Data Integration for Mobile Wellness Apps to Support Treatment of GDM Sarita Pais Auckland University of Technology Auckland New Zealand +64 9 921 9999 ext. 8953 sarita.pais@aut.ac.nz Dave Parry, Elaine Rush Auckland University of Technology Auckland New Zealand +64 9 921 9999 ext. 8918, +64 9 9219758 dave.parry@aut.ac.nz, elaine.rush@aut.ac.nz Janet Rowan National Women’s Health Auckland New Zealand +64 211662988 janetrowan1@gmail.com ABSTRACTData collected through mobile wellness apps is not currently effectively captured for clinical data use. It may be helpful to share data from wellness apps collected by the patients with clinicians. This study focuses on women with gestational diabetes mellitus (GDM). It is suggested that the team of clinicians taking care of these women could benefit if wellness data such as food diaries, exercise and glucose readings maintained in various mobile apps and blood glucose meters, are integrated using a software system into a format semantically interoperable with other health information systems (HIS). Potential clinical standards are explored in this work to be able to propose a possible solution for this interoperability. Categories and Subject Descriptors•Applied Computing ?Enterprise Computing ?HealthcareInformation systemKeywordsMobile wellness apps; gestational mellitus diabetes; data interoperability INTRODUCTION Obesity-related chronic diseases are on the rise globally. There is a need to support healthy lifestyles and reduce the burden on the public health system. In 2010 New Zealand initiated a project arising from the National Health IT Plan and has made progress in this direction [1]. Patients are empowered to take care of their health through patient portals. Some medical centres have their patient portal tethered to their HIS. Patients can request a booking for a doctor’s appointment and view their medical reports. The maternity record view is part of this initiative where patients are allowed to view their medical records. Tethered patient portals currently only allow patients to view their medical data such as blood test results. The portal has no facility for the patient to feed in their wellness data such as blood glucose readings. There are many mobile wellness apps available on Android and iOS which allow users to keep track of their wellness data, such as blood glucose readings, food diaries and physical activity. In many mobile apps the data can be shared with caregivers and clinicians by email. However such data is not currently captured and stored in a database for clinical use. DATA INTEROPERABILITY There is no universally accepted standard for data transfer from mobile wellness apps to clinical databases. Similar issues are faced in clinical systems when patient health data from one medical system need to be used in another system. Clinical standards such as Health Level Seven (HL7), Systematized Nomenclature of Medicine - Clinical Terms (SNOMED CT) are used to allow clinical data interoperability. Such clinical standards allow semantic interoperability for health data, so that when it is transferred from another system it conveys the same meaning in the new system. 2.1 Mobile Wellness Apps Many patient portals do not allow patients to enter their health data. Clinicians do not trust the quality of data entered by patients [2] and documented blood glucose results often do not match the meter directly. However mobile wellness apps for food diaries are quite intuitive and have good user interface with drop down options to select food from the food database as in My Meal Mate [3] and Pattern-Oriented Nutrition diary [4]. Mobile apps with required functionalities need to be identified, which could be challenging when there are around 8000 apps available on healthy living, exercise and diet [5]. The US FDA has announced regulations for mobile apps which connect to medical devices such as glucose meters. Emerging new data about wellness from devices such as smartphones and home devices have been discussed recently [6]. Re-use of such data needs to be in a format such that allows for semantic interoperability. 2.2 Data Integration Extensible Markup Language (XML), Structured Query Language – Data Definition Language (SQL-DDL), Resource DescriptionFramework (RDF) and ontologies are different ways to achieve successful interoperability [7]. However this is not easily achieved and there are operational issues. Various XML standards used in business to business (B2B) interoperability were discussed by Lampathaki et al. [8]. The Clio project [9] provided algorithms to map data from source schema to the target schema. Such declarative schema mappings have previously been used in related research [10] [11]. Such data integration projects require the user Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for prof i t or commercial advantage and that copies bear this notice and the full citation on the fi rst p age. To copy otherwise, to republish, to post on servers or to redistribute to lists, requires prior specif i c permission and/or a fee.ACE ’16 Canberra, ACT AustraliaCopyright 2016 ACM 978-1-4503-4042-7/16/02 ...$15.00.http://dx.doi.org/10.1145/2843043.2843382
