Comparison of the Clinical Effectiveness of Telerehabilitation with Traditional Rehabilitation Methods in Multiple Sclerosis Patients: A Systematic Review.

Background: The rehabilitation process for multiple sclerosis (MS) patients is long and complex, which can lead to reduced rehabilitation outcomes and reduced quality improvement. Thus, there is a need to use new methods to boost traditional rehabilitation. Innovations such as telerehabilitation can be helpful to remove the obstacles to treatment, but evidence for their effectiveness is limited. The objective of this work was to compare the clinical effectiveness of telerehabilitation with traditional interventions in MS patients. Methods: Seven bibliographic databases (PubMed, Cochran Library, Scopus, Science Direct, Web of Science, Embase, and ProQuest) were used in this research. The initial search resulted in the extraction of 8,239 articles; after the review of the title, abstract, and full text, 11 articles were selected. In addition, backward reference list checking of the selected studies was conducted. Studies that were related to our objectives were included. Quality assessment was performed using the CONSORT checklist. Then, data extraction was done using the form set by the researcher in Word 2016 software. Results: Overall, telerehabilitation achieved more positive effects compared to traditional rehabilitation on physical (n = 6), cognitive (n = 3), cognitive, and physical outcomes (n = 2), respectively. Synchronous telerehabilitation was more effective than other modalities (n = 8). In four studies, virtual reality-based telerehabilitation was used. Also, telerehabilitation in home offered better clinical outcomes compared to rehabilitation center (n = 9). Conclusions: This review provides evidence for the potential effectiveness of telerehabilitation for the improvement of clinical outcomes in MS patients. However, more robust randomized controlled trials are needed to confirm the observed positive effects.

Patients' perceptions, experiences, and satisfaction with e-prescribing system: A cross-sectional study.

INTRODUCTION: Electronic prescribing (e-prescribing) systems have the potential to increase the quality of care and reduce costs. Officially, since 22 December 2021, e-prescribing has been mandated in Iran. This study aimed to investigate the patients' perceptions about the e-prescribing system. METHODS: A descriptive-analytic cross-sectional study was conducted in 2023. The study sample comprised 394 patients who were referred to the pharmacies of five teaching hospitals. The sample size was estimated using Cochran's formula. Data collection was performed using a researcher-made questionnaire. The data were analyzed using descriptive (mean, standard deviation, frequency, and percentage) and analytic (Pearson and Spearman correlation, One-way ANOVA, and two-sample t-test) statistics. RESULTS: About 85 % of the patients were aware of the e-prescribing system, and 70 % of them preferred the e-prescribing. Almost 57 % of the patients believed that e-prescribing did not impact their medication adherence. The mean score of patients' satisfaction with e-prescribing, patients' attitude toward e-prescribing, and the impact of e-prescribing on patient care was 3.91 ± 0.046, 3.45 ± 0.028, and 3.10 ± 0.050 out of 5, respectively. There was a significant fair correlation between the impact of e-prescribing on patient care and patients' attitude towards e-prescribing. Additionally, there was a significant but poor correlation between patient satisfaction with the impact of e-prescribing on patient care and patients' attitude toward e-prescribing (P < 0.05). CONCLUSION: The majority of the patients demonstrated awareness of the e-prescribing system and expressed a preference for electronic prescribing. Patients reported overall positive satisfaction, as well as relatively positive perceptions and experiences with the evaluated e-prescribing system. From the patients' perspective, receiving the e-prescribing tracking code through SMS was the most popular method for tracking their prescriptions. A greater focus on patient engagement and considering their requirements and needs in the system are crucial to improve the delivery of patient-centered care.

Design, development, implementation, and evaluation of a severe drug-drug interaction alert system in the ICU: An analysis of acceptance and override rates.

BACKGROUND AND OBJECTIVE: The override rate of Drug-Drug Interaction Alerts (DDIA) in Intensive Care Units (ICUs) is very high. Therefore, this study aimed to design, develop, implement, and evaluate a severe Drug-Drug Alert System (DDIAS) in a system of ICUs and measure the override rate of this system. METHODS: This is a cross-sectional study that details the design, development, implementation, and evaluation of a DDIAS for severe interactions into a Computerized Provider Order Entry (CPOE) system in the ICUs of Nemazee general teaching hospitals in 2021. The patients exposed to the volume of DDIAS, acceptance and overridden of DDIAS, and usability of DDIAS have been collected. The study was approved by the local Institutional Review Board (IRB) and; the ethics committee of Shiraz University of Medical Science on date: 2019-11-23 (Approval ID: IR.SUMS.REC.1398.1046). RESULTS: The knowledge base of the DDIAS contains 9,809 severe potential drug-drug interactions (pDDIs). A total of 2672 medications were prescribed in the population study. The volume and acceptance rate for the DDIAS were 81 % and 97.5 %, respectively. The override rate was 2.5 %. The mean System Usability Scale (SUS) score of the DDIAS was 75. CONCLUSION: This study demonstrates that implementing high-risk DDIAS at the point of prescribing in ICUs improves adherence to alerts. In addition, the usability of the DDIAS was reasonable. Further studies are needed to investigate the establishment of severe DDIAS and measure the prescribers' response to DDIAS on a larger scale.

Tele-dentistry, its trends, scope, and future framework in oral medicine; a scoping review during January 1999 to December 2021.

BACKGROUND: Tele-dentistry has been increasingly used for different purposes of visit, consultation, triage, screening, and training in oral medicine. This study aims to determine the main facilitators, barriers, and participants` viewpoints of applying tele-dentistry in oral medicine and develop a framework indicating the input, process, output, and feedback. METHOD: This was a scoping review conducted in 2022 applying Arksey and O'Malley (2005) approach. Four databases including ISI web of science, PubMed, Scopus, and ProQuest were searched from January 1999 to December 2021. Inclusion criteria consisted of all original and non-original articles (reviews, editorials, letters, comments, and book chapters), and dissertations in English with a full text electronic file. Excel2016 was used for descriptive quantitative analysis and MAXQDA version 10 was applied for qualitative thematic analysis. A thematic framework was developed customizing the results of the review in a virtual mini expert panel. RESULTS: Descriptive results show that among 59 included articles, 27 (46%) have addressed the various applications of tele-dentistry during COVID-19 pandemic in the field of oral medicine. From geographical distribution perspective, most of the papers were published in Brazil (n = 13)/ 22.03%, India (n = 7)/11.86% and USA (n = 6)/10.17%. Thematic analysis shows that seven main themes of "information", "skill", "human resource", 'technical", "administrative', 'financial', and 'training and education' are explored as facilitators. 'Individual', 'environmental', 'organizational', 'regulation', 'clinical', and 'technical barriers' are also identified as main barriers of tele-dentistry in oral medicine. CONCLUSION: According to the results for using tele-dentistry services in oral medicine, a diverse category of facilitators should be considered and at the same time, different barriers should be managed. Users` satisfaction and perceived usefulness of tele-dentistry as final outcomes can be increased considering the system`s feedback and applying facilitator incentives as well as decreasing the barriers.

Usability Assessment of an Electronic Medical Record-Embedded Clinical Decision Support System for Arterial Blood Gas Interpretation.

Since usability is considered a significant success factor for Clinical decision support systems (CDSSs), this study seeks to assess the usability of an electronic medical records-embedded CDSS for arterial blood gas (ABG) interpretation and ordering. The current study was conducted in the general ICU of a teaching hospital, using the System Usability Scale (SUS) and interviews with all anesthesiology residents and intensive care fellows in two rounds of CDSS usability testing. The feedback from the participants was discussed with the research team across a series of meetings, and the second version of CDSS was designed and tailored to participants' feedbacks. Subsequently, the CDSS usability score increased from 67.22±4.58 to 80.00±4.84 (P-value<0.001) through participatory, iterative design and the users' usability testing feedbacks.

An evaluation of the risk factors associated with implementing projects of health information technology by fuzzy combined ANP-DEMATEL.

BACKGROUND: Application of a Clinical Information System (CIS) like Electronic Patient Record (EPR), PACS system and CPOE has turned into one of the most important criteria of priorities of health care systems. The aims of the clinical information system include improving the physicians' efficiency level, integrating the caring process, and expanding the fuzzy quality of the services offered to patients. Achievement of these benefits in reality is not an easy task, and there are lots of plans in this field which are doomed to failure. About 50% of the implementation plans of clinical information systems in health care organizations have failed, and this trend is significantly affecting industrial countries. Proper implementation of hospital information systems lies in identifying and assessing the relationships among the most important risk factors of fuzzy. The present study aimed to provide an applicable model for identifying, ranking and evaluating the risk factors associated with projects of clinical information technology in hospitals of Shiraz University of Medical Sciences. METHOD: This is an applied study which evaluates the risk factors associated with implementation of clinical information technology projects in hospitals of Shiraz Medical Sciences University. The participants consisted of professionals and senior experts of clinical information technology. Fuzzy logic was used in this study. We also applied ANP-DEMATEL combined model with fuzzy procedure to provide the analytic model of the study. RESULTS: According to the study findings, lack of top-executive supports, and unstable organizational environment were the two most important risk factors, while the main organizational factors and technology were also highly important. In addition, the factors associated with technology had the highest influence on the other studied risk factors. CONCLUSION: Hospital authorities can benefit from this proposed model to reduce the risk of implementing the projects of clinical information technology and improve the success coefficient of the risk of such projects.

Psychometric Evaluation of Self-assessment Persian Version of the Alzheimer Questionnaire (AQ).

Introduction: Mild cognitive impairment (MCI) is a primary disorder intensified by aging. Rapid diagnosis of MCI can prevent its progression towards the development of dementia. Thus, the present study was conducted to evaluate the psychometric features of the self-assessment Persian version of the Alzheimer questionnaire (AQ) in the elderly to detect MCI. Methods: First, the AQ was translated into the Persian language; then, its content validity was evaluated by the content validity index (CVI) and content validity ratio (CVR) method, and face validity was determined by two checklists for expert panel and the elderly. The convergent validity of the self-assessment AQ with the Montreal cognitive assessment (MoCA) was assessed using the Pearson correlation. The test-retest and internal consistency reliability were evaluated using intra-class correlation (ICC) and Kuder-Richardson coefficients, respectively. Moreover, the receiver operating characteristic curve was used to determine the optimal cut-off point of self-assessment AQ. Among 148 older people who took part in this study, 93 met our inclusion criteria (aged 60 years old or older, had reading and writing skills, and were able to speak and communicate). Results: A translated version of the questionnaire was named "M-check." The developed test showed good content and face validity. Statistically significant correlations were found between M-check and MoCA (r=-0.83, P<0.05). The Kuder-Richardson and ICC coefficients were obtained as 0.84 and 0.92, respectively. Area under the curve presented satisfactory values (Area under curve [AUC]=0.852, sensitivity=0.62, specificity=0.94). Conclusion: The M-check can be used as a valid and reliable instrument for assessing cognitive state and screening MCI in older adults. Highlights: All questions achieved desired face validity.The convergent validity of Alzheimer Questioner (AQ) was confirmed with high correlation.The AQ is statistically significant with Montreal Cognitive Assessment (MoCA).The AQ had acceptable stability, repeatability, and reliability.All findings demonstrated that the M-Check had high values in predicting MCI in the early stages. Plain Language Summary: Mild cognitive impairment (MCI) is a subset of mental disorders that is an early condition that may lead to dementia. People with MCI are usually prone to forgetfulness in a short time. If MCI is not detected in the early stages, it can progress to dementia or Alzheimer's to higher degrees. On the other hand, cognitive decline and MCI can cause major problems for patients and their families. So it is essential to act out as soon as possible. It is considered that a tool for the early identification of MCI that is self-assessed by individuals, without the presence of an expert and trained person to interpret the results, was not observed in Iran. Thus, the present study was conducted to evaluate the psychometric features of the self-assessment Persian version of the Alzheimer questionnaire (AQ) in the elderly. The results showed that the AQ is a simple one that can be quickly completed by any person at home or by family members of the elderly so that people can refer to the relevant specialist more soon if needed.

Effect of a Developed Nursing Stretch Break Application on Work-Related Musculoskeletal Complications and Fatigue among Nurses: An Interventional Study.

Objective: The present study aimed to develop Nursing Stretch Break (NSB) application to relieve work-related musculoskeletal complications and fatigue among hospital nurses. Methods: This interventional study was conducted among 71 nurses (15 men and 56 women with a mean age of 33.32 ± 6.42) employed in Shiraz governmental hospitals, Southwest Iran, for four months. In this study, NSB was developed; it includes eight main menus for the user, including (1) Registration, (2) Stretches, (3) User panel, (4) Questions from the researcher, (5) About us, (6) Contact us, (7) Reports, and (8) Answers to questions. Data were collected pre and post-intervention via the Persian version of the Nordic Musculoskeletal Questionnaire (P-NMQ), the Persian version of the Multidimensional Assessment of Fatigue (P-MAF) Scale, the Persian version of the Numeric Rating Scale (P-NRS), and the Persian version of the Usefulness, Satisfaction, and Ease of use (P-USE) questionnaire. Results: NSB application usability testing showed that the mean scores of P-USE subscales were high. The prevalence of work-related musculoskeletal symptoms (WMSs) in the last 7 days in nurses' body parts, except the elbows and knees, was significantly lower after the intervention than before. In addition, the intensity of work-related musculoskeletal pain/discomfort in all body parts, except the knees, was significant relief after the intervention compared to before. The results demonstrated that the difference in the mean score of the total fatigue and its subscales, except "degree of interference with activities of daily living," was significant after the intervention compared to before. Conclusions: NSB could be a low-cost and feasible ergonomic solution to improve the nurses' musculoskeletal health.

Supervised Machine Learning Approach to COVID-19 Detection Based on Clinical Data.

Background: The new coronavirus has been spreading since the beginning of 2020, and many efforts have been made to develop vaccines to help patients recover. It is now clear that the world needs a rapid solution to curb the spread of COVID-19 worldwide with non-clinical approaches such as artificial intelligence techniques. These approaches can be effective in reducing the burden on the health care system to provide the best possible way to diagnose the COVID-19 epidemic. This study was conducted to use Machine Learning (ML) algorithms for the early detection of COVID-19 in patients. Methods: This retrospective study used data from hospitals affiliated with Shiraz University of Medical Sciences in Iran. This dataset was collected in the period March to October 2020 andcontained 10055 cases with 63 features. We selected and compared six algorithms: C4.5, support vector machine (SVM), Naive Bayes, logistic Regression (LR), Random Forest, and K-Nearest Neighbor algorithm using Rapid Miner software. The performance of algorithms was measured using evaluation metrics, such as precision, recall, accuracy, and f-measure. Results: The results of the study show that among the various used classification methods in the diagnosis of coronavirus, SVM (93.41% accuracy) and C4.5 (91.87% accuracy) achieved the highest performance. According to the C4.5 decision tree, "contact with a person who has COVID-19" was considered the most important diagnostic criterion based on the Gini index. Conclusion: We found that ML approaches enable a reasonable level of accuracy in the diagnosis of COVID-19.

Usability of Iranian Primary Vitiligo Patient Registry (IPVPR): A Pilot Study.

BACKGROUND: Usability is essential for the acceptance and success of vitiligo patient registry system. Poor usability could decrease system efficiency and effectiveness, and have a negative impact on using the system and providing services. This study aims to evaluate the usability of vitiligo patient registry system. METHODS: This pilot study was conducted in 2021. In total, 17 users who were working in the vitiligo ward participated in the study. System usability scale (SUS) was used to evaluate the usability of vitiligo patient registry system. RESULTS: In the usability evaluation stage, the mean score of the system usability scale was obtained as 77.79. CONCLUSION: Developing vitiligo patient registry system with high usability and making decisions based on the registered data could provide better understanding of this disease and facilitate research in this field. Application of this system and its acceptance by users could decrease costs and increase effectiveness and quality of services.

Virtual reality applications for rehabilitation of COVID-19 patients: A systematic review.

Background and Aims: The COVID-19 pandemic has changed people's lifestyles as well as the way healthcare services are delivered. Undoubtedly, the difficulties associated with COVID-19 infection and rehabilitation and those associated with quarantine and viral preventive efforts may exacerbate the need for virtual reality to be used as a part of a complete rehabilitation strategy for these individuals. Thus, the present research aimed to evaluate the potential uses of virtual reality for the rehabilitation of individuals suffering from COVID-19. Methods: From 2019 to March 1, 2022, a systematic search was conducted in PubMed, Cochran Library, Scopus, Science Direct, ProQuest, and Web of Science databases. The papers were selected based on search terms and those that discussed the use of virtual reality in the rehabilitation of COVID-19 patients were reviewed. Each step of the study was reviewed by two authors. Results: A total of 699 papers were found during the first search. Three papers were chosen for further investigation after a thorough evaluation of the publications' titles, abstracts, and full texts. Cross-sectional studies, randomized controlled clinical trials, and case reports comprised 33%, 33%, and 33% of the publications, respectively. Based on the results, people suffering from COVID-19 were the focus of two papers (66%) that employed immersion virtual reality for cognitive rehabilitation, whereas one study (33%) used non-immersive virtual reality for physical rehabilitation. In two papers (66%), virtual reality was also offered to patients in the form of a game. Conclusion: According to the results of the present research, virtual reality games may enhance functional and cognitive consequences, contentment levels among patients, and their ability to take charge of their own health care. In light of the obstacles faced by COVID-19 patients, alterations in the delivery of healthcare, and the significance of rehabilitation in this group during quarantine, new techniques have been considered for these patients to maintain treatment, return to regular life, and enhance their standard of life.

Quality of death certificates completion for COVID-19 cases in the southeast of Iran: A cross-sectional study.

Background and Aim: Death certificate (DC) data provides a basis for public health policies and statistics and contributes to the evaluation of a pandemic's evolution. This study aimed to evaluate the quality of the COVID-19-related DC completion. Methods: A descriptive-analytical study was conducted to review a total of 339 medical records and DCs issued for COVID-19 cases from February 20 to September 21, 2020. A univariate analysis (χ 2 as an unadjusted analysis) was performed, and multiple logistic regression models (odd ratio [OR] and 95% confidence interval [CI] as adjusted analyses) were used to evaluate the associations between variables. Results: Errors in DCs were classified as major and minor. All of the 339 examined DCs were erroneous; more than half of DCs (57.8%) had at least one major error; all of them had at least one minor error. Improper sequencing (49.3%), unacceptable underlying causes of death (UCOD) (33.3%), recording more than one cause per line (20.1%), listing general conditions instead of specific terms (11.2%), illegible handwriting (8.3%), competing causes (6.2%), and mechanisms (3.8%) were most common major errors, respectively. Absence of time interval (100%), listing mechanism allying with UCOD (51.6%), using abbreviations (45.4%), missing major comorbidities (16.5%), and listing major comorbidities in part I (16.5%) were most common minor errors, respectively. Conclusion: The rate of both major and minor errors was high. Using automated tools for recording and selecting death cause(s), promoting certifiers' skills on DC completion, and applying quality control mechanisms in DC documentation can improve death data and statistics.

The effect of information technology intervention on using appropriate VTE prophylaxis in non-surgical patients: A systematic review and meta-analysis.

Introduction: Clinical decision support systems (CDSSs) play an important role in summarizing the best clinical practices, thereby promoting high standards of care in specific medical fields. These systems can serve as tools for gaining knowledge and mediating between clinical guidelines and physicians thereby providing the right information to the right person at the right time. Objective: This review aims to evaluate the effect of CDSSs on adherence to guidelines for venous thromboembolism (VTE) prophylaxis and VTE events compared to routine care without CDSSs in non-surgical patients. Methods: In order to conduct a systematic literature review, the published studies were identified through screening EMBASE, the international clinical trials registry, OVID, Cochrane database, PubMed, ISI Web of Science, and Scopus databases, from 1982 to March 2021. The included studies were reviewed by two independent reviewers; the proportion of patients that correctly received VTE prophylaxis has been next extracted for further analysis. Additionally, patients were divided into two groups: CDSS-recommended VTE prophylaxis and routine care without using a CDSS. Results: Twelve articles (three randomized controlled trials, seven prospective cohort trials, and two retrospective cohort trials) were in fine analyzed. The use of CDSSs is found to be associated with a significant increase in the rate of using the appropriate prophylaxis for VTE (p < 0.05) and a significant decrease in the incidence of VTE (p < 0.05). Conclusion: Implementation of CDSSs can help improving the appropriate use of VTE prophylaxis in non-surgical patients. Further, evidence-based and interventional studies on the development of CDSSs can provide more in-depth knowledge on both this tool design and efficiency.

Identification of data elements for blood gas analysis dataset: a base for developing registries and artificial intelligence-based systems.

BACKGROUND: One of the challenging decision-making tasks in healthcare centers is the interpretation of blood gas tests. One of the most effective assisting approaches for the interpretation of blood gas analysis (BGA) can be artificial intelligence (AI)-based decision support systems. A primary step to develop intelligent systems is to determine information requirements and automated data input for the secondary analyses. Datasets can help the automated data input from dispersed information systems. Therefore, the current study aimed to identify the data elements required for supporting BGA as a dataset. MATERIALS AND METHODS: This cross-sectional descriptive study was conducted in Nemazee Hospital, Shiraz, Iran. A combination of literature review, experts' consensus, and the Delphi technique was used to develop the dataset. A review of the literature was performed on electronic databases to find the dataset for BGA. An expert panel was formed to discuss on, add, or remove the data elements extracted through searching the literature. Delphi technique was used to reach consensus and validate the draft dataset. RESULTS: The data elements of the BGA dataset were categorized into ten categories, namely personal information, admission details, present illnesses, past medical history, social status, physical examination, paraclinical investigation, blood gas parameter, sequential organ failure assessment (SOFA) score, and sampling technique errors. Overall, 313 data elements, including 172 mandatory and 141 optional data elements were confirmed by the experts for being included in the dataset. CONCLUSIONS: We proposed a dataset as a base for registries and AI-based systems to assist BGA. It helps the storage of accurate and comprehensive data, as well as integrating them with other information systems. As a result, high-quality care is provided and clinical decision-making is improved.

Students' Satisfaction and e-Learning Courses in Covid-19 Pandemic Era: A Case Study.

The present study is conducted to determine the status of e-learning, student satisfaction and the relationship between these two variables in Zahedan University of Medical Sciences (ZAUMS). According to a descriptive study, there was just a significant difference between the mean score of e-Learning experience and student satisfaction, and a positive correlation between the education level and student satisfaction. Also, there was a positive correlation between all variables of e-learning and student satisfaction The findings showed that the more capable learners were outcome of better educational content, stronger e-learning infrastructure, better support and assessment of e-learning quality, which, in turn, resulted in the greater the students' satisfaction. As a result, the experiences from the evaluation of e-learning in the Covid-19 pandemic period may be regarded a good guide in improving the course during the Covid-19 pandemic, and also it can be considered a key factor in providing educations in the post-Covid-19 period.

Usability of Venous Thromboembolism Prophylaxis Recommender System: A Pilot Study.

Poor usability of clinical decision support system impact negative on healthcare professionals, decrease usage and quality of clinical decision support system and result in a negative effect on patient outcome. Therefore, the objective of this study was the usability evaluation of the venous thromboembolism prophylaxis recommendation system. This study design is a pilot study. Totally seven individuals participate in the study that 4 out of 7 were ICU attending and 3 out of 7 were Residents in ICUs setting. System Usability Scale (SUS) was used to assess the usability of the clinical decision support system (venous thromboembolism prophylaxis recommendation system) integrated into the medication order entry system in the ICU setting. This study has shown that the mean System Usability Scale (SUS) score was 74.64. Summing up the results, it can be concluded that the usability quality of the venous thromboembolism prophylaxis recommendations system is good. Further research requires to evaluate the usability of the venous thromboembolism prophylaxis recommendation system by quantitative and qualitative methods in large scale.

Myocardial Infarction Prediction and Estimating the Importance of its Risk Factors Using Prediction Models.

Background: According to World Health Organization (WHO), cardiovascular diseases (CVDs) are the leading cause of death globally. Although significant progress has been made in the diagnosis of CVDs, more investigation can be helpful. Therefore, this study aimed to predict the risk of myocardial infarction (MI) using data mining algorithms. Methods: The applied data were related to the admitted patients in Rajaei specialized cardiovascular hospital located in Tehran. At first, a literature review and interview with a cardiologist were conducted to understand MI. Then, data preparation (cleaning and normalizing the data) was performed. After all, different classification algorithms were applied in IBM SPSS Modeler (14.2) software on the prepared data; and, power of the applied algorithms and the importance of the risk factors in predicting the probability of getting involved with MI was calculated in the mentioned software. Results: This study was able to predict MI % 75.28 and 77.77% in terms of accuracy and sensitivity, respectively. The results also revealed that cigarette consumption, addiction, blood pressure, and cholesterol were the most important risk factors in predicting the probability of getting involved with MI, respectively. Conclusions: Predicting studies aim to support rather than replace clinical judgment. Our prediction models are not sufficiently accurate to supplant decision-making by physicians but have considerable tips about MI risk factors.

Developing a minimum data set required to create a registry system for patients with vitiligo.

Background: Vitiligo can be psychologically devastating and stigmatizing, with significant impacts on patients. As such, the early treatment and understanding of the profound psychosocial impact of this skin disease cannot be overstated. A standardized method of data collection with consistent definitions is a prerequisite for vitiligo management. Against this background, this study aimed to develop a minimum data set (MDS) for the vitiligo registry system. Materials and methods: The study was conducted in four steps in 2020 in Iran. After a comprehensive literature review to find relevant resources in English, medical records of patients with vitiligo were examined to assess the status quo of the country. Then, a model was developed from the data obtained in the previous step and through interviews. To reach a consensus on the data items, the Delphi technique was applied using a questionnaire, and the mean of expert judgments on each data item was calculated. Results: A total of 127 data elements were developed through two rounds of the Delphi technique. The MDS was divided into an administrative part with three sections and 18 data items, and a clinical part with seven sections and 109 data items. Conclusion: This study is the first step towards establishing a registry system for patients with vitiligo. Accurate identification of data items, such as MDSs, can be useful in establishing a vitiligo registry, planning, and improving the quality of patient care.

Affecting factors of cloud computing adoption in public hospitals affiliated with Zahedan University of Medical Sciences: A cross-sectional study in the Southeast of Iran.

OBJECTIVE: Health care organizations require cloud computing to remain efficient and cost-effective, and provide high-quality health care services. Adoption of this technology by users plays a critical role in the success of its application. This study aimed to determine factors affecting cloud computing adoption in public hospitals affiliated with Zahedan University of Medical Sciences. METHODS: A cross-sectional descriptive and analytic study was performed in 2017. The study population comprised information technology and hospital information system authorities and hospital information system users. The sample consisted of 573 participants. The data were collected using a questionnaire and analyzed with the Statistical Package for Social Sciences software using descriptive and analytical statistics. RESULTS: The mean score of environmental, human, organizational, technological, and intention dimensions of cloud computing adoption was 3.39 ± 0.81, 3.27 ± 0.63, 3.19 ± 0.71, 3 ± 0.43, and 3.55 ± 1.10, respectively. Furthermore, a significant positive relationship was found between intention of cloud computing adoption and environmental (R = 0.521, p = 0.000), organizational (R = 0.426, p = 0.000), human (R = 0.492, p = 0.000), and technological dimensions (R = 0.157, p = 0.000). CONCLUSIONS: Benefits of cloud computing adoption, relative advantage, and competitive pressure were identified as the most influential factors in accepting cloud computing. Simplifying the users' understanding of this technology and its application, improving the staff's technical capabilities, promoting executive managers' understanding of the nature and functions of cloud computing, and fully supporting and increasing governmental mandates for adoption of new technologies are necessary for facilitating the adoption of cloud computing in given hospitals.

Prerequisites of Personal Health Record for Chronic Kidney Disease: A Scoping Review and Evaluation of the Content Validity.

BACKGROUND: It is obvious that the Personal Health Record (PHR) is a major cornerstone for "improving the self-management of patient". However, lack of an effective and comprehensive personal health record system prohibits the widespread use of PHRs. The aim of this study was to identify the core data sets and required functionalities for designing a PHRs for chronic kidney disease (CKD) management and assess their validity. METHODS: It was a study including two phases. In the initial phase, a scoping review was conducted with the aim of determination the core data sets and required functionalities for designing PHRs. Then in the second phase, the validity of data items and functionalities was determined by 25 multidisciplinary experts. RESULTS: 22 studies were eligible after screening 1335 titles and abstracts and reviewing 88 full texts. We determined 20 core data set and 8 required functionalities of PHRs. From the perspective of experts, 'health maintenance' and 'advance directives' were most often marked as useful but not essential, while 'test and examination', 'medication list' and 'diagnosis and comorbid conditions" were predominantly considered as essential by all experts (n=25,100%). CONCLUSION: This research is a step that we have taken to identify prerequisites that could be used for the design, development, and implementation of an effective and comprehensive electronic personal health record.