Remote home management for chronic kidney disease: A systematic review

Abstract

Background

Remote home management is a new healthcare model that uses information technology to enhance patients' self-management of disease in a home setting. This study is designed to identify the effects of remote home management on patients with chronic kidney disease (CKD).

Methods

A comprehensive search of PubMed, MEDLINE, Embase, and the Cochrane Central Register of Controlled Trials was performed in January 2015. The reference listings of the included articles in this review were also manually examined. Randomized controlled trials (RCTs) designed to evaluate the effects of remote home management on patients with CKD were included.

Results

Eight trials were identified. The results of this study suggest that the quality of life (QOL) enabled by remote home management was higher than typical care in certain dimensions. However, the effects of remote home management on blood pressure (BP) remain inconclusive. The studies that assessed health service utilization demonstrated a significant decrease in hospital readmission, emergency room visits, and number of days in the hospital. Another favorable result of this study is that regardless of their gender, age or nationality, patients tend to comply with remote home management programs and the use of related technologies.

Conclusions

The available data indicate that remote home management may be a novel and effective disease management strategy for improving CKD patients' QOL and influencing their attitudes and behaviors. And, relatively little is known about BP and cost-effectiveness, so future research should focus on these two aspects for the entire population of patients with CKD.

Keywords

Chronic kidney disease remote home management quality of life blood pressure

Backgrounds

Chronic kidney disease (CKD) is a common long-term condition that is frequently associated with a high prevalence and very high health costs.¹ There are more than 70 million patients with CKD worldwide and, according to estimates, the prevalence of CKD will increase as the aging population increases dramatically. However, although numerous advances have been made in the diagnosis and medical care of patients with CKD, significant improvements in patients' clinical conditions and long-term survival have not been achieved. In addition, the burden of treating and managing such patients is exacerbated by limited healthcare resources.² A serious shortage of healthcare personnel exists in many areas, especially in developing countries, and there is no realistic prospect that this situation will be resolved in the short term.³ Therefore, the management of patients with CKD requires a fundamental change. Remote home management, using information technology to enhance patients’ self-management of disease in a home setting, may help patients with CKD to understand their conditions and improve their health status. Although previous reviews have suggested that this new healthcare delivery model is effective in treating hypertension, heart failure, diabetes, and other chronic illnesses,^4–6 studies of remote home management in patients with CKD have been limited and are controversial. Therefore, the objective of the present paper was to perform a systematic review of published evidence on the value of remote home management for patients with CKD and provide a solid foundation for medical decision-making and healthcare reform.

Materials and methods

Literature search

We conducted a systematic review of the available literature adhering to the QUORUM guidelines and performed meta-analyses of intervention studies.⁷ PubMed, MEDLINE, Embase, and the Cochrane Central Register of Controlled Trials (CENTRAL) were searched in January 2015 by professional document retrieval personnel from the Xiang-Ya Medical Library of Central South University using the following search terms: ‘telemedicine,’ ‘telehealth,’ ‘telemonitoring,’ ‘ehealth,’ ‘mobile health,’ ‘home health care,’ ‘home care services,’ ‘home-base,’ ‘blood pressure measurement,’ ‘self measurement,’ ‘renal insufficiency,’ ‘chronic,’ ‘hypertension,’ ‘high blood pressure,’ ‘renal,’ ‘kidney,’ and ‘controlled clinical trial.’ Reference listings of relevant meta-analyses and reviews were manually examined. There were neither language nor data restrictions. All of the potentially relevant studies were examined in full.

Selection criteria

Randomized controlled trials (RCTs) that investigated the effect of remote home management on patients with CKD were included in the study. The duration of the intervention had to be at least four weeks to achieve clinically meaningful outcomes. Only adult patients (≥18 years of age) who satisfied the diagnosis criteria of CKD were eligible to participate in the study. Additionally, we used the latest report from repeat studies of the same or similar content. We operationally defined remote home management as any strategy of telemedicine application in CKD patients in which there was a direct or indirect personalized feedback information from a healthcare practitioner to the patient about the forwarded clinical data, with a traditional care group not using remote home management. The strategies of telemedicine application included in this review were computerized systems for information exchange, video conferencing, and exchange of information via telephone or other mobile devices, short message service, or through the Internet.⁸

Quality assessment

The methodological quality and risk of bias were evaluated by two reviewers in accordance with the standards of the Cochrane Collaboration.⁹ The items were as follows: random sequence generation, allocation concealment, blinding of participants and personnel, blinding of outcome assessment, incomplete outcome data, selective reporting, and other biases, such as funding sources. All of the items were assigned a value of ‘low risk,' ‘high risk,' or ‘unclear.' Moreover, the intention-to-treat analysis (ITT) principle was used to evaluate the integrity of the outcome data. The GRADE¹⁰ system was used to grade the quality of evidence and the strength of the recommendations. This system evaluates five primary domains for each outcome: limitations of the study design and execution, inconsistency, indirectness, imprecision of results, and publication bias.

Data extraction

Two reviewers who focused on CKD research extracted data from the included studies based on methods (allocation, blinding, and follow-up duration), participants (diagnosis, country, randomized number, age, gender, ethnicity, inclusion criteria, and exclusion criteria), interventions (intervention duration and process of intervention) and outcomes (quality of life; change from baseline in mean BP and interdialytic weight; patient’s attitude; cost and healthcare service utilization including readmission, emergency room visits, and number of days in the hospital). Correspondence with the authors of the included studies was initiated as necessary. To determine the change in BP and quality of life (QOL) for remote home management compared to typical care, the difference in the mean values, with 95% confidence intervals (CIs), was calculated. Data from studies that expressed outcomes in terms of p and F values, rather than mean and standard deviation values, were transformed to estimates of mean and standard deviation values according to the Cochrane handbook.⁹ If there were discrepancies, all of the authors reached a consensus by discussion. All of the obtained data were carefully examined for accuracy.

Statistical analysis

The data from each included trial were analyzed using Review Manager (RevMan, Version 5.3, Copenhagen: The Nordic Cochrane Centre, The Cochrane Collaboration, 2014). The quantitative analysis was based on ITT principles as much as possible. BP reductions and the score of QOL were calculated before data pooling and were subsequently combined. Mild, moderate, and severe heterogeneity were defined using I² values of 25%, 50%, and 75%, respectively. If there was significant heterogeneity, the random effects model was used. An evaluation of publication bias was planned if we had more than 10 studies, but it was not assessed because of the small number of studies.¹¹ Values of p ≤ 0.05 were considered to be statistically significant.

Results

Flow of included studies

A total of 2734 studies were identified by searching PubMed, MEDLINE, Embase, and the Cochrane Central Register of Controlled Trials. After removing duplicate studies, 2334 abstracts were screened. A total of 17 relevant full-text articles were assessed for eligibility, of which eight trials fulfilled the inclusion criteria^12–19 (Figure 1).

Figure 1.

Flow chart for eligible studies.

Study characteristics

Eight trials, which provided data on 648 patients, were included in the systematic review. The numbers of participants were 99, 120, 160, 47, 21, 57, 44, and 100. The average age of the patients ranged from 46–68 years. Males tended to be more highly represented than females. No trials reported ethnicity. One study was conducted in Germany,¹⁷ one in Spain¹² two in China,^13,19 and the remainder of the studies were conducted in the USA.^14–16,18 In all except one study,¹⁸ the patients were receiving replacement therapy including hemodialysis, peritoneal dialysis and renal transplantation. Five^{13,15,17–19} of the eight studies provided intervention via telephone, either in the form of a call or a text message; three studies^12,14,16 provided intervention via television or video-conferencing. The design, duration and set-up of the trials were different, representing substantial heterogeneity. Three trials^15,17,18 reported BP changes from baseline to endpoint, three trials⁴ reported changes in QOL. Four trials^12,14,16,19 reported that the healthcare service utilization included emergency department visits, readmission, and the number of days in the hospital; among them, two trials^12,14 reported the cost of intervention. Two trials^15,18 reported the patients’ attitude. The data for QOL, BP, and their standard error were obtained from tables; however, one study did not provide the mean SD values for BP (Table 1).

Table 1.

Baseline characteristics of included studies (by first author and year).

	Gallar, 2007^1 2	Chow, 2010^1 3	Berman, 2011^1 4	McGillicuddy, 2013¹⁵	Minatodani, 2013¹⁶	Neumann, 2013^1 7	Rifkin, 2013^1 8	Zhai, 2014^1 9
Country	USA	China, Hong Kong	USA	USA	USA	Germany	USA	China
Design	Randomized Non-blinded	Randomized Non-blinded	Randomized Non-blinded	Randomized Non-blinded	Randomized Non-blinded	Randomized Non-blinded	Randomized Non-blinded	Randomized Non-blinded
Duration	8 months	6 weeks	21 months	3 months	3 years	3 months	6 months	3 months
Description of study population	Patients undergoing peritoneal dialysis	Chronic kidney disease undergoing peritoneal dialysis	High-risk dialysis patients	Renal transplant recipients	End-stage renal failure requiring hemodialysis	End-stage renal failure requiring hemodialysis	Veterans with stage 3 or greater chronic kidney disease and uncontrolled hypertension	Chronic kidney disease undergoing peritoneal dialysis
No. of patients	57	100	44	21	99	120	47	160
Men, n (%)	15 (60%)	NR	26 (59%)	NR	NR	61 (51%)	NR	79 (58%)
Age (years)	46.3	57	NR	NR	60	≥60	≤50	55
Interventions	Patients received alternately a monthly teleconsultation through television set.	A standardized 6-week nurse-initiated telephone follow-up regi men	Remote technology (video-conferencing) with RCN	A smart phone that received and transmitted encrypted physiological data and delivered reminders to measure BP using text messaging	Received home monitoring via remote technology (video conferencing) with RCN oversight	Standard care supplied with telemetric weight monitoring which can sent the parameters to mobile phone.	Physicians or pharmacist called to discuss the readings, provide counseling, or adjust medications as indicated by telephone	A standardized 6-week post-discharge nurse-led telephone support intervention
Outcomes	Hospitalization rate, cost	QOL (KDQL-SF)	Health outcome (hospitalizations, ER visits, number of days hospitalized), cost, QOL	Acceptability, adherence to the protocols medication adherence, BP	Health resource outcome measures (hospitalizations, ER visits, number of days hospitalized), Economic analysis, Remote care nurse–patient contact	IWG, the average ultra-filtration; BP	Data exchange, device acceptability, BP	QOL (KDQL-SF), blood chemistry, complication control, readmission, clinic visit rates

BP: blood pressure; ER: emergency room; IWG: inter-dialytic weight gain; KDQL-SF: Kidney Disease Quality of Life Short Form; NR: not reported; QOL: quality of life; RCN: remote care nurse.

Ten trials^20–29 examining the effect of remote home management for patients with CKD were excluded. The reasons for exclusion are reported in Table 2.

Table 2.

Characteristics of excluded studies.

Study, first author, year	Reason for exclusion
Daelemans, 2014²⁰	Self-control design
Aberger, 2014²¹	Self-control design
Scherpiber-de Haan, 2013²²	Intervention (family physician vs nephrologist) did not meet inclusion criteria
Bernstein, 2010²³	Intervention (remote full-care hemodialysis units and without onsite nephrologist vs with on site nephrologists) did not meet inclusion criteria
Becker, 2010²⁴	Self-control design
Michael, 2009²⁵	This study is not a controlled trial
Schulz, 2007²⁶	The data of this study is repeat analysis by “Neumann 2013”
Nakamoto, 2007²⁷	Self-control design
Nakamoto, 2004²⁸	Self-control design
Cargill, 2003²⁹	The patients of this study included children

Risk of bias in the included studies

All of the trials were randomized; however, only two trials^13,19 described the generation of random sequencing. Only one trial¹⁸ described the concealment of allocation. None of the trials were double blinded, as determined by the nature of the intervention. Five trials^{13–15,18,19} had incomplete outcome data, which might have influenced the results for QOL and BP. In addition, none of the studies were affected by selective reporting or other biases. Figures 2 and 3 illustrate the overall risks of bias detected in the 8 included trials.

Figure 2.

Risk of bias graph according to recommendations from the Cochrane Collaboration.

Figure 3.

Risk of bias summary according to recommendations from the Cochrane Collaboration.

Quality of life and utilization of healthcare services

Two of three trials,^13,19 according to the Kidney Disease Quality of Life Short Form (KDQL-SF) scale, confirmed a significant difference in certain dimensions of QOL. Indeed, patients in the remote home management group believed that they were receiving more staff encouragement at six weeks (p = 0.03) (Mean Difference (MD), 4.94; 95% CI, 0.42–9.46), and their pain was significantly improved at six and 12 weeks (p = 0.0009, 0.02). However, the other aspects of QOL did not show a significant difference. Sexual function and sleep exhibited significant heterogeneity at six weeks (I²= 90%, 59%); sexual function, quality of social interaction, sleep and patient satisfaction demonstrated significant heterogeneity at 12 weeks (I²= 64%, 85%, 71%, and 66%, respectively) (Tables 3 and 4). The other trial,¹⁴ which used the Short Form 36-Item Health Survey (SF-36) scale, a standard QOL instrument, were not included in the analysis because they did not report the actual QOL score values; thus, the result could not be pooled.

Table 3.

Forest plot of comparison: Remote home management vs usual care: quality of life (six weeks).

Outcome measures	MD	Relative (95% CI)	p Value	I²
Symptom/problem	0.52	−3.53–4.58	0.8	0
Effect of kidney disease	2.69	−1.46–6.85	0.2	0
Burden of kidney disease	0	−3.51–3.51	1	0
Work status	−0.46	−3.85–2.92	0.79	0
Cognitive function	1.87	−2.89–6.63	0.44	0
Quality of social interaction	−1.46	−5.76–2.83	0.5	20%
Sexual function	−2.8	−8.47–2.87	0.33	90%
Sleep	−1.19	−6.23–3.84	0.64	59%
Social support	−0.08	−4.66–4.50	0.97	0%
Staff encouragement	−1.26	−5.79–3.28	0.59	0%
Patient satisfaction	0.58	−3.14–4.30	0.76	0%
Physical functioning	−1.04	−5.36–3.29	0.64	0%
Role–physical	2.92	−1.65–7.49	0.21	42%
Pain	8.59	3.52,13.66	0.0009^a	0%
General health perception	2.03	−2.18–6.25	0.34	0%
Emotional wellbeing	0.46	−4.42–5.34	0.85	0%
Role-emotional	−0.63	−5.86–4.59	0.81	0%
Social function	3.22	−2.08–8.52	0.23	0%
Energy/fatigue	2.6	−2.40–7.60	0.31	0%
Overall health	1.59	−3.08–6.26	0.5	0%

CI: confidence interval; MD: mean difference.

Table 4.

Forest plot of comparison: Remote home management vs usual care: quality of life (12 weeks).

Outcome measures	MD	Relative (95% CI)	p Value	I²
Symptom/problem	−0.61	−4.53–3.31	0.76	0
Effect of kidney disease	2.8	−1.21–6.81	0.17	0
Burden of kidney disease	1.35	−2.26–4.95	0.46	0
Work status	−0.01	−3.37–3.36	1	0
Cognitive function	−1.23	−5.98–3.53	0.61	0
Quality of social interaction	−2.42	−6.71–1.88	0.27	64%
Sexual function	2	−2.79–6.79	0.41	85%
Sleep	2.68	−2.40–7.77	0.3	71%
Social support	−2.64	−7.04–2.12	0.29	0%
Staff encouragement	4.94	−0.42–9.46	0.03^a	0%
Patient satisfaction	0.72	−2.99–4.22	0.7	66%
Physical functioning	−3.1	−6.90–0.69	0.11	0%
Role-physical	0.07	−4.13–4.27	0.97	0%
Pain	0.28	1.17–11.39	0.02^a	0%
General health perception	1.03	−3.59–5.66	0.66	0%
Emotional wellbeing	−0.24	−4.99–4.51	0.92	0%
Role-emotional	0.75	−6.04–4.55	0.78	0%
Social function	3.22	−2.08–8.52	0.23	0%
Energy/fatigue	2.12	−2.98–7.22	0.41	0%
Overall health	−0.26	−5.19–4.67	0.92	0%

CI: confidence interval; MD: mean difference.

p < 0.05, for differences between groups.

Additionally, the effect of remote home management on the healthcare service utilization was reported in four studies, which demonstrated a significant decrease in hospital readmission, emergency room (ER) visits, and the number of days in the hospital. The two articles that performed cost analyses showed conflicting results, One study¹⁶ showed that the cost of remote home management was lower than traditional care management, whereas the other study¹² showed the opposite result.

Blood pressure (BP) and interdialytic weight

The analysis of the mean difference in BP from the trials showed that the remote home management group had an increased systolic blood pressure (SBP) by 4.89 mm Hg (95% CI, −2.13–11.91; p = 0.14) and a reduced diastolic blood pressure (DBP) by 0.17 mm Hg (95% CI, −2.64–2.30; p = 0.41). However, neither result reached statistical significance. Heterogeneity was observed among the trials (I²= 0%, 49%) (Figures 4 and 5). Moreover, although limited to small samples, studies involving patients requiring dialysis demonstrated the ability of remote home management to optimize interdialytic weight gain and reduce the ultra-filtration rate.

Figure 4.

Forest plot of comparison: remote home management vs usual care: systolic blood pressure (SBP). CI: confidence interval; SD: standard deviation.

Figure 5.

Forest plot of comparison: remote home management vs usual care: diastolic blood pressure (DBP). CI: confidence interval; SD: standard deviation.

Patients’ attitude

The impact of remote home management on patients’ attitude was consistent across the trials included in this review. In general, patients were willing to accept remote home management as a self-management approach and showed a positive attitude toward it. McGillcuddy et al.¹⁵ demonstrated that the acceptability of patients' participation was high (75%), and the intervention group reported high overall satisfaction with mobile phone-based programs (average score, 4.8/5 points; Likert scale: one means strongly disagree and five means strongly agree). Rifkin et al.¹⁸ showed a high-level satisfaction with wireless blood pressure monitoring, and 96% of the participants reported that they would like to continue using the device. Similarly, clinical physicians considered the device to be a highly acceptable intervention.

Publication bias

Our strategy employed a comprehensive search that included conference papers. Our reviews included eight RCTs, only five articles made a quantitative analysis. According to the Cochrane Handbook for Systematic Reviews⁹ and previous literature,³⁰ the test for a funnel plot only can be done when there are at least 10 studies included in a meta-analysis. So we were unable to employ a funnel plot to assess publication bias because of the small number of eligible studies. However, the results reported in the included RCTs were equivocal in favoring remote home management and typical care. Hence, there does not appear to be a publication bias in this field of interest.

Discussion

CKD is a worldwide public health problem that affects millions of people in developed and developing countries. In China alone, there are more than 119.5 million individuals with CKD.³¹ The increasing number of patients with CKD not only threatens public health but also substantially increases the nation’s financial burden. Studies have demonstrated that CKD is associated with increased hospitalization, cardiovascular disease and mortality. Moreover, CKD affects patients' psychological health, daily functioning, general well-being and social functioning, which are determinants of the patients' QOL.³² Lower scores of QOL are often associated with a higher risk of developing end-stage kidney disease and all-cause mortality.³³ Thus, there is great demand for patient-centered comprehensive management to improve clinical outcomes and maintain a desirable QOL. Recent studies have indicated that the appropriate comprehensive management of patients with CKD should not only provide proper medications, lifestyle instructions and relevant information regarding CKD treatment but also motivate the patients to accept the care.³⁴ Some evidence demonstrates^20,21 the beneficial effects of patient monitoring and timely feedback, focused on a prominent role of patients' self-management with the supervision and support of healthcare professionals, bringing into focus the advances in wearable device and information technology, which can be exploited to improve CKD management. Remote home management can be a strategy for closer monitoring, timely feedback and appropriate intervention to not only achieve better clinical outcomes but also to increase participation and improve QOL.

Quality of life and healthcare service utilization

The results showed that the QOL with remote home management was higher than the QOL with traditional care in certain dimensions of the KDQL-SF which is the specific instrument that focuses on problems associated with CKD.³⁵ Indeed, the study group patients were experiencing less physical pain and receiving more staff encouragement than the traditional care group at six weeks or 12 weeks. In a previous review, researchers showed that severe pain is prevalent among patients with CKD and that more than 58% of CKD patients experience pain and 49% of the patients rate their pain as moderate or severe.³⁶ Early detection of and intervention for pain among patients with CKD can help substantially reduce the financial burden associated with pain-related hospital readmission and promote better QOL⁸ In remote home management, the health data from the patient’s feedback can assist healthcare professionals to treat pain in a timely manner. In addition, such a patient-centered and physician-supervised approach can reinforce self-management and promote medication adherence for pain reduction. Because of the unexpected adverse effects and lack of desire to increase an already large pill burden, patients with CKD showed poor compliance in taking analgesic agents.³⁷ Overall, the remote home management approach can provide support and referral when patients suffer from pain and can increase patients' self-efficacy in pain control.

The characteristics of interventions varied in each study, including the duration, type and intensity of the intervention; however, all showed positive effects on health service utilization. Remote home management results in a significant decrease in hospital readmissions, ER visits, and number of days in the hospital, which is consistent with the finding that the frequency of hospital readmission has a negative correlation with QOL.³⁸ In addition to these factors, the type and duration of treatment given can greatly influence the QOL in patients with CKD. However, little is known concerning the QOL in CKD patients before renal replacement therapy, and the present analysis primarily included hemodialysis and peritoneal dialysis patients.

Blood pressure and weight

The significance of the effects of remote home management on BP, which is important in lowering CKD morbidity and mortality, remains inconclusive. In fact, remote home management holds the potential to greatly enhance CKD patients' BP and self-management of disease. The results of this study, however, only revealed a declining effect on DBP, and even an increasing trend on SBP, when home remote management was compared to traditional care. This finding is inconsistent for those with pre-hypertension or hypertension alone, for whom remote home management interventions significantly reduce BP and improve adherence to medical therapy.^39,40 Moreover, some self-control studies confirmed that home blood pressure management combined with web-enabled collaborative care results in better and faster BP control.^20,21 There are a few potential reasons for why this review failed to find any major effect of BP as a result of this new healthcare delivery model. On the one hand, the studies that focused on BP were not conducted using a double-blind design. Although it was not possible to blind participants to the intervention because of the nature of the intervention involving patient self-management, the research staff during study visits could be blinded to treatment allocation. On the other hand, some of the studies included in the review were not evaluated using ITT analysis. The introduction of these potential biases might affect the results of BP in the individual studies or in the overall systematic review. Therefore, despite this review’s failure to illustrate a robust response to intervention by patients with CKD, we still believe that remote home management holds promise for controlling BP. In the future, more high-quality studies should be performed to the effects of evaluate home management on BP.

It is worth noting that the interdialytic weight and ultra-filtration rate, which are closely related to BP, were significantly reduced. A likely reason is that the remote home management patients received more dialysis staff encouragement. It has been well documented that patient-received encouragement from the dialysis staff is an important factor in improving fluid control adherence.⁴¹

Patients' attitude

Favorable effects were observed in the patient’s attitude; however, these effects were difficult to quantify given the disparate methodologies employed. In general, regardless of their gender, age or nationality, the patients complied with remote home management programs and the use of technologies, which means that patients were receptive to remote home management as a self-management approach and they demonstrated a positive attitude toward it. This result is also reflected in the questionnaire, which is the easiest way to measure patients' attitudes, although both the validity and reliability of this method are weak.⁴² Indeed, active patient participation plays an important role in the effective management of CKD, which is a long-lasting, frustrating and often progressive disease.

The GRADE analysis of the quality of included studies showed that the strength of evidence for quality of life, BP and interdialytic weight was ‘low' due to the presence of publication bias and/or the lack of ITT analysis. Moreover, because of the presence of potential bias and publication bias, the strength of evidence for healthcare service utilization and patients' attitude was ‘very low' (Table 5).

Table 5.

GRADE analysis: Remote home management vs usual care, outcome for chronic kidney disease (CKD) patients.

Clinical outcome	Participants (studies) follow-up	Risk of bias	Inconsistency	Indirectness	Imprecision	Publication bias	Large effect	Plausible confounding would change effect	Dose response gradient	Overall quality of evidence
Quality of life	264 (3 studies); 3–12 months	Very serious^a,b	No	No	No	No	No	No	No	Low
Blood pressure	182 (3 studies); 3–6 months	Very serious^a	No	No	No	No	No	No	No	Low
Inter-dialytic weight	120 (1 study) 3 month	Serious^a,b	No	No	No	Strongly suspected^c	No	No	No	Low
Patient's attitude	62 (2 studies) 3–6 months	Very serious^a,b	No	No	No	Strongly suspected^d	No	No	No	Very low
Healthcare services utilization	335 (4 studies) 3–36 months	Very serious^a,b	No	No	No	Strongly suspected^e	No	No	No	Very low

The basis for the assumed risk: ^aall of studies were non-blinded; ^bfailure to adhere to the intention to treat principle; ^cpublication of evidence is limited to one trial; ^dpublication of evidence is limited to two trials; ^epublication of evidence is limited to four trials.

GRADE Working Group grades of evidence. High quality: Further research is very unlikely to change our confidence in the estimate of effect. Moderate quality: Further research is likely to have an important impact on our confidence in the estimate of effect and may change the estimate. Low quality: Further research is very likely to have an important impact on our confidence in the estimate of effect and is likely to change the estimate. Very low quality: We are very uncertain about the estimate.

The present analysis has several limitations. Only one study used power calculations to determine sample sizes.¹³ Thus, the results should be interpreted with caution. Furthermore, most of the studies included in this review focused on patients with end-stage renal failure and those receiving dialysis but included only a limited number of early-stage CKD patients; thus, the results cannot be generalized for the entire population of patients with CKD.

Conclusion

The available data indicate that remote home management may be a novel and effective disease management strategy for improving the QOL of patients with CKD and influencing their attitudes and behaviors. However, the present studies are all small sample research and have some potential bias, so the large-scale multi-site effectiveness RCTs are needed to improve the persuasiveness of the evidence and provide support for implementation of the research. And, relatively little is known about blood pressure and cost-effectiveness, so future research should focus on these two aspects for the entire population of patients with CKD. Additionally, using different mobile technologies as well as different aesthetic design may provide important insights into the scope of remote home management’s potential benefits.

Footnotes

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: the study was supported by the National Natural Science Foundation of China (no. 81273594), the National Science and Technology Major Projects (no. 2012ZX0903014001), the National Key Technology R&D Program (no. 2012BAI37B05), and the Project of Technology Department of Hunan Province (no. 2013TZ2014).

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