eHealth Solutions for Symptom Assessment and Monitoring in Adults With Chronic Kidney Disease: A Systematic Review

ABSTRACT

Aims

This systematic review examined eHealth solutions used to assess and monitor symptoms among adults with CKD.

Design

A systematic review was conducted and reported in accordance with the PRISMA checklist. The review protocol was registered in PROSPERO (CRD4202452973).

Methods

Seven databases were searched for English language studies that reported eHealth solutions for symptom assessment and monitoring in CKD between January 2000 and May 2024. The methodological quality of studies was evaluated using the Mixed Methods Appraisal Tool and a co‐design evaluation tool.

Results

Thirty‐eight studies involving 4345 participants with CKD were included. Most of the included studies were non‐randomised controlled trials (n = 16) and non‐experimental studies (n = 13); only a few studies (n = 9) were randomised controlled trials. Current eHealth solutions varied in technologies and functions but were primarily focused on self‐monitoring (n = 22), data recording (n = 14), education (n = 13), providing information (n = 10) and reminders/alerts (n = 10). There was limited evidence from few intervention studies involving eHealth solutions showing improvements in CKD symptoms and/or health‐related quality of life. Among the 14 studies that assessed user satisfaction, satisfaction was high, but challenges and barriers to implementing these solutions were reported.

Conclusion

eHealth solutions have the potential to facilitate symptom assessment and monitoring for adults with CKD, but further high‐quality experimental studies are required to provide better evidence in practice.

Summary

eHealth symptom assessment and monitoring are increasing in practice. While some adults are willing and able to use eHealth solutions, barriers remain due to limited digital health literacy. As few randomised controlled trials exist, further studies are needed to evaluate the benefits of reducing chronic kidney disease symptom burden.

Patient or Public Contribution

No Patient or Public Contribution.

Summary.

• This present review presents a comprehensive synthesis of current eHealth solutions designed for symptom assessment and monitoring in adults with chronic kidney disease.

• The existing eHealth solutions vary in technologies and functions, with a primary focus on self‐monitoring, data recording, and providing information and educational resources for symptom management.

• Due to methodological differences across studies, there remains insufficient evidence on the effectiveness of eHealth intervention in reducing symptom burden and improving health‐related quality of life. High‐quality experimental studies are needed to provide robust evidence for clinical practice.

1. Introduction

eHealth solutions involve health services, information systems and various electronic technologies to support healthcare delivery (Eysenbach 2001). There is a wide range of eHealth modalities reported in the literature, including electronic health records, telehealth, mobile health, web apps and social media (Wang and Ku 2020). In each category, various applications have been developed to deliver healthcare services. In the era of advanced technology, eHealth solutions have the potential to improve healthcare practices and patient outcomes (Aiyegbusi et al. 2019). Accessing healthcare services via eHealth could allow more people to get the care they need because it allows better care access with time and cost savings for both patients and healthcare providers, as well as reduced travel by patients to healthcare appointments (Jiang et al. 2019; LeBlanc et al. 2020). Disadvantages, however, such as limited eHealth literacy levels, barriers to usability, user costs, lack of privacy, security concerns and erroneous information persist (Russell et al. 2022).

It is estimated that, globally, at least 10% of the adult population has chronic kidney disease (CKD) (Bello et al. 2024). Reduced kidney function contributes to various physical, psychological and emotional symptoms. Common symptoms include fatigue, pain, pruritus, poor mobility, depression, anxiety, poor sleep, and restless legs (Fletcher et al. 2022; Huang et al. 2021; Menzaghi et al. 2023; Safarpour et al. 2023). While symptoms might be prevalent, there are varying degrees of severity and frequency (Humphreys et al. 2008). About 70% of adults with CKD experience fatigue, with one in four reporting a high level of this symptom (Gregg et al. 2021). Pain is also common in CKD, with 60% of adults on dialysis indicating that pain impacts their daily life activities (dos Santos et al. 2021; James et al. 2020). Symptom burden in CKD is also associated with poor health‐related quality of life (HRQoL), as symptoms interfere with usual activities, limit social interaction, reduce capacity to undertake work, and contribute to significant morbidity and mortality (Fletcher et al. 2022; Moore et al. 2022; Yapa et al. 2020).

Efforts have been made to enhance patient symptom management, but kidney care providers may not routinely screen and assess symptoms (Meuleman et al. 2024). In addition, those with CKD find it difficult to self‐monitor their symptoms because of a lack of knowledge and skill as well as supportive monitoring methods (Shen et al. 2021). Symptom assessment is necessary to make an initial diagnosis, understand the symptom's cause, assess the disease's everity and progression, inform the treatment and evaluate the response to treatment (Davison et al. 2015; Metzger et al. 2021). Symptom assessment and monitoring are crucial initial steps for identifying symptoms early, initiating evidence‐based interventions and anticipating patient needs (van der Veer et al. 2017).

The use of eHealth to support CKD self‐management has increased (Lewis et al. 2019; Stevenson et al. 2019) and is used for lifestyle, dietary and medication education, monitoring blood pressure and providing social and psychological support (Curtis et al. 2024; Lewis et al. 2019; Russell et al. 2022). A systematic review of eHealth CKD self‐management interventions found improvements in health outcomes such as blood pressure control, medication adherence and enhanced quality of life (Shen et al. 2019). Users of eHealth solutions found these acceptable and expressed interest in using them to support CKD management (Aiyegbusi et al. 2019; Schrauben et al. 2021). As global healthcare trends have moved towards remote symptom monitoring by applying technology, studies in CKD symptom assessment and management using eHealth solutions are emerging. For example, the Symptom Monitoring with Feedback Trial (SWIFT) aims to evaluate the effect of regular electronic symptom monitoring with feedback in adults receiving haemodialysis on symptoms and HRQoL (Greenham et al. 2022). Findings from a pilot SWIFT study involving 226 adults receiving haemodialysis in 4 satellite units in Australia over 6 months indicated that electronic symptom monitoring was feasible and identified improvement in HRQoL dimensions and symptom burden scores (Agarwal et al. 2023). As a complex intervention, the components that are included in these eHealth solutions and how these work to support CKD symptom self‐management remain unclear. Additionally, it is uncertain whether the existing eHealth solutions for symptom assessment and monitoring are based on sufficient evidence, involve target users and relevant stakeholders in their development process and whether current study findings can effectively inform clinical practice in CKD care.

In other health conditions, such as cancer care, a systematic review of remote symptom monitoring integrated into electronic health records found that most existing systems were developed to monitor cancer patients' symptoms longitudinally between visits (Gandrup et al. 2020). These systems generated real‐time alerts to healthcare providers during consultations. While studies have reported benefits of remote symptom monitoring, there is a need for robust evidence from intervention studies, particularly beyond oncology (Gandrup et al. 2020). Although eHealth solutions are increasingly used in kidney care, evidence for symptom assessment and monitoring in CKD remains insufficient. To date, no systematic reviews on CKD management have explicitly focused on symptom assessment and monitoring. Therefore, a review of the evidence in the CKD population is essential to inform practice.

This systematic review examines eHealth solutions used to assess and/or monitor symptoms in adults with CKD. Specifically, this review addresses the following questions: (1) what eHealth solutions exist, and how are these used to assess and/or monitor symptoms in adults with CKD? (2) what patient‐related health outcomes have been assessed and/or monitored by eHealth solutions in adults with CKD? and (3) what changes to patients' outcomes have occurred for adults with CKD when eHealth solutions are used?

2. Methods

The systematic review protocol was registered in PROSPERO (CRD4202452973). This review is reported according to the Preferred Reporting Items for Systematic Reviews and Meta‐Analyses (PRISMA) statement (Page et al. 2021).

2.1. Eligibility Criteria

Eligibility criteria were defined using the PICO (Population, Intervention, Comparison, Outcome) framework. Adults over 18 years with CKD of any grade or duration were considered as the study population. The reviewers did not screen papers based on specific diagnostic standards for CKD. Instead, this review included studies that identified the study population as having CKD. In terms of intervention, eHealth is defined as “health services and information delivered or enhanced through the Internet and related technologies” (Eysenbach 2001), and includes different categories such as electronic health records, telehealth, mobile health, web apps and social media (Wang and Ku 2020). A description of each is presented in Table S1. In this review, eHealth solutions included any programs, strategies, formats, platforms, tools or interventions delivered through any form of eHealth technology (including mobile apps, telemedicine services, remote monitoring devices, online programs, computer‐based programs and electronic devices) to assess and/or monitor symptoms (Eysenbach 2001; Wang and Ku 2020). In this review, CKD symptoms were any subjective symptoms experienced and self‐reported by patients. Symptom assessment and monitoring require the use of tools to collect data related to symptoms experienced by patients (Anderson et al. 2023; Ishaque et al. 2019). Studies in which these tools were used in an eHealth solution (even if part of a broader study) were included in this review. Studies were included regardless of design. For experimental studies involving one or more intervention groups, comparators were usual care, face‐to‐face intervention or no comparison. Outcomes of interest were symptoms, HRQoL, satisfaction and patients' and/or healthcare providers' opinions about usability and feasibility. Studies were excluded from this review according to the following criteria: (1) studies focused only on family caregivers or healthcare providers, (2) studies did not report at least one of the outcomes of interest (above), (3) studies did not include an eHealth intervention corresponding with the definition (above), (4) study protocols or (5) conference abstracts.

2.2. Search Strategy

Comprehensive database searches were conducted in PubMed, MEDLINE, CINAHL, Embase, Cochrane Library, JBI and PsycINFO for English language studies published from January 2000 to May 2024. The review team developed the search strategy and then discussed it with an experienced university librarian. The search strategy was developed for PubMed and then adapted for other databases using keywords: “chronic kidney disease”, “end‐stage kidney disease”, “chronic renal insufficiency”, “eHealth”, “mHealth”, “telehealth”, “telemedicine”, “information and communication technology”, “symptom”, “symptom assessment” and “monitoring”. The whole search strategy can be found in Table S2.

2.3. Selection Process

Covidence software was used to screen and extract data (Covidence 2024). After removing duplicate studies, titles and abstracts were independently screened for eligibility by two reviewers (KLB, AH). Studies not meeting inclusion criteria were removed. Next, the full texts of eligible studies were independently reviewed by two reviewers (KLB, AH). Any disagreement was resolved by another reviewer (AB).

2.4. Data Extraction

Three reviewers (KLB, AH, LP) independently extracted data from the eligible studies using a customised data extraction form in Covidence. Data were study characteristics (authors, year of publication, country of study), study design, sample size, participant characteristics (sex, mean age, grade of CKD), study setting, type of intervention (eHealth solution‐specific information) and control, duration of intervention, theoretical framework, outcome measurements and study results. Any discrepancies in the data extraction process were discussed with a separate reviewer (AB) to reach a consensus.

2.5. Quality Assessment

The Mixed Methods Appraisal Tool (MMAT) was used to appraise the quality of all studies (Hong et al. 2018), except co‐design studies, which were assessed for quality using the guidance for assessing action research proposals and projects (McGill et al. 2022; Waterman et al. 2001). The MMAT encompasses core quality assessment categories for these study designs: randomised controlled trials, quantitative non‐randomised controlled trials, descriptive studies, qualitative studies and mixed method studies. An overall MMAT score is not calculated, although each of the categories is used to inform the quality of the included studies (Hong et al. 2018). To provide an overall methodological quality of included studies, the ratings were calculated as a percentage, with each quality assessment category contributing 20%. Therefore, a study meeting all quality criteria would achieve a score of 100% (no methodological limitations). Studies meeting 80% were considered to have minor methodological limitations, 60% were considered moderate and studies scoring 40% or lower were rated as having major methodological limitations. This approach has been used in other reviews (Adams et al. 2021; Gómez‐Cantarino et al. 2020).

2.6. Data Synthesis

The included studies are reported in a narrative summary. All outcomes of interest were synthesised, and findings were grouped by the type of technology, delivery method, disease grade and duration, setting and patients' outcomes. The classification of eHealth was adapted from a study by Shen and colleagues; it includes data recording, consultation, behavioural counselling, communication, education, self‐monitoring, information, reminders/alerts and others (Shen et al. 2019).

3. Results

3.1. Study Characteristics

In total, 1642 studies were initially retrieved, and 466 duplicates were removed. After screening the titles and abstracts, 72 full‐text studies were assessed for eligibility. Thirty‐eight studies were included in this review (see Figure 1). Study characteristics are presented in Table 1. Among the 38 studies, there were 16 non‐randomised controlled trials, 9 randomised controlled trials, 5 cross‐sectional, 3 qualitative descriptive, 2 co‐design and 3 mixed method studies. Studies were conducted in the United States (n = 12), Canada (n = 7), Australia (n = 4), United Kingdom (n = 3), Netherlands (n = 3), China (n = 2), Iran (n = 2), Denmark (n = 1), Ireland (n = 1), Korea (n = 1), Italy (n = 1) and Qatar (n = 1). All studies were published after 2014, with two‐thirds (n = 26) published between 2020 and 2024. The studies involved 4345 adults with CKD, with sample sizes ranging from 8 to 1080. More than half of the participants (n = 2246) were on haemodialysis, 223 were kidney transplant recipients, 167 were receiving peritoneal dialysis and 1709 were not receiving kidney replacement therapy. The mean age of participants was over 50 years in most studies (n = 34), and most participants were male (about 59%). eHealth solutions were used in various settings, including dialysis centres (n = 19), kidney units/wards (n = 13), patients' homes (n = 10), outpatient clinics (n = 9) and transplant centres (n = 2). The duration of interventions varied between the included studies. Four studies provided the intervention at a single timepoint (Aiyegbusi et al. 2018; Hussain et al. 2022; Schick‐Makaroff and Molzahn 2014, 2015). Twenty‐four study interventions invited participants to engage for a period of time; most interventions ranged from 6 to 12 weeks in duration (Chae and Kim 2024; Chan et al. 2016; Dingwall et al. 2021; Doyle et al. 2019; Gross et al. 2017; Jakubowski et al. 2020; Jhamb, Devaraj, et al. 2023; Jhamb, Steel, et al. 2023; Li et al. 2014; Mansouri et al. 2020; Nadort et al. 2022; Reilly‐Spong et al. 2015; Tangaro et al. 2016; Thompson et al. 2021; Zhao et al. 2020). Among these 24 studies, half reported a high adherence or completion rate among participants, but only a few reported how participants engaged with the intervention over time. For instance, Dingwall et al. reported good engagement in a mobile app program by adults undergoing haemodialysis, with more than 93% after 3 months of intervention and 90% over 6 months of follow‐up still using the app (Dingwall et al. 2021). Another study showed no drop‐off in interest over time, and participants still maintained a high level of use of the smartphone‐based self‐management system up to 6 months later (Ong et al. 2016). However, Flythe et al. showed that engagement with a tablet‐based ePROM system reduced after 16 weeks (Flythe et al. 2020). Only 6 studies were informed by a theory or conceptual framework (Anderson et al. 2021; Chae and Kim 2024; Donald et al. 2021; Flythe et al. 2020; Li et al. 2014; Zare Moayedi et al. 2018), such as Social Cognitive Theory or Knowledge to Action framework.

FIGURE 1.

PRISMA flow diagram.

TABLE 1.

Characteristics of included studies (N = 38).

No	Authors, year, country	Characteristics of participants	Setting	Intervention	Theory/Model/Framework	Outcomes and measures	Findings
	Study design			Duration
1	Aiyegbusi 2018 UK Observational study	Adults with stage 4–5 CKD N = 8 Mean age: 64.3 (range 36–87) Sex (female): 4 (50%)	Home	Web portal to collect PROM symptom data electronically Duration: one‐off	Not reported	User experience: qualitative interviews User satisfaction: Likert scale Efficiency: time taken Effectiveness: error rate, assistance required	Simple and easy to use High usability and user satisfaction Those familiar with the internet complete more quickly 5 non‐critical and 1 critical error due to omissions of participants
2	Anderson 2021 UK Qualitative research	Adults receiving HD N = 22 Mean age: Not specified Sex (female): 10 (45%) in patients	Home, Hospital	Electronic formats of patient‐reported outcomes Duration: NA	Consolidated Framework for Implementation Research	Experiences, views and perceptions of patients and healthcare providers: Semi‐structured interview	The intervention must be flexible but simple and measure outcomes that matter to patients and clinicians Users need IT assistance until they become familiar eHealth solution covered comprehensive key symptoms Patients and healthcare providers expressed a degree of acceptance Concern about how data were used to improve patients' outcomes and it may miss acute symptoms
3	Brys 2020 The Netherlands Observational study	Adults receiving HD for > 6 months N = 40 Mean age: 64.35 ± 13.60 Sex (female): 9 (22.5%)	Dialysis centre, Home	PsyMate smartphone‐based mHealth application to assess fatigue and mood Duration: 7 days	Not reported	Momentary fatigue score, depression score, sleep quality: ESM questionnaire Retrospective fatigue score: Fatigue Severity Scale Retrospective depression score: Hospital Anxiety and Depression Scale	Fatigue scores significantly higher retrospective compared to momentary
4	Brys 2021 The Netherlands Observational study	Adults receiving HD for > 6 months N = 40 Mean age: 64.35 ± 13.60 Sex (female): 9 (22.5%)	Dialysis centre, Home	PsyMate (a smartphone‐based mHealth application) Duration: 7 days	Not reported	Fatigue: Fatigue Severity Scale Depressive symptoms and Anxiety: Hospital Anxiety and Depression Scale	Fatigue in 68% of all random momentary observations Fatigue scores were significantly higher on HD treatment days Fatigue was significantly related to the type of activity, quality of sleep Higher momentary fatigue significantly predicted more depressed feelings Quality of sleep score was 3.92 ± 1.83 (range 1–7)
5	Chae 2024 South Korea Randomised controlled trial	Adults on PD for > 3 months N = 53 Mean age: 45.48 ± 11.60 in IG 48.81 ± 10.87 in CG Sex (female): 28 (52.8%)	Hospital	I: A self‐management mobile application C: Usual care Duration: 10 weeks	Social cognitive theory and ADDIE model (analysis, design, development, implementation and evaluation)	PD‐related knowledge, PD‐related self‐efficacy, PD‐related health behaviour: developed questionnaires HRQoL: Kidney Disease Quality of Life‐36	No significant differences between 2 groups in terms of HRQOL physical domain and psychological domain The IG showed a significant improvement in PD‐related knowledge, PD‐related health behaviour No significant differences between 2 groups regarding self‐efficacy
6	Chan 2016 Australia Non‐randomised experimental study	Adults on HD N = 22 Mean age: 53.1 ± 15.3 Sex (female): 6 (30%)	Hospital	Internet‐delivered CBT treatment course (Wellbeing Course) Duration: 8 weeks	Not reported	Depression: Patient Health Questionnaire‐9 item Anxiety: Generalised Anxiety Disorder‐7 item Psychological distress: Kessler 10‐item Functional impairment: Sheehan Disability Scale HRQOL: Health Survey SF 12	Improvement of depression, anxiety and psychological distress No change in functional impairment Improvement of mental HRQoL Acceptability and satisfaction (63%)
7	Chan 2020 United States Retrospective cohort	Adults on HD N = 1080 Mean age: 64 ± 13.3 Sex (female): 433 (42%)	Dialysis centre	I: Natural language processing of clinical documentation C: ICD‐10 codes from billing data Duration: 9 year 2.5 months	Not reported	Symptom prevalence Compare using natural language processing and ICD: Concordance with prevalence from ICD‐10	The percentage of patients with symptoms: fatigue (84%), Nausea/vomiting (74%), Pain (93%) Natural language processing was more accurate and had better sensitivity than ICD at identifying 7 common symptoms
8	Dano 2023 Canada Cross‐sectional study	Adults treated with dialysis or kidney transplant recipients N = 198 Mean age: 57 ± 14 Sex (female): 85 (43%)	Dialysis centre Hospital	Patient outcome measurement information system fatigue computer adaptive test (PROMIS‐CAT) Duration: NA	Not reported	Fatigue: Functional Assessment of Chronic Illness Therapy‐Fatigue (FACIT‐F) Physical and emotional symptoms: Edmonton Symptom Assessment System‐Revised	24% had clinically relevant fatigue, with a higher proportion in dialysis patients compared to a transplant group Tiredness score was 0.53 (95% CI 0.42 to 0.63)
9	Dey 2016 UK Non‐randomised experimental study	Adult on PD N = 22 Mean age: 61.6 (range 26.4 to 93.4 years) Sex (female): 10 (45.5%)	Dialysis centre Home	Telemedicine Duration: 314.9 days (8.0–458.0 days)	Not reported	HRQoL: Kidney Disease Quality of Life 36 User acceptability: Quebec user evaluation of satisfaction with assistive technology Clinical interventions: examination of data related to blood pressure trends, weight gain, pedal oedema or worsening shortness of breath	No significant increase in physical and mental health HRQoL No significant decrease in the effects of kidney disease and disease burden Clinical interventions: effective in reducing admission by early recognition of fluid overload, 36 admissions were avoided Satisfaction scores and retention rates remained high until the end of the programme that suggest a high level of acceptability
10	Dingwall 2021 Australia Randomised controlled trial	Indigenous adults on HD N = 156 Mean age: 55 ± 9.4 Sex (female): No information	Dialysis centre Home	Arm 1: AIMhi Stay Strong App Arm 2: Hep B story contact control/delayed stay strong treatment (HepB/DSS) Arm 3: usual/delayed stay strong treatment (TAU/DSS) Duration: 3 months	Not reported	Anxiety: Kessler Distress Scale (K10) Depression: Patient Health Questionnaire (PHQ‐9) HRQOL: EuroHRQoL (EQ‐5D) Fidelity: number of missed sessions and average minutes for each session by treatment group	Significant decreases in K10 and PHD‐9 scores for both Stay Strong and Hep B Story at 3 and 6 months No significant differences in HRQoL Acceptable level of fidelity
11	Donald 2021 Canada Co‐design	Patients with CKD currently on dialysis and not a previous kidney transplant recipient N = 14 Mean age: 67% were over the age of 65 years Sex (female): 5 (28%)	No information	My Kidney My Health website Duration: NA	Knowledge to action framework	Individuals' perceived ability to find, evaluate and apply eHealth information: eHealth Literacy Scale Usability: SUS scale and Interview	A mean score on the eHealth Literacy Scale was 26.7 (range 15–32), demonstrating various perceived abilities to use information technology for health. High usability with a usability mean score of 90 out of 100
12	Doyle 2019 Ireland Non‐randomised experimental study	Adult patients with CKD N = 23 Mean age: 50.1 ± 15.7 Sex (female): 9 (45%)	Hospital	MiKidney smartphone app Duration: 12 weeks	Not reported	Physical activities: International Physical Activity Questionnaire long form (IPAQ‐LF), the six‐minute walking test (6MWT) Nutritional wellbeing: BMI, waist circumference, body fat, blood parameters (total cholesterol, LDL cholesterol) App usage: app usage and patient satisfaction	No significant increase in physical activity The percentage of overweight and obese participants was reduced, but no significance A significant decrease at T3 in waist circumference and body fat measurements Significant improvement in Total cholesterol and LDL cholesterol at T3 App easy to navigate
13	Finkelstein 2021 United States Cross‐sectional study	Adults with CKD not on dialysis, Adults on PD N = 186 (44 PD and 142 CKD) Mean age: PD 60 ± 8 (range 21 to 88) CKD 68 ± 13 (range 22 to 93) Sex (female): 45% in PD, 53% in CKD	Dialysis centre Hospital	Electronic patient‐reported outcome measures using computer adaptive technology Duration: NA	Not reported	General health, overall quality of life, impact of kidney disease and satisfaction with care: 20 questions on a 10‐point scale Physical symptoms: adapted from the Dialysis Symptom Index and the Broadening Options for Long‐Term Dialysis in the Elderly Depressive symptoms: Patient Health Questionnaire‐2 (PHQ‐2) Anxiety: General Anxiety Disorder‐2 (GAD‐2)	32% of patients on PD and 47% of patients with CKD have depressive symptoms 30% patients on PD and 20% of patients with CKD were troubled by anxiety 50% patients on PD and 33% of patients with CKD have sleep problems 75% patients on PD and 27% of patients with CKD have restless legs
14	Flythe 2020 United States Mixed method	Adults receiving in‐centre HD for > 6 months Phase 1: N = 62 Phase 2: N = 32 Mean age: Phase 1: 61 ± 15 Phase 2: 62 ± 14 Sex (female): Phase 1: 21 (34%) Phase 2: 10 (31%)	Dialysis centre Hospital	Tablet‐Based ePROM System Duration: 16 weeks	Quality Implementation Framework	Quality improvement outcomes: the proportion of symptom ePROMs completed, requiring assistance, completion time Change in patient‐reported patient‐centredness of care: Patient Perception of Patient‐Centredness Scale (PPPC) Symptom ePROM implementation: interviews and observations	The overall completion rate was 84%, with varying completion rates across time. Reasons for missed ePROMs: patient late arrival, sleeping, refusal, forgot No change in pre‐to post‐project patient‐centred care scale scores Symptom ePROM administration was feasible Patients and care team satisfied with the ePROM system and showed acceptance
15	Gabbard 2021 United States Non‐randomised experimental study	Aged 60 and older on HD > 3 months N = 22 Mean age: 69.4 ± 6.6 Sex (female): 14 (63.6%)	Dialysis centre	“K‐Pal” (iPad‐based ePROM) Duration: 6 months	Not reported	Usability: System usability scale (2) Pain: short‐form McGill pain questionnaire 2 Depression: Patient Health Questionnaire‐9 (PHQ‐9) Anxiety: Generalised Anxiety Disorder 7 Item Survey (GAD‐7) Symptom burden: Dialysis Symptom Index HRQoL: Kidney Disease Quality of Life	36% prevalence of depression, 13.6% of anxiety, 50% of pain, 50% of cramping, 50% of dry skin No symptoms improved over time
16	Gross 2017 United States Randomised controlled trial	Adults with progressive kidney disease eligible for kidney or kidney pancreas transplant N = 55 Mean age: 54 ± 12 Sex (female): 31 (56%)	Dialysis centre Home	I: Telephone‐adapted Mindfulness‐based Stress Reduction (tMBSR) C: Telephone‐based support Duration: 8 weeks	Not reported	Anxiety: State–Trait Anxiety Inventory HRQOL, pain: SF‐12 Physical and Mental Component Summaries Depression: Centre for Epidemiologic Studies Depression Scale Sleep quality: Pittsburgh Sleep Quality Index Fatigue: PROMIS‐Fatigue Short Form	No significant reductions in anxiety, depression, fatigue and pain No significant improvement in sleep quality Significant improve mental HRQOL at follow‐up: +6.2 points on the mental component summaries (95% CI: 1.66 to 10.8, p = 0.01)
17	Grove 2024 Denmark Cross‐sectional study	Adults with CKD (eGFR < 40 mL/min/m2) N = 105 Mean age: 74 ± 11 Sex (female): 54 (35.5%)	Renal outpatient clinic	Remote patient‐reported outcomes Duration: NA	Not reported	Reach, Dose, Fidelity and clinical engagement of the intervention: data extracted from data source and interview	Lower participation by older age and lower health literacy The mean adherence rate to the intervention was 82% Lower adherence by poor reported health status and lower patient activation Patients in the PRO‐based telephone follow‐up had a higher adherence rate than PRO‐based follow‐up group Common reasons for needing assistance were measuring blood pressure, undergo blood tests, access the questionnaire
18	Hernandez 2018 United States Non‐randomised experimental study	Adults on HD for > 3 months reporting elevated symptoms of depression N = 14 Mean age: 57.43 ± 12.12 Sex (female): 7 (50%)	Outpatient HD clinic	Internet‐based positive psychological intervention Duration: 5 weeks	Not reported	Feasibility: recruitment rates, refusal rates, retention rates, compliance or adherence rates Depression: Centre for epidemiologic studies depression scale (CES‐D) HRQoL: Kidney disease quality of life (KDQL) Dietary adherence: Renal adherence behaviour questionnaire (RABQ) Utility and usefulness for weekly exercise practices: process evaluation	Significant improvements in depression No significant improvement in multiple HRQoL domains A greater engagement in renal adherence but no statistically significant in self‐care behaviours
19	Hernandez 2021 United States Non‐randomised experimental study	Adults on HD N = 20 Mean age: 55.3 ± 13.1 Sex (female): 4 (20%)	Dialysis centre	Joviality VR program Duration: two consecutive HD treatment sessions (25‐min each sessions)	Not reported	Safety of the VR: Simulator Sickness Questionnaire (SSQ) Subjective ratings of presence and immersion in the VR program: IGroup Presence Questionnaire (IPQ) Subjective ratings of the VR device and software: System Usability Scale (SUS)	Significant decreases were observed after the first VR exposure for fatigue, nausea, oculomotor symptoms, disorientation and total symptomatology The VR device and software had moderate levels of usability (82.74 ± 21.85, range from 15 to 100) The program was fun and easy to use
20	Hussain 2022 Canada Cross‐sectional study	stable kidney transplant recipients and adults on in‐centre HD N = 217 (84 on HD, 133 kidney transplant recipients) Mean age: 54 ± 14 Sex (female): 89 (41%)	Dialysis centre Outpatient transplant clinic	PROMIS sleep disturbance item bank computer adaptive test Duration: one‐off	Not reported	Legacy: Insomnia Severity Index, Edmonton Symptom Assessment System‐Revised (ESAS‐r), Generalised Anxiety Disorder 7‐item Scale (GAD‐7, PROMIS Depression bank, Kidney Disease Quality of Life‐36 (KDHRQOL‐36), Medical Outcomes Study 12‐item Short Form (SF‐12)	15% had moderate/severe sleep disturbance Intervention exhibited good test–retest and scale reliability.
21	Jakubowski 2020 United States Non‐randomised experimental study	Adults on HD for > 3 months with elevated levels of at least one symptom including depression, pain and fatigue N = 10 Mean age: 58.7 ± 12.16 Sex (female): 5 (50%)	Dialysis centre	Technology‐assisted CBT Duration: 8–10 weeks	Not reported	Fatigue: Functional Assessment of Chronic Illness Therapy‐Fatigue (FACIT‐F) Depression: Centre for Epidemiological Studies Depression (CES‐D) Pain: Brief Pain Inventory (BPI) HRQOL: Medical Outcomes Short Form 36 Health Survey (SF‐36) Satisfaction: open‐ended questions	Statistically significant but not clinically meaningful improvements on the SF‐36 physical component score at 3 months follow‐up No significant improvement in depressive symptoms, fatigue, pain at follow‐up Patient adherence to the intervention was high Patients were comfortable engaging with their therapist using headphones and a study laptop and denied concerns related to privacy Patients reported high acceptability and satisfaction with video‐conferencing sessions
22	Jhamb 2023 United States Non‐randomised experimental study	Adults receiving in‐centre HD N = 17 Mean age: 63.6 ± 15.1 Sex (female): 54%	Outpatient dialysis unit	COMEX program Duration: 3 months	Not reported	Physical functions: Short Physical Performance Battery (SPPB); 30 s sit to stand (30‐s STS) test; Gait speed; 6‐Minute Walk Test (6MWT); and Measurement of Leg Strength with Biodex System 3 Pro Fatigue: FACIT‐F Depression: BDI Sleep quality: PSQI Physical, mental and social health: PROMIS Adult Global Health HRQoL: SF‐36 Physical activity: PASE Objective sleep: Actigraph, activPAL3 technology; Sleep and Physical Activity Diary Skeletal Muscle Biopsy: Biopsy of the vastus lateralis muscle; blood samples	Fatigue improved in 8 (62%) patients Depressive symptoms improved in 8 (62%) patients No meaningful change in sleep quality Pain improved or remained unchanged in 8 (62%) patients An increase in physical activity with a mean score increase from 74.9 (61.2) at baseline to 111.5 (68.4) at 3 months High satisfaction
23	Jhamb 2023 United States Randomised controlled trial	Adults receiving in‐centre 3‐times weekly HD N = 160 Mean age: 58 ± 14 Sex (female): 72 (45%)	Dialysis centre Home	I: TÄ€C care 12 weekly sessions of CBT delivered via telehealth C: telehealth health education Duration: 12 weeks	Not reported	Fatigue: Functional Assessment of Chronic Illness Therapy‐Fatigue Pain severity: Brief Pain Inventory Depression: Beck Depression Inventory	Fatigue: Patients in the intervention group experienced statistically and clinically significant reductions in fatigue at 3 months and sustained at 6 months Pain: Significant reduction in pain severity at 3 months and sustained at 6 months Depression: Improvement at 3 months was significant but small
24	Li 2014 China Randomised controlled trial	Adults on PD N = 135 Mean age: 56.3 ± 12.4 Sex (female): 56 (41.5%)	Hospital	I: Nurse‐led telephone support post‐discharge C: Routine discharge care Duration: 6 weeks	Omaha system	HRQoL: Kidney Disease Quality of Life Short Form (KDQoL‐SF) Complication control: the presence of oedema, the existence of peritonitis, catheter infections and weight gain Health service utilisation: data from hospital information system	No effect on total HRQoL, possible improvement in sleep, staff encouragement No difference in complication control Fewer clinic visits at 12 weeks
25	Mansouri 2020 Iran Randomised controlled trial	Kidney transplant recipients N = 80 Mean age: 39.47 (range 20 to 64 years) Sex (female): 23 (28.6%)	Hospital	I: Interactive multimedia (CD) C: Booklet educational method Duration: 2 months	Not reported	HRQoL: Quality of life questionnaire for kidney transplant patients (KTQ‐25)	The overall mean of HRQoL in both groups increased significantly
26	Nadort 2022 The Netherlands Randomised controlled trial	Adults on HD with increased levels of depression N = 190 Mean age: 64 ± 15 Sex (female): 73 (38%)	Dialysis centre	I: Internet‐based self‐help cognitive behavioural therapy C: Usual care Duration: 12 weeks	Not reported	Depressive symptoms: BDI‐II Anxiety: Beck Anxiety Inventory (BAI) HRQoL: Short Form‐12 Prevalence and impact of dialysis symptoms: Dialysis symptom index	No significant improvement in depressive symptoms, anxiety scores, dialysis symptoms, physical and mental components of HRQoL
27	Ong 2016 Canada Non‐randomised experimental study	Adults with stage 4 or 5 CKD N = 47 Mean age: 59.4 ± 14 Sex (female): 21 (44.7%)	Outpatient renal clinic	Smartphone‐based self‐management system Duration: 6 months	Not reported	Acceptability: adoption rate, adherence to recommended scheduled use, user satisfaction and feature usage Blood pressure: the automated sphygmomanometer Medications: unintentional medication discrepancies CKD‐related symptoms: number of alerts sent to the kidney care team and the proportion that required clinical intervention and instruction to change a behaviour CKD‐specific laboratory tests: blood tests	Blood pressure measured both in the clinic and at home fell from entry to exit, but no statistical significance High acceptance, Monthly adherence rates were mostly over 80% No drop‐off in interest over time The percentage of patients with one or more clinically relevant discrepancies was 80% at baseline and 72% at exit
28	Reilly‐Spong 2015 United States Randomised controlled trial	Adult kidney transplant candidates N = 63 Mean age: 52.8 ± 11.7 Sex (female): 36 (57%)	Home Hospital Transplant centre	I: telephone‐adopted mindfulness‐based stress reduction C: tSupport (a time and attention comparison condition using the workshop‐telephone format) Duration: 8 weeks	Not reported	Anxiety: State–Trait Anxiety Inventory (STAI) Depression: Centre for Epidemiologic Studies‐ Depression Insomnia: Pittsburgh Sleep Quality Index HRQoL: Short‐Form 12	High treatment satisfaction A feasible and acceptable intervention reported by participants Participants expected their intervention to be quite a bit or extremely useful for managing their health
29	Schick‐Makaroff 2014 Canada Cross‐sectional study	Adults on dialysis N = 56 Mean age: 66 ± 12 Sex (female): 21 (37%)	Outpatient dialysis clinics	Tablet computer Duration: one‐off	Not reported	Patient satisfaction: Participant's Level of Satisfaction questionnaire and open‐ended questions Time involved in administering HRQoL and symptom assessment	High satisfaction Time involved in administering HRQOL and symptom assessment: 1.15 min (SD = 0.41) for Level of Satisfaction; 2.55 min (SD = 1.04) for ESAS; 9.56 min (SD = 2.03) for HRQoL
30	Schick‐Makaroff 2015 Canada Qualitative research	Adults on dialysis N = 56 Mean age: 66 ± 12 Sex (female): 21 (37%)	Outpatient dialysis clinics	Electronic format of patient‐reported outcomes (ePROs) using tablet computers Duration: one‐off	Not reported	Issues emerged in a study that incorporated ePROs in clinical settings: qualitative interview	Logistics for the use of the technology Technology Security Institutional and financial support Elements of electronic design
31	Tangaro 2016 Italy Non‐randomised experimental study	Adults on HD N = 10 Mean age: 60.1 ± 10.9 Sex (female): 3 (33.3%)	Hospital	Digital self‐management program (My kidneys and Me) Duration: 6 weeks	Not reported	Accurate classification performance of system: heart rate, blood pressure and weight before and after the dialysis	Sensitive in the identification of nonsymptomatic sessions and the specificity in the identification of symptomatic sessions
32	Tarca 2024 Australia Longitudinal study	Adult on PD N = 48 Mean age: 61 ± 13.5 Sex (female): 35%	Home	Ecological Momentary Assessment Mobile Software Duration: 7 days	Not reported	Fatigue: The Visual Analogue Scale to Evaluate Fatigue Severity (VAS‐F) Mood: The Visual Analogue Mood Scale Physical activity levels: a wrist‐worn Feasibility and acceptability: a study‐made survey	Significant improvements in fatigue, energy No significant change in mood The overall adherence across the 7‐day period was 73% Participants had a positive experience and found the app acceptable, easy, quick and simple to use
33	Thompson 2021 Canada Mixed method	Adults receiving in‐centre HD N = 77 Mean age: 61 (range from 35 to 67) Sex (female): 30 (39%)	Outpatient centres	Web app Duration: 8 weeks	Not reported	Usability: satisfaction scale semi‐structured interview Quality of communication: Communication assessment tool (CAT‐14)	The lower proportion of patients in the web app group submitted at least one concern compared to the paper form (56.7% vs. 87.9%) Main themes explained usability: (1) influence on the encounter, (2) contextual factors influencing update and (3) the user experience High satisfaction with the tools in both groups Higher satisfaction with the information provided by the nephrologist compared to the paper group
34	Viecelli 2022 Australia Qualitative research	Adults on HD N = 12 Mean age: 69.5 ± 13.41 Sex (female): 5 (42%)	HD units	ePROMs (electronic patient‐reported outcome measures) Duration: 6 months	Not reported	Perspectives and experiences of patient participants, nephrologist and nurses regarding the acceptability and feasibility of ePROM: semi‐structured interview (by telephone or face‐to‐face) and focus group (video conference or face‐to‐face)	Benefits: enabling efficient, systematic and multidisciplinary patient‐centred care Concerns: experiencing limited data and symptom management options): Enablers: requiring familiarity with technology and processes Barriers
35	Wetmore 2023 United States Retrospective study	Adults with CKD stages 4 or 5 N = 728 Mean age: 68 ± 13 Sex (female): 320 (44%)	Hospital	Electronic health record (Optum deidentified Integrated Claims—Clinical dataset) Duration: NA	Not reported	Changes of recorded symptoms	During the 6‐month period before dialysis, 83% had pain, 68% had fatigue or weakness, 54% had shortness of breath, 51% had nausea or vomiting, 27% had difficulty with concentration The odds of five key symptoms (pain, fatigue/weakness, shortness of breath, nausea/vomiting and difficulty concentrating) increased over time in the 6 months before dialysis initiation, decreased immediately on initiation and remained unchanged in the 6 months thereafter
36	ZareMoayedi 2018 Iran Co‐design	recipients of kidney transplant recipients for > 6 months with stable physical condition N = 10 Mean age: Not specified Sex (female): Not specified	Transplantation Centre	Patient decision aid Duration: NA	Chronic illness management care pattern	Usability: System Usability Scale	The mean score of the system's usability assessment rated and patients were 91 out of 100 The users satisfied with the application in all aspects The application was evaluated at an excellent level
37	Zhao 2020 China Non‐randomised experimental study	Adults with CKD N = 278 Mean age: 41.1 ± 14.7 in active response patients 41.2 ± 17.0 in no active response patients Sex (female): 131 (47.1%)	Outpatient clinic	I: Clipboard of Medicine app C: The old online following system Duration: 6 weeks	Not reported	Psychological status of patients: Impact of Event Scale‐Revised Psychological distress	Online telemedicine care program provided a rapid triage function, effective CKD disease management and potentially essential psychological support During follow‐up, eGFR of patients in both groups declined, but eGFR of the control group showed a statistically significant decline Participants showed active responses to the program 97.4% of patients believed the program was helpful
38	Zhou 2020 Qatar Randomised controlled trial	Aged 50 years or older with diabetes receiving HD N = 73 Mean age: 62.7 ± 6.8 (IG) 66.5 ± 10.0 (CG) Sex (female): 40 (54.8%)	Dialysis centre	I: Exergame (a gamified non‐weight‐bearing intradialytic exercise program) C: Nurse‐supervised intradialytic exercise Duration: 4 weeks	Not reported	Depression: Centre for Epidemiologic Studies Depression (CES‐D) Scale User experience: a revised technology acceptance model (TAM)	The number of participants at risk for clinical depression reduced in the two groups Significant reduction in depression scores for both groups, no between‐group difference The IG expressed a positive experience, including fun, safety and helpfulness of sensor feedback

Abbreviations: C, comparator; CBT, cognitive behavioural therapy; CG, control group; CKD, chronic kidney disease; eGFR, estimated glomerular filtration rate; ePROM, electronic patient‐reported outcome measures; HD, haemodialysis; HRQoL, health‐related quality of life; I, intervention; ICD, International Classification of Diseases; IG, intervention group; NA, Not applicable; PD, peritoneal dialysis; VR, virtual reality.

3.2. Quality of Studies

Critical appraisal of included studies with MMAT found that 14 met 100% of the quality assessment criteria (Aiyegbusi et al. 2018; Anderson et al. 2021; Brys et al. 2020, 2021; Chae and Kim 2024; Dano et al. 2023; Grove et al. 2024; Hernandez et al. 2021; Hernandez et al. 2018; Hussain et al. 2022; Jhamb, Steel, et al. 2023; Schick‐Makaroff and Molzahn 2015; Thompson et al. 2021; Viecelli et al. 2022). Eleven studies met 80% of the criteria (Chan et al. 2016; Dey et al. 2016; Dingwall et al. 2021; Flythe et al. 2020; Gabbard et al. 2021; Jakubowski et al. 2020; Jhamb, Devaraj, et al. 2023; Mansouri et al. 2020; Ong et al. 2016; Reilly‐Spong et al. 2015; Tarca et al. 2024), 6 fulfilled 60% (Chan et al. 2020; Li et al. 2014; Nadort et al. 2022; Schick‐Makaroff and Molzahn 2014; Wetmore et al. 2024; Zhao et al. 2020) and the remaining 5 met 20%–40% of the quality assessment criteria (Doyle et al. 2019; Finkelstein et al. 2021; Gross et al. 2017; Tangaro et al. 2016; Zhou et al. 2020). Most quantitative non‐randomised controlled trials did not report confounders in design and analysis, while five randomised controlled trials lacked blinding of outcome assessors. Two quality assessment criteria, relevant sampling strategy and proper measurements, were lacking in reporting in four quantitative descriptive studies. The qualitative domains in qualitative studies generally demonstrated higher quality than quantitative studies. In the appraisal of the two co‐designed studies, one met more than 80% of the criteria (Donald et al. 2021), and another study fulfilled 60% of the quality assessment criteria (Zare Moayedi et al. 2018). Results for the quality appraisal can be found in Tables S3 and S4.

3.3. Technology Formats and Functions of eHealth Solutions

The eHealth solutions were categorised into mobile health (n = 17), telehealth (n = 6), web apps (n = 5), electronic health records (n = 2), virtual reality (n = 1) and multiple components (n = 4) that combined various technologies (e.g., combination of computer and wearable sensors, smartphone with wearable devices) and others (n = 3) (see Table 2). Smartphone apps (n = 7) and tablet apps (n = 10) are two types of mobile health applications. Six studies (15.8%) used telehealth systems (video, telephone calls and online conferences) to monitor patients' symptoms. In addition, 6 studies provided online cognitive and behavioural skills lessons or information sessions about identifying common concerns/symptoms and addressing them. One study reported virtual reality's effectiveness in promoting intradialytic exercise (Hernandez et al. 2021). Four studies involved at least two types of technologies (Aiyegbusi et al. 2018; Ong et al. 2016; Tarca et al. 2024; Zhou et al. 2020). For example, Zhou et al. provided a gamified non‐weight‐bearing intradialytic exercise intervention via computer (Zhou et al. 2020). Patients were then virtually supervised based on interactive feedback collected from wearable sensors attached to the lower extremities (Zhou et al. 2020). In another study, data on fatigue and mood was collected via smartphone‐based software; researchers also measured patients' physical activity levels with a wrist‐worn device (Tarca et al. 2024). The main functions and technology descriptions are provided in Table S5.

TABLE 2.

Classification of eHealth solutions.

Category of eHealth a	Study ID	Classification b
		Data recording	Consultation	Behavioural counselling	Communication	Education	Self‐monitoring	Information	Reminders/Alerts	Other
Electronic health record	Chan 2020									√
	Wetmore 2023	✓
Telehealth	Jakubowski 2020			✓		✓		✓
	Jhamb 2023				✓	✓
	Jhamb 2023			✓		✓
	Li 2014			✓		✓		✓
	Reilly‐Spong 2015			✓		✓
	Tangaro 2016						✓		✓
Mobile health	Brys 2020	✓					✓		✓
	Brys 2021	✓					✓		✓
	Dano 2023						✓		✓
	Dey 2016	✓					✓		✓
	Chae 2024	✓		✓			✓	✓	✓	✓
	Dingwall 2021							✓		✓
	Doyle 2019	✓					✓	✓	✓
	Finkelstein 2021						✓
	Flythe 2020						✓		✓
	Gross 2017			✓		✓
	Gabbard 2021	✓						✓	✓
	Hussain 2022						✓
	Viecelli 2022	✓					✓
	Schick‐Makaroff 2014	✓					✓
	Schick‐Makaroff 2015	✓					✓
	ZareMoayedi 2018	✓					✓		✓	✓
	Zhao 2020		✓			✓	✓		✓
Web app	Chan 2016	✓		✓		✓		✓
	Donald 2021					✓	✓	✓
	Hernandez 2018					✓
	Nadort 2022					✓
	Thompson 2021	✓					✓
Virtual reality	Hernandez 2021					✓
Multiple components	Aiyegbusi 2018						✓
	Ong 2016	✓			✓		✓	✓	✓
	Tarca 2024	✓					✓
	Zhou 2020						✓			✓
Others	Anderson 2021						✓
	Grove 2024						✓
	Mansouri 2020					✓		✓

^a Category of eHealth based on a study by Wang and colleagues (2).

^b Descriptions of eHealth symptom assessment and monitoring adapted from a study by Shen and colleagues (26).

Most eHealth solutions contain various functions to deliver symptom assessment and monitoring. Self‐monitoring was the most common function offered by current eHealth solutions (n = 22). Adults with CKD were able to monitor their symptoms using different approaches, for instance, by answering questionnaires on tablet or web‐based platforms (Flythe et al. 2020; Gabbard et al. 2021), while health providers used telephone and/or video calls to assess and monitor symptoms directly (Li et al. 2014). Figure 2 depicts the number of studies for each eHealth classification.

FIGURE 2.

Classifications of eHealth solutions. [Colour figure can be viewed at wileyonlinelibrary.com]

Besides self‐monitoring symptoms, many eHealth solutions studies integrated additional functions, such as data recording (n = 14), providing education (n = 13) and information (n = 10) and reminders or alerts (n = 10). Information about dialysis, symptoms and health, such as fluid intake, foods, exercise and medications, was recorded in a dashboard where healthcare providers and patients could review this information (Brys et al. 2020, 2021; Chae and Kim 2024). Different types of training to manage CKD symptoms were provided, and these included intradialytic exercise or cognitive behavioural therapy (Chan et al. 2016; Gross et al. 2017; Hernandez et al. 2018; Jakubowski et al. 2020; Jhamb, Steel, et al. 2023; Nadort et al. 2022). This training provided information about the disease and how to manage common symptoms, medications and diet (Dingwall et al. 2021; Donald et al. 2021; Doyle et al. 2019; Reilly‐Spong et al. 2015). In two studies, adults with CKD received text message reminders to self‐assess for symptoms or to increase the frequency of symptom reporting (Chae and Kim 2024; Zare Moayedi et al. 2018). In two other studies, they received an auditory signal from their smartphones to remind them to complete a real‐time symptom self‐report (Brys et al. 2020, 2021). If participants showed any warning signs (e.g., if blood pressure was higher than 180/110 mmHg or worsening symptoms), then an alert was sent. They then received a follow‐up phone call or text message from their healthcare provider team to advise them to visit the hospital for a further in‐person assessment (Flythe et al. 2020; Ong et al. 2016; Zare Moayedi et al. 2018). Healthcare providers could receive an email from the system to inform them about a patient's symptoms that need attention (Flythe et al. 2020).

Only 10 studies reported how privacy and data security were incorporated. In three studies, video chats or conferences were provided via a secure Wi‐Fi hotspot to maintain data security (Jakubowski et al. 2020; Jhamb, Devaraj, et al. 2023; Jhamb, Steel, et al. 2023). Three studies have used devices to collect patients' data connecting to a secure encryption network (Aiyegbusi et al. 2018; Gabbard et al. 2021; Ong et al. 2016). Exported data was then stored on secure servers in two studies (Schick‐Makaroff and Molzahn 2014, 2015). Some web‐based interventions required the users to create an account and log in with a unique username and password (Dey et al. 2016; Hernandez et al. 2018).

3.4. Study Outcomes

eHealth studies reported outcomes for symptoms, HRQoL, user satisfaction and acceptance, usability and feasibility and challenges and barriers. Table 3 presents a summary of patient‐related outcomes. The most frequent symptoms that were measured were depression (n = 13), fatigue (n = 11), anxiety (n = 7) and pain (n = 7). Standardised tools used were the Fatigue Severity Scale, Hospital Anxiety and Depression Scale, Patient Health Questionnaire‐9 item, Generalised Anxiety Disorder‐7 item, Patient Health Questionnaire, Kessler Distress Scale and Brief Pain Inventory. Following the introduction of the individual eHealth solutions, there were reduced levels of depression (n = 7), anxiety (n = 4), fatigue (n = 3) and pain (n = 1). Significant reductions in fatigue, pain, and depression were reported in one study (Jhamb, Steel, et al. 2023). In another study delivered via a mobile app, a significant decrease in anxiety and depression was reported (Dingwall et al. 2021). Thirteen studies measured the HRQoL, although different instruments were used (Kidney Disease Quality of Life‐36, EuroQoL and Health Survey SF‐12). Four studies showed a statistically significant improvement in HRQoL after introducing an eHealth intervention (Chan et al. 2016; Gross et al. 2017; Jakubowski et al. 2020; Mansouri et al. 2020). The remaining studies reported no significant improvement in HRQoL. A mapping of included studies categorised by eHealth technology and study outcomes is found in Table S6.

TABLE 3.

Summary of symptom and health‐related quality of life outcomes.

Outcome category	Total number of studies in each subcategory	Effect
		Positive effect n (%)	Mixed effect n (%)	No effect n (%)
Depression	13	7 (53.4)	0	6 (46.6)
Fatigue	11	3 (27.3)	0	8 (72.7)
Anxiety	7	3 (42.3)	1 (14.3)	3 (42.3)
Pain	7	1 (14.3)	0	6 (85.7)
Sleep quality	4	0	0	4 (100)
Nausea	3	1 (33.3)	0	2 (66.7)
Physical activity	2	1 (50.0)	0	1 (50.0)
Psychological distress	2	1 (50.0)	1 (50.0)	0
Health‐related quality of life	13	4 (30.7)	3 (23.1)	6 (49.2)

Adults with CKD reported positive experiences and perceptions of using eHealth solutions to assess and monitor their symptoms in six studies (Aiyegbusi et al. 2018; Dey et al. 2016; Jhamb, Devaraj, et al. 2023; Reilly‐Spong et al. 2015; Schick‐Makaroff and Molzahn 2014; Thompson et al. 2021). Overall, eHealth solutions were rated as easy to use and user‐friendly. Qualitative feedback from patients showed that the Ecological Momentary Assessment Mobile Software was easy, quick and simple to use (Tarca et al. 2024) and helped them better understand the importance of symptom reporting and controlling their health‐related problems (Anderson et al. 2021; Flythe et al. 2020). A web app where patients could document their concerns made medical practitioners more prepared for healthcare appointments because the important issues were known (Thompson et al. 2021). Kidney healthcare providers agreed that electronic patient‐reported outcome measures raised awareness about symptoms and improved communication about symptoms with patients (Flythe et al. 2020).

Even though positive experiences have been reported, adults with CKD were still faced with challenges and barriers to using eHealth solutions to assess and monitor their symptoms. The most frequent challenge was unfamiliarity with using technology (Aiyegbusi et al. 2018; Viecelli et al. 2022). Patients also reported that it was sometimes inconvenient to log in to the app (Thompson et al. 2021). Patients were worried about the lack of connection with their kidney healthcare providers and that face‐to‐face consultations would be replaced (Thompson et al. 2021; Viecelli et al. 2022). Healthcare providers indicated concerns about potentially missing acute symptoms or a time lag of feedback for patients. They identified physical limitations and low educational attainment as barriers for patients, especially older patients, to report their symptoms on eHealth technologies such as tablets (Viecelli et al. 2022).

4. Discussion

This review identified 38 studies, all published during the last 10 years, that indicated a growing emphasis on using eHealth solutions to facilitate symptom assessment and monitoring for adults with CKD. Interestingly, most studies were published between 2020 and 2024, during and after the COVID‐19 pandemic. This period aligns with a transformation from traditional to remote modes of healthcare provision as technology‐based advances were rapidly developed and implemented during social isolation periods (Mann et al. 2020).

The current review identified that eHealth symptom assessment and monitoring were used with different frequencies. The eHealth solutions that aimed to screen or assess symptoms before a scheduled clinic appointment were completed via a tablet in waiting rooms (Schick‐Makaroff and Molzahn 2015). The collected data would then be used during real‐time consultations with members of the multidisciplinary renal team. The single request of patient‐reported symptom monitoring was implemented to replace the typical waiting room and screening symptoms and supportive care needs among patients with cancer (Garcia et al. 2019; Girgis et al. 2017). With eHealth aimed at monitoring symptoms remotely for people with CKD living at home, these tools could be used daily or weekly and then nurses could check the data remotely (Brys et al. 2020, 2021; Dey et al. 2016). Another included study assessing the feasibility of tablet‐based patient‐reported symptoms of adults on haemodialysis concluded that the optimal administration frequency of remote symptom monitoring in their practice was twice a month (Flythe et al. 2020). The frequency of reporting CKD symptoms remotely varied daily and monthly depending on the functions available and the primary purpose of capturing patient symptom data. This finding aligns with the administration of eHealth patient‐reported symptom systems in other fields, such as cancer and rheumatology (Gandrup et al. 2020). The required frequency of reporting symptoms or interacting with eHealth technology is a key consideration during either the development of an intervention or its routine implementation in practice. Involving target users of eHealth solutions early in the design process is crucial and may help determine the appropriate reporting frequency of symptoms based on the patient's preferences and needs (Tran et al. 2024).

Previous research has shown that socio‐demographic factors such as older age, less experience using technology, lower education level and income are associated with lower digital health literacy (Arcury et al. 2020; Estrela et al. 2023). Individuals with limited eHealth skills tend to be less engaged with digital health solutions to facilitate their health management (Cheng et al. 2022). However, many existing eHealth studies did not consider participant information regarding digital health literacy, potentially excluding those with limited digital health literacy from benefiting from these eHealth solutions. Future studies should investigate their participants' digital health literacy levels and incorporate strategies to engage them effectively. Providing appropriate training on how to use eHealth interventions and arranging technical support throughout the study period is needed. Additionally, new eHealth applications should be designed to be easy to use and adaptable to varying digital health literacy levels. Involving participants, healthcare providers and stakeholders in a co‐designed process should be considered in designing eHealth solutions to ensure that end users' perspectives and experiences are paramount (Graham‐Brown et al. 2022).

If an eHealth intervention is difficult to engage with or time‐consuming, then its users lose interest in and might stop using the application (Eysenbach 2005). To maintain the high usage of eHealth solutions, future interventions should avoid the additional burden that creates usage discontinuation. Allocating a reasonable amount of time to complete tasks among participants is necessary. Functions like reminders to complete tasks or motivate users should be embedded in the eHealth solutions development process.

In this review, several intervention studies showed improved CKD symptoms and/or HRQoL when using eHealth solutions. Similarly, evidence about the effectiveness of eHealth solutions has also been found in other health conditions. For instance, patients with metastatic cancer of any type receiving chemotherapy after using weekly electronic patient‐reported outcomes to monitor symptoms for 3 months reported improvement in physical function, symptom control, and HRQoL (Basch et al. 2022). In another study, adults receiving chemotherapy for breast or colorectal cancer reported significant reductions in psychological and physical symptoms after using a real‐time remote symptom monitoring system (Maguire et al. 2021). Monitoring symptoms via mobile apps increased understanding of their symptoms, assisted with adjusting their health behaviours and increased treatment adherence (Maguire et al. 2021; Zhang et al. 2024). Future eHealth research in CKD can learn lessons from cancer studies in eHealth symptom assessment and monitoring.

The eHealth solutions used for adults with CKD reflected diverse technologies and functions. The majority were mobile apps and computer tablets. In the context of global growth in mobile technology, facilitating the development and implementation of smartphone‐based applications seems reasonable for enhancing CKD symptom management. Those with CKD could use these eHealth interventions for symptom evaluation to assess and monitor their symptoms, learn how to manage them and communicate with healthcare providers from home.

This review has several strengths and limitations. The review's search strategy was comprehensive, and MeSH terms and keywords of CKD and eHealth were combined. Seven databases were searched to minimise the possibilities of publication bias, but unpublished eHealth initiatives and studies not published in English may have been missed. Of the included studies, 24 had minor to major methodological limitations, so this review's findings should be interpreted with caution. Due to the variation between eHealth solutions used, study outcomes and measures, a meta‐analysis of any outcomes or comparing study outcomes among different groups was not possible. There is a need for further robust experimental studies to inform evidence for future practice.

5. Implications for Nursing Practice

eHealth has an important role in CKD management, and there are implications for nursing practice and healthcare delivery. For instance, having these supportive solutions could enhance efficiency and workflow, which could then afford nurses more time to focus on patient care. These could also improve both on‐site and remote patient monitoring, enhance nurse–patient interactions and communication and increase collaboration among the multidisciplinary kidney team to deliver healthcare (Forde‐Johnston et al. 2023; Lottonen et al. 2024). Nurses can be hesitant to use eHealth interventions due to time barriers, lack of technology skills, readily available (and contemporary) equipment, concerns with security and a lack of high‐quality and reliable internet (Anderson et al. 2021; Flythe et al. 2020). Nurses, however, need to be prepared to practice in an increasingly digital health technology environment. They will require both initial and continuing education about eHealth to acquire the confidence and abilities to work in a rapidly evolving digital health environment. Education and having suitable digital technologies accessible will enable nurses to effectively integrate eHealth technologies into nursing practice, which is then more likely to improve patient care and health outcomes through efficient work practices. Nurses also have an important role in creating and implementing new digital health products and ensuring there are sound policies for using eHealth technologies for data security.

6. Conclusion

While robust evidence about the effectiveness of eHealth symptom assessment and monitoring solutions to improve symptoms and patient‐related outcomes in CKD is still limited, these solutions enable the earlier introduction of symptom management strategies—particularly for people when at home. Existing eHealth solutions appear acceptable and feasible for adults with CKD and healthcare providers. These findings suggest that eHealth could be an effective option for remote CKD care. Future solutions should be co‐designed with adults with CKD so as to ensure accessibility for those with limited digital health literacy.

Author Contributions

All authors contributed to the manuscript's conceptualisation, methodology, formal analysis, writing, review, and editing. All authors have read and agreed to the published version of the manuscript.

Conflicts of Interest

The authors declare no conflicts of interest.

Supporting information

Data S1.

Data S2.

Data Availability Statement

The data that support the findings of this study are available from the corresponding author upon reasonable request.