Obstructive Sleep Apnea Home-Monitoring Using a Commercial Wearable Device.

Obstructive sleep apnea (OSA) is a common sleep disorder and polysomnography (PSG) is the gold standard for its diagnosis and treatment monitoring. There are nowadays several activity trackers measuring sleep quality through the detection of sleep stages. To allow an easier monitoring of the treatment efficacy at home, this work explores the possibility of using one of those commercial smart-bands. To this aim, we studied the signals provided by PSG and a Fitbit smart-band on 26 consecutive patients, admitted to the hospital after the diagnosis of OSA, and submitted to ventilation or positional treatment. They underwent monitoring for three nights (basal, titration, and control). We developed both a visualization software allowing doctors to visually compare the two hypnograms, and a set of statistics for assessing the concordance of the two methods. Results indicate that Fitbit can detect normal sleep patterns, while it is less able to detect the abnormal ones.

Development and validation of the Neonatal Abstinence Syndrome Minimum Data Set (NAS-MDS): a systematic review, focus group discussion, and Delphi technique.

OBJECTIVES: Neonatal abstinence syndrome (NAS) is a combination of symptoms in infants exposed to any variety of substances in utero. Information systems and registries help to collect information about these patients; however, there is always a deep gap between complete and accurate information to be collected, understood, and applied in the health care system; thus, defining a minimum data sets (MDS) as one of the primarily steps of designing a registry system is essential. The aim of this study was to develop an MDS of the registry for infants with NAS in Iran. METHODS: This research is a descriptive cross-sectional study. In this study, three steps were carried out to develop the MDS including systematic review, Delphi technique, and focus group discussion. A systematic review was conducted in relevant databases to identify appropriate related data. In the second phase, a focus group discussion was used to classify the extracted data elements by contributing neonatologists. Finally, data elements were chosen through the decision Delphi technique in two distinct rounds. Collected data were analyzed using SPSS 22 (SPSS Inc., Chicago, IL). RESULTS: By reviewing related papers and available NAS registries in other countries, 145 essential data elements were identified. They were classified into two main categories based on the eight experts' opinions including maternal with two sections and infant with two sections. After applying two rounds of Delphi technique, the final data elements for maternal and infant categories were 42 and 31, respectively. Thus, on completion of the survey, 73 data elements were approved. CONCLUSION: The proposed MDS for NAS can help to store an accurate and comprehensive data, document medical records, integrate them with other information systems and registries, and communicate with other healthcare providers and healthcare centers. This MDS can contribute to the provision of high-quality care and better clinical decisions.

Development and evaluation of a gamified smart phone mobile health application for oral health promotion in early childhood: a randomized controlled trial.

BACKGROUND: This study aimed to design a gamified smartphone application (app) and assess its efficacy for education of mothers regarding oral healthcare of their children. METHODS: In this pretest-posttest controlled clinical trial, a simple app and a gamified version of it were designed to enhance the oral health knowledge and practice of mothers. The app contains information about early childhood caries, health diet, sugars, baby-oral hygiene, fluoride effect, fluoride toothpaste, tooth-brushing training video and regular dental visits. The opinion of experts and 3 mothers were obtained and both apps were revised accordingly. The intervention was implemented on mothers of preschoolers referring to the specialty dental clinic of Tehran School of Dentistry in 2019. The mothers were randomly allocated to the simple app or gamified app group. Before the intervention, all mothers filled out a questionnaire regarding oral health knowledge and practice, and their demographics were collected. The plaque index (PI) of children was also measured. The mothers filled out the same questionnaire 1 month after the intervention, and the PI of children was measured again. Paired t test and linear regression model were used for statistical analysis of the data. RESULTS: Totally, 58 mother and child pairs entered the study; 40% of children were boys. The mean age of children was 4.7 ± 1.2 years. The mean knowledge score of mothers in the pretest was 10.5 and 11.3 in simple app and gamified app group, respectively, which changed to 13.1 and 14.3, respectively in the posttest. The mean practice score of mothers was 4.4 and 4.8 in simple app and gamified app groups, respectively in the pretest, which changed to 8.5 and 8, respectively in the posttest. The mean dental plaque index of children in the pretest was 0.8 and 1 in simple app and gamified app groups, respectively, which changed to 0.5 and 0.5, respectively in the posttest. Children had better Plaque control in gamified app group (P < 0.05). CONCLUSION: After 1 month, both apps effectively improved the oral-health knowledge and practice of mothers while oral hygiene as a result of plaque control was superior in children of mothers using the gamified app. Trial registration IRCT, IRCT20131102015238N2. Registered 24 February 2019-Retrospectively registered, https://fa.irct.ir/trial/36600 .

The necessity to develop a national classification system for Iranian traditional medicine.

BACKGROUND: Classification of disease and interventions in traditional medicine (TM) is necessary for standardised coding of information. Currently, in Iran, there is no standard electronic classification system for disease and interventions in TM. OBJECTIVE: The current study aimed to develop a national framework for the classification of disease and intervention in Persian medicine based on expert opinion. METHOD: A descriptive cross-sectional study was carried out in 2018. The existing systems for the classification of disease and interventions in TM were reviewed in detail, and some of the structural and content characteristics were extracted for the development of the classification of Iranian traditional medicine. Based on these features, a self-administered questionnaire was developed. Study participants (25) were experts in the field of Persian medicine and health information management in Tehran medical universities. RESULTS: Main axes for the classification of disease and interventions were determined. The most important applications of the classification system were related to clinical coding, policymaking, reporting of mortality and morbidity data, cost analysis and determining the quality indicators. Half of the participants (50%) stated that the classification system should be designed by maintaining the main axis of the World Health Organization classification system and changing the subgroups if necessary. A computer-assisted coding system for TM was proposed for the current study. CONCLUSION: Development of this classification system will provide nationally comparable data that can be widely used by governments, national organisations and academic researchers.

Neonatal abstinence syndrome: a systematic review of current databases and registries.

OBJECTIVES: Registries are considered as rich sources of data for determination of infants with neonatal abstinence syndrome (NAS), the improvement of provided care and research. The aims of this study were: (1) to investigate the existing studies including NAS registries, (2) to identify and extract the required data elements. METHODS: The following electronic databases were searched: PubMed, Scopus, Web of Science, ProQuest, Embase/Medline, and Psych Info. In addition, a review of gray literature was undertaken to identify relevant studies in English covering the period from 1 January 2009 to 1 November 2018 including registries and databases. Screening of titles, abstracts, and full-texts were conducted independently by two researchers based on PRISMA guidelines. The basic registry information, scope, registry type, data source, the purpose of registry, important variables were extracted and analyzed. RESULTS: Twenty-five articles were eligible and included in the review; they reported 37 registries and databases related to NAS at the national and state levels in 11 countries from 1876 to 2013. We proposed a NAS registry design framework based on well-known data-information-knowledge (DIK) structure due to Ackoff's DIK hierarchy has a defined role as a central model of information systems, information management, and knowledge management. CONCLUSIONS: To the best of our knowledge, this is the first study which has systematically reviewed NAS-related registries. Since there are no international standards to develop new NAS registries, the proposed framework in this article can be beneficial. This framework is essential not only to facilitate the NAS registry design but also to help the collection of high-value clinical data necessary for the acquisition of better clinical knowledge.

ART Registries-Characteristics and experiences: A comparative study.

BACKGROUND: The incident of infertility is continuously increasing. As a result, the demand for medical care such as assisted reproductive technology (ART) technology is equally increasing. In order to manage the growing data and information collected on ART, there is a need for a registry system can provide accurate statistics about activities and outcomes and ensure the quality control. Therefore, the aim of this study was to examine and compare In vitro fertilization (IVF) and ART registries. METHODS: This is a descriptive-comparative study in which data from the national ART registries of 14 selected countries in 2018 were collected. In this study, databases such as PubMed, Web of Sciences, and Scopus, as well as Google Scholar websites were searched. RESULTS: Important aspects of the registry were studied. One of the most important goals of these systems is to collect information about ART, as well as to monitor and report the results and implications, and also implement new care plans. CONCLUSION: A national registry helps to better understand the scope and the effect of assisted reproduction on the health of infertile couples. By this registry system, different countries can compare the data with other countries, allowing the improvement of techniques and the best possible care for patients.

A systematic literature review and classification of knowledge discovery in traditional medicine.

INTRODUCTION AND OBJECTIVE: Despite the importance of machine learning methods application in traditional medicine there is a no systematic literature review and a classification for this field. This is the first comprehensive literature review of the application of data mining methods in traditional medicine. METHOD: We reviewed 5 database between 2000 to 2017 based on the Kitchenham systematic review methodology. 502 articles were identified and reviewed for their relevance to application of machine learning methods in traditional medicine, 42 selected papers were classified and categorized on four dimension; 1) application domain of data mining techniques in traditional medicine; 2) the data mining methods most frequently used in traditional medicine; 3) main strength and limitation of data mining techniques in traditional medicine; 4) the performance evaluation methods in data mining methods in traditional medicine. RESULT: The result obtained showed that main application domain of data mining techniques in traditional medicine was related to syndrome differentiation. Bayesian Networks (BNs), Artificial Neural Networks (ANNs) and Support Vector Machines (SVMs) were recognized as being the methods most frequently applied in traditional medicine. Furthermore, each data mining techniques has its own strength and limitations when applied in traditional medicine. Single scaler methods were frequently used for performance evaluation of data mining methods. CONCLUSION: Machine learning methods have become an important research field in traditional medicine. Our research provides information about this methods by examining the related articles.

Designing and Implementation of a Heart Failure Telemonitoring System.

INTRODUCTION: The aim of this study was to identify patients at-risk, enhancing self-care management of HF patients at home and reduce the disease exacerbations and readmissions. METHOD: In this research according to standard heart failure guidelines and Semi-structured interviews with 10 heart failure Specialists, a draft heart failure rule set for alerts and patient instructions was developed. Eventually, the clinical champion of the project vetted the rule set. Also we designed a transactional system to enhance monitoring and follow up of CHF patients. With this system, CHF patients are required to measure their physiological measurements (vital signs and body weight) every day and to submit their symptoms using the app. additionally, based on their data, they will receive customized notifications and motivation messages to classify risk of disease exacerbation. The architecture of system comprised of six major components: 1) a patient data collection suite including a mobile app and website; 2) Data Receiver; 3) Database; 4) a Specialists expert Panel; 5) Rule engine classifier; 6) Notifier engine. RESULTS: This system has implemented in Iran for the first time and we are currently in the testing phase with 10 patients to evaluate the technical performance of our system. The developed expert system generates alerts and instructions based on the patient's data and the notify engine notifies responsible nurses and physicians and sometimes patients. Detailed analysis of those results will be reported in a future report. CONCLUSION: This study is based on the design of a telemonitoring system for heart failure self-care that intents to overcome the gap that occurs when patients discharge from the hospital and tries to accurate requirement of readmission. A rule set for classifying and resulting automated alerts and patient instructions for heart failure telemonitoring was developed. It also facilitates daily communication among patients and heart failure clinicians so any deterioration in health could be identified immediately.

A Three-Phase Decision Model of Computer-Aided Coding for the Iranian Classification of Health Interventions (IRCHI).

INTRODUCTION: Accurate coded data in the healthcare are critical. Computer-Assisted Coding (CAC) is an effective tool to improve clinical coding in particular when a new classification will be developed and implemented. But determine the appropriate method for development need to consider the specifications of existing CAC systems, requirements for each type, our infrastructure and also, the classification scheme. AIM: The aim of the study was the development of a decision model for determining accurate code of each medical intervention in Iranian Classification of Health Interventions (IRCHI) that can be implemented as a suitable CAC system. METHODS: first, a sample of existing CAC systems was reviewed. Then feasibility of each one of CAC types was examined with regard to their prerequisites for their implementation. The next step, proper model was proposed according to the structure of the classification scheme and was implemented as an interactive system. RESULTS: There is a significant relationship between the level of assistance of a CAC system and integration of it with electronic medical documents. Implementation of fully automated CAC systems is impossible due to immature development of electronic medical record and problems in using language for medical documenting. So, a model was proposed to develop semi-automated CAC system based on hierarchical relationships between entities in the classification scheme and also the logic of decision making to specify the characters of code step by step through a web-based interactive user interface for CAC. It was composed of three phases to select Target, Action and Means respectively for an intervention. CONCLUSION: The proposed model was suitable the current status of clinical documentation and coding in Iran and also, the structure of new classification scheme. Our results show it was practical. However, the model needs to be evaluated in the next stage of the research.

Applying data mining techniques to determine important parameters in chronic kidney disease and the relations of these parameters to each other.

Introduction: Chronic kidney disease (CKD) includes a wide range of pathophysiological processes which will be observed along with abnormal function of kidneys and progressive decrease in glomerular filtration rate (GFR). According to the definition decreasing GFR must have been present for at least three months. CKD will eventually result in end-stage kidney disease. In this process different factors play role and finding the relations between effective parameters in this regard can help to prevent or slow progression of this disease. There are always a lot of data being collected from the patients' medical records. This huge array of data can be considered a valuable source for analyzing, exploring and discovering information. Objectives: Using the data mining techniques, the present study tries to specify the effective parameters and also aims to determine their relations with each other in Iranian patients with CKD. Material and Methods: The study population includes 31996 patients with CKD. First, all of the data is registered in the database. Then data mining tools were used to find the hidden rules and relationships between parameters in collected data. Results: After data cleaning based on CRISP-DM (Cross Industry Standard Process for Data Mining) methodology and running mining algorithms on the data in the database the relationships between the effective parameters was specified. Conclusion: This study was done using the data mining method pertaining to the effective factors on patients with CKD.

Designing and Implementation of Retina Image Drawing System and Automatic Report Generation from Retina Examinations.

INTRODUCTION: Electronic medical records as one of major parts of electronic health records is an important application of Medical Informatics. EMR includes different types of data, Graphical items being one of these data types. To this end, a standard structure for storing and recovering and finally exchanging this data type is required. In order to standardize information items in this research, UMLS standard is used. In this research, graphical information from fondues designing in retina surgery forms is used for the task of implementation. IMPLEMENTATION: Three-layer software architecture is used for implementation of this system, which includes user interface, data base access and business logic. XML database is used for storing and exchanging of data. User interface is designed by the means of Adobe Flash. Also in the user interface for eye examinations, appropriate icons compatible with current pathologies in retina examinations are considered and UMLS codes are used for standardizations purposes. RESULTS: As this project is independently implemented in Adobe Flash, it can be run in most of electronic patient records software. For evaluation purposes of this research, an EMR system for eye clinics is used. Tree structure is used for data entry and finally a text report based on the entered data will be generated. By storing graphical items in this software editing and searching in medical concepts and also comparing features will be available. CONCLUSION: One of the data items that we encounter in various medical records is graphical data. In order to cover the patient's complete electronic medical records, the Electronic Implementation of this information is important. For this purpose, graphical items in retina surgery forms were used and finally a software application for drawing retina picture was developed. Also, XML files were used for the purpose of storing valuable medical data from the pictures, and also UMLS were applied for the standardization purpose. The developed software is currently being used in some of eye clinics in Iran.