Evaluación de la Eficacia de la Telemedicina en el Manejo de la Diabetes: Un Vistazo a un Estudio Retrospectivo en un Área Urbana con Población Médicamente Desatendida (UMUPA)

Evaluación de la Eficacia de la Telemedicina en el Manejo de la Diabetes: Un Vistazo a un Estudio Retrospectivo en un Área Urbana con Población Médicamente Desatendida (UMUPA)

Autores/as

Palabras clave:

Telemedicina, Manejo de la Diabetes, Estudio Retrospectivo, Población Médicamente Desatendida

Resumen

Este estudio evalúa la efectividad de la tecnología de telemedicina (TM) en comparación con las visitas tradicionales cara a cara (F2F) como un método alternativo de prestación de servicios de salud para abordar la diabetes en poblaciones que residen en áreas urbanas médicamente desatendidas (UMUPAs). Los registros electrónicos de salud de pacientes (ePHR) con diabetes mellitus tipo 2 (T2DM) fueron examinados retrospectivamente desde el 1 de enero de 2019 hasta el 30 de junio de 2021. Los modelos de regresión lineal múltiple revelaron que los pacientes con T2DM y diabetes no controlada que utilizaban TM mostraban resultados similares a aquellos con visitas tradicionales en la reducción de los niveles de hemoglobina (HbA1c). El tipo de servicio de atención médica influyó significativamente en los valores de HbA1c %, como lo evidenció el coeficiente de regresión para TM (vs. F2F), que indicaba una asociación negativa significativa (B = -0.339, p < 0.001). Esto sugiere que los pacientes que utilizaban TM probablemente tenían, en promedio, valores de HbA1c % 0.34 más bajos en comparación con aquellos que optaban por visitas F2F. Además, el coeficiente de regresión para el género femenino (vs. masculino) mostró una asociación positiva (B = 0.190, p < 0.034), revelando que las pacientes femeninas tenían niveles de HbA1c % 0.19 más altos que sus contrapartes masculinas. La edad (B = -0.026, p < 0.001) surgió como un predictor significativo de los niveles de HbA1c %, con una disminución de 0.026 HbA1c % por cada aumento de año en la edad. En cuanto a los factores demográficos, los adultos afroamericanos (B = 0.888, p < 0.001) eran estadísticamente más propensos a mostrar niveles de HbA1c % 0.888 más altos en promedio en comparación con los adultos blancos.

Citas

WHO. WHO Reveals Leading Causes of Death and Disability Worldwide: 2000–2019. Available online: https://www.who.int/news/item/09-12-2020-who-reveals-leading-causes-of-death-and-disability-worldwide-2000-2019 (accessed on 28 April 2021).

American Diabetes Association. Economic Costs of Diabetes in the U.S. in 2017. Diabetes Care 2018, 41, 917–928. [CrossRef]

Report of the First Meeting of the WHO Global Diabetes Compact Forum. 2021. Available online: https://www.who.int/publications/i/item/9789240045705 (accessed on 14 January 2023).

WHO. Int Fact Diabetes Sheet. Available online: https://www.who.int/news-room/fact-sheets/detail/diabetes (accessed on 5 May 2021).

CDC. Certain Medical Conditions and Risk for Severe COVID-19 Illness|CDC. Available online: https://www.cdc.gov/coronavirus/2019-ncov/need-extra-precautions/people-with-medical-conditions.html (accessed on 28 April 2021).

Adegunsoye, A.; Ventura, I.B.; Liarski, V.M. Association of Black Race with Outcomes in COVID-19 Disease: A Retrospective

Cohort Study. Ann. Am. Thorac. Soc. 2020, 17, 1336–1339. [CrossRef] [PubMed]

Braveman, P. Health Disparities and Health Equity: Concepts and Measurement. Annu. Rev. Public Health 2006, 27, 167–194.

[CrossRef]

Ward, L.A. Effectiveness of Telemedicine in Diabetes Management: A Retrospective Study in an Urban Medically Underserved

Population Area (UMUPA). Available online:

https://digitalcommons.georgiasouthern.edu/cgi/viewcontent.cgi?article=3706

&context=etd (accessed on 3 November 2022).

Temesgen, Z.M.; DeSimone, D.C.; Mahmood, M.; Libertin, C.R.; Varatharaj Palraj, B.R.; Berbari, E.F. Health Care After the

COVID-19 Pandemic and the Influence of Telemedicine. Mayo Clin. Proc. 2020, 95, S66–S68. [CrossRef]

CDC. Preventing Diabetes-Related Complications|Diabetes|CDC. Available online:

https://www.cdc.gov/diabetes/data/statistics-report/preventing-complications.html (accessed on 7 September 2021).

McElroy, J.A.; Day, T.M.; Becevic, M. The Influence of Telehealth for Better Health Across Communities. Prev. Chronic Dis. 2020,

, 200254. [CrossRef]

. Andreozzi, F.; Candido, R.; Corrao, S.; Fornengo, R.; Giancaterini, A.; Ponzani, P.; Ponziani, M.C.; Tuccinardi, F.; Mannino, D.

Clinical inertia is the enemy of therapeutic success in the management of diabetes and its complications: A narrative literatura review. Diabetol. Metab. Syndr. 2020, 12, 52. [CrossRef] [PubMed]

Classification and Diagnosis of Diabetes: Standards of Medical Care in Diabetes—2020|Diabetes Care. Available online: https://care.diabetesjournals.org/content/43/Supplement_1/S14 (accessed on 7 September 2021).

Pantalone, K.M.; Misra-Hebert, A.D.; Hobbs, T.M.; Ji, X.; Kong, S.X.; Milinovich, A.; Weng, W.; Bauman, J.; Ganguly, R.; Burguera,

B.; et al. Clinical Inertia in Type 2 Diabetes Management: Evidence From a Large, Real-World Data Set. Diabetes Care 2018, 41,

e113–e114. [CrossRef]

Cade, W.T. Diabetes-Related Microvascular and Macrovascular Diseases in the Physical Therapy Setting. Phys. Ther. 2008, 88,

–1335. [CrossRef]

Stratton, I.M. Association of glycaemia with macrovascular and microvascular complications of type 2 diabetes (UKPDS 35):

Prospective observational study. BMJ 2000, 321, 405–412. [CrossRef] [PubMed]

Informatics 2023, 10, 16 12 of 12

Hirakawa, Y.; Arima, H.; Zoungas, S.; Ninomiya, T.; Cooper, M.; Hamet, P.; Mancia, G.; Poulter, N.; Harrap, S.; Woodward,

M.; et al. Impact of Visit-to-Visit Glycemic Variability on the Risks of Macrovascular and Microvascular Events and All-Cause Mortality in Type 2 Diabetes: The Advance Trial. Diabetes Care 2014, 37, 2359–2365. [CrossRef]

Khunti, K.; Gomes, M.B.; Pocock, S.; Shestakova, M.V.; Pintat, S.; Fenici, P.; Hammar, N.; Medina, J. Therapeutic inertia in the treatment of hyperglycaemia in patients with type 2 diabetes: A systematic review. Diabetes Obes. Metab. 2018, 20, 427–437.

[CrossRef] [PubMed]

Telehealth Basics-ATA. Available online: https://www.americantelemed.org/resource/why-telemedicine/ (accessed on 2 September 2021).

DHS. Federally-Facilitated Marketplace Assister Curriculum Serving Vulnerable and Underserved Populations. Department of Health & Human Services Centers for Medicare & Medicaid Services Center for Consumer Information & Insurance Oversight;

:108. Available online:

https://mail.google.com/mail/u/0/#inbox/WhctKKXpSdCrPvRlSTHvtnfmSgRmFchWfGmFFvLsCgFKCVbzKrBCMgxLPjcmtncgpsJRlgG?compose=new&projector=1&messagePartId=0.1 (accessed on 25 June 2022).

Vilendrer, S.; Patel, B.; Chadwick, W.; Hwa, M.; Asch, S.; Pageler, N.; Ramdeo, R.; Saliba-Gustafsson, E.A.; Strong, P.; Sharp, C.

Rapid Deployment of Inpatient Telemedicine In Response to COVID-19 Across Three Health Systems. J. Am. Med. Inform. Assoc.

, 27, 1102–1109. [CrossRef] [PubMed]

Bashshur, R.; Doarn, C.R.; Frenk, J.M.; Kvedar, J.C.; Woolliscroft, J.O. Telemedicine and the COVID-19 Pandemic, Lessons for the Future. Telemed. E Health 2020, 26, 571–573. [CrossRef] [PubMed]

Sounderajah, V.; Patel, V.; Varatharajan, L.; Harling, L.; Normahani, P.; Symons, J.; Barlow, J.; Darzi, A.; Ashrafian, H. Are disruptive innovations recognised in the healthcare literature? A systematic review. BMJ Innov. 2021, 7, 208–216. [CrossRef]

[PubMed]

Demiris, G. Integration of Telemedicine in Graduate Medical Informatics Education. J. Am. Med. Inform Assoc. 2003, 10, 310–314.

[CrossRef] [PubMed]

About Social Determinants of Health (SDOH). Published 10 March 2021. Available online: https://www.cdc.gov/socialdeterminants/about.html (accessed on 23 April 2021).

.Walker, R.J.; Strom Williams, J.; Egede, L.E. Influence of Race, Ethnicity and Social Determinants of Health on Diabetes Outcomes.

Am. J. Med. Sci. 2016, 351, 366–373. [CrossRef]

. Klein, R.; Huang, D. Defining and Measuring Disparities, Inequities, and Inequalities in the Healthy People Initiative. National Center of Health Statistics NCHS-CDC. Available online:

https://www.cdc.gov/nchs/ppt/nchs2010/41_klein.pdf (accessed on July 2022).

Eberle, C.; Stichling, S. Effect of Telemetric Interventions on Glycated Hemoglobin A1c and Management of Type 2 Diabetes Mellitus: Systematic Meta-Review. J. Med. Int. Res. 2021, 23, e23252. [CrossRef]

De Groot, J.; Wu, D.; Flynn, D.; Robertson, D.; Grant, G.; Sun, J. Efficacy of telemedicine on glycaemic control in patients with type 2 diabetes: A meta-analysis. World J. Diabetes 2021, 12, 170–197. [CrossRef]

Shea, S.; Weinstock, R.S.; Teresi, J.A.; Palmas, W.; Starren, J.; Cimino, J.J.; Lai, A.M.; Field, L.; Morin, P.C.; Goland, R.; et al.

A Randomized Trial Comparing Telemedicine Case Management with Usual Care in Older, Ethnically Diverse, Medically Underserved Patients with Diabetes Mellitus: 5 Year Results of the IDEATel Study. J. Am. Med. Inform. Assoc. 2009, 16, 446–456.

[CrossRef]

Duval County, Florida|County Health Rankings & Roadmaps. Available online: https://www.countyhealthrankings.org/app/florida/2021/rankings/duval/county/outcomes/overall/snapshot (accessed on 23 April 2021).

U.S. Census Bureau QuickFacts: Duval County, Florida. Available online:

https://www.census.gov/quickfacts/fact/table/duvalcountyflorida/INC110219 (accessed on 10 October 2021).

Livingood, W.C.; Razaila, L.; Reuter, E.; Filipowicz, R.; Butterfield, R.C.; Lukens-Bull, K.; Edwards, L.; Palacio, C.; Wood, D.L.

Using multiple sources of data to assess the prevalence of diabetes at the subcounty level, Duval County, Florida, 2007. Prev.

Chronic Dis. 2010, 7, A108.

FLHealthCHARTS.com: Chronic Disease Data. Available online: https://flhealthcharts.com (accessed on 10 October 2021).

Difference between Medicare and Medicaid Insurance. Available online:

https://www.hhs.gov/answers/medicare-andmedicaid/what-is-the-difference-between-medicare-medicaid/index.html (accessed on 12 January 2023).

Canedo, J.R.; Miller, S.T.; Schlundt, D.; Fadden, M.K.; Sanderson, M. Racial/Ethnic Disparities in Diabetes Quality of Care: The Role of Healthcare Access and Socioeconomic Status. J. Racial Ethn. Health Disparities 2018, 5, 7–14. [CrossRef] [PubMed]

Viigimaa, M.; Sachinidis, A.; Toumpourleka, M.; Koutsampasopoulos, K.; Alliksoo, S.; Titma, T. Macrovascular Complications of Type 2 Diabetes Mellitus. Curr. Vasc. Pharmacol. 2020, 18, 110–116. [CrossRef] [PubMed]

Publicado

2022-09-29

Cómo citar

Oliver Chag, A. (2022). Evaluación de la Eficacia de la Telemedicina en el Manejo de la Diabetes: Un Vistazo a un Estudio Retrospectivo en un Área Urbana con Población Médicamente Desatendida (UMUPA). Infotech Revista Científica Y Académica , 3(1), 110–134. Recuperado a partir de https://infotechjournal.org/index.php/infotech/article/view/14

Número

Sección

Articles
Loading...