Adoption of Electronic Medical Records in Healthcare Facilities in the Emirate of Dubai.

OBJECTIVES: This paper aimed to assess the adoption of electronic medical records (EMRs) in healthcare facilities in Dubai, the largest city in the United Arab Emirates (UAE) and a location where extensive healthcare services are provided. It explored the challenges, milestones, and accomplishments associated with this process. METHODS: A situation analysis was conducted by contacting 2,089 healthcare facilities in Dubai to determine whether they had implemented EMR in their medical practices and to identify the challenges they faced during this process. Additionally, the Electronic Medical Record Adoption Model (EMRAM) was utilized to measure the maturity level of hospitals in terms of EMR adoption. The EMRAM stages were rated on a scale from 0 to 7, with 0 representing the least mature stage and 7 the most mature. RESULTS: By September 2023, all hospitals (100%, n = 54) and 75% of private clinics (n = 1,460) in Dubai had implemented EMRs. Several challenges were identified, including the absence of EMRs within the healthcare facility, having an EMR with a low EMRAM score, or the lack of a unified interoperability standard. Additionally, the absence of a clear licensing program for EMR vendors, whether standalone or cloud-based, was among the other challenges noted. CONCLUSIONS: EMR implementation in healthcare facilities in Dubai is at a mature stage. However, further efforts are required at both the decision-making and technical levels. We believe that our experience can benefit other countries in the region in implementing EMRs and using EMRAM to assess their health information systems.

The use and perceived value of electronic health information resources by health care professionals in the field of medicine, pharmacy, and nursing in Jazan province, Saudi Arabia.

Background: Healthcare workers increasingly use Electronic Health Information Resources (EHIRs) to make evidence-based decisions. Our study was intended to assess the perception, attitude, and practice of healthcare professionals in medicine, pharmacy, and nursing regarding their perceived value and use of EHIRs. Methods: We conducted an observational cross-sectional study using a pre-validated questionnaire among healthcare professionals in Jazan province from September 2022 to February 2023. We included healthcare professionals and interns with medical, pharmacy, or nursing degrees and excluded those who refused informed consent. Results: We included fully completed data from 294 participants, with an actual response rate of just 80.1 %. Almost 87.41 % utilized the health information resources at their workplace, with UpToDate [39.45 %] and Medscape [67.01 %] being the most frequently used medical databases. The health facilities' access to electronic health resources significantly impacted healthcare professionals' [p = 0.04] and medical interns' [p = 0.02] roles. Faculty members felt the need to access electronic health information at their workplace [p = 0.00]. Lack of time to access electronic health information due to a busy schedule was a significant reason that impacted the attitude of medical professionals [p = 0.008] and nursing staff [p = 0.025]. An excessive amount of clinically unrelated data was the primary obstacle (181/294, p < 0.0001) in using electronic health information resources. Conclusion: Our study showed the pattern of healthcare professionals using EHIRs in the Jazan province, Saudi Arabia. We believe the study's outcome can help increase the calibre of electronic health information services available to healthcare professionals and raise awareness of different EHIRs in improving clinical care.

Greens appraisal of validated stability indicating RP-HPLC method and forced degradation study for quantification of Ebastine in wastewater and dosage form.

OBJECTIVES: Allergic rhinitis and chronic idiopathic urticaria are common conditions triggered by environmental irritants, stress, and certain foods. The FDA has recently announced that the efficacy and safety of Ebastine (EBS) have been thoroughly evaluated and confirmed. This study considered using various tools to assess their greenness. We used AGREEprep, analytical eco-scale (ESA), and analytical method volume intensity (AMVI) to evaluate the greenness of the validated stability-indicating method and a forced degradation study. This allowed for easy determination and quantitation of EBS in wastewater and dosage form. METHODS: The method was established on Symmetry RP-C18 (150mm×4.6mm,5µm) using mobile phase, which can be prepared by mixing buffer solution of pH 3 with acetonitrile in a ratio of (37.5: 62.5, v/v) in addition to dissolving 0.72 gm of sodium lauryl sulfate in the final solution. The separation process was executed at a flow rate of 1.5mL/min and 5µL injection volume with UV detection at 254nm. Linearity was conducted for EBS in the 5-50µg/mL range. Different validation parameters were investigated, including accuracy, precision, robustness, and specificity. RESULTS: The limits of both detection and quantification were 0.84µg/mL and 2.57µg/mL for EBS. The recovery percentages of EBS were found to be 101.01% and 101.02% for wastewater and pharmaceutical formulations, respectively. CONCLUSION: According to International Council for Harmonisation (ICH) guidelines, a forced degradation study of EBS was evaluated, including acid, base hydrolysis, and oxidative hydrolysis using hydrogen peroxide and photolytic and thermal degradation. The highest degradation was achieved by acid hydrolysis. The safety and efficacy of EBS were evaluated via a safety comparative profile study.

COVID-19 Vaccine Hesitancy among Population in Jazan Region of Saudi Arabia.

COVID-19 vaccine acceptance and refusal vary across countries and among different socio-demographic groups. This study investigates hesitancy related to the COVID-19 vaccine and the associated factors in the rural-community-dominated Jazan Province, Saudi Arabia. A cross-sectional study through an online questionnaire was conducted from February to April 2021 to investigate the extent of vaccine hesitancy related to the COVID-19 vaccine and the associated factors in the Jazan region. A Chi-squared test and post hoc analysis were conducted to analyze the statistical significance of the association between variables. Of the 569 participants who completed the online questionnaire, the majority were males (81.5%) and had a university education (72.6%). Of the participants, more than one-third (36.9%) were hesitant to vaccinate. Concern about adverse side effects following vaccination was the most reported reason for vaccine hesitancy (42.6%), followed by beliefs that the vaccine was unsafe or ineffective (15.5%). The data analysis revealed that people who lived in cities in Jazan Province or those who did not have a family history of COVID-19 infection were more likely to be vaccine hesitant. It is more important than ever to develop and implement community-based strategies to address vaccine hesitancy, especially in rural areas.

Chromatographic Techniques for Assessment of Bisoprolol Fumarate and Perindopril Arginine in Solid Formulations under Various Stress Conditions and Application to Six Sigma, Content Uniformity, and Comparative Dissolution Approaches.

BACKGROUND: Antihypertensives bisoprolol fumarate (BIS) and perindopril arginine (PER) were simultaneously determined in their pure, bulk, and combined tablet dosage form. OBJECTIVE: This study develops a novel, reproducible, and accurate Reversed phase high-performance liquid chromatography (RP-HPLC) and Reversed phase ultra-performance liquid chromatography (RP-UPLC) with photodiode array detection techniques, which were then applied to in vitro dissolution studies. METHODS: The first RP-HPLC method relied on isocratic elution using a mobile phase of methanol-0.05 M phosphate buffer pH 2.6 (1 + 1, by volume), and separation was performed using a Thermo Hypersil C8 column (150 mm × 4.6 mm, 5 µm). Ion-pair UPLC was the second method. An acceptable resolution was achieved using an RP-C18 chromatographic column, Agilent Eclipse (100 × 2.1 mm, 1.7 µm), with a mobile phase containing 0.005 M sodium 1-heptane sulfonate-triethylamine (64 + 1 + 35, by volume), adjusted with phosphoric acid to a pH of 2.0. RP-HPLC used a 1.0 mL/min flow rate, while UPLC used 0.5 mL/min, and the two methods used detection at 210 nm. RESULTS: Calibration curves of BIS and PER were linear for RP-HPLC and RP-UPLC methods at 0.5-15 and 0.5-40 µg/mL, respectively. BIS and PER had RP-UPLC LODs of 0.22 and 0.10 µg/mL, respectively, and LOQs of 0.68 and 0.31 µg/mL, respectively. As a result, the approach has been effectively applied to in vitro dissolution testing for drugs in generic and reference products, showing that the two products are comparable. The Six Sigma approach was implemented to compare the recommended and United States Pharmacopeia (USP) procedures, which both exhibited process capability index (Cpk) >1.33. A content uniformity test demonstrated that the drugs in their dosage form met the acceptance limit (85-115%). The degradation products were reliably distinguished from pure drugs for a range of retention times. CONCLUSION: In their commercial drug product, the proposed method could be used in QC laboratories for concurrent testing, content uniformity, and in vitro dissolution investigations of BIS and PER. The methods were successfully validated per International Council for Harmonisation (ICH) guidelines. HIGHLIGHTS: This study is innovative since it is the first to establish and validate specific and reproducible UPLC and HPLC methods for the concurrent quantitation of the studied drugs in their binary mixture and application to lean Six Sigma, content uniformity, and comparative dissolution approaches.

Unlocking the eHealth professionals' career pathways: A case of Gulf Cooperation Council countries.

BACKGROUND: During the past two decades, various sectors and industries have undergone digital transformation. Healthcare is poised to make a full transformation in the near future. Although steps have been taken toward creating an infrastructure for digital health in the Middle East, as it stands, digital health is still an emerging field here. The current global health care crisis has underscoredthe need for digitization of the healthcare sector to provide high-value, high-quality care and knowledge generation. With the advent of digital transformation in countries around the globe, there is a rising demand for investment and innovation in health information technology. With the demand for health informatics (HI) graduates in different disciplines (e.g., healthcare professions, information technology, etc.), there is an urgent need to determine and regulate clear career pathways and the core competencies necessary for digital health professional to practice effectively and to allow technology to add value to the healthcare systems. Given the changing landscape of the profession, the Kingdom of Saudi Arabia (KSA) and the Gulf Cooperation Council (GCC) countries are experiencing a rising demand to produce digital health professionals who can meet the needs of all the stakeholders involved, including patients, healthcare professionals, managers, and policymakers. However, despite the number of region-wide initiatives in the form of training programs, there remains a knowledge-practice gap and unclear job roles within the HI community. In recent years, regional digital health workforce initiatives have been put forward, such as the GCC Taskforce on Workforce Development in Digital Healthcare. The taskforce initiated a survey and several workshops to identify and classify HI disciplines according to the needs of the job market and through comparisons with similar efforts developed across the globe, such as the TIGER project and the EU*US eHealth Work project. Digital health implementation has been flourishing in the Middle East for the past 15 years. During this period, while digital health professions have been thriving in the industry to deliver tools and technologies, academic institutions have offered some amount of training and education in digital health; however, the career pathway for digital health professionals is not clear due to mismatch about the qualifications, skills, competencies and experience needed by the healthcare industry. OBJECTIVES: Due to this discrepancy between the academic curriculum and the skills needed in the healthcare industry, the objectives of this study are to define the career pathway for eHealth professions and identify the challenges experienced by academic institutions and the industry in describing digital health professionals. METHODS: We elicited qualitative data by conducting six focus groups with individuals from different professional backgrounds, including healthcare workers, information managers, computer sciences professionals, and workers in the revenue cycle who participated in a workshop on November 2-3, 2019, in Dubai. All focus group sessions were audio-recorded and transcribed, and participants were de-identified before analysis. An exploratory method was used to identify themes and subthemes. Saturation was reached when similar responses were found during the analysis. In this study, we found that respondents clearly defined eHealth career pathways based on criteria that included qualifications, experience, job scope, and competency. We also explored the challenges that the respondents encountered, including differences in the required skill sets and training and the need to standardize the academic curriculum across the GCC region, to recognize the various career pathways, and to develop local training programs. Additionally, country-specific projects have been initiated, such as the competency-based Digital Health framework, which was developed by the Saudi Commission of Healthcare Specialties (SCFHS) in 2018. Competency-based digital health frameworks generally include relevant job definitions, roles, and recommended competencies. Both the GCC taskforce and the Saudi studies capitalized on previous efforts by professional organizations, including Canada's Digital Health formerly known as (COACH), the U.S. Office of the National Coordinator for Health Information Technology (ONC), the American Medical Informatics Association (AMIA), and the Health Information and Management Systems Society (HIMSS). RESULTS: In this study, we found that respondents defined eHealth career pathways based on different criteria such as: qualifications; various background of health and IT in the HI field; work experiences; job scope and competency. We also further explore the challenges that the respondents encountered which delineates four key aspects such as need of hybrid skills to manage the digital transformation, need of standardization of academic curriculum across GCC, recognition of the career pathways by the industry in order to open up career opportunity and career advancement, and availability of local training programs for up-skilling the current health workforce. CONCLUSION: We believe that successful health digital transformation is not limited to technology advancement but requires an adaptive change in: the related competency-based frameworks, the organisation of work and career paths for eHealth professionals, and the development of educational programmes and joint degrees to equip clinicians with understanding of technology, and informaticians with understanding of healthcare. We anticipate that this work will be expanded and adopted by relevant professional and scientific bodies in the GCC region.

Delivering Digital Healthcare for Elderly: A Holistic Framework for the Adoption of Ambient Assisted Living.

Adoption of Ambient Assisted Living (AAL) technologies for geriatric healthcare is suboptimal. This study aims to present the AAL Adoption Diamond Framework, encompassing a set of key enablers/barriers as factors, and describe our approach to developing this framework. A systematic literature review was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. SCOPUS, IEEE Xplore, PubMed, ProQuest, Science Direct, ACM Digital Library, SpringerLink, Wiley Online Library and grey literature were searched. Thematic analysis was performed to identify factors reported or perceived to be important for adopting AAL technologies. Of 3717 studies initially retrieved, 109 were thoroughly screened and 52 met our inclusion criteria. Nineteen unique technology adoption factors were identified. The most common factor was privacy (50%) whereas data accuracy and affordability were the least common factors (4%). The highest number of factors found per a given study was eleven whereas the average number of factors across all studies included in our sample was four (mean = 3.9). We formed an AAL technology adoption framework based on the retrieved information and named it the AAL Adoption Diamond Framework. This holistic framework was formed by organising the identified technology adoption factors into four key dimensions: Human, Technology, Business, and Organisation. To conclude, the AAL Adoption Diamond Framework is holistic in term of recognizing key factors for the adoption of AAL technologies, and novel and unmatched in term of structuring them into four overarching themes or dimensions, bringing together the individual and the systemic factors evolving around the adoption of AAL technology. This framework is useful for stakeholders (e.g., decision-makers, healthcare providers, and caregivers) to adopt and implement AAL technologies.

Exploring the Influential Factors of Consumers' Willingness Toward Using COVID-19 Related Chatbots: An Empirical Study.

BACKGROUND: Consumers' willingness to use health chatbots can eventually determine if the adoption of health chatbots will succeed in delivering healthcare services for combating COVID-19. However, little research to date has empirically explored influential factors of consumer willingness toward using these novel technologies, and the effect of individual differences in predicting this willingness. OBJECTIVES: This study aims to explore (a) the influential factors of consumers' willingness to use health chatbots related to COVID-19, (b) the effect of individual differences in predicting willingness, and (c) the likelihood of using health chatbots in the near future as well as the challenges/barriers that could hinder peoples' motivations. METHODS: An online survey was conducted which comprised of two sections. Section one measured participants' willingness by evaluating the following six factors: performance efficacy, intrinsic motivation, anthropomorphism, social influence, facilitating conditions, and emotions. Section two included questions on demographics, the likelihood of using health chatbots in the future, and concerns that could impede such motivation. RESULTS: A total of 166 individuals provided complete responses. Although 40% were aware of health chatbots and only 24% had used them before, about 84% wanted to use health chatbots in the future. The strongest predictors of willingness to use health chatbots came from the intrinsic motivation factor whereas the next strongest predictors came from the performance efficacy factor. Nearly 39.5% of participants perceived health chatbots to have human-like features such as consciousness and free will, but no emotions. About 38.4% were uncertain about the ease of using health chatbots. CONCLUSION: This study contributes toward theoretically understanding factors influencing peoples' willingness to use COVID-19-related health chatbots. The findings also show that the perception of chatbots' benefits outweigh the challenges.

Health Apps for Combating COVID-19: Descriptive Review and Taxonomy.

BACKGROUND: Mobile phone apps have been leveraged to combat the spread of COVID-19. However, little is known about these technologies' characteristics, technical features, and various applications in health care when responding to this public health crisis. The lack of understanding has led developers and governments to make poor choices about apps' designs, which resulted in creating less useful apps that are overall less appealing to consumers due to their technical flaws. OBJECTIVE: This review aims to identify, analyze, and categorize health apps related to COVID-19 that are currently available for consumers in app stores; in particular, it focuses on exploring their key technical features and classifying the purposes that these apps were designed to serve. METHODS: A review of health apps was conducted using the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews) guidelines. The Apple Store and Google Play were searched between April 20 and September 11, 2020. An app was included if it was dedicated for this disease and was listed under the health and medical categories in these app stores. The descriptions of these apps were extracted from the apps' web pages and thematically analyzed via open coding to identify both their key technical features and overall purpose. The characteristics of the included apps were summarized and presented with descriptive statistics. RESULTS: Of the 298 health apps that were initially retrieved, 115 met the inclusion criteria. A total of 29 technical features were found in our sample of apps, which were then categorized into five key purposes of apps related to COVID-19. A total of 77 (67%) apps were developed by governments or national authorities and for the purpose of promoting users to track their personal health (9/29, 31%). Other purposes included raising awareness on how to combat COVID-19 (8/29, 27%), managing exposure to COVID-19 (6/29, 20%), monitoring health by health care professionals (5/29, 17%), and conducting research studies (1/29, 3.5%). CONCLUSIONS: This study provides an overview and taxonomy of the health apps currently available in the market to combat COVID-19 based on their differences in basic technical features and purpose. As most of the apps were provided by governments or national authorities, it indicates the essential role these apps have as tools in public health crisis management. By involving most of the population in self-tracking their personal health and providing them with the technology to self-assess, the role of these apps is deemed to be a key driver for a participatory approach to curtail the spread of COVID-19. Further effort is required from researchers to evaluate these apps' effectiveness and from governmental organizations to increase public awareness of these digital solutions.

A multi-perspective approach to developing the Saudi Health Informatics Competency Framework.

BACKGROUND: Determining the key sets of competencies necessary for a Health Informatics (HI) professional to practice effectively either solo or as a member of a multidisciplinary team has been challenging for the regulator and registration body responsible for the healthcare workforce in Saudi Arabia, which is the Saudi Commission for Health Specialties (SCFHS). OBJECTIVE: The aim of this study was to develop a HI competency framework to guide SCFHS to introduce a HI certification program that meets local healthcare needs and is aligned with the national digital health transformation strategy. METHODOLOGY: A two-phase mixed methods approach was used in this study. For phase 1, a scoping review was conducted to identify HI competencies that have been published in the relevant literature. Out of a total 116 articles found relevant, 20 were included for further analysis. For phase 2, Saudi HI stakeholders (N = 24) that included HI professionals, administrators, academics, and healthcare professionals were identified and participated in an online survey, and asked to rank the importance of HI competencies distinguished in phase 1. To further validate and contextualize the competency framework, multiple focus groups and expert panel meetings were undertaken with the key stakeholders. RESULTS: For phase 1, about 1315 competencies were initially extracted from the included studies. After iterative reviews and refinements of codes and themes, 6 preliminary domains, 23 sub-domains and 152 competencies were identified. In phase 2, a total of 24 experts participated in the online surveys and ranked 58 out of 152 competencies as 'very important/required', each received 75 % or more of votes. The remaining competencies (N = 94) were included in a list for a further discussion in the focus groups. A Total of fourteen HI experts accepted and joined in the focus groups. The multiphase approach resulted in a competency framework that included 92 competencies, that were grouped into 6 domains and 22 subdomains. The six key domains are: Core Principles; Information and Communication Technology (ICT); Health Sciences; Health Data Analytics; Education and Research; Leadership and Management. CONCLUSION: The study developed the Saudi Health Informatics Competency Framework (SHICF) that is based on an iterative, evidence-based approach, with validation from key stakeholders. Future work should continue the validation, review, and development of the framework with continued collaboration from relevant stakeholders representing both the healthcare and educational communities. We anticipate that this work will be expanded and adopted by relative professional and scientific bodies in the Gulf Cooperation Council (GCC) region.

Health Chatbots for Fighting COVID-19: a Scoping Review.

BACKGROUND: Health chatbots are rising in popularity and capability for fighting the novel SARS-CoV-2 coronavirus (COVID-19). OBJECTIVES: This study aims to review the current literature on COVID-19 related chatbots in healthcare, identify and characterize these emerging technologies and their applications for combating COVID-19, and describe related challenges. METHODS: The authors conducted a scoping review of peer-reviewed literature on COVID-19, guided by the Arksey and O'Malley framework. PubMed/MEDLINE and Google Scholar were searched over a period between January and September 2020 by using the keywords "COVID* chatbot", "virtual assistant", "AI enabled platform COVID" and associated synonyms. Relevant studies' references were checked for further articles. The content of these studies was screened and thematically analyzed by the two authors. RESULTS: Out of 543 articles initially identified, 9 were eligible for inclusion. Studies describing chatbots' development and architecture (n=6) were the most common, and only 3 empirical studies on the user experience were identified. Our scoping review identified five key applications of the current health chatbots, which were: disseminating health information and knowledge; self-triage and personal risk assessment; monitoring exposure and notifications; tracking COVID-19 symptoms and health aspects; and combating misinformation and fake news. Furthermore, these technologies can accomplish the following tasks: ask and answer questions; create health records and history of use; complete forms and generate reports; and take simple actions. Nonetheless, the use of health chatbots poses many challenges both at the level of the social system (i.e., consumers' acceptability) as well as the technical system (i.e., design and usability). CONCLUSION: Using health chatbots to combat COVID-19 is a practice still in its infancy. We believe that our work will help researchers in this domain gain better understanding of this novel technology's design and applications, which are needed for continuous improvement in the health chatbots' functionalities and their usefulness to fight COVID-19.

Perceived Utilities of COVID-19 Related Chatbots in Saudi Arabia: a Cross-sectional Study.

INTRODUCTION: Health chatbots are increasingly being utilized in healthcare to combat COVID-19. However, few studies have explored the perception and willingness of end-users toward COVID-19-related chatbots. Furthermore, no studies have been conducted in Saudi Arabia. AIM: This paper explored 166 end-users' perceived utilities of health chatbots in Saudi Arabia, and how their characteristics affect their perceptions. METHODS: We conducted a quantitative descriptive study by implementing an online survey. The survey asked 20 questions on participants' demographics and their perception of health chatbots' usefulness. RESULTS: We found that users were more willing to use health chatbots to seek general information about COVID-19 (82.5%) over seeking information regarding COVID-19 medical treatments (72.3%). Furthermore, participants with undergraduate degrees tend to use them to learn how to prevent COVID-19's spread (P = 0.015), to self-track COVID-19 symptoms (P = 0.028), and to seek information about medication (P = 0.035) in comparison to those who had postgraduate degrees. Participants who frequently searched for health information on the internet were more likely to look for nearby medical services using health chatbots (P = 0.023). Lastly, participants who provided any sort of healthcare services information were more likely to self-assess COVID-19 symptoms by using health chatbots (P = 0.036). CONCLUSION: Participant awareness and use of health chatbots were low; however, most had positive perceptions of these emerging technologies and displayed willingness to use them. Further research is needed to capture the real-world usability of these novel technologies by employing more rigid methodological designs (e.g, field trials).

Developing a Saudi Health Informatics Competency Framework: A Comparative Assessment.

In 2018, the Saudi Commission for Health Specialties (SCFHS) created a national working group composed of key health informatics (HI) professionals, researchers and educators tasked with the development of a draft competency framework for Saudi HI professionals. Over an eight-month period, the research group collected data obtained from literature sources (both academic and grey), international competency standards, participant surveys, focus groups, and expert panel reviews. Through multiple rounds of discussions and graphic visualisation of the information collected using Microsoft PowerPoint and flip charts, the data were summarised and a visual representation of the proposed SHICF was developed. The result of this effort was the development of the first Saudi Health Informatics Competency Framework (SHICF). This paper provides a comparative assessment between the Saudi HI competency framework development and that of other internationally recognised HI competency development frameworks. Challenges related to the development of the SHICF are also discussed.

Development and Validation of a Taxonomy for Characterizing Measurements in Health Self-Quantification.

BACKGROUND: The use of wearable tools for health self-quantification (SQ) introduces new ways of thinking about one's body and about how to achieve desired health outcomes. Measurements from individuals, such as heart rate, respiratory volume, skin temperature, sleep, mood, blood pressure, food consumed, and quality of surrounding air can be acquired, quantified, and aggregated in a holistic way that has never been possible before. However, health SQ still lacks a formal common language or taxonomy for describing these kinds of measurements. Establishing such taxonomy is important because it would enable systematic investigations that are needed to advance in the use of wearable tools in health self-care. For a start, a taxonomy would help to improve the accuracy of database searching when doing systematic reviews and meta-analyses in this field. Overall, more systematic research would contribute to build evidence of sufficient quality to determine whether and how health SQ is a worthwhile health care paradigm. OBJECTIVE: The aim of this study was to investigate a sample of SQ tools and services to build and test a taxonomy of measurements in health SQ, titled: the classification of data and activity in self-quantification systems (CDA-SQS). METHODS: Eight health SQ tools and services were selected to be examined: Zeo Sleep Manager, Fitbit Ultra, Fitlinxx Actipressure, MoodPanda, iBGStar, Sensaris Senspod, 23andMe, and uBiome. An open coding analytical approach was used to find all the themes related to the research aim. RESULTS: This study distinguished three types of measurements in health SQ: body structures and functions, body actions and activities, and around the body. CONCLUSIONS: The CDA-SQS classification should be applicable to align health SQ measurement data from people with many different health objectives, health states, and health conditions. CDA-SQS is a critical contribution to a much more consistent way of studying health SQ.

Person-generated Data in Self-quantification. A Health Informatics Research Program.

OBJECTIVES: The availability of internet-connected mobile, wearable and ambient consumer technologies, direct-to-consumer e-services and peer-to-peer social media sites far outstrips evidence about the efficiency, effectiveness and efficacy of using them in healthcare applications. The aim of this paper is to describe one approach to build a program of health informatics research, so as to generate rich and robust evidence about health data and information processing in self-quantification and associated healthcare and health outcomes. METHODS: The paper summarises relevant health informatics research approaches in the literature and presents an example of developing a program of research in the Health and Biomedical Informatics Centre (HaBIC) at the University of Melbourne. The paper describes this program in terms of research infrastructure, conceptual models, research design, research reporting and knowledge sharing. RESULTS: The paper identifies key outcomes from integrative and multiple-angle approaches to investigating the management of information and data generated by use of this Centre's collection of wearable, mobiles and other devices in health self-monitoring experiments. These research results offer lessons for consumers, developers, clinical practitioners and biomedical and health informatics researchers. CONCLUSIONS: Health informatics is increasingly called upon to make sense of emerging self-quantification and other digital health phenomena that are well beyond the conventions of healthcare in which the field of informatics originated and consolidated. To make a substantial contribution to optimise the aims, processes and outcomes of health self-quantification needs further work at scale in multi-centre collaborations for this Centre and for health informatics researchers generally.

Refining the Concepts of Self-quantification Needed for Health Self-management. A Thematic Literature Review.

BACKGROUND: Questions like 'How is your health? How are you feeling? How have you been?' now can be answered in a different way due to innovative health self-quantification apps and devices. These apps and devices generate data that enable individuals to be informed and more responsible about their own health. OBJECTIVES: The aim of this paper is to review studies on health SQ, firstly, exploring the concepts that are associated with the users' interaction with and around data for managing health; and secondly, the potential benefits and challenges that are associated with the use of such data to maintain or promote health, as well as their impact on the users' certainty or confidence in taking effective actions upon such data. METHODS: To answer these questions, we conducted a comprehensive literature review to build our study sample. We searched a number of electronic bibliographic databases including Scopus, Web of Science, Medline, and Google Scholar. Thematic analysis was conducted for each study to find all the themes that are related to our research aims. RESULTS: In the reviewed literature, conceptualisation of health SQ is messy and inconsistent. Personal tracking, personal analytics, personal experimentation, and personal health activation are different concepts within the practice of health SQ; thus, a new definition and structure is proposed to set out boundaries between them. Using the data that are generated by SQS for managing health has many advantages but also poses many challenges. CONCLUSIONS: Inconsistency in conceptualisation of health SQ - as well as the challenges that users experience in health self-management - reveal the need for frameworks that can describe the users' health SQ practice in a holistic and consistent manner. Our ongoing work toward developing these frameworks will help researchers in this domain to gain better understanding of this practice, and will enable more systematic investigations which are needed to improve the use of SQS and their data in health self-management.

Activity Theory as a Theoretical Framework for Health Self-Quantification: A Systematic Review of Empirical Studies.

BACKGROUND: Self-quantification (SQ) is a way of working in which, by using tracking tools, people aim to collect, manage, and reflect on personal health data to gain a better understanding of their own body, health behavior, and interaction with the world around them. However, health SQ lacks a formal framework for describing the self-quantifiers' activities and their contextual components or constructs to pursue these health related goals. Establishing such framework is important because it is the first step to operationalize health SQ fully. This may in turn help to achieve the aims of health professionals and researchers who seek to make or study changes in the self-quantifiers' health systematically. OBJECTIVE: The aim of this study was to review studies on health SQ in order to answer the following questions: What are the general features of the work and the particular activities that self-quantifiers perform to achieve their health objectives? What constructs of health SQ have been identified in the scientific literature? How have these studies described such constructs? How would it be possible to model these constructs theoretically to characterize the work of health SQ? METHODS: A systematic review of peer-reviewed literature was conducted. A total of 26 empirical studies were included. The content of these studies was thematically analyzed using Activity Theory as an organizing framework. RESULTS: The literature provided varying descriptions of health SQ as data-driven and objective-oriented work mediated by SQ tools. From the literature, we identified two types of SQ work: work on data (ie, data management activities) and work with data (ie, health management activities). Using Activity Theory, these activities could be characterized into 6 constructs: users, tracking tools, health objectives, division of work, community or group setting, and SQ plan and rules. We could not find a reference to any single study that accounted for all these activities and constructs of health SQ activity. CONCLUSIONS: A Health Self-Quantification Activity Framework is presented, which shows SQ tool use in context, in relation to the goals, plans, and competence of the user. This makes it easier to analyze issues affecting SQ activity, and thereby makes it more feasible to address them. This review makes two significant contributions to research in this field: it explores health SQ work and its constructs thoroughly and it adapts Activity Theory to describe health SQ activity systematically.

Quantifying the Activities of Self-quantifiers: Management of Data, Time and Health.

Current self-quantification systems (SQS) are limited in their ability to support the acquisition of health-related information essential for individuals to make informed decisions based on their health status. They do not offer services such as data handling and data aggregation in a single place, and using multiple types of tools for this purpose complicates data and health self-management for self-quantifiers. An online survey was used to elicit information from self-quantifiers about the methods they used to undertake key activities related to health self-management. This paper provides empirical evidence about self-quantifiers' time spent using different data collection, data handling, data analysis, and data sharing tools and draws implications for health self-management activities.

The use of self-quantification systems for personal health information: big data management activities and prospects.

BACKGROUND: Self-quantification is seen as an emerging paradigm for health care self-management. Self-quantification systems (SQS) can be used for tracking, monitoring, and quantifying health aspects including mental, emotional, physical, and social aspects in order to gain self-knowledge. However, there has been a lack of a systematic approach for conceptualising and mapping the essential activities that are undertaken by individuals who are using SQS in order to improve health outcomes. In this paper, we propose a new model of personal health information self-quantification systems (PHI-SQS). PHI-SQS model describes two types of activities that individuals go through during their journey of health self-managed practice, which are 'self-quantification' and 'self-activation'. OBJECTIVES: In this paper, we aimed to examine thoroughly the first type of activity in PHI-SQS which is 'self-quantification'. Our objectives were to review the data management processes currently supported in a representative set of self-quantification tools and ancillary applications, and provide a systematic approach for conceptualising and mapping these processes with the individuals' activities. METHOD: We reviewed and compared eleven self-quantification tools and applications (Zeo Sleep Manager, Fitbit, Actipressure, MoodPanda, iBGStar, Sensaris Senspod, 23andMe, uBiome, Digifit, BodyTrack, and Wikilife), that collect three key health data types (Environmental exposure, Physiological patterns, Genetic traits). We investigated the interaction taking place at different data flow stages between the individual user and the self-quantification technology used. FINDINGS: We found that these eleven self-quantification tools and applications represent two major tool types (primary and secondary self-quantification systems). In each type, the individuals experience different processes and activities which are substantially influenced by the technologies' data management capabilities. CONCLUSIONS: Self-quantification in personal health maintenance appears promising and exciting. However, more studies are needed to support its use in this field. The proposed model will in the future lead to developing a measure for assessing the effectiveness of interventions to support using SQS for health self-management (e.g., assessing the complexity of self-quantification activities, and activation of the individuals).

Proposal for a Standardised Reporting Guideline to Annotate Health-related Self-Quantification Experiments.

Self-monitoring experiments are becoming increasingly common as it is the case in other complex environments their interpretation and reproducibility relies heavily in the amount of associated meta-data available. In this work we propose a standardised reporting guideline to annotate these experiments and facilitate their interpretation. The existence of such reporting guideline may lead the development of future standards that would facilitate platform interoperability, data sharing and the improvement in the interpretation of such experiments as well as their reproducibility.