Applied Health Information Technology
Volume:3 Issue: 1, Winter-Spring 2022

This study aims to outline the major phases involved in developing a mobile app for self-management of knee and lumbar osteoarthritis.

This developmental research had three phases, including, content selection, application design and development, and evaluation. First, a questionnaire was created based on the literature review, and its content validity index (CVI) and content validity ratio (CVR) were measured by 15 specialists. To approve the contents of the app, the 15 rheumatologists used the Delphi technique. The application was designed using Android programming tools after the content was selected. SQLite was also used to develop a database. Finally, 12 patients evaluated the application's usability through the questionnaire for user interaction satisfaction (QUIS).

Based on the rheumatologists' preferences for information content and format, 45 key data elements were specified in 8 sections. The application was then built, which included six primary modules: medical records, educational information, disease management, record activities, reminders, and reporting. Finally, the application's usability was praised (7.56 out of 9). The application was updated with the necessary improvements based on user feedback following the evaluation.

app evaluating is currently underway to verify the application's usability and feasibility, and its effect on osteoarthritis outcomes linked to pain control and physical activity will be investigated in future studies.

The present study aimed to compare six data mining approaches and find the best methods for predicting breast cancer.

In this study, six classification methods, including Random Forest (RF), Neural Network (NN), Support Vector Machine (SVM), Auto Multilayer Perceptron (AutoMLP), Naïve Bayes (NB), and Deep Learning (DL) were applied for breast cancer detection. Data related to 116 patients and healthy people from the UCI repository with nine predictors were used for training and testing. To develop the model, data were first divided into two parts: training and testing. The data of the training set (70%) produced the models, and the data of the test set (30%) was applied to validate the models.

To compare the performance of the techniques used to diagnose breast cancer, accuracy, recall, precision, AUC (Area Under the ROC Curve), sensitivity, and specificity were calculated and reported for all approaches. Evaluation of data mining algorithms revealed that deep learning with 81.89% accuracy performed better than other techniques. The results of one-way ANOVA for performance in six modeling methods showed no statistically significant difference between the methods (P-value <0.05).

Choosing the most effective computer diagnostic methods can provide a comprehensive system for the early detection of breast cancer. By reducing the cost of treating patients and increasing the quality of services offered, these intelligent methods take practical steps to improve medicine and lead to a systematic diagnosis.

To offer high-quality healthcare services, individuals need to utilize high-quality information. The present study aims to evaluate the data quality in the hospital information system (HIS) at a selected educational hospital.

This descriptive and cross-sectional study was conducted in 2018. The statistical population consisted of 202 users of the hospital HIS at Amir-al-momenin Hospital in Zabol.  The respondents were selected using stratified random sampling. Data were collected using a researcher-made questionnaire. Then, they were analyzed through SPSS-20 and descriptive statistics.

It was found that 45 of the respondents stated in the comprehensibility of the hospital information, while 76 considered the hospital information not very understandable. Moreover, 34.7% believed that the hospital information would be rapidly accessible when needed. The average scores of the dimensions were found to be 5-8.5, and there were significant, positive relationships between all the dimensions under the study (P-value<0.05).

Findings suggest that only a small number of staff had complete information on the HIS and associated subsystems. Other respondents lacked sufficient awareness of the HIS or were unaware of its existence. The authors suggest that the needs of users be evaluated before designing a HIS system in order to ensure that it will meet those needs. Despite the use of HIS subsystems in all the units of the hospital under study, respondents had insufficient information on how these subsystems could be used.

Health information is used for better healthcare treatment, research, insurance, employment, auditing, and accreditation. The importance of retention of health information, the complexity of regulations, and the inability of healthcare institutions to keep such records permanently, led to this study.

This scoping review explicitly refers to “retention and destruction of health information” or equivalent terms regarding relevant studies and laws, published in PubMed, Web of Science and CINAHL, SID, and websites of the Ministry of Health in countries since 2000. Data collection tool was the data collection form. It included details of the law, duration of retention, type of health information, year, and country of origin. Data analysis was conducted using comparative tables and determination of the common and different aspects of the system as a descriptive-theoretical analysis.

The study was carried out on regulations concerning the storing of hospitalization records of the usual, minor, emergency, death, and legal cases in different countries. In the countries under study, health information retention laws were updated according to the type and content of medical data, type of institution, and national conditions and laws.

The legal period of retaining medical records is determined by variables like the type of illness or injury, location of an accident, patient's legal age, the likely course of treatment in terms of patient recovery or death, type of admission, and also the effect of these factors on medical, legal and scientific needs.

This study aims to identify the challenges of pharmacy information systems (PIS) in Iran.

The present study is a systematic literature review. Initially, sources were retrieved using a search strategy and via Persian sites such as SID, Iranmedex, and Magiran, and databases like Embase, WOS, PubMed, ProQuest, and Scopus. Then, the sources related to the research were selected and examined using inclusion, and exclusion criteria, and finally, the findings were classified in the form of the challenges of the PIS.

16 studies were entered into this research. The results of evaluations displayed that the challenges of PIS included four parts: 1) documentation challenges, 2) lack of support for clinical decisions 3) standard policies and rule-related challenges, 4) challenges regarding non-compliance of designed plans to the responsibilities of a pharmacy

 Due to the main goal of the pharmacy information system regarding the increase clients' satisfaction along with cost reduction, and developing a PIS, removing challenges and problems is necessary.

This study aims to conduct a review of information technologies and telemedicine services during Covid-19 pandemic in order to identify the main challenges on the way, and provide recommendations.

A systematic review of medical informatics and telemedicine application in the 2019n-CoV period was conducted based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyzes (PRISMA) method. The original papers or proceedings in English language containing the keywords were considered eligible for this study. 323 studies from the seven databases searched (PubMed, Web of Science, Science Direct, Scopus, Google Scholar, IEEE Xplore Library, and Springer Link) were imported to a project in Covidence.com and checked for duplications. After the reviewers screened their titles and abstracts, each potentially relevant study (n=107) was assessed in full text by one reviewer. As a result, 37 papers entered the study. The selected papers were then thoroughly checked by the reviewers for the desired data.

The included studies were reviewed to extract the following information: types of technologies used in each paper, challenges and limitations faced around the world (both developed and developing countries). It also provided recommendations made by reviewed studies as solutions to the mentioned challenges.

This review unveils that there are few suitable policies and strategies simplifying technology use in managing crisis like pandemics even in countries that do not lack infrastructures or equipment. This study can present a starting point as it identifies the most utilized technologies and existing limitations on the way and offers practical recommendations to conquer them.

Clinical and pre-clinical radiotherapy data represent one of the most valuable assets for radiation therapy and oncology institutions. The present study aimed to review various clinical information systems used in the field of radiotherapy and the critical success factors influencing the system implementation.

This review study was completed in 2022. In this study, papers related to clinical information systems in the field of oncology were retrieved by using keywords. The databases and the search engine were Scopus, PubMed, Science Direct, Web of Knowledge, Ovid, Medline, and Google Scholar and the time frame was between 2010 and 2022. Initially, a total of 427 papers were retrieved, and finally, 18 related papers were selected.

The main clinical information systems used in radiotherapy included developing a patient’s electronic chart checks (two studies), establishing a web-based Integrated Radiation Oncology Information Platform, implementing a web-based Electronic Data Capture system, developing a data archiving system, developing a prototype software for the anonymization of radiation therapy treatment plans, creating a national radiation oncology registry, identifying deficiencies in treatment plans and radiotherapy simulation, creating a web-based radiotherapy system and other related studies (nine studies).

The use of clinical information systems in the field of radiotherapy is inevitable, mainly due to the wide range of benefits that these systems have. However, to implement these systems successfully, proper choice of technology, user training, application of standards, use of big data, periodic evaluations, as well as workflow identification are required for effective use of these systems.