Health Data Collection Systems Research Articles

Искусственный интеллект в здравоохранении России: сбор и подготовка данных для машинного обучения.

This scientific article draws attention to the importance of collecting and preparing high-quality medical data for the development of artificial intelligence (AI) systems in Russian healthcare. Materials and methods. The main emphasis is on the need to create a unified federal standard for collecting structured digitized medical data, which will unify the processes of collecting and generating datasets for medical organizations. Results. The article proposes the introduction of digital assistants, including pre-medical diagnostic questionnaires, mobile applications and software modules for medical examinations, which will reduce the time spent filling out medical documentation and ensure the collection of more complete and accurate information. The next step is to reengineer the health data collection process, including patient engagement via smartphones and personal health assistants. The article identifies methodological problems such as unreliability, incompleteness and lack of extensional knowledge in the collected data, and proposes a roadmap for the development of a health data collection system, including the creation of digital standards, data collection methods and the development of AI-based decision support. Conclusions. Solving the described problems and the data development plan are important for the successful implementation of the national project «Data Economy», supporting the development and application of AI systems in the medical field.

Disaster and public health emergency health data collection and management: A scoping review.

The World Health Organization (WHO) developed the Emergency Medical Team (EMT) Minimum Data Set (MDS) to provide a structured, data-based approach to health data collection and management during disasters and public health emergencies. Given recent creation of the EMT MDS, we conducted a scoping review to gauge current practices surrounding health data collection and sharing in emergent settings. An English-based scoping review of PubMed and Embase databases of publications before June 28, 2021. The review aimed to identify facilitators and barriers to the implementation of the WHO-standardized health data collection systems in the context of disasters and public health emergencies; characterize best practices regarding implementation of an MDS to improve health data collection capacity in differing settings; and highlight internationally accepted, standardized tools or methods for setting up essential public health data for disaster response. A total of 8,038 citations from PubMed and Embase were imported into Covidence with 46 duplicates removed. Among these, 7,992 citations underwent title screening and abstract review, with 161 articles proceeding to full-text article review where an additional 109 articles were excluded. Fifty-two citations were included in final data abstraction. Findings revealed a range of critical operational, structural, and functional insights of relevance to implementation of the EMT MDS. The literature identified facilitators and barriers to collecting and storing disaster-based datasets, gaps in standardization of data collection resulting in poor data quality during the transition from the acute to post-acute phase, and best practices in the collection of EMT MDS.

POSB199 Prevalence of Prurigo Nodularis in the Regional Area of Brittany (France): Estimation by Matching Two Databases

The objective of this study was to estimate the PN prevalence in Brittany and to describe treatments. We estimated the prevalence of PN by using 2 health data collection systems: - A registry data from the Brest University Hospital Center; - Medical/administrative data from the French SNDS database which links the hospitalization database (PMSI) with the outpatients claim database. Patients hospitalized between 2009-2018 with a primary or a secondary diagnosis of PN (ICD-10 code L28.1) were identified. The 2 sources were combined to identify patients that would be identified in the 2 databases as having a PN and to estimate the total number of PN patients in Brittany with the capture-recapture method. The prevalence rate was estimated by dividing the number of PN patients (capture-recapture estimate) by resident Brittany population. 63 unique patients with PN were identified: 5 patients in both sources, 21 only in the centre and 37 only in SNDS database. With the capture recapture method, the total number of unique PN cases was 218 (IC95%=[125 – 349]). As there were 3,310,000 inhabitants in Brittany, the prevalence was estimated at 0.07/1000 (IC95%=[0.04;0.11]). Among the 63 patients, 37 (58.7%) were females. Mean age was 70 years. In 2018, 61% of patients received topical corticoids, 49.2% antihistamines, 47.5% antidepressants. In 2009-2018, 93.2% of patients received topical corticoids, 96.6% antihistamines, 64% psychoanaleptics, 52.5% pregabaline. No patients received tacrolimus, pimecrolimus, capsaicin or peripheral opioid receptor antagonists. This study shows a prevalence 0.07/1000 for PN in Brittany. This prevalence appears low, but the French PN definition was very restrictive before the European one.

Application of Blockchain-Based Sports Health Data Collection System in the Development of Sports Industry

In recent years, with the continuous development of blockchain technology and the prosperity of digital currency, various industries have carried out extensive practice around the application of blockchain technology, such as my country’s sports industry. Through the measurement and collection of athletes’ health and exercise information, the athlete’s exercise volume and exercise level can be quantitatively evaluated. Blockchain technology provides a new opportunity for the development of the sports industry. The characteristics of the decentralization, security, credibility, and traceability of the data collection system are highly compatible with the development of the sports industry. In order to develop and expand the sports industry and scientifically evaluate the physical fitness of athletes, this research focuses on the blockchain-based sports health data collection system in the sports industry. This article adopts the accuracy index and the formula of data return and conducts demand analysis, accuracy, and recall analysis of the health data collection system. The research conclusion of this paper is that when using sensors to collect sports health data, the data collection of sensors located on the arm is more accurate, with an accuracy rate of over 90%, and the collection effect of multinode sensors is higher than that of single-node sensors. The collection of sports health data is beneficial to the training of athletes and the development of the sports industry to meet the growing demand for sports health. Our country’s sports industry will also develop with the application of blockchain.

Form‐based security in mobile health data collection systems

AbstractMobile Health Data Collection Systems (MHDCS) use electronic forms for data collection in place of paper surveys. Data is entered into the electronic forms by community health workers with smartphones. These systems are used in clinical trials and continuous monitoring of participants. Data collected in MHDCS is diverse with varying sensitivity levels. This therefore calls for the application of different security mechanisms to protect the data. In this paper, a data sensitivity classification model is proposed. It determines the sensitivity levels of form attributes depending on the context and sensitive parameters. The electronic form is the starting point of the data collection process. We augment the form with sensitivity levels and a mapping of security mechanisms to the sensitivity levels is made. Through threat modeling, we identify potential threats and possible mitigations. We demonstrate the feasibility of our approach by prototyping the proposed model into the Open Data Kit tool suite. Tests show that the security mitigations specified during form design are executed once the secure form is loaded on the mobile device during data collection. Our ultimate aim is to facilitate the addition of security requirements into the data collection processes right from the start of the design process.

E-Consent for Data Privacy: Consent Management for Mobile Health Technologies in Public Health Surveys and Disease Surveillance.

Community health workers in primary care programs increasingly use Mobile Health Data Collection Systems (MDCSs) to report their activities and conduct health surveys, replacing paper-based approaches. The mHealth systems are inherently privacy invasive, thus informing individuals and obtaining their consent is important to protect their rights to privacy. In this paper, we introduce an e-Consent tool tailored for MDCSs. It is developed based on the requirement analysis of consent management for data privacy and built upon the solutions of Participant-Centered Consent toolkit and Consent Receipt specification. The e-Consent solution has been evaluated in a usability study. The study results show that the design is useful for informing individuals on the nature of data processing, allowing them to make informed decisions.

A Mobile Health Data Collection System for Remote Areas to Monitor Women Participating in a Cervical Cancer Screening Campaign.

Barriers to efficient cervical cancer screening in low- and medium-income countries include the lack of systematic monitoring of the participants' data. The aim of this study was to assess the feasibility of a mobile health (m-Health) data collection system to facilitate monitoring of women participating to cervical cancer screening campaign. Women aged 30-65 years, participating in a cervical cancer screening campaign in Ambanja, Madagascar, were invited to participate in the study. Cervical Cancer Prevention System, an m-Health application, allows the registration of clinical data, while women are undergoing cervical cancer screening. All data registered in the smartphone were transmitted onto a secure, Web-based platform through the use of an Internet connection. Healthcare providers had access to the central database and could use it for the follow-up visits. Quality of data was assessed by computing the percentage of key data missing. A total of 151 women were recruited in the study. Mean age of participants was 41.8 years. The percentage of missing data for the key variables was less than 0.02%, corresponding to one woman's medical history data, which was not sent to the central database. Technical problems, including transmission of photos, human papillomavirus test results, and pelvic examination data, have subsequently been solved through a system update. The quality of the data was satisfactory and allowed monitoring of cervical cancer screening data of participants. Larger studies evaluating the efficacy of the system for the women's follow-up are needed in order to confirm its efficiency on a long-term scale.

Documenting patterns of breast reconstruction in Australia: The national picture

IntroductionDifferences in national health data collection systems preclude accurate assessments of how much breast reconstruction (BR) is performed in Australia. This paper aims to quantitatively document and visually map the national prevalence and distribution of BR, using the best available evidence. Materials and methodsQuantitative analysis and spatial mapping of hospital-level data on BR prevalence in all six Australian states and two mainland territories. Data was extracted on 3786 women, under the care of members of Breast Surgeons of Australia and New Zealand Incorporated, who had mastectomy for breast malignancy with or without post-mastectomy BR in 2013. ResultsAnalysis revealed a national BR rate of 18.3%. Statistically significant differences in BR uptake (p < .0001) were found between jurisdictions [χ2 (df = 7) = 284.29], with BR more likely in younger women [χ2 (df = 14) = 395.62] and in private hospitals (χ2 = 63.99) and less likely in remote areas [χ2 (df = 4) = 66.49]. ConclusionAnalysis of this substantial subset of Australian women requiring mastectomy for breast cancer has demonstrated significant variation in provision or uptake of BR across four important variables. As BR has been shown to provide long-term survivorship benefits for the growing number of women living longer following mastectomy for breast cancer, there is an urgent need to ensure BR is accessible and affordable for all women who choose this option.

BRIDGE Health: BRidging Information and Data Generation for Evidence-based Health Policy and Research

The objective of BRIDGE-Health is to create a European health information system (EU-HIS) infrastructure. The project bridges the best of the EU projects in domains of population and health system monitoring, indicator development, health examination surveys, environment and health, population injury and disease registries, clinical and administrative health data collection systems and methods …

The Joint Medical Workstation (JMeWS) Database in 2003: Intradeployment Health Encounters of Military Personnel Supporting Operations Enduring Freedom and Iraqi Freedom

The Joint Medical Work Station (JMeWS) is a theater medical surveillance system that integrates information from three separate health data collection systems for the Army, Navy, Air Force, and Marines. Our objective was to characterize JMeWS data during its first year of implementation in 2003. We conducted a descriptive analysis of health events documented in JMeWS among military personnel deployed to Operations Enduring Freedom and Iraqi Freedom. Among the 38,498 individuals (7.8%) with a JMeWS record, women, college-educated, older individuals, and Reserve/Guard personnel were over-represented. There was wide variability by service (Air Force, 25%; Army, 5.5%; Marine Corps, 1.2%; and Navy, 0.6%). The most common diagnoses were in the categories of injury and poisoning, respiratory conditions, and musculoskeletal disorders. Differences in distribution of the various patient encounter modules in theater likely resulted in variable data capture across services. System enhancements should improve future applications.

Pilot Study of the Introduction of the J95 Health Data Collection System

J95 is a health data collection system aimed at gathering information on the weight of health problems facing the Army in order to allow rational and effective prioritization. Before implementing the system Army-wide, a pilot study has been undertaken to validate the J95 ICD 9-based classification system, to test the practical problems encountered with operating the system and its practical value to decision-makers. Both internal and external coding validity were tested in terms of agreement with a "gold standard' and in terms of repeatability and they scored highly. A number of problems were identified analysing discordances and using the comments raised by the participants. A final shortened version of the classification was developed accordingly. The report also contains a number of examples of the potential of the system which is due to be implemented by 1 January 1996.

Fertility and Infertility Assessment by Review of Records

The assessment of fertility and infertility in dairy herds requires accurate and complete data that are collected in a timely manner. The data must be entered in a record system that provides easy accessibility. An understanding of terminology and statistical calculations, along with knowledge of industry standards, reproductive physiology, and pathology is essential if problem solving is to occur. Problem solving begins by developing an understanding of the events influencing past reproductive performance. Progress is made by establishing a detailed reproductive management plan to monitor the current breeding herd and to identify potential problems before they occur. The introduction of microcomputers and on-farm record systems has greatly enhanced the veterinarian's ability to access and process data. For the first time in history, cowside health data collection systems integrated with production records are being used. This provides the opportunity to collect and summarize and analyze reproductive and production data as the events occur. Successful reproductive performance depends on effective and efficient management. For veterinarians to effectively and positively influence the reproductive performance of the herd, they must influence management. This requires working with dairy management to make changes in job assignments and description. Taking time to assess records with managers is an invaluable tool to convince dairy management of the necessity for change.

Grants and Outcomes

Grants and Outcomes