Home telehealth uptake and continued use among heart failure and chronic obstructive pulmonary disease patients: a systematic review.

BACKGROUND: Home telehealth has the potential to benefit heart failure (HF) and chronic obstructive pulmonary disease (COPD) patients, however large-scale deployment is yet to be achieved. PURPOSE: The aim of this review was to assess levels of uptake of home telehealth by patients with HF and COPD and the factors that determine whether patients do or do not accept and continue to use telehealth. METHODS: This research performs a narrative synthesis of the results from included studies. RESULTS: Thirty-seven studies met the inclusion criteria. Studies that reported rates of refusal and/or withdrawal found that almost one third of patients who were offered telehealth refused and one fifth of participants who did accept later abandoned telehealth. Seven barriers to, and nine facilitators of, home telehealth use were identified. CONCLUSIONS: Research reports need to provide more details regarding telehealth refusal and abandonment, in order to understand the reasons why patients decide not to use telehealth.

Telerehabilitation: enabling the remote delivery of healthcare, rehabilitation, and self management.

Telerehabilitation refers to the use of Information and Communication Technologies (ICT) to provide rehabilitation services to people remotely in their homes or other environments. By using ICT, client access to care can be improved and the reach of clinicians can extend beyond the physical walls of a traditional healthcare facility, thus expanding continuity of care to persons with disabling conditions. The concept of telecare, when telerehabilitation is used to deliver services to clients in their homes or other living environments, empowers and enables individuals to take control of the management of their medical needs and interventions by enabling personalized care, choice and personal control. A wide variety of assessment and treatment interventions can be delivered to clients using remote monitoring systems, robotic and virtual reality technologies, and synchronized collaboration with online material. This chapter will present a brief history of telerehabilitation and telecare and offer an overview of the technology used to provide remote rehabilitation services. Emphasis will be given to the importance of human factors and user-centered design in the planning, development, and implementation of telerehabilitation systems and programs. The issue of self-care in rehabilitation and self-management will be discussed along with the rationale for how telerehabilitation can be used to promote client self-care and self-management. Two case studies of real-world telerehabilitation systems will be given, with a focus on how they were planned and implemented so as to maximize their potential benefits. The chapter will close with a discussion of obstacles and challenges facing telerehabilitation and suggestions for ways to promote its growth in use and acceptance.

An evaluation of second and third generation telecare services in older people's housing.

In a controlled study of older people living in sheltered housing (retirement housing), 24 people provided with telecare were compared with a control group of 28 people. The intervention consisted of second generation telecare equipment, such as automatic flood or falls detectors, a third generation lifestyle reassurance system and an Internet café. After a 12-month monitoring period, there was no noticeable change in the fear of falling. There was no significant difference for eight of the nine SF-36 domains. However, the Social Functioning domain showed a significant difference (P = 0.049), with scores 8% higher in the intervention group, suggesting a beneficial effect of telecare. Positive trends were also evident in areas such as an increase in the length of time spent out of the home, improved feelings of safety during the day and night, and a reduction in the fear of crime. The Internet café was used by 25% of people for at least 20 min per week. The results suggest that second generation telecare systems and Internet facilities could be more widely used in service delivery, but that lifestyle reassurance requires further development.

A speech-controlled environmental control system for people with severe dysarthria.

Automatic speech recognition (ASR) can provide a rapid means of controlling electronic assistive technology. Off-the-shelf ASR systems function poorly for users with severe dysarthria because of the increased variability of their articulations. We have developed a limited vocabulary speaker dependent speech recognition application which has greater tolerance to variability of speech, coupled with a computerised training package which assists dysarthric speakers to improve the consistency of their vocalisations and provides more data for recogniser training. These applications, and their implementation as the interface for a speech-controlled environmental control system (ECS), are described. The results of field trials to evaluate the training program and the speech-controlled ECS are presented. The user-training phase increased the recognition rate from 88.5% to 95.4% (p<0.001). Recognition rates were good for people with even the most severe dysarthria in everyday usage in the home (mean word recognition rate 86.9%). Speech-controlled ECS were less accurate (mean task completion accuracy 78.6% versus 94.8%) but were faster to use than switch-scanning systems, even taking into account the need to repeat unsuccessful operations (mean task completion time 7.7s versus 16.9s, p<0.001). It is concluded that a speech-controlled ECS is a viable alternative to switch-scanning systems for some people with severe dysarthria and would lead, in many cases, to more efficient control of the home.

The role of telecare in supporting the needs of elderly people.

A literature review was conducted to identify the 'trigger factors' associated with a need for increased levels of care and support for elderly people. An expert panel then prioritized the trigger factors into one of five bands of importance. The literature review produced 2037 hits. Of these, 1768 were excluded after reading the abstract and 111 after reading the full paper, leaving 158 papers for inclusion in the review. From these papers, 102 unique factors that triggered a need for greater care and support among elderly people were identified. The expert panel ranked 36 of the trigger factors into the top three bands of importance. Subsequent analysis suggested that telecare could be used to assist, prevent or minimise the impact of some 66% of these 36 trigger factors and 75% of the top 12 factors. This suggests that telecare has a significant role to play in the support of elderly people and should be a major consideration when re-designing services.

TElehealth in CHronic disease: mixed-methods study to develop the TECH conceptual model for intervention design and evaluation.

OBJECTIVE: To develop a conceptual model for effective use of telehealth in the management of chronic health conditions, and to use this to develop and evaluate an intervention for people with two exemplar conditions: raised cardiovascular disease risk and depression. DESIGN: The model was based on several strands of evidence: a metareview and realist synthesis of quantitative and qualitative evidence on telehealth for chronic conditions; a qualitative study of patients' and health professionals' experience of telehealth; a quantitative survey of patients' interest in using telehealth; and review of existing models of chronic condition management and evidence-based treatment guidelines. Based on these evidence strands, a model was developed and then refined at a stakeholder workshop. Then a telehealth intervention ('Healthlines') was designed by incorporating strategies to address each of the model components. The model also provided a framework for evaluation of this intervention within parallel randomised controlled trials in the two exemplar conditions, and the accompanying process evaluations and economic evaluations. SETTING: Primary care. RESULTS: The TElehealth in CHronic Disease (TECH) model proposes that attention to four components will offer interventions the best chance of success: (1) engagement of patients and health professionals, (2) effective chronic disease management (including subcomponents of self-management, optimisation of treatment, care coordination), (3) partnership between providers and (4) patient, social and health system context. Key intended outcomes are improved health, access to care, patient experience and cost-effective care. CONCLUSIONS: A conceptual model has been developed based on multiple sources of evidence which articulates how telehealth may best provide benefits for patients with chronic health conditions. It can be used to structure the design and evaluation of telehealth programmes which aim to be acceptable to patients and providers, and cost-effective.

Automatic fall detectors and the fear of falling.

We studied the effect of automatic fall detection units on the fear of falling. Participants were community alarm users living in the community aged over 75 years or those aged 60-74 years who had experienced a fall in the previous six months. Of those approached, 31% consented to take part; the main reason given for potential participants declining involvement was that they were happy with the technology they already had. Subjects were assigned to a control group (n = 21) or intervention group (n = 34) based on age, the number of self-reported falls in the previous six months and their score on the self-administered Falls Efficacy Scale (FES), which measures fear of falling on a scale of 0-100, with higher scores indicating less fear. The monitoring period lasted a mean of 17 weeks (SD 3.1). There was no significant difference between the intervention and control groups in their mean ratings of fear of falls (40.3 vs 37.5, difference 2.8, 95% CI 6.2 to 11.8), health-related quality of life or morale. Differences in fear of falling between an intervention subgroup who wore their detector at least occasionally (62%) and those who did not (38%) suggested that some people may benefit from a fall detector while others may lose confidence if they are provided with one. Most users who wore their detectors at least occasionally felt more confident and independent and considered that the detector improved their safety.

A home daily activity simulation model for the evaluation of lifestyle monitoring systems.

Lifestyle monitoring (LM) technology is part of a new generation of telecare which aims to observe the daily activities of older or vulnerable individuals and determine if a medical or care intervention would be beneficial. The development and validation of new LM systems should ideally involve extensive trials with users in real conditions. Unfortunately, effective user trials are very challenging, generally limited in scope and costly. In this paper, a simulator is proposed that can serve to generate synthetic data of daily activity which can then be used as a tool for the validation and development of LM systems. The most challenging part of the simulator is to replicate people's behaviour. In the paper, a novel model of daily activity simulation is proposed. Such daily activities are dependent on a number of external factors that control the need or desire to perform the activity. The proposed simulator aims to reproduce behaviour such that the probability of performing an activity increases until the need is fulfilled. It is possible to parameterise the behavioural model according to a set of features representing a particular individual. The simulator parameters have been populated using real world experiments through hardware testing and data collection with older people. Experimental verification that the desired features are reasonably reproduced by the simulator is provided.

Emotive computing may have a role in telecare.

This brief paper sets out arguments for the introduction of new technologies into telecare and lifestyle monitoring that can detect and monitor the emotive state of patients. The significantly increased use of computers by older people will enable the elements of emotive computing to be integrated with features such as keyboards and webcams, to provide additional information on emotional state. When this is combined with other data, there will be significant opportunities for system enhancement and the identification of changes in user status, and hence of need. The ubiquity of home computing makes the keyboard a very attractive, economic and non-intrusive means of data collection and analysis.

A systematic review of digital interactive television systems and their applications in the health and social care fields.

We conducted a systematic review of the applications and technical features of digital interactive television (DITV) in the health and social care fields. The Web of Knowledge and IEEE Xplore databases were searched for articles published between January 2000 and March 2010 which related to DITV systems facilitating the communication of information to/from an individual's home with either a health or social care application. Out of 1679 articles retrieved, 42 met the inclusion criteria and were selected for review. An additional 20 articles were obtained from online grey literature sources. Twenty-five DITV systems operating in health and social care were identified, including seven commercial systems. The most common applications were related to health care, such as vital signs monitoring (68% of systems) and health information or advice (56% of systems). The most common technical features of DITV systems were two-way communication (88%), medical peripherals (68%), on-screen messaging (48%) and video communication (36%). Digital interactive television has the potential to deliver health and social care to people in their own homes. However, the requirement for a high-bandwidth communications infrastructure, the usability of the systems, their level of personalisation and the lack of evidence regarding clinical and cost-effectiveness will all need to be addressed if this approach is to flourish.

A systematic review of lifestyle monitoring technologies.

The evidence base for lifestyle monitoring is relatively weak, even though there are significant numbers of commercial installations around the world. We conducted a literature review to summarize the current position with regard to lifestyle monitoring based on sensors in the home. In total, 74 papers met the inclusion criteria. Only four papers reported trials involving 20 or more subjects, with a further 21 papers reporting trials involving one or more subjects. Most papers (n = 49) were concerned with technology development. Motion detection was the most common of the technologies employed, followed by door and electrical appliance usage. The predominant monitoring strategy was that of detecting changes in activity. However, little attention has been given to determining when or how changes in the profile of activity should be used to raise a call for assistance from a health or care professional. Lifestyle monitoring remains a relatively immature research area in which there is little detailed understanding of how to provide comprehensive and effective systems.

Predicting need for intervention in individuals with congestive heart failure using a home-based telecare system.

We have studied how well the need for a medical intervention can be predicted by a telecare monitoring system. During a study period of about 18 months, 45 elderly individuals with congestive heart failure used a home health monitor to enter daily information pertaining to their symptoms and health status. A total of 8576 alerts were generated by the monitoring system, although in most cases, patient and service provider interaction was not required. When system alerts were considered to be serious, or if symptoms persisted, the patient was contacted. A total of 171 key medical events (6 deaths; 28 hospital admissions; 59 changes in medication; 54 cases of advice given; 24 instances where immediate medical attention was recommended) were recorded in the monitoring logs. A multivariate logistic regression model was developed to predict these medical interventions/events. The model correctly predicted key medical events in 75% of cases with a specificity of 74% and an overall cross-validated accuracy of 74% (95% CI, 68-80%). Key predictors included the number of system alerts, self-rated mobility, self-rated health and self-rated anxiety. This suggests that subjective measures are useful in addition to physiological ones for predicting health status. A multivariate decision support model has potential to supplement practitioners and current telecare systems in identifying heart failure patients in need of medical intervention.