JMIR Publications

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  mHealth in a Clinical Setting

  Jan 23, 2020

  Benefits of Mobile Apps for Cancer Pain Management: Systematic Review

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  Authors List:

  • Caiyun Zheng  
  • Xu Chen  
  • Lizhu Weng  
  • Ling Guo  
  • Haiting Xu  
  • Meimei Lin  
  • Yan Xue  
  • Xiuqin Lin  
  • Aiqin Yang  
  • Lili Yu  
  • Zenggui Xue  
  • Jing Yang  

  Abstract:

  Background: Pain ratings reported by patients with cancer continue to increase, and numerous computer and phone apps for managing cancer-related pain have been developed recently; however, whether these apps effectively alleviate patients’ pain remains unknown. Objective: This study aimed to comprehensively evaluate the role of mobile apps in the management of cancer pain. Methods: Literature on the use of apps for cancer pain management and interventions, published before August 2019, was retrieved from the following databases: MEDLINE, Embase, Cochrane, CINAHL, Scopus, and PsycINFO. The effects of apps on cancer pain were evaluated using RevMan5.3 software, and the rates of adverse drug reactions were analyzed using the R Statistical Software Package 3.5.3. Results: A total of 13 studies were selected for the analysis: 5 randomized controlled trials (RCTs), 4 before-after studies, 2 single-arm trials, 1 prospective cohort study, and 1 prospective descriptive study. The 5 RCTs reported data for 487 patients (240 patients in the intervention group and 247 patients in the control group), and the remaining studies reported data for 428 patients. We conducted a meta-analysis of the RCTs. According to the meta-analysis, apps can significantly reduce pain scores (mean difference [MD]=–0.50, 95% CI –0.94 to –0.07, I²=62%, P=.02). We then used apps that have an instant messaging module for subgroup analysis; these apps significantly reduced patients’ pain scores (MD=–0.67, 95% CI –1.06 to –0.28, I²=57%, P<.01). Patients using apps without an instant messaging module did not see a reduction in the pain score (MD=0.30, 95% CI –1.31 to 1.92, I²=70%, P=.71). Overall, patients were highly satisfied with using apps. Other outcomes, such as pain catastrophizing or quality of life, demonstrated greater improvement in patients using apps with instant messaging modules compared with patients not using an app. Conclusions: The use of apps with instant messaging modules is associated with reduced pain scores in patients with cancer-related pain, and patient acceptance of these apps is high. Apps without instant messaging modules are associated with relatively higher pain scores. The presence of an instant messaging module may be a key factor affecting the effect of an app on cancer pain.

  • JMIR Mhealth Uhealth 2020;8(1):e17055

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  Evaluation and Research Methodology...

  Jan 22, 2020

  Quality Assurance of Health Wearables Data: Participatory Workshop on Barriers, Solutions, and Expectations

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  Authors List:

  • Robab Abdolkhani  
  • Kathleen Gray  
  • Ann Borda  
  • Ruth DeSouza  

  Abstract:

  Background: The ubiquity of health wearables and the consequent production of patient-generated health data (PGHD) are rapidly escalating. However, the utilization of PGHD in routine clinical practices is still low because of data quality issues. There is no agreed approach to PGHD quality assurance; therefore, realizing the promise of PGHD requires in-depth discussion among diverse stakeholders to identify the data quality assurance challenges they face and understand their needs for PGHD quality assurance. Objective: This paper reports findings from a workshop aimed to explore stakeholders’ data quality challenges, identify their needs and expectations, and offer practical solutions. Methods: A qualitative multi-stakeholder workshop was conducted as a half-day event on the campus of an Australian University located in a major health care precinct, namely the Melbourne Parkville Precinct. The 18 participants had experience of PGHD use in clinical care, including people who identified as health care consumers, clinical care providers, wearables suppliers, and health information specialists. Data collection was done by facilitators capturing written notes of the proceedings as attendees engaged in participatory design activities in written and oral formats, using a range of whole-group and small-group interactive methods. The collected data were analyzed thematically, using deductive and inductive coding. Results: The participants’ discussions revealed a range of technical, behavioral, operational, and organizational challenges surrounding PGHD, from the time when data are collected by patients to the time data are used by health care providers for clinical decision making. PGHD stakeholders found consensus on training and engagement needs, continuous collaboration among stakeholders, and development of technical and policy standards to assure PGHD quality. Conclusions: Assuring PGHD quality is a complex process that requires the contribution of all PGHD stakeholders. The variety and depth of inputs in our workshop highlighted the importance of co-designing guidance for PGHD quality guidance.

  • JMIR Mhealth Uhealth 2020;8(1):e15329

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  Design and Formative Evaluation of...

  Jan 22, 2020

  Considerations for Improved Mobile Health Evaluation: Retrospective Qualitative Investigation

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  Authors List:

  • Samantha Dick  
  • Yvonne O'Connor  
  • Matthew J Thompson  
  • John O'Donoghue  
  • Victoria Hardy  
  • Tsung-Shu Joseph Wu  
  • Timothy O'Sullivan  
  • Griphin Baxter Chirambo  
  • Ciara Heavin  

  Abstract:

  Background: Mobile phone use and, consequently, mobile health (mHealth) interventions have seen an exponential increase in the last decade. There is an excess of 318,000 health-related apps available free of cost for consumers to download. However, many of these interventions are not evaluated and are lacking appropriate regulations. Randomized controlled trials are often considered the gold standard study design in determining the effectiveness of interventions, but recent literature has identified limitations in the methodology when used to evaluate mHealth. Objective: The objective of this study was to investigate the system developers’ experiences of evaluating mHealth interventions in the context of a developing country. Methods: We employed a qualitative exploratory approach, conducting semistructured interviews with multidisciplinary members of an mHealth project consortium. A conventional content analysis approach was used to allow codes and themes to be identified directly from the data. Results: The findings from this study identified the system developers’ perceptions of mHealth evaluation, providing an insight into the requirements of an effective mHealth evaluation. This study identified social and technical factors which should be taken into account when evaluating an mHealth intervention. Conclusions: Contextual issues represented one of the most recurrent challenges of mHealth evaluation in the context of a developing country, highlighting the importance of a mixed method evaluation. There is a myriad of social, technical, and regulatory variables, which may impact the effectiveness of an mHealth intervention. Failure to account for these variables in an evaluation may limit the ability of the intervention to achieve long-term implementation and scale.

  • JMIR Mhealth Uhealth 2020;8(1):e12424

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  mHealth in a Clinical Setting

  Jan 21, 2020

  Testing Consultation Recordings in a Clinical Setting With the SecondEars Smartphone App: Mixed Methods Implementation Study

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  Authors List:

  • Amelia Hyatt  
  • Ruby Lipson-Smith  
  • Bryce Morkunas  
  • Meinir Krishnasamy  
  • Michael Jefford  
  • Kathryn Baxter  
  • Karla Gough  
  • Declan Murphy  
  • Allison Drosdowsky  
  • Jo Phipps-Nelson  
  • Fiona White  
  • Alan White  
  • Lesley Serong  
  • Geraldine McDonald  
  • Donna Milne  

  Abstract:

  Background: Health care systems are increasingly looking to mobile device technologies (mobile health) to improve patient experience and health outcomes. SecondEars is a smartphone app designed to allow patients to audio-record medical consultations to improve recall, understanding, and health care self-management. Novel health interventions such as SecondEars often fail to be implemented post pilot-testing owing to inadequate user experience (UX) assessment, a key component of a comprehensive implementation strategy. Objective: This study aimed to pilot the SecondEars app within an active clinical setting to identify factors necessary for optimal implementation. Objectives were to (1) investigate patient UX and acceptability, utility, and satisfaction with the SecondEars app, and (2) understand health professional perspectives on issues, solutions, and strategies for effective implementation of SecondEars. Methods: A mixed methods implementation study was employed. Patients were invited to test the app to record consultations with participating oncology health professionals. Follow-up interviews were conducted with all participating patients (or carers) and health professionals, regarding uptake and extent of app use. Responses to the Mobile App Rating Scale (MARS) were also collected. Interviews were analyzed using interpretive descriptive methodology; all quantitative data were analyzed descriptively. Results: A total of 24 patients used SecondEars to record consultations with 10 multidisciplinary health professionals. In all, 22 of these patients used SecondEars to listen to all or part of the recording, either alone or with family. All 100% of patient participants reported in the MARS that they would use SecondEars again and recommend it to others. A total of 3 themes were identified from the patient interviews relating to the UX of SecondEars: empowerment, facilitating support in cancer care, and usability. Further, 5 themes were identified from the health professional interviews relating to implementation of SecondEars: changing hospital culture, mitigating medico-legal concerns, improving patient care, communication, and practical implementation solutions. Conclusions: Data collected during pilot testing regarding recording use, UX, and health professional and patient perspectives will be important for designing an effective implementation strategy for SecondEars. Those testing the app found it useful and felt that it could facilitate the benefits of consultation recordings, along with providing patient empowerment and support. Potential issues regarding implementation were discussed, and solutions were generated. Clinical Trial: Australia and New Zealand Clinical Trials Registry ACTRN12618000730202; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=373915&isClinicalTrial=False

  • JMIR Mhealth Uhealth 2020;8(1):e15593

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  mHealth for Wellness, Behavior Change...

  Jan 21, 2020

  Effect of mHealth With Offline Antiobesity Treatment in a Community-Based Weight Management Program: Cross-Sectional Study

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  Authors List:

  • Youngin Kim  
  • Bumjo Oh  
  • Hyun-Young Shin  

  Abstract:

  Background: Weight loss interventions using mobile phone apps have recently shown promising results. Objective: This study aimed to analyze the short-term weight loss effect of a mobile coaching intervention when it is integrated with a local public health care center and a regional hospital’s antiobesity clinic as a multidisciplinary model. Methods: A total of 150 overweight or obese adults signed up to complete an 8-week antiobesity intervention program with human coaching through a mobile platform. Paired t tests and multiple linear regression analysis were used to identify the intervention factors related to weight change. Results: Among the 150 participants enrolled in this study, 112 completed the 8-week weight loss intervention. Weight (baseline: mean 77.5 kg, SD 12.9; after intervention: mean 74.8 kg, SD 12.6; mean difference −2.73 kg), body mass index, waist circumference, fat mass (baseline: mean 28.3 kg, SD 6.6; after intervention: mean 25.7 kg, SD 6.3; mean difference −2.65 kg), and fat percentage all showed a statistically significant decrease, and metabolic equivalent of task (MET) showed a statistically significant increase after intervention. In multiple linear regression analysis, age (beta=.07; P=.06), △MET (beta=−.0009; P=.10), number of articles read (beta=−.01; P=.04), and frequency of weight records (beta=−.05; P=.10; R²=0.4843) were identified as significant factors of weight change. Moreover, age (beta=.06; P=.03), sex (female; beta=1.16; P=.08), △MET (beta=−.0009; P<.001), and number of articles read (beta=−.02; P<.001; R²=0.3728) were identified as significant variables of fat mass change. Conclusions: The multidisciplinary approach, combining a mobile health (mHealth) care app by health care providers, was effective for short-term weight loss. Additional studies are needed to evaluate the efficacy of mHealth care apps in obesity treatment.

  • JMIR Mhealth Uhealth 2020;8(1):e13273

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  mHealth in a Clinical Setting

  Jan 20, 2020

  A Smartphone App Designed to Empower Patients to Contribute Toward Safer Surgical Care: Community-Based Evaluation Using a Participatory Approach

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  Authors List:

  • Stephanie Russ  
  • Zahira Latif  
  • Ahmarah Leah Hazell  
  • Helen Ogunmuyiwa  
  • Josephine Tapper  
  • Sylvia Wachuku-King  
  • Nick Sevdalis  
  • Josephine Ocloo  

  Abstract:

  Background: MySurgery is a smartphone app designed to increase patient and carer involvement in behaviors that contribute toward safety in surgical care. Objective: This study presents a pilot evaluation of MySurgery in which we evaluated surgical patients’ perceptions of the app in terms of its content, usability, and potential impacts on communication and safety. Methods: A participatory action research (PAR) approach was used to formulate a research steering group consisting of 5 public representatives and 4 researchers with equal decision-making input. Surgical patients were recruited from the community using multiple approaches, including Web based (eg, social media, recruitment websites, and charitable or voluntary organizations) and face to face (via community centers). Participants referred to MySurgery before, during, and after their surgery and provided feedback via an embedded questionnaire and using reflective notes. Results: A diverse mix of 42 patients took part with good representation from 2 “seldom heard” groups: those with a disability and those from a black, Asian, or minority ethnic group. Most were very supportive of MySurgery, particularly those with previous experience of surgery and those who felt comfortable to be involved in conversations and decisions around their care. The app showed particular potential to empower patients to become involved in their care conversations and safety-related behaviors. Perceptions did not differ according to age, ethnicity, or length of hospital stay. Suggestions for improving the app included how to make it more accessible to certain groups, for example, those with a disability. Conclusions: MySurgery is a novel technology-driven approach for empowering patients to play a role in improving surgical safety that seems feasible for use within the United Kingdom’s National Health Service. Adopting a PAR approach and the use of a diversity strategy considerably enhanced the research process in terms of gaining diverse participant recruitment and patient and public involvement. Further testing with stakeholder groups will follow.

  • JMIR Mhealth Uhealth 2020;8(1):e12859

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  mHealth for Symptom and Disease...

  Jan 17, 2020

  A Tablet App Supporting Self-Management for People With Dementia: Explorative Study of Adoption and Use Patterns

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  Authors List:

  • Laila Øksnebjerg  
  • Bob Woods  
  • Kathrine Ruth  
  • Annette Lauridsen  
  • Susanne Kristiansen  
  • Helle Dalsgaard Holst  
  • Gunhild Waldemar  

  Abstract:

  Background: Assistive technology (AT) is rapidly emerging within dementia care and support. One area of AT application is support of people with dementia in compensating for cognitive symptoms and thereby promoting their self-management. There is, however, little evidence for the applicability, usability, and effectiveness of AT for people with dementia, and there is a need to identify factors that can promote adoption. Objective: This study aimed to (1) evaluate the applicability and usability of an app, tailor-made for people with dementia; (2) explore factors affecting adoption; (3) explore the possible influence of caregiver involvement; and (4) contribute to process evaluation of the intervention. Methods: The ReACT (Rehabilitation in Alzheimer's disease using Cognitive support Technology) app was designed as a holistic solution to support memory and structure in daily living. Persons with dementia had access to a personal user account, and family caregivers were given a parallel login. Written and Web-based materials were provided to support self-applied implementation. A mixed methods design was applied to explore adoption and use patterns, including background and disease-related data, qualitative data from a survey, and log data. Adoption was defined as the use of the app over a period of ≥90 days. Results: Data from 112 participants and 98 caregivers were included. Shorter time from diagnosis (U=595; P=.046; r=0.19) and caregiver activating the app (P=.02) had a significant impact on the participant adoption status. Logistic regression analysis showed that if caregivers had activated the app, the participant was five times more likely to become an adopter (odds ratio 5.1, 95% CI 1.29-19.99; P=.02). However, the overall predictive power was low, and there was a wide variation in background and disease-related characteristics among adopters. The level of experience and skills in tablet use were not significantly different between adopters and nonadopters. Adopters generally rated the app high on usefulness, satisfaction, and ease of use (rated on the USEdem questionnaire). Their scores were significantly higher compared with nonadopters (U=5.5; P=.02; r=0.64). Analysis of use patterns showed that all functionalities of the app were used among adopters. Conclusions: For participants who became adopters, the ReACT app and the methods for self-applied implementation were applicable. However, the results were also in accordance with the well-known challenges of nonadoption and nonadherence to digital health interventions. The study provided insight into the importance of timely introduction and caregiver support for adoption of AT among people with dementia. It also underlined the high complexity of personal and contextual factors that influence adoption. These complex factors need to be considered when designing and implementing AT for people with dementia.

  • JMIR Mhealth Uhealth 2020;8(1):e14694

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  mHealth for Wellness, Behavior Change...

  Jan 15, 2020

  Mobile Health Technology Interventions for Suicide Prevention: Systematic Review

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  Authors List:

  • Ruth Melia  
  • Kady Francis  
  • Emma Hickey  
  • John Bogue  
  • Jim Duggan  
  • Mary O'Sullivan  
  • Karen Young  

  Abstract:

  Background: Digital interventions are proposed as one way by which effective treatments for self-harm and suicidal ideation may be improved and their scalability enhanced. Mobile devices offer a potentially powerful medium to deliver evidence-based interventions with greater specificity to the individual when the intervention is needed. The recent proliferation of publicly available mobile apps designed for suicide prevention underlines the need for robust evidence to promote safe practice. Objective: This review aimed to examine the effectiveness of currently available mobile health (mHealth) technology tools in reducing suicide-specific outcomes. Methods: The following databases were searched: Cochrane Central Register of Controlled Trials (The Cochrane Library), MEDLINE, EMBASE, PsycINFO, and relevant sources of gray literature. All published and unpublished randomized controlled trials (RCTs), pseudo-RCTs, and pre-post observational studies that evaluated the effectiveness of mHealth technology in suicide prevention delivered via mobile computing and communication technology were included. Studies were included if they measured at least one suicide outcome variable (ie, suicidal ideation, suicidal intent, nonsuicidal self-injurious behavior, and suicidal behavior). A total of 2 review authors independently extracted data and assessed study suitability, in accordance with the Cochrane Collaboration Risk of Bias Tool, on July 31, 2018. Owing to the heterogeneity of outcomes found across studies, results were not amenable for pooled synthesis, and a meta-analysis was not performed. A narrative synthesis of the available research is presented here. Results: A total of 7 studies met criteria for inclusion . Four published articles that reported on the effectiveness of the following mobile phone apps were included: iBobbly, Virtual Hope Box, BlueIce, and Therapeutic Evaluative Conditioning. Results demonstrated some positive impacts for individuals at elevated risk of suicide or self-harm, including reductions in depression, psychological distress, and self-harm and increases in coping self-efficacy. None of the apps evaluated demonstrated the ability to significantly decrease suicidal ideation compared with a control condition. In addition, 3 unpublished and recently completed trials also met criteria for inclusion in the review. Conclusions: Further research is needed to evaluate the efficacy of stand-alone mHealth technology–based interventions in suicide prevention. The small number of studies reported in this review tentatively indicate that such tools may have a positive impact on suicide-specific outcomes. Future mHealth intervention evaluations would benefit from addressing the following 3 main methodological limitations : (1) heterogeneity of outcomes: a lack of standardized measurement of suicide outcomes across studies; (2) ecological validity: the tendency to exclude potential participants because of the elevated suicide risk may reduce generalizability within clinical settings; and (3) app regulation and definition: the lack of a standardized classification system for mHealth intervention type points to the need for better definition of the scope of such technologies to promote safe practice.

  • JMIR Mhealth Uhealth 2020;8(1):e12516

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  mHealth for Wellness, Behavior Change...

  Jan 15, 2020

  A Mobile Phone App to Improve the Mental Health of Taxi Drivers: Single-Arm Feasibility Trial

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  Authors List:

  • Sandra Davidson  
  • Susan Fletcher  
  • Greg Wadley  
  • Nicola Reavley  
  • Jane Gunn  
  • Darryl Wade  

  Abstract:

  Background: Psychological distress among taxi drivers is 5 times higher than that in the general population, and more than half of all drivers have experienced 3 or more potentially traumatic events in their lifetime. Nevertheless, help-seeking for mental health problems in this male-dominated, predominately immigrant workforce is low. Mobile technologies have the potential to increase mental health awareness, teach self-help skills, and encourage help-seeking in this hard-to-reach population. Objective: This study aimed to assess the feasibility, acceptability, and potential efficacy of Driving to Health, a mobile phone–friendly mental health website app designed for people working as taxi drivers. Methods: Drivers (n=46) were recruited from the Melbourne Airport Taxi Holding Yard to participate in a single-arm trial. Self-reported, paper-based assessments were completed at baseline and at 1 month. Feasibility was measured by completion rates, representativeness of study participants, and levels of use. Acceptability was assessed by measuring users’ perception of the quality of the app and anticipated levels of future use. The efficacy of Driving to Health to increase awareness, self-help behaviors, and intentions to seek help was assessed using the user version of the Mobile App Rating Scale (uMARS) and the General Help-Seeking Questionnaire (GHSQ). Psychological symptoms were measured using the short form of the Depression, Anxiety, and Stress Scale (DASS-21). Data were analyzed using complete case analysis. Results: In total, 42 participants comprising drivers from 10 different countries of origin, and 14 different languages, completed pre- and poststudy measures (42/46, 91% completion rate). Just under half (45%) of all users used the app more than once with an average visit of 4 min 8 seconds. Responding to the uMARS, 62% (26/42) of the participants said that they would recommend the app to many people. Nearly all (40/42, 95%) participants said that Driving to Health increased awareness of their own mental health; 86% (36/42) said that it increased their mental health knowledge; and 76% (32/42) said that it increased their self-help behaviors. Increases in help-seeking intentions on the GHSQ were not significant, and increases on all 3 scales of DASS-21 were not reliable or meaningful. Conclusions: This study suggests that Driving to Health is an acceptable and feasible electronic health intervention for a hard-to-reach population. Our findings also suggest that Driving to Health results in increases in mental health awareness, behaviors, and willingness to seek help.

  • JMIR Mhealth Uhealth 2020;8(1):e13133

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  mHealth for Health Administration

  Jan 15, 2020

  A Gig mHealth Economy Framework: Scoping Review of Internet Publications

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  Authors List:

  • Fahad Alanezi  
  • Turki Alanzi  

  Abstract:

  Background: The gig economy (characterized by short-term contracts rather than being a full-time employee in an organization) is one of the most recent and important tendencies that have expanded through the global economic market thanks to advances in internet and communication technologies. Similarly, mobile health (mHealth) technologies have also evolved rapidly with the development of the internet and mobile apps, attracting attention globally for their health care benefits. Objective: This study aimed to propose an integration of mHealth within the framework of the gig economy that leads to a new dimension of health care services and the proposal of a new term: gig mHealth. Methods: A review and systematic search of articles, books, and opinions that allowed for answering the research questions were executed through the internet. In this sense, the concept of the gig economy and examples, advantages and disadvantages, were reviewed. Similarly, the general characteristics of mHealth technologies were revised. In addition, the role of technology in supporting the development of the gig economy and mHealth technologies and the interactions between them were investigated. Results: The findings suggested that the gig economy is characterized by its flexibility in working hours, on-demand work, free agents, freelancing, freedom in the choice of work, and independent contracts. In addition, an analysis of an mHealth system indicated that it was composed of patients, specialists, nurses, and database administrators. In this system, patients and specialists or nurses are connected to cloud services for the transmission of data and medical information through a mobile app. Here, the administrators update the database and app features, among other technical tasks. Conversely, a general structure of an integrated gig mHealth system was developed. In this structure, the mHealth care services and the mHealth care activities were incorporated into a gig economy model. In addition, a practical example of an integrated view of a gig economy app in mHealth that illustrates the interaction between the patients (consumers) and providers (partners) of mHealth care services, mHealth care activities, health care professionals, and individual contractors was presented. The consumers and providers were interconnected with the health care company, brand, or firm through digital means using a mobile app or Windows platforms. Conclusions: The analysis carried out in this study suggested the possibility of integrating mHealth within the framework of the gig economy enhancing health care service delivery and the management of health care activities. The following 4 major areas of apps proposed in the mHealth framework that can catalyze the operations using the features of the gig economy were sharing/renting medical and diagnostic equipment and resources, on-demand appointments/self-health management, on-demand health care services, and assigning health care activities/gigs to individual contractors. This integration leads to a new dimension for health care services and the proposal of a new term: gig mHealth.

  • JMIR Mhealth Uhealth 2020;8(1):e14213

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  Viewpoint

  Jan 14, 2020

  Back to the Future: Achieving Health Equity Through Health Informatics and Digital Health

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  Authors List:

  • LaPrincess C Brewer  
  • Karen L Fortuna  
  • Clarence Jones  
  • Robert Walker  
  • Sharonne N Hayes  
  • Christi A Patten  
  • Lisa A Cooper  

  Abstract:

  The rapid proliferation of health informatics and digital health innovations has revolutionized clinical and research practices. There is no doubt that these fields will continue to have accelerated growth and a substantial impact on population health. However, there are legitimate concerns about how these promising technological advances can lead to unintended consequences such as perpetuating health and health care disparities for underresourced populations. To mitigate this potential pitfall, it is imperative for the health informatics and digital health scientific communities to understand the challenges faced by disadvantaged groups, including racial and ethnic minorities, which hinder their achievement of ideal health. This paper presents illustrative exemplars as case studies of contextually tailored, sociotechnical mobile health interventions designed with community members to address health inequities using community-engaged research approaches. We strongly encourage researchers and innovators to integrate community engagement into the development of data-driven, modernized solutions for every sector of society to truly achieve health equity for all.

  • JMIR Mhealth Uhealth 2020;8(1):e14512

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  mHealth in the Developing...

  Jan 14, 2020

  An Ototoxicity Grading System Within a Mobile App (OtoCalc) for a Resource-Limited Setting to Guide Grading and Management of Drug-Induced Hearing Loss in...

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  Authors List:

  • Cara Hollander  
  • Karin Joubert  
  • Natalie Schellack  

  Abstract:

  Background: Tuberculosis (TB) affects millions of people worldwide and is treated with medication including aminoglycosides and polypeptides. Individuals respond differently to medications as a result of their genetic inheritance. These differences in genetic inheritance can result in the underdosing or overdosing of medication, which may affect the efficacy or, in the case of aminoglycosides and polypeptides used in the treatment of all forms of TB, result in ototoxicity. When ototoxicity is detected, physicians should adjust dosages to minimize further ototoxicity and hearing loss; however, there are no suitable grading systems to define significant hearing loss. Objective: The aim of this study was to develop a standardized grading system by making use of an electronic health (eHealth) platform to ensure that a user-friendly method was available to interpret hearing test results, calculate significant hearing loss, and provide recommendations with regard to dosage adjustments and management. It further aimed to establish the sensitivity of the newly developed grading scale. Methods: This grading system was developed in South Africa based on data that were obtained from an audiology and pharmacokinetic study on patients with drug-resistant TB (DR-TB) at two DR-TB units at state-run hospitals. This feasibility study employed a prospective, cross-sectional, exploratory, descriptive case series research design, with a total of 22 participants. Participants underwent audiological and pharmacological assessments at baseline and every 2 weeks for the first 3 months of treatment. Various professionals (8 in total) were subsequently involved in the development of the eHealth system, including a software engineer, four audiologists, a pharmacist, a medical doctor, and a nurse. The app underwent 14 modifications that involved aspects of data storage, ease of usability, grades, and the risk factor checklist. Results: An ototoxicity grading system within a mobile app for use by doctors, nurses, and audiologists was developed for patients with DR-TB. The purpose of this user-friendly ototoxicity calculator, OtoCalc, is to (1) assist health professionals in assessing patients for ototoxicity, (2) establish the clinical significance of ototoxicity by calculating the grade of hearing loss, (3) monitor the progression of hearing loss, and (4) enable systematic referral and management of patients according to their needs. Conclusions: This newly developed system is more sensitive than the existing grading methods for determining ototoxicity in patients with DR-TB. This app needs to be trialed in a larger sample to establish data security, ease of use, and suitability within this population.

  • JMIR Mhealth Uhealth 2020;8(1):e14036

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