SciELO - Scientific Electronic Library Online

 
vol.48 issue3Clinical, laboratory and treatment characteristics of patients with thrombotic thrombocytopenic purpuraTechnology, its gaps and their impact on health care author indexsubject indexarticles search
Home Pagealphabetic serial listing  

Services on Demand

Journal

Article

Indicators

Related links

  • On index processCited by Google
  • Have no similar articlesSimilars in SciELO
  • On index processSimilars in Google

Share


Acta Medica Colombiana

Print version ISSN 0120-2448

Acta Med Colomb vol.48 no.3 Bogotá July/Sept. 2023  Epub Apr 08, 2024

https://doi.org/10.36104/amc.2023.2826 

Review

Information and communications technology-based solutions to improve treatment adherence in patients with type 2 diabetes mellitus. A rapid review of the literature

CARLOS MARIO CORTINA-GARCÍAa  * 

SANTIAGO PATIÑO-GIRALDOb 

a Médico General, Magíster en Telesalud. Director de Transformación Digital Cielum Health. Profesor Maestría TIC en Salud Universidad CES; Medellín (Colombia).

b Especialista en Medicina Interna, Magíster en Educación Superior en Salud. Profesor Universidad de Antioquia. Grupo INFORMED. Medellín (Colombia).


Abstract

Objective of the review:

to determine if the information and communications technology-based care alternatives support treatment adherence in adult patients with type 2 diabetes mellitus.

Source of the data:

Medline, Embase, Scopus and Lilacs.

Study selection:

a rapid review of the literature was performed using the terms telemedicina, telemonitoreo, adherencia terapéutica and diabetes mellitus tipo 2. Controlled clinical trials, and pre-post or observational cohort studies from January 2008 to December 2018 in English and Spanish were included. Data analysis and extraction were conducted independently by two authors. The measured outcome was adherence in its various dimensions. The results are presented descriptively. Neither a meta-analysis nor subgroup analyses were considered.

Data extraction and synthesis:

The search yielded a total of 466 studies, 29 articles of which were included (clinical trials n=17, pre-post n=7 and cohort n=3). The most commonly used technology was smartphones (n=8; 27.5%), followed by traditional telephones (n=7; 24.1%). In 22 studies, HbA1c was measured to evaluate adherence, with positive results in 15 (68%). Non-pharmacological adherence was measured in 16 studies, with positive results in 13 (81.25%).

Conclusions:

different technologies have a positive impact on adherence measured through HbA1c, with smartphones and conventional telephones being the most used. The evidence is low-quality and therefore more studies of this problem are needed. (Acta Med Colomb 2022; 48. DOI:https://doi.org/10.36104/amc.2023.2826).

Keywords: telemedicine; telemonitoring; treatment adherence; type 2 diabetes mellitus; rapid

Resumen

Propósito de la revisión:

determinar las alternativas de atención fundamentadas en tecnologías de la información y comunicación que apoyan la adherencia terapéutica en pacientes adultos con diabetes mellitus tipo 2.

Fuente de obtención de los datos:

Medline, Embase, Scopus y Lilacs.

Selección de los estudios:

se realizó una revisión rápida de la literatura con los términos tele medicina, telemonitoreo, adherencia terapéutica y diabetes mellitus tipo 2. Se incluyeron ensayos clínicos controlados, pre-post u observacionales tipo cohorte en el periodo enero de 2008 a diciembre 2018 en idioma inglés y español. Se realizó análisis y extracción de datos por dos autores en forma independiente. El desenlace medido fue adherencia en sus diferentes dimensiones. Se presentan resultados en forma descriptiva. No se consideró meta-análisis ni análisis de sub-grupos.

Extracción y síntesis de los datos:

La búsqueda arrojó un total de 466 estudios, de los cuáles 29 artículos fueron incluidos (ensayos clínicos n=17, pre-post n=7 y cohorte n=3). La tecnología más utilizada fue el teléfono inteligente (n=8; 27.5%, seguido del teléfono tradicional (n=7; 24.1%). En 22 estudios se hizo medición de HbA1c para evaluar adherencia con resultados positivos en 15 de ellos (68%). En 16 estudios se hizo medición de adherencia no farmacológica, 13 con resultados positivos (81.25%).

Conclusiones:

distintas tecnologías impactan positivamente en la adherencia medida por HbA1c, siendo el teléfono inteligente y convencional los más usados. La evidencia es de baja calidad por lo que se requieren más estudios frente a este problema. (Acta Med Colomb 2022; 48. DOI:https://doi.org/10.36104/amc.2023.2826).

Palabras clave: telemedicina; telemonitoreo; adherencia terapéutica; diabetes mellitus tipo 2; revisión rápida

Introduction

Diabetes mellitus, along with cardiovascular diseases, cancer and respiratory diseases, is part of a public health interest group known as chronic noncommunicable diseases (CNCDs). In and of itself, it is responsible for 1.6 million deaths per year 1, being the seventh cause of death in the United States 2, with clear evidence of an accelerated growth in its prevalence in developing countries 3. In Colombia, in 2015, the prevalence of type 2 diabetes mellitus was 9.6% 4.

Diabetes mellitus treatment is based on three pillars: nonpharmacological measures, diabetes education and medications. Nonpharmacological management seeks to achieve lifestyle changes leading to permanent metabolic control through normalizing and maintaining weight (diet) and a persistent increase in physical activity. The educational program supports nonpharmacological management so the patients can modify their lifestyle and achieve the treatment goals. Finally, pharmacological treatment should be specific and personalized 5,6.

Inappropriate or no treatment increases the likelihood of micro and macrovascular complications like cardiovascular disease, diabetic retinopathy, kidney disease, diabetic neuropathy and diabetic foot 7, and therefore disease control should be early, effective and sustained 8.

Despite this, there are difficulties in patients adhering to treatment. There are many reasons for poor adherence: side effects of the medications, the complexity of the treatment plan, not remembering, the distance to the care site, as well as sociodemographic factors like educational level and monthly income 9,10.

Lack of adherence has become a big problem, as this is essential for patients' health recovery and maintenance. The adherence of patients with chronic illnesses in developed countries is, in the best of cases, 50%, and six months after beginning treatment, only 20 to 70% still take it 11. For diabetes mellitus, adherence to diabetes treatment plans has been recognized as a key factor in its control and the prevention of complications and fatal outcomes 12-18. An impact has also been shown on its direct and indirect care costs 19,20.

Therefore, the World Health Organization has created a guide for dealing with lack of adherence, presenting guidelines for its control. It proposes five groups of factors, or dimensions, of adherence: 1) socioeconomic, 2) healthcare system/healthcare provider -related, 3) disease-related, 4) treatment-related and 5) patient-related 21-23.

In light of this problem, new strategies and care models are essential to improve the adherence of patients with diabetes mellitus in its different dimensions 24. These new strategies include those supported by information and communication technologies (ICTs), for example, telemedicine. Several studies have shown a positive impact on adherence, knowledge of the disease, therapeutic lifestyle changes and self-care 25-34. The objective of this study is to answer the following question: In patients with type 2 diabetes mellitus, what ICT-based care alternatives support treatment adherence, compared with usual care?

Data collection

A systematic review of the literature was performed following the Cochrane guidelines and presented in line with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) recommendations. A search was performed of the following databases: Medline, Embase, Scopus and LILACs, using MeSH, Emtree and free-text terms with the following key words: telemedicine, tele-monitoring, treatment adherence and type 2 diabetes mellitus. The search was done by the first author in English and Spanish (Annex 1), supported by a librarian. Experimental (controlled clinical trials), quasi-experimental (pre-post) or cohort observational studies from January 2008 through December 2018 were included. Studies without a comparison group, those that did not evaluate adherence or did not include results (clinical trial protocols), type 1 diabetes patients, minors or studies which were not published in full text were excluded. Both authors searched for and selected the articles independently. Any differences were resolved by consensus. The selected articles were evaluated for bias by the second author, in five categories: random sequence generation, sequence masking, incomplete outcome data (patient attrition), selective reporting and others. Given the characteristics of the intervention and outcome, intervention blinding was omitted.

Data extraction was performed independently by both authors, and differences were resolved by consensus. The information obtained included the title, author, year, design, population, scale of the approach, type of measurement, method used, technology used and outcome. Review Manager 5.3 (Copenhagen: The Nordic Cochrane Centre, The Cochrane Collaboration, 2014) was used for data management. The results were organized in a table for presentation. Neither meta-analysis nor sub-group analyses were performed.

As this was a secondary source study, research ethics committee approval was not required. The authors participated in preparing the manuscript and reviewed the result prior to submitting it for publication.

Results

The search yielded a total of 466 studies, and 29 articles were included in the study (Figure 1). Of these, 17 (59%) were RCTs, 10 (34%) were pre-post studies and 2 (7%) were cohort studies (Table 1). The studies' bias assessment is reported in Figure 2. Blinding was not assessed in most cases, since it is very difficult for the intervention to be hidden from patients and investigators. Almost half of the studies had difficulties with patient attrition (n=21) or did not have an adequate description of the methods for random group assignment (n=11).

Figure 1 Results selection. Source: Prepared by the authors. 

Table 1 Articles included in the review. 

Figure 2 Bias assessment. Source: Prepared by the authors. 

All of the studies (n=29) deal with the problem of adherence in the "patient-related" dimension; that is, they address the patients' knowledge of the disease, lifestyle and habit modification, self-administration of treatment and improved motivation for self-care.

None of the studies measured adherence directly. The study by Brath et al. 40 came the closest, using an electronic blister pack that sent a signal when the medication was removed. In 28 studies (96.5%), the main method used to measure adherence was a questionnaire. The questions were aimed at information on glycemic control (blood glucose measurements), vital signs (blood pressure, weight, height, BMI), knowledge of the disease, adherence to pharmacological measures (taking the medications) and nonpharmacological measures (exercising or following the diet) and monitoring medical variables.

To measure the effectiveness of the intervention, nine studies (31%) only used physiological markers like HbA1c, lipid profile or blood sugar. Two studies (7%) used pharmacological and nonpharmacological adherence scales, and 18 studies used both (62%).

Of the studies that used HbA1c as an outcome, 68% (15/22) showed a statistically significant reduction in HbA1c levels after the intervention. Ten studies measured fasting blood sugar, with six (60%) reporting a statistically significant reduction in fasting blood sugar after the intervention.

Fourteen studies measured pharmacological adherence. Thirteen (92.9%) used a questionnaire and one (7.1%) used an electronic blister pack. Sixty-four percent of these studies showed a statistically significant improvement in pharmacological adherence levels after the intervention. In the 16 studies which measured nonpharmacological adherence, this was done through a questionnaire. In 13 (81%) of these studies there was a statistically significant improvement in nonpharmacological adherence levels after the intervention.

All of these studies used technology differently. Some studies used only one technology, while others used a combination of several. The most frequently used technology was the smartphone (n=8; 27.6%) and conventional phone (n=7; 24.1%) (Figure 3).

Figure 3 Technology used. Source: Prepared by the authors. 

Regardless of the technology used, in addition to telemonitoring, all of the interventions were accompanied by health tele-education (n=29). Only 16 (55%) explained the type of tele-education they provided. These topics were framed within information about the disease such as its causes, medication side effects, associated comorbidities, foot care and how to detect episodes of hypo and hyperglycemia; motivation for physical activity and health eating; helping change the negative perception of the disease, anxiety or stress; persuasion to generate self-control over constant blood sugar measurement, both fasting and postprandial, and its normal values; and HbA1c, blood pressure and lipid profile goals. Furthermore, patients received information and reminders on taking their medications, monitoring glucose, exercise, nutrition and foot care.

Discussion

This literature review found that several types of technology are used to support treatment adherence in patients with type 2 diabetes mellitus, with smartphones or conventional phones being the tools most often studied. These data coincide with the study by Lerman et al. 41 which showed that monthly telephone calls to promote self-care behaviors and detect and try to solve problems related to diabetes control improved adherence to diet and pharmacological treatment. Another study by Vervloet M et al. 42 used SMS to impact on adherence over one year of follow up and showed significant improvement compared with the control (79.5 vs. 64.5%; p<0.001). After two years, the improved adherence in the SMS group persisted and remained significantly higher than in the control group (80.4 vs. 68.4%; p<0.01).

We found that the use of smart mobile devices, conventional phones, connected biomedical devices, web pages or text messages have proven to be useful in positively impacting adherence to diabetes treatment, as shown by Huang Z et al.'s meta-analysis (43), but it is notable that all of the analyzed studies are aimed at patient-related factors. However, other factors impacting adherence cannot be overlooked, such as socioeconomic, healthcare system, disease and treatment factors, as considered by WHO 22. It would be interesting to evaluate the impact of ICTs on these other dimensions of adherence.

A study by Cheong C et al. 44 analyzed pharmacological adherence to two comparable types of diabetes medications with different prices, showing that the cheaper medication generated more adherence, but they did not use ICT. It is likely that the other dimensions are not as easily addressed with the use of ICT. In a case-control study in which patients' co-pays were reduced, 36.1% had a higher likelihood of being adherent (OR: 1.56 [95% CI: 1.04-2.34]; p=0.03) 45 and they did not use ICT, either.

The studies were found to have poor methodological quality, as occurs with most telemedicine studies, as shown by Huang Z et al. 43 and Zhai YK et al. 46 in different meta-analyses. Therefore, it is important for research teams to develop strategies to strengthen the methodological quality of telemedicine studies.

The analysis showed that the main technologies used are smartphones and conventional phones. With the growing number of smartphones, it is estimated that, in the next 10 years, 80 to 90% of people in developed countries will have these devices, thus facilitating remote and more efficient interaction with the healthcare team. This is a great opportunity to design models to leverage treatment adherence for type 2 diabetes using this type of technology, as shown by Boulos et al. 47 and Klasnja et al. 48.

One of the limitations of this study is that grey literature (congresses, seminars, bibliographic references) was not searched. However, the most important databases were included, like Medline, Embase, Scopus and LILACS. Another limitation is that only one author performed bias assessment. However, this author is experienced in critical appraisal of the literature, which reduces the risk of bias.

The use of ICTs is unequal, depending largely on each country's level of development. A bibliographic search of the use of these technologies in diabetes management and the improvement of adherence in Latin American countries or Spain yields very few studies, with more studies found in other parts of the world. This limits decision making aimed at our developing countries. We must continue with the research line of controlled studies to provide evidence of the usefulness of these new tools in our setting 49.

Conclusion

In the analysis of the problem of lack of adherence as a significant cause of inadequate type 2 diabetes mellitus treatment, the studies we found showed that various ICTs, but especially smartphones and conventional phones, can help solve this problem. In all cases, the approach was aimed at patient-related factors, perhaps due to the fact that this type of technology is applied to people and not to the other dimensions affecting adherence. Management with this type of technology should be aimed at improving knowledge of the disease, empowerment, motivation and self-care. In any case, very little evidence was found, and more studies are needed to improve decision making regarding the solution to this problem.

References

1. OMS. Enfermedades no transmisibles. In: Enfermedades No Transmisibles [Internet]. World Health Organization; 2017 [cited 2018 Jan 21]. p. 1. Available from: Available from: http://www.who.int/mediacentre/factsheets/fs355/es/Links ]

2. Facts F, Diabetes ON. National Diabetes Fact Sheet. Centers Dis Control Prev US Dep Heal Hum Serv [Internet]. 2011 [cited 2018 Jan 22];CS217080A(Division of Diabetes Translation):1-12. Available from: Available from: https://www.cdc.gov/diabetes/pubs/pdf/ndfs_2011.pdfLinks ]

3. World Health Organization. Global Report on Diabetes. Isbn [Internet]. 2016 [cited 2018 Jan 14];978:88. Available from: Available from: http://www.who.int/about/licensing/Links ]

4. Vargas Uricoechea H. Estado actual de la Diabetes Mellitus en Colombia. 2016 [cited 2018 Jan 23]; Available from: Available from: http://www.endocrino.org.co/wp-content/uploads/2016/10/1.-Dr.-Hernando-Vargas-Diabetes-estado-actual.pdfLinks ]

5. American Diabetes Association (ADA). Standard of medical care in diabetes - 2017. Diabetes Care [Internet]. 2017 [cited 2018 Feb 22];40 (sup 1) (January):s4-128. Available from: Available from: http://care.diabetesjournals.org/content/diacare/suppl/2016/12/15/40.Supplement_1.DC1/DC_40_S1_final.pdfLinks ]

6. Abellán M, Badenes D, Campdelacreu J, Flores E, Gascón J, Lléo A, et al. Guía de Práctica Clínica sobre la Atención Integral a las Personas con Enfermedad de Alzheimer y otras Demencias [Internet]. Plan de Calidad para el Sistema Nacional de Salud del Ministerio de Sanidad, Política Social e Igualdad. 2009 p. 507. Available from: http://www.guiasalud.es/GPC/GPC_484_Alzheimer_AIAQS_compl.pdfLinks ]

7. Centers for Disease Control and Prevention. Chronic disease Prevention and Health Promotion: Chronic disease overview [Internet]. CDC. 2008 [cited 2018 Jan 9]. Available from: Available from: https://www.cdc.gov/chronicdisease/overview/index.htmLinks ]

8. Ministerio de salud. Guía de Práctica Clínica para el diagnóstico, tratamiento y seguimiento de la diabetes mellitus tipo 2 en la población mayor de 18 años [Internet]. Colombia; 2015 [cited 2018 Jan 22]. p. 1-420. Available from: Available from: http://gpc.minsalud.gov.co/gpc_sites/Repositorio/Otros_conv/GPC_e_renal/gpc_e_renal.aspxLinks ]

9. Kassahun A, Gashe F, Mulisa E, Rike W. Nonadherence and factors affecting adherence of diabetic patients to anti-diabetic medication in Assela General Hospital, Oromia Region, Ethiopia. J Pharm Bioallied Sci [Internet]. 2016 [cited 2018 Feb 16];8(2): 124. Available from: Available from: http://www.ncbi.nlm.nih.gov/pubmed/27134464Links ]

10. Salcedo A, Gomez A. Grados de riesgo para la adherencia terapéutica en personas con hipertensión arterial Degrees of risk for therapeutical adherence in persons with arterial hypertension Graus de risco para a aderência terapêutica em pessoas com hipertensão arterial. Avales Enferm. 2014;(1):33-43. [ Links ]

11. Sanahuja MA, Villagrasa V, Martínez-Romero F, Moreno Royo L. Adherencia terapéutica. Vol. 14, Pharmaceutical Care Espana. 2012. p. 162-7. [ Links ]

12. Feldman BS, Cohen-Stavi CJ, Leibowitz M, Hoshen MB, Singer SR, Bitterman H, et al. Defining the role of medication adherence in poor glycemic control among a general adult population with diabetes. PLoS One [Internet]. 2014 [cited 2018 Feb 16];9(9). Available from: Available from: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4178119/pdf/pone.0108145.pdfLinks ]

13. Rodriguez, J, Ruiz F, Peñaloza E, Eslava J, Gómez LC, Sánchez H, Amaya JL, Arenas R BY. Encuesta Nacional de Salud 2007. Resultados Nacionales [National Health Survey 2007. National Results] [Internet]. 2009 [cited 2018 Apr 16]. 27-260 p. Available from: Available from: https://www.minsalud.gov.co/Documentos_y_Publicaciones/ENCUESTA NACIONAL.pdfLinks ]

14. The New England Healthcare Institute. Thinking Outside the Pillbox: A System-wide Approach to Improving Patient Medication Adherence for Chronic Disease. New Engl Healthc Inst [Internet]. 2009;(August):1-21. Available from: http://www.nehi.net/writable/publication_files/file/pa_issue_brief_final.pdfLinks ]

15. Venkatesan M, Dongre A, Ganapathy K. A community-based study on diabetes medication nonadherence and its risk factors in rural Tamil Nadu. Indian J Community Med [Internet]. 2018 [cited 2018 Jun 12];43(2):72-6. Available from: Available from: http://www.ncbi.nlm.nih.gov/pubmed/29899603Links ]

16. Kunasegaran S, Beig J, Khanolkar M, Cundy T. Adherence to medication, glycaemic control and hospital attendance in young adults with type 2 diabetes. Intern Med J [Internet]. 2018 Jun [cited 2018 Jun 10];48(6):728-31. Available from: Available from: http://doi.wiley.com/10.1111/imj.13808Links ]

17. Khunti K, Seidu S, Kunutsor S, Davies M. Association Between Adherence to Pharmacotherapy and Outcomes in Type 2 Diabetes: A Meta-analysis. Diabetes Care [Internet]. 2017 Nov;40(11):1588-96. Available from: http://care.diabetes-journals.org/lookup/doi/10.2337/dc16-1925Links ]

18. Asche C, LaFleur J, Conner C. A Review of Diabetes Treatment Adherence and the Association with Clinical and Economic Outcomes. Clin Ther [Internet]. 2011 Jan;33(1):74-109. Available from: http://dx.doi.org/10.1016/j.clinthera.2011.01.019Links ]

19. Pérez N, Murillo R, Pinzón C, Hernández G. Costos de la atención médica del cáncer de pulmón, la EPOC y el IAM atribuibles al consumo de tabaco en Colombia (proyecto multicéntrico de la OPS). Rev Colomb Cancerol [Internet]. 2007 [cited 2018 Apr 15];11(4):241-9. Available from: Available from: http://www.who.int/fctc/reporting/party_reports/colombia_annex4_smoking_costs_article.pdfLinks ]

20. Solarte KG, Benavides Acosta FP, Rosales Jiménez R. Costos de la enfermedad crónica no transmisible: la realidad colombiana. Rev Cienc Salud [Internet]. 2016 [cited 2018 Apr 12];1414(11):103-14. Available from: Available from: http://www.scielo.org.co/pdf/recis/v14n1/v14n1a10.pdfLinks ]

21. Brown MT, Bussell JK. Medication adherence: WHO cares? [Internet]. Vol. 86, Mayo Clinic Proceedings. 2011 [cited 2018 May 28]. p. 304-14. Available from: Available from: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3068890/pdf/mayoclin-proc_86_4_007.pdfLinks ]

22. Organización Mundial de la Salud (OMS). Adherencia a los tratamiento a largo plazo: pruebas para la acción. Adherencia a los Trat a largo plazo pruebas para la acción [Internet]. 2004 [cited 2018 May 17];127-32. Available from: Available from: http://www1.paho.org/Spanish/AD/DPC/NC/adherencia-largo-plazo.pdfLinks ]

23. Salud O-SV de S. Adherencia al tratamiento farmacológico en patologías crónicas. Boletín INFAC [Internet]. 2011 [cited 2018 May 22];6. Available from: Available from: http://www.euskadi.eus/contenidos/informacion/cevime_infac_2011/es_def/adjuntos/infac_v19_n1.pdfLinks ]

24. Kalyango JN, Owino E, Nambuya AP. Non-adherence to diabetes treatment at mulago hospital in Uganda: Prevalence and associated factors. Afr Health Sci [Internet]. 2008 Dec 19 [cited 2018 May 26];8(2):67-73. Available from: Available from: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2584325/pdf/AFHS0802-0067.pdfLinks ]

25. Weinstock RS, Teresi JA, Goland R, Izquierdo R, Palmas W, Eimicke JP, et al. Glycemic control and health disparities in older ethnically diverse underserved adults with diabetes: Five-year results from the Informatics for Diabetes Education and Telemedicine (IDEATel) study. Diabetes Care [Internet]. 2011 [cited 2018 May 28];34(2):274-9. Available from: Available from: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3024333/pdf/274.pdfLinks ]

26. Trief PM, Izquierdo R, Eimicke JP, Teresi JA, Goland R, Palmas W, et al. Adherence to diabetes self care for white, African-American and Hispanic American telemedicine participants: 5 year results from the IDEATel project. Ethn Heal [Internet]. 2013 Feb [cited 2018 Jun 4];18(1):83-96. Available from: Available from: http://www.tandfonline.com/doi/abs/10.1080/13557858.2012.700915Links ]

27. Kempf K, Altpeter B, Berger J, Reuß O, Fuchs M, Schneider M, et al. Efficacy of the telemedical lifestyle intervention program TeLiPro in advanced stages of type 2 diabetes: A randomized controlled trial. Diabetes Care [Internet]. 2017 [cited 2018 Aug 18];40(7):863-71. Available from: Available from: http://care.diabetesjournals.org/lookup/suppl/doi:10.2337/dc17-0303/-/DC1.http://www.diabetesjournals.org/content/diabetes-core-update-podcasts . [ Links ]

28. Kerfoot BP, Gagnon DR, McMahon GT, Orlander JD, Kurgansky KE, Conlin PR. A team-based online game improves blood glucose control in veterans with type 2 diabetes: A randomized controlled trial. Diabetes Care [Internet]. 2017 [cited 2018 Aug 18];40(9):1218-25. Available from: Available from: http://care.diabetesjournals.org/lookup/suppl/doi:10.2337/dc17-0310/-/DC1.http://www.diabetesjournals.org/content/diabetes-core-update-podcasts . [ Links ]

29. Anderson RM, Fitzgerald JT, Gruppen LD, Funnell MM, Oh MS. The diabetes empowerment scale-short form (DES-SF) [8] [Internet]. Vol. 26, Diabetes Care. American Diabetes Association; 2003 [cited 2018 Aug 18]. p. 1641-2. Available from: Available from: http://www.ncbi.nlm.nih.gov/pubmed/12716841Links ]

30. Armstrong AW, Watson AJ, Makredes M, Frangos JE, Kimball AB, Kvedar JC. Text-Message Reminders to Improve Sunscreen Use. Arch Dermatol [Internet]. 2009; 145(11): 1230-6. Available from: http://archderm.jamanetwork.com/article.aspx?doi=10.1001/archdermatol.2009.269Links ]

31. Lee H, Park J-B, Choi SW, Yoon YE, Park HE, Lee SE, et al. Impact of a Telehealth Program With Voice Recognition Technology in Patients With Chronic Heart Failure: Feasibility Study. JMIR mHealth uHealth [Internet]. 2017 [cited 2018 Jun 4];5(10):e127. Available from: Available from: https://asset.jmir.pub/assets/4c936619bb4b8d0bca0d9b23845a26fb.pdfLinks ]

32. Gentry MT, Lapid MI, Clark MM, Rummans TA. Evidence for telehealth group-based treatment: A systematic review. J Telemed Telecare [Internet]. 2018 May 22 [cited 2018 Jun 3];16. Available from: Available from: http://journals.sagepub.com/doi/10.1177/1357633X18775855Links ]

33. American Telemedicine Association. Services Provided by Telehealth - ATA Main [Internet]. [cited 2018 Aug 5]. Available from: Available from: http://www.americantelemed.org/main/about/about-telemedicine/services-provided-by-telehealthLinks ]

34. American Telemedicine Association. Delivery Mechanisms - ATA Main [Internet]. [cited 2018 Aug 2]. Available from: Available from: http://www.americantelemed.org/main/about/about-telemedicine/delivery-mechanismsLinks ]

35. López Romero LA, Romero Guevara SL, Parra DI, Rojas Sánchez LZ. Adherencia al tratamiento: concepto y medición. Hacia Promoción la Salud [Internet]. 2016 [cited 2018 Aug 4];21(1):117-37. Available from: Available from: http://www.scielo.org.co/pdf/hpsal/v21n1/v21n1a10.pdfLinks ]

36. Casas Piedrahíta MC, Chavarro Olarte LM, Cardona Rivas D. Patients adherence to high blood pressure treatment in two municipalities of Colombia. 2010-2011. Hacia la Promoción la Salud [Internet]. 2010 [cited 2018 Aug 4]; 18(1):81-96. Available from: Available from: http://vip.ucaldas.edu.co/promocionsalud/downloads/Revista18(1)_7.pdfLinks ]

37. Alayón AN, Mosquera-Vásquez M. Adherencia al Tratamiento basado en Comportamientos en Pacientes Diabéticos Cartagena de Indias, Colombia. Rev Salud Pública [Internet]. 2008 Dec [cited 2018 Aug 4];10(5):777-87. Available from: Available from: http://www.scielosp.org/scielo.php?script=sci_arttext&pid=S0124-00642008000500010&lng=es&nrm=iso&tlng=esLinks ]

38. Olivella Fernández MC, Bastidas Sánchez CV, Bonilla Ibañez CP. Comportamientos de autocuidado y adherencia terapéutica en personas con enfermedad coronaria que reciben atención en una institución hospitalaria de Ibagué, Colombia. Investig en Enfermería Imagen y Desarro [Internet]. 2016 May 2 [cited 2018 Aug 4];18(2):13-29. Available from: Available from: http://revistas.javeriana.edu.co/index.php/imagenydesarrollo/article/view/12370Links ]

39. Osterberg L, Blaschke T, Koop-C Everett. Adherence to Medication. N Engl J Med [Internet]. 2005 [cited 2018 Aug 12];353:487-97. Available from: Available from: www.nejm.orgLinks ]

40. Brath H, Morak J, Kâstenbauer T, Modre-Osprian R, Strohner-Kästenbauer H, Schwarz M, et al. Mobile health (mHealth) based medication adherence measurement - a pilot trial using electronic blisters in diabetes patients. Br J Clin Pharmacol 2013;76(S1):47-55. [ Links ]

41. Lerman I, López-Ponce A, Villa AR, Escobedo M, Caballero EA, Velasco ML, et al. Estudio piloto de dos diferentes estrategias para reforzar conductas de autocuidado y adherencia al tratamiento en pacientes de bajos recursos económicos con diabetes tipo 2. Gac Med Mex. 2009;145(1):15-9. [ Links ]

42. Vervloet M, van Dijk L, de Bakker DH, Souverein PC, Santen-Reestman J, van Vlijmen B, et al. Short- and long-term effects of real-time medication monitoring with short message service (SMS) reminders for missed doses on the refill adherence of people with Type 2 diabetes: evidence from a randomized controlled trial. Diabet Med [Internet]. 2014 Jul 1 [cited 2019 Jun 25];31(7):821-8. Available from: Available from: http://doi.wiley.com/10.1111/dme.12439Links ]

43. Huang Z, Tao H, Meng Q, Jing L. Effects of telecare intervention on glycemic control in type 2 diabetes: A systematic review and meta-analysis of randomized controlled trials. Eur J Endocrinol. 2015;172(3):R93-101. [ Links ]

44. Cheong C, Barner JC, Lawson KA, Johnsrud MT. Patient adherence and reimbursement amount for antidiabetic fixed-dose combination products compared with dual therapy among texas medicaid recipients. Clin Ther [Internet]. 2008 [cited 2019 Jun 25];30(10):1893-907. Available from: Available from: www.Rxlist.comLinks ]

45. Zeng F, An JJ, Scully R, Barrington C, Patel B V, Nichol MB. The Impact of Value-Based Benefit Design on Adherence to Diabetes Medications: A Propensity Score-Weighted Difference in Difference Evaluationv he_730 846-852. Value Heal [Internet]. 2010[cited 2019 Jun 25];13:846-52. Available from: Available from: http://www.ispor.org/Links ]

46. Zhai Y, Zhu W, Cai Y, Sun D, Zhao J. Clinical- and Cost-effectiveness of Telemedicine in Type 2 Diabetes Mellitus. Medicine (Baltimore) [Internet]. 2014 Dec [cited 2019 Jun 25];93(28):e312. Available from: Available from: http://www.ncbi.nlm.nih.gov/pubmed/25526482Links ]

47. Boulos MNK, Wheeler S, Tavares C, Jones R. How smartphones are changing the face of mobile and participatory healthcare: An overview, with example from eCAALYX. Biomed Eng Online. 2011;10:1-14. [ Links ]

48. Klasnja P, Pratt W. Healthcare in the pocket: Mapping the space of mobile-phone health interventions. J Biomed Inform [Internet]. 2012;45(1):184-98. Available from: http://dx.doi.org/10.1016/j.jbi.2011.08.017Links ]

49. Mira-Solves JJ, Orozco-Beltrán D, Sánchez-Molla M, Sánchez García JJ. Evaluación de la satisfacción de los pacientes crónicos con los dispositivos de telemedicina y con el resultado de la atención recibida. Programa ValCrònic. Aten Primaria [Internet]. 2014 [cited 2019 Jan 24];46(S3):16-23. Available from: Available from: http://www.elsevier.es/es-revista-atencion-primaria-27-pdf-S0212656714700617Links ]

Received: January 05, 2023; Accepted: May 08, 2023

* Correspondencia: Carlos Mario Cortina-García. Medellín (Colombia). E-Mail: cortina@doctor.com

Creative Commons License This is an open-access article distributed under the terms of the Creative Commons Attribution License