Menstrual Cycle Tracking Apps: An Applied Combined Medical and Data Privacy Scoring.

Today, many menstruating individuals track their cycles with mobile apps. These cycle apps use a lot of highly sensitive personal data. The goal of this study is to evaluate current cycle apps based on data privacy and medical criteria. First, a market analysis of currently available apps was conducted. Second, a scoring system was developed based on Digital Health application (Digitale Gesundheitsanwendungen, DiGA in German) guidelines, Mobile App Rating Scale (MARS), and other resources. A total of 18 apps were evaluated. The final scores (range from 0 to 1) ranged from 0.12 (worst result) to 0.64 (best result). The average "data privacy score" was 0.4, and the average "medical score" was 0.11. Only six apps received any points in the medical part of the scoring. A clear weakness of many tested apps was the issue of data minimization. 89% of the apps had permissions that were not necessary for this type of health app.

Barriers and Facilitators to the Implementation of eHealth Services: Systematic Literature Analysis.

BACKGROUND: The field of eHealth has a history of more than 20 years. During that time, many different eHealth services were developed. However, factors influencing the adoption of such services were seldom the main focus of analyses. For this reason, organizations adopting and implementing eHealth services seem not to be fully aware of the barriers and facilitators influencing the integration of eHealth services into routine care. OBJECTIVE: The objective of this work is to provide (1) a comprehensive list of relevant barriers to be considered and (2) a list of facilitators or success factors to help in planning and implementing successful eHealth services. METHODS: For this study, a twofold approach was applied. First, we gathered experts' current opinions on facilitators and barriers in implementing eHealth services via expert discussions at two health informatics conferences held in Europe. Second, we conducted a systematic literature analysis concerning the barriers and facilitators for the implementation of eHealth services. Finally, we merged the results of the expert discussions with those of the systematic literature analysis. RESULTS: Both expert discussions (23 and 10 experts, respectively) identified 15 barriers and 31 facilitators, whereas 76 barriers and 268 facilitators were found in 38 of the initial 56 articles published from 12 different countries. For the analyzed publications, the count of distinct barriers reported ranged from 0 to 40 (mean 10.24, SD 8.87, median 8). Likewise, between 0 and 48 facilitators were mentioned in the literature (mean 9.18, SD 9.33, median 6). The combination of both sources resulted in 77 barriers and 292 facilitators for the adoption and implementation of eHealth services. CONCLUSIONS: This work contributes a comprehensive list of barriers and facilitators for the implementation and adoption of eHealth services. Addressing barriers early, and leveraging facilitators during the implementation, can help create eHealth services that better meet the needs of users and provide higher benefits for patients and caregivers.