Clinical Characteristics and Outcomes in Hospitalized Patients with COVID-19 and Cancer History: A Multicenter Cross-Sectional Study in Southwestern Iran.

Background: Cancer patients are more exposed to opportunistic infections, such as COVID-19, due to their poor health status. This study aimed to identify the clinical characteristics of cancer and non-cancer patients with COVID-19 that may lead to death, intubation, and ICU admission. Materials and Methods: A Multicenter Cross-Sectional study was conducted on confirmed COVID-19 adult patients with and without a history of cancer from March 2019 to March 2021. Demographic and clinical features, ICU admission, intubation, and discharge status have been extracted from patients' medical records. Chi-square, odds ratio, Mann-Whitney test, and logistic regression were used to analyze the data. Results: The death rate in 1332 cancer patients was 28% compared to the 91464 noncancer patients which was 9% with an odds ratio of 3.94 and p<0.001. ICU admission rates among the cancer group were 43%, while in the noncancer group, it was 17.9% (p<0.001). Moreover, intubation was done for 20.9% of cancer patients and 7.4% of non-cancer patients (p<0.001). However, no significant difference was observed between the two groups in terms of length of stay in the hospital. Multivariable logistic regression analysis showed that age, level of consciousness, SPO2, and autoimmune disorders were associated with mortality in cancer patients with COVID-19. Conclusion: This study showed that older age, loss of consciousness, low oxygen saturation, and suffering from autoimmune disorders were the predictors of death in cancer patients with COVID-19. These results can have important implications for the management and care of cancer patients with COVID-19.

Implementation of thyroid eye disease registry in Iran: rationale and research protocol.

BACKGROUND: To describe the implementation of a registry system for patients with thyroid eye disease (TED) in Iran to obtain more information about its nature, prevalence, and annual incidence, as well as extend insight into the etiology, pathogenesis, and eventually make an accurate prognosis of different medical or surgical treatment methods. METHODS: After receiving approval from the Disease Registry Committee of Iran University of Medical Sciences (IUMS) in 2019 and the Ministry of Health and Medical Education (MOHME) in 2020, the protocol was introduced in three consecutive phases at regional, provincial and national levels. The establishment of a registry committee in Rassoul Akram Hospital, one of the medical centers affiliated to IUMS, was the first step to organizing the registry project's main core. The steering committee included six subgroups of required subject fields. The members are experts in developing a guideline, providing a new dataset, drawing an outline for the next steps, and structuring user-friendly software through several panel discussion meetings. The data is collected from clinical and para-clinical/imaging findings, laboratory evaluations, and their selected treatment strategy, retrospectively and prospectively. RESULTS: The purpose is to broaden our knowledge about the profile of TED; accordingly, data related to patients' demographics, thyroid gland disease (status, duration, treatments, and function tests), general medical and ocular history, along with visual/ocular exams resulting TED status are collected and recorded in a 2- language software. The web-based software system is accessible at https://orc.iums.ac.ir . To maintain data security, prioritized user access was defined for different members. Furthermore, diverse methods, such as employing trained staff and utilizing software validation rules, were implemented to control data quality in every step of data collection, entry, and registration. Medical records of retrospective subjects were also evaluated and entered after accuracy verification. CONCLUSION: Iran's TED registry provides practitioners with comprehensive data on natural history and phenotype variations in clinical features and outcomes. It facilitates patient recruitment and, consequently, earlier diagnosis on a large scale which helps improve treatment and quality of life for patients.

Patients' perspectives and preferences toward telemedicine versus in-person visits: a mixed-methods study on 1226 patients.

INTRODUCTION: Despite the fact that telemedicine can eliminate geographical and time limitations and offer the possibility of diagnosing, treating, and preventing diseases by sharing reliable information, many individuals still prefer to visit medical centers for in-person consultations. The aim of this study was to determine the level of acceptance of telemedicine compared to in-person visits, identify the perceived advantages of telemedicine over in-person visits, and to explore the reasons why patients choose either of these two types of visits. METHODS: We developed a questionnaire using the rational method. The questionnaire consisted of multiple-choice questions and one open-ended question. A total of 2059 patients were invited to participate in the study. Chi-square tests and descriptive statistics were employed for data analysis. To analyze the data from the open-ended question, we conducted qualitative content analysis using MAXQDA 18. RESULTS: Out of the 1226 participants who completed the questionnaire, 865 (71%) preferred in-person visits, while 361 (29%) preferred telemedicine. Factors such as education level, specific health conditions, and prior experience with telemedicine influenced the preference for telemedicine. The participants provided a total of 183 different reasons for choosing either telemedicine (108 reasons) or in-person visits (75 reasons). Avoiding infectious diseases, saving cost, and eliminating and overcoming geographical distance barriers were three primary telemedicine benefits. The primary reasons for selecting an in-person visit were: more accurate diagnosis of the disease, more accurate and better examination of the patient by the physician, and more accurate and better treatment of the disease. CONCLUSION: The results demonstrate that despite the numerous benefits offered by telemedicine, the majority of patients still exhibit a preference for in-person visits. In order to promote broader acceptance of telemedicine, it becomes crucial for telemedicine services to address patient preferences and concerns effectively. Employing effective change management strategies can aid in overcoming resistance and facilitating the widespread adoption of telemedicine within the population.

Patient safety classifications, taxonomies and ontologies, part 2: A systematic review on content coverage.

BACKGROUND: Content coverage of patient safety ontology and classification systems should be evaluated to provide a guide for users to select appropriate ones for specific applications. In this review, we identified and compare content coverage of patient safety classifications and ontologies. METHODS: We searched different databases and ontology/classification repositories to identify these classifications and ontologies. We included patient safety-related taxonomies, ontologies, classifications, and terminologies. We identified and extracted different concepts covered by these systems and mapped these concepts to international classification for patient safety (ICPS) and finally compared the content of these systems. RESULTS: Finally, 89 papers (77 classifications or ontologies) were analyzed. Thirteen classifications have been developed to cover all medical domains. Among specific domain systems, most systems cover medication (16), surgery (8), medical devices (3), general practice (3), and primary care (3). The most common patient safety-related concepts covered in these systems include incident types (41), contributing factors/hazards (31), patient outcomes (29), degree of harm (25), and action (18). However, stage/phase (6), incident characteristics (5), detection (5), people involved (5), organizational outcomes (4), error type (4), and care setting (3) are some of the less covered concepts in these classifications/ontologies. CONCLUSION: Among general systems, ICPS, World Health Organization's Adverse Reaction Terminology (WHO-ART), and Ontology of Adverse Events (OAE) cover most patient safety concepts and can be used as a gold standard for all medical domains. As a result, reporting systems could make use of these broad classifications, but the majority of their covered concepts are related to patient outcomes, with the exception of ICPS, which covers other patient safety concepts. However, the ICPS does not cover specialized domain concepts. For specific medical domains, MedDRA, NCC MERP, OPAE, ADRO, PPST, OCCME, TRTE, TSAHI, and PSIC-PC provide the broadest coverage of concepts. Many of the patient safety classifications and ontologies are not formally registered or available as formal classification/ontology in ontology repositories such as BioPortal. This study may be used as a guide for choosing appropriate classifications for various applications or expanding less developed patient safety classifications/ontologies. Furthermore, the same concepts are not represented by the same terms; therefore, the current study could be used to guide a harmonization process for existing or future patient safety classifications/ontologies.

Machine learning models to detect and predict patient safety events using electronic health records: A systematic review.

INTRODUCTION: Identifying patient safety events using electronic health records (EHRs) and automated machine learning-based detection methods can help improve the efficiency and quality of healthcare service provision. OBJECTIVE: This study aimed to systematically review machine learning-based methods and techniques, as well as their results for patient safety event management using EHRs. METHODS: We reviewed the studies that focused on machine learning techniques, including automatic prediction and detection of patient safety events and medical errors through EHR analysis to manage patient safety events. The data were collected by searching Scopus, PubMed (Medline), Web of Science, EMBASE, and IEEE Xplore databases. RESULTS: After screening, 41 papers were reviewed. Support vector machine (SVM), random forest, conditional random field (CRF), and bidirectional long short-term memory with conditional random field (BiLSTM-CRF) algorithms were mostly applied to predict, identify, and classify patient safety events using EHRs; however, they had different performances. BiLSTM-CRF was employed in most of the studies to extract and identify concepts, e.g., adverse drug events (ADEs) and adverse drug reactions (ADRs), as well as relationships between drug and severity, drug and ADEs, drug and ADRs. Recurrent neural networks (RNN) and BiLSTM-CRF had the best results in detecting ADEs compared to other patient safety events. Linear classifiers and Naive Bayes (NB) had the highest performance for ADR detection. Logistic regression had the best results in detecting surgical site infections. According to the findings, the quality of articles has non-significantly improved in recent years, but they had low average scores. CONCLUSIONS: Machine learning can be useful in automatic detection and prediction of patient safety events. However, most of these algorithms have not yet been externally validated or prospectively tested. Therefore, further studies are required to improve the performance of these automated systems.

Using Electronic Health Record System to Establish a National Patient's Registry : Lessons learned from the Cancer Registry in Iran.

BACKGROUND: In Iran, the Integrated Electronic Health Record system, called SEPAS, has been established to store all patient encounters of individuals referring to healthcare facilities. OBJECTIVE: We aimed to develop a model for cleaning SEPAS and applying its data in other databases. METHODS: We used cancer data from SEPAS as the sample. We developed a guideline to identify codes for cancer-related diagnoses and services in the database. Furthermore, we searched the SEPAS database based on ICD-10 and the diagnosis description in English and Farsi in an Excel sheet. We added codes and descriptions of pharmaceuticals and procedures to the list. We applied the above database and linked it to the patient records to identify cancer patients. A dashboard was designed based on this information for every cancer patient. RESULTS: We selected 5,841 diagnostic codes and phrases, 9,300 cancer pharmaceutics codes, and 452 codes from cancer-specific items related to the diagnostic procedures and treatment methods. Linkage of this list to the patient list generated a database of about 197,164 cancer patients for linkage in the registry database. CONCLUSIONS: Patient registries are one of the most important sources of information in healthcare systems. Data linkage between Electronic Health Record Systems (EHRs) and registries, despite its challenges, is profitable. EHRs can be used for case finding in any patient registry to reduce the time and cost of case finding.

Effect of a sensory diet smartphone application on the symptoms of children with attention deficit hyperactivity disorder (ADHD): A feasibility study.

Introduction: Sensory integration and sensory diet can improve the symptoms of children with attention deficit/hyperactivity disorder (ADHD). This feasibility study aimed to evaluate the effect of using a sensory diet smartphone application by mothers on the main symptoms of their children with ADHD, including hyperactivity, attention deficit, and impulsivity. Methods: We conducted a need assessment study with the collaboration of 15 occupational therapists, developed an Android-based prototype, and evaluated it in terms of usability with the participation of 12 available mothers of children with ADHD. 12 other selected children were divided into control and experimental groups. At first, these children were evaluated using the hyperactivity subscale of the fourth version of the Pediatric Symptoms Questionnaire, and after two months of using the application by the mothers of the children in the experimental group, both groups were re-evaluated using the same questionnaire. We compared the mean score of this questionnaire before and after the mothers' use of the application. Results: The application included 105 sensory diet exercises presented in animated format with accompanying text explanations. According to mothers' feedback, the usability of the application was rated at a high level with an average score of 8.35 out of 9. In the experimental group, attention deficit significantly improved compared to the pre-intervention stage (Mean ± SD = 13.67 ± 6.86 vs. 22 ± 6.13, P-value<0.0001) and compared to the control group after the intervention (P-value = 0.048). Additionally, after the intervention, the experimental group showed significant improvements in impulsivity (mean difference = -1.33) and hyperactivity (mean difference = -4.67) compared to the pre-intervention (P-value = 0.025 and 0.034, respectively). However, these improvements were not statistically significant when compared to the control group (P-value = 0.937 and 0.58, respectively). Conclusion: The findings suggest that sensory diet smartphone applications have the potential to help alleviate symptoms related to attention deficit in children with ADHD.

A health terminological system for inherited retinal diseases: Content coverage evaluation and a proposed classification.

PURPOSE: To present a classification of inherited retinal diseases (IRDs) and evaluate its content coverage in comparison with common standard terminology systems. METHODS: In this comparative cross-sectional study, a panel of subject matter experts annotated a list of IRDs based on a comprehensive review of the literature. Then, they leveraged clinical terminologies from various reference sets including Unified Medical Language System (UMLS), Online Mendelian Inheritance in Man (OMIM), International Classification of Diseases (ICD-11), Systematized Nomenclature of Medicine (SNOMED-CT) and Orphanet Rare Disease Ontology (ORDO). RESULTS: Initially, we generated a hierarchical classification of 62 IRD diagnosis concepts in six categories. Subsequently, the classification was extended to 164 IRD diagnoses after adding concepts from various standard terminologies. Finally, 158 concepts were selected to be classified into six categories and genetic subtypes of 412 cases were added to the related concepts. UMLS has the greatest content coverage of 90.51% followed respectively by SNOMED-CT (83.54%), ORDO (81.01%), OMIM (60.76%), and ICD-11 (60.13%). There were 53 IRD concepts (33.54%) that were covered by all five investigated systems. However, 2.53% of the IRD concepts in our classification were not covered by any of the standard terminologies. CONCLUSIONS: This comprehensive classification system was established to organize IRD diseases based on phenotypic and genotypic specifications. It could potentially be used for IRD clinical documentation purposes and could also be considered a preliminary step forward to developing a more robust standard ontology for IRDs or updating available standard terminologies. In comparison, the greatest content coverage of our proposed classification was related to the UMLS Metathesaurus.

A data set for the design and implementation of the upper limb disability registry.

BACKGROUND: If the data elements needed for patient registries are not identified, designing and implementing them can be very challenging. Identifying and introducing a Data Set (DS) can help solve this challenge. The aim of this study was to identify and present a DS for the design and implementation of the upper limb disability registry. MATERIALS AND METHODS: This cross-sectional study was conducted in two phases. In the first phase, to identify the administrative and clinical data elements required for registry, a comprehensive study was conducted in PubMed, Web of Science, and Scopus databases. Then, the necessary data elements were extracted from the studies and a questionnaire was designed based on them. In the second phase, in order to confirm the DS, the questionnaire was distributed to 20 orthopedic, physical medicine and rehabilitation physicians and physiotherapists during a two-round Delphi. In order to analyze the data, the frequency and mean score of each data element were calculated. Data elements that received an agreement more than 75% in the first or two-round Delphi were considered for the final DS. RESULTS: A total of 81 data elements in five categories of "demographic data", "clinical presentation", "past medical history", "psychological issues", and "pharmacological and non-pharmacological treatments" were extracted from the studies. Finally, 78 data elements were approved by experts as essential data elements for designing a patient registry for upper limb disabilities. CONCLUSION: In this study, the data elements necessary for the design and implementation of the upper limb disability registry were suggested. This DS can help registry designers and health data administrators know what data needs to be included in the registry system in order to have a successful design and implementation. Moreover, this standardized DS can be effective for integrating and improving the information management of people with upper limb disabilities and used to accurately gather the upper limb disabilities data for research and policymaking purposes.

Comparison of the accuracy of inpatient morbidity coding with ICD-11 and ICD-10.

BACKGROUND: One of the challenges when transitioning from International Statistical Classification of Diseases and Related Health Problems, 10th Revision (ICD-10) to International Classification of Diseases, 11th Revision (ICD-11) is to ensure clinical coding accuracy. OBJECTIVE: To determine the accuracy of clinical coding with ICD-11 in comparison with ICD-10 and identify causes of coding errors in real clinical coding environments. METHOD: The study was conducted prospectively in two general hospitals. Medical records of discharged inpatients were coded by hospital clinical coders with both ICD-11 and ICD-10 on different days. These medical records were recoded by five mentors. Codes assigned by mentors were used as the gold standard for the evaluation of accuracy. RESULTS: The accuracy of ICD-10 and ICD-11 coding for 1578 and 2168 codes was evaluated. Coding accuracy was 89.1% and 74.2% for ICD-10 and ICD-11. In ICD-11, the lowest accuracy was observed in chapters 22 (injuries), 10 (ear) and 11 (circulatory) (51.1%, 53.8% and 62.7%, respectively). In both ICD-10 and ICD-11, the most important cause of the coding errors was clinical coders' mistakes (79.5% and 81.8% for ICD-10 and ICD-11, respectively). CONCLUSION: Accuracy of clinical coding with ICD-11 was lower relative to ICD-10. Hence, it is essential to carry out initial preparations, particularly the training of clinical coders based on their needs, as well as the necessary interventions to enhance the documentation of medical records according to ICD-11 before or simultaneous with the country-wide implementation. IMPLICATIONS: Clinical coders need complete training, especially in using extension codes and post-coordination coding. Local ICD-11 guidelines based on the needs of local users and reporting policies should be developed. Furthermore, documentation guidelines based on ICD-11 requirements should be developed.

Machine learning-based mortality prediction models for smoker COVID-19 patients.

BACKGROUND: The large number of SARS-Cov-2 cases during the COVID-19 global pandemic has burdened healthcare systems and created a shortage of resources and services. In recent years, mortality prediction models have shown a potential in alleviating this issue; however, these models are susceptible to biases in specific subpopulations with different risks of mortality, such as patients with prior history of smoking. The current study aims to develop a machine learning-based mortality prediction model for COVID-19 patients that have a history of smoking in the Iranian population. METHODS: A retrospective study was conducted across six medical centers between 18 and 2020 and 15 March 2022, comprised of 678 CT scans and laboratory-confirmed COVID-19 patients that had a history of smoking. Multiple machine learning models were developed using 10-fold cross-validation. The target variable was in-hospital mortality and input features included patient demographics, levels of care, vital signs, medications, and comorbidities. Two sets of models were developed for at-admission and post-admission predictions. Subsequently, the top five prediction models were selected from at-admission models and post-admission models and their probabilities were calibrated. RESULTS: The in-hospital mortality rate for smoker COVID-19 patients was 20.1%. For "at admission" models, the best-calibrated model was XGBoost which yielded an accuracy of 87.5% and F1 score of 86.2%. For the "post-admission" models, XGBoost also outperformed the rest with an accuracy of 90.5% and F1 score of 89.9%. Active smoking was among the most important features in patients' mortality prediction. CONCLUSION: Our machine learning-based mortality prediction models have the potential to be adapted for improving the management of smoker COVID-19 patients and predicting patients' chance of survival.

Establishment of Iran Musculoskeletal Tumor Registry: A Study Protocol and Lessons Learned from Implementation and the Pilot Phase.

Background: The number of available musculoskeletal tumor registries is relatively small. We developed a registry system focused on the clinical aspects of musculoskeletal tumors to improve quality of care indexes through the development of updated national protocols. In this study, we describe our protocol, challenges, and the data collected during the implementation of the registry system in a single-specialty orthopedic center in Iran. Methods: Three main malignant bone tumors, including osteosarcoma, Ewing sarcoma, and chondrosarcoma, were included in the registry. After establishing a steering committee, we defined the minimum data set based on a literature review and suggestions from an expert panel. Accordingly, the data collection forms and the web-based software were developed. The collected information was categorized into 9 classes, including demographics, socioeconomic data, signs and symptoms, past medical history, family history, laboratory tests, tumor characteristics, primary treatment, and follow-up. Data collection was performed both retrospectively and prospectively. Results: Until September 21, 2022, a total of 71 patients were registered (21 patients prospectively and 50 patients retrospectively) and consisted of 36 (50.7%) cases of osteosarcoma, 13 (18.3%) cases of Ewing sarcoma, and 22 (31%) cases of chondrosarcoma. The implementation of the registry demonstrated promising data regarding the tumor characteristics, delay patterns, and socioeconomic status of the patients. Conclusion: The main lessons learned were to develop a monitoring system to make sure that the new staff is adequately trained for the registration process as well as avoid the inclusion of time-consuming useless data in the minimum data set.

Overview of the role of robots in upper limb disabilities rehabilitation: a scoping review.

BACKGROUND: Neuromotor rehabilitation and improvement of upper limb functions are necessary to improve the life quality of patients who have experienced injuries or have pathological outcomes. Modern approaches, such as robotic-assisted rehabilitation can help to improve rehabilitation processes and thus improve upper limb functions. Therefore, the aim of this study was to investigate the role of robots in upper limb disability improvement and rehabilitation. METHODS: This scoping review was conducted by search in PubMed, Web of Science, Scopus, and IEEE (January 2012- February 2022). Articles related to upper limb rehabilitation robots were selected. The methodological quality of all the included studies will be appraised using the Mixed Methods Appraisal Tool (MMAT). We used an 18-field data extraction form to extract data from articles and extracted the information such as study year, country, type of study, purpose, illness or accident leading to disability, level of disability, assistive technologies, number of participants in the study, sex, age, rehabilitated part of the upper limb using a robot, duration and frequency of treatment, methods of performing rehabilitation exercises, type of evaluation, number of participants in the evaluation process, duration of intervention, study outcomes, and study conclusions. The selection of articles and data extraction was made by three authors based on inclusion and exclusion criteria. Disagreements were resolved through consultation with the fifth author. Inclusion criteria were articles involving upper limb rehabilitation robots, articles about upper limb disability caused by any illness or injury, and articles published in English. Also, articles involving other than upper limb rehabilitation robots, robots related to rehabilitation of diseases other than upper limb, systematic reviews, reviews, and meta-analyses, books, book chapters, letters to the editor, and conference papers were also excluded. Descriptive statistics methods (frequency and percentage) were used to analyses the data. RESULTS: We finally included 55 relevant articles. Most of the studies were done in Italy (33.82%). Most robots were used to rehabilitate stroke patients (80%). About 60.52% of the studies used games and virtual reality rehabilitate the upper limb disabilities using robots. Among the 14 types of applied evaluation methods, "evaluation and measurement of upper limb function and dexterity" was the most applied evaluation method. "Improvement in musculoskeletal functions", "no adverse effect on patients", and "Safe and reliable treatment" were the most cited outcomes, respectively. CONCLUSIONS: Our findings show that robots can improve musculoskeletal functions (musculoskeletal strength, sensation, perception, vibration, muscle coordination, less spasticity, flexibility, and range of motion) and empower people by providing a variety of rehabilitation capabilities.

An analysis of clinical outcomes and essential parameters for designing effective games for upper limb rehabilitation: A scoping review.

Background and Aims: Upper limb disabilities are one of the most common disabilities among different groups of people who always need rehabilitation. One of the important methods in helping to carry out efficient rehabilitation processes and exercises is the use of games. The aim of this study is to identify the parameters necessary to design a successful rehabilitation game and the outcomes of using these games in upper limb disabilities rehabilitation. Methods: This scoping review was conducted by searching the Web of Science, PubMed, and Scopus. The eligibility criteria were: any form of game-based upper limb rehabilitation, published in a peer-reviewed journal, published in English, and not include articles that did not focus upper limb disabilities rehabilitation games, review, meta-analysis, or conference papers. Analysis of collected data was done using descriptive statistics (frequency and percentage). Results: The search strategy retrieved 537 relevant articles. Finally, after removing irrelevant and repetitive articles, 21 articles were included in this study. Among the six categories of diseases or complications of upper limb disabilities, games were mostly designed for stroke patients. Smart wearables, robots and telerehabilitation were three technologies that were used for rehabilitation along with games. Sports and shooters were the most used games for upper limb disability rehabilitation. Among 99 necessary parameters for designing and implementing a successful rehabilitation game in ten categories. "Increasing the patient's motivation to perform rehabilitation exercises", "Game difficulty levels", "Enjoying and the attractiveness of the game for patients", and "Providing positive or negative audiovisual feedback" were the most important parameters. "Improvement in musculoskeletal performance" and "Increasing users' enjoyment/joy of therapeutic exercises and their motivation to perform these exercises" were the most important positive outcomes, and "Mild discomfort such as nausea and dizziness when using games" was the only negative outcome. Conclusions: The successful design of a game according to the parameters identified in the present study can lead to an increase in the positive outcomes of using games in the rehabilitation of disabilities. The study results indicate that upper limb therapeutic exercise augmented with virtual reality games may be highly effective in enhancing motor rehabilitation outcomes.

A case-based reasoning system for neonatal survival and LOS prediction in neonatal intensive care units: a development and validation study.

Early prediction of neonates' survival and Length of Stay (LOS) in Neonatal Intensive Care Units (NICU) is effective in decision-making. We developed an intelligent system to predict neonatal survival and LOS using the "Case-Based Reasoning" (CBR) method. We developed a web-based CBR system based on K-Nearest Neighborhood (KNN) on 1682 neonates and 17 variables for mortality and 13 variables for LOS and evaluated the system with 336 retrospectively collected data. We implemented the system in a NICU to externally validate the system and evaluate the system prediction acceptability and usability. Our internal validation on the balanced case base showed high accuracy (97.02%), and F-score (0.984) for survival prediction. The root Mean Square Error (RMSE) for LOS was 4.78 days. External validation on the balanced case base indicated high accuracy (98.91%), and F-score (0.993) to predict survival. RMSE for LOS was 3.27 days. Usability evaluation showed that more than half of the issues identified were related to appearance and rated as a low priority to be fixed. Acceptability assessment showed a high acceptance and confidence in responses. The usability score (80.71) indicated high system usability for neonatologists. This system is available at http://neonatalcdss.ir/ . Positive results of our system in terms of performance, acceptability, and usability indicated this system can be used to improve neonatal care.

Effect of picture archiving and communication system on diagnosis accuracy in CT and radiography examinations in emergency departments.

INTRODUCTION: Picture archiving and communication system (PACS) affects the radiologists' and physicians' performance. We aimed to evaluate the effect of implementing PACS on the emergency department (ED) physicians' accuracy compared to a radiologist's diagnosis in Iran. METHODS: We retrospectively collected data for three six-month periods before and after the implementation of PACS on CT scan and radiography examinations. We compared ED physicians' diagnoses of CT scan and radiography images with a radiologist's interpretations for the same images. We compared 374 CT scans and 346 radiography examinations before implementing PACS (July 2015 to December 2015); 507 CT scans and 480 radiography examinations immediately after PACS (July 2016 to December 2016); and 870 CT scans and 1137 radiography examinations one year after PACS (July 2017 to December 2017). RESULTS: We found that diagnosis accuracy of ED physicians on CT scans increased from 75.9 % before implementing PACS to 84.4 % immediately after PACS and 94.9 % one year after PACS (p-value < 0.0001). Diagnosis accuracy for radiography images increased from 63.0 % before implementing PACS to 80.2 % immediately after PACS and 93.1 % one year after PACS (p-value < 0.0001). CONCLUSION: Implementation of PACS technology increases ED physicians' diagnosis accuracy.

Identification of root causes of clinical coding problems in Iranian hospitals.

BACKGROUND: Improving the quality of coded data requires the identification and evaluation of the root causes of clinical coding problems to inform appropriate solutions. OBJECTIVE: The objective of this study was to identify the root causes of clinical coding problems. METHOD: Twenty-one clinical coders from three cities in Iran were interviewed. The five formal categories in Ishikawa's cause-and-effect diagram were applied as pre-determined themes for the data analysis. RESULTS: The study indicated 16 root causes of clinical coding problems in the five main themes: (i) policies, protocols, and processes (lack of clinical documentation guidelines; lack of audit of clinical coding and feedback to clinical coders; the long interval between documentation and clinical coding; and not using coded data for reimbursement; (ii) individual factors (shortage of clinical coders; low-skilled clinical coders; clinical coders' insufficient communication with physicians; and the lack of continuing education; (iii) equipment and materials (incomplete medical records; lack of access to electronic medical records and electronic coding support tools; (iv) working environment (lack of an appropriate, dynamic, and motivational workspace; and (v) management factors (mangers' inattention to the importance of coding and clinical documentation; and to providing the required staff support. CONCLUSION: The study identified 16 root causes of clinical coding problems that stand in the way of clinical coding quality improvement. IMPLICATIONS: The quality of clinical coding could be improved by hospital managers and health policymakers taking these problems into account to develop strategies and implement solutions that target the root causes of clinical coding problems.

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.

A competency framework for Ph.D. programs in health information management.

INTRODUCTION: The job expectations and professional competencies required by health information management (HIM) students/graduates are constantly changing and workforce development requires curricula in line with new emerging competencies. Although there are some competency frameworks in this field, there is no one specifically for Ph.D. educational programs in HIM. We aimed to develop a competency framework for Ph.D. programs in HIM in Iran. METHODS: We firstly developed a list of competencies based on those published in the literature or by related associations in nine domains and 51 sub-domains. We used the modified Delphi technique and invited Ph.D. students/graduates in HIM and related faculty members throughout the country to participate. Competencies with more than 75% agreement were considered as high priority competencies and those with 50% to 75% agreement as a medium priority. Competencies with less than 50% agreement were dropped. After two rounds, the competency framework was finalized. RESULTS: All suggested competencies were considered a high priority in the first round. Based on suggestions, two new domains (health knowledge management and information technology) and 20 new sub-competencies were added and then accepted in the second round. The final framework includes these competency domains: health data and information management; health data analytics; information technology; teaching competencies; research competencies; health information technology and digital health; health information classifications, terminologies, and ontologies; health information systems governance; managerial competencies; health knowledge management; and digital health entrepreneurship. CONCLUSION: This framework suggests a list of competencies in 11 domains and 71 sub-domains for Ph.D. students/graduates in HIM that should be considered for the development of future curricula for these educational programs.

Telerehabilitation for upper limb disabilities: a scoping review on functions, outcomes, and evaluation methods.

BACKGROUND: Upper limb (UL) disabilities have attracted worldwide attention due to the high economic costs of health care and the negative effects on the quality of life of patients with these disabilities. Telerehabilitation technologies are one of the most important ways to reduce rehabilitation costs and increase the quality of life of patients. Therefore, the aim of this study was to investigate the role of telerehabilitation in improving the health status of patients with upper limb disabilities. METHODS: This scoping review was conducted by searching the Web of Science, PubMed, and Scopus until July 30, 2021. We used a data extraction form with 18 fields to extract data from primary studies. The selection of articles and data extraction was made by four researchers using a data collection form based on inclusion and exclusion criteria. Disagreements were resolved through consultation with the fifth and sixth researchers.Inclusion criteria were studies published in English, studies on upper limb disability, and telerehabilitation based on any technology (synchronous telerehabilitation, asynchronous, or both). Exclusion criteria were articles that did not focus on telerehabilitation and upper limb disabilities. Also, books, book chapters, letters to the editor, and conference abstracts were also removed. RESULTS: A total of 458 articles were retrieved, and after removing irrelevant and duplicate articles, 29 articles were finally included in this review. Most telerehabilitation was performed for patients with stroke (65%). Among the 15 different services provided with telerehabilitation technologies, "Evaluation of exercises and also a musculoskeletal function of patients by the therapist","Recording of patients' rehabilitation exercises and sending them to the therapist" and "Prescribing new rehabilitation exercises by the therapist" were the most widely used services, respectively. Virtual reality technologies, smart wearables, and robots were used to provide telerehabilitation services. Among the 13 types of evaluation used for telerehabilitation systems, "Evaluation and measurement of upper limb function" was the most used evaluation in the studies. "Improvement in musculoskeletal functions", "Increasing patients' interest and motivation to perform rehabilitation exercises", and "Increasing adherence to rehabilitation exercises and greater participation in treatment processes" were the most important outcomes, respectively. CONCLUSION: Our findings indicate that telerehabilitation provides individuals with equitable access to rehabilitation services, improves musculoskeletal function, and empowers individuals by providing a variety of rehabilitation capabilities.