Medication Management Apps for Diabetes: Systematic Assessment of the Transparency and Reliability of Health Information Dissemination

Quality assessment of mHealth apps: a scoping review

Introduction

The number of mHealth apps has increased rapidly during recent years. Literature suggests a number of problems and barriers to the adoption of mHealth apps, including issues such as validity, usability, as well as data privacy and security. Continuous quality assessment and assurance systems might help to overcome these barriers. Aim of this scoping review was to collate literature on quality assessment tools and quality assurance systems for mHealth apps, compile the components of the tools, and derive overarching quality dimensions, which are potentially relevant for the continuous quality assessment of mHealth apps.

Methods

Literature searches were performed in Medline, EMBASE and PsycInfo. Articles in English or German language were included if they contained information on development, application, or validation of generic concepts of quality assessment or quality assurance of mHealth apps. Screening and extraction were carried out by two researchers independently. Identified quality criteria and aspects were extracted and clustered into quality dimensions.

Results

A total of 70 publications met inclusion criteria. Included publications contain information on five quality assurance systems and further 24 quality assessment tools for mHealth apps. Of these 29 systems/tools, 8 were developed for the assessment of mHealth apps for specific diseases, 16 for assessing mHealth apps for all fields of health and another five are not restricted to health apps. Identified quality criteria and aspects were extracted and grouped into a total of 14 quality dimensions, namely "information and transparency", "validity and (added) value", "(medical) safety", "interoperability and compatibility", "actuality", "engagement", "data privacy and data security", "usability and design", "technology", "organizational aspects", "social aspects", "legal aspects", "equity and equality", and "cost(-effectiveness)".

Discussion

This scoping review provides a broad overview of existing quality assessment and assurance systems. Many of the tools included cover only a few dimensions and aspects and therefore do not allow for a comprehensive quality assessment or quality assurance. Our findings can contribute to the development of continuous quality assessment and assurance systems for mHealth apps.

Systematic Review Registration

https://www.researchprotocols.org/2022/7/e36974/, International Registered Report Identifier, IRRID (DERR1-10.2196/36974).

Smartphone apps for point-of-care information summaries: systematic assessment of the quality and content

BACKGROUND

Clinicians need easy access to evidence-based information to inform their clinical practice. Point-of-care information summaries are increasingly available in the form of smartphone apps. However, the quality of information from the apps is questionable as there is currently no regulation on the content of the medical apps.

OBJECTIVES

This study aimed to systematically assess the quality and content of the medical apps providing point-of-care information summaries that were available in two major app stores. We evaluated apps designed specifically for healthcare professionals and assessed their content development, editorial policy, coverage of medical conditions and trustworthiness.

METHODS

We conducted a systematic assessment of medical apps providing point-of-care information summaries available in Google Play and Apple app stores. Apps launched or updated since January 2020 were identified through a systematic search using 42matters. Apps meeting the inclusion criteria were downloaded and assessed. The data extraction and app assessment were done in parallel and independently by at least two reviewers. Apps were evaluated against the adapted criteria: (1) general characteristics, (2) content presentation of the summaries, (3) editorial quality, (4) evidence-based methodology, (5) coverage (volume) of the medical conditions, (6) usability of apps and (7) trustworthiness of the app based on HONcode principles. HONcode principles are guidelines used to inform users about the credibility and reliability of health information online. The results were reported as a narrative review.

RESULTS

Eight medical apps met the inclusion criteria and were systematically appraised. Based on our evaluation criteria, UpToDate supported 16 languages, and all other apps were English. Bullet points and brief paragraphs were used in all apps, and only DynaMed and Micromedex and Pathway-medical knowledge provided a formal grading system for the strength of recommendations for all the medical conditions in their apps. All the other apps either lacked a formal grading system altogether or offered one for some of the medical conditions. About 30% of the editorial quality assessment and 47.5% of the evidence-based methodology assessment were unclear or missing. UpToDate contained the most point-of-care evidence-based documents with >10 500 documents. All apps except 5-Minute Clinical Consult and DynaMed and Micromedex were available for offline access. Only Medscape complied with the HONcode principles.

CONCLUSIONS

Future apps should report a more detailed evidence-based methodology, be accessible for offline use and support search in more than one language. There should be clearer information provided in future apps regarding the declaration of authorship and conflict of interest.

Efficacy of a basal insulin dose management smartphone application for controlling fasting blood glucose in patients with type-2 diabetes mellitus: A single-centre, randomised clinical study

OBJECTIVE

To explore the efficacy and safety of the 'Walk with you' application for titrating basal insulin (BI) doses in type-2 diabetes mellitus (T2DM) hospitalised patients.

METHODS

This was a randomised, single-centre, open-label, controlled clinical trial to compare the changes in fasting blood glucose (FBG) and postprandial blood glucose (PBG), time to reach target FBG (FBG-TRT), incidence of hypoglycaemia events and FBG coefficient of variation in the application group (weight-based titration of BI dose regimen) and control group (typical adjustment regimen).

PATIENTS

This study selected 173 patients with T2DM using basal-prandial insulin therapy who were admitted to Binhaiwan Central Hospital of Dongguan between December 2021 and December 2022. Patients were randomised to the control group or the application group (App group) and then titrated to achieve an FBG concentration of less than 7.0 mmol/L.

RESULTS

There were 86 patients in the control group and 87 patients in the App group. The FBG concentrations in the control and App groups were decreased by 6.77 ± 4.75 and 5.95 ± 4.06 mmol/L, respectively. The FBG-TRTs in the control and App groups were 3.80 ± 1.52 and 2.82 ± 1.34 days, respectively (p < .001). Fewer patients in the control group reached the FBG-TRT within 3 days than in the App group, with 46.5% and 71.3% of patients reaching that target, respectively. There was no significant between-group difference in hypoglycaemia incidence.

CONCLUSION

The use of this weight-based insulin dose titration protocol for BI app is effective and safe for achieving the target FBG in noncritically ill patients with T2DM and is free, easy to use and user friendly.

Development, validation and international certification of a health portal for people with disabilities

ABSTRACT Objectives: to develop, validate with specialists and internationally certify a virtual health portal, the D+Informação. Methods: a quantitative methodological study. Twenty-two expert judges validated the Portal in the health and computer science areas using the Content Validity Index and the Gwet test. International certification followed HONcode principles® to ensure the trust of information. Results: judges of health and computer science validated the portal obtaining a minimum Content Validity Index in more than 75% of the topics, in addition to the evaluation of general agreement, 0.253; content evaluation, 0.193, and interface evaluation, 0.230. All presented the value of Gwet with p ≤ 0,001. Conclusions: the portal D+Informação was developed, validated, internationally certified and is hosted on this website: https://demaisinformacao.com.br

mHealth apps for gestational diabetes mellitus that provide clinical decision support or artificial intelligence: A scoping review

AIMS

Gestational diabetes (GDM) is the most common metabolic disorder of pregnancy, requiring complex management and empowerment of those affected. Mobile health (mHealth) applications (apps) are proposed for streamlining healthcare service delivery, extending care relationships into the community, and empowering those affected by prolonged medical disorders to be equal collaborators in their healthcare. This review investigates mHealth apps intended for use with GDM; specifically those powered by artificial intelligence (AI) or providing decision support.

METHODS

A scoping review using the novel Survey Tool approach for collaborative literature Reviews (STaR) process was performed.

RESULTS

From 18 papers, 11 discrete GDM-based mHealth apps were identified, but only 3 were reasonably mature with only one currently in use in a clinical setting. Two-thirds of the apps provided condition-relevant contextual user feedback that could aid in patient self care. However, although each app targeted one or more components of the GDM clinical pathway, no app addressed the entirety from diagnosis to postpartum.

CONCLUSIONS

There are limited mHealth apps for GDM that incorporate AI or AI-based decision support. Many exist only to record patient information like blood glucose readings or diet, provide generic patient education or advice, or to reduce adverse events by providing medication or appointment alerts. Significant barriers remain that continue to limit the adoption of mHealth apps in clinical care settings. Further research and development are needed to deliver intelligent holistic mHealth apps using AI that can truly reduce healthcare resource use and improve outcomes by enabling patient self care in the community.

Privacy Policy Compliance of Chronic Disease Management Apps in China: Scale Development and Content Evaluation

Background

With the development of mobile health (mHealth), chronic disease management apps have brought not only the possibility of reducing the burden of chronic diseases but also huge privacy risks to patients’ health data.

Objective

The purpose of the study was to analyze the extent to which chronic disease management apps in China comply with the Personal Information Security Specification (PI Specification).

Methods

The compliance of 45 popular chronic disease management apps was evaluated from the perspective of the information life cycle. To conduct a fine-grained evaluation, a scale based on the PI Specification was developed. Finally, 6 level 1 indicators, 22 level 2 indicators, and 61 level 3 indicators were defined.

Results

There were 33/45 apps (73%) with a privacy policy, and the average score of these apps was 40.4 out of 100. Items of level 1 indicators with high scores included general characteristics (mean 51.9% [SD 28.1%]), information collection and use (mean 51.1% [SD 36.7%]), and information sharing and transfer (mean 50.3% [SD 33.5%]). Information storage and protection had the lowest compliance with PI Specification (mean 29.4% [SD 32.4%]). Few personal information (PI) controllers have stated how to handle security incidents, including security incident reporting (7/33, 21%), security incident notification (10/33, 30%), and commitment to bear corresponding legal responsibility for PI security incidents (1/33, 3%). The performance of apps in the stage of information destruction (mean 31.8% [SD 40.0%]) was poor, and only 21% (7/33) apps would notify third parties to promptly delete PI after individuals cancelled their accounts. Moreover, the scoring rate for rights of PI subjects is generally low (mean 31.2% [SD 35.5%]), especially for obtaining copies of PI (15%) and responding to requests (25%).

Conclusions

Although most chronic disease management apps had a privacy policy, the total compliance rate of the policy content was low, especially in the stage of information storage and protection. Thus, the field has a long way to go with regard to compliance around personal privacy protection in China.