Dr. Wakefield is Research Scientist, Mr. Holman is Research Specialist, and Ms. Ray and Ms. Scherubel are Research Nurses, U.S. Department of Veterans Affairs (VA) Health Services Research and Development Center for Comprehensive Access and Delivery Research and Evaluation (CADRE), Iowa City VA Medical Center, Iowa City, Iowa.
The authors disclose that they have no significant financial interests in any product or class of products discussed directly or indirectly in this activity. The research reported here was supported by the U.S. Department of Veterans Affairs, Veterans Health Administration, Health Services Research and Development Service (NRI 03–312). The views expressed in this article are those of the authors and do not necessarily represent the views of the U.S. Department of Veterans Affairs.
Address correspondence to Bonnie J. Wakefield, PhD, RN, FAAN, Research Scientist, Research Service (152), Iowa City VA Medical Center, 601 Highway 6 West, Iowa City, IA 52246; e-mail: email@example.com.
Use of telecommunications technology to provide remote monitoring for people with chronic disease is becoming increasingly accepted as a means to improve patient outcomes and reduce resource use (Darkins et al., 2008; Hersh et al., 2006; Paré, Jaana, & Sicotte, 2007; Shea et al., 2006; Shea et al., 2009). Data provided through this type of monitoring enable clinicians to provide close surveillance so earlier intervention may be implemented when clinical parameters are out of control or when data indicate additional health information or support is needed. To date, most evaluations of patient perceptions of these technologies in older adults have been cursory (Agency for Healthcare Research and Quality, 2008). It is important to measure patient perceptions beyond generic satisfaction data to identify barriers and facilitators to implementation of these technologies. In this article, we report data from a larger study that evaluated patient perceptions of remote monitoring.
The main results of the parent study are reported elsewhere (Wakefield et al., in press), but the study methods are briefly overviewed here. The study was a randomized, controlled clinical trial comparing the efficacy of two remote monitoring intensity levels (low and high) to usual care in patients with comorbid diabetes and hypertension.
The remote monitoring device used in the study (Viterion® 100 TeleHealth Monitor; Bayer HealthCare, Tarrytown, NY) used a standard telephone landline to enable data transmission between the patient’s home and the study center. Using the device, intervention participants entered blood pressure (BP) and blood glucose (BG) measurements and responded to standardized questions based on their group assignment. The device prompts the patient to send data at the end of the patient’s session before turning off the machine, making the trended data on BP, BG, and responses to health questions available for the nurse to review the next time she logs on to the secure website. The device also allows individualized messages to be transmitted to participants from the study center. Participants received and were trained on use of the device at the enrollment clinic visit.
Both intervention groups received care management from a study nurse. Both groups were instructed to measure BP daily and BG as directed by their physician (i.e., frequency of home BG monitoring was not changed). Participants in the low-intensity group responded to three questions each day (two were asked every day, and the third question was one of seven that rotated each day throughout the study period). The high-intensity group responded to questions from an investigator-developed algorithm that focused on diet, exercise, smoking cessation, foot care, advice for sick days, medications, weight management, preventive care, and behavior modification and lifestyle adjustments. A rotating schedule was established for each question set so that participants received both standard questions each day and a rotation of questions based on the categories above. The study team also provided the high-intensity group with educational tips each day. Patient perception data reported in this article were collected at the end of the intervention period (6 months) in the two intervention groups using an investigator-developed, 12-item, Likert-type questionnaire (Wakefield, Holman, Ray, Morse, & Kienzle, 2004). Participants were also interviewed by the study nurses with one open-ended question: “What were your likes/dislikes about this program?”
Descriptive statistics were calculated for the 12-item questionnaire, and the two groups were compared using t tests. For the qualitative data analysis, all comments from both groups were read separately by two investigators (B.J.W., J.E.H.) who developed initial codes for each comment. Using these initial codes and following discussion between the investigators, a code book was developed. Using the code book, the same two coders re-coded the data and met to reach consensus on all coding. Once all comments were coded, the comments were grouped by intervention group to assess for differences between the two groups.
In the parent study, participants were mostly men (98%), Caucasian (96%), and married (66%), with a mean age of 68 (SD = 10 years; age range = 40 to 89). Most had a high school education or higher (89%).
Questionnaires were completed by the 129 participants who completed the 6-month data collection. The two groups were not significantly different across the 12 items in the questionnaire, with one exception: “Using the health messaging device could alert my provider to a health problem that I would not otherwise know existed.” For this item, the low-intensity group indicated stronger agreement compared with the high-intensity group. Overall, the means for each group demonstrate a relatively positive perception of the device and program (Table 1).
Table 1: Summary of Postintervention Device Perceptions Questionnaire
For the qualitative analysis, responses to the open-ended question were received from 113 participants (56 high intensity and 57 low intensity), representing 88% of participants who completed the questionnaire. Overall, 197 phrases were coded across the two groups: 92 in the low intensity and 105 in the high intensity group (Table 2).
Table 2: Summary of Qualitative Comment Data
The highest number of comments focused on the design of the remote monitoring device. Comments addressed the device programming, physical interaction with the device, portability of the device, and ease of use. Comments on device programming included that it was not always clear how to navigate between menus (i.e., entering vital signs then going to the questions required pressing the “cancel” button; some participants found this confusing and suggested the button be renamed “back”). Also, data could be entered only for the current day, and participants wanted to be able to go back and enter numbers from previous days. A few comments were about the physical interaction with the device (e.g., the “pressure required to press buttons was too high, especially after heart surgery”). Similarly, another participant noted that older adults or those with arthritis may experience difficulty pushing the buttons. The participants perceived that the device was not portable, so it was not possible to transmit data when traveling. Regarding ease of use, some participants thought the device was “simple and straightforward,” “simple and easy to use,” and had “big numbers, easy to see and press; display was good.”
The next most common comment was about the device’s connection speed when answering questions, navigating around the device, and uploading data. All of these comments focused on the slow speed of accomplishing these tasks.
Integration into Daily Routine
Comments on the integration into daily routine included those about initial adjustment and learning period, use of remote monitoring becoming part of one’s habits and daily routine, time, and convenience. Comments included that using the devices was “mostly positive, once I got used to it,” and that it “took time to get used to but then it was simple, part of daily routine.” Others were not as positive, noting that using the device was “too time consuming. Really good idea, but it was cumbersome in my life. Rather answer questions just once a week” and “Sometimes it is a pain to use because it is hard to remember to do it.” One participant thought it was a convenient way to communicate: “[I] think it’s a great way of communicating with health providers without coming here. I live 120 miles away.”
Connection problems refer to connection issues not related to speed of the connection (i.e., getting connected to the data center). During the initial part of the study, the data center did not have enough telephone lines, so the device would need to redial several times. Once this issue was resolved by the company, connection problems were less prevalent.
Nurse/Self-Monitoring and Patient Adherence
Comments on nurse/self-monitoring and patient adherence addressed patient engagement, changing health behaviors, and increased awareness of their diabetes and hypertension. Comments in this category were all positive and included:
- “[The] questions helped [me] to remember to report health problems and information sent was helpful.”
- “I think it kept me aware.”
- “[I] like the direct link to the nurse.”
- “It’s good. It could alert you if you were way out of line with your blood sugar.”
- “The program helped awareness and commitment to good health practices; [the patient] likes being monitored each day.”
- “It made me check my blood pressure every day.”
- “[It] makes me think about my health a little more than I otherwise would.”
- “[It] does make you aware of taking medicines, checking sugar.”
- “[It] made me more aware of how foods affected my blood sugar.”
- “[It] keeps you on your toes!”
Intervention Questions and Educational Messages
Intervention questions and educational messages refer to comments made about the algorithm of health questions and educational tips programmed into the device by study staff. Although participants in both groups mostly responded that the questions were repetitive, slightly more comments were about repetition in the high-intensity group relative to the low-intensity group. However, there were also positive comments about the questions, mostly that the educational tips and questions were helpful. One participant offered a suggestion: “I would suggest improving the messages. Would like specific messages, i.e., a small potato is x number of carbohydrates.” One participant in the low-intensity group wanted more options to answer some of the questions.
The category of general perceptions included global comments about the program or study, which were mostly positive (i.e., they liked the program). One patient reported that he liked it and that he quit smoking, his blood pressure went down, and he quit eating salt. Another participant wanted more instruction on using the device beyond the initial training.
Finally, two-way communication addressed the desire by some participants to send messages to the nurse or provider, as the device provided only nurse-to-patient messaging capability.
The quantitative questionnaire indicated generally positive perceptions of the program and device. In contrast, the qualitative comments indicated several criticisms of the program and device. These included those on device programming, physical design, portability, and connection speed; difficulties integrating the program into their daily routine; the repetitive nature of the questions programmed into the device; and the inability to send messages to the nurse. Comments on the nurse and self-monitoring aspects of the program were all positive.
Prior work has shown that patients are generally satisfied with remote monitoring programs. However, many of these studies have used only a few quantitative questions. In a recent study (LaFramboise, Woster, Yager, & Yates, 2009), investigators conducted a series of focus groups and interviews with patients with heart failure who used a device for home monitoring much like the one used in the current study. Participants in that study reported similar perceptions as those in our study (i.e., they found that after an initial adjustment period, the program promoted self-management and they liked being monitored). Criticisms included monotonous content, a desire for more options for answering questions, remembering to use the device each day, and the need for a telephone jack nearby to use the device. Our qualitative categories are also consistent with a recently published model (Or et al., 2011) to guide assessment of patient perceptions and satisfaction with web-based self-management technology (i.e., perceived usefulness, perceived ease of use, and upper extremity functional ability).
We used only one open-ended question and did not probe in depth to gain a deeper understanding of patient perceptions. Because these data were drawn from a larger study focused on the efficacy of remote monitoring, only one device was evaluated; thus, we could not compare patient perceptions across multiple devices.
Conclusion and Implications
There is value in using both quantitative and qualitative approaches when assessing patient perceptions of a new program. The most common and efficient method to collect patient satisfaction ratings of health care is questionnaires and surveys, and the data are typically skewed in a positive direction. Interviews with patients are more time consuming but may offer richer data for identifying areas for program improvement. For these technologies to reach their full potential, detailed patient input into the design and evaluation of these devices and programs is critical.
- Agency for Healthcare Research and Quality. (2008). Barriers and drivers of health information technology use for the elderly, chronically ill, and underserved (Publication No. 09-E004). Retrieved from http://www.ahrq.gov/clinic/tp/hitbartp.htm
- Darkins, A., Ryan, P., Kobb, R., Foster, L., Edmonson, E., Wakefield, B. & Lancaster, A.E. (2008). Care coordination/home telehealth: The systematic implementation of health informatics, home telehealth, and disease management to support the care of veteran patients with chronic conditions. Telemedicine and e-Health, 14, 1118–1126. doi: doi:10.1089/tmj.2008.0021 [CrossRef]
- Hersh, W.R., Hickam, D.H., Severance, S.M., Dana, T.L., Krages, K.P. & Helfand, M. (2006). Diagnosis, access and outcomes: Update of a systematic review of telemedicine services. Journal of Telemedicine and Telecare, 12(Suppl. 2), 3–31. doi:10.1258/135763306778393117 [CrossRef]
- LaFramboise, L.M., Woster, J., Yager, A. & Yates, B.C. (2009). A technological life buoy: Patient perceptions of the Health Buddy. Journal of Cardiovascular Nursing, 24, 216–224.
- Or, C.K., Karsh, B.T., Severtson, D.J., Burke, L.J., Brown, R.L. & Brennan, P.F. (2011). Factors affecting home care patients’ acceptance of a web-based interactive self-management technology. Journal of the American Medical Informatics Association, 18, 51–59. doi:10.1136/jamia.2010.007336 [CrossRef]
- Paré, G., Jaana, M. & Sicotte, C. (2007). Systematic review of home telemonitoring for chronic diseases: The evidence base. Journal of the American Medical Informatics Association, 14, 269–277. doi:10.1197/jamia.M2270 [CrossRef]
- Shea, S., Weinstock, R.S., Starren, J., Teresi, J., Palmas, W., Field, L. & Lantigua, R.A.,… (2006). A randomized trial comparing telemedicine case management with usual care in older, ethnically diverse, medically underserved patients with diabetes mellitus. Journal of the American Medical Informatics Association, 13, 40–51. doi:10.1197/jamia.M1917 [CrossRef]
- Shea, S., Weinstock, R.S., Teresi, J.A., Palmas, W., Starren, J., Cimino, J.J. & Eimicke, J.P.,… (2009). A randomized trial comparing telemedicine case management with usual care in older, ethnically diverse, medically underserved patients with diabetes mellitus: 5 year results of the IDEATel study. Journal of the American Medical Informatics Association, 16, 446–456. doi:10.1197/jamia.M3157 [CrossRef]
- Wakefield, B., Holman, J., Ray, A., Scherubel, M., Adams, M., Hillis, S. & Rosenthal, G.E. (in press). Effectiveness of home telehealth in comorbid diabetes and hypertension: A randomized controlled trial. Telemedicine & e-Health.
- Wakefield, B.J., Holman, J.E., Ray, A., Morse, J. & Kienzle, M.G. (2004). Nurse and patient communication via low- and high-bandwidth home telecare systems. Journal of Telemedicine and Telecare, 10, 156–159. doi: doi:10.1258/135763304323070805 [CrossRef]
Summary of Postintervention Device Perceptions Questionnaire
|Low-Intensity Monitoring (n= 65)||High-Intensity Monitoring (n= 64)|
|Questionnaire Item||Mean (SD)||Mean (SD)|
|The health messaging device was simple to set up.||1.3 (0.5)||1.3 (0.5)|
|The health messaging device is easy to use.||1.6 (0.9)||1.6 (0.9)|
|Using the health messaging device interferes with my lifestyle.||4.0 (1.2)||3.9 (1.3)|
|It is easy to read the display screen.||1.2 (0.5)||1.3 (0.4)|
|Knowing that nurses are monitoring my health daily gives me peace of mind.||1.6 (0.7)||1.8 (0.9)|
|Using the health messaging device could alert me to a health problem that I would not otherwise know existed.||1.6 (0.8)||1.9 (1.2)|
|Using the health messaging device could alert my provider to a health problem that I would not otherwise know existed.||1.3 (0.6)||1.6a (0.9)|
|It is easy to remember to use the health messaging device every day.||1.9 (1.1)||2.0 (1.2)|
|Answering the questions every day takes too much time.||4.2 (1.2)||4.1 (1.1)|
|If given the option, I would want to continue using a health messaging device after the study period ends.||2.3 (1.3)||2.6 (1.4)|
|I would recommend use of this type of machine to my friends or other patients with the same condition.||1.4 (0.7)||1.5 (0.8)|
|Using the health messaging device helped me to manage my health.||1.8 (0.8)||1.8 (1.0)|
Summary of Qualitative Comment Data
|Comment Category||Overall (n= 197 coded phrases)||Low-Intensity Monitoringa (n= 92 coded phrases)||High-Intensity Monitoringb (n= 105 coded phrases)|
|Integration into daily routine||15%||18%||12%|
|Nurse/self-monitoring and patient adherence||12%||13%||11%|
|Intervention questions and educational messages||7%||4%||10%|