Using Smartphones for Accountable Care and Evidence-based Decision Making in Managing Gestational Diabetes: An Australian Case Study

Abstract

Better managing diabetes has become a global priority, especially given the exponential increase in the number of diabetes patients and the financial implications of treating this silent epidemic. In this paper, we focus on how it might be possible to use a mobile technology solution to support and enable superior diabetes monitoring and management. To test this solution, we examined the context of gestational diabetes and adopted a non-blinded randomized control trial with two-arm cross over applied to a private hospital in Victoria, Australia. Further, we use an accountable care system as the theoretical lens and, from this, develop a conceptual framework to bridge evidence-based management with technologies. Theoretically, we unpack McCleallan, McKethan, Lewis, Roski, and Fisher's (2010) study with our conceptual framework that comprises providers for information (evidence-based management) and technology (smartphone). We enhance Muhlestein, Croshaw, Merrill, Pena, and James' (2013) accountable care paradigm with three concepts: 1) quality of life, 2) evidence-based management, and 3) affordable care. From the perspective of practice, far-reaching implications have arisen particularly for hospital management pertaining to the cost and quality of care issues. In particular, it appears that adapting mobile technology solutions such as smartphones to support various aspects of care and patient-clinician interactions is a prudent choice to minimize costs and yet provide highquality care.

The use of mobile health interventions for gestational diabetes mellitus: a descriptive literature review

“…Smartphone-based: Smartphones support various aspects of care and patient-clinician interactions, provide high-quality care and support self-management of GDM [ 46 , 47 , 54 , 57 , 58 , 62 ]. The use of m-health can increase GDM patients’ compliance with lifestyle interventions and reduce future risk of type 2 diabetes mellitus and its sequelae [ 81 ]; however, this result was not supported by McLean et al [ 41 ].…”

“…Six studies have evaluated disease costs and reported that m-health interventions are economically cost-effective and can reduce disease costs [ 49 , 51 , 54 , 58 , 61 , 64 ].…”

Propuesta y evaluación de un sistema de telemedicina y de ayuda a la decisión para el cuidado de pacientes con diabetes gestacional

“…Las nuevas posibilidades que ofrecen los teléfonos de nueva generación ha posibilitado el desarrollo de numerosas aplicaciones para este tipo de plataformas (Wickramasinghe, 2015;Lanzola et al, 2016). La mayoría de ellas permite transferir los valores del medidor de glucosa al teléfono mediante Bluetooth (Bartholomew et al, 2015), etiquetarlas manualmente con la ingesta (DNO, CMDA o CNA) y momento (PRE o POS) correspondientes, y enviarlas a un servidor para su evaluación remota por parte del personal médico (Wickramasinghe, 2015). La visualización suele imitar las cartillas de papel de las pacientes y suelen permitir la introducción de otros datos de monitorización como por ejemplo la dosis de insulina, o incluso solicitar tiras reactivas al equipo médico.…”