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Introduction
Rheumatoid arthritis (RA) is an autoimmune, chronic, inflammatory, and multisystemic disease.1 This condition affects 1% of the population worldwide; For the year 2018, according to the Community Oriented Program for Control of Rheumatic Diseases (COPCORD) questionnaire; a prevalence of RA of 1.49% was estimated in Colombia,2 which makes it the most prevalent inflammatory rheumatic disease.
Due to the alarming levels of propagation and severity of the SARS-CoV-2 virus, the World Health Organization (WHO) declared that coronavirus 19 disease (COVID-19) constituted a pandemic.3 In Colombia, in response to the declaration of a health emergency, specific measures, such as mandatory preventive isolation and restriction of access to healthcare centers in person, were adopted to mitigate the rapid spread of the virus. For this reason, strategies such as tele-health, which is based on remote service through information and telecommunication technologies, were defined.4-6The patients diagnosed with RA usually have a higher risk of infection compared with the general population, due to impaired immune system, added to the iatrogenic effect generated by the different drugs that control the disease.7 Taking into account that these characteristics alter the immune response to infectious diseases, it can be considered that the patients with RA are more vulnerable to covid-19 and, therefore, the telehealth strategy would help to mitigate the risk of contagion.
With regard to telehealth in the population with RA, a systematic literature review revealed a high viability and good level of acceptance, with a proven effectiveness greater than or equal to that of conventional consultation.8 In the context of the health emergency due to Covid-19, the experience of implementing telehealth in patients with RA in China was reported, and it was concluded that the access to medical services through online tools avoids saturation of outpatient services and reduces cross-infections, by restricting face-to-face attendance during the pandemic.9 In the same line, a research conducted in Bogotá (Colombia) identified that there was no incidence of COVID-19 infection in a cohort of patients treated by telemedicine at the beginning of the pandemic, and it was found that almost 75% of the patients were well controlled.10 Before the pandemic period, Cajas et al.11 conducted a descriptive study, between August 2017 and March 2020, in which they determined the performance of synchronous tele-health in several cities of the country, including 479 patients with RA. When measuring the disease activity (using the DAS-28), they found a decrease in the proportion of patients with high disease activity of up to 57%, which demonstrated the clinical efficacy of telehealth.
Some of the fundamental dimensions for monitoring health care, and in this case telehealth, are: the assessment of self-care agency, described by Dorothea Orem as a set of intentional actions carried out by the person to control internal or external factors that can compromise his/her life12; the quality of life, defined by the WHO as the perception that the individual has of his/her position in life with respect to the culture and value systems that surround him/her13; and finally, the adherence to treatment, understood as the degree of behavior of a patient, related to taking medications and following healthy habits14.These 3 dimensions then allow to comprehensively assess the physical, social, and emotional aspects in patients with chronic diseases, such as RA, since the clinical manifestations have an impact on the decrease in quality of life and the performance of their daily activities.15
Meanwhile, there are no studies in the literature that describe the effect of telehealth on the outcomes of self-care agency capacity, and there are very few studies that assess adherence to treatment in this context in patients with RA. The objective of this study was to describe the changes in the level of therapeutic adherence, quality of life and self-care agency capacity, during a follow-up period, in a group of patients with RA connected with a non-face-to-face multidisciplinary consultation model during the COVID-19 pandemic.
Methodology
Study design and study population
This study is a subanalysis of the research project entitled "Evaluation of a non-face-to-face multidisciplinary health care model in a population with RA, highly vulnerable to SARS-CoV-2/COVID-19, in a situation of health emergency". It corresponds to a descriptive cohort study in a 12-week follow-up period, between July and October 2020. It was made a description of the levels of therapeutic adherence, quality of life and self-care capacity, which were measured using structured questionnaires. These questionnaires were carried out through telehealth care (synchronous telemedicine), in accordance with the regulations in force in the country where the study was conducted, for which a telephone call was made, in the context of a non-face-to-face multidiscilinary care, in a health provider institution (IPS) located in Bogotá, Colombia. The population consisted of patients with RA, highly vulnerable to SARS-CoV-2, who had the power to voluntarily migrate between the non-face-to-face and face-to-face models during follow-up.
Patients over 18 years of age with a confirmed diagnosis of RA and access to information and communication technologies (ICT) by telephone were included. Patients who did not accept to enter to the study, patients who did not have access to the telephone call and those who, due to their cognitive conditions, did not have the capacity to provide the reliable information necessary for the development of the study, were excluded.
Variables assessed
Information on sociodemographic and clinical variables was collected by data extraction from medical records.
For the evaluation of possible changes in the quality of life, adherence to treatment and self-care capacity, within the framework of telehealth care, two measurements were made: one at the beginning of the follow-up (week 0) and the other at the end (week 12), through telephone calls by the research group, which was composed of health professionals who are experts in each area and in the application of these scales. In the same telephone call during the attention, the health professionals applied the three questionnaires of the measured scales.
The European Quality of Life 5 Dimensions 3 Levels (EQ-5D-3L) scale validated in Spanish was used for the evaluation of the quality of life.16,17The results are presented as the changes in each of its 5 spheres when comparing the final measurement with the initial one. In addition, for the EQ-5D-3L, an overall index score was calculated, measuring from the lowest (worst) to the highest (best) score for each patient and time point. Likewise, we used the time trade-off (TTO) assessment technique, based on the list of sets of preference values currently available for the EQ-5D-3L for each state of health, obtained from studies in the general population. This is an index that can range between the value 1 (the best state of health) and 0 (death). For this calculation, the sets of values from Spain were chosen, since none of them is currently available for Colombia. Finally, the state of health was also measured with the global valoration scale (global VAS) with a score from 0 to 100, in which higher scores are equivalent to a better state of health.
For the assessment of the adherence to treatment, the Morisky Green Levine Medication Adherence Scale (MGLS) was applied,18,19and 2 levels of adherence to medication were obtained, based on the MGLS score: high (adherent) and low (non-adherent) adherence, with 0 and 1-1 points, respectively. The changes in the scores of each item at the end with respect to the beginning were analyzed, as well as the change of the adherent and non-adherent status.
In order to assess self-care capacity, the Appraisal of Self-care Agency Scale-Revised (ASA-R), adapted to Spanish, was used.12 This scale has a total of15 questions in 3 areas, and each question is developed from a 5-point Likert scale; the area that lacks of self-care capacity is reverse-coded. The changes in the proportion of answers for each question were analyzed, according to the 5 items, and in turn the total score; a higher total score was interpreted as a higher level of self-care capacity.
Data collection and statistical analysis
The data collection was carried out in the period between July and October 2020; it was recorded in the Redcap software (https://www.project-redcap.org/) and then exported to the Stata® 13 program for the respective statistical analyses.
The calculation of the sample size is described in detail in Annex Appendix B, available in the Supplementary File 1. The analysis was reported using absolute and relative frequencies for the qualitative variables and means with standard deviation or medians, with minimum and maximum values or interquartile range (IQR), for the quantitative ones, in accordance with the distribution of the data. To evaluate the possible changes (from the initial measurement to the final measurement) in the quality of life, adherence to treatment and self-care capacity, when the categories (dichotomous qualitative variables) were analyzed, the McNemar test was used, and the Wilcoxon test was used when non-dichotomous variables were analyzed. It was determined that the statistical differences were significant with p-values <0.05.
Ethical considerations
The research was developed under legal ethical criteria, taking into account Resolution 8430 of 1993, which classifies the research as of minimal risk. Authorization for the use of personal data was requested, in accordance to Law 1581 of 2012. This study was approved by the Human Research Ethics Committee HSJ-FUCS (CEISH) 0235-2019 of the Hospital de San José. Verbal informed consent was obtained by telephone from the clinical setting, in which the procedures performed within the telehealth model established by the IPS were explained.
Results
One hundred individuals who met the inclusion criteria and provided informed consent were invited and included. During the study follow-up, 29 patients evaluated through telehealth voluntarily migrated to the face-to-face model, which is why the descriptive cohort of 71 individuals who remained in the telehealth modality throughout the study was analyzed. The data of the individuals who preferred to continue face-to-face care are not presented or analyzed. 86% were women (n = 61), the age range was between 33 and 86 years, with a median of 63 years (Table 1). The most prevalent comorbidities were arterial hypertension and diabetes mellitus, each with 35.2% (Table 1).
Table 1 Sociodemographic characteristics and clinical antecedents.
| Variable | n = 71 | % |
|---|---|---|
| Age | ||
| Median 63 (min. 33/max. 86) | ||
| Sex | ||
| Female | 61 | 85.9 |
| Male | 10 | 14.1 |
| Marital status | ||
| Single | 22 | 30.9 |
| Married | 31 | 43.6 |
| Divorced | 4 | 5.6 |
| Widower | 10 | 14.1 |
| Free Union | 4 | 5.6 |
| Socioeconomic stratum a | ||
| 1 | 6 | 8.5 |
| 2 | 37 | 52.1 |
| 3 | 21 | 29.6 |
| 4 | 5 | 7.0 |
| 5 | 1 | 1.4 |
| 6 | 1 | 1.4 |
| Origin | ||
| Bogotá | 50 | 70.4 |
| Out of Bogotá | 21 | 29.6 |
| Occupation | ||
| Intelectual or office activities | 10 | 14.1 |
| Manual activities | 15 | 20.1 |
| Household | 31 | 43.7 |
| Retired | 9 | 12.7 |
| Independent | 3 | 4.2 |
| Unemployed | 3 | 4.2 |
| Educational level | ||
| Elementary | 33 | 46.5 |
| High school | 19 | 26.8 |
| Technician | 14 | 19.7 |
| University | 4 | 5.6 |
| Posgraduate | 1 | 1.4 |
| General pathological antecedents at the beginning of the study | ||
| Variable | n | % |
| Age at diagnosis of RA | ||
| Median 50 (min 16/max 77) | ||
| Erosivity (n = 67) | ||
| Yes | 35 | 47.8 |
| Pathological antecedents (n = 71) | ||
| Arterial hypertension | 25 | 35.2 |
| Diabetes mellitus | 6 | 35.2 |
| Kidney disease | 1 | 1.4 |
| Ischemic heart disease | 3 | 4.2 |
| Infection | 4 | 5.6 |
| Osteoarthrosis | 58 | 82.9 |
| Fibromyalgia | 1 | 1.4 |
| Hypothyroidism | 18 | 25.4 |
| Osteoporosis | 23 | 32.4 |
| Other cardiovascular | 3 | 4.2 |
| Other musculoskeletal | 10 | 14.1 |
| Metabolic | 4 | 5.6 |
| Respiratory | 5 | 7.0 |
| Neoplasms | 1 | 1.4 |
| Dermatological | 2 | 2.8 |
| Gastrointestinal | 6 | 8.4 |
| Variable | n = 71 | % |
| Psychiatric | 1 | 1.4 |
| Renal | 4 | 5.6 |
| Ophthalmological | 2 | 2.8 |
Source: table elaborated by the researchers.
a Tariff system for public services and taxes in Colombia, which is administered through socioeconomic stratification, based on the characteristics of the dwellings and their surroundings; stratum 1 is defined as the lowest and stratum 6 as the highest.
As for the quality of life, assessed through the categories of the 5 questions of the EQ-5D-3L, as well as with the global VAS, the TTO and the score of the overall index evaluated using the same scale, statistically significant differences were not observed (Table 2).
Table 2 Change in the quality of life variable at the beginning and the end of the follow-up.
| Scales | Beginning n = 71 | End n = 71 | ||||
|---|---|---|---|---|---|---|
| EQ-5D-3L | n | % | n | % | p-Value* | |
| Mobility | 0.486 | |||||
| No problems | 38 | 53.5 | 33 | 46.5 | ||
| Some problems | 29 | 40.9 | 35 | 49.3 | ||
| Disability | 4 | 5.6 | 3 | 4.2 | ||
| Personal care | 0.574 | |||||
| No problems | 54 | 76.1 | 51 | 71.8 | ||
| Some problems | 16 | 22.5 | 19 | 26.8 | ||
| Disability | 1 | 1.4 | 1 | 1.4 | ||
| Daily activities | 0.535 | |||||
| No problems | 40 | 56.3 | 36 | 50.7 | ||
| Some problems | 27 | 38.1 | 31 | 43.7 | ||
| Disability | 4 | 5.6 | 4 | 5.6 | ||
| Pain/discomfort | 0.564 | |||||
| No problems | 20 | 28.2 | 14 | 19.7 | ||
| Some problems | 44 | 62.0 | 53 | 74.7 | ||
| Disability | 7 | 9.9 | 4 | 5.6 | ||
| Anxiety/depression | 0.438 | |||||
| 39 | 54.9 | 42 | 59.1 | |||
| No problems | 28 | 39.4 | 29 | 40.9 | 0.1153 | |
| Disability | 4 | 5.6 | 0 | 0 | 0.411 | |
| Disability | Median | (IQR) | Median | (IQR) | 0.4294 | |
| EQ5-VAS global | 70 | (50-80) | 70 | (60-80) | ||
| EQ5-TTO | 0.7 | (0.6-0.9) | 0.7 | (0.6-0.9) | ||
| EQ5-general index score | 0.7 | (0.5-0.8) | 0.7 | (0.5-0.8) | ||
EQ-5D-3L: European Quality of Life 5 Dimensions 3 Levels (EQ-5D-3L); IQR: interquartile range; TTO: time trade-off evaluation technique; VAS:
Visual Analogue Scale, scale of global assessment.
Source: table elaborated by the researchers.
* Wlcoxon test.
In relation to treatment adherence, although there were no statistically significant differences in total adherence, a decrease was observed in patients who were not adherents, from 45.1% to 32.2% between the 2 measures. The only dimension that showed a significant difference was "when you feel well, you stop taking the medication" (p = 0.0253) (Table 3).
Table 3 Changes in therapeutic adherence variables at the beginning and at the end of the follow-up.
| MGLS n | % | n | % | p-Value* |
|---|---|---|---|---|
| Adherent 39 | 54.9 | 48 | 67.6 | 0.060 |
| Non-adherent 32 | 45.1 | 23 | 32.4 | |
| Analysis item by item | ||||
| Do you ever forget to take your medications | ||||
| No 55 | 77.46 | 59 | 83.1 | 0.205 |
| Yes 16 | 22.54 | 12 | 16.9 | |
| Do you take the medications at the indicated times | ||||
| No 14 | 19.7 | 9 | 12.7 | 0.165 |
| Yes 57 | 80.2 | 62 | 87.3 | |
| When you are well, you stop to take the medication | ||||
| No 66 | 93.0 | 71 | 100 | 0.025 |
| Yes 5 | 7.0 | 0 | 0 | |
| If it ever makes you feel bad. You stop taking it | ||||
| No 57 | 80.3 | 56 | 78.9 | 0.818 |
| Yes 14 | 19.7 | 15 | 21.1 |
MGLS: Morisky Green Levine Scale.
Source: table elaborated by the researchers.
* McNemar's test.
Regarding the self-care capacity, significant improvements were observed at the end of the follow-up in the following dimensions: "When I have to take a new medicine, I get informed about the side effects to take better care of myself" (p = 0.0028); "In the past, I have changed some habits in order to improve my health" (p = 0.0442); "I usually take measures to guarantee my safety and that of my family" (p = 0.0003); "In my day to day, I barely have time to take care of myself" (p = 0.0025); "I rarely have time for myself" (p = 0.0213). However, when the total score was evaluated, no significant differences were found in the self-care capacity at the end, when compared with the beginning of the follow-up (Table 4).
Table 4 Changes in the self-care capacity variables at the beginning and at the end of the follow-up.
| Self-care capacity | n | % | n | % | p-Value* |
|---|---|---|---|---|---|
| 1. As my circumstances change, I am making the | 0.2782 | ||||
| adjustments that I need to stay healthy | |||||
| Strongly disagree | 0 | 0 | 0 | 0 | |
| Disagree | 2 | 2.9 | 0 | 0 | |
| Neither agree nor disagree | 2 | 2.9 | 6 | 8.4 | |
| Agree | 55 | 78.6 | 46 | 64.8 | |
| Totally agree | 11 | 15.7 | 19 | 26.8 | |
| 2. If I have problems moving or scrolling I make the | 0.9465 | ||||
| necessary adjustments | |||||
| Strongly disagree | 1 | 1.5 | 0 | 0 | |
| Disagree | 3 | 4.3 | 3 | 4.2 | |
| Neither agree nor disagree | 7 | 10.1 | 11 | 15.5 | |
| Agree | 45 | 65.2 | 41 | 57.8 | |
| Totally agree | 13 | 18.8 | 16 | 22.5 | |
| 3. When necessary, I establish as new priorities the | 0.4467 | ||||
| most appropriate measures to stay healthy | |||||
| Strongly disagree | 0 | 0 | 0 | 0 | |
| Disagree | 1 | 1.5 | 0 | 0 | |
| Neither agree nor disagree | 5 | 7.3 | 4 | 5.6 | |
| Agree | 41 | 59.4 | 41 | 57.8 | |
| Totally agree | 22 | 31.8 | 26 | 36.6 | |
| 4. I often lack the strength needed to take care of myself as I know I should | 0.7113 | ||||
| Strongly disagree | 10 | 14.1 | 5 | 7.1 | |
| Disagree | 24 | 33.8 | 30 | 42.3 | |
| Neither agree nor disagree | 5 | 7.1 | 4 | 5.6 | |
| Agree | 23 | 22.4 | 22 | 31.0 | |
| Totally agree | 9 | 12.7 | 10 | 14.1 | |
| 5. I seek better ways to take care of myself | 0.1478 | ||||
| Strongly disagree | 1 | 1.4 | 1 | 1.4 | |
| Disagree | 1 | 1.4 | 1 | 1.4 | |
| Neither agree nor disagree | 1 | 1.4 | 5 | 7.1 | |
| Agree | 54 | 76.1 | 38 | 53.5 | |
| Totally agree | 14 | 19.7 | 26 | 36.6 | |
| 6. If I need it, I find time to take care of myself | 0.3492 | ||||
| Strongly disagree | 0 | 0 | 0 | 0 | |
| Disagree | 3 | 4.2 | 2 | 2.8 | |
| Neither agree nor disagree | 2 | 2.8 | 2 | 2.8 | |
| Agree | 48 | 67.6 | 44 | 62.0 | |
| Totally agree | 18 | 25.4 | 23 | 32.4 | |
| 7. When I have to take a new medicine, I get informed about the side effects to take better care of myself | 0.0028 | ||||
| Strongly disagree | 11 | 15.5 | 1 | 1.4 | |
| Disagree | 14 | 19.7 | 19 | 26.8 | |
| Neither agree nor disagree | 10 | 14.1 | 3 | 4.2 | |
| Agree | 28 | 39.4 | 24 | 33.8 | |
| Totally agree | 8 | 11.3 | 24 | 33.8 | |
| 8. In the past, I have changed some habits in order to improve my health | 0.0442 | ||||
| Strongly disagree | 5 | 7.1 | 0 | 0 | |
| Disagree | 5 | 7.1 | 5 | 7.1 | |
| Neither agree nor disagree | 0 | 0 | 4 | 5.6 | |
| Agree | 49 | 69.0 | 38 | 53.5 | |
| Totally agree | 12 | 16.9 | 24 | 33.8 | |
| 9. I usually take measures to guarantee my safety and that of my family | 0.0003 | ||||
| Strongly disagree | 1 | 1.4 | 0 | 0 | |
| Disagree | 2 | 2.8 | 1 | 1.4 | |
| Neither agree nor disagree | 1 | 1.4 | 3 | 4.2 | |
| Agree | 51 | 71.8 | 28 | 39.4 | |
| Totally agree | 16 | 22.5 | 39 | 54.9 | |
| Self-care capacity | n | % | n | % | p-Value* |
| 10. I usually evaluate whether the things I do to stay healthy are working | 0.3429 | ||||
| Strongly disagree | 0 | 0 | 0 | 0 | |
| Disagree | 6 | 8.5 | 8 | 11.3 | |
| Neither agree nor disagree | 10 | 14.1 | 8 | 11.3 | |
| Agree | 47 | 66.2 | 39 | 54.9 | |
| Totally agree | 8 | 11.3 | 16 | 22.5 | |
| 11. In my day to day, I barely have time to take care of myself | 0.0025 | ||||
| Strongly disagree | 11 | 15.5 | 5 | 7.1 | |
| Disagree | 46 | 64.8 | 35 | 49.3 | |
| Neither agree nor disagree | 3 | 4.2 | 5 | 7.1 | |
| Agree | 8 | 11.3 | 24 | 33.8 | |
| Totally agree | 3 | 4.2 | 2 | 2.8 | |
| 12. I am able to find the information that I need when my health is threatened | 0.2080 | ||||
| Strongly disagree | 2 | 2.8 | 1 | 1.41 | |
| Disagree | 4 | 5.6 | 11 | 15.5 | |
| Neither agree nor disagree | 6 | 8.5 | 4 | 5.6 | |
| Agree | 53 | 74.7 | 35 | 49.3 | |
| Totalmente de acuerdo | 6 | 8.5 | 20 | 28.2 | |
| 13. I seek help when I cannot take care of myself | 0.3329 | ||||
| Strongly disagree | 0 | 0 | 0 | 0 | |
| Disagree | 7 | 9.9 | 4 | 5.6 | |
| Neither agree nor disagree | 1 | 1.4 | 3 | 4.2 | |
| De acuerdo | 33 | 46.5 | 28 | 39.4 | |
| Totally agree | 30 | 42.3 | 36 | 50.7 | |
| 14. I rarely have time for myself | 0.0213 | ||||
| Strongly disagree | 18 | 25.7 | 2 | 2.8 | |
| Disagree | 36 | 51.4 | 50 | 70.4 | |
| Neither agree nor disagree | 7 | 10.0 | 7 | 9.9 | |
| Agree | 8 | 11.4 | 12 | 16.9 | |
| Totally agree | 1 | 1.4 | 0 | 0 | |
| 15. I cannot always take care of myself as I would like | 0.2869 | ||||
| Strongly disagree | 8 | 11.4 | 2 | 2.8 | |
| Disagree | 13 | 18.6 | 19 | 26.8 | |
| Neither agree nor disagree | 11 | 15.7 | 9 | 12.7 | |
| Agree | 34 | 48.6 | 31 | 43.7 | |
| Totally agree | 4 | 5.7 | 10 | 14,.1 | |
| ASAS-R total score | Median 65 | (IQR) (60-69) | Median 67 | (IQR) (63-71) | 0.1481 |
IQR: interquartile range.
Source: table elaborated by the researchers.
* Wilcoxon test.
Discussion
The present study describes the findings of the evaluation of a group of patients with RA assessed in the context of telehealth in a pandemic period, without finding significant changes in the quality of life, the adherence to treatment, and the capacity for self-care, which remained similar to the baseline values when they attended face-to-face care. The sociodemographic characteristics of the population studied are similar to those described in other populations evaluated in the context of telehealth in a pandemic or in the Colombian population in the context of traditional care.20,21The comorbidities most frequently associated with RA were also analyzed, finding similarities with other studies.22
As for telehealth, studies such as that conducted by Song et al. have implemented clinical assessment models in patients with RA using telemedicine.14 The investigations developed by Chew et al. and by Ferucci et al. used tools to evaluate the disease activity in patients with RA, in a model of telehealth follow-up prior to the pandemic.23,24 During this, a study designed by Zhang et al. reported the experience of 76 patients with this disease who participated in a telehealth assessment program to reduce the effects of contagion. As a result, satisfaction was demonstrated in the experience with virtual management and an average score of 4.6 out of 5 was obtained in the evaluation of the satisfaction of these patients,9 which proves that telehealth is useful for chronic conditions that require strict follow-up.
With regard to the variables of interest in the population with RA, no significant changes were found in adherence to treatment in the total group, which demonstrates that there was no decrease in adherence, but neither was there an increase. This suggests that telehealth does not induce a reduction in the intake of medications. With respect to the final effect of the follow-up in the present study, improvements were evident, since 100% of the studied population demonstrated that they did not interrupt the continuity of their treatment during the periods in which they stated that they were in full general health, unlike the baseline, in which 7% decided to stop taking the medication when they felt well.
Several studies consider that the current evidence on the self-care for RA is limited and that the factors that influence the self-care capacity in these patients are insufficient.25,26 It should be noted that most of these studies that assess self-care capacity have been conducted in patients with RA assessed in person. There is no report of studies that have evaluated the self-care agency with the ASA-R instrument in patients with RA under the telehealth model during a pandemic, which is a novel aspect of the present study. Although no significant differences were found in self-care capacity during follow-up, improvements were noted in the aforementioned dimensions. Thus, self-care during the health emergency remained constant during the follow-up period and improved in some areas, thus contributing, most likely, to the personal and interpersonal well-being and functionality of the patients evaluated.
There are few studies that have measured quality of life in the telehealth context with the EQ-5D-3L instrument in patients with RA. In the research conducted by Munchey et al., developed in a face-to-face care context, the dimension most commonly reported was pain/ discomfort (66.1%), in which the EQ-5D utility score obtained a median (IQR) of 0.65 (0.5-0.73) and a median EQ-VAS score of 70, similar to what was presented in our case.27 In the present study, no significant differences were found in the dimensions evaluated before and after the follow-up of this variable, which could indicate that the patients maintained the same levels of pain/discomfort during the period evaluated, without deteriorating their quality of life.
Limitations
Since there are very few studies that have used the Morisky Green, EQ-5D-3L and ASA-R scales in research that includes patients with RA in the context of telehealth, it was difficult to contrast the results with other similar studies. There is a high risk of selection bias in this study, due to its methodological characteristics. In order to prevent some of them from being presented, strict compliance with the above mentioned inclusion criteria was applied. A weakness of the study is the lack of analysis of the outcomes of disease activity (e.g., DAS28) and response, as well as the typification of the treatments received. It should be made clear that it was not carried out because it was not our objective. The short follow-up period could also be considered a weakness; however, it was adjusted to the periods of strict quarantine, in accordance with the rhythms of the COVID-19 pandemic. In addition, in some scenarios, the use of an exclusively telephone tool to assess the patients in this telehealth model could be considered a weakness, however, we consider that the contributions of this study may be valuable, considering that in many opportunities in our country other type of ICT that involves videos or screens for said attention is not available. In the present study, the impact of telehealth on the economic dimension of the healthcare system was not evaluated, and multivariate analyses to assess the relationship between quality of life, adherence, and self-care capacity with the variables specific to RA, in order to analyze the outcome of disease activity were not performed. Finally, due to the type of design of the present study, there are very important confounding factors since patients with difficulties in using the telemedicine service, with cognitive alterations or who did not have access to technology were excluded, which could be related to the educational and socioeconomic status, and multivariate analyses were not carried out to eliminate said biases.
Conclusions
Through the present descriptive cohort study, it is demonstrated that, in a very short follow-up period, in particular conditions such as the covid-19 pandemic and quarantine, in patients with RA evaluated through telehealth there are no major changes in their quality of life, adherence and self-care capacity levels, and stability is maintained during the tele-health intervention.
In the context of the pandemic, telehealth has relied on ICTs and has achieved an exchange of valid information for the diagnosis, treatment, prevention, research and evaluation of the disease, which has made it possible to implement this strategy for the care of patients with RA through mixed models (face-to-face and remote). It is possible that this type of care allows the approach to multidisciplinary assessment of patients with RA who live in dispersed populations and with difficult access to face-to-face consultation, thus enabling timely access. We consider necessary to continue implementing strategies to evaluate and enhance adherence to treatment and the self-care capacity of the population who suffer from chronic rheumatological pathologies treated by telehealth.
