IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v17y2020i20p7590-d431001.html
   My bibliography  Save this article

Impact of Non-Tailored One-Way Automated Short Messaging Service (OASMS) on Glycemic Control in Type 2 Diabetes: A Retrospective Feasibility Study

Author

Listed:
  • Ahmad Alamer

    (Center for Health Outcomes and Pharmaco-Economic Research, University of Arizona College of Pharmacy, Tucson, AZ 85721, USA
    Department of Pharmacy Practice, College of Pharmacy, Prince Sattam Bin Abdulaziz University, Alkharj 16278, Saudi Arabia)

  • Charles Palm

    (Banner—University Medicine Endocrinology and Diabetes Clinic, Tucson, AZ 85714, USA)

  • Abdulaziz S. Almulhim

    (Department of Pharmacy Practice, College of Clinical Pharmacy, King Faisal University, Al-Ahsa 31982, Saudi Arabia)

  • Charisse Te

    (Banner—University Medicine Endocrinology and Diabetes Clinic, Tucson, AZ 85714, USA
    Department of Medicine, Division of Endocrinology, Diabetes and Metabolism, College of Medicine, Tucson, AZ 85724, USA)

  • Merri L. Pendergrass

    (Banner—University Medicine Endocrinology and Diabetes Clinic, Tucson, AZ 85714, USA
    Department of Medicine, Division of Endocrinology, Diabetes and Metabolism, College of Medicine, Tucson, AZ 85724, USA
    Department of Pharmacy Practice & Science, College of Pharmacy, The University of Arizona, Tucson, AZ 85721, USA)

  • Maryam T. Fazel

    (Banner—University Medicine Endocrinology and Diabetes Clinic, Tucson, AZ 85714, USA
    Department of Medicine, Division of Endocrinology, Diabetes and Metabolism, College of Medicine, Tucson, AZ 85724, USA
    Department of Pharmacy Practice & Science, College of Pharmacy, The University of Arizona, Tucson, AZ 85721, USA)

Abstract

Short message service (SMS) is easily accessible and potentially an ideal platform for delivering patient-targeted messages. However, an effective SMS dosing strategy is not well established. Our purpose was to evaluate the impact of diabetes self-care promoting messages via non-tailored one-way automated SMS (OASMS) on glycemic control in type 2 diabetes (T2DM). The change in hemoglobin A1c (HbA1c) was compared between patients who received the service and those who did not. This retrospective quasi-experimental pre–post feasibility study was conducted at an academic medical center endocrinology clinic. English-speaking adults (≥18 years) with uncontrolled T2DM (HbA1c ≥ 8%) were included. A total of 69 patients (intervention n = 34; control n = 35) met the inclusion criteria. The mean (±SD) baseline HbA1c values were 10.2% (±1.9%) and 9.9% (±1.7%) in the intervention and control arms, respectively. Median follow-up was 3.3 months (IQR = 3–4.2). An ANCOVA model adjusted for baseline HbA1c and age showed an estimated HbA1c reduction difference of −0.97% (95% CI, −1.73 to −0.20%, p = 0.014), favoring the intervention arm. Inverse propensity score weighting confirmed the ANCOVA results. Our study suggests that adding diabetes self-care promoting messages via non-tailored OASMS to usual care improves glycemic control in poorly controlled T2DM. Larger and longer studies are needed to evaluate different features of the non-tailored OASMS strategy.

Suggested Citation

  • Ahmad Alamer & Charles Palm & Abdulaziz S. Almulhim & Charisse Te & Merri L. Pendergrass & Maryam T. Fazel, 2020. "Impact of Non-Tailored One-Way Automated Short Messaging Service (OASMS) on Glycemic Control in Type 2 Diabetes: A Retrospective Feasibility Study," IJERPH, MDPI, vol. 17(20), pages 1-10, October.
    • Handle: RePEc:gam:jijerp:v:17:y:2020:i:20:p:7590-:d:431001
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/17/20/7590/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1660-4601/17/20/7590/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. van der Wal, Willem M. & Geskus, Ronald B., 2011. "ipw: An R Package for Inverse Probability Weighting," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 43(i13).
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Meyer, Maximilian & Hulke, Carolin & Kamwi, Jonathan & Kolem, Hannah & Börner, Jan, 2022. "Spatially heterogeneous effects of collective action on environmental dependence in Namibia’s Zambezi region," World Development, Elsevier, vol. 159(C).
    2. Waverly Wei & Maya Petersen & Mark J van der Laan & Zeyu Zheng & Chong Wu & Jingshen Wang, 2023. "Efficient targeted learning of heterogeneous treatment effects for multiple subgroups," Biometrics, The International Biometric Society, vol. 79(3), pages 1934-1946, September.
    3. Albert Stuart Reece & Gary Kenneth Hulse, 2022. "European Epidemiological Patterns of Cannabis- and Substance-Related Congenital Neurological Anomalies: Geospatiotemporal and Causal Inferential Study," IJERPH, MDPI, vol. 20(1), pages 1-35, December.
    4. Albert Stuart Reece & Gary Kenneth Hulse, 2022. "European Epidemiological Patterns of Cannabis- and Substance-Related Body Wall Congenital Anomalies: Geospatiotemporal and Causal Inferential Study," IJERPH, MDPI, vol. 19(15), pages 1-38, July.
    5. Stjepan Srhoj & Michael Lapinski & Janette Walde, 2019. "Size matters? Impact evaluation of business development grants on SME performance," Working Papers 2019-14, Faculty of Economics and Statistics, Universität Innsbruck.
    6. Satyam Kumar & Yelleti Vivek & Vadlamani Ravi & Indranil Bose, 2023. "Causal Inference for Banking Finance and Insurance A Survey," Papers 2307.16427, arXiv.org.
    7. Sebastian Daza & Alberto Palloni & Jerrett Jones, 2020. "The Consequences of Incarceration for Mortality in the United States," Demography, Springer;Population Association of America (PAA), vol. 57(2), pages 577-598, April.
    8. Andrea Ciccarelli & Elena Fabrizi & Eleonora Romano & Pietro Zoppoli, 2022. "Health, Well-Being and Work History Patterns: Insight on Territorial Differences," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 161(2), pages 629-647, June.
    9. Bastien Bourrion & Cécile Souty & Lucie Fournier & Ana-Maria Vilcu & Thierry Blanchon & Pierre-Yves Böelle & Thomas Hanslik & Mathilde François, 2021. "Bisphosphonate Use and Hospitalization for Hip Fractures in Women: An Observational Population-Based Study in France," IJERPH, MDPI, vol. 18(16), pages 1-11, August.
    10. Albert Stuart Reece & Gary Kenneth Hulse, 2022. "Socioeconomic, Ethnocultural, Substance- and Cannabinoid-Related Epidemiology of Down Syndrome USA 1986–2016: Combined Geotemporospatial and Causal Inference Investigation," IJERPH, MDPI, vol. 19(20), pages 1-37, October.
    11. Maria Llistosella & Pere Castellvi & Andrea Miranda-Mendizabal & Silvia Recoder & Ester Calbo & Marc Casajuana-Closas & David Leiva & Rumen Manolov & Nuria Matilla-Santander & Carlos G. Forero, 2022. "Low Resilience Was a Risk Factor of Mental Health Problems during the COVID-19 Pandemic but Not in Individuals Exposed to COVID-19: A Cohort Study in Spanish Adult General Population," IJERPH, MDPI, vol. 19(22), pages 1-15, November.
    12. Jan-Philip Steinmann & Hannes Kröger & Jörg Hartmann & Theresa M. Entringer, 2024. "Did Religious Well-Being Benefits Converge or Diverge During the Early Stages of the COVID-19 Pandemic in Germany?," Journal of Happiness Studies, Springer, vol. 25(7), pages 1-35, October.
    13. Benedetta Pongiglione & Aleksandra Torbica, 2022. "How real can we get in generating real world evidence? Exploring the opportunities of routinely collected administrative data for evaluation of medical devices," Health Economics, John Wiley & Sons, Ltd., vol. 31(S1), pages 25-43, September.
    14. Juraj Bodik, 2024. "Extreme Treatment Effect: Extrapolating Dose-Response Function into Extreme Treatment Domain," Mathematics, MDPI, vol. 12(10), pages 1-36, May.
    15. Kallus Nathan & Santacatterina Michele, 2021. "Optimal balancing of time-dependent confounders for marginal structural models," Journal of Causal Inference, De Gruyter, vol. 9(1), pages 345-369, January.
    16. Bartolucci, Francesco & Grilli, Leonardo & Pieroni, Luca, 2012. "Estimating dynamic causal effects with unobserved confounders: a latent class version of the inverse probability weighted estimator," MPRA Paper 43430, University Library of Munich, Germany.
    17. Stjepan Srhoj & Michal Lapinski & Janette Walde, 2021. "Impact evaluation of business development grants on SME performance," Small Business Economics, Springer, vol. 57(3), pages 1285-1301, October.
    18. Javier Perez-Saez & María-Eugenia Zaballa & Julien Lamour & Sabine Yerly & Richard Dubos & Delphine S. Courvoisier & Jennifer Villers & Jean-François Balavoine & Didier Pittet & Omar Kherad & Nicolas , 2023. "Long term anti-SARS-CoV-2 antibody kinetics and correlate of protection against Omicron BA.1/BA.2 infection," Nature Communications, Nature, vol. 14(1), pages 1-9, December.
    19. Albert Stuart Reece & Gary Kenneth Hulse, 2022. "Cannabis- and Substance-Related Epidemiological Patterns of Chromosomal Congenital Anomalies in Europe: Geospatiotemporal and Causal Inferential Study," IJERPH, MDPI, vol. 19(18), pages 1-51, September.
    20. Albert Stuart Reece & Gary Kenneth Hulse, 2022. "Epidemiology of Δ8THC-Related Carcinogenesis in USA: A Panel Regression and Causal Inferential Study," IJERPH, MDPI, vol. 19(13), pages 1-27, June.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jijerp:v:17:y:2020:i:20:p:7590-:d:431001. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.