Health Data Management Research Articles

Report on the Second International Workshop on Semantic Web Meets Health Data Management (SWH 2019)

The advancements in health-care have brought to the foreground the need for flexible access to health-related information and created an ever-growing demand for efficient data management infrastructures. To this direction, many challenges must be first overcome, enabling seamless, effective and efficient access to several health data sets and novel methods for exploiting the existing information. The second international workshop on semantic Web technologies for health data management aimed at putting together an interdisciplinary audience that is interested in the fields of semantic web, data management and health informatics to discuss the challenges in health-care data management and to propose new solutions for the next generation data-driven health-care systems. In this article, we summarize the outcomes of the workshop, and we present a number of key observations and research directions that emerge.

Status and Influential Factors of Intelligent Healthcare in Nursing Homes in China.

With the support of the Chinese government, nursing homes have increasingly adopted Internet and intelligent information technology to provide daily healthcare services to residents. However, no research has reported the status of intelligent healthcare in nursing homes. From September 2017 to May 2018, we conducted a survey of 197 nursing homes and collected information on their general characteristics, the intelligent healthcare services provided, the effectiveness of the application products used, and the attitudes of the staff and residents toward intelligent healthcare. Overall, 79.69% of the surveyed nursing homes have provided intelligent healthcare services, including medical care services (eg, chronic disease management and intelligent nursing) and daily life services (eg, fall monitoring and wireless positioning). Portable health monitoring devices and data management and service platforms are the most used healthcare products. The attitudes of staff probably affected the development of intelligent healthcare. Financial investment and the attitudes of staff and residents are factors that influence the effectiveness of the application of intelligent healthcare products in nursing homes. With the support of national policies, nursing homes have implemented primary intelligent healthcare. Stakeholders play pivotal roles in the provision of intelligent healthcare services.

Proposed Implementation of Blockchain in British Columbia's Health Care Data Management.

BackgroundThere are several challenges such as information silos and lack of interoperability with the current electronic medical record (EMR) infrastructure in the Canadian health care system. These challenges can be alleviated by implementing a blockchain-based health care data management solution.ObjectiveThis study aims to provide a detailed overview of the current health data management infrastructure in British Columbia for identifying some of the gaps and inefficiencies in the Canadian health care data management system. We explored whether blockchain is a viable option for bridging the existing gaps in EMR solutions in British Columbia’s health care system.MethodsWe constructed the British Columbia health care data infrastructure and health information flow based on publicly available information and in partnership with an industry expert familiar with the health systems information technology network of British Columbia’s Provincial Health Services Authorities. Information flow gaps, inconsistencies, and inefficiencies were the target of our analyses.ResultsWe found that hospitals and clinics have several choices for managing electronic records of health care information, such as different EMR software or cloud-based data management, and that the system development, implementation, and operations for EMRs are carried out by the private sector. As of 2013, EMR adoption in British Columbia was at 80% across all hospitals and the process of entering medical information into EMR systems in British Columbia could have a lag of up to 1 month. During this lag period, disease progression updates are continually written on physical paper charts and not immediately updated in the system, creating a continuous lag period and increasing the probability of errors and disjointed notes. The current major stumbling block for health care data management is interoperability resulting from the use of a wide range of unique information systems by different health care facilities.ConclusionsOur analysis of British Columbia’s health care data management revealed several challenges, including information silos, the potential for medical errors, the general unwillingness of parties within the health care system to trust and share data, and the potential for security breaches and operational issues in the current EMR infrastructure. A blockchain-based solution has the highest potential in solving most of the challenges in managing health care data in British Columbia and other Canadian provinces.

Effects of SARS-CoV-2 (COVID-19) Pandemic on Primary Health Care Service Delivery and Data Management in Nigeria, July 2020

Primary health care, the foundation of healthcare systems around the world, recognized for its ability to deliver efficient, equitable, high-quality, patient-centered care. As with the rest of the world, Nigeria is currently dealing with COVID-19 pandemic. On February 27, 2020, the first case of COVID-19 in Nigeria was reported. As of July 31 2020, there were over Forty Thousand cases and 900 deaths. We assessed the effects of SARS-CoV-2 on primary health care service delivery and data management in Nigeria A desk review (secondary data analysis) of health data submitted monthly (January 2020 – May 2020 reporting period) on National Health Management Information System hosted on the national instance of the District Health Information System was conducted. Other procedures include: Selection of primary healthcare performance indicators, download of data from District Health Information System, data cleaning and analysis There was no significant impact on the completeness of the report for the month of March, April and May 2020 which dropped from 83.2% in February, 2020 to 82.7%, 82.7% and 82.4% in March, April and May, 2020 respectively. Amidst the increasing number of COVID-19 cases in the FCT despite the total lockdown proclaimed by the government, other PHC indicators had also been on the decline. Since the first confirmed COVID-19 case in Lagos, PHC indicators had been on the decline. In Ogun state, Total facility attendance declined significantly in the month of March and April when the lockdown was implemented. Although fixed sessions for routine immunization increased, antenatal attendance declined and Penta dropout rate increased over the period of the lockdown. Access to healthcare is a fundamental human right, but the strain that the COVID 19 pandemic has placed on Nigerian citizens especially in areas where restrictive measures were met has in turn, affected many people’s access to healthcare.Funding Statement: The author(s) received no specific funding for this work.Declaration of Interests: The authors have no conflicts of interest to declare. Ethics Approval Statement: Not required.

LifeTime and improving European healthcare through cell-based interceptive medicine.

Here we describe the LifeTime Initiative, which aims to track, understand and target human cells during the onset and progression of complex diseases, and to analyse their response to therapy at single-cell resolution. This mission will be implemented through the development, integration and application of single-cell multi-omics and imaging, artificial intelligence and patient-derived experimental disease models during the progression from health to disease. The analysis of large molecular and clinical datasets will identify molecular mechanisms, create predictive computational models of disease progression, and reveal new drug targets and therapies. The timely detection and interception of disease embedded in an ethical and patient-centred vision will be achieved through interactions across academia, hospitals, patient associations, health data management systems and industry. The application of this strategy to key medical challenges in cancer, neurological and neuropsychiatric disorders, and infectious, chronic inflammatory and cardiovascular diseases at the single-cell level will usher in cell-based interceptive medicine in Europe over the next decade.

Community-based health agents practices in Burkina Faso

Abstract Background It is estimated that around 25% of the world's infant mortality is in West Africa where undernutrition accounts for more than 50% of the underlying causes of under-5 mortality. Malnutrition rates have decreased slightly, especially compared to the targets set for 2025. Since Alma-Ata's declaration in 1978, community participation in primary health care has been one way of reducing health inequalities. WHO recommended the integration of community health workers (CHW) into the health system and their inclusion in the human resources planning strategy. We observed a decline of programs involving CHW in the 1990s, then a definite revaluation since the 1990s and specifically, since 2012. They provide health education, as well as referral for a range of services, and provide support and assistance to communities and families through preventive health, easier access to curative health services as well as social services. The specific objectives of this project include: to describe the roles and functions of CHW in Burkina Faso, to identify the workers' needs, to explore the changes in the system and to identify the conditions related to their deployment. Methods A qualitative case study allowed to describe the processes and also facilitated the discovery of key elements related to the experiences of community agents, considering the elements of complexity and context. Results Our results include activities in promotional services, preventive services, curative services and health data management. In addition, we will shed light on their feelings and experiences related to integration into the system, on the strategies they use, on the advantages that bring their role as community workers, their concerns and finally, we will share their perception of their impact. Some recommendations are proposed in regards to training and supervision. Key messages CHW are major players in health systems by creating a bridge between health and social service providers and communities with reduced access. CHW contributes to social justice by facilitating access, promoting recognition and creating empowering processes through increased participation.

Implementation of a national electronic health information system in Gabon: a survey of healthcare providers\u2019 perceptions

BackgroundThe Health Information System (HIS) is a set of computerized tools for the collection, storage, management, and transmission of health data. The role of such tools in supporting the modernization of health systems, improving access to quality healthcare, and reducing costs in developing countries is unquestionable, but their implementation faces several challenges. In Gabon, a unique national electronic HIS has been launched. It will connect healthcare institutions and providers at all levels in the whole country.ObjectiveThis study aims to explore and identify the factors influencing healthcare providers’ perceptions of the national electronic HIS in Gabon.MethodsA 44-item questionnaire based on the Information System Success Model (ISSM) was administered between February and April 2018 among 2600 healthcare providers across the country. The questions assessed the different aspects of the HIS that could influence its perceived impact on a 5-level Likert scale (from fully agree to totally disagree). The reliability and construct validity of the questionnaire were checked using Cronbach alpha and congeneric reliability coefficients. A logistic regression was used to identify the factors influencing healthcare providers’ perceptions of the system.ResultsA total of 2327 questionnaires were completed (i.e. 89.5% response rate). The logistic regression identified five elements that significantly influenced perceived system impact: System Quality (Odds Ratio–OR = 1.70), Information Quality (OR = 1.69), Actual Use (OR = 1.41), Support Quality (OR = 1.37), and Useful Functions (OR = 1.14). The model explained 30% of the variance in providers’ perception that the national HIS leads to positive impacts.DiscussionThe results show that healthcare providers’ perceptions regarding the positive impact of the national HIS in Gabon are influenced by their previous use of an HIS, the scope of their usage, and the quality of the system, information, and support provided to users. These results could inform the development of strategies to ensure adequate change of management and user experience for the implementation of the national HIS in Gabon, and eventually in other low resource environments.

Effectiveness of Mobile App-Assisted Self-Care Interventions for Improving Patient Outcomes in Type 2 Diabetes and/or Hypertension: Systematic Review and Meta-Analysis of Randomized Controlled Trials.

BackgroundMobile app-assisted self-care interventions are emerging promising tools to support self-care of patients with chronic diseases such as type 2 diabetes and hypertension. The effectiveness of such interventions requires further exploration for more supporting evidence.ObjectiveA systematic review and meta-analysis of randomized controlled trials (RCTs) were conducted to examine the effectiveness of mobile app-assisted self-care interventions developed for type 2 diabetes and/or hypertension in improving patient outcomes.MethodsWe followed the Cochrane Collaboration guidelines and searched MEDLINE, Cochrane Library, EMBASE, and CINAHL Plus for relevant studies published between January 2007 and January 2019. Primary outcomes included changes in hemoglobin A1c (HbA1c) levels, systolic blood pressure (SBP), and diastolic blood pressure (DBP). Changes in other clinical-, behavioral-, knowledge-, and psychosocial-related outcomes were included as secondary outcomes. Primary outcomes and objective secondary outcomes that were reported in at least two trials were meta-analyzed; otherwise, a narrative synthesis was used for data analysis.ResultsA total of 27 trials were identified and analyzed. For primary outcomes, the use of mobile app-assisted self-care interventions was associated with significant reductions in HbA1c levels (standardized mean difference [SMD] −0.44, 95% CI −0.59 to −0.29; P<.001), SBP (SMD −0.17, 95% CI −0.31 to −0.03, P=.02), and DBP (SMD −0.17, 95% CI −0.30 to −0.03, P=.02). Subgroup analyses for primary outcomes showed that several intervention features were supportive of self-management, including blood glucose, blood pressure, and medication monitoring, communication with health care providers, automated feedback, personalized goal setting, reminders, education materials, and data visualization. In addition, 8 objective secondary outcomes were meta-analyzed, which showed that the interventions had significant lowering effects on fasting blood glucose levels and waist circumference. A total of 42 secondary outcomes were narratively synthesized, and mixed results were found.ConclusionsMobile app-assisted self-care interventions can be effective tools for managing blood glucose and blood pressure, likely because their use facilitates remote management of health issues and data, provision of personalized self-care recommendations, patient–care provider communication, and decision making. More studies are required to further determine which combinations of intervention features are most effective in improving the control of the diseases. Moreover, evidence regarding the effects of these interventions on the behavioral, knowledge, and psychosocial outcomes of patients is still scarce, which warrants further examination.

Requirements of Health Data Management Systems for Biomedical Care and Research: Scoping Review.

BackgroundOver the last century, disruptive incidents in the fields of clinical and biomedical research have yielded a tremendous change in health data management systems. This is due to a number of breakthroughs in the medical field and the need for big data analytics and the Internet of Things (IoT) to be incorporated in a real-time smart health information management system. In addition, the requirements of patient care have evolved over time, allowing for more accurate prognoses and diagnoses. In this paper, we discuss the temporal evolution of health data management systems and capture the requirements that led to the development of a given system over a certain period of time. Consequently, we provide insights into those systems and give suggestions and research directions on how they can be improved for a better health care system.ObjectiveThis study aimed to show that there is a need for a secure and efficient health data management system that will allow physicians and patients to update decentralized medical records and to analyze the medical data for supporting more precise diagnoses, prognoses, and public insights. Limitations of existing health data management systems were analyzed.MethodsTo study the evolution and requirements of health data management systems over the years, a search was conducted to obtain research articles and information on medical lawsuits, health regulations, and acts. These materials were obtained from the Institute of Electrical and Electronics Engineers, the Association for Computing Machinery, Elsevier, MEDLINE, PubMed, Scopus, and Web of Science databases.ResultsHealth data management systems have undergone a disruptive transformation over the years from paper to computer, web, cloud, IoT, big data analytics, and finally to blockchain. The requirements of a health data management system revealed from the evolving definitions of medical records and their management are (1) medical record data, (2) real-time data access, (3) patient participation, (4) data sharing, (5) data security, (6) patient identity privacy, and (7) public insights. This paper reviewed health data management systems based on these 7 requirements across studies conducted over the years. To our knowledge, this is the first analysis of the temporal evolution of health data management systems giving insights into the system requirements for better health care.ConclusionsThere is a need for a comprehensive real-time health data management system that allows physicians, patients, and external users to input their medical and lifestyle data into the system. The incorporation of big data analytics will aid in better prognosis or diagnosis of the diseases and the prediction of diseases. The prediction results will help in the development of an effective prevention plan.

Legal Challenges for IT Service Providers in Pharmacogenomics.

IT providers offering services based on genetic data face serious challenges in managing health data in compliance with the General Data Protection Regulation (GDPR). Based on a literature research and our experiences, an overview of GDPR compliant processing of sensitive data is given. The GDPR requirements for processing sensitive data were specified for a use case concerning a service provider of a pharmacogenomic decision support system. Start-ups who want to enter into the health market also have to comply with the Medical Device Regulation (MDR). The associated efforts for legal compliance constitute an impediment for many start-ups. We created a comprehensive overview, which aligned the requirements of the GDPR with the life-cycle of a medical device. This overview shall help start-ups to grasp and overcome the regulatory hurdles faster.

A Review of Mobile Health Applications in Epidemic and Pandemic Outbreaks: Lessons Learned for COVID-19

Context: Using smart mobile devices, called mobile health (mHealth), facilitates providing health services, speeds up the process, and reduces the costs and complications of direct services. Also, mHealth has many capabilities and applications in epidemic and pandemic outbreaks. This study aimed to identify mHealth applications in epidemic/pandemic outbreaks and provide some suggestions for tackling COVID-19. Methods: To find the relevant studies, searches were done in PubMed and Scopus by related keywords during 2014 - 2020 (March 10). After selecting the studies based on the inclusion and exclusion criteria, data were collected by a data-gathering form. Results: Of the 727 retrieved studies, 17 studies were included. All studies emphasized the positive effect of mHealth for use in epidemic/pandemic outbreaks. The main applications of mHealth for epidemic/pandemic outbreaks included public health aspects, data management, educational programs, diagnosis, and treatment. Conclusions: mHealth is an appropriate method for encountering epidemic/pandemic outbreaks due to its extensive applications. In the pandemic outbreak of COVID-19, mHealth is one of the best choices to use in the patient-physician relationship as tele-visits, using in fever coach, providing real-time information for healthcare providers, population monitoring, and detecting the disease based on obtained data from different locations.

From Raw Data to FAIR Data: The FAIRification Workflow for Health Research

FAIR (findability, accessibility, interoperability, and reusability) guiding principles seek the reuse of data and other digital research input, output, and objects (algorithms, tools, and workflows that led to that data) making them findable, accessible, interoperable, and reusable. GO FAIR - a bottom-up, stakeholder driven and self-governed initiative - defined a seven-step FAIRification process focusing on data, but also indicating the required work for metadata. This FAIRification process aims at addressing the translation of raw datasets into FAIR datasets in a general way, without considering specific requirements and challenges that may arise when dealing with some particular types of data. This scientific contribution addresses the architecture design of an open technological solution built upon the FAIRification process proposed by "GO FAIR" which addresses the identified gaps that such process has when dealing with health datasets. A common FAIRification workflow was developed by applying restrictions on existing steps and introducing new steps for specific requirements of health data. These requirements have been elicited after analyzing the FAIRification workflow from different perspectives: technical barriers, ethical implications, and legal framework. This analysis identified gaps when applying the FAIRification process proposed by GO FAIR to health research data management in terms of data curation, validation, deidentification, versioning, and indexing. A technological architecture based on the use of Health Level Seven International (HL7) FHIR (fast health care interoperability resources) resources is proposed to support the revised FAIRification workflow. Research funding agencies all over the world increasingly demand the application of the FAIR guiding principles to health research output. Existing tools do not fully address the identified needs for health data management. Therefore, researchers may benefit in the coming years from a common framework that supports the proposed FAIRification workflow applied to health datasets. Routine health care datasets or data resulting from health research can be FAIRified, shared and reused within the health research community following the proposed FAIRification workflow and implementing technical architecture.

Fog computing in health: A systematic literature review

Currently, technology greatly benefits the area of healthcare. Modern computers can quickly process a large volume of patient health records. Due to recent advances in the area of Internet of Things and healthcare, patient data can be dispersed in multiple locations. As a result, scientists have been proposing solutions based on Cloud Computing to manage healthcare data. However, suchs solutions present challenges regarding access latency, context-awareness, and large volumes of data. There is an increased probability of processing and transmission errors are more likely to occur as health data sets become larger and more complex. In this context, Fog Computing presents itself as an alternative to reduce health data management complexity, consequently increasing its reliability. To that end, it is important to comprehend the associated challenges before defining a Fog Computing-based architecture to manage healthcare data. This article presents a systematic literature review of fog computing being applied to healthcare area. We propose a taxonomy to explore the open issues and most important challenges on these fields of study. We selected 1070 scientific articles published in the last 10 years, filtering the 44 most significant works for an in-depth analysis. We found that there is several challenges to be addressed such as interoperability, privacy, security, data processing, management of resources and Big Data issues. Also, our contribution include developing a taxonomy for the Fog Computing and healthcare fields of study and finding out challenges and open questions of this area.

Improving the Healthcare Effectiveness: The Possible Role of EHR, IoMT and Blockchain

New types of patient health records aim to help physicians shift from a medical practice, often based on their personal experience, towards one of evidence based medicine, thus improving the communication among patients and care providers and increasing the availability of personal medical information. These new records, allowing patients and care providers to share medical data and clinical information, and access them whenever they need, can be considered enabling Ambient Assisted Living technologies. Furthermore, new personal disease monitoring tools support specialists in their tasks, as an example allowing acquisition, transmission and analysis of medical images. The growing interest around these new technologies poses serious questions regarding data integrity and transaction security. The huge amount of sensitive data stored in these new records surely attracts the interest of malicious hackers, therefore it is necessary to guarantee the integrity and the maximum security of servers and transactions. Blockchain technology can be an important turning point in the development of personal health records. This paper discusses some issues regarding the management and protection of health data exchanged through new medical or diagnostic devices.

Monitoring, analysis and spatial and temporal zoning of air pollution (carbon monoxide) using Sentinel-5 satellite data for health management in Iran, located in the Middle East

Various natural and anthropogenic factors are effective in causing air pollution. The effects of air pollution are more pronounced on the health of living things, especially on the mental and physical health. Therefore, this issue is important because of the importance of health and well-being. The purpose of the present study is to investigate the spatial and temporal monitoring and analysis of air pollution (carbon monoxide, CO) using satellite and remote sensing data in Iran. To do this, Sentinel-5 satellite data for air pollution (CO) monitoring over a 14-month period (November 2018 to December 2019) and Terra satellite and MODIS satellite data with LST index for monitoring changes of daily and nocturnal temperatures (Kelvin unit) over a 24-month period (January 2018 to December 2019) were used. The results showed that the highest amount of air pollution (CO) was obtained in April 2019 with 0.39 mol/m2. However, the highest amount of air pollution in spatial monitoring of CO was obtained for Tehran and Guilan provinces with values of 0.51 mol/m2 and 0.49 mol/m2 respectively, while the lowest amount of CO was 0.19 mol/m2 for December 2019. Northwestern Iran, south and west areas of the central part of Ardebil province, south half and eastern part of East Azarbaijan province, Sahand mountain range, and western part of the border section of West Azerbaijan province were exposed to air pollution with average values of 0 to 0.21 mol/m2. Since the highest amounts of air pollution (CO) occur during the cold months of the year, people who are vulnerable to this phenomenon should travel to the polluted sites with observing hygiene principles.

Impact of the European General Data Protection Regulation (GDPR) on Health Data Management in a European Union Candidate Country: A Case Study of Serbia

As of May 2018, all relevant institutions within member countries of the European Economic Area are required to comply with the European General Data Protection Regulation (GDPR) or face significant fines. This regulation has also had a notable effect on the European Union (EU) candidate countries, which are undergoing the process of harmonizing their legislature with the EU as part of the accession process. The Republic of Serbia is an example of such a candidate country, and its 2018 Personal Data Protection Act mirrors the majority of provisions in the GDPR. This paper presents the impact of the GDPR on health data management and Serbia’s capability to conduct international health data research projects. Data protection incidents reported in Serbia are explored to identify common underlying causes using a novel taxonomy of contributing factors across aspects and health system levels. The GDPR has an extraterritorial application for the non-EU data controllers who process the data of EU citizens and residents, which mainly affects private practices used by medical tourists from the EU, public health care institutions frequented by foreigners, as well as expatriates, dual citizens, tourists, and other visitors. Serbia generally does not have well-established procedures to support international research collaborations around its health data. For smaller projects, contractual arrangements can be made with health data providers and their ethics committees. Even then, organizations that have not previously participated in similar ventures may require approval or support from health authorities. Extensive studies that involve multisite data typically require the support of central health system institutions and relevant research data aggregators or electronic health record vendors. The lack of a framework for preparation, anonymization, and assurance of privacy preservation forces researchers to rely heavily on local expertise and support. Given the current limitation and potential issues with the legislation, it remains to be seen whether the move toward the GDPR will be beneficial for the Serbian health system, medical research, protection of personal data and privacy rights, and research capacity. Although significant progress has been made so far, a strategic approach is needed at the national level to address insufficient resources in the area of data protection and develop the personal data protection environment further. This will also require a targeted educational effort among health workers and decision makers, aiming to improve awareness and develop skills and knowledge necessary for the workforce.

The Need for Machine-Processable Agreements in Health Data Management

Data processing agreements in health data management are laid out by organisations in monolithic “Terms and Conditions” documents written in natural legal language. These top-down policies usually protect the interest of the service providers, rather than the data owners. They are coarse-grained and do not allow for more than a few opt-in or opt-out options for individuals to express their consent on personal data processing, and these options often do not transfer to software as they were intended to. In this paper, we study the problem of health data sharing and we advocate the need for individuals to describe their personal contract of data usage in a formal, machine-processable language. We develop an application for sharing patient genomic information and test results, and use interactions with patients and clinicians in order to identify the particular peculiarities a privacy/policy/consent language should offer in this complicated domain. We present how Semantic Web technologies can have a central role in this approach by providing the formal tools and features required in such a language. We present our ongoing approach to construct an ontology-based framework and a policy language that allows patients and clinicians to express fine-grained consent, preferences or suggestions on sharing medical information. Our language offers unique features such as multi-party ownership of data or data sharing dependencies. We evaluate the landscape of policy languages from different areas, and show how they are lacking major requirements needed in health data management. In addition to enabling patients, our approach helps organisations increase technological capabilities, abide by legal requirements, and save resources.

Developing a national minimum data set for hospital information systems in the Islamic Republic of Iran.

Standardized data collection supports disease information management and leads to better quality of care. The Islamic Republic of Iran lacks a standard data set for data collection in hospitals. The aim of this study was to design a minimum data set for hospital information systems in the Islamic Republic of Iran. This study was conducted in 2015. Data sets of other countries, hospital records, hospital information systems and electronic health record systems in the Islamic Republic of Iran were reviewed for data elements for the minimum data set. Data elements were collected using a data extraction form and were categorized into similar classes, which were divided into administrative and clinical sections. The list of data elements was reviewed by experts in technical offices of the Iranian Ministry of Health and Medical Education, and a minimum data set was drawn up. There were nine and 18 data classes in the administrative and clinical sections with a total of 166 and 684 data elements respectively. After review by the expert panel, 159 administrative and 621 clinical data elements were retained as the minimum data set for the Iranian hospital information system. Our dataset can be used by the Iranian health ministry, hospital information system companies and health surveillance centres for more efficient management of health data.

Improving data management system from health, Safety and Environmental data external assurance

A constantly increasing number of investors and stakeholders are seeking key sustainability related information. The necessity of third-party assurance of non-financial disclosure has been dwelt on in various literature. External assurance of sustainability reporting plays a key role in raising credibility, trust and engagement of the reporting organization’s stakeholders. Yet, limited research has been done on how the external assurance process can be used to strengthen internal reporting and management systems, thereby, enhancing Board and CEO reliance on material and trustworthy information. This paper examines the status quo of Health, Safety and Environment (HSE) data management at a multinational company, identifying challenges and opportunities in integrating sustainability measurement and management approaches. Questionnaires submitted in sites located in four continents and covering close to 90% of environmental impacts of the company, identified worst performing sites of HSE data management as those with cumulated environmental impact of over 66% of the total. In addition, 50% of sites implementing internal controls do not meet requirements of a reasonable assurance statement. Recommendations on urgent measures to be implemented and an HSE data Management Improvement Tree are provided as practical contributions to research on tools to enhance processes between company-internal actors and linkages among sustainability accounting, management control and internal communication and reporting methods.

Deaths from HIV/AIDS in aged adults in the Federal District: an analysis from 2007 to 2016

Introduction: Infection with the human immunodeficiency virus/acquired immunodeficiency syndrome (HIV/AIDS) in Brazil experienced a significant increase in the last decade among individuals aged over 60 years. This scenario indicates the need to know the mortality profile from AIDS in aged adults, in order to promote educational and preventive actions, in addition to professional development to improve the care provided to these patients. Objective: To describe the epidemiological profile of aged adults who died of AIDS in the Federal District (FD) from 2007 to 2016. Methods: This is a descriptive ecological study, based on secondary data from the Brazilian Mortality Information System, obtained through the Health Situation Analysis and Data Management of the Health Department of the FD. The analysis was carried out in the Statistical Package for the Social Sciences (SPSS). Results: Deaths occurred more frequently among men (74.1%), especially those aged from 60 to 69 years (70.4%). The gender ratio was 2.85. Most of them only had primary school education (42.0%), were married or in a common-law marriage (43.0%), and were white/Caucasian (52%). Regarding the place of residence, Plano Piloto was the place with the highest incidence (45.7%), followed by Ceilândia (12.3%) and Taguatinga (8.6%). Conclusion: It was found that AIDS, among aged adults, follows the national trend, occurring most frequently in older males, demonstrating that it is necessary to improve the implementation of prevention practices among this population. It is necessary to better study AIDS-related stigma and prejudice barriers, both among older adults and health professionals, to overcome them, to increase life expectancy of these patients and to improve their quality of life.