital promotion using a social capital approach. This is a quantitative study in the form of a survey. The statistical population of the study included 15415 employees and faculty members of Mashhad University of Medical Sciences. The statistical sample was obtained from 416 subjects using a two-stage stratified sampling method (with proportional allocation). The study tool included a 91-item questionnaire made by the researcher. The data from this study were analyzed using SPSS software using Amos structural equations. The research findings in the quantitative model of intellectual capital promotion with social capital approach consisted of 7 dimensions and 17 components, of which 3 dimensions and 7 components related to social capital included structural, relational, and cognitive capital; also, 4 dimensions of intellectual capital included human capital, structural capital, client’s reverence, and innovative capital, which had 10 components. Given that the coefficients of all the dimensions and components of the model (t>1.96) were significant and because in the structural model, almost all the fit indices were within the desired range, the appropriateness of the model was confirmed. The analysis of the data revealed that the quantitative model of intellectual capital promotion at Mashhad University of Medical Sciences through using a social capital approach was designed successfully, and all the fit indices were within the desired range.