Effects of Home Telemonitoring to Support Improved Care for Chronic Obstructive Pulmonary Diseases

Abstract

Objective: To assess the impact of a home telemonitoring technology on patients with chronic obstructive pulmonary disease in terms of care satisfaction, patient empowerment, improved quality of life, and utilization of hospital and home care. Design: A quasi-experimental retrospective and prospective design was developed with a matched control group to compare the effects of telemonitoring (the experimental group, n = 23) with the traditional homecare offering (the control group, n = 23). Measurements: Satisfaction, patient empowerment, and quality of life were measured using validated Likert scales, whereas the data on care utilization were collected from the participating patients' medical record. Results: Mixed results were observed. The clinical effects of home telemonitoring were very positive in terms of patients' satisfaction and empowerment. The perceptions of care providers as well as those of patients were congruent in this respect. Also, the study suggests that telemonitoring may have a positive effect on quality of life for patients with chronic obstructive pulmonary diseases. In contrast, the results were disappointing in terms of resource savings for the use of both homecare and hospital care. Conclusion: Capturing the full potential of these new technologies will require a much more fundamental reorganization of work than just a simple deployment of the technology.

Introduction

The increasing prevalence of chronic diseases is placing a growing burden on the health systems of industrialized countries. In 2000, the prevalence of chronic obstructive pulmonary diseases (COPDs) among adults around the world ranged from 0.5% in certain parts of Africa to 3% to 4% in North America.¹ In the European Union, the total direct cost of respiratory diseases is estimated at 6% of total healthcare budgets, with COPDs accounting for 56% of this cost.² The total direct cost of COPDs in the United States in 2002 has been estimated at $18 billion (U.S. dollars).² In Canada, the COPD hospitalization costs are estimated at $1.5 billion (Canadian dollars) per year.³

To meet this challenge, many observers recommend innovative clinical approaches to encourage systematic monitoring of a patient's state of health and greater patient involvement in the management of their illness.^4
–6 In this sense, information technologies are an attractive alternative in terms of their capacity to provide remote patient monitoring and be used for communications between patients and their care providers.^7,8

To better understand the potential of these technologies, this article presents the results of a study that analyzed the impact of a home telemonitoring intervention with COPD patients. The study sought to assess a wide range of effects—satisfaction, patient empowerment, improved quality of life, and utilization of hospital and home care—from the points of view of both patients and the professionals providing homecare.

Background

Home telemonitoring may be defined as the use of information and communication technologies in exchanges of information between the patients' homes and health professionals. Typically, a communication system is installed in the patients' home so that they can use it regularly, entering information on their condition. This information is transferred in real time to a central data management system, the purpose of which is to systematically monitor a patient's state of health based on personalized care protocols. Through pre-programmed intelligent functions, the system is able to sound an alarm if the patient's condition stays beyond certain predefined parameters as well as provide decision support directly to the patient or the care team. This allows the clinical team to remotely monitor patient data and quickly respond as required. Telemonitoring can also encourage the patients to become involved in the management of their own condition, while it also allows for systematic monitoring through an efficient investment of professional resources, who usually intervene from a remote location. Empowering a patient to more effectively monitor their own condition—when combined with regular, systematic remote monitoring—may prevent an excessive decline in the patient's clinical condition and decrease both decompensation and acute-phase hospital care.

The studies on the effects of home telemonitoring for COPD patients have mostly examined the potential savings in terms of hospital resources.^9,10 A reduction in hospitalizations is the most frequently reported effect,^11

–16 and the net savings can be quite significant. Two studies have assessed these savings at between 12% and 17%.^14,15 However, a more recent economic analysis, designed as a randomized controlled clinical trial, found no significant savings.¹⁷ Besides, studies that have examined utilization of emergency services found no effects.^12,13 The only study that analyzed the use of the resources in the patient's home gave mixed results: it found that the savings in terms of care providers (fewer home visits) were eliminated by increased salary expenses for the nursing staff in charge of the remote monitoring.¹⁵ Thus, no consistent evidence exists in relation to the extent to which home telemonitoring reduces the utilization of health services.

Few studies on COPDs also analyzed the clinical impacts of home telemonitoring. Two results were constant and positive: patient satisfaction was high,^11,14,15,17 and telemonitoring reduced the number of decompensations.^11,14,16 The analyses of quality-of-life effects produced mixed results: in one study they were positive,¹⁷ but in the other they were negative.¹⁶ No study analyzed the effects of telemonitoring on patient empowerment.

Methods

Technology Used

A telemonitoring technology was acquired in 2007 by a regional homecare program that serves 48 urban and rural municipalities (220,650 inhabitants) in Quebec, Canada. The targeted clients were patients with COPD. Enough devices were acquired to serve 15 to 20 patients at a time. The present study was conducted with the second wave of patients so that the clinical teams would have had sufficient time to become familiar with the new system.

The device installed in the patient's home was a Web phone equipped with a touch-screen monitor. The patients used their Web phones every day to enter data as requested by a software program developed to monitor COPD. The data were sent over the Internet in real time, so that the patients' condition and their compliance with treatment could be monitored remotely. The system also automatically interacted with the patient based on predetermined parameters to alert the patient and provide advice tailored to changes in their condition. Through their interactions with the system, the patients were better able to understand the relations between their habits and their health conditions leading to a useful empowerment. The system also sent warning messages to a surveillance center that operated 24 h a day, 7 days a week. The nursing staff and the center would then contact the patient by telephone. Finally, the telemonitoring intervention was temporary; it was to serve the purpose of patient education. The goal was to train the patient to become involved in the management of their own clinical condition through a better understanding of relationships between their health and their life habits. The telemonitoring service was ended when the patient had acquired the necessary knowledge and adopted the desired behaviors.

The system was the Remote Patient Monitoring solution marketed by Telus, one of Canada's largest telecommunications companies. At the time of the new system's acquisition, the regional home care program thought that it would meet a growing need for home care and help address the problem of staff shortages by reducing the number of home visits for each patient.

Study Design

A quasi-experimental retrospective and prospective design was developed with a matched control group to compare the effects of telemonitoring with the traditional homecare offering. The patient served as the unit of analysis. The experimental group was formed from March 2008 to December 2008 from the patients in the second wave of patients benefiting from the new telemonitoring system. Patients were selected according to a strict set of inclusion and exclusion criteria. The patients had to have severe COPD that required frequent home visits. Patients were excluded if they had psychological or cognitive problems that would prevent them from participating in their treatment or if they had visual or motor impairments that would prevent them from using the technology. The patients in the control group were recruited from the same homecare program. Since only a limited number of telemonitoring devices were available, it was possible to have enough subjects who were receiving their homecare in the traditional manner. To reduce the differences between the two groups, each patient in the control group was individually matched to a patient in the experimental group. The matching criteria were age, sex, and the severity of their illness. The study was approved by university ethics authorities.

Variables and Data Sources

The effects of telemonitoring were assessed on four dimensions: satisfaction, patient empowerment, quality of life, and care utilization. The first three dimensions were measured using validated Likert scales. First, an overall assessment of patient satisfaction was made using a validated scale¹⁸ to examine all the homecare they had received. Further, the satisfaction with the telemonitoring intervention was measured using validated scales: five for the patients' perceptions and two for the nurses' perceptions.¹⁹ Second, an overall assessment of patient empowerment was made for all the homecare received using scales from validated instruments.^20
–22 Further validated scales were used to measure the benefits of the telemonitoring system perceived by the patients and their nurses.^23,24 Satisfaction and empowerment were assessed in the days following the end of the telemonitoring period. Detailed information on those scales is provided in Appendixes A and B. Third, quality of life was measured using the Medical Outcome Study–short form 12 items (MOS-SF12) scale²⁵ at the beginning and end of the telemonitoring intervention. Fourth, use of homecare and hospital care was measured retrospectively (over 15 months) and prospectively (the telemonitoring period + 3 months). Five variables were used for homecare: number of home visits and number of hours of homecare provided, respectively, by nurses and by respiratory therapists, and number of phone calls initiated by the patient, the nursing staff, and the surveillance center. Three variables were used for hospital care: number of visits to an emergency department, number of hospitalizations, and length of hospital stay. These variables were documented from each patient's clinical record, which also provided data on patient characteristics and the severity of their illnesses.

Results

Patient Characteristics

The study was based on a total of 46 patients evenly distributed between the experimental group and the control group. Table 1 presents the characteristics of these patients. Their average age was close to 75 years. They were severely ill patients, with half of them classified in the highest level of the scale used to measure COPD severity. Two patients died during the course of study. The comparative analysis of the experimental and control groups showed that the matching strategy was effective. Only the age variable registered a difference that was statistically significant, and this difference was slight, with a deviation of <2 years.

Table 1.

Characteristics of the Patients Who Participated in the Study

	Experimental Group (N = 23), Mean (SD)	Control Group (N = 23), Mean (SD)	Paired Comparative Test (T-Test/Chi-Square), P-Value
Gender			NS
Female	10	10
Male	13	13
Age	73.7 (9.6)	75.4 (9.7)	0.02
Severity of the illness^a
Mild	3	3	NS
Moderate	8	7
Severe	12	13
Oxygen therapy in the home	6	3	NS
Death	1	1	NS
Average number of days of telemonitoring	146.7 (72.3)	NA	NA

Classification of the COPD according to the seriousness of symptoms and the disability, based on the recommendations of the Canadian Thoracic Society. Mild severity, shortness of breath from COPD when hurrying on the level or walking up a slight hill; moderate severity, shortness of breath from COPD causing the patient to stop after walking about 100 m (or after a few minutes) on the level; severe, shortness of breath from COPD resulting in the patient being too breathless to leave the house, breathlessness after dressing/undressing, or the presence of chronic respiratory failure or clinical signs of right heart failure.

COPD, chronic obstructive pulmonary disease; NS, not significant; SD, standard deviation; NA, non-applicable.

Psychometric Qualities of Satisfaction and Empowerment Measures

Overall, the coefficients of internal consistency (Cronbach's α) of the measurement scales were satisfactory ranging from 0.58 to 0.94 for satisfaction and 0.52 to 0.84 for empowerment (Table 2). Even though four measures did not attain the minimal threshold of 0.70,²⁶ we kept these variables because they were of interest.

Table 2.

Measurement of the Effects of Homecare and Telemonitoring in Terms of Satisfaction and Empowerment

	Experimental Group			Control Group
Satisfaction	No. of Items	α	Mean (SD)	α	Mean (SD)	Paired Comparative Test, P-Value
Overall assessment of patient homecare satisfaction^a	9	0.94	4.5 (0.5)	0.90	4.5 (0.5)	0.84
Patient satisfaction with Telemonitoring^a
Information quality	3	0.66	4.6 (0.5)	NA	NA	NA
Information usefulness	1	—	4.2 (1.4)	NA	NA	NA
Telemonitoring ease of use	3	0.58	4.7 (0.4)	NA	NA	NA
Technical performance	1	—	4.2 (0.8)	NA	NA	NA
Overall telemonitoring satisfaction	1	—	4.6 (0.8)	NA	NA	NA
Nurses satisfaction with telemonitoring^b
Contribution to quality of care	5	0.64	7.9 (1.1)	NA	NA	NA
Usefulness of telemonitoring	3	0.93	8.0 (1.8)	NA	NA	NA

Empowerment
Perceptions of patients
Homecare overall assessment^a
Patient participation in the management of their illness	3	0.74	3.9 (1.0)	0.82	3.6 (1.1)	0.28
Patient's skills in managing their illness	4	0.77	4.2 (0.7)	0.85	3.8 (1.1)	0.25
Benefits in terms of compliance with their medication regime	2	0.54	4.4 (0.6)	0.52	4.6 (0.7)	0.49
Telemonitoring benefits in terms of self-care	4	0.71	3.6 (1.0)	NA	NA	NA
Perceptions of professionals^b
Telemonitoring
Improved patient knowledge	3	0.84	7.7 (1.5)	NA	NA	NA
Improved self-care	4	0.84	7.0 (1.4)	NA	NA	NA
Dependence on the technology^c	1	—	8.3 (1.7)	NA	NA	NA

Five-step Likert scale (very little [1] to very good [5]). We had intended to use only scales of 10 levels, but the pre-test demonstrated that this type of scale is difficult to administer to elderly patients over the telephone, so the patient scales were reduced to 5 levels.

Ten-step Likert scale (very little [1] to very good [10]).

A negative-value item.

Satisfaction

Patients' overall satisfaction with their homecare was very high (4.5 on a scale of 5). No difference was found between the experimental and the control groups. The patients in the experimental group were also very satisfied with their telemonitoring: three out of the five measures assessing telemonitoring were higher than the scores obtained for homecare as a whole. The care providers' satisfaction with telemonitoring was also very positive. Their satisfaction with quality of care and the usefulness of telemonitoring were 7.9 and 8.0 out of 10.

Patient Empowerment

The patients' overall perception that they could managed their own care through homecare was positive. The three measures of empowerment were high (3.9–4.4 on a scale of 5) in both the experimental and control groups. No significant difference was found between the two groups. The effect of telemonitoring alone was also positively assessed by the patients in the experimental group. However, the care providers' reported mixed perceptions of the telemonitoring. They gave positive assessments of improvements to patients' knowledge of how to manage their own illness and their ability to care for themselves, but made severe judgments of its effect on the patients' dependence on the telemonitoring service.

Patient Quality of Life

The analysis comparing the beginning with the end of the intervention showed that quality of life in the experimental group was stable over the period (Table 3). In contrast, the analysis for the control group showed significant deterioration in quality of life over the same period. Similarly, the initial statistically significant difference between the groups in terms of a better patient perception of physical health disappeared over the course of the study period. This finding, that perceived quality of life was unchanged in the experimental group while it felt significantly in the control group, suggests that telemonitoring has positive effects.

Table 3.

The Effects of Homecare and Telemonitoring on Patient Quality of Life^a

Quality of Life (SF12)	Experimental (N = 22), Mean (SD)	Control (N = 22), Mean (SD)	Paired Intergroup T-Test, P-Value
Pre-telemonitoring
Scale for physical health	32.1 (17.9)	44.9 (23.6)	0.03
Scale for emotional health	55.3 (23.0)	58.1 (30.7)	0.78
Post-telemonitoring
Scale for physical health	27.9 (14.8)	37.5 (19.5)	0.15
Scale for emotional health	54.5 (24.2)	45.5 (20.8)	0.16
Paired pre-post telemonitoring t-test	p-value	p-value
Scale for physical health	0.26	0.03
Scale for emotional health	0.89	0.03

MOS-SF12 (Medical Outcome Study–short form 12 items) (Gandek et al.²⁵).

Care Utilization

Finally, the study analyzed the effects of telemonitoring in terms of resource savings. The results were mixed (Table 4). First, the experimental group's use of homecare increased over the period of the study. The number and length of visits by respiratory therapists increased significantly, and there was a large increase in telephone calls. Second, the results on hospitalizations were also mixed. While the number of hospitalizations fell, the length of such stays was unchanged. No reduction in the length of hospital stays suggests that even if the patients with telemonitoring were hospitalized less often, once they were in hospital, they stayed there just as long. Further, the number of visits to emergency departments was unchanged over the period.

Table 4.

Measuring the Effects of Telemonitoring in Terms of Homecare Utilization and Hospital Care^a

	Experimental Group		Control Group
	Pre-Telemonitoring		Pre-Telemonitoring
Homecare	No., Mean (SD)	Los (Min), Mean (SD)	No., Mean (SD)	Los (Min), Mean (SD)	Paired Comparative Intergroup Test, P-Value
Respiratory therapists visits	0.36 (0.08)	18.5 (4.0)	0.43 (0.10)	23.1 (5.8)	0.60	0.52
Nurses visits	0.73 (0.12)	29.9 (4.5)	0.68 (0.14)	26.0 (5.6)	0.80	0.58
Phone calls	0.06 (0.02)	—	0.01 (0.00)	—	0.02	—

	Post-Telemonitoring		Post-Telemonitoring
Respiratory therapists visits	0.46 (0.08)	23.9 (4.5)	0.65 (0.19)	36.6 (12.7)	0.36	0.38
Nurses visits	0.65 (0.12)	24.3 (4.2)	1.10 (0.38)	37.0 (12.2)	0.32	0.37
Phone calls	1.14 (0.15)	—	0.04 (0.03)	—	0.00	—

Paired comparative pre-post test	P-Value	P-Value	P-Value	P-Value
Respiratory therapists visits	0.08	0.03	0.18	0.25
Nurses visits	0.81	0.22	0.22	0.34
Phone calls	0.00	—	0.21	—

	Pre-Telemonitoring		Pre-Telemonitoring
Hospital Care	No., Mean (SD)	Los (Days), Mean (SD)	No., Mean (SD)	Los (Days), Mean (SD)	Paired Comparative Intergroup Test, p-Value
ER visits	0.13 (0.03)	—	0.04 (0.01)	—	0.01	—
Hospitalizations	0.09 (0.02)	0.58 (0.16)	0.02 (0.01)	0.15 (0.05)	0.01	0.01

	Post-Telemonitoring		Post-Telemonitoring
ER visits	0.10 (0.04)	—	0.05 (0.03)	—	0.34	—
Hospitalizations	0.05 (0.02)	0.55 (0.29)	0.03 (0.02)	0.22 (0.15)	0.65	0.35

Paired Comparative Pre-Post Test	P-Value	P-Value	P-Value	P-Value
ER visits	0.33	—	0.71	—
Hospitalizations	0.04	0.84	0.80	0.76

The care utilization data are presented in the form of monthly averages per patient to control for unequal observation periods between the pre-period and the post-period, which accumulated the length of the intervention (average of 4.8 months), and a period of 3 additional months.

LOS, length of stay; ER, emergency room.

Discussion

The main results of the study may be summarized as follows. First, they support a consistent result in the literature that patients have a favorable attitude to home telemonitoring.^11,14,15,17 In addition, the study has filled a gap that was recently identified in a systematic review that noted a lack of studies on care providers' attitudes toward home telemonitoring.¹⁰ This study shows very positive satisfaction on the part of care providers. These positive results concerning patients' and care providers' attitudes should help reassure some observers who have voiced fears that an ill and very old population will not be able to make appropriate use of these new technologies.

Second, the study makes a relevant contribution by analyzing the effects of telemonitoring on the empowerment of patients with COPD. It shows that telemonitoring can have positive effects by improving patients' attitudes and behaviors concerning their ability to manage their own conditions. These results were supported by their care providers, who reported that they too had seen improvements in their patients. The concern care providers had—concerning the creation of a dependency among patients toward the technology—may be perceived as minor, inasmuch as it was possible to withdraw the telemonitoring system from all patients as planned. This result suggests interesting opportunities to redefine the role played by home telemonitoring, which until now has often been presented as a permanent device for systematic patient monitoring. The concept of a temporary intervention that could empower patients to manage their own illnesses would appear promising, since it may reduce costs and address the problem of how to attain sustained use of the technology. Indeed, it has been observed in a systematic review that the perseverance of patients to send the data that are required regularly for continuous and systematic monitoring of their health diminished over time.¹⁰

Third, the study suggests that telemonitoring may have a positive effect on quality of life for patients with COPD. This result needs to be interpreted carefully, however, since it is based on the observation that the quality of life of patients in the control group declined over the study period, whereas the quality of life of patients in the experimental group was unchanged. Of the two other studies that examined this issue, one reported no effect¹⁶ and the other reported a positive effect.¹⁷

Finally, the results were rather disappointing in terms of any savings in resources. First, the present study found the opposite in terms of homecare. The use of homecare nurses was unchanged, whereas the use of respiratory therapists increased. In this respect, we must point out that the model of care was not changed to reflect the use of telemonitoring. This decision was made to minimize the organizational change attributable to the introduction of a new technology, and we believe that it resulted in a decrease in the potential savings. Further, much like other researchers,¹⁶ we found that telemonitoring could generate significant costs in terms of the nursing staff required by activities in the surveillance center that maintains contact with patients. The results on use of hospital services were also disappointing. Even if the study supports earlier findings from several studies that the number of hospitalizations is reduced,^11,13

–16 we did not find a corresponding decrease in the length of hospital stays. Despite the fact that the patients in the experimental group were hospitalized less often, they stayed in hospital just as long as the patients in the control group. This negative result validates the findings of another study.¹² However, there was a potential for cost avoidance, to the extent that the number of hospitalizations had decreased. Such results allow us to emphasize the importance of envisaging a large spectrum of changes—for instance, changes to care practices and corridors of care—if real resource savings are to be achieved. Finally, we did not find a reduction in visits to emergency departments; this also supports the findings of another study.¹³

In the face of this inability to achieve the desired effects, the new technology does not represent the only cause. Our field interviews reveal that insufficient efforts had been made to transform the nature of work at the time of the study, such that the full potential of the technology could not be realized. No reorganization of the nurses' care plans was attempted to reduce the number of homecare visits. This stands as another of the important lessons of the present study. The technology alone cannot achieve the desired results; significant effort must also be made to reorganize work. Also, the example of an increase in telephone calls in the experimental group provides a good demonstration of the challenges in trying to design an efficient home telemonitoring system that can attain a balance between patient empowerment and the system's sensitivity in terms of alerts triggered at the surveillance center to ensure patient security. In addition, the savings achieved in hospital care requires closer coordination with the hospital to ensure continuity of care and ensure that the patient can be swiftly returned to the community.

Finally, these results should not be interpreted without taking into account certain limitations of this study. First, the sample was small, and this may have prevented the detection of certain effects. Second, our results are based on 3 months of post-intervention measures. It would have strengthened our results to be able to take more measures over a longer period, such as at 6 and 12 months. This would have improved the strength of our measures of impact and sustainability. Third, the large number of telephone calls made by members of the nursing staff at the surveillance center may have had a positive impact on patient satisfaction, empowerment, and quality of life. Such frequent personal contact between nurses and patients is not typically associated with remote interventions. In other words, the remote intervention under study was not based uniquely on the Web phone; it also featured more frequent telephone conversations between care providers and patients.

Conclusions

If we want to confront the growing problem of the amount of resources required to manage patients with chronic health conditions, we must acknowledge that a deployment of such technology is not in itself enough to generate the desired effects. Capturing the full potential of these new technologies will require a much more fundamental reorganization of work than just a simple deployment of the technology. Consistent and significant changes will be required in the care practices used by clinical teams and in the corridors of care between primary and secondary care.

Footnotes

Acknowledgments

The Canadian Institutes of Health Research (CIHR) are gratefully acknowledged for their financial support.

Disclosure Statement

No competing financial interests exist.

Appendix

Appendix B.

Description of the Scales Measuring Empowerment

	Experimental (N = 20), Mean (SD)	Control (N = 20), Mean (SD)	Intergroup Test, P-Value
Measure of patient participation in the management of their illness (3 items: 5-step Likert scale)	3.9 (1.0) α = 0.74	3.6 (1.1) α = 0.82	0.28
Over the last 3 months, … 1. Were you asked for your opinion when your treatment plan was being developed?	3.7 (1.4)	3.4 (1.3)	0.41
2. Were you involved in decision making about your care and treatment?	4.2 (1.1)	3.7 (1.2)	0.20
3. Were you asked if you had any problems following the recommended treatment?	4.0 (1.0)	3.8 (1.4)	0.57
Measure of patient skills in managing their illness (4 items: 5-step Likert scale)	4.2 (0.7) α = 0.77	3.8 (1.1) α = 0.85	0.25
1. Were you taught things that helped you gain more control over your illness?	4.3 (1.1)	4.2 (1.2)	0.91
2. Are you confident that you'll be able to take care of yourself in a way that will make you less likely to consult a physician?	3.7 (1.2)	4.0 (1.3)	0.51
3. Are you confident that you'll be able to do something other than take medication to reduce the symptoms you experience in your everyday life?	4.2 (0.8)	3.4 (1.4)	0.05
4. Are you confident that you'll be able to know when changes in your health mean that you should contact a doctor or nurse?	4.6 (0.7)	3.7 (1.4)	0.03
Measure of compliance with a medication regime (2 items: 5-step Likert scale)	4.4 (0.6) α = 0.54	4.6 (0.7) α = 0.52	0.49
1. Do you always take your medication as prescribed by your doctor?	4.8 (0.4)	4.8 (0.4)	1.00
2. When you feel well, do you ever stop taking medication that you should be taking on a regular basis?	2.1 (1.5)	1.7 (1.2)	0.42
Benefits perceived by the patient in their use of the technology (4 items: 5-step Likert scale)	3.6 (1.0)	NA	NA
1. Helps me more quickly detect the signs and symptoms of deterioration in my state of health	3.6 (1.3)
2. Helps me know what measures to take when things take a turn for the worse	4.1 (1.3)
3. Helps me take my medication as prescribed	2.5 (1.7)
4. Helps me by reassuring me	4.2 (1.2)
Three benefits as perceived by the attending nurses
1. Improved knowledge (3 items: 10-step Likert scale)	7.7 (1.5) α = 0.84	NA	NA
The technology improved patient knowledge:of the nature of their clinical condition	7.3 (2.1)
of the symptoms they should watch for	7.6 (1.8)
of ways they can better control their illness	8.2 (1.3)
2. Improved case management (4 items: 10-step Likert scale)	7.0 (1.4) α = 0.84	NA	NA
The technology improved how the patient monitors their health condition	7.6 (1.6)
The technology improved the patient's control over their health condition	7.3 (1.9)
The technology made the patient feel more secure about their health condition	6.0 (1.9)
The technology improved the patient's own self-care	7.0 (1.8)
3. Creation of a dependency on the technology (1 item)	8.3 (1.7)

References

Lopez

, Shibuya

, Rao

, Mathers

, Hansell

, Held

et al. Chronic obstructive pulmonary disease: Current burden and future projections. Eur Respir J, 2006; 27:397–412.

GOLD. Global strategy for diagnosis, management and prevention of COPD: GOLD executive summary—updated. 2009. www.goldgroup.org. 2010 March 1.

Mittmann

, Kuramoto

, Seung

, Haddon

, Bradley-Kennedy

, FitzGerald

. The cost of moderate and severe COPD exacerbations to the Canadian healthcare system. Respir Med, 2008; 102:413–421.

Bodenheimer

, Wagner

, Grumbach

. Improving primary care for patients with chronic illness. JAMA, 2002; 288:1775–1779.

Bodenheimer

, Wagner

, Grumbach

. Improving primary care for patients with chronic illness. The chronic care model, Part 2. JAMA, 2002; 288:1909–1914.

Lewis

, Dixon

. Rethinking management of chronic diseases. Br Med J, 2004; 328:220–222.

Young

, Chaney

, Shoai

, Bonner

, Doebbeling

, Dorr

, Goldstein

, Kerr

, Nichol

, Perrin

. Information technology to support improved care for chronic illness. J Gen Intern Med, 2007; 22,Suppl 3:425–430.

Dorr

, Bonner

, Cohen

, Shoai

, Perrin

, Chaney

, Young

. Informatics systems to promote improved care for chronic illness: A literature review. J Am Med Inform Assoc, 2007; 14:156–163.

Paré

, Jaana

, Sicotte

. Systematic review of home telemonitoring for chronic diseases: The evidence base. J Am Med Inform Assoc, 2007; 14:269–277.

10.

Jaana

, Paré

, Sicotte

. Home Telemonitoring for respiratory conditions: A systematic review. Am J Manag Care, 2009; 15:313–320.

11.

Dale

, Connor

, Tolley

. An evaluation of the west Surrey telemedicine monitoring project. J Telemed Telecare, 2003; 9,Suppl 1:S39–S41.

12.

Dang

, Ma

, Nedd

et al. Differential resource utilization benefits with Internet-based care coordination in elderly veterans with chronic diseases associated with high resource utilization. J Telemed Telecare, 2006; 12:14–23.

13.

De Toledo

, Jiménez

, del Pozo

, Roca

, Alonso

, Hernandez

. Telemedicine experience for chronic care in COPD. IEEE Trans Inf Technol Biomed, 2006; 103:567–573.

14.

Maiolo

, Mohamed

, Fiorani

, De Lorenzo

. Home telemonitoring for patients with severe respiratory illness: The Italian experience. J Telemed Telecare, 2003; 9:67–71.

15.

Paré

, Sicotte

, St.-Jules

, Gauthier

. Cost-minimisation analysis of a telehomecare program for patients with chronic obstructive pulmonary disease. Telemed e-Health, 2006; 12:114–121.

16.

Trappenburg

JCA

, Niesink

, de Weert-van Oene

et al. Effects of telemonitoring in patients with chronic obstructive pulmonary disease. J Telemed Telecare, 2008; 14:138–146.

17.

Koff

, Jones

, Cashman

, Noelkel

, Vandivier

. Proactive integrated care improves quality of life in patients with COPD. Eur Respir J, 2009; 33:1031–1038.

18.

Larsen

, Attkisson

, Hargreaves

, Nguyen

. Assessment of client/patient satisfaction: Development of a general scale. Eval Program Plann, 1979; 2:197–207.

19.

Sicotte

, Paré

, Moreault

, Lemay

, Valiquette

, Barkun

. Replacing an inpatient electronic medical record—Lessons learned from user satisfaction with the former system. Methods Inform Med, 2009; 48:92–100.

20.

Glasgow

, Wagner

, Schaefer

, Mahoney

, Reid

, Greene

. Development and validation of the Patient Assessment of Chronic Illness Care (PACIC) Med Care, 2005; 43:436–444.

21.

Lorig

, Stewart

, Ritter

, Gonzalez

, Laurent

, Lynch

. Outcome measures for health education and other health care interventions. Thousand Oaks, CA: Sage publications, 1996.

22.

Morisky

, Green

, Levine

. Concurrent and predictive validity of a self-reported measure of medication adherence. Med Care, 1986; 24:67–74.

23.

Bakken

, Grullon-Figueroa

, Izquierdo

, Lee

, Morin

, Palmas

, Teresi

, Weinstock

, Shea

, Starren

. Development, validation, and use of English and Spanish versions of the telemedicine satisfaction and usefulness questionnaire. J Am Med Inform Assoc, 2006; 13:660–667.

24.

Tudiver

, Wolff

, Morin

, Teresi

, Palmas

, Starren

, Shea

, Weinstock

. Primary care providers' perceptions of home diabetes telemedicine care in the IDEATel project. J Rural Health, 2007; 23:55–61.

25.

Gandek

, Ware

, Aaronson

et al. Cross-validation of item selection and scoring for the SF-12 health survey in nine countries: Results form IQOLA project. International Quality of Life assessment. J Clin Epidemiol, 1998; 51:1171–1178.

26.

Nunally

. Psychometric theory. New York: McGraw-Hill, 1978.