Content Analysis of Apps for Growth Monitoring and Growth Hormone Treatment: Systematic Search in the Android App Store

The growzen™ buddy smartphone app to improve adherence in patients receiving recombinant human growth hormone therapy: a retrospective observational study in Argentina

Introduction

This study in Argentina evaluated the impact of the growzen™ buddy smartphone app on adherence to recombinant human growth hormone (r-hGH) treatment.

Methods

The adherence data, invitation dates with a link to the app, app activation dates, and height measurements entered were extracted from the growzen™ digital health ecosystem. Patients with 12 months of adherence data, aged ≥2 years at treatment start, and aged <19 years were selected both before and after app implementation. Mean adherence was classified as optimal (≥85%) versus suboptimal (<85%). Adherence before and after implementation and the pre-post effect on adherence were assessed.

Results

Data for 830 patients were available. Prior to app implementation, the proportion of patients with optimal adherence was 68% (n = 348/515). Following the app implementation, out of 315 patients, 302 (96%) received an invitation with a link to the app, 225 (71%) activated their account, and 127 (40%) entered height data in the first year. There was a significant early increase in the proportion of patients with optimal adherence following implementation: 82% (n = 258/315), p < 0.001. After implementation, the proportion of patients with optimal adherence included 80% (n = 78/98) of those with an active account who did not enter height measurements and 89% (n = 113/127) of those who did. There was a significant and positive pre-post app effect on adherence (p < 0.01) in patients with an active account.

Discussion

Our results show that using the growzen™ buddy app has a rapid and positive impact on adherence to r-hGH treatment, and patients who were more engaged with the app demonstrated better adherence.

An Augmented Reality Mobile App (Easypod AR) as a Complementary Tool in the Nurse-Led Integrated Support of Patients Receiving Recombinant Human Growth Hormone: Usability and Validation Study

BACKGROUND

Children with growth hormone deficiency face the prospect of long-term recombinant human growth hormone (r-hGH) treatment requiring daily injections. Adherence to treatment is important, especially at treatment initiation, to achieve positive health outcomes. Historically, telenursing services embedded in patient support programs (PSPs) have been a valid approach to support r-hGH treatment initiation and patient education and facilitate adherence by identifying and optimizing appropriate injection techniques. The development of mobile phones with augmented reality (AR) capabilities offers nurses new tools to support patient education.

OBJECTIVE

To investigate experiences among nurses of a new mobile phone app developed to support patient training with a phone-based PSP for r-hGH treatment.

METHODS

In 2020, the Easypod AR mobile app was launched to support nurse-driven telehealth education for patients initiating r-hGH therapy with the Easypod electromechanical auto-injector device. Nurses who were part of PSPs in countries where the Easypod AR app had been launched or where training was provided as part of an anticipated future launch of the app were invited to participate in an online survey based on the Mobile App Rating Scale to capture their feedback after using the app.

RESULTS

In total, 23 nurses completed the online questionnaire. They positively rated the quality of the app across multiple dimensions. The highest mean scores were 4.0 for engagement (ie, adaptation to the target group; SD 0.74), 4.1 (SD 0.79) for functionality (navigation) and 4.1 (SD 0.67) for aesthetics (graphics). Responses indicated the potential positive impact of such a tool on enhancing patient education, patient support, and communication between patients and PSP nurses. Some participants also suggested enhancements to the app, including gamification techniques that they felt have the potential to support the formation of positive treatment behaviors and habits.

CONCLUSIONS

This study highlights the potential for new digital health solutions to reinforce PSP nurse services, including patient education. Future studies could explore possible correlations between any behavioral and clinical benefits that patients may derive from the use of such apps and how they may contribute to support improved patient experiences and treatment outcomes.

Automated growth monitoring app (GROWIN): a mobile Health (mHealth) tool to improve the diagnosis and early management of growth and nutritional disorders in childhood

OBJECTIVE

To assess the functionality and feasibility of the GROWIN app for promoting early detection of growth disorders in childhood, supporting early interventions, and improving children's lifestyle by analyzing data collected over 3 years (2018-2020).

METHODS

We retrospectively assessed the growth parameters (height, weight, body mass index [BMI], abdominal circumference) entered by users (caregivers/parents) in the GROWIN app. We also analyzed the potential health problems detected and the messages/recommendations the app showed. Finally, we assessed the possible impact/benefit of the app on the growth of the children.

RESULTS

A total of 21 633 users (Spanish [65%], Latin American [30%], and others [5%]) entered 10.5 ± 8.3 measurements (0-15 y old). 1200 recommendations were for low height and 550 for low weight. 1250 improved their measurements. A specialist review was recommended in 500 patients due to low height. 2567 nutrition tests were run. All children with obesity (n = 855, BMI: 27.8 kg/m2 [2.25 SD]) completed the initial test with a follow-up of ≥1 year. Initial results (score: 8.1) showed poor eating habits (fast food, commercially baked goods, candy, etc.), with >90% not having breakfast. After 3-6 months, BMI decreased ≥1 point, and test scores increased ≥2 points. This benefit was maintained beyond 1 year and was correlated with an improvement in BMI (r = -.65, P = .01).

DISCUSSION/CONCLUSIONS

The GROWIN app represents an innovative automated solution for families to monitor growth. It allows the early detection of abnormal growth indicators during childhood and adolescence, promoting early interventions. Additionally, in children with obesity, an improvement in healthy nutritional habits and a decrease in BMI were observed.

Digital technologies to improve the precision of paediatric growth disorder diagnosis and management

Paediatric disorders of impaired linear growth are challenging to manage, in part because of delays in the identification of pathological short stature and subsequent referral and diagnosis, the requirement for long-term therapy, and frequent poor adherence to treatment, notably with human growth hormone (hGH). Digital health technologies hold promise for improving outcomes in paediatric growth disorders by supporting personalisation of care, from diagnosis to treatment and follow up. The value of automated systems in monitoring linear growth in children has been demonstrated in Finland, with findings that such a system is more effective than a traditional manual system for early diagnosis of abnormal growth. Artificial intelligence has potential to resolve problems of variability that may occur during analysis of growth information, and augmented reality systems have been developed that aim to educate patients and caregivers about growth disorders and their treatment (such as injection techniques for hGH administration). Adherence to hGH treatment is often suboptimal, which negatively impacts the achievement of physical and psychological benefits of the treatment. Personalisation of adherence support necessitates capturing individual patient adherence data; the use of technology to assist with this is exemplified by the use of an electronic injection device, which shares real-time recordings of the timing, date and dose of hGH delivered to the patient with the clinician, via web-based software. The use of an electronic device is associated with high levels of adherence to hGH treatment and improved growth outcomes. It can be anticipated that future technological advances, coupled with continued 'human interventions' from healthcare providers, will further improve management of paediatric growth disorders.

Digital Health for Supporting Precision Medicine in Pediatric Endocrine Disorders: Opportunities for Improved Patient Care

Digitalization of healthcare delivery is rapidly fostering development of precision medicine. Multiple digital technologies, known as telehealth or eHealth tools, are guiding individualized diagnosis and treatment for patients, and can contribute significantly to the objectives of precision medicine. From a basis of "one-size-fits-all" healthcare, precision medicine provides a paradigm shift to deliver a more nuanced and personalized approach. Genomic medicine utilizing new technologies can provide precision analysis of causative mutations, with personalized understanding of mechanisms and effective therapy. Education is fundamental to the telehealth process, with artificial intelligence (AI) enhancing learning for healthcare professionals and empowering patients to contribute to their care. The Gulf Cooperation Council (GCC) region is rapidly implementing telehealth strategies at all levels and a workshop was convened to discuss aspirations of precision medicine in the context of pediatric endocrinology, including diabetes and growth disorders, with this paper based on those discussions. GCC regional investment in AI, bioinformatics and genomic medicine, is rapidly providing healthcare benefits. However, embracing precision medicine is presenting some major new design, installation and skills challenges. Genomic medicine is enabling precision and personalization of diagnosis and therapy of endocrine conditions. Digital education and communication tools in the field of endocrinology include chatbots, interactive robots and augmented reality. Obesity and diabetes are a major challenge in the GCC region and eHealth tools are increasingly being used for management of care. With regard to growth failure, digital technologies for growth hormone (GH) administration are being shown to enhance adherence and response outcomes. While technical innovations become more affordable with increasing adoption, we should be aware of sustainability, design and implementation costs, training of HCPs and prediction of overall healthcare benefits, which are essential for precision medicine to develop and for its objectives to be achieved.

Important Tools for Use by Pediatric Endocrinologists in the Assessment of Short Stature

Assessment and management of children with growth failure has improved greatly over recent years. However, there remains a strong potential for further improvements by using novel digital techniques. A panel of experts discussed developments in digitalization of a number of important tools used by pediatric endocrinologists at the third 360° European Meeting on Growth and Endocrine Disorders, funded by Merck KGaA, Germany, and this review is based on those discussions. It was reported that electronic monitoring and new algorithms have been devised that are providing more sensitive referral for short stature. In addition, computer programs have improved ways in which diagnoses are coded for use by various groups including healthcare providers and government health systems. Innovative cranial imaging techniques have been devised that are considered safer than using gadolinium contrast agents and are also more sensitive and accurate. Deep-learning neural networks are changing the way that bone age and bone health are assessed, which are more objective than standard methodologies. Models for prediction of growth response to growth hormone (GH) treatment are being improved by applying novel artificial intelligence methods that can identify non-linear and linear factors that relate to response, providing more accurate predictions. Determination and interpretation of insulin-like growth factor-1 (IGF-1) levels are becoming more standardized and consistent, for evaluation across different patient groups, and computer-learning models indicate that baseline IGF-1 standard deviation score is among the most important indicators of GH therapy response. While physicians involved in child growth and treatment of disorders resulting in growth failure need to be aware of, and keep abreast of, these latest developments, treatment decisions and management should continue to be based on clinical decisions. New digital technologies and advancements in the field should be aimed at improving clinical decisions, making greater standardization of assessment and facilitating patient-centered approaches.

Mobile Health Apps for Medical Emergencies: Systematic Review

Background

Mobile health apps are used to improve the quality of health care. These apps are changing the current scenario in health care, and their numbers are increasing.

Objective

We wanted to perform an analysis of the current status of mobile health technologies and apps for medical emergencies. We aimed to synthesize the existing body of knowledge to provide relevant insights for this topic. Moreover, we wanted to identify common threads and gaps to support new challenging, interesting, and relevant research directions.

Methods

We reviewed the main relevant papers and apps available in the literature. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology was used in this review. The search criteria were adopted using systematic methods to select papers and apps. On one hand, a bibliographic review was carried out in different search databases to collect papers related to each application in the health emergency field using defined criteria. On the other hand, a review of mobile apps in two virtual storage platforms (Google Play Store and Apple App Store) was carried out. The Google Play Store and Apple App Store are related to the Android and iOS operating systems, respectively.

Results

In the literature review, 28 papers in the field of medical emergency were included. These studies were collected and selected according to established criteria. Moreover, we proposed a taxonomy using six groups of applications. In total, 324 mobile apps were found, with 192 identified in the Google Play Store and 132 identified in the Apple App Store.

Conclusions

We found that all apps in the Google Play Store were free, and 73 apps in the Apple App Store were paid, with the price ranging from US $0.89 to US $5.99. Moreover, 39% (11/28) of the included studies were related to warning systems for emergency services and 21% (6/28) were associated with disaster management apps.

A Mobile App, KhunLook, to Support Thai Parents and Caregivers With Child Health Supervision: Development, Validation, and Acceptability Study

BACKGROUND

In Thailand, children born in government hospitals receive a maternal and child health handbook (MCHH). However, when a new MCHH edition is released, those with the previous editions do not have access to the updated information. A mobile app is an appealing platform to fill this gap. We developed a mobile app called "KhunLook" as an interactive electronic MCHH intended to assist parents in child health supervision.

OBJECTIVE

This study describes the user requirements and development of the KhunLook mobile app, validity of parents' growth assessments, and parents' evaluation of feasibility and acceptability of the app.

METHODS

Phase 1 was a qualitative study using individual interviews. The interview data were used to revise the prototype. In phase 2, parents were randomly assigned to assess their children's growth with the app or the MCHH. The outcomes were compared to those of the physician's assessment, and congruence was determined. In phase 3, parents evaluated the feasibility and acceptability of the app in comparison to the MCHH through a web-based survey.

RESULTS

Four health care providers and 8 parents participated in phase 1. Two themes were identified: (1) the mobile app potentially counters parents' infrequent use of the MCHH with accuracy, attractiveness, convenience, and simplicity, and (2) health supervision needs to be standard, up-to-date, and understandable. KhunLook was publicly launched with a family page and 7 key features: growth and nutrition, development, immunizations, oral health, reminders for the next appointment, memories, and health advice. In phase 2, 56 parents participated in the growth parameter assessments; 34 were in the App group and 22 in the MCHH group. The outcomes of the growth parameter assessments between parents and physicians in both the App and MCHH groups were not significantly different. The congruence proportions were higher in the App group for weight and head circumference, but the differences were not statistically significant. In phase 3, 356 parents from all over Thailand participated in a web-based survey. Parents rated the app feasibility as "very easy to easy" to use at higher proportions than the MCHH in all health assessment domains (growth, development, and immunizations) and ease-of-use domains with statistical significance (P<.001). The KhunLook app received a significantly higher mean score (8.59/10) than the MCHH (7.6/10) (P<.001). Most parents (317/356, 89.0%) preferred the app over MCHH. Further, 93.5% (333/356) of the parents stated that they would continue to use the app and 96.9% (345/356) would recommend others to use it.

CONCLUSIONS

KhunLook, a Thai mobile app for child health supervision, was developed, validated for growth assessments, and was well accepted for ease-of-use by parents. Further studies should be conducted with a large scale of users, and the impact of this app on health behaviors and health outcomes must be evaluated.

Analysis of real-world data on growth hormone therapy adherence using a connected injection device

Background

Poor adherence to long-term recombinant human growth hormone (r-hGH) treatment can lead to suboptimal clinical outcomes; consequently, supporting and monitoring adherence is a crucial part of patient management. We assessed adherence to r-hGH treatment in children with growth disorders over 48 months using a connected monitoring device (easypod™), which automatically transmits adherence data via an online portal (easypod™ connect); both sit within an adherence decision support system (ADSS). We also investigated the effect of age and sex on adherence.

Methods

Data from children transmitting over 10 injections between January 2007 and February 2019 were analyzed. Adherence (mg injected/mg prescribed) was categorized as high (≥85%), intermediate (> 56–84%) or low (≤56%) and assessed at seven time points from the start of treatment up to 48 months. Adherence was investigated over time and stratified by puberty status and sex. Mean transmission rate in each adherence category (total number of transmissions/total number of children) at each time point was calculated as a proxy measure of engagement in disease and treatment management. Descriptive analyses were performed.

Results

Longitudinal records were available for 13,553 children. Overall, 71% (n = 9578) had high adherence, 22% (n = 2989) intermediate and 7% (n = 986) low. The proportion of children with high adherence decreased over time from 87% (n = 12,964) to 65% (n = 957) and was higher in pre-pubertal than pubertal children (girls: 80% [n = 1270] vs 70% [n = 4496]; boys 79% [n = 2573] vs 65% [n = 5214]). Children with high adherence had a higher mean number of transmissions (12.5 [SD 24.9]) than children with intermediate (7.2 [SD 15.3]) or low (3.5 [SD 5.7]) adherence.

Conclusions

High adherence was seen in patients administering r-hGH using the connected device. Children with high adherence were most likely to regularly transmit data. Pubertal children showed lower adherence. We show the potential to develop an ADSS to analyze trends in real-world adherence data. This may prove useful to direct interventions to improve adherence while the ability to readily share data with healthcare professionals may itself improve adherence.