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      iOS Appstore-Based Phone Apps for Diabetes Management: Potential for Use in Medication Adherence

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          Abstract

          Background

          Currently, various phone apps have been developed to assist patients. Many of these apps are developed to assist patients in the self-management of chronic diseases such as diabetes. It is essential to analyze these various apps to understand the key features that would potentially be instrumental in helping patients successfully achieve goals in disease self-management.

          Objective

          The objective of this study was to conduct a review of all the available diabetes-related apps in the iOS App Store to evaluate which diabetic app is more interactive and offers a wide variety of operations such as monitoring glucose, water, carbohydrate intake, weight, body mass index (BMI), medication, blood pressure (BP) levels, reminders or push notifications, food database, charts, exercise management, email, sync between devices, syncing data directly to the prescribers, and other miscellaneous functions such as (Twitter integration, password protection, retina display, barcode scanner, apple watch functionality, and cloud syncing).

          Methods

          Data was gathered using the iOS App Store on an iPad. The search term “diabetes” resulted in 1209 results. Many of the results obtained were remotely related to diabetes and focused mainly on diet, exercise, emergency services, refill reminders, providing general diabetes information, and other nontherapeutic options. We reviewed each app description and only included apps that were meant for tracking blood glucose levels. All data were obtained in one sitting by one person on the same device, as we found that carrying out the search at different times or on different devices (iPhones) resulted in varying results. Apps that did not have a feature for tracking glucose levels were excluded from the study.

          Results

          The search resulted in 1209 results; 85 apps were retained based on the inclusion criteria mentioned above. All the apps were reviewed for average customer ratings, number of reviews, price, and functions. Of all the apps surveyed, 18 apps with the highest number of user ratings were used for in-depth analysis. Of these 18 apps, 50% (9/18) also had a medication adherence function. Our analysis revealed that the Diabetes logbook used by the mySugr app was one of the best; it differentiated itself by introducing fun as a method of increasing adherence.

          Conclusions

          A large variation was seen in patient ratings of app features. Many patient reviewers desired simplicity of app functions. Glucose level tracking and email features potentially helped patients and health care providers manage the disease more efficiently. However, none of the apps could sync data directly to the prescribers. Additional features such as graph customization, availability of data backup, and recording previous entries were also requested by many users. Thus, the use of apps in disease management and patient and health-care provider involvement in future app refinement and development should be encouraged.

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          Most cited references23

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          Prevalence of obesity, diabetes, and obesity-related health risk factors, 2001.

          Obesity and diabetes are increasing in the United States. To estimate the prevalence of obesity and diabetes among US adults in 2001. Random-digit telephone survey of 195 005 adults aged 18 years or older residing in all states participating in the Behavioral Risk Factor Surveillance System in 2001. Body mass index, based on self-reported weight and height and self-reported diabetes. In 2001 the prevalence of obesity (BMI > or =30) was 20.9% vs 19.8% in 2000, an increase of 5.6%. The prevalence of diabetes increased to 7.9% vs 7.3% in 2000, an increase of 8.2%. The prevalence of BMI of 40 or higher in 2001 was 2.3%. Overweight and obesity were significantly associated with diabetes, high blood pressure, high cholesterol, asthma, arthritis, and poor health status. Compared with adults with normal weight, adults with a BMI of 40 or higher had an odds ratio (OR) of 7.37 (95% confidence interval [CI], 6.39-8.50) for diagnosed diabetes, 6.38 (95% CI, 5.67-7.17) for high blood pressure, 1.88 (95% CI,1.67-2.13) for high cholesterol levels, 2.72 (95% CI, 2.38-3.12) for asthma, 4.41 (95% CI, 3.91-4.97) for arthritis, and 4.19 (95% CI, 3.68-4.76) for fair or poor health. Increases in obesity and diabetes among US adults continue in both sexes, all ages, all races, all educational levels, and all smoking levels. Obesity is strongly associated with several major health risk factors.
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            Multiple Chronic Conditions Among US Adults: A 2012 Update

            The objective of this research was to update earlier estimates of prevalence rates of single chronic conditions and multiple (>2) chronic conditions (MCC) among the noninstitutionalized, civilian US adult population. Data from the 2012 National Health Interview Survey (NHIS) were used to generate estimates of MCC for US adults and by select demographic characteristics. Approximately half (117 million) of US adults have at least one of the 10 chronic conditions examined (ie, hypertension, coronary heart disease, stroke, diabetes, cancer, arthritis, hepatitis, weak or failing kidneys, current asthma, or chronic obstructive pulmonary disease [COPD]). Furthermore, 1 in 4 adults has MCC.
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              The Smartphone in Medicine: A Review of Current and Potential Use Among Physicians and Students

              Background Advancements in technology have always had major impacts in medicine. The smartphone is one of the most ubiquitous and dynamic trends in communication, in which one’s mobile phone can also be used for communicating via email, performing Internet searches, and using specific applications. The smartphone is one of the fastest growing sectors in the technology industry, and its impact in medicine has already been significant. Objective To provide a comprehensive and up-to-date summary of the role of the smartphone in medicine by highlighting the ways in which it can enhance continuing medical education, patient care, and communication. We also examine the evidence base for this technology. Methods We conducted a review of all published uses of the smartphone that could be applicable to the field of medicine and medical education with the exclusion of only surgical-related uses. Results In the 60 studies that were identified, we found many uses for the smartphone in medicine; however, we also found that very few high-quality studies exist to help us understand how best to use this technology. Conclusions While the smartphone’s role in medicine and education appears promising and exciting, more high-quality studies are needed to better understand the role it will have in this field. We recommend popular smartphone applications for physicians that are lacking in evidence and discuss future studies to support their use.
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                Author and article information

                Contributors
                Journal
                JMIR Diabetes
                JMIR Diabetes
                JD
                JMIR Diabetes
                JMIR Publications (Toronto, Canada )
                2371-4379
                Jul-Dec 2017
                11 July 2017
                : 2
                : 2
                : e12
                Affiliations
                [1 ] Philadelphia College of Osteopathic Medicine - GA campus School of Pharmacy Suwanee, GA United States
                Author notes
                Corresponding Author: Harish Singh Parihar harishpa@ 123456pcom.edu
                Author information
                http://orcid.org/0000-0002-7612-6692
                http://orcid.org/0000-0001-8982-0192
                http://orcid.org/0000-0002-0632-2196
                http://orcid.org/0000-0002-2801-8726
                http://orcid.org/0000-0002-0779-0418
                http://orcid.org/0000-0001-6147-7732
                Article
                v2i2e12
                10.2196/diabetes.6468
                6238890
                30291096
                316a79fb-509b-4619-bb09-d646a3336521
                ©Mark Martinez, Su Bin Park, Isaac Maison, Vicky Mody, Lewis Sungkon Soh, Harish Singh Parihar. Originally published in JMIR Diabetes (http://diabetes.jmir.org), 11.07.2017.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License ( https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Diabetes, is properly cited. The complete bibliographic information, a link to the original publication on http://diabetes.jmir.org/.as well as this copyright and license information must be included.

                History
                : 8 August 2016
                : 10 October 2016
                : 1 February 2017
                : 14 April 2017
                Categories
                Original Paper
                Case Report

                diabetes,telemedicine,blood glucose self-monitoring glucose monitoring,mobile applications,self-care,mobile health

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