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      The Mobile Insulin Titration Intervention (MITI) for Insulin Adjustment in an Urban, Low-Income Population: Randomized Controlled Trial

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          Abstract

          Background

          Diabetes patients are usually started on a low dose of insulin and their dose is adjusted or “titrated” according to their blood glucose levels. Insulin titration administered through face-to-face visits with a clinician can be time consuming and logistically burdensome for patients, especially those of low socioeconomic status (SES). Given the wide use of mobile phones among this population, there is the potential to use short message service (SMS) text messaging and phone calls to perform insulin titration remotely.

          Objective

          The goals of this pilot study were to (1) evaluate if our Mobile Insulin Titration Intervention (MITI) intervention using text messaging and phone calls was effective in helping patients reach their optimal insulin glargine dose within 12 weeks, (2) assess the feasibility of the intervention within our clinic setting and patient population, (3) collect data on the cost savings associated with the intervention, and (4) measure patient satisfaction with the intervention.

          Methods

          This was a pilot study evaluating an intervention for patients requiring insulin glargine titration in the outpatient medical clinic of Bellevue Hospital Center in New York City. Patients in the intervention arm received weekday SMS text messages from a health management platform requesting their fasting blood glucose values. The clinic’s diabetes nurse educator monitored the texted responses on the platform website each weekday for alarm values. Once a week, the nurse reviewed the glucose values, consulted the MITI titration algorithm, and called patients to adjust their insulin dose. Patients in the usual care arm continued to receive their standard clinic care for insulin titration. The primary outcome was whether a patient reached his/her optimal insulin glargine dose within 12 weeks.

          Results

          A total of 61 patients consented and were randomized into the study. A significantly greater proportion of patients in the intervention arm reached their optimal insulin glargine dose than patients in the usual care arm (88%, 29/33 vs 37%, 10/27; P<.001). Patients responded to 84.3% (420/498) of the SMS text messages requesting their blood glucose values. The nurse reached patients within 2 attempts or by voicemail 91% of the time (90/99 assigned calls). When patients traveled to the clinic, they spent a median of 45 minutes (IQR 30-60) on travel and 39 minutes (IQR 30-64) waiting prior to appointments. A total of 61% (37/61) of patients had appointment copays. After participating in the study, patients in the intervention arm reported higher treatment satisfaction than those in the usual care arm.

          Conclusions

          MITI is an effective way to help low-SES patients reach their optimal insulin glargine dose using basic SMS text messaging and phone calls. The intervention was feasible and patients were highly satisfied with their treatment. The intervention was cost saving in terms of time for patients, who were able to have their insulin titrated without multiple clinic appointments. Similar interventions should be explored to improve care for low-SES patients managing chronic disease.

          Trial Registration

          Clinicaltrials.gov NCT01879579; https://clinicaltrials.gov/ct2/show/NCT01879579 (Archived by WebCite at http://www.webcitation.org/6YZik33L3).

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          Most cited references29

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          A mobile health intervention for inner city patients with poorly controlled diabetes: proof-of-concept of the TExT-MED program.

          Numerous mobile health (mHealth) interventions are being developed to aid in management of complex chronic medical conditions. However, the acceptance of mHealth programs by low-income, bilingual populations has not yet been evaluated. The Trial to Examine Text-based mHealth for Emergency department patients with Diabetes (TExT-MED) program is a text message-based mHealth program designed specifically for resource-poor patients with diabetes. We conducted a prospective proof-of-concept trial to assess satisfaction and preliminary effectiveness of the TExT-MED program. A consecutive sample of adult patients in the emergency department with diabetes and a text message-capable mobile phone was enrolled in the TExT-MED program. Participants received three text messages daily for 3 weeks in English or Spanish in the following domains: educational/motivational, medication reminders, healthy living challenges, diabetes trivia, and links to free diabetes management tools. Twenty-three patients with diabetes (median hemoglobin A1c, 8.9%) were enrolled in TExT-MED. In the week before TExT-MED, 56.5% of subjects reported eating fruits/vegetables daily versus 83% after, 43.5% reported exercising before versus 74% after, and 74% reported performing foot checks before versus 85% after. Self-efficacy, measured by the Diabetes Empowerment Scale-Short Form, improved from 3.9 to 4.2. Scores on the Morisky Medication Adherence Scale improved more dramatically from 3.5 to 4.75. Ninety percent of participants indicated they would like to continue the program, and 100% would recommend the program to family or friends. This pilot trial of the TExT-MED program demonstrated increased healthy behaviors, improved diabetes self-efficacy and medication adherence, and received excellent satisfaction scores in resource-poor, inner city patients with diabetes.
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            Smartphone apps for calculating insulin dose: a systematic assessment

            Background Medical apps are widely available, increasingly used by patients and clinicians, and are being actively promoted for use in routine care. However, there is little systematic evidence exploring possible risks associated with apps intended for patient use. Because self-medication errors are a recognized source of avoidable harm, apps that affect medication use, such as dose calculators, deserve particular scrutiny. We explored the accuracy and clinical suitability of apps for calculating medication doses, focusing on insulin calculators for patients with diabetes as a representative use for a prevalent long-term condition. Methods We performed a systematic assessment of all English-language rapid/short-acting insulin dose calculators available for iOS and Android. Results Searches identified 46 calculators that performed simple mathematical operations using planned carbohydrate intake and measured blood glucose. While 59% (n = 27/46) of apps included a clinical disclaimer, only 30% (n = 14/46) documented the calculation formula. 91% (n = 42/46) lacked numeric input validation, 59% (n = 27/46) allowed calculation when one or more values were missing, 48% (n = 22/46) used ambiguous terminology, 9% (n = 4/46) did not use adequate numeric precision and 4% (n = 2/46) did not store parameters faithfully. 67% (n = 31/46) of apps carried a risk of inappropriate output dose recommendation that either violated basic clinical assumptions (48%, n = 22/46) or did not match a stated formula (14%, n = 3/21) or correctly update in response to changing user inputs (37%, n = 17/46). Only one app, for iOS, was issue-free according to our criteria. No significant differences were observed in issue prevalence by payment model or platform. Conclusions The majority of insulin dose calculator apps provide no protection against, and may actively contribute to, incorrect or inappropriate dose recommendations that put current users at risk of both catastrophic overdose and more subtle harms resulting from suboptimal glucose control. Healthcare professionals should exercise substantial caution in recommending unregulated dose calculators to patients and address app safety as part of self-management education. The prevalence of errors attributable to incorrect interpretation of medical principles underlines the importance of clinical input during app design. Systemic issues affecting the safety and suitability of higher-risk apps may require coordinated surveillance and action at national and international levels involving regulators, health agencies and app stores. Electronic supplementary material The online version of this article (doi:10.1186/s12916-015-0314-7) contains supplementary material, which is available to authorized users.
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              National diabetes statistics report: estimates of diabetes and its burden in the United States, 2014

              (2014)
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                Author and article information

                Contributors
                Journal
                J Med Internet Res
                J. Med. Internet Res
                JMIR
                Journal of Medical Internet Research
                JMIR Publications Inc. (Toronto, Canada )
                1439-4456
                1438-8871
                July 2015
                17 July 2015
                : 17
                : 7
                : e180
                Affiliations
                [1] 1Division of General Internal Medicine and Clinical Innovation Department of Medicine New York University School of Medicine New York, NYUnited States
                [2] 2Bellevue Hospital Center New York, NYUnited States
                [3] 3Gouverneur Diagnostic and Treatment Center New York, NYUnited States
                [4] 4Department of Healthcare Policy and Research Weill Cornell Medical College New York, NYUnited States
                [5] 5Division of Biostatistics Department of Population Health New York University School of Medicine New York, NYUnited States
                [6] 6Department of Population Health New York University School of Medicine New York, NYUnited States
                [7] 7Department of Veterans Affairs New York Harbor Healthcare System New York, NYUnited States
                Author notes
                Corresponding Author: Victoria Moynihan Victoria.Ramsay@ 123456nyumc.org
                Author information
                http://orcid.org/0000-0003-2956-5876
                http://orcid.org/0000-0002-5480-0578
                http://orcid.org/0000-0001-9165-3100
                http://orcid.org/0000-0003-1543-0962
                http://orcid.org/0000-0003-4943-6756
                http://orcid.org/0000-0001-7697-8759
                http://orcid.org/0000-0003-0104-9140
                http://orcid.org/0000-0001-8037-1028
                http://orcid.org/0000-0003-1360-4324
                Article
                v17i7e180
                10.2196/jmir.4716
                4527003
                26187303
                dc070833-3ecd-4944-8b2c-9a50fe2ebae0
                ©Natalie Levy, Victoria Moynihan, Annielyn Nilo, Karyn Singer, Lidia S Bernik, Mary-Ann Etiebet, Yixin Fang, James Cho, Sundar Natarajan. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 17.07.2015.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on http://www.jmir.org/, as well as this copyright and license information must be included.

                History
                : 18 May 2015
                : 13 June 2015
                : 18 June 2015
                : 29 June 2015
                Categories
                Original Paper
                Original Paper

                Medicine
                patient-centered care,health care disparities,telemedicine,remote consultation,cell phones,insulin, long-acting,text messaging

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