Mobile personal health records for pregnancy monitoring functionalities: Analysis and potential

• Entering or Calculating the estimated birth date is the only feature used in all the analyzed mPHRs for pregnancy monitoring.
• Some applications only provide information to the users and others focus on monitoring the information provided by the users.
• The less frequently used feature in the mPHRs for pregnancy monitoring studied is the geolocation of nearby medical services.
• Only 9% of the evaluated mPHRs include at least two methods of data protection and 12% use a password method of protection.
• Connecting sensors to mPHRs for pregnancy monitoring should be taken into consideration in order to provide accurate records.

Background and objectivePersonal Health Records (PHRs) are a rapidly growing area of health information technology. PHR users are able to manage their own health data and communicate with doctors in order to improve healthcare quality and efficiency. Mobile PHR (mPHR) applications for mobile devices have obtained an interesting market quota since the appearance of more powerful mobile devices. These devices allow users to gain access to applications that used to be available only for personal computers. This paper analyzes the functionalities of mobile PHRs that are specific to pregnancy monitoring.MethodsA well-known Systematic Literature Review (SLR) protocol was used in the analysis process. A questionnaire was developed for this task, based on the rigorous study of scientific literature concerning pregnancy and applications available on the market, with 9 data items and 35 quality assessments. The data items contain calendars, pregnancy information, health habits, counters, diaries, mobile features, security, backup, configuration and architectural design.ResultsA total of 33 mPHRs for pregnancy monitoring, available for iOS and Android, were selected from Apple App store and Google Play store, respectively. The results show that none of the mPHRs selected met 100% of the functionalities analyzed in this paper. The highest score achieved was 77%, while the lowest was 17%.ConclusionsIn this paper, these features are discussed and possible paths for future development of similar applications are proposed, which may lead to a more efficient use of smartphone capabilities.