Integrated Telehealth and Telecare for Monitoring Frail Elderly with Chronic Disease.

Objective: To investigate the potential of an integrated care system that acquires vital clinical signs and habits data to support independent living for elderly people with chronic disease. Materials and Methods: We developed an IEEE 11073 standards-based telemonitoring platform for monitoring vital signs and activity data of elderly living alone in their home. The platform has important features for monitoring the elderly: unobtrusive, simple, elderly-friendly, plug and play interoperable, and self-integration of sensors. Thirty-six (36) patients in a primary care practice in the United Kingdom (mean [standard deviation] age, 82 [10] years) with congestive heart failure (CHF) or chronic obstructive pulmonary disease (COPD) were provided with clinical sensors to measure the vital signs for their disease (blood pressure [BP] and weight for CHF, and oxygen saturation for COPD) and one passive infrared (PIR) motion sensor and/or a chair/bed sensor were installed in a patient's home to obtain their activity data. The patients were asked to take one measurement each day of their vital signs in the morning before breakfast. All data were automatically transmitted wirelessly to the remote server and displayed on a clinical portal for clinicians to monitor each patient. An alert algorithm detected outliers in the data and indicated alerts on the portal. Patient data have been analyzed retrospectively following hospital admission, emergency room visit or death, to determine whether the data could predict the event. Results: Data of patients who were monitored for a long period and had interventions were analyzed to identify useful parameters and develop algorithms to define alert rules. Twenty of the 36 participants had a clinical referral during the time of monitoring; 16 of them received some type of intervention. The most common reason for intervention was due to low oxygen levels for patients with COPD and high BP levels for CHF. Activity data were found to contain information on the well-being of patients, in particular for those with COPD. During exacerbation the activity level from PIR sensors increased slightly, and there was a decrease in bed occupancy. One subject with CHF who felt unwell spent most of the day in the bedroom. Conclusions: Our results suggest that integrated care monitoring technologies have a potential for providing improved care and can have positive impact on well-being of the elderly by enabling timely intervention. Long-term BP and pulse oximetry data could indicate exacerbation and lead to effective intervention; physical activity data provided important information on the well-being of patients. However, there remains a need for better understanding of long-term variations in vital signs and activity data to establish intervention protocols for improved disease management.

Evaluation of the National Health Service (NHS) Direct Pilot Telehealth Program: Cost-Effectiveness Analysis.

OBJECTIVE: To evaluate the cost-effectiveness of a pilot telehealth program applied to a wide population of patients with chronic obstructive pulmonary disease (COPD). DESIGN: Vital signs data were transmitted from the home of the patient on a daily basis using a patient monitoring system for review by community nurse to assist decisions on management. SETTING: Community services for patients diagnosed with COPD. PARTICIPANTS: Two Primary Care Trusts (PCTs) enrolled 321 patients diagnosed with COPD into the telehealth program. Two hundred twenty-seven (n = 227) patients having a complete baseline record of at least 88 days of continuous remote monitoring and meeting all inclusion criteria were included in the statistical analysis. INTERVENTION: Remote monitoring. METHODS: Resource and cost data associated with patient events (inpatient hospitalization, accident and emergency [A&E], and home visits) 12 months before, immediately before and during monitoring, equipment, start-up, and administration were collected and compared to determine cost-effectiveness of the program. MAIN OUTCOME MEASURES: Cost-effectiveness of program, impact on resource usage, and patterns of change in resource usage. RESULTS: Cost-effectiveness was determined for the two PCTs and the two periods before monitoring to provide four separate estimates. Cost-effectiveness had high variance both between the PCTs and between the comparison periods ranging from a saving of £140,800 ($176,000) to an increase of £9,600 ($12,000). The average saving was £1,023 ($1,280) per patient per year. The largest impact was on length of stay with a fall in the average length of inpatient care in PCT1 from 11.5 days in the period 12 months before monitoring to 6.5 days during monitoring, and similarly in PCT2 from 7.5 to 5.2 days. CONCLUSION: There was a wide discrepancy in the results from the two PCTs. This places doubt on outcomes and may indicate also why the literature on cost-effectiveness remains inconclusive. The wide variance on savings and the uncertainty of monitoring cost do not allow a definitive conclusion on the cost-effectiveness as an outcome of this study. It might well be that the average saving was £1,023 ($1,280) per patient per year, but the variance is too great to allow this to be statistically significant. Each locality-based clinical service provides a service to achieve the same clinical goal, but it does so in significantly different ways. The introduction of remote monitoring has a profound effect on team learning and clinical practice and thus distorts the cost-effectiveness evaluation of the use of the technology. Cost-effectiveness studies will continue to struggle to provide a definitive answer because outcome measurements are too dependent on factors other than the technology.

Clinical Relevance of the First Domomedicine Platform Securing Multidrug Chronotherapy Delivery in Metastatic Cancer Patients at Home: The inCASA European Project.

BACKGROUND: Telehealth solutions can improve the safety of ambulatory chemotherapy, contributing to the maintenance of patients at their home, hence improving their well-being, all the while reducing health care costs. There is, however, need for a practicable multilevel monitoring solution, encompassing relevant outputs involved in the pathophysiology of chemotherapy-induced toxicity. Domomedicine embraces the delivery of complex care and medical procedures at the patient's home based on modern technologies, and thus it offers an integrated approach for increasing the safety of cancer patients on chemotherapy. OBJECTIVE: The objective was to evaluate patient compliance and clinical relevance of a novel integrated multiparametric telemonitoring domomedicine platform in cancer patients receiving multidrug chemotherapy at home. METHODS: Self-measured body weight, self-rated symptoms using the 19-item MD Anderson Symptom Inventory (MDASI), and circadian rest-activity rhythm recording with a wrist accelerometer (actigraph) were transmitted daily by patients to a server via the Internet, using a dedicated platform installed at home. Daily body weight changes, individual MDASI scores, and relative percentage of activity in-bed versus out-of-bed (I

Designing effective visualizations of habits data to aid clinical decision making.

BACKGROUND: Changes in daily habits can provide important information regarding the overall health status of an individual. This research aimed to determine how meaningful information may be extracted from limited sensor data and transformed to provide clear visualization for the clinicians who must use and interact with the data and make judgments on the condition of patients. We ascertained that a number of insightful features related to habits and physical condition could be determined from usage and motion sensor data. METHODS: Our approach to the design of the visualization follows User Centered Design, specifically, defining requirements, designing corresponding visualizations and finally evaluating results. This cycle was iterated three times. RESULTS: The User Centered Design method was successfully employed to converge to a design that met the main objective of this study. The resulting visualizations of relevant features that were extracted from the sensor data were considered highly effective and intuitive to the clinicians and were considered suitable for monitoring the behavior patterns of patients. CONCLUSIONS: We observed important differences in the approach and attitude of the researchers and clinicians. Whereas the researchers would prefer to have as many features and information as possible in each visualization, the clinicians would prefer clarity and simplicity, often each visualization having only a single feature, with several visualizations per page. In addition, concepts considered intuitive to the researchers were not always to the clinicians.

Tele-Monitoring of Cancer Patients' Rhythms during Daily Life Identifies Actionable Determinants of Circadian and Sleep Disruption.

The dichotomy index (I < O), a quantitative estimate of the circadian regulation of daytime activity and sleep, predicted overall cancer survival and emergency hospitalization, supporting its integration in a mHealth platform. Modifiable causes of I < O deterioration below 97.5%-(I < O)low-were sought in 25 gastrointestinal cancer patients and 33 age- and sex-stratified controls. Rest-activity and temperature were tele-monitored with a wireless chest sensor, while daily activities, meals, and sleep were self-reported for one week. Salivary cortisol rhythm and dim light melatonin onset (DLMO) were determined. Circadian parameters were estimated using Hidden Markov modelling, and spectral analysis. Actionable predictors of (I < O)low were identified through correlation and regression analyses. Median compliance with protocol exceeded 95%. Circadian disruption-(I < O)low-was identified in 13 (52%) patients and four (12%) controls (p = 0.002). Cancer patients with (I < O)low had lower median activity counts, worse fragmented sleep, and an abnormal or no circadian temperature rhythm compared to patients with I < O exceeding 97.5%-(I < O)high-(p < 0.012). Six (I < O)low patients had newly-diagnosed sleep conditions. Altered circadian coordination of rest-activity and chest surface temperature, physical inactivity, and irregular sleep were identified as modifiable determinants of (I < O)low. Circadian rhythm and sleep tele-monitoring results support the design of specific interventions to improve outcomes within a patient-centered systems approach to health care.

Early experience in using telemonitoring for the management of chronic disease in primary care.

We have investigated the use of telemonitoring in three long-term conditions: chronic heart failure (CHF), type 2 diabetes and essential hypertension. Participants were provided with a home telemonitoring unit for a 12-week period and entered physiological data each day. The data were sent automatically via the participant's telephone line to a server and could be viewed via a web browser. An intervention algorithm was developed to improve the accuracy with which patients requiring intervention were recognized compared to existing systems based on a simple threshold. Thirty patients completed the 12-week trial. One patient dropped out, giving data on 29 patients (mean age 70 years, 17 women). The algorithm prompted a clinical intervention in 11 patients (38%). The average time that elapsed before the first intervention was 47 days (SD 21). Primarily the interventions (72%) resulted in changes to medication and health advice. The results suggest that four weeks is sufficient time in which to recognize the need to intervene clinically and that in 12 weeks it is possible to effect a change towards a target.

An automated personalised intervention algorithm for remote patient monitoring.

An automated personalised intervention algorithm was developed to determine when and if patients with chronic disease in a remote monitoring programme required intervention for management of their condition. The effectiveness of the algorithm has so far been evaluated on 29 patients. It was found to be particularly effective in monitoring newly diagnosed patients, patients requiring a change in medication as well as highlighting those that were not conforming to their medication. Our approach indicates that RPM used with the intervention algorithm and a clinical protocol can be effective in a primary care setting for targeting those patients that would most benefit from monitoring.

Dynamic Threshold Analysis of Daily Oxygen Saturation for Improved Management of COPD Patients.

This study presents a novel dynamic threshold algorithm that is applied to daily self-measured SpO2 data for management of chronic obstructive pulmonary disease (COPD) patients in remote patient monitoring to improve accuracy of detection of exacerbation. Conventional approaches based on a fixed threshold applied to a single SpO 2 reading to detect deterioration in patient condition are known to have poor accuracy and result in high false alarm rates. This study develops and evaluates use of a dynamic threshold algorithm to reduce false alarm rates. Daily data from four COPD patients with a record of clinical interventions during the period were selected for analysis. We model the SpO2 time-series data as a combination of a trend and a stochastic component (residual). We estimate the long-term trend using a locally weighed least-squares (low-pass) filter over a long-term processing window. Results show that the time evolution of the long-term trend indicated exacerbation with improved accuracy compared to a fixed threshold in our study population. Deterioration in the condition of a patient also resulted in an increase in the standard deviation of the residual (σres ), from 2% or less when the patient is in a healthy condition to 4% or more when condition deteriorates. Statistical analysis of the residuals showed they had a normal distribution when the condition of the patient was stable but had a long tail on the lower side during deterioration.

Realization of a service for the long-term risk assessment of diabetes-related complications.

AIM: We present a computerized system for the assessment of the long-term risk of developing diabetes-related complications. METHODS: The core of the system consists of a set of predictive models, developed through a data-mining/machine-learning approach, which are able to evaluate individual patient profiles and provide personalized risk assessments. Missing data is a common issue in (electronic) patient records, thus the models are paired with a module for the intelligent management of missing information. RESULTS: The system has been deployed and made publicly available as Web service, and it has been fully integrated within the diabetes-management platform developed by the European project REACTION. Preliminary usability tests showed that the clinicians judged the models useful for risk assessment and for communicating the risk to the patient. Furthermore, the system performs as well as the United Kingdom Prospective Diabetes Study (UKPDS) Risk Engine when both systems are tested on an independent cohort of UK diabetes patients. CONCLUSIONS: Our work provides a working example of risk-stratification tool that is (a) specific for diabetes patients, (b) able to handle several different diabetes related complications, (c) performing as well as the widely known UKPDS Risk Engine on an external validation cohort.

Early experiences of the use of remote patient monitoring for the long term management of chronic disease.

We describe our experiences of using remote patient monitoring to support the long term management and clinical intervention in patients with chronic disease. Within the project we developed new algorithms to determine from vital signs collected on a daily basis, those patients requiring clinical investigation for their condition. Our aim was for patients to achieve and sustain clinically recommended values for parameters. In our study, the telemonitoring prompted clinical intervention in 37% of patients. Our approach proved particularly effective for the newly diagnosed, and for those with long term issues of management.