The effect of telehealth versus usual care for home-care patients with long-term conditions: A systematic review,meta-analysis and qualitative synthesis

Abstract

Introduction

Approximately 26 million people in the United Kingdom are living with one long-term condition and 10 million are living with two or more; these figures are projected to continue increasing (NHS England 2018). People with long-term conditions are two to three times more likely to have poor psychological wellbeing and utilise 50% of GP appointments, 64% of outpatient appointments and over 70 of inpatient bed days. Research in this population could help with increasing constraints on healthcare budgets and resources. Technology-enabled healthcare in the community might help improve quality of life and reduce healthcare costs of managing chronic disease but the overall impact is unclear, we therefore conducted a systematic review.

Methods

Keywords and MeSH terms were used to search MEDLINE and CINAHL. We included qualitative and quantitative studies that reported on adult home-care patients diagnosed with at least one long-term condition, comparing telehealth to usual home care. Meta-analyses and sensitivity analyses were conducted using RevMan 5. Qualitative findings were thematically synthesised and reported narratively.

Results

In total, 2568 studies were identified and nine (2611 participants) were included. Telehealth was not statistically significantly different versus standard home care for quality of life, psychological wellbeing, physical function, anxiety, depression, disease specific outcomes or bed days of care at 3, 6, 9 and 12 months. Qualitative findings showed patients found telehealth was beneficial for providing peace of mind and legitimising access to healthcare.

Conclusion

Telehealth may offer reassurance to those living in the community with long-term conditions; however, a lack of high-quality studies and heterogeneity between interventions makes conclusions difficult.

Keywords

eHealth home telecare telegeriatrics telehealth systematic review meta-analysis chronic disease

Introduction

Globally, the four most prominent chronic diseases are cardiovascular disease, cancer, chronic obstructive pulmonary disease and diabetes.¹ Approximately 26 million people in the United Kingdom (UK) are living with one long-term condition (LTC) and the number of people living with three or more LTCs is rising. Those living with an LTC are two to three times more likely to have poor mental health, particularly depression and anxiety, than the rest of the population. Chronic obstructive pulmonary disease is associated with a three times greater prevalence of a mental health condition³ and those with cardiovascular disease or diabetes mellitus have a 2–3-fold higher prevalence of depression than those without these diseases.^2,3

LTCs take up 50% of general medical practitioner appointments, 64% of hospital outpatient appointments and over 70% of inpatient bed days in the UK.⁴ Services and care provision for people with LTCs account for 70% of the annual health and social care spend.⁵ By 2020–21, in the UK a £30 billion funding gap is forecast in health and social care as a result of LTCs, together with an aging population.^4,6 This healthcare burden is outstripping healthcare resources and community provision. As this is set to continue, technology-assisted solutions are of key interest to commissioners and policy leaders to make healthcare more efficient and effective.^7,8

Evidence from various case studies shows that proper implementation of telehealth services can be cost effective and improve efficiency. In 2011, the Department of Health reported the use of telehealth can reduce mortality, accident and emergency visits and emergency admissions by 45%, 15% and 20% respectively.⁹

Several examples of technology-enabled home care have been implemented in the past with varying impacts in terms of quality of life, hospital admissions and cost-benefit.^35,36

However, widespread adoption and uptake of telehealth is poor among all stakeholders – service users, carers, healthcare professionals and commissioners.⁴ From a professional point of view, this may be due to the heterogeneity of evidence, meaning effectiveness is unclear and perceived beliefs around additional work burden at an already stretched and high-pressure time.¹⁰ From a service-user point of view telehealth maybe an unwelcome constant reminder of a chronic condition. They may like taking daily medical readings or having medical technology in their home.¹¹ The older population may be insufficiently well acquainted with technology to embrace its use. They may be concerned telehealth will impact negatively on their current treatment and undermine valued healthcare services and relationships with healthcare professionals.^12–14

Aim

The aim of this research is therefore to conduct a systematic review on the evidence of cost effectiveness of telehealth interventions in the community compared to usual care and its impact on quality of life.

Objectives

To conduct a systematic review of studies of any design that meet the following criteria:

Adults living at home with an LTC.

Telehealth, defined as the remote exchange of medical data using electronic equipment between a service user and healthcare professional, has been used instead of usual home care (home-care nursing and visits for assessment, diagnosis, treatment management plans, services user and carer support).

Quality of life (either quantitatively or qualitatively) or cost effectiveness have been measured.

Methods

Search criteria

Medline and CINAHL databases were searched for studies using medical subject headings and keywords to include terms for: LTCs OR life-limiting conditions AND telehealth OR tele monitoring. Terms were agreed with a subject librarian and the author team. Full details of the search strategy are in Appendix 1.

Study selection

Titles and abstracts were screened to identify potentially relevant articles fitting the inclusion criteria (Table 1). The full text of these articles was then reviewed with further irrelevant studies excluded at this stage. Final articles were checked in terms of relevance to the research question and inclusion criteria by a second author.

Table 1.

Inclusion and exclusion criteria.

	Inclusion criteria	Exclusion criteria
Population	• Adult population (over 18 years old)• Diagnosis of one or more chronic conditions• Home-care patients only	Under 18 years old• Participant age range not stated• No clear diagnosis of chronic condition• Cancer and chronic kidney disease (as short-term curable treatments are available)
Intervention	Remote exchange of medical information between a service user and healthcare professional	Non-health-related smart home technology (energy consumption, home security)• Remote consultation• Internet education• Remote monitoring• Motivational messages or reminders• Telephone follow-up
Comparator	Standard home care• Face-to-face visit from healthcare assistant or district nurse	Care in nursing homes, residential homes or sheltered accommodation• Hospital-based inpatient care
Outcomes	Quality of life scales• Qualitative data depicting quality of life• Cost effectiveness	No quality of life results• No cost effectiveness reported
Study design	Qualitative• Quantitative• Mixed methods	No design restriction
Language type	All languages included	No language restriction
Date of publication	• 1990–present	Papers published pre-1990 as they are likely to relate to technologies which are now obsolete due to the recent surge in technology interest and advances
Type of publication	Research papers that have undergone peer review	Magazine articles• Book chapters• Dissertations and theses

Data extraction

Data were extracted from each of the studies and included study design, sample size, demographics and medical condition of the population, intervention description, comparator and outcomes related to quality of life and cost effectiveness.

Data analysis

Where available, intention to treat data were extracted in preference to completer analysis data. Meta-analyses were conducted to combine results of two or more sufficiently similar studies measuring comparable outcomes. Software used for meta-analyses in this paper was Rev Man 5 and a random effects model was used. Heterogeneity was assessed using the I² statistic. Sensitivity analyses was conducted to see if the results were robust enough to remove studies with a high risk of bias.

Reporting of qualitative results was narrative, using thematic analysis and based on qualitative synthesis recommendation by Walsh (2005).³⁸ Once complete, this was then peer reviewed by a second author.

Assessment of risk of bias

The Cochrane tool for assessing the risk of bias was used to assess the bias of random sequence generation, allocation concealment, blinding of participants and personnel, blinding of outcome assessment, incomplete data outcome and selective reporting of quantitative studies. A Critical Appraisal Skills Programme Checklist was used to assess qualitative research.

Results

Study selection

The search yielded 2568 citations. Once duplicate citations were removed, 2375 papers remained to be screened. Of these, 2298 were rejected by screening the title and abstract. The remaining 77 full-text articles were assessed for eligibility; 19 were excluded due to a lack of formal diagnosis, 21 provided no clear description of the telehealth intervention and 29 did not report quality of life as an outcome measure. Nine studies were included in the review, the PRISMA flowchart is detailed in Figure 1.

Figure 1.

Preferred reporting items in systematic review and meta-analysis (PRISMA) flowchart for search strategy.

Characteristics of included studies

A total of nine studies were included in this review, two of which were qualitative papers.^13,14 Of the quantitative research, one was a single-site cohort study,²⁵ two were multi-site cluster trials^28,37 and the remaining four studies were randomised trials.

Study participants

A total of 2611 home-care adults living with chronic conditions were involved in this review (Table 2). The sample size varied among the studies from seven to 1201 participants. Studies were predominantly conducted in the UK (78%), five of nine in England, one in Ireland and one in Wales. Two studies were carried out in the United States.

Table 2.

Study characteristics.

	Country of origin	Study type	Number of participants: Total (control vs intervention)	Gender (m/f)	Age range (or SD)	Long term condition diagnosis	Description of telehealth intervention	Length of intervention	Total length of study including follow-up	Quality of life measures
Lewis, Annandale, Warm et al., 2010	Wales, UK	Quantitative: randomised trial	40 (20/20)	20/20	63–79	Primary diagnosis of moderate to severe COPD	6-month telemonitoring in addition to standard care. Questions plus temperature and pulse oximetry sent every evening 02.00am for nurse to review in the morning	6 months	12 months (6 months TH then 6 months standard care vs 12 months standard care)	Measured: St Georges Respiratory Questionnaire, Hospital Anxiety and Depression Score, EuroQuol-5D Questionnaire
McDowell, McClean, Gibbon et al., 2014	Northern Ireland, UK	Quantitative, Randomised clinical trial	100 (52/48)	38/62	70 (7)	Primary diagnosis of moderate to severe COPD	Standard programme care plus HomeMed: answer questions plus blood pressure and finger probe reading, nurse read within 10 minutes of data arrival	6 months daily	6 months	St Georges Respiratory Questionnaire, Hospital Anxiety and Depression Score, EuroQuol-5D Questionnaire
Pecina, Hanson, Houten et al., 2013	USA	Quantitative: Randomised controlled trial	166 (89/77)	78/88	79 (9)	Presence of chronic disease. Not specific	Intel Health Guide to collect biometric data (blood pressure, weight, pulse, temperature, pulse oximetry, peak flows). Daily readings and videoconferencing available. Time delay between monitoring and nurse viewing results not specified.	12 months	12 months	Physical and mental score on the Short Form Health Questionnaire (SF-12v1). Patient Health Questionnaire (PHQ 9). Barthel Index and self-reported health status
Henderson, Knapp, Fernandez et al., 2013	London, UK	Cluster randomised controlled trial	965 (431/534)	521/384	70 (11)	COPD, chronic heart failure, diabetes	Weighing scales, pulse oximeter, blood pressure cuff, glucometer. Different equipment for participants in different regions based on health care provider	12 months	12 months	Quality Adjusted Life Years, ICECAP-O, BriefSTAI and Centre for Epidemologic Studies Depression Scale (CESD-10)
Cartwright, Hirani, Rixon et al., 2013	London, UK	Cluster randomised controlled trial	1201 (531/670)	723/478	70 (11)	COPD, chronic heart failure, diabetes	Weighing scales, pulse oximeter, blood pressure cuff, glucometer, symptom reports transmitted. Second generation system: non-immediate data analysis	12 months	12 months	SF-12, EQ-5D, BreifSTAI, CESD-10
Lusignan, Wells, Johnson et al., 2001	Guildford, UK	Randomised controlled pilot trial	20 (10/10)	-	-	Diagnosis of chronic heart failure	NAIS memory Blood Pressure Watch: pulse and blood pressure plus weighing scales and video consultation equipment	12 months	12 months	GHQ and chronic heart failure symptomatology questionnaire
Noel, Vogel and Erdos et al., 2004	Connecticut, USA	Single blind, single site randomised large sample study	104 (57/47)	101/3	71 (54–90)	Complex heart failure, COPD, diabetes	Peripheral devices to collect blood glucose, blood pressure, temperature, three-lead electrocardiogram, stethoscope for heart and lung sounds, pulse oximetry and weight. Pain level 0–9 via self-reported questionnaire. Data transmitted via facilities electronic database (VISTA)	12 months	12 months	No validated scale. Objective and subjective measures of self-reported quality of life taken and recorded at baseline, and quarterly until 12 months (cognitive status, HBA1C levels, functional level, patient satisfaction, self-rated health status). Cost data were recorded 6 months preceding the study and 6 months during participation.
Gorst, Coates and Armitage, 2016	Sheffield, UK	Qualitative using IPA analysis.	8	3/5	68 (58–84)	COPD	Six with small sized telehealth equipment: peripheral devices to take vital sign recordings. Two had large telehealth equipment which allowed them to view their graphs. All patients monitored blood pressure, oxygen level, pulse rate and temperature. Two patients with larger equipment monitored weight.	Patients already been using telehealth equipment to manage condition, no intervention period.		Face-to-face interviews, semi structured interview template. IPA used to gain complete and in-depth understanding of patient experiences of illness and healthcare.
Gale and Sultan, 2013	Birmingham, UK	Qualitative	7	5/2	67 (57–85)	COPD	Blood pressure, weight and temperature every weekday sent to Community Respiratory Service team	9 months	9 months	Situated interviewing (at patients’ homes). Observations of the home made. Thematic analysis used.

COPD: chronic obstructive pulmonary disease; IPA: Interpretative Phenomenological Analysis; GHQ: General Health Questionnaire; PHQ: Patient Health Questionnaire; TH: Telehealth; UK: United Kingdom; USA: United States of America.

Of the nine included papers, eight provided information on gender. The distribution of males to females included equates to 1489 (59%) and 1042 (41%) respectively.

The ages of participants varied between 49 and 90 years old although the mean age was 71 years old. All participants have a formal diagnosis of at least one chronic condition, the most prevalent being chronic obstructive pulmonary disease (COPD). Four of nine papers included participants with only this condition, two focussed on people with chronic heart failure (CHF). Other remaining studies included patients with a diagnosis of diabetes mellitus (DM) and presence of co-morbidity (CHF and DM, CHF and COPD, COPD and DM or CHF, COPD and DM).

Interventions

Each of the included studies described a technology-enabled intervention that involved the remote exchange of medical information between a service user and assigned healthcare professional. All study participants were given devices with which they were expected to measure vital signs including weight, blood pressure, temperature and pulse oximetry. Three studies specified that recordings were expected to be measured and sent daily.^11,27,29

A qualitative study implemented a new telehealth intervention whereby COPD patients were able to send vital signs to a Community Respiratory Service. This included their oxygen saturation, blood pressure, weight and temperature every week day. This intervention lasted for 9 months prior to the commencement of interviews.¹³ Only one qualitative study reported on patients with pre-existing telehealth to gain an understanding of the longer term (exceeding 12 months) impact of telehealth on quality of life outcomes.¹⁴ Most other quantitative studies only followed up participants for 12 months.

Two studies reported shorter-term outcome measures at 3-, 6- and 9-month intervals.^25,26 One study²⁷ reported at 6 and 12 months and one other study measured only from baseline and at 6-month follow-up.¹¹ Cartwright et al. (2013) and measures short-term outcomes at 4 months and 12 months for long-term outcome assessment.²⁸

Comparator

All but two studies included a comparator, which was standard health and social care. Details of what this entailed in terms of frequency of visit or contact with a community health professional for each study is limited. Cartwright et al. (2013) stated usual homecare consisted of pre-established tailored care plans of multidisciplinary teams. They report that visit frequency depended on condition severity and ranged from between once per week to once per year, depending on the patient.

The two qualitative studies reported on patients who had been using telehealth anyway or for a 9-month study period.^13,14 For these studies, there was no comparator being investigated.

Outcome measures

Studies measured quality of life using EuroQol-5Dimensions (EQ-5D), EuroQol-Visual Analogue Scale (EQ-VAS), self-rated health and qualitative reporting methods.^11,27–29 Proxy measures to quality of life included psychological wellbeing measured by mental component score, the Kokmen test and the 28-item General Health Questionnaire.²⁸ Depression and anxiety was measured by Hospital Depression and Anxiety (HADS Depression or HADS Anxiety), Centre for Epidemiologic Studies Depression scale (CESD)-10, Patient Health Questionnaire (PHQ9), Brief-State Trait Anxiety Index (STAI).^{11,27–29,37} Physical function was measured using the physical component score and Barthel Index.^27,28 Disease specific quality of life was measured by Chronic Heart Failure Questionnaire and St Georges Respiratory Questionnaire for COPD (SGRC-C).^11,26,29 Cost effectiveness was measured as Quality Adjusted Life Years and ICECAP-O.³⁷

Assessment of bias

McDowell et al. (2014), Lewis et al. (2011) and Cartwright et al. (2014) were all considered to be a lower risk of bias than the other studies (Figure 2).

Figure 2.

Assessment of bias table.

Meta-analyses

Meta-analyses are a method of pooling data from different studies to report on overall mean effect across studies and assess statistical significance. The overall mean effect and the spread of this data is represented by a diamond at the right-hand side of the forest plot/figure. Statistical significance is determined by the positioning of the diamond at the bottom. If the diamond overlaps 0, the result shows no statistically significant difference between study groups. This will result in a p value > 0.05. The forest plots are weighted by study size and the ‘traffic light’ labelling of the study takes into account the methodological rigour based on the domains listed in a previous section.

Quality of life

Pooling the results in a meta-analyses from the studies measuring quality of life show that telehealth versus standard home care are not statistically significantly different in terms of change in quality of life at 3 months (Figure 3), 6 months (Figures 4 and 5), 9 months (Figure 6) and 12 months (Figures 7 and 8).

Figure 3.

Quality of life at 3-month follow-up.

Figure 4.

Quality of life at 6-month follow-up.

Figure 5.

Sensitivity analysis for quality of life at 6-month follow-up.

Figure 6.

Quality of life at 9-month follow-up.

Figure 7.

Quality of life at 12-month follow-up.

Figure 8.

Sensitivity analysis for quality of life at 12-month follow-up.

Sensitivity analysis removing studies at high risk of bias was conducted on results from 6 months (Figure 4 and 5) and 12 months (Figures 7 and 8) but this had a negligible effect on the results.

Psychological wellbeing

Figures 9, 10 and 11 show telehealth and standard home care are not statistically significantly different in terms of change in psychological wellbeing at 3, 6 and 12 months. These results are not clinically meaningful because of the minimal effect size.

Figure 9.

Psychological wellbeing at 3-month follow-up.

Figure 10.

Psychological wellbeing at 6-month follow-up.

Figure 11.

Psychological wellbeing at 12-month follow-up.

Physical function

These meta-analyses show telehealth and standard home care are not statistically significantly different in terms of change in patients’ physical function at 3 months (Figure 12), 6 months (Figure 13) and 12 months (Figure 14). These results consistently favour telehealth, but the effect size is negligible and not clinically important.

Figure 12.

Physical function at 3-month follow-up.

Figure 13.

Physical function at 6-month follow-up.

Figure 14.

Physical function at 12-month follow-up.

Anxiety

Figures 15 and 16 present results on anxiety at 6 and 12 months respectively. These meta-analyses combine low-level bias studies only, yet are still statistically not significant in terms of a difference in change in anxiety scores between telehealth and standard home care.

Figure 15.

Anxiety at 6-month follow-up.

Figure 16.

Anxiety at 12-month follow-up.

Depression

These meta analyses show telehealth and standard home care are not statistically significantly different with regard to change in patients’ depression scores at 6 and 12 months (Figures 17 –20).

Figure 17.

Depression at 6-month follow-up.

Figure 18.

Sensitivity analysis for depression at 6-month follow-up.

Figure 19.

Depression at 12-month follow-up.

Figure 20.

Sensitivity analysis for depression at 12-month follow-up.

Sensitivity analysis was conducted on data at 6 months and 12 months to combine low-level bias studies only to assess whether this influenced the results. Results from both sensitivity analyses were not significantly different to primary findings.

Change effect size is minimal at both time intervals, which reflects no clinically meaningful difference result.

Disease-specific outcomes

Results from data on disease-specific outcomes at 6 months (Figures 21 and 22) and 12 months (Figure 23) show changes in these scores between telehealth and standard home care are not statistically significantly different.

Figure 21.

Disease specific outcomes at 6-month follow-up.

Figure 22.

Sensitivity analysis for disease-specific outcomes at 6-month follow-up.

Figure 23.

Disease specific outcomes at 12-month follow-up.

Two studies^11,29 used SGRC and these were combined in sensitivity analysis to assess disease-specific outcomes for COPD patients only. These results were highly heterogeneous (85%).

The minimal change effect size means the difference between telehealth and standard home care for disease specific outcomes is not clinically meaningful.

Cost-utility analysis

One study reported on quality of life in terms of Quality Adjusted Life Years (QALYs).³⁷ QALYs for usual care group was 0.55 compared to 0.56 for telehealth. The cost associated with this was £5559 and £6384 for usual care and telehealth groups respectively.

Inpatient bed days of care

Noel et al. (2004) reported the difference in bed days of care (BDOC). At 6 months, telehealth group had reduced from 12.2 to 1.9 (SD 3.3) whereas control group BDOC decreased from 13.8 to 5.1 (SD 10.5).

Henderson et al. (2013) who reported inpatient bed days at 12-month follow-up were 1.2 (SE 0.2) for usual care group and 1.0 (SE 0.2) for telehealth group.

Figure 24 presents a meta-analysis combining the above studies and found no statistically significant mean difference between telehealth and usual care group for bed days of care.

Figure 24.

Bed days of care at 6- and 12-month follow-up.

Findings from qualitative studies

Two qualitative papers explored the effect of using telehealth on quality of life.^13,14 Both papers reported on adult COPD participants and overall study characteristics and intervention context were similar to those of included quantitative studies. Thematic synthesis of both qualitative papers enabled the development of four summative themes as discussed below.

Telehealth provides peace of mind

Telehealth provides peace of mind and reassurance for the patient and their family. The results from qualitative papers illustrated this, as shown by the following quotes.

‘I just find it reassuring that I can check manually what my oxygen levels are, because I’m aware of the fact I get anxious about things … they [family] are very much aware of the fact that I do not look after myself and so it reduces worry for them.’

‘I’d go so far as to say if I could afford it, I’d buy my own equipment and this peace of mind syndrome, it relaxes you a lot.’

Part of this peace of mind came from managing feelings of isolation and helplessness: ‘knowing there’s someone at the end of the line that can help me’, ‘reassuring, it’s like having another person with you even though it’s a machine.’

This reduced the need for help form healthcare professionals: ‘I haven’t called them [district nurses] out so often since I’ve had the telehealth’.

Telehealth improves healthcare accessibility as people feel less of a burden

Patients found telehealth facilitated ‘better access to healthcare professionals’. Having the ability to remotely send vital sign data because it meant that ‘you’re not overlooked’ and if you need a healthcare professional to contact you, ‘they’re straight onto it.’ This was valued by both patients and their carers and led to a feeling of ‘enhanced active engagement’ in healthcare.

Telehealth also facilitated access to healthcare by legitimising contact and ‘ensured that nurses telephoned or made a visit when they were really needed’. This encouraged patients to engage with telehealth and provided relief of the sense of being a burden to health services. Patients who expressed a fear ‘that they will waste their time’ overcame this via telehealth, which enabled visits to be made ‘when they were really needed’.

Legitimised contact and access to healthcare was reported to have an impact on early identification of symptoms and early intervention. Telehealth was described as ‘sort of a lifeline’ because ‘knowing that somebody is at the end of the line, that’s important’ and ‘I think I would have been in hospital without it.’ Telehealth meant patients who previously rarely sought medical advice due to not believing they were ‘ill enough to warrant treatment’ began to act on symptoms because they were able to ‘readily ascertain whether there is a problem’ and seek help accordingly.¹⁴

In terms of human resources, this factor highlights the potential telehealth has for patients to be triaged appropriately, while enabling them access and reassurance.

Telehealth promotes ownership and self-management

Patients felt more confident to self-manage their condition because telehealth enhances ‘aware[ness] of what is happening’, ‘I seem to be eating a lot better’ and ‘it could be that I’ve got my confidence back’, which demonstrates a positive engagement with telehealth.

Self-management and improved engagement with their condition and health was expressed by most participants. Improved awareness ‘definitely helped with health management’ and made patients more engaged with their condition: ‘I want to know about my health now.’ Prior to using telehealth, people were of the opinion ‘that [the] community matron was responsible for looking after [them]’, so they previously ‘did nothing to manage [their] own health condition’.

Telehealth empowered participants to feel ‘more self-sufficient’ and some resulted in purchasing their own equipment.

Fear of reduced face to face contact and isolation

The disadvantages of telehealth were reported. Results discuss the impact telehealth has on limiting face-to-face contact for patients who may not have any other visitors. ‘The only thing I miss with it [telehealth] is that I do not get the nurses coming to visit like I used to, human contact’; however, participants did acknowledge ‘the nurse side of it is not necessary, there’s no point having an nurse when they’re only going to do exactly what you can do yourself’ but ‘it’s nice to have someone to speak to occasionally’.

One participant from the qualitative studies provided a different opinion, not to be overlooked. They explained a ‘sense of restriction and invasion of medical technologies’ into their life, which felt like being a ‘dog on a lead’. This is significant when considering the practicalities and psychological barriers to acceptance and adherence to telehealth as a management intervention for people living in their own home.

Synthesis of quantitative and qualitative findings

Quantitative findings reflected no statistically significant difference between telehealth and usual home care in terms of psychological wellbeing, anxiety and depression (see Meta-analyses above). Qualitative findings, however, reflect that patients did value telehealth and gained ‘peace of mind’ from its installation as well as experienced ‘better access’ and improved ‘active engagement’ with healthcare professionals due to ‘legitimised contact’.

Despite meta-analyses representing a larger sample size and a pool of sufficiently similar data, we recognise its limitations in terms of drop-out rating and varying methodological rigour. In terms of psychological wellbeing, the qualitative findings are useful for presenting the patient voice that maybe masked in our non-statistically significant meta-analysis.

Bed days of care was not statistically significantly different between participant groups; however, both qualitative papers found people with telehealth were favoured. The explanation for such a result is that telehealth facilitates self-monitoring and self-management, which enables patients to seek help when they need it rather than allowing their symptoms to deteriorate for fear of being a burden.

Discussion

Summary of key findings

The purpose of this systematic review was to identify whether telehealth is a useful intervention for home-care patients with LTCs. The primary outcome of interest was quality of life due to the existing evidence of strong correlation between diagnosis of chronic condition and poor psychological wellbeing.

There was no statistically significant difference between telehealth and standard home care. This was found in terms of quality of life, psychological wellbeing, physical function, anxiety, depression disease specific outcomes or bed days of care at 3-, 6-, 9- and 12-month intervals.

Cost utility was calculated using QALYs in one paper only. The differences in QALYs between intervention arms were negligible at 0.549 and 0.564 for standard home care and telehealth respectively. As this was the only study to report QALYs as an outcome, it is difficult to interpret this as a definitive finding.

Qualitative findings from two papers were predominantly positive about telehealth. Recurring themes suggest telehealth provides peace of mind, increases access to healthcare improves ownership and promotes self-management. However, for some, the negative aspects of less personal contact and invasiveness were voiced.

Strengths and limitations

Rigorous methodology

This systematic review followed Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) 27-item checklist.³¹ The search strategy used in this review was formulated and practised alongside the support of a subject expert librarian. MeSH terms and keywords were used as well as truncation terms. The inclusion and exclusion criteria for this review were concise with clear, agreed definitions reducing risk of ambiguity and uncertainty.

General limitations

The limitations of this review are largely the result of the quality of included studies. Sample sizes of included studies were mainly small, except from the Whole Systems Demonstrator trial and high drop-out rates were common in all quantitative studies. Common reasons were funding, lack of participant acceptance of the technology, hospitalisation and mortality. To limit the impact on reliability of results, data were combined in sub analysis and reported separately. Heterogeneity among available quantitative study design, sample size and diagnosis of participants, follow up time and drop-out rates also made conclusions difficult. Most results reflect telehealth use and impact over a short period of time (6 to 12 months) rather than providing a true reflection of its long-term use.

A random-effects model was used in the meta-analyses of this paper. This method has known limitations including overestimation of effect size and wider confidence intervals, but it was more appropriate than fixed effects given differences between interventions.

Only one researcher was responsible for the search strategy and decision over inclusion and exclusion of papers. However, to minimise selection bias, the search strategy was checked and approved by two members of the supervisory team, and final papers for inclusion were agreed with one supervisor.

Potential publication bias

No language restriction was used when carrying out the search strategy for this review. Despite that, all included papers in this review were in English. There is a recognition and discussion of editorial bias whereby papers published in English are more likely to report positive results.³³ Here, this is noted as a potential limitation to this study. Searches using non-English-language scientific databases were not conducted. Databases to search for grey literature were also not included in the search strategy, which does pose a risk of publication bias. Nonetheless, to our knowledge this is the first review attempting to pool and summarise results on the added value of a specific telehealth in long-term conditions.

Generalisability and applicability

The inclusion criteria were broad to ensure maximum generalisability and transferability of the findings; however, included papers were from economically developed countries and predominantly reported on the UK population. Nonetheless, included studies had a demographic and medical context that is reflective of the highest proportion of LTC prevalence globally as well as in the UK. Participants in this review were adults with a mean age of 71 years.^49–90 In context, this population is responsible for a £5 billion annual cost to the healthcare system and is projected to continue to increase by a further £5 billion by 2020, which outstrips healthcare resources. Our review suggests telehealth offers peace of mind, promotes self-management and more appropriate access to healthcare.

Consistency of findings

This is the first review attempting to pool and summarise results on the added value of telehealth, defined as the exchange of medical information between a service user and healthcare professional, in LTCs. A review of randomised controlled trials investigating telemedicine in broader terms to include video-conferencing, remote monitoring, education and real-time assessment of clinical status found disease-specific quality of life improved more for heart failure patients receiving telemedicine than usual care (mean difference in Minnesota Living with Heart Failure Questionnaire: −4.39 95% confidence interval (−7.94, −0.83), N = 482, five studies). Like our results, no difference was found in hospital stays. With pooling results from multiple technologies, it is difficult to tease out which type is responsible for changes in outcomes and the ineffectiveness of one technology could be masking the effectiveness of another, so the applicability of such findings is limited.

Conclusions

Quantitatively, telehealth is not statistically significantly different to usual care for changes in quality of life, psychological wellbeing, physical function, anxiety, depression, disease specific outcomes or bed days of care at 3-, 6-, 9- and 12-month intervals.

Qualitative findings suggest important benefits to patients’ peace of mind and confidence to access healthcare appropriately.

Future research

The findings presented in this paper are useful for providing an overview of the current evidence base of technology use in home-care patients with LTCs and its potential to impact quality of life. However, high-quality randomised controlled trials are needed that are specific to a technological intervention and disease state for results to be clinically meaningful and truly reflective of usability and impact.

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) received no financial support for the research, authorship and/or publication of this article.

Appendix 1

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