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Patients with cardiovascular diseases managed by a person-centered care (PCC) approach have been observed to have better treatment outcomes and satisfaction than with traditional care. eHealth may facilitate the often slow transition to more person-centered health care by increasing patients’ beliefs in their own capacities (self-efficacy) to manage their care trajectory. eHealth is being increasingly used, but most studies continue to focus on health care professionals’ logic of care. Knowledge is lacking regarding the effects of an eHealth tool on self-efficacy when combined with PCC for patients with chronic heart diseases.
The objective of our study was to investigate the effect of an eHealth diary and symptom-tracking tool in combination with PCC for patients with acute coronary syndrome (ACS).
This was a substudy of a randomized controlled trial investigating the effects of PCC in patients hospitalized with ACS. In total, 199 patients with ACS aged <75 years were randomly assigned to a PCC intervention (n=94) or standard treatment (control group, n=105) and were followed up for 6 months. Patients in the intervention arm could choose to use a Web-based or mobile-based eHealth tool, or both, for at least 2 months after hospital discharge. The primary end point was a composite score of changes in general self-efficacy, return to work or prior activity level, and rehospitalization or death 6 months after discharge.
Of the 94 patients in the intervention arm, 37 (39%) used the eHealth tool at least once after the index hospitalization. Most of these (24/37, 65%) used the mobile app and not the Web-based app as the primary source of daily self-rating input. Patients used the eHealth tool a mean of 38 times during the first 8 weeks (range 1–118, SD 33) and 64 times over a 6-month period (range 1–597, SD 104). Patients who used the eHealth tool in combination with the PCC intervention had a 4-fold improvement in the primary end point compared with the control group (odds ratio 4.0, 95% CI 1.5–10.5;
We found a significant effect on improved general self-efficacy and the composite score for patients using an eHealth diary and symptom-tracking tool in combination with PCC compared with traditional care.
Swedish registry, Researchweb.org, ID NR 65 791.
Acute coronary syndrome (ACS) is an acute manifestation of coronary heart disease that includes myocardial infarction and unstable angina pectoris. In patients with ACS, eHealth studies have shown positive health-related outcomes [
In contrast to eHealth, remote monitoring considers monitoring a disease from an objective perspective and implies 1-way communication between health care professionals and patients [
Consequently, there is a lack of knowledge about whether such solutions can be used in a PCC approach to strengthen a patient’s self-efficacy. Therefore, this study aimed to investigate the effect of a Web- and mobile-based eHealth diary and symptom-tracking tool (henceforth eHealth tool) combined with a PCC intervention in patients hospitalized for an ACS event.
This study was part of a randomized intervention study: Person-centered Care after Acute Coronary Syndrome (PACS study, Swedish registry, Researchweb.org, ID NR 65 791) [
For this substudy, all of the patients in the control group of the original PACS study were included and compared with those in the intervention group of PACS who chose an eHealth tool (eHealth group). The patients who were included in the eHealth group received the same structured PCC approach as described in the main PACS study [
The eHealth tool consisted of a mobile app and access to a webpage, and the patient had the option to use the webpage or the mobile app, or both. Patients who were enrolled in the control group were managed according to standard rehabilitation, which followed guideline-directed care that was compliant with Swedish standards. Patients in the control group answered questionnaires and instruments, similar to the eHealth group, at baseline, 4 weeks, 8 weeks, and 6 months.
The mobile app consisted of 3 modules: (1) a self-rated fatigue scale, (2) a symptom trend graph, and (3) a built-in accelerometer within the phone to provide a daily average of the patient’s physical activity level (
Functional similarities and differences between the webpage and the mobile app eHealth interventions.
Webpage | Mobile app |
Rating of fatigue | Rating of fatigue |
Visual symptom trend graph over time | Visual symptom trend graph over time |
Free-text diary function | Daily activity measurement using a built-in accelerometer |
Chat function |
|
Personal links to relevant webpages |
|
Patient self-rating of fatigue used in the webpage and mobile app eHealth interventions.
Dimension | Rating |
Physical fatigue | I feel that I am in great condition |
|
I feel that I am in good condition |
|
I feel that I am in fair condition |
|
I feel that I am in poor condition |
Mental fatigue | I have no problem concentrating |
|
I have to make an effort to concentrate |
|
I have to make a huge effort to keep concentrating |
|
I cannot concentrate at all |
Motivation | I want to do a lot of things |
|
I only do the most necessary things |
|
I have no motivation to do anything |
|
I dread doing anything at all |
Activity level | I feel very active |
|
I manage what needs to be done |
|
I get very little done |
|
I do nothing |
The webpage consisted of 5 modules: (1) self-rated symptoms of fatigue (same as on the mobile app described above), (2) a symptom trend graph, (3) a diary function for free-text entries to capture the everyday experience using the patient’s own words, (4) a chat function with other patients and registered nurses within the study, and (5) personal links to relevant webpages and the ability to upload documents (
A registered nurse at the hospital asked all of the patients in the eHealth group if they were interested in using the eHealth tool. Patients had the opportunity to borrow a mobile phone with the eHealth app preinstalled or to download it for use on their own mobile phone. Users were registered with a username and password on the webpage, and the online webpage was connected to the mobile app. An introductory demonstration, which required the patient to test the eHealth tools, was provided by a registered nurse who was familiar with the study so that patients could start using the tools freely during their hospital stay. Additional training could be requested if needed. Patients also had access to a video demonstration online for further information. The patients themselves decided on the frequency and patterns of use of the eHealth tools. After 8 weeks, the registered nurse and physician at the primary care center asked patients whether they wanted to return (if borrowed) or continue to use the mobile phone. Access to the webpage had no time restriction.
We evaluated patient-reported scores on the General Self-Efficacy Scale (GSES) using the Swedish version [
Patients in the control and eHealth groups filled out the GSES instrument at baseline at the hospital, and at 4 weeks, 8 weeks, and 6 months.
The primary end point was a composite of changes in general self-efficacy, return to work or prior activity level, and rehospitalization or death. Each patient was classified as improved, deteriorated, or unchanged. An increase of 4.6 units in the GSES has been suggested to show the minimal clinical important difference for patients [
Those patients who had neither deteriorated nor improved were considered unchanged. Patients were dichotomized into improved versus deteriorated or unchanged status.
Patients in the PCC intervention group who had used the eHealth tool at least once after discharge were included into this substudy and compared with the control group. We used descriptive statistics, such as frequency, mean, median, range, and SD, to describe user patterns. Between-group differences were tested using Fisher exact test for dichotomous variables and the Mann-Whitney
The Regional Ethics Committee of the University of Gothenburg approved the study (DNr 275-11). The study adhered to the rules of the Declaration of Helsinki of ethical principles.
Of the 94 patients in the intervention arm, 37 (39%) chose to use the eHealth tool (PCC + eHealth) and continued to use it at least once, even after discharge from the hospital. The remaining patients (PCC no eHealth, n=57) did not choose to use the eHealth tool (n=39) or did not use the eHealth tool after discharge (n=18) (
General characteristics of the study population divided into control versus PCCa+ eHealth and PCC no eHealth.
Characteristic | Control |
PCC + eHealth |
PCC no eHealth |
|
Female, n (%) | 32 (30.5) | 7 (19) | 16 (28.1) | |
Age in years, mean (SD) | 61.3 (8.9) | 59.8 (10.1) | 60.9 (8.7) | |
|
|
|
|
|
|
None | 1 (1.0) | 1 (3) | 0 (0) |
|
Compulsory | 21 (20.0) | 5 (14) | 11 (19) |
|
Secondary school | 28 (26.7) | 7 (19) | 16 (28) |
|
Vocational college | 14 (13.3) | 9 (24) | 12 (21) |
|
University | 41 (39.0) | 15 (41) | 18 (32) |
Employed, n (%) | 60 (57.1) | 24 (65) | 30 (53) | |
|
|
|
|
|
|
Low | 13 (12.4) | 5 (14) | 10 (18) |
|
Lower-middle | 20 (19.0) | 4 (11) | 9 (16) |
|
Upper-middle | 30 (28.6) | 18 (49) | 17 (30) |
|
High | 30 (28.6) | 8 (22) | 16 (28) |
|
Missing data | 12 (11.4) | 2 (5) | 5 (9) |
|
|
|
|
|
|
ST-elevation myocardial infarction | 24 (22.9) | 9 (24) | 15 (26) |
|
Non-ST-elevation myocardial infarction | 51 (48.6) | 13 (35) | 25 (44) |
|
Unstable angina | 30 (28.5) | 15 (41) | 17 (30) |
General self-efficacy, mean (SD) | 30.3 (5.6) | 28.8 (6) | 30.0 (6) |
aPCC: person-centered care.
A higher percentage of patients (11/37, 30%) in the PCC + eHealth group improved in the composite score than those in the control group (n=105) over a 6-month period (OR 4.0, 95% CI 1.5–10.5;
There were 6 events in the PCC + eHealth group (1 death, 5 readmissions), 12 events in the PCC group without eHealth (3 deaths, 9 readmissions), and 16 events in the control group (2 deaths, 14 readmissions). The proportion of patients who returned to work was similar between groups at 6 months (PCC + eHealth 30/34, 88%; PCC no eHealth 47/53, 89%; control 89/98, 91%).
Primary end point: change in composite score dichotomized into improved versus unchanged or deteriorated condition in the control group compared with PCCawith or without an eHealth intervention.
Change in composite score at 6 months | Control |
PCC + eHealth |
PCC no eHealth |
|
Improved, n (%) | 10 (9.5) | 11 (30) | 10 (18) | |
|
|
|
.006 | .21 |
Unchanged or deteriorated, n (%) | 95 (90.5) | 26 (70) | 47 (83) |
aPCC: person-centered care.
Study profile. ACS, acute coronary syndrome; CABG: coronary artery bypass graft; LOS: length of hospital stay; PCC: person-centered care.
We found that patients who used the eHealth tool in combination with PCC had a 4 times higher improvement in the primary end point compared with those receiving usual care. However, fewer than half of the eligible patients used the eHealth tool after discharge, and they preferred the mobile app over the webpage. In comparison with the patients receiving PCC who did not choose or did not use the eHealth tool after the index hospitalization, improvement in the primary end point was less prominent.
This study showed feasibility, to a limited extent, for use of an eHealth tool by patients after an ACS event because approximately 40% of the eligible patients used the eHealth intervention after discharge. Patients were offered use of the eHealth tool as a completely optional supplement without any reminders. ACS is an overwhelming event inducing several concerns during hospitalization [
Clark et al [
Whereas we observed no difference between groups regarding death or rehospitalization, the primary end point was determined by an improvement in the patients’ self-efficacy level. Self-efficacy is a person’s belief in his or her own ability to execute the behavior required to achieve desired outcomes [
The eHealth tool also made it possible for patients and health care professionals to develop a partnership through their communication via the chat function on the webpage and by patients presenting their trend graphs during follow-up visits. Since this is a complex intervention it is difficult to differentiate which component of the PCC intervention contributed most to the improvement in general self-efficacy. This study suggested that an eHealth tool in addition to a PCC intervention was associated with even higher improvement levels in the composite score in this selected group of patients than in the control group. The effect was driven by improved general self-efficacy, which suggests that an eHealth tool added to a PCC intervention can improve patients’ beliefs in their ability to successfully respond to challenges across a wide range of situations. This in turn was shown to contribute to improved disease management and clinical outcomes, such as health status and health care utilization [
While 94 patients were included in the PCC intervention arm, only 37 (39%) chose the eHealth tool. Nevertheless, 11 patients (30% of the active users, or 12% of the total intervention group) improved even more in the primary end point when they complemented PCC with the eHealth tool in comparison with PCC alone. A comparison of this study outcome with that in the original paper published by Fors et al [
eHealth was still not considered as a viable support tool by the majority of patients in this study. Qualitative studies in telecare suggest that patients with congestive heart failure emphasize the value of the relationship with their health care professional [
This study has several limitations. Results should be interpreted based on the limitation that this was a substudy. Only approximately 40% of the patients included in the intervention agreed to participate in this study, which used an eHealth tool at least once after discharge. This group could consist of the most motivated individuals. Additionally, comparing these patients with the entire control group was a limitation of this study. However, there were no significant differences at baseline in demographic variables between the control and intervention groups. Despite this limitation, our study suggests that, for a selected group of people, this type of eHealth tool adds value in combination with PCC. Finally, another limitation is that we did not know whether the patients actively used the eHealth solution as part of the follow-up visits at the outpatient clinic or in primary care. While patients who used the eHealth tool had significantly higher general self-efficacy levels compared with the control group, the effect of using eHealth tools on shared decision making in a PCC setting still needs to be investigated. More studies, also using a qualitative approach, need to evaluate the potential of the intervention in terms of understanding the tool and patients’ own role in PCC and among a broader study population.
An eHealth diary and symptom-tracking tool in combination with a structured PCC intervention is associated with improved combined scores, comprising self-efficacy, return to work or prior activity level, rehospitalization, and death, in a selected group of patients with ACS compared with usual care. Future research should address the effects and efficiency of an eHealth tool throughout PCC interventions compared with traditional care.
acute coronary syndrome
General Self-Efficacy Scale
odds ratio
Person-centered Care after Acute Coronary Syndrome
person-centered care
This work was supported by the Centre for Person-Centred Care at the University of Gothenburg (GPCC), Sweden and the Swedish Internet fund (internetfonden.se). The GPCC is funded by the Swedish Government’s grant for Strategic Research Area in Care Sciences and is cofunded by the University of Gothenburg, Sweden. The Swedish Research Council; the Swedish agreement between the government and the county councils concerning economic support for providing an infrastructure for research and education of doctors; and Närhälsan Research and Development, Primary Health Care, Region Västra Götaland also contributed to the funding of the study.
AW is the founder and owner of a company that designs and develops mobile apps, and the mobile app discussed in this article has been developed by that company. Other authors have no conflicts of interest to declare.