Health Data Management System Research Articles

Blockchain in Health Data Management

The introduction of blockchain technology into the realm of health data management has generated a substantial level of interest due to its potential benefits. This intriguing development prompted the investigation presented in this research paper, which delves into the profound impact that blockchain could have on the traditional methods of storing, accessing, and sharing health-related information. By exploring the intricacies of blockchain technology, the paper aims to shed light on how this innovative approach could potentially revolutionize the landscape of managing health data. Moreover, an in-depth examination is conducted to elucidate the critical obstacles that currently impede the efficiency of health data management systems, paving the way for a discussion on how blockchain technology could effectively mitigate these challenges. The exploration further expands to elucidate how blockchain offers novel solutions that not only bolster security measures but also uphold the fundamental principles of privacy and interoperability within health data management. Through a comprehensive analysis of diverse use cases in the healthcare sector, the paper seeks to underscore the manifold advantages of incorporating blockchain technology, bringing to the forefront its transformative influence on patient care and medical research endeavors.

Member States’ preparedness in joining the European Health Data Space

Abstract The third presentation will focus on the findings of the TEHDAS country visits carried out between December 2021-December 2022, which mapped 12 countries’ health data management systems and preparedness to join the European Health Data Space (EHDS) for secondary use (for research and policy making). The presentation will cover the methodology used, based on the WHO tool for health information system assessment, adapted to the specific focus of secondary use of health data. The presentation will outline the key findings from the TEHDAS country visits. In general, countries recognise the benefits of the EHDS and the potential it provides for improvements at national level. The presentation will focus on overarching findings across countries, with a particular focus on preparedness for the EHDS, and the needs and concerns raised by countries.

2.G. Round table: Member States’ Health Information Systems: State-of-play and best practices

Abstract Health Information Systems (HIS) are at the basis of the generation of knowledge for improving the health and well-being of the population. The COVID-19 pandemic put health systems under enormous pressure and forced them to quickly adapt to the changing conditions while continuing to deliver essential health services, highlighting the importance of robust data flows to inform appropriate policy responses. To be better prepared for future health treats, countries can learn important lessons from the COVID-19 crisis and strengthen their own health information systems. At European level, the Health Emergency and Preparedness Response Authority (HERA) and the European Health Data Space (EHDS) are key components of the European Health Union, which aims to improve the resilience of the health systems. Assessments of health information systems allows identification of strengths and weaknesses. To assess HISs in Europe in different contexts, mapping exercises are conducted across three different European projects: the Population Health Information Research Infrastructure (PHIRI), the Joint Action Towards the European Health Data Space (TEHDAS), and the European Interoperability with the HERA IT Platform (EU-HIP) project. The three mapping exercises focus on different aspects of national health information systems. The assessments also create opportunities for engagement and knowledge exchange with national stakeholders and authorities, to learn from the experiences that were gained during the assessments and contribute to capacity building across Europe. The mapping exercises were all based on the “Support tool to strengthen health information systems: guidance for health information system assessment and strategy development” developed by the WHO, to ensure consistency, comparability, and alignment with best practice. PHIRI conducted assessments to map the HIS that monitor the effects of COVID-19 on population health in 8 European countries. Concurrently, TEHDAS conducted 12 country visits to map the state-of-play of health data management systems and their preparedness to join the European Health Data Space (EHDS), one of the key components of the European Health Union. The EU-HIP project will map countries’ interoperability with the upcoming HERA IT Platform, focusing on data flows for intelligence gathering and threat assessment for health emergency preparedness in relation to medical countermeasures. Throughout the session, the exchange of knowledge, experiences and opinions with the audience will be fostered by the moderator and by using Slido to allow the attendees to interact as much as possible with the panelists. This will ensure key messages will be assimilated by the participants. After a presentation from each of the project on the main findings of the assessments, the panelists will discuss key aspects related to the resilience of health systems and the next steps for ensuring stronger health systems across Europe. Key messages • Resilient HIS have the capacity to prepare, absorb, recover, and learn from experience. Robust data flows are key to resilience, both within countries and in cross-border European initiatives. • Structured assessments of health information systems can identify strengths and weakness to be addressed to improve the resilience of the health information system.

Evaluation of Spatial Spillover Effect of Multidimensional Hybrid Financial Risk Contagion Based on the DAI Spatial Econometric Model

The process of global integration has accelerated, and the international financial market has become increasingly closely linked. The financial risks that come with them are becoming more complex and difficult to guard against. Multimedia modeling in Health Cloud biometric authentication and data management systems can be applied to the analysis of financial markets. Most of the current financial risk analysis models are based on a single time, and the models are relatively simple and cannot adapt to the current complex multidimensional mixed financial risk environment. Therefore, this paper aimed to analyze the spatial spillover effect of financial risk contagion based on the directed asymmetric (DAI) spatial econometric model. This paper proposed to transfer entropy information weight information and introduce the GARCH (generalized auto-regressive conditional heteroskedasticity) model to improve the traditional econometric model. By constructing a DAI measurement model, the spatial contagion of multidimensional mixed financial risks was analyzed, and on this basis, a generalized multidimensional economic space was established to analyze spatial spillover effects and analyze the specific path of spatial spillover effects. The model results in this paper showed that the degree of correlation between the stock and bond market varied greatly between countries. Among them, the change coefficient W s ⟶ b r s D of the event period was judged to have a large degree of negative change in the United Kingdom, Germany, and France in the European Union, which were −0.9885, −0.9876, and −0.9748, respectively. This showed that the model in this paper had a good and reliable ability to cope with the current multidimensional mixed complex financial risk environment and could be used as a reference for financial risk-related research. At the same time, it also proved that multimedia modeling in health cloud biometric authentication and data management system could provide a role in financial risk contagion analysis.

Evaluation of the Construction of a Data Center-Driven Financial Shared Service Platform From the Remote Multimedia Network Perspective

The financial shared service (FSS) platform under the remote multimedia network perspective is a newly proposed accounting and reporting business management mode in recent years that plays a good role in the operation of enterprises. The multimedia technology in the health cloud biological authentication and data management system can be applied to the construction of the data center-driven FSS platform. This study used multimedia in the data management system to build a data center-driven FSS platform to maintain the normal operation of the enterprise. Moreover, the study analyzed from the perspective of employee satisfaction, work efficiency, enterprise cost, and work continuity and drew a conclusion. The survey of employee satisfaction showed that the satisfaction of employees after modeling had been greatly improved compared with that before modeling. Moreover, according to the survey of work efficiency, the work efficiency of employees in the five enterprises after modeling has been greatly improved compared with that before modeling. Furthermore, in the survey of enterprise cost, the cost reduction effect of postal enterprises is best after using multimedia technology to model the data center-driven FSS platform. Then, according to the survey on work continuity, the work continuity of the five enterprises has been improved to varying degrees after the establishment of the FSS platform. Among them, the work continuity of Enterprise 2 has been improved by 11%, with the best effect. The multimedia modeling in the health cloud biological authentication and data management system plays a role in promoting the development of enterprises.

An Extended Review Concerning the Relevance of Deep Learning and Privacy Techniques for Data-Driven Soft Sensors

The continuously increasing number of mobile devices actively being used in the world amounted to approximately 6.8 billion by 2022. Consequently, this implies a substantial increase in the amount of personal data collected, transported, processed, and stored. The authors of this paper designed and implemented an integrated personal health data management system, which considers data-driven software and hardware sensors, comprehensive data privacy techniques, and machine-learning-based algorithmic models. It was determined that there are very few relevant and complete surveys concerning this specific problem. Therefore, the current scientific research was considered, and this paper comprehensively analyzes the importance of deep learning techniques that are applied to the overall management of data collected by data-driven soft sensors. This survey considers aspects that are related to demographics, health and body parameters, and human activity and behaviour pattern detection. Additionally, the relatively complex problem of designing and implementing data privacy mechanisms, while ensuring efficient data access, is also discussed, and the relevant metrics are presented. The paper concludes by presenting the most important open research questions and challenges. The paper provides a comprehensive and thorough scientific literature survey, which is useful for any researcher or practitioner in the scope of data-driven soft sensors and privacy techniques, in relation to the relevant machine-learning-based models.

NikshayChain: A Blockchain-Based Proposal for Tuberculosis Data Management in India

A recent development in the Internet of Things (IoT) has accelerated the application of IoT-based solutions in healthcare. Next-Gen networks and IoT, supported by the development of technologies such as Artificial Intelligence (AI) and blockchain, have propelled the growth of e-health applications. However, there are some unique challenges in the widespread acceptance of IoT in healthcare. Safe storage, transfer, authorized access control, and the privacy and security aspects of patient data management are crucial barriers to the widespread adoption of IoT in healthcare. This makes it necessary to identify current issues in the various health data management systems to develop novel healthcare solutions. As a case study, this work considers a scheme launched by the Government of India for tuberculosis care called Nikshay Poshan Yojana (NPY). It is a web-based Direct Benefit Transfer scheme to provide a nutritional incentive of INR 500/- per month to all tuberculosis patients. The main objective of this work is to identify the current implementation challenges of the NPY scheme from patient and healthcare stakeholder perspectives and proposes a blockchain-based architecture called NikshayChain for sharing patient medical reports and bank details among several healthcare stakeholders within or across Indian cities. The proposed architecture accelerates healthcare stakeholder productivity by reducing workload and overall costs while ensuring effective data management. This architecture can significantly improve medical care, incentive transfer, and data verification, propelling the use of e-health applications.

6.G. Workshop: The European Health Data Space 2: is Europe ready to maximise the re-use of health data?

Abstract The EU's Heads of State called in October 2020 to set up a European Health Data Space (EHDS): “The European Council welcomes the creation of common European data spaces in strategic sectors, and in particular invites the Commission to give priority to the health data space”. As a response, multiple initiatives were set-up to engage the views and expectations from EU member states in the development of the upcoming legislative proposal on the EHDS for primary (EHDS1) and secondary use of health data (EHDS2). One of these was the launch of the Joint Action (JA) Towards the European Health Data Space (TEHDAS) in February 2021. The aim of TEHDAS is to support the European Commission (EC) and Member States (MS), identifying the challenges and providing concepts and options for the EHDS2. It is built on the needs and expectations of national and international stakeholders, citizens’ engagement and existing infrastructure. The major expected outcome of this JA is a sustainable roadmap towards the EHDS2 implementation promoting the cross-border sharing of health data for secondary use. The EHDS2 will benefit population health by facilitating the timely exchange of and access to health data, improving not only the care of patients but also facilitating research, epidemiology, disease prevention and data-based policy decisions. This workshop aims to provide an overview of the preparedness of MS to join the EHDS for secondary use of health data, covering current state-of-play of health data management systems in the EU, barriers on the secondary use of health data, the ongoing work on the development and deployment of the EHDS2 infrastructure and finally, how population health research can benefit from the EHDS2. The workshop will begin with a short introduction on the TEHDAS JA, followed by a presentation on the outcomes of the TEHDAS country visits. In these country visits, the state-of-play of the health data management system and the preparedness to join the EHDS2 were mapped in 12 different EU MS. The next presentation will continue with the results from a study that collected more evidence on the barriers to cross-border sharing of health data for secondary use and options on how to overcome these. It will focus on the legal preparedness and barriers and will discuss how the options proposed by experts in the field align with the legislative proposal for the EHDS2. The audience will be able to give their opinion on the different options through an interactive voting poll during the session. Some of the options on how to overcome technical barriers will be taken further in the development of a pilot infrastructure for the EHDS2. Therefore, the last two presentations will focus on the development and deployment of this pilot infrastructure for the EHDS2 and the role and benefits that population health research will have in it. Throughout the workshop there will be discussion sessions between presentations to allow exchange of knowledge, experiences and opinions with the audience. Key messages • The main outputs will support EU countries to prepare their health data management system for the EHDS2 based on the best practices and actions presented. • The presentations will inform and align participants on the current work on the technical EHDS infrastructure that is being developed for secondary use of health data, the EHDS2.

Results from the TEHDAS country visits: State-of-play of 12 EU member states in relation to the EHDS2

Abstract Successfully launching a sustainable EHDS requires a clear understanding of the current situation in Member States, taking into account the existing diversity. With this in mind, country visits are being carried out in a group of 12 countries: Denmark, Belgium, Hungary, Netherlands, Estonia, Ireland, Portugal, Finland, Czech Republic, Slovenia, Sweden, Germany. The aim of the country visits is to map the state-of-play of health data management in different countries and explore their preparedness to join the EHDS. The topics explored include: the health data sources available, the health data infrastructure (storage, access and interoperability), data quality assurance mechanisms, data governance, as well as resource and training needs and opportunities. Another aim of the country visits is to explore needs and expectations at national level, and how the EHDS can respond to them. This presentation will include an overview of the health data management systems of the 12 countries mapped, providing a snapshot of the situation across Europe. It will then present the findings on their preparedness to join the EHDS. Preparedness takes into account a variety of factors, including political will, as well as legal and technical factors. The presentation will further share the lessons learnt and best practices highlighted from the country visits. Finally, based on these findings, the presentation will close with an overarching view on the preparedness across Europe to deploy the EHDS for the secondary use of health data, EHDS2, as well as planned actions that would facilitate the implementation of the EHDS2 in different member states.

Highly private blockchain-based management system for digital COVID-19 certificates

As a result of the declaration of the COVID-19 pandemic, several proposals of blockchain-based solutions for digital COVID-19 certificates have been presented. Considering that health data have high privacy requirements, a health data management system must fulfil several strict privacy and security requirements. On the one hand, confidentiality of the medical data must be assured, being the data owner (the patient) the actor that maintain control over the privacy of their certificates. On the other hand, the entities involved in the generation and validation of certificates must be supervised by a regulatory authority. This set of requirements are generally not achieved together in previous proposals. Moreover, it is required that a digital COVID-19 certificate management protocol provides an easy verification process and also strongly avoid the risk of forgery. In this paper we present the design and implementation of a protocol to manage digital COVID-19 certificates where individual users decide how to share their private data in a hierarchical system. In order to achieve this, we put together two different technologies: the use of a proxy re-encryption (PRE) service in conjunction with a blockchain-based protocol. Additionally, our protocol introduces an authority to control and regulate the centers that can generate digital COVID-19 certificates and offers two kinds of validation of certificates for registered and non-registered verification entities. Therefore, the paper achieves all the requirements, that is, data sovereignty, high privacy, forgery avoidance, regulation of entities, security and easy verification.

Data management needs assessment for the scale-up of district health information system and introduction of routine (essential) immunization module in Bauchi State, Nigeria, 2015.

Introductionthe National Primary Health Care Development Agency, African Field Epidemiology Network, United States Centers for Disease Control and Prevention and the Bill and Melinda Gates Foundation are implementing a Routine Immunization (RI) Module as part of their Routine Health Data Management System based on the 2013 - 2015 Accountability Framework for RI in Nigeria. To inform planning and evidence-based decision making, a data management needs assessment was conducted in Bauchi state which was one of the states selected for the deployment of the DHIS2 RI module.Methodsdesk reviews were conducted, and a semi-structured questionnaire was administered in four Local Government Areas (LGAs) in Bauchi state that were selected based on the initial evaluation of the performance of all 20 Bauchi LGAs. Ganjuwa and Shira were selected as high-performing LGAs and Alkaleri and Bogoro as low-performing LGAs. Four Health Facilities (HF) were selected in each LGA based on rural or urban classification, type of HFs (private or public), security and accessibility.Resultslocal Immunization Officers (LIOs) prepare monthly reports in high-performing LGAs, and Community Health Care workers are mostly (69%) responsible for report compilation at the HFs. Shira and Alkaleri met 77% and 44% of training indicator targets, respectively, in the previous 12 months. Data recording and reporting was the type of training received the most by health facility personnel. Functioning refrigerators were in all visited LGAs, working thermometer and updated temperature monitoring charts were available in all the cold chain stores. However, no health facility reported having available computers for data-related activities.Conclusionthis assessment provided an improved understanding of the Bauchi state Routine Health Data Management System and informed the content of the state-wide scale-up.

Construction of Sports and Health Data Resources and Transformation of Teachers' Orientation Based on Web Database.

In the intelligent era, emerging information technology helps to transform the information society into an intelligent society and the educational system into a new educational ecology. Teachers must change their roles to be competent for future education and teaching as a result of social transformation, technology application, and education development. Simultaneously, figuring out how to sort sports health data and analyze students' physical health information with a low error rate is an urgent problem that needs to be solved. Data management skills are an unavoidable requirement of the current state of school physical education. Sports health information management will become easier as computer technology advances and the country places a greater emphasis on computer networks. This paper proposes a Web database-based sports health data management system. This paper can help schools understand the relationship between important factors and indicators that affect students' health in order to guide them in making timely changes to their physical education programs. Provide a reasonable sports health plan based on scientific analysis and evaluation to achieve the goal of improving students' physical quality and reducing workload.

Data Mining Algorithm for Physical Health Monitoring of Young Students Based on Big Data.

With the continuous improvement of living standards, the level of physical development of adolescents has improved significantly. The physical functions and healthy development of adolescents are relatively slow and even appear to decline. This paper proposes a novel data mining algorithm based on big data for monitoring of adolescent student's physical health to overcome this problem and enhance young people's physical fitness and mental health. Since big data technology has positive practical significance in promoting young people's healthy development and promoting individual health rights, this article will implement commonly used data mining algorithms and Hadoop/Spark big data processing. The algorithm on different platforms verified that the big data platform has good computing performance for the data mining algorithm by comparing the running time. The current work will prove to be a complete physical health data management system and effectively save, process, and analyze adolescents' physical test data.

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.

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.

Transforming healthcare with blockchain

Sharing medical data with numerous stakeholders for varied purposes is a perplexing problem facing healthcare systems throughout the world. All this needs to be done, whilst ensuring patient and health data privacy and data integrity. Through this paper, an attempt has been made to present a novel distributed digital health record management system. The blockchain framework has been built using the tools provided by hyper ledger, an open source project. This system empowers patients with a comprehensive, secure, immutable, and easily accessible digital record of their health. Also, this information is available across multiple practitioners and healthcare providers throughout the world. This system can therefore empower the emergence of health data economics, empowering researchers with the health data and giving patients an opportunity to share their health data without losing anonymity. The purpose of this paper is to introduce a prototype of a health data management system utilising blockchain.

Integration of the UNHCR Refugee Health Information System into the National Health Information Management System for Uganda.

The Uganda Government, together with development partners, has provided continuing support services (including protection, food, nutrition, healthcare, water and sanitation) to refugee-hosting Districts to successfully manage refugees from different neighbouring countries in established settlements. This service has increased the need for timely and accurate information to facilitate planning, resource allocation and decision-making. Complexity in providing effective public health interventions in refugee settings coupled with increased funding requirements has created demands for better data and improved accountability. Health data management in refugee settings is faced with several information gaps that require harmonisation of the Ugandan National Health Management Information System (UHMIS) and United Nations High Commission for Refugees (UNHCR) Refugee Health Information System (RHIS). This article discusses the rationale for harmonisation of the UNHCR RHIS, which currently captures refugee data, with the UHMIS. It also provides insights into how refugee health data management can be harmonised within a country's national health management information system. A consultative meeting with various stakeholders, including the Ugandan Ministry of Health, district health teams, representatives from UNHCR, the United Nations Children Education Fund (UNICEF), United States Government and civil society organisations, was held with an aim to review the UHMIS and UNHCR RHIS health data management systems and identify ways to harmonise the two to achieve an integrated system for monitoring health service delivery in Uganda. Several challenges facing refugee-hosting district health teams with regard to health data management were identified, including data collection, analysis and reporting. There was unanimous agreement to prioritise an integrated data management system and harmonisation of national refugee stakeholder data requirements, guided by key recommendations developed at the meeting. This article outlines a proposed model that can be used to harmonise the UNHCR RHIS with the UHMIS. The national refugee stakeholder data requirements have been harmonised, and Uganda looks forward to achieving better health data quality through a more comprehensive national UHMIS to inform policy planning and evidence-based decision-making.

A survey of issues and solutions of health data management systems

In the recent era, data science plays an important role in the health-care domain to provide a cost-effective and better treatment procedure. To achieve this goal, the data management system has a huge contribution by controlling, arranging, storing and preprocessing a large volume of health dataset. Already there are a lot of investigation and designing of different approaches to support the big data applications in different domain. Still, management of big data is a challenging task for the data scientist due to the complex characteristics of data and demands of the application. In this survey paper, we discuss the occurring challenges and it’s possible solutions by considering the entities related to data services. It will help the data scientist to understand the supporting parameters of data storage system for designing big data management system.

Use of mobile technology-based participatory mapping approaches to geolocate health facility attendees for disease surveillance in low resource settings

Background Identifying fine-scale spatial patterns of disease is essential for effective disease control and elimination programmes. In low resource areas without formal addresses, novel strategies are needed to locate residences of individuals attending health facilities in order to efficiently map disease patterns. We aimed to assess the use of Android tablet-based applications containing high resolution maps to geolocate individual residences, whilst comparing the functionality, usability and cost of three software packages designed to collect spatial information.ResultsUsing Open Data Kit GeoODK, we designed and piloted an electronic questionnaire for rolling cross sectional surveys of health facility attendees as part of a malaria elimination campaign in two predominantly rural sites in the Rizal, Palawan, the Philippines and Kulon Progo Regency, Yogyakarta, Indonesia. The majority of health workers were able to use the tablets effectively, including locating participant households on electronic maps. For all households sampled (n = 603), health facility workers were able to retrospectively find the participant household using the Global Positioning System (GPS) coordinates and data collected by tablet computers. Median distance between actual house locations and points collected on the tablet was 116 m (IQR 42–368) in Rizal and 493 m (IQR 258–886) in Kulon Progo Regency. Accuracy varied between health facilities and decreased in less populated areas with fewer prominent landmarks.ConclusionsResults demonstrate the utility of this approach to develop real-time high-resolution maps of disease in resource-poor environments. This method provides an attractive approach for quickly obtaining spatial information on individuals presenting at health facilities in resource poor areas where formal addresses are unavailable and internet connectivity is limited. Further research is needed on how to integrate these with other health data management systems and implement in a wider operational context.

Design Considerations in Development of a Mobile Health Intervention Program: The TEXT ME and TEXTMEDS Experience.

BackgroundMobile health (mHealth) has huge potential to deliver preventative health services. However, there is paucity of literature on theoretical constructs, technical, practical, and regulatory considerations that enable delivery of such services.ObjectivesThe objective of this study was to outline the key considerations in the development of a text message-based mHealth program; thus providing broad recommendations and guidance to future researchers designing similar programs.MethodsWe describe the key considerations in designing the intervention with respect to functionality, technical infrastructure, data management, software components, regulatory requirements, and operationalization. We also illustrate some of the potential issues and decision points utilizing our experience of developing text message (short message service, SMS) management systems to support 2 large randomized controlled trials: TEXT messages to improve MEDication adherence & Secondary prevention (TEXTMEDS) and Tobacco, EXercise and dieT MEssages (TEXT ME).ResultsThe steps identified in the development process were: (1) background research and development of the text message bank based on scientific evidence and disease-specific guidelines, (2) pilot testing with target audience and incorporating feedback, (3) software-hardware customization to enable delivery of complex personalized programs using prespecified algorithms, and (4) legal and regulatory considerations. Additional considerations in developing text message management systems include: balancing the use of customized versus preexisting software systems, the level of automation versus need for human inputs, monitoring, ensuring data security, interface flexibility, and the ability for upscaling.ConclusionsA merging of expertise in clinical and behavioral sciences, health and research data management systems, software engineering, and mobile phone regulatory requirements is essential to develop a platform to deliver and manage support programs to hundreds of participants simultaneously as in TEXT ME and TEXTMEDS trials. This research provides broad principles that may assist other researchers in developing mHealth programs.