@article{ 
author = {Eslami, Majid and Mousavian, Iman and EskandariFarsani, Farideh and Dadgostar, Reyhane and Asadollahi, Mohamad and Rahimi, Negar and Hatami, Atefeh and Mohammadkhani, Samaneh},  
title = {Evaluation of a Virtual Reality-Based Wearable Device for Patients with Ankle Movement Disorders}, 
abstract ={Introduction: Rehabilitation is one of the priorities that should be performed on patients with stroke injuries or accidents leading to disability. This study aimed to evaluate the equipment and designed virtual reality environment to improve the treatment of patients with mobility problems in the lower torso (ankle). Method: The research consisted of three basic parts. In the section of mechanics, a movement mechanism was developed after design, and with the help of electronic equipment and Arduino (1.18.5), movements were measured. And finally, by designing a virtual reality environment in Unity software, communication with hardware, processors, and sensors was provided. Results: Paying attention to graphic attractiveness and encouraging users to reuse the virtual reality system is one of the desirable results of this project, which can be effective in motivating users. In addition, considering the existence of distance and time of movement in a virtual reality environment, which depends on the user's movements in the real environment, it is possible to intelligently assess the patient's progress based on the number of sessions and distance traveled. Conclusion: Virtual reality-based rehabilitation methods can have a good effect on the treatment process due to the graphic attractiveness in this environment, and along with other rehabilitation methods, can be effective in faster recovery of people who need rehabilitation services. This method can help patients return to normal living conditions and reduce the time of this process.},  
Keywords = {Virtual Reality, Unity, Motion Sensor, Ankle Rehabilitation, Arduino},
volume = {9},
Number = {1}, 
pages = {1-11}, 
publisher = {دانشگاه علوم پزشکی کرمان},
url = {http://jhbmi.ir/article-1-683-en.html},  
eprint = {http://jhbmi.ir/article-1-683-en.pdf},  
journal = {Journal of Health and Biomedical Informatics},  
issn = {2423-3870}, 
eissn = {2423-3498}, 
year = {2022}  
}

@article{ 
author = {Shishehchi, Saman and Banihashem, Seyed Yashar},  
title = {Development of a Combined System Based on Data Mining and Semantic Web for the Diagnosis of Autism}, 
abstract ={Introduction: Autism is a nervous system disorder, and since there is no direct diagnosis for it, data mining can help diagnose the disease. Ontology as a backbone of the semantic web, a knowledge database with shareability and reusability, can be a confirmation of the correctness of disease diagnosis systems. This study aimed to provide a system for diagnosing autistic children with a combination of semantic web and data mining. Method: Data is taken from the UCI database. There were a total of 292 data records available of which 80% (234 records) were used for modeling through the decision tree. Knowledge about patients and autism disease was presented via ontology using the Protégé 5 software. The ontology has four classes and 12 properties to communicate between the individuals in the classes. The rules extracted from the decision tree were transformed into a comprehensible form (SWRL) for interpretation in the ontology using a converter. Results: Whether the child is healthy or not can be determined by the rules obtained in the decision tree. In addition, the output of the ontology using the interpretation of 25 rules confirmed the diagnosis of an Autistic child using the decision tree. The evaluation of the ontology also confirmed its correctness. Conclusion: According to the similarity between the result of the ontology and the decision tree regarding the diagnosis of the disease, the accuracy of the proposed method can be emphasized.  },  
Keywords = {Autism, Data Mining, Decision Tree, Ontology, Rule-based System},
volume = {9},
Number = {1}, 
pages = {12-24}, 
publisher = {دانشگاه علوم پزشکی کرمان},
url = {http://jhbmi.ir/article-1-681-en.html},  
eprint = {http://jhbmi.ir/article-1-681-en.pdf},  
journal = {Journal of Health and Biomedical Informatics},  
issn = {2423-3870}, 
eissn = {2423-3498}, 
year = {2022}  
}

@article{ 
author = {Moulaei, Khadijeh},  
title = {Future studies of physicians\' practice and digital health}, 
abstract ={The article is a letter to the editor, so it has no abstract.},  
Keywords = {},
volume = {9},
Number = {1}, 
pages = {25-26}, 
publisher = {دانشگاه علوم پزشکی کرمان},
url = {http://jhbmi.ir/article-1-702-en.html},  
eprint = {http://jhbmi.ir/article-1-702-en.pdf},  
journal = {Journal of Health and Biomedical Informatics},  
issn = {2423-3870}, 
eissn = {2423-3498}, 
year = {2022}  
}

@article{ 
author = {Makhloughi, Fatemeh and Goshvarpour, Ateke},  
title = {Prediction of Covid-19 Prevalence and Fatality Rates in Iran Using Long Short-Term Memory Neural Network}, 
abstract ={Introduction: The rapid spread of COVID-19 has become a critical threat to the world. So far, millions of people worldwide have been infected with the disease. The Covid-19 pandemic has had significant effects on various aspects of human life. Currently, prediction of the virus's spread is essential in order to be safe and make necessary arrangements. It can help control the rate of its outbreak and deaths. Previous studies have mainly used statistical tools and machine learning-based algorithms. However, the former was inadequate for analyzing unpredictable epidemics, and the latter experienced under-fitting or over-fitting problems. This research has proposed a method based on deep learning on long-term data to overcome these problems. Method: In this cross-sectional analytical study, we presented an approach for predicting the confirmed and death cases of COVID-19 based on long short-term memory (LSTM) networks. The LSTM model was applied to the time series data of Iran between January 22, 2020, and December 14, 2021, and RMSE and MAE evaluation metrics were calculated. Results: The best results of this study were RMSE = 27.57 and MAE = 19.01 for predicting death cases data. The results showed that the LSTM neural network had a good performance in predicting the number of confirmed and death cases of COVID-19 in Iran. Conclusion: The proposed model showed that it was appropriate for modeling and predicting the prevalence of the virus. Estimating the number of confirmed and death cases of COVID-19 can help control the pandemic situation.},  
Keywords = {COVID-19, Time Series Prediction, Recurrent Neural Network, Long Short-Term Memory, Iran},
volume = {9},
Number = {1}, 
pages = {27-39}, 
publisher = {دانشگاه علوم پزشکی کرمان},
url = {http://jhbmi.ir/article-1-667-en.html},  
eprint = {http://jhbmi.ir/article-1-667-en.pdf},  
journal = {Journal of Health and Biomedical Informatics},  
issn = {2423-3870}, 
eissn = {2423-3498}, 
year = {2022}  
}

@article{ 
author = {Yousefi, Mahdi and Hedyehzadeh, Mohammadrez},  
title = {Recurrence Detection of Non-small cell Lung Cancer (NSCLC) Tumors Using Imaging and Clinical Features}, 
abstract ={Introduction: Evaluation of treatment response is one of the most challenging tasks in the treatment planning of cancer cases. Regarding the significant effect of tumor recurrence in the treatment planning of patients with lung cancer, finding an approach to predict the recurrence of these tumors is of great importance. Nowadays, this process is done experimentally, and its accuracy depends on the experience and proficiency of the oncologist. This study aimed to provide an automated method to detect the recurrence of lung cancer based on imaging and clinical features. Method: Our proposed method was evaluated in 162 patients with non-small cell lung cancer (NSCLC) using the NSCLC radiogenomic database in the Cancer Imaging Archive (TCIA) portal. After pre-processing, segmentation was performed using the Otsu method. In the next step, the radiomic features were extracted using pre-trained AlexNet and GoogleNet models, and along with clinical features, they were used to detect lesion recurrence. Finally, all cases were classified into two classes using machine learning methods. Results: The proposed method used clinical and deep features. The classification was done using various models, and the accuracy of the support vector machine by AlexNet features resulted in the highest performance. The mean values of accuracy, sensitivity, and specificity for this model are 99.76, 99.77, and 99.76%, respectively. Conclusion: The main finding of this study was revealing the capability of deep learning methods in extracting features from medical images. For example, the AlexNet was able to extract features from CT images of NSCLC patients, which are very helpful in the recurrence prediction of these lesions.},  
Keywords = {Non-small cell Lung Cancer, Image Processing, Machine Learning, Deep Learning, Radiomics Features},
volume = {9},
Number = {1}, 
pages = {40-49}, 
publisher = {دانشگاه علوم پزشکی کرمان},
url = {http://jhbmi.ir/article-1-692-en.html},  
eprint = {http://jhbmi.ir/article-1-692-en.pdf},  
journal = {Journal of Health and Biomedical Informatics},  
issn = {2423-3870}, 
eissn = {2423-3498}, 
year = {2022}  
}

@article{ 
author = {Maghsoudi, Banafsheh and Langarizadeh, Mostafa and Esmaeili, Rouhparvar and MovahediRad, Marzieh},  
title = {Providing a Personal Health Record System for Patients with Hypothyroid Disease}, 
abstract ={Introduction: Hypothyroidism is a chronic disease in which patients become inattentive to their disease over time. Patients' management skills should be improved to minimize the risk of complications of this disease. This study aimed to provide a personal health record system for patients with hypothyroidism. Method: This developmental-applied research has been conducted in two phases. The first phase was the needs assessment, which was done with the participation of 10 endocrinologists. Then the prototype of the personal health record system was designed using ESP.NET in the Visual Studio software. In the second phase, system usability evaluation was performed by 52 patients. Data were analyzed using SPSS software, and the mean scores were classified into three levels as follows: "poor" (0-3), "moderate" (3.1-6), and "good" (6.1-9). Results: The findings of the first phase showed that data elements were recognized in six main groups, including demographic data, health history, general body examinations, laboratory results, treatment plan, and diagnostic information, and also 64 data elements approved by endocrinologists. Mean and standard deviation of usability evaluation according to users' point of view were reported in different indicators as follows: system usage (7.89±0.81), screen design (7.43±1.55), terminology and information (7.51±1.20), system learning capability (8.25±0.79) and overall system capabilities (8.14 ± 0.70). The usability of the system was evaluated as "good". Conclusion: The output of this study was designing a personal health records system for hypothyroid patients. This system could be helpful for physicians and patients in terms of providing care plans for patients, collecting accurate information from patients, improving patient participation in treatment, enhancing life quality, and reducing costs.  },  
Keywords = {Thyroid Disease, Hypothyroid, Personal Health Record, Web-based System},
volume = {9},
Number = {2}, 
pages = {50-57}, 
publisher = {دانشگاه علوم پزشکی کرمان},
url = {http://jhbmi.ir/article-1-693-en.html},  
eprint = {http://jhbmi.ir/article-1-693-en.pdf},  
journal = {Journal of Health and Biomedical Informatics},  
issn = {2423-3870}, 
eissn = {2423-3498}, 
year = {2022}  
}

@article{ 
author = {Salmanizadeh, Farzad and SarafiNejad, Afshin and Etminan, Abbas and Ahmadian, Leil},  
title = {Evaluating the Quality of Content and Degree of Completeness of Discharge Summaries from the Physicians\' Perspective}, 
abstract ={Introduction: Discharge summaries (DSs) are among the most important tools for transferring information from hospital physicians to other physicians and play an important role in the continuity of care. Low quality and lack of information are the main problems of DSs, and evaluation of their quality from the physicians' perspective in Iran has rarely been done. This study aimed to evaluate the DSs' quality of content and completeness. Method: This descriptive cross-sectional study was performed on the DSs of Shafa Hospital in Kerman. A valid and reliable researcher-made questionnaire (α=0.97) was used. This questionnaire had three sections, including questions related to demographic information, evaluation of the quality of DSs (8 questions), and the degree of completeness of the DSs (8 questions). Results: Out of 110 physicians, 98 (89%) filled out questionnaires. Completeness, awareness, continuity of care, legibility, relevancy, length, consistency, organization, and physicians’ satisfaction were below the average (50%) throughout the hospital. The highest level of physicians' satisfaction with the quality of the content (79.27%) and completeness (77.73%) was attributed to electronic discharge summaries of the neurology department. Organization, legibility, and consistency, respectively, were identified as the best predictors of physicians' satisfaction with the quality of the DSs’ content. Conclusion: Policymakers should increase the quality of DSs by creating instructions, holding documentation training courses, increasing the supervision of senior physicians on interns and residents, and finally developing electronic automated DSs.  },  
Keywords = {Patient Discharge Summaries, Documentation, Physicians, Medical Records, Hospital},
volume = {9},
Number = {2}, 
pages = {58-71}, 
publisher = {دانشگاه علوم پزشکی کرمان},
url = {http://jhbmi.ir/article-1-706-en.html},  
eprint = {http://jhbmi.ir/article-1-706-en.pdf},  
journal = {Journal of Health and Biomedical Informatics},  
issn = {2423-3870}, 
eissn = {2423-3498}, 
year = {2022}  
}

@article{ 
author = {Dinari, Fatemeh and Ghaemi, Mohammad Mehdi and Mashoof, Esmat and Moulaei, Khadijeh},  
title = {Identifying and Determining the Requirements for Designing and Developing a Mobile-Based Self-Care Application to Control and Reduce Students\' Stress and Anxiety}, 
abstract ={Introduction: The increase in stress and anxiety among students has a negative effect on their physical and mental health and can prevent their efficient academic performance. Self-care applications can help control and reduce students' anxiety and depression. The aim of this study was to determine the necessary requirements related to the design and development of a mobile-based self-care application to control and reduce stress and anxiety in students. Method: This research is a cross-sectional study that was conducted in 2022. To conduct this study, 38 students of Varastegan Institute for Medical Sciences (Razavi Khorasan province, Mashhad city) were included in the study based on the inclusion criteria and answered the questions of the questionnaire. Data were analyzed using descriptive statistics and SPSS version 25. Results: Out of 91 informational-educational needs and capabilities, 67 items with a mean score of ≥3.75 were considered essential for application design. Information-educational needs and capabilities were categorized into eight axes: user profile, clinical records, lifestyle, disease management and control, sedation instructions, warnings and reminders, reporting and application capabilities. Conclusion: Identifying and determining the requirements related to the design of an application based on a mobile phone is one of the basic principles of developing an application that by involving users and obtaining their opinions can have an important role in their continue use of these applications. Therefore, application designers can design and develop an organized mobile-based self-care application to control and manage students' stress and anxiety by using the information-educational needs and capabilities presented in the present study.},  
Keywords = {Application, Self-Care, Students, Stress, Anxiety},
volume = {9},
Number = {2}, 
pages = {72-83}, 
publisher = {دانشگاه علوم پزشکی کرمان},
url = {http://jhbmi.ir/article-1-724-en.html},  
eprint = {http://jhbmi.ir/article-1-724-en.pdf},  
journal = {Journal of Health and Biomedical Informatics},  
issn = {2423-3870}, 
eissn = {2423-3498}, 
year = {2022}  
}

@article{ 
author = {Langarizadeh, Mostafa and Zahedi, Hoda and Allahquli, Leil},  
title = {Developing a Smartphone-Based Educational Application for Women at Risk of Endometriosis}, 
abstract ={Introduction: Since endometriosis is a chronic disease and requires long-term care, it can have a devastating effect on life quality. For this reason, it is necessary to increase awareness and educate women about endometriosis. In this regard, a mobile phone-based endometriosis training program was designed. Method: The present paper is a development-applied study and was conducted in two stages. In the first stage, to determine the educational content, after reviewing previous studies, the questions obtained were given to eleven gynecologists and reproductive health doctors to measure the necessity and effectiveness of each question. After being designed, the program was provided to 40 women of reproductive age, and the usability of the program was assessed. Data analysis was performed using SPSS 22 software. Results: The required educational content of the application was presented in five groups and confirmed by specialists. The mean age of women who participated in this study was 32.35 ± 11.70 years. The average score of usability of the program was 8.34 out of 9 points which indicates a "good" level of satisfaction. Conclusion: Educating women through new popular tools such as mobile phones can play an important role in raising awareness and influencing their treatment. Therefore, designing a mobile phone-based training program in the field of education and awareness for women at risk of endometriosis can be advantageous.  },  
Keywords = {Endometriosis, Education, Mobile Health, Usability},
volume = {9},
Number = {2}, 
pages = {84-91}, 
publisher = {دانشگاه علوم پزشکی کرمان},
url = {http://jhbmi.ir/article-1-697-en.html},  
eprint = {http://jhbmi.ir/article-1-697-en.pdf},  
journal = {Journal of Health and Biomedical Informatics},  
issn = {2423-3870}, 
eissn = {2423-3498}, 
year = {2022}  
}

@article{ 
author = {Moshiri, Fatemeh and Asosheh, Abbas},  
title = {Presenting an Integrated Architecture of Hospital Information Systems Based on Interoperability Model: Clinical Information Systems}, 
abstract ={Introduction: Hospital information system (HIS) as an integrated information system is used for daily operations, planning, care, and treatment of patients. Due to the existence of various and heterogeneous healthcare information systems, HIS encounters interoperability problems. In this regard, this study aimed to propose an integrated architecture for HIS based on the interoperability model. Method: This research is a strategic-applied study for achieving an integrated HIS architecture, focusing on clinical information systems (CIS). First, the requirements of clinical information systems were carried out through library studies, the review of the statistics office of the Ministry of Health, Treatment and Medical Education, and it was also reviewed and confirmed by information technology experts. Then, different interoperability frameworks and HIS architecture models were studied. Finally, the integrated HIS architecture model was proposed based on the interoperability model. Results: The integrated HIS architecture based on the interoperability model includes three architecture models as follows: references, software, and information. Reference architecture is proposed generally for the HIS and customized for CIS. For implementing various HISs, software architecture is proposed. And information architecture is used for storing, processing, and transmitting the information. Conclusion: Considering the necessity of integration in the health system, this study creates the possibility of interoperability and integration between HIS systems by applying the guidelines of integration in the architecture, which leads to cost reduction, quality improvement, and timely decision-making.},  
Keywords = {Reference Architecture, Hospital Information System, Service Orientation, Interoperability},
volume = {9},
Number = {2}, 
pages = {92-103}, 
publisher = {دانشگاه علوم پزشکی کرمان},
url = {http://jhbmi.ir/article-1-698-en.html},  
eprint = {http://jhbmi.ir/article-1-698-en.pdf},  
journal = {Journal of Health and Biomedical Informatics},  
issn = {2423-3870}, 
eissn = {2423-3498}, 
year = {2022}  
}

@article{ 
author = {Hajesmaeel-Gohari, Sadrieh},  
title = {Application of Digital Games in the Field of Health}, 
abstract ={The article is a letter to the editor, so it has no abstract.},  
Keywords = {},
volume = {9},
Number = {2}, 
pages = {104-105}, 
publisher = {دانشگاه علوم پزشکی کرمان},
url = {http://jhbmi.ir/article-1-715-en.html},  
eprint = {http://jhbmi.ir/article-1-715-en.pdf},  
journal = {Journal of Health and Biomedical Informatics},  
issn = {2423-3870}, 
eissn = {2423-3498}, 
year = {2022}  
}

@article{ 
author = {Fariborzi, Mana and Zeinalnezhad, Masoomeh and Saghaei, Abbas},  
title = {Accuracy Improvement of Mood Disorders Prediction using a Combination of Data Mining and Meta-Heuristic Algorithms}, 
abstract ={Introduction: Since the delay or mistake in the diagnosis of mood disorders due to the similarity of their symptoms hinders effective treatment, this study aimed to accurately diagnose mood disorders including psychosis, autism, personality disorder, bipolar, depression, and schizophrenia, through modeling and analyzing patients' data. Method: Data collected in this applied developmental research included 996 records with 130 features obtained by interviewing and completing questionnaires in a mental hospital in the city of Sari, Iran in 2021. After preprocessing, the number of features was reduced to 91, and then through Principal Component Analysis (PCA) reduced to 35 factors.  Modeling was done in Python software with K-Nearest Neighbor (KNN), Naive Bayes (NB), Decision Tree (DT), Random Forest (RF), Logistic Regression (LR), and Support Vector Machine (SVM) algorithms. The models were evaluated to select algorithms with higher accuracy. Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) were applied to determine the optimal parameters of the selected algorithms. Results: Among the machine learning algorithms, random forest with 91% accuracy and support vector machine with 90% accuracy showed better performance. The genetic algorithms did not make any notable increase in prediction accuracy. Whereas considering N=30, T=150, W=0.9, c1=2, and c2=2 in the particle swarm optimization algorithm increased the prediction accuracy up to 3.3 %. Conclusion: With less classification error compared to similar studies, the PSO-SVM model designed in this study can be used in patient data monitoring with acceptable accuracy and can be used in intelligent systems in psychiatric centers.},  
Keywords = {Mood Disorder, Machine Learning, Meta-Heuristic Algorithms, Data Mining, Prediction},
volume = {9},
Number = {3}, 
pages = {106-119}, 
publisher = {دانشگاه علوم پزشکی کرمان},

doi = {10.34172/jhbmi.2022.01},
url = {http://jhbmi.ir/article-1-712-en.html},  
eprint = {http://jhbmi.ir/article-1-712-en.pdf},  
journal = {Journal of Health and Biomedical Informatics},  
issn = {2423-3870}, 
eissn = {2423-3498}, 
year = {2022}  
}

@article{ 
author = {Aliakbarpour, Hamideh and Shahmansoury, Ashraf and Bazaee, Ghasemali},  
title = {Identifying the Challenges of the Blockchain Technology Maturity Model in Health-Oriented Organizations}, 
abstract ={Introduction: Blockchain is a widely used technology in the health area; however, it also comes with challenges. By identifying these challenges, the road to blockchain maturity can be made smoother in this field. This study aimed to identify the challenges of the blockchain technology maturity model in health-oriented organizations. Method: In this phenomenological qualitative study, experts in the field of blockchain technology were the statistical population 12 of whom were selected to conduct an in-depth interview. The validity of the findings was guaranteed by the methods of matching by members and peer review. In this manner, the participants reviewed the process of primary data (interview results) analysis. And in the peer review procedure, supervisors, advisors, and two doctoral students commented on the findings. To analyze the data, open and axial coding was used. Results: The challenges of this model, in the technical and organizational sections, have been drawn and presented in the form of a structural model. In the resulting model, each of the categories is specified with its subset, and their frequency is also specified in the model to prioritize and determine their importance. Conclusion: In health-oriented organizations, the challenges of information security in the technology sector and transparency in the organizational structure are among the most important challenges. The security of data, due to the high importance of maintaining them, and creating transparency, due to the impossibility of manipulating data, are challenges that if ignored, the process of reaching technology maturity in health-oriented organizations will fail.},  
Keywords = {Risks and Challenges, Blockchain Technology Maturity Model, Health-Oriented Organizations, Blockchain Technology, Phenomenology},
volume = {9},
Number = {3}, 
pages = {120-129}, 
publisher = {دانشگاه علوم پزشکی کرمان},

doi = {10.34172/jhbmi.2022.02},
url = {http://jhbmi.ir/article-1-699-en.html},  
eprint = {http://jhbmi.ir/article-1-699-en.pdf},  
journal = {Journal of Health and Biomedical Informatics},  
issn = {2423-3870}, 
eissn = {2423-3498}, 
year = {2022}  
}

@article{ 
author = {Farokhzadian, Jamileh and Jouparinejad, Somayeh and Farahmandnia, Hojjat},  
title = {Investigating the Information Technology Competency of Nurses in Critical Care Units: A cross-sectional study}, 
abstract ={Introduction: With the rapid growth of information technology (IT) and the expectations of health care environments, the presence of nurses with informatics skills in the health care environment to effectively use and manage health care information in health care delivery seems necessary; therefore, this study was conducted to evaluate the IT competency of special care nurses from their point of view. Method: This cross-sectional study aimed to investigate the IT competency of nurses in the special care departments of Afzalipur Hospital of Kerman University of Medical Sciences in 1400 SH. The study population included 60 nurses working in the intensive care units (ICU and CCU) who were included in the study using a census method. The Nursing Informatics Competency Assessment Tool (NICAT) was used in this research. Results: The findings of the study showed that the average score of IT qualification of nurses in the special care department (2.70 ± 0.85) is within the range of “competent”. The data showed that the highest score of IT competency of the studied nurses was attributed to the computer literacy section (2.82±0.93), and the lowest score was related to the information management skills section (2.58±0.85). Conclusion: It is suggested that clinical nursing managers improve the IT competency of nurses by implementing educational programs in the field of “IT literacy in the hospital”, especially in the division of information management skills which had the lowest average score, so that they can use the latest evidence to provide more effective care at the bedside.  },  
Keywords = {Technology Competency, Information, Nursing, Critical Care Units},
volume = {9},
Number = {3}, 
pages = {130-137}, 
publisher = {دانشگاه علوم پزشکی کرمان},

doi = {10.34172/jhbmi.2022.03},
url = {http://jhbmi.ir/article-1-732-en.html},  
eprint = {http://jhbmi.ir/article-1-732-en.pdf},  
journal = {Journal of Health and Biomedical Informatics},  
issn = {2423-3870}, 
eissn = {2423-3498}, 
year = {2022}  
}

@article{ 
author = {Hosseini, Seyed Mostafa and Borjalilu, Somaieh},  
title = {Impact of the Mobile App “Cognogene” on University Students\' Communication Skills}, 
abstract ={Introduction: The notion of electronic mental health care is suggested in today's world. With the aid of this care, people's talents are no longer limited by time or location, and those in need of mental health care can get these services by downloading and installing software on their mobile devices. The Cognogene application software has been created to provide electronic mental health services on the smartphone platform. This study aimed to measure the impact of the mobile app “Cognogene” on university students' communication skills. Method: The statistical population of this study included 104 students studying at Tehran University in the winter semester (2021-2022). They were randomly divided into two 54-member groups (experimental and control). The experimental group received electronic psychological education (consisting of short video clips, daily homework, motivational letters, etc.) in 21 sessions, while the control group did not. To collect data, Queen Dom's communication skills questionnaire was used in two stages: pre-test and post-test. The data were analyzed using the one-way analysis of variance. Results: Results showed that the intervention made a significant difference in the mean score of all components of the study of communication skills except the components of "receiving and sending messages" and "emotional control". Conclusion: This finding suggests that training through the Cognogene application can be used as a complement to other training methods to improve communication skills},  
Keywords = {Electronic Health, Communication Skills, Cognogene},
volume = {9},
Number = {3}, 
pages = {138-147}, 
publisher = {دانشگاه علوم پزشکی کرمان},

doi = {10.34172/jhbmi.2022.04},
url = {http://jhbmi.ir/article-1-717-en.html},  
eprint = {http://jhbmi.ir/article-1-717-en.pdf},  
journal = {Journal of Health and Biomedical Informatics},  
issn = {2423-3870}, 
eissn = {2423-3498}, 
year = {2022}  
}

@article{ 
author = {Besharati, Reza and Tahmasbi, Hamidrez},  
title = {Hypertension Prediction in Primary School Students Using an Ensemble Machine Learning Method}, 
abstract ={Introduction: The prevalence of hypertension in children is increasing, and this complication is considered the most important risk factor for cardiovascular diseases in older age. Early detection and control of hypertension can prevent its progress and reduce its consequences. Machine learning methods can help predict this complication promptly and reduce cost and time. This study aimed to provide a model based on ensemble machine learning methods to more accurately predict the hypertension of primary school children. Method: This is an applied developmental study that was conducted using the information of 1287 primary school children aged 7-13 years in Kashmar city. After data preprocessing, to achieve a more accurate diagnosis of hypertension in children, the output results of five common machine learning methods in disease diagnosis including decision tree, naive Bayesian, nearest neighbors, artificial neural network, and support vector machine using weighted majority voting method were combined. Results: The results showed that the accuracy, sensitivity, and specificity of the proposed model were 90.31%, 80.65%, and 93.54%, respectively, and compared to similar studies it performed better. Conclusion: The proposed model can better predict and diagnose hypertension in children and improve accuracy and reduce the error rate. This model can be a useful and early tool in the diagnosis of hypertension in children, reducing the consequences and costs of this complication and being a big step in the fight against hypertension.},  
Keywords = {Hypertension, Primary School Students, Machine Learning Methods, Prediction},
volume = {9},
Number = {3}, 
pages = {148-157}, 
publisher = {دانشگاه علوم پزشکی کرمان},

doi = {10.34172/jhbmi.2022.05},
url = {http://jhbmi.ir/article-1-723-en.html},  
eprint = {http://jhbmi.ir/article-1-723-en.pdf},  
journal = {Journal of Health and Biomedical Informatics},  
issn = {2423-3870}, 
eissn = {2423-3498}, 
year = {2022}  
}

@article{ 
author = {Moniri, Marziye and Niazkhani, Zahra and Makhdoomi, Khadijeh and RashidiKhazaee, Parviz and Pirnejad, Habibollah},  
title = {Clinical decision supports for brain-dead kidney allocation: a review study of requirements, challenges, and solutions}, 
abstract ={Introduction: With the change in the epidemiology of diseases, chronic kidney disease has shown a significant increase worldwide. Kidney transplantation is the optimal treatment option to improve patient quality of life. The main challenge in benefiting from a brain-dead patient's kidney is the selection of a right recipient in limited time. The purpose of this study was to review the requirements for designing and implementing clinical decision support systems for allocating brain-dead kidneys and the challenges facing them. Method: This scoping review was conducted by searching Scopus, PubMed, and Google scholar to find full-text English articles published until the end of 2021. The articles were analyzed based on the objectives of the study, the factors used in decision-making for allocation, the algorithms used in the decision-making process, and their outcome evaluations. Results: Two categories of medical (including the quality of the donated kidney) and equity/fairness factors were used in most allocation algorithms. However, the number of factors, the method, and the order of their application were different in different studies. Studies have reported different challenges but a positive impact using decision support systems. Conclusion: One of the main challenges in the proper management of kidney transplants from brain-dead donors is to have local, agreed-upon protocols and algorithms regarding the methods, order, and weight of each of the medical and equity factors in the proposed protocol. Algorithms based on scoring have mostly been favored. Therefore, the probability of using a decision support system on this base seems to be higher.  },  
Keywords = {kidney transplant, kidney allocation system, cadaver donor, clinical decision support system, scoring system, donor-recipient matching system, review study},
volume = {9},
Number = {3}, 
pages = {158-179}, 
publisher = {دانشگاه علوم پزشکی کرمان},

doi = {10.34172/jhbmi.2022.06},
url = {http://jhbmi.ir/article-1-716-en.html},  
eprint = {http://jhbmi.ir/article-1-716-en.pdf},  
journal = {Journal of Health and Biomedical Informatics},  
issn = {2423-3870}, 
eissn = {2423-3498}, 
year = {2022}  
}

@article{ 
author = {AnvariSadi, Zahra and Safaei, Aliasghar},  
title = {A Narrative Review of Blockchain in Healthcare: Applications and challenges}, 
abstract ={Introduction: Healthcare as an industry has unique requirements such as patient security and privacy, interoperability, sharing, transmission, and access control of patient data. On the other hand, the advantages of blockchain technology and the compliance of these advantages with the requirements of the health industry have encouraged researchers to investigate the methods of applying blockchain in healthcare. The rapid increase in blockchain and health research has created many applications. Despite the high potential of this technology for health applications, there are still challenges to be reviewed. In this article, we provide a narrative overview of blockchain applications and challenges in the healthcare industry. Method: In this narrative review, published studies until October 2022 that were accessible in PubMed, IEEE Xplore, Web of Science, and Scopus databases were searched; from 254 related studies, 171 were identified by their titles, and finally, after applying inclusion and exclusion criteria, 30 articles were selected to be reviewed. Results: The results showed that 10 applications of blockchain technology in healthcare are as follows: safe sharing of health data, establishing electronic medical records, medical record tracking, opioid prescription tracking, deep learning, drug supply chain, clinical trials, COVID-19 pandemic management, and remote patient monitoring. The application of blockchain technology in healthcare also has challenges such as interoperability, security and privacy, immutability, scalability, patient engagement, transparency, and confidentiality. Conclusion: The compatibility between the requirements of the health industry and the characteristics of the blockchain has created a suitable platform for the use of this technology in the health industry. However, there are challenges in the path of these applications that must be solved.  },  
Keywords = {Blockchain, Healthcare, Applications and Challenges, Narrative Review},
volume = {9},
Number = {3}, 
pages = {180-192}, 
publisher = {دانشگاه علوم پزشکی کرمان},

doi = {10.34172/jhbmi.2022.07},
url = {http://jhbmi.ir/article-1-728-en.html},  
eprint = {http://jhbmi.ir/article-1-728-en.pdf},  
journal = {Journal of Health and Biomedical Informatics},  
issn = {2423-3870}, 
eissn = {2423-3498}, 
year = {2022}  
}

@article{ 
author = {Nabizadeh, Amirhosei},  
title = {Artificial Intelligence in Healthcare}, 
abstract ={The article is a letter to the editor, so it has no abstract.},  
Keywords = {Artificial Intelligence, Healthcare},
volume = {9},
Number = {3}, 
pages = {193-195}, 
publisher = {دانشگاه علوم پزشکی کرمان},

doi = {10.34172/jhbmi.2022.08},
url = {http://jhbmi.ir/article-1-749-en.html},  
eprint = {http://jhbmi.ir/article-1-749-en.pdf},  
journal = {Journal of Health and Biomedical Informatics},  
issn = {2423-3870}, 
eissn = {2423-3498}, 
year = {2022}  
}

@article{ 
author = {Mortezaei, Saman and Khanjani, Sajjad and Mohammadnejad, Eissa and MokariAmjad, Pouy},  
title = {Design and Evaluation of an mHealth Application in Self-Management of Post-Traumatic Stress Disorder}, 
abstract ={Introduction: Recent developments in the use of mobile technologies have given rise to opportunities for more effective and cost-efficient services for people with chronic diseases. Considering the relatively high prevalence of post-traumatic stress disorder (PTSD) in Iran and the lack of a native application for the self-management of many complications of this disorder, the present study aims to develop and evaluate a mobile application for PTSD self-management. Method: This developmental-applied study was conducted in two stages. In the first stage, interviews and a literature review were carried out to identify users’ requirements and expectations of the application. Then, the application was modeled, designed, developed, and tested based on the requirements. In the second stage, the usability of developed application was evaluated by experts and users. Results: The following services were implemented in the application: psychoeducation, coping skills, breathing exercise, relaxation, positive affect, social support, self-assessment, reminders, useful links, and self-monitoring. According to experts’ evaluation, the application was of acceptable quality (78.25%). The application was relatively acceptable from the users’ point of view (68.67%). In the evaluation process, experts were most satisfied with the functionality of the application (80 %), and users were most satisfied with the application’s ease of use (76%). Conclusion: Using the application can be useful in promoting access to healthcare services for patients with PTSD, and in addition to saving time and costs, it can be effective in the self-management of this disorder.},  
Keywords = {Post-traumatic stress disorder, mHealth, Self-Management, Usability, Medical Informatics},
volume = {9},
Number = {4}, 
pages = {196-208}, 
publisher = {دانشگاه علوم پزشکی کرمان},

doi = {10.34172/jhbmi.2023.01},
url = {http://jhbmi.ir/article-1-735-en.html},  
eprint = {http://jhbmi.ir/article-1-735-en.pdf},  
journal = {Journal of Health and Biomedical Informatics},  
issn = {2423-3870}, 
eissn = {2423-3498}, 
year = {2023}  
}

@article{ 
author = {Maghsoudi, Rouhollah and Mirzarezaee, Mitra and Sadeghi, Mehdi and Najar-Araabi, Babak},  
title = {Development of a Pharmacogenomics Model based on Support Vector Regression with Optimal Features Selection Approach to Determine the Initial Therapeutic Dose of Warfarin Anticoagulant Drug}, 
abstract ={Introduction: Using artificial intelligence tools in pharmacogenomics is one of the latest bioinformatics research fields. One of the most important drugs that determining its initial therapeutic dose is difficult is the anticoagulant warfarin. Warfarin is an oral anticoagulant that, due to its narrow therapeutic window and complex interrelationships of individual factors, the selection of its optimal dose is challenging. Method: Among the relatively successful methods of kernel-based estimation, comparison and identification of suitable kernels have not been researched. In the present research, while carefully examining this approach, different features of selection algorithms were analyzed based on expert opinions, and an appropriate subset of efficient predictor variables was identified for dose estimation. Results: In the current study, a dataset collected by the International Warfarin Consortium was used. The results showed that the support vector machine with a suitable kernel and a subset of the proposed features can successfully predict the ideal dose of warfarin for a significant percentage of patients with an error of approximately 0.7 mg per week. Conclusion: The estimation was conducted using the least squares version of the support vector regression based on a suitable kernel and feature selection strategy. In this method, a better approach for predicting the optimal therapeutic dose of warfarin was presented, which can significantly reduce the wrong dose error and its consequences.},  
Keywords = {Pharmacogenomics, Initial Warfarin Dose Estimation, Feature Selection, Least Squares Support Vector Regression},
volume = {9},
Number = {4}, 
pages = {209-229}, 
publisher = {دانشگاه علوم پزشکی کرمان},

doi = {doi: 10.34172/jhbmi.2023.02},
url = {http://jhbmi.ir/article-1-721-en.html},  
eprint = {http://jhbmi.ir/article-1-721-en.pdf},  
journal = {Journal of Health and Biomedical Informatics},  
issn = {2423-3870}, 
eissn = {2423-3498}, 
year = {2023}  
}

@article{ 
author = {ModaresTorbati, Mehran and KazemidoustDemochali, Sadegh and Farzinfard, Mansour and Bagheri, Morteza and Bagheri, Hasan and Arabfard, Masou},  
title = {Design and Implementation of a Review Management System in the Field of Medicine and Health}, 
abstract ={Introduction: The increasing growth of science and specialized articles in various fields, especially in health and treatment, has faced researchers with the challenge of keeping up with this progress. Review research provides researchers with the possibility to gain access to an acceptable and categorized amount of information by spending less time and money and helps them reach the original essence of the research. However, carrying out such research is very difficult because it requires deep knowledge of the specific field as well as reviewing several studies to find and gather appropriate information. By developing a system, we intended to help researchers in the process of categorizing, extracting, and aggregating data and findings. This study aimed to design and implement a database management system to review studies in the field of medicine and health. Method: This practical study was done in 2022, and associated with software development. The system was developed in three stages as follows: 1) analysis, 2) implementation, and 3) testing and troubleshooting. This system is implemented using the frameworks based on JavaScript, Angular on the front-end side and Node JS on the back-end side. In the final stage, the system was tested using actual research, and possible defects and problems were detected and solved; finally, the system was handed over to the research team to conduct new research. Results: In the process of testing the system, we found that by using this system, the accuracy of the information entry process can be greatly increased, and the analysis of the results can be done online with high speed and accuracy. Conclusion: The results of the present analysis can help policy makers for appropriate legislation and business managers to solve identified problems and increase user trust and satisfaction.},  
Keywords = {System Design, Database Management, Review Research, Medicine and Health},
volume = {9},
Number = {4}, 
pages = {230-243}, 
publisher = {دانشگاه علوم پزشکی کرمان},

doi = {‎ doi:10.34172/jhbmi.2023.03},
url = {http://jhbmi.ir/article-1-747-en.html},  
eprint = {http://jhbmi.ir/article-1-747-en.pdf},  
journal = {Journal of Health and Biomedical Informatics},  
issn = {2423-3870}, 
eissn = {2423-3498}, 
year = {2023}  
}

@article{ 
author = {Ghaderi, Fatemeh and RajabzadehGhatari‌, Ali and Radfar, Rez},  
title = {Prioritization of Purchasing Criteria by Linear Best-Worst Multi-Criteria Decision-Making Method for Optimal Provision of Medical Supplies}, 
abstract ={Introduction: One of the main challenges of the health system is improving the quality of healthcare services by adjusting the costs. The right choice of tools will bring economic savings besides excellent service quality. Since medical supplies are among the fundamental and costly elements in providing services, the expertise of purchasing has become an important and complex issue. This study aimed to prioritize criteria for purchasing medical supplies. Method: This research is an applied study conducted with a descriptive survey method. In this study, the criteria collected from related studies and completed with the opinion of experts were prioritized and weighted for four categories of medical supplies by the linear best-worst multi-criteria decision-making method using Lingo and Excel software. Results: By weighting sixteen sub-criteria of purchasing medical supplies in the form of five categories, the importance of each criterion was determined. According to the results, the two sub-criteria of "quality" and "price" were recognized as the most important and "seller's record" as the least important indicator in the purchase of medical supplies. Conclusion: Using the linear best-worst multi-criteria decision-making method with definite consistency of results and high reliability led to the prioritization and accurate weighting of criteria for purchasing supplies. Paying attention to the indicators in the purchase of medical supplies, in addition to guaranteeing the quality and continuity of services, will lead to a significant reduction in supply costs.},  
Keywords = {Health and Treatment Centers, Medical Supplies, Purchasing Expertise, Multi-Criteria Decision-Making, Best-Worst Method},
volume = {9},
Number = {4}, 
pages = {244-255}, 
publisher = {دانشگاه علوم پزشکی کرمان},

doi = {10.34172/jhbmi.2023.04   },
url = {http://jhbmi.ir/article-1-729-en.html},  
eprint = {http://jhbmi.ir/article-1-729-en.pdf},  
journal = {Journal of Health and Biomedical Informatics},  
issn = {2423-3870}, 
eissn = {2423-3498}, 
year = {2023}  
}

@article{ 
author = {Salehnia, Nafiseh and Salehnia, Fatemeh},  
title = {Identifying the Challenges of Users in Using the Services of Electronic Health Platforms}, 
abstract ={Introduction: In recent years, especially with the spread of the COVID-19 disease, the use of electronic health services has increased greatly. Along with the growth and development of the use of electronic services among users, the concern about ethical and legal issues increases. The purpose of this article was to review the current state of electronic health provision by active platforms in this field and to identify the challenges and problems of users in using these services to achieve the desired state. Method: This qualitative study was conducted using the content analysis method. User comments were collected in Bazaar and Myket mobile applications. Then, using the purposeful sampling method, 300 selected comments containing users' difficulties were analyzed by qualitative content analysis method based on the six steps proposed by Graneheim & Lundman using MAXQDA software. Results: The most important problems reported by users of e-health services fall into two main categories: issues related to care and issues related to the service provider's platform; these difficulties are classified into six subcategories, including doctor-patient relationships, the standard of care, platform quality, user feedback, responsibility, and service tariff. Among the user comments, the most dissatisfaction was associated with the subcategory of the platform's responsibility and accountability (especially the issue of not receiving services despite paying, poor support, and no refunds), followed by issues related to the standard of care. Conclusion: The results of the present analysis can help policymakers with appropriate legislation and regulation and help business managers with solving identified problems. It also increases user satisfaction and trust.},  
Keywords = {e-Health, Telemedicine, User, Content Analysis},
volume = {9},
Number = {4}, 
pages = {256-266}, 
publisher = {دانشگاه علوم پزشکی کرمان},

doi = {10.34172/jhbmi.2023.05  },
url = {http://jhbmi.ir/article-1-737-en.html},  
eprint = {http://jhbmi.ir/article-1-737-en.pdf},  
journal = {Journal of Health and Biomedical Informatics},  
issn = {2423-3870}, 
eissn = {2423-3498}, 
year = {2023}  
}

@article{ 
author = {Yadegari, Fatemeh and Asosheh, Abbas},  
title = {Introducing a Service Model in IoT-based Smart Hospital}, 
abstract ={Introduction: Nowadays, the world of technology is facing a growing phenomenon called the Internet of Things (IoT). The purpose of this study is to provide the infrastructure requirements, service model, and conceptual model for a smart hospital based on IoT, which is a safe and reliable method due to the integration of exchanges between objects. Method: In this strategic applied study, the infrastructure requirements of a smart hospital based on IoT are explained explains. First, basic requirements were prepared through library studies and, by setting up a questionnaire for medical staff and specialists in medical informatics, information technology, and health information technology, they were evaluated and then finalized using the Delphi technique. Then, based on extracted requirements, the service model of a smart hospital was presented. Finally, the conceptual model of IoT-based smart hospital infrastructure was suggested. Results: Thirty functional and non-functional requirements for IoT-based smart hospital infrastructure were determined. After that, the proposed model of services that can be provided in the hospital, including infrastructure, core and value-added services, was presented. Then, a conceptual model that includes the health ecosystem of the country, consisting of the levels of communication and information infrastructure, digital service systems, and the health system was provided. Conclusion: Agreement on the requirements, service and conceptual model, will help to design and implement the IoT-based smart hospital and make it more accurate and simple, according to factors affecting such as precision, speed and reliability in healthcare.},  
Keywords = {Smart Hospital, Healthcare-Internet of Things (H-IoT), Infrastructure, Requirements, Integration},
volume = {9},
Number = {4}, 
pages = {267-276}, 
publisher = {دانشگاه علوم پزشکی کرمان},

doi = {10.34172/jhbmi.2023.06},
url = {http://jhbmi.ir/article-1-734-en.html},  
eprint = {http://jhbmi.ir/article-1-734-en.pdf},  
journal = {Journal of Health and Biomedical Informatics},  
issn = {2423-3870}, 
eissn = {2423-3498}, 
year = {2023}  
}

@article{ 
author = {Bashiri, Azadeh and Shahmoradi, Leila and AlizadehSavareh, Behrouz and Ghazisaeedi, Marj},  
title = {Identification of Effective Computerized Cognitive Rehabilitation Programs in Improving Attention in the Children and Adolescents with Attention Deficit Hyperactivity Disorder}, 
abstract ={Introduction: Computerized programs for brain empowerment with regular, intensive, and continuous cognitive exercises improve cognitive functions such as attention in attention deficit hyperactivity disorder. This review study aimed to identify effective computerized programs for improving attention in children and adolescents with attention deficit hyperactivity disorder (ADHD). Method: This descriptive narrative review was done in 2018 through library review and searching keywords including "attention deficit hyperactivity disorder", "computerized cognitive rehabilitation programs", and "play therapy" in databases such as PubMed, Scopus, and Google Scholar. The results of this review were investigated through the semi-structured interview and classified based on the attention areas of children and adolescents with ADHD. Results: Based on the review, Caption Log, Pay Attention, Cogmed Working Memory, Memory GYM, Attention GYM, Brainware Safari, 8 Sciences' ACTIVATET, Lumosity, My Happy Neuron, Smart Driver, and educational packages such as Maghzine were effective programs to improve different types of attention (focused, divided, intermittent, continuous, and selective) in the ADHD children aged four years old and older. Conclusion: Considering the significant effects of computerized cognitive rehabilitation programs in empowering cognitive skills such as attention, their use as a complementary treatment in improving the quality of life of children and adolescents with ADHD is promising. However, it is suggested to evaluate such programs with larger samples, transfer their educational effects to daily life, and improve their quality by providing more components of such programs.},  
Keywords = {Attention Deficit, Hyperactivity, Computerized Cognitive Rehabilitation, Game Therapy},
volume = {9},
Number = {4}, 
pages = {277-288}, 
publisher = {دانشگاه علوم پزشکی کرمان},

doi = {10.34172/jhbmi.2023.07},
url = {http://jhbmi.ir/article-1-730-en.html},  
eprint = {http://jhbmi.ir/article-1-730-en.pdf},  
journal = {Journal of Health and Biomedical Informatics},  
issn = {2423-3870}, 
eissn = {2423-3498}, 
year = {2023}  
}

@article{ 
author = {Ameri, Fatemeh and Haghparast, Fatemeh and Akhondi, Zahra and MirdoostiDozein, Seyedeh Zahra and Javanmard, Zohreh},  
title = {Application of Virtual Reality in Hospitals: A Systematic Review}, 
abstract ={Introduction: Due to the increasing use of virtual reality (VR) technology in the healthcare field, the present study was conducted to systematically investigate the use of VR in hospitals. Method: To access related articles, the keywords "Virtual Reality" and "Hospital" and their synonyms were searched in databases of Web of Science, PubMed, Scopus, and Google Scholar without a time limit until August 15, 2022. The original articles that were published in English and dealt with "the application of virtual reality in the hospital" were included in the study, and their characteristics were analyzed. Results: Eleven articles were included in the present study, in which various applications for VR in the hospital environment have been reported. The most common uses of VR in hospitals are as follows: managing behavioral symptoms, creating relaxation and inducing positive emotions in patients, providing treatment and physical, mental, and emotional rehabilitation in patients, providing training for care providers in different hospital departments, virtual presence at home for hospitalized children and teenagers; VR can also work as a supplement to the procedure for the children's lives and an adaptive substitute for experiences in the real environment for the medical residents.. Conclusion: Considering the positive impact of using VR in hospitals, using this technology as an auxiliary tool to improve education, treatment, and prevention in the healthcare system is suggested.},  
Keywords = {Virtual Reality, Hospital, Systematic review},
volume = {9},
Number = {4}, 
pages = {289-303}, 
publisher = {دانشگاه علوم پزشکی کرمان},

doi = {10.34172/jhbmi.2023.08},
url = {http://jhbmi.ir/article-1-741-en.html},  
eprint = {http://jhbmi.ir/article-1-741-en.pdf},  
journal = {Journal of Health and Biomedical Informatics},  
issn = {2423-3870}, 
eissn = {2423-3498}, 
year = {2023}  
}

@article{ 
author = {Kaboutarizadeh, Leila and Kordi, Marzieh and Koohmare, Zahra and Hosseini, Seyyed Mohsen and Azizi, Amirabbas},  
title = {Developing a Native Model for Evaluating the Usability of Health Information Systems Through Heuristic Evaluation Technique}, 
abstract ={Introduction: A quality criterion for evaluating information systems (ISs) is their usability, which can be determined by examining the user interface. User interface issues may generate user errors, dissatisfaction, and inefficiency, making IS adoption difficult. Therefore, the International Standard Organization recommends usability testing to evaluate IS acceptability and deployment. So, this study aimed to develop a native model for the usability testing of hospital information systems (HISs) via heuristic evaluation (HE). Method: This multi-staged qualitative study was conducted in 2020; ScienceDirect, PubMed, Web of Science, Scopus, Civilica, and Magiran databases were searched. After meeting the inclusion criteria, the articles were scored. Then, the initial model was created in the following stage by extracting data from library sources and validated using the Delphi technique, and consequently, the final model was presented. Results: : The native model was developed using thirteen principles: 1) visibility of system status, 2) the match between the system and the real world, 3) users’ control and freedom, 4) consistency and standards, 5) error prevention, 6) recognition rather than recall, 7) flexibility and efficiency of use, 8) aesthetic and minimalist design, 9) helping users recognize, diagnose, and recover errors, 10) documentation and help, 11) skill , 12) pleasurable, respectful interaction with users, and 13) privacy protection. Conclusion: This study demonstrated that localizing the usability evaluation of HISs based on trustworthy sources and HE is a wise strategy, because not only it avoids repetitive processes, but also it uses the best up-to-date resources to enable the presentation of the highest evaluation quality.},  
Keywords = {Health information systems, Heuristic evaluation, Usability},
volume = {9},
Number = {4}, 
pages = {304-324}, 
publisher = {دانشگاه علوم پزشکی کرمان},

doi = {10.34172/jhbmi.2023.09},
url = {http://jhbmi.ir/article-1-754-en.html},  
eprint = {http://jhbmi.ir/article-1-754-en.pdf},  
journal = {Journal of Health and Biomedical Informatics},  
issn = {2423-3870}, 
eissn = {2423-3498}, 
year = {2023}  
}