Open-source mobile digital platform for clinical trial data collection in low-resource settings

Enhancing asthma research and improving health equity through decentralized clinical trials (DCTs) and mHealth technology

The COVID-19 pandemic led to widespread disruption and termination of clinical research and a prompt adoption of mobile health (mHealth) technologies in the healthcare space. As the United States' healthcare system has rapidly become reliant on remotely conducted activities, the implementation of decentralized methods using mHealth technology in research investigation has become a necessary alternative to traditional in-person cohort studies. The aim of this article is to: report successful and unsuccessful examples of remote asthma clinical studies, explore the benefits and potential drawbacks of virtual clinical investigation, discuss the potential impact on equity and representation in asthma research, and provide suggestions through which investigators can implement decentralized clinical trials. Enhanced study accessibility, participant diversity, safety measures, and research efficacy are some of the benefits identified with a focused discussion on the impact on equity that decentralized clinical trials renders. Furthermore, potential concerns regarding regulatory compliance, data privacy, and effective mHealth design and solutions are discussed. Despite the setbacks and interruptions faced by the study participants and investigators due to the pandemic, the transition to decentralized clinical studies using mHealth technology is a positive, feasible step toward innovation and equity in the allergy and immunology field.

Using Principles of Digital Development for a Smartphone App to Support Data Collection in Patients With Acute Myocardial Infarction and Physical Activity Intolerance: Case Study

BACKGROUND

Advances in health have highlighted the need to implement technologies as a fundamental part of the diagnosis, treatment, and recovery of patients at risk of or with health alterations. For this purpose, digital platforms have demonstrated their applicability in the identification of care needs. Nursing is a fundamental component in the care of patients with cardiovascular disorders and plays a crucial role in diagnosing human responses to these health conditions. Consequently, the validation of nursing diagnoses through ongoing research processes has become a necessity that can significantly impact both patients and health care professionals.

OBJECTIVE

We aimed to describe the process of developing a mobile app to validate the nursing diagnosis "intolerance to physical activity" in patients with acute myocardial infarction.

METHODS

We describe the development and pilot-testing of a mobile system to support data collection for validating the nursing diagnosis of activity intolerance. This was a descriptive study conducted with 11 adults (aged ≥18 years) who attended a health institution for highly complex needs with a suspected diagnosis of coronary syndrome between August and September 2019 in Floridablanca, Colombia. An app for the clinical validation of activity intolerance (North American Nursing Diagnosis Association [NANDA] code 00092) in patients with acute coronary syndrome was developed in two steps: (1) operationalization of the nursing diagnosis and (2) the app development process, which included an evaluation of the initial requirements, development and digitization of the forms, and a pilot test. The agreement level between the 2 evaluating nurses was evaluated with the κ index.

RESULTS

We developed a form that included sociodemographic data, hospital admission data, medical history, current pharmacological treatment, and thrombolysis in myocardial infarction risk score (TIMI-RS) and GRACE (Global Registry of Acute Coronary Events) scores. To identify the defining characteristics, we included official guidelines, physiological measurements, and scales such as the Piper fatigue scale and Borg scale. Participants in the pilot test (n=11) had an average age of 63.2 (SD 4.0) years and were 82% (9/11) men; 18% (2/11) had incomplete primary schooling. The agreement between the evaluators was approximately 80% for most of the defining characteristics. The most prevalent characteristics were exercise discomfort (10/11, 91%), weakness (7/11, 64%), dyspnea (3/11, 27%), abnormal heart rate in response to exercise (2/10, 20%), electrocardiogram abnormalities (1/10, 9%), and abnormal blood pressure in response to activity (1/10, 10%).

CONCLUSIONS

We developed a mobile app for validating the diagnosis of "activity intolerance." Its use will guarantee not only optimal data collection, minimizing errors to perform validation, but will also allow the identification of individual care needs.

Opportunities and challenges for decentralised clinical trials in sub-Saharan Africa: a qualitative study

INTRODUCTION

Digital health has gained traction in research and development, and clinical decision support systems. The COVID-19 pandemic accelerated the adoption of decentralised clinical trials (DCTs) as a mitigation and efficiency improvement strategy. We assessed the opportunities and challenges of a digital transformation in clinical research in sub-Saharan Africa from different stakeholders' perspectives.

METHODS

A qualitative study, including 40 in-depth semi structured interviews, was conducted with investigators of three leading research institutions in sub-Saharan Africa and Switzerland, contract research organisations and sponsors managing clinical trials in sub-Saharan Africa. A thematic approach was used for the analysis.

RESULTS

Interviewees perceived DCTs as an opportunity for trial efficiency improvement, quality improvement and reducing the burden of people participating in clinical trials. However, to gain and maintain an optimal quality of clinical trials, a transition period is necessary to tackle contextual challenges before DCTs are being implemented. The main challenges are categorised into four themes: (1) usability and practicability of the technology; (2) paradigm shift and trial data quality; (3) ethical and regulatory hurdles and (4) contextual factors (site-specific research environment and sociocultural aspects).

CONCLUSION

The transformation from a site to a patient-centric model with an increased responsibility of participants should be context adapted. The transformation requires substantial investment, training of the various stakeholders and an efficient communication. Additionally, commitment of sponsors, investigators, ethics and regulatory authorities and the buy-in of the communities are essential for this change.

The SisaMob Information System: Implementation of Digital Data Collection as a Tool for Surveillance and Vector Control in the State of São Paulo

Information systems are essential instruments in managing resources, in the evaluation of the epidemiological situation, and for decision-making at all hierarchical levels. Technological advances have allowed the development of systems that meet these premises. Therefore, it is recommended to consider the optimization of data entry and its immediate georeferencing in order to obtain information in real time. To meet this objective, we describe the application introduction process for the implementation of the digital collection of primary data and its integration with the database through synchronization with the SisaWeb platform (Information System for surveillance and control of Aedes aegypti), developed to meet the needs of the Arbovirus Surveillance and Control Program in the state of São Paulo, Brazil. For this purpose, the application-SisaMob-was conceived in the Android Studio development environment, Google^®, following the same guidelines as the traditional collection method. Tablets equipped with the Android^® operating system were used. To evaluate the implementation of the application, a semi-structured test was applied. The results highlighted that 774.9% (27) of the interviewees evaluated its use positively and, replacing the standard bulletin, 61.1% (22) of the users considered it regular to excellent. The automatic collection of geographic coordinates represented the greatest innovation in the use of the portable device, with reductions in errors and in the time taken to complete the report in the field. The integration to SisaWeb allowed obtaining information in real-time, being easily presented in tabular and graphic modes and spatially arranged through maps, making it possible to monitor the work at a distance, and allowing preliminary analyses during the data collection process. For the future, we must improve the mechanisms for assessing the effectiveness of information, increase the potential of the tool to produce more accurate analyses, which can direct actions more efficiently.

Use of mobile data collection systems within large-scale epidemiological field trials: findings and lessons-learned from a vector control trial in Iquitos, Peru

Vector-borne diseases are among the most burdensome infectious diseases worldwide with high burden to health systems in developing regions in the tropics. For many of these diseases, vector control to reduce human biting rates or arthropod populations remains the primary strategy for prevention. New vector control interventions intended to be marketed through public health channels must be assessed by the World Health Organization for public health value using data generated from large-scale trials integrating epidemiological endpoints of human health impact. Such phase III trials typically follow large numbers of study subjects to meet necessary power requirements for detecting significant differences between treatment arms, thereby generating substantive and complex datasets. Data is often gathered directly in the field, in resource-poor settings, leading to challenges in efficient data reporting and/or quality assurance. With advancing technology, mobile data collection (MDC) systems have been implemented in many studies to overcome these challenges. Here we describe the development and implementation of a MDC system during a randomized-cluster, placebo-controlled clinical trial evaluating the protective efficacy of a spatial repellent intervention in reducing human infection with Aedes-borne viruses (ABV) in the urban setting of Iquitos, Peru, as well as the data management system that supported it. We discuss the benefits, remaining capacity gaps and the key lessons learned from using a MDC system in this context in detail.

Introducing field digital data collection systems into seasonal malaria chemoprevention campaigns: opportunities for robust evidence development and national e-health strategies

Seasonal malaria chemoprevention (SMC) is a World Health Organization-recommended intervention to protect children under the age of 5 in Africa’s Sahel region. While SMC remains highly effective in decreasing malaria cases, implementing countries face several challenges regarding collecting quality data; monitoring coverage and compliance and overcoming delays in campaigns due to late payment to field distributors.

To address these challenges, the National Malaria Control Programmes of Benin, The Gambia, Ghana and Nigeria introduced digital data collection (DDC) tools to support their SMC campaigns. To facilitate cross-country learning, this paper investigates the impact of using DDCs in SMC campaigns by comparing country responses.

Country experience suggests that in comparison to paper-based data collection systems, using DDC tools help to overcome data quality and operational challenges; cloud-based features also made data more accessible. Thus, scaling up DDC tools and linking them with routine national health management systems could help generate robust evidence for malaria policy development and programming. Of note, evidence from Benin showed that using digital tools reduced the time to pay staff and volunteers by 5 weeks. In Benin’s experience, DDC also offered cost benefits (1.5 times cheaper) versus the use of paper-based tools.

The authors note that no application offers greater benefits than the other—countries will select a technology that best suits their needs. Several applications are currently being used and newer ones are also being developed. Another option is to develop in-house applications that can be adjusted to local health programmes.

Cost-effectiveness studies to inform on whether DDCs offer cost advantages would be beneficial. More studies on DDC are needed from SMC-implementing countries to identify additional benefits and drawbacks of digital applications. These will similarly help national malaria policy and programming efforts.

From reverse innovation to global innovation in animal health: A review

Reverse innovation refers to learning from or diffusion of innovations developed in low income settings and further translated to industrialized countries. There is lack of consensus regarding terminology, but the idea that innovations in low-income countries are promising for adoption in high-income contexts is not new. However, in healthcare literature globally, the vast majority of publications referring to 'disruptive innovation' were published in the last ten years. To assess the potential of innovative developments and technologies for improving animal health, we initiated a literature review in 2020. We used a combined approach, incorporating targeted searching in PubMed using a key word algorithm with a snowball technique, to identify 120 relevant publications and extract data for qualitative coding. Heterogeneity of articles precluded meta-analysis, quality scoring and risk of bias analysis. We can distinguish technical innovations like new digital devices, diagnostic tests and procedures, and social innovations of intersectoral cooperation. We profile two case studies to describe potential global innovations: an integrated surveillance and response system in Somali Regional State, Ethiopia and a blockchain secured One Health intervention to optimally provide post-exposure prophylaxis for rabies exposed people in West Africa. Innovation follows no borders and can also occur in low-income settings, under constraints of cost, lack of services and infrastructure. Lower administrative and legal barriers may contribute to produce innovations that would not be possible under conditions of high density of regulation. We recommend using the term global innovation, which highlights those emanating from international partnership to solve problems of global implications.

A REDCap-based model for online interventional research: Parent sleep education in autism

INTRODUCTION

The use of online platforms for pediatric healthcare research is timely, given the current pandemic. These platforms facilitate trial efficiency integration including electronic consent, randomization, collection of patient/family survey data, delivery of an intervention, and basic data analysis.

METHODS

We created an online digital platform for a multicenter study that delivered an intervention for sleep disorders to parents of children with autism spectrum disorder (ASD). An advisory parent group provided input. Participants were randomized to receive either a sleep education pamphlet only or the sleep education pamphlet plus three quick-tips sheets and two videos that reinforced the material in the pamphlet (multimedia materials). Three measures - Family Inventory of Sleep Habits (FISH), Children's Sleep Habits Questionnaire modified for ASD (CSHQ-ASD), and Parenting Sense of Competence (PSOC) - were completed before and after 12 weeks of sleep education.

RESULTS

Enrollment exceeded recruitment goals. Trial efficiency was improved, especially in data entry and automatic notification of participants related to survey completion. Most families commented favorably on the study. While study measures did not improve with treatment in either group (pamphlet or multimedia materials), parents reporting an improvement of ≥3 points in the FISH score showed a significantly improved change in the total CSHQ (P = 0.038).

CONCLUSION

Our study demonstrates the feasibility of using online research delivery platforms to support studies in ASD, and more broadly, pediatric clinical and translational research. Online platforms may increase participant inclusion in enrollment and increase convenience and safety for participants and study personnel.

Comparing Single-Page, Multipage, and Conversational Digital Forms in Health Care: Usability Study

Background

Even in the era of digital technology, several hospitals still rely on paper-based forms for data entry for patient admission, triage, drug prescriptions, and procedures. Paper-based forms can be quick and convenient to complete but often at the expense of data quality, completeness, sustainability, and automated data analytics. Digital forms can improve data quality by assisting the user when deciding on the appropriate response to certain data inputs (eg, classifying symptoms). Greater data quality via digital form completion not only helps with auditing, service improvement, and patient record keeping but also helps with novel data science and machine learning research. Although digital forms are becoming more prevalent in health care, there is a lack of empirical best practices and guidelines for their design. The study-based hospital had a definite plan to abolish the paper form; hence, it was not necessary to compare the digital forms with the paper form.

Objective

This study aims to assess the usability of three different interactive forms: a single-page digital form (in which all data input is required on one web page), a multipage digital form, and a conversational digital form (a chatbot).

Methods

The three digital forms were developed as candidates to replace the current paper-based form used to record patient referrals to an interventional cardiology department (Cath-Lab) at Altnagelvin Hospital. We recorded usability data in a counterbalanced usability test (60 usability tests: 20 subjects×3 form usability tests). The usability data included task completion times, System Usability Scale (SUS) scores, User Experience Questionnaire data, and data from a postexperiment questionnaire.

Results

We found that the single-page form outperformed the other two digital forms in almost all usability metrics. The mean SUS score for the single-page form was 76 (SD 15.8; P=.01) when compared with the multipage form, which had a mean score of 67 (SD 17), and the conversational form attained the lowest scores in usability testing and was the least preferred choice of users, with a mean score of 57 (SD 24). An SUS score of >68 was considered above average. The single-page form achieved the least task completion time compared with the other two digital form styles.

Conclusions

In conclusion, the digital single-page form outperformed the other two forms in almost all usability metrics; it had the least task completion time compared with those of the other two digital forms. Moreover, on answering the open-ended question from the final customized postexperiment questionnaire, the single-page form was the preferred choice.

Anomaly Detection Algorithm for Real-World Data and Evidence in Clinical Research: Implementation, Evaluation, and Validation Study

BACKGROUND

Statistical analysis, which has become an integral part of evidence-based medicine, relies heavily on data quality that is of critical importance in modern clinical research. Input data are not only at risk of being falsified or fabricated, but also at risk of being mishandled by investigators.

OBJECTIVE

The urgent need to assure the highest data quality possible has led to the implementation of various auditing strategies designed to monitor clinical trials and detect errors of different origin that frequently occur in the field. The objective of this study was to describe a machine learning-based algorithm to detect anomalous patterns in data created as a consequence of carelessness, systematic error, or intentionally by entering fabricated values.

METHODS

A particular electronic data capture (EDC) system, which is used for data management in clinical registries, is presented including its architecture and data structure. This EDC system features an algorithm based on machine learning designed to detect anomalous patterns in quantitative data. The detection algorithm combines clustering with a series of 7 distance metrics that serve to determine the strength of an anomaly. For the detection process, the thresholds and combinations of the metrics were used and the detection performance was evaluated and validated in the experiments involving simulated anomalous data and real-world data.

RESULTS

Five different clinical registries related to neuroscience were presented-all of them running in the given EDC system. Two of the registries were selected for the evaluation experiments and served also to validate the detection performance on an independent data set. The best performing combination of the distance metrics was that of Canberra, Manhattan, and Mahalanobis, whereas Cosine and Chebyshev metrics had been excluded from further analysis due to the lowest performance when used as single distance metric-based classifiers.

CONCLUSIONS

The experimental results demonstrate that the algorithm is universal in nature, and as such may be implemented in other EDC systems, and is capable of anomalous data detection with a sensitivity exceeding 85%.

A Good Practice-Compliant Clinical Trial Imaging Management System for Multicenter Clinical Trials: Development and Validation Study

Background

With the rapid increase in utilization of imaging endpoints in multicenter clinical trials, the amount of data and workflow complexity have also increased. A Clinical Trial Imaging Management System (CTIMS) is required to comprehensively support imaging processes in clinical trials. The US Food and Drug Administration (FDA) issued a guidance protocol in 2018 for appropriate use of medical imaging in accordance with many regulations including the Good Clinical Practice (GCP) guidelines. Existing research on CTIMS, however, has mainly focused on functions and structures of systems rather than regulation and compliance.

Objective

We aimed to develop a comprehensive CTIMS to meet the current regulatory guidelines and various required functions. We also aimed to perform computerized system validation focusing on the regulatory compliance of our CTIMS.

Methods

Key regulatory requirements of CTIMS were extracted thorough review of many related regulations and guidelines including International Conference on Harmonization-GCP E6, FDA 21 Code of Federal Regulations parts 11 and 820, Good Automated Manufacturing Practice, and Clinical Data Interchange Standards Consortium. The system architecture was designed in accordance with these regulations by a multidisciplinary team including radiologists, engineers, clinical trial specialists, and regulatory medicine professionals. Computerized system validation of the developed CTIMS was performed internally and externally.

Results

Our CTIMS (AiCRO) was developed based on a two-layer design composed of the server system and the client system, which is efficient at meeting the regulatory and functional requirements. The server system manages system security, data archive, backup, and audit trail. The client system provides various functions including deidentification, image transfer, image viewer, image quality control, and electronic record. Computerized system validation was performed internally using a V-model and externally by a global quality assurance company to demonstrate that AiCRO meets all regulatory and functional requirements.

Conclusions

We developed a Good Practice–compliant CTIMS—AiCRO system—to manage large amounts of image data and complexity of imaging management processes in clinical trials. Our CTIMS adopts and adheres to all regulatory and functional requirements and has been thoroughly validated.

The Promise of Mobile Technologies for the Health Care System in the Developing World: A Systematic Review

Evolution of mobile technologies and their rapid penetration into people's daily lives, especially in the developing countries, have highlighted mobile health, or m-health, as a promising solution to improve health outcomes. Several studies have been conducted that characterize the impact of m-health solutions in resource-limited settings and assess their potential to improve health care. The aim of this review is twofold: 1) to present an overview of the background and significance of m-health and 2) to summarize and discuss the existing evidence for the effectiveness of m-health in the developing world. A systematic search in the literature was performed in Pubmed, Scopus, as well as reference lists, and a broad sample of 98 relevant articles was identified, which were then categorized into five wider m-health categories. Although statistically significant conclusions cannot be drawn since the majority of studies relied on small-scale trials and limited assessment of long-term effects, this review provides a systematic and extensive analysis of the advantages, disadvantages, and challenges of m-health in developing countries in an attempt to determine future research directions of m-health interventions.

Design and evaluation of a web-based decision support tool for district-level disease surveillance in a low-resource setting

During the 2014 West African Ebola Virus outbreak it became apparent that the initial response to the outbreak was hampered by limitations in the collection, aggregation, analysis and use of data for intervention planning. As part of the post-Ebola recovery phase, IBM Research Africa partnered with the Port Loko District Health Management Team (DHMT) in Sierra Leone and GOAL Global, to design, implement and deploy a web-based decision support tool for district-level disease surveillance. This paper discusses the design process and the functionality of the first version of the system. The paper presents evaluation results prior to a pilot deployment and identifies features for future iterations. A qualitative assessment of the tool prior to pilot deployment indicates that it improves the timeliness and ease of using data for making decisions at the DHMT level.

Mobile health solutions in developing countries: a stakeholder perspective

Infrastructural deficiencies, limited access to medical care, and shortage of health care workers are just a few of the barriers to health care in developing countries. mHealth has the potential to overcome at least some of these challenges. To address this, a stakeholder perspective is adopted and an analysis of existing research is undertaken to look at mHealth delivery in developing countries. This study focuses on four key stakeholder groups i.e., health care workers, patients, system developers, and facilitators. A systematic review identifies 108 peer-reviewed articles, which are analysed to determine the extent these articles investigate the different types of stakeholder interactions, and to identify high-level themes emerging within these interactions. This analysis illustrates two key gaps. First, while interactions involving health care workers and/or patients have received significant attention, little research has looked at the role of patient-to-patient interactions. Second, the interactions between system developers and the other stakeholder groups are strikingly under-represented.

Development and Application of Direct Data Capture for Monitoring Medication Compliance in Clinical Trials

OBJECTIVES

The monitoring of medication compliance in clinical trials is important but labor intensive. To check medication compliance in clinical trials, a system was developed, and its technical feasibility evaluated.

METHODS

The system consisted of three parts: a management part (clinical trial center database and a developed program), clinical trial investigator part (monitoring), and clinical trial participant part (personal digital assistant [PDA] with a barcode scanner). The system was tested with 20 participants for 2 weeks, and compliance was evaluated.

RESULTS

This study developed a medication compliance monitoring system that used a PDA with a barcode scanner, which sent reminder/warning messages, logged medication barcode data, and provided compliance information to investigators. Registered participants received short message service (SMS) reminder/warning messages on their PDA and sent barcode data at the dosing time. The age range of the participants was 29 to 73 years. Five participants were <50 years old and 8 were ≥65 years old. The total mean compliance rate was 82.3%. The mean compliance rate was 83.1% in participants <65 years old and 81.1% in those ≥65 years old.

CONCLUSIONS

The system was feasible, usable, and effective, even with elderly participants, for monitoring medication compliance in clinical trials using a PDA with a barcode scanner, and may improve the quality of clinical trials.

Using Digital Technologies in Clinical HIV Research: Real-World Applications and Considerations for Future Work

BACKGROUND

Digital technologies, especially if used in novel ways, provide a number of potential advantages to clinical research in trials related to human immunodeficiency virus (HIV) and acquired immune deficiency syndrome (AIDS) and may greatly facilitate operations as well as data collection and analysis. These technologies may even allow answering questions that are not answerable with older technologies. However, they come with a variety of potential concerns for both the participants and the trial sponsors. The exact challenges and means for alleviation depend on the technology and on the population in which it is deployed, and the rapidly changing landscape of digital technologies presents a challenge for creating future-proof guidelines for technology application.

OBJECTIVE

The aim of this study was to identify and summarize some common themes that are frequently encountered by researchers in this context and highlight those that should be carefully considered before making a decision to include these technologies in their research.

METHODS

In April 2016, the Global HIV Vaccine Enterprise surveyed the field for research groups with recent experience in novel applications of digital technologies in HIV clinical research and convened these groups for a 1-day meeting. Real-world uses of various technologies were presented and discussed by 46 attendees, most of whom were researchers involved in the design and conduct of clinical trials of biomedical HIV prevention and treatment approaches. After the meeting, a small group of organizers reviewed the presentations and feedback obtained during the meeting and categorized various lessons-learned to identify common themes. A group of 9 experts developed a draft summary of the findings that was circulated via email to all 46 attendees for review. Taking into account the feedback received, the group finalized the considerations that are presented here.

RESULTS

Meeting presenters and attendees discussed the many successful applications of digital technologies to improve research outcomes, such as those for recruitment and enrollment, participant identification, informed consent, data collection, data quality, and protocol or treatment adherence. These discussions also revealed unintended consequence of technology usage, including risks to study participants and risks to study integrity.

CONCLUSIONS

Key lessons learned from these discussions included the need to thoroughly evaluate systems to be used, the idea that early success may not be sustained throughout the study, that some failures will occur, and considerations for study-provided devices. Additionally, taking these key lessons into account, the group generated recommendations on how to move forward with the use of technology in HIV vaccine and biomedical prevention trials.

Building Capability for Clinical Pharmacology Research in Sub-Saharan Africa

A strong scientific rationale exists for conducting clinical pharmacology studies in target populations because local factors such as genetics, environment, comorbidities, and diet can affect variability in drug responses. However, clinical pharmacology studies are not widely conducted in sub-Saharan Africa, in part due to limitations in technical expertise and infrastructure. Since 2012, a novel public-private partnership model involving research institutions and a pharmaceutical company has been applied to developing increased capability for clinical pharmacology research in multiple African countries.