Client Satisfaction with Telehealth in Assisted Living and Homecare
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1 Client Satisfaction with Telehealth in Assisted Living and Homecare Leslie A. Grant, PhD, Todd Rockwood, PhD, and Leif Stennes, PhD Division of Health Policy and Management, School of Public Health, University of Minnesota, Minneapolis, Minnesota. Abstract Background: The Evangelical Lutheran Good Samaritan Society launched to provide telehealth services to clients in assisted living and home healthcare. assures client safety through remote monitoring of physiological parameters and assessment of nonbiometric parameters. Public policies increasingly support aging in place by allowing older adults with greater levels of impairment avoid or delay nursing home placement through alternative services offered in assisted living facilities and home healthcare agencies. Provider organizations face challenges caring for frail seniors with complex medical needs. Telehealth services may be helpful in supporting frail seniors living at home. Materials and Methods: Seniors were recruited into a randomized trial. Telehealth services were provided to 820 experimental subjects. Control subjects (n = 762) received usual care. Clients rated their satisfaction at three points in time postimplementation: baseline, 6 months, and 12 months. Fisher s exact test compared client ratings at each measurement interval. Results: No statistically significant differences were found between experimental and control subjects at baseline. Statistically significant differences emerged at follow-up. Experimental subjects in home healthcare agencies reported higher levels of satisfaction relative to controls, whereas experimental subjects in assisted living facilities reported lower levels of satisfaction. Conclusions: Telehealth services increased the probability that clients will be more satisfied compared with those without telehealth in homecare agencies. The opposite effect resulted among assisted living residents. Value propositions among community-dwelling older adults may influence their satisfaction with telehealth services postimplementation. More research is needed to examine the clinical efficacy and cost-effectiveness of these services. Key words: home health monitoring, sensor technology, telehealth, telenursing Introduction Public policies in the United States increasingly support aging in place by allowing frail older adults to remain at home. Policymakers often see assisted living facilities and home healthcare services as more economical and less institutional alternatives to care in nursing homes. Home healthcare agencies face challenges related to caring for sicker patients with complex medical needs, providing access to services in markets with nursing shortages, and finding efficient means of delivering care in rural communities. Assisted living facilities face similar challenges. Without appropriate nursing care, assisted living residents will likely face relocation to a nursing home when unmet care needs put them at risk. One strategy for assisted living facilities and home healthcare agencies to support aging in place is to deploy telehealth services to monitor safety and health status remotely. The LivingWell@Home (LW@H) program was implemented in late 2010 by The Evangelical Lutheran Good Samaritan Society (aka the Good Samaritan Society). This article describes client satisfaction with telehealth services deployed through LW@H. The Good Samaritan Society (headquartered in Sioux Falls, SD) is the largest not-for-profit, faith-based senior services organization in the United States. The Good Samaritan Society provides a broad range of services, including skilled nursing care, assisted living facilities, home healthcare, postacute care, housing, inpatient and outpatient rehabilitation therapy, and memory care. The Good Samaritan Society has facilities in more than 240 locations nationwide, it provides services to more than 27,000 seniors in 24 states, and it employs 21,000 staff. Telehealth services are being tested by the Good Samaritan Society in 14 home healthcare agencies and 32 assisted living facilities across five states (Iowa, Minnesota, Nebraska, North Dakota, and South Dakota). Materials and Methods Assisted living facility residents and home healthcare clients were recruited into a randomized trial. Seniors were randomly assigned to experimental versus control conditions. Telehealth services were provided to 820 experimental subjects. Control subjects (n = 762) received usual care. A research team from the University of Minnesota evaluated the efficacy DOI: /tmj ª MARY ANN LIEBERT, INC. VOL. 21 NO. 12 DECEMBER 2015 TELEMEDICINE and e-health 987
2 GRANT ET AL. of these services. All participants signed informed consent forms assuring confidentiality. The Institutional Review Board at the University of Minnesota approved these protocols. Data collection began in 2011 and ended in Data were collected longitudinally at baseline, 6 months postdischarge (home), and 12 months postdischarge. Home healthcare agency nurses and housing managers of assisted living facilities recruited research subjects, obtained informed consent, and randomized subjects into experimental Table 1. Participant Demographics (n = 1,582) Gender TOTAL (%) EXPERIMENTAL (%) CONTROL (%) Female 1,065 (67) 557 (68) 508 (67) Male 416 (26) 209 (26) 207 (27) Not determined 101 (6) 54 (7) 47 (6) Marital status Never married 71 (5) 40 (5) 31 (4) Married 397 (25) 191 (23) 206 (27) Widowed 781 (49) 419 (51) 362 (48) Divorced 164 (10) 78 (10) 86 (11) Separated 12 (1) 5 (1) 7 (1) Living together (unmarried) 10 (<1) 10 (1) 0 (0) Not determined 147 (9) 77 (9) 70 (9) Ethnicity/race Black (not Hispanic) 4 (<1) 2 (<1) 2 (<1) Hispanic 5 (<1) 4 (1) 1 (<1) White (not Hispanic) 1420 (90) 734 (90) 686 (90) American Indian/Alaskan Native 7 (<1) 3 (<1) 4 (1) Asian 4 (<1) 3 (<1) 1 (<1) Other 9 (<1) 5 (1) 4 (1) Not determined 132 (8) 68 (8) 64 (5) Annual household income Less than $35, (54) 439 (54) 413 (54) $35,000 49, (7) 61 (7) 53 (7) $50,000 74, (5) 33 (4) 49 (6) $75,000 99, (2) 12 (2) 13 (2) $100,000 or more 8 (1) 3 (<1) 5 (1) Not determined 501 (32) 272 (33) 229 (30) Age (years) [mean (range)] 81 (43 112) 81 (43 109) 81 (43 112) and control groups. Survey data were collected using face-toface interviews. Four groups were recruited: (1) patients being discharged home from subacute care units in nursing facilities (aka transitional care or postacute care) (n = 365); (2) patients being discharged home following an acute inpatient hospitalization (n = 368); (3) people who are dually eligible for Medicare and Medicaid services who had been hospitalized in the recent past (n = 126); and (4) assisted living residents (n = 723). Table 1 shows the demographic characteristics of research subjects. Most were female (67%) and white (90%). One-quarter (25%) were married. Almost half (49%) were widowed. Most (54%) had an annual household income of less than $35,000. The mean age was 81 years, with a range of years. Experimental and control subjects were similar in terms of demographic characteristics. LW@H tested three types of telehealth devices: (1) sensors, (2) emergency response systems, and (3) biometric monitors. Sensors (e.g., motion detectors, bed sensors, and humidity sensors) send wireless signals to detect sleep patterns, motion, bathing, toileting, cooking, and other activities of daily living. Personal emergency response systems were used to enhance client safety using a pendant with a button that can be pressed to summon help. The pendant has a built-in accelerometer that automatically sends a signal should a person fall and become unconscious. Biometric monitors were used to conduct physiologic evaluations (e.g., heart rate, blood pressure, weight, pulse oximetry, and blood glucose). These devices are connected to a data management system that is monitored remotely by a team composed of registered nurses and trained unlicensed staff called data review specialists. The team monitors the telemetry from the LivingWell Center located in Sioux Falls. Online reports alert the team to emergency health problems. These telehealth services have identified many types of sentinel health events such as falls, accidents, urinary tract infections, sleep irregularities, reactions to prescription medications, behavioral risks such as elopement, cognitive changes, and 988 TELEMEDICINE and e-health DECEMBER 2015 ª MARY ANN LIEBERT, INC.
3 TELEHEALTH IN ASSISTED LIVING AND HOMECARE Table 2. Clients Reporting High Satisfaction with External Systems CONTROL EXPERIMENTAL RESPONSES YES (%) RESPONSES YES (%) P VALUE Home healthcare agency clients (n) Baseline (45) (42) months (45) (49) months (45) (57) Assisted living facility residents (n) Baseline (60) (51) months (51) (44) months (53) (48) other risk factors. This information can be used to support older adults living at home. MEASURING CLIENT SATISFACTION Clients were asked to rate service providers on 25 items assessing their Satisfaction with Internal Systems (SIS) and Satisfaction with External Systems (SES). Both SIS and SES scales are described elsewhere. 1 SES assesses client concerns that lie outside the organizational processes of the Good Samaritan Society (e.g., quality of services provided by outside doctors, nurses, clinics, and hospitals and global ratings of medical care providers; how well family members were kept informed about the client s health condition; how family members obtained assistance in planning for the client s care; and support, comfort, management of medical conditions, and other systems supportive of aging in place). SIS assessed client ratings of services that are internal to the Table 3. Clients Reporting High Satisfaction with Internal Systems CONTROL EXPERIMENTAL RESPONSES YES (%) RESPONSES YES (%) P VALUE Home healthcare agency clients (n) Baseline (44) (44) months (46) (56) months (52) (63) Assisted living facility residents (n) Baseline (63) (57) months (61) (49) months (55) (46) organization (e.g., quality of services provided by Good Samaritan Society staff such as ease of getting assistance, quality of care, responsiveness, competency, care or concern, and global ratings of Good Samaritan Society services; healthcare services such as meeting health and medical needs, coordinating services with doctors and other medical professionals, handling medical emergencies or unexpected events, meeting personal needs for assistance, and independence and safety). SES and SIS scales have good internal consistency (Cronbach s a = 0.97). The Shapiro Wilk test found that the distribution of SES and SIS scores is nonnormal. Accordingly, a nonparametric method (Fisher s exact test) was used to compare scores of client ratings dichotomized into two groups based on high versus low SIS and SES scores: clients were assigned to a high satisfaction group if scores were above the mean; otherwise, clients were assigned to a low satisfaction group. Results Table 2 shows the percentage of clients in the high satisfaction group for SES for homecare clients and assisted living facility residents. Among homecare clients, there were similar proportions of clients reporting high SES at baseline and at 6 months. At 12 months, there were significantly more homecare clients in the experimental group who reported high satisfaction ( p = 0.049). There were no statistically significant differences between experimental and control subjects among residents of assisted living facilities. Table 3 shows the proportion of clients in the high satisfaction group for SIS. Among homecare clients there were similar proportions reporting high SIS at baseline and at 12 months; at 6 months, there were significantly more homecare clients in the experimental group who reported high satisfaction ( p = 0.031). Among assisted living facility residents, there were no statistically significant differences ª MARY ANN LIEBERT, INC. VOL. 21 NO. 12 DECEMBER 2015 TELEMEDICINE and e-health 989
4 GRANT ET AL. Fig. 1. Satisfaction with External Systems scores (percentages of experimental and control subjects). ALF, assisted living facilities; HHC, home healthcare. between experimental and control subjects at baseline and 12 months; at 6 months, there were significantly fewer assisted living clients in the experimental group who reported high satisfaction ( p = 0.030). Figures 1 and 2 show linear trend lines depicting the proportion of experimental and control subjects in home healthcare agencies and assisted living facilities with high SES and high SIS scores. Experimental subjects in home healthcare agencies show an increase in the proportion with high SES and high SIS scores from baseline to 12 months. Research subjects in assisted living facilities show a decline over time in the proportion with high SES and high SIS scores. Discussion Qualitative studies of services offered through LW@H highlight the value of telehealth services for housing managers, family members, and nurses. 2,3 These technologies provide housing managers with objective information to help them manage resident risks proactively. Family members gain added assurance knowing that their relative is being monitored by nurses to help assure safety and well-being. Nurses see value in deploying these telehealth services due to perceived improvements in clinical processes. The present study suggests that the value proposition offered by these telehealth services differs between home healthcare clients and assisted living facility residents. Responses to open-ended questions posed to housing managers during focus groups shed light about why older adults in assisted living may not see positive value in these services. Assisted living residents sometimes fear relocation to a nursing home, and they don t want to be seen as a burden to others. In some cases residents may be in denial about their personal frailties. Denial as a coping mechanism helps support a more positive self-concept compared with reality (as evidenced in the objective data collected by telehealth monitoring). Accordingly, some resident try to mask their frailties from housing managers and nurses. For example, residents may deny infrequent bathing or showering when objective data collected through telehealth monitoring show otherwise. Cognitive dissonance may pose challenges in convincing assisted living residents that they may actually benefit from these technologies. One assisted living manager noted, I have learned that your residents will mask their symptoms to make you think that they are healthier.than they are. Another stated: Sometimes I think that they want to portray to us that they are healthy, so they can stay at the assisted living. They have this Fig. 2. Satisfaction with Internal Systems scores (percentages of experimental and control subjects). ALF, assisted living facilities; HHC, home healthcare. 990 TELEMEDICINE and e-health DECEMBER 2015 ª MARY ANN LIEBERT, INC.
5 TELEHEALTH IN ASSISTED LIVING AND HOMECARE fear of going to the nursing home. And, they feel like, if I have one more UTI [urinary tract infection] or one more fall, they re gonna get rid of me. This technology doesn t lie. I mean it gives you a real view of what is happening... And, some of them would not consent to the program [LW@H] because they did not want us to have access to that [information]. You know, they felt it was an invasion of their privacy. Some assisted living mangers saw greater value in observations made by on-site staff compared with information collected remotely using telehealth services. One manager noted, Well, because of the assisted living environment, they re [residents] out three times a day [for meals]. We re checking on them more than that with all the medication passes. We can catch it [problems] probably 80% of the time before the sensors catch it. Potential challenges in marketing telehealth services to assisted living residents were also noted. One manager raised this issue from the resident s perspective: Why should I pay for another monitoring program when I thought the staff was going to be here 24 hours a day? Some assisted living managers believe that telehealth services would be easier to market to seniors living at home than to those already in assisted living. A manager commented, I think that the technology is probably geared for those living at home. They want to stay at home anyway, and it would be great to market that they can stay at home. And, at a certain price it s [more] affordable to have the technology put in their home than for them to move into assisted living or nursing home. STUDY LIMITATIONS Several study limitations should be noted. First, the study was conducted within home healthcare agencies and assisted living facilities operated by the Good Samaritan Society, so these findings may not generalize to other settings. Second, there was a high degree of attrition among study participants between baseline and 12-month follow-up, so there is the possibility for attrition bias. Third, response set bias may exist because data were collected by Good Samaritan Society staff during face-to-face interviews. The results are based on subjective perceptions of clients who may give socially desirable answers as opposed to expressing their true beliefs. The LW@H program tests telehealth services to support aging in place. These services offer divergent value propositions to older adults served by home healthcare agencies and assisted living facilities. Value propositions among community-dwelling older adults are likely to influence their satisfaction with these services following implementation. More research is needed to examine the clinical efficacy and costeffectiveness of these telehealth services. Acknowledgments This work was supported by the Rural Healthcare Program of The Leona M. and Harry B. Helmsley Charitable Trust. Disclosure Statement No competing financial interests exist. REFERENCES 1. Grant LA, Rockwood T, Stennes L. Client satisfaction with telehealth services in home health care agencies. J Telemed Telecare 2015;21: Grant LA, Rockwood T, Stennes L. Technology-enhanced nurse monitoring in assisted living: Results from focus groups with housing managers. Seniors Housing Care J 2013;21: Grant LA, Rockwood T, Stennes L. Testing telehealth using technology-enhanced nurse monitoring. J Gerontol Nurs 2014;40: Address correspondence to: Leslie A. Grant, PhD Division of Health Policy and Management School of Public Health University of Minnesota D262 Mayo Memorial Building Mayo Mail Code Delaware Street S.E. Minneapolis, MN grant004@umn.edu Received: October 27, 2014 Revised: February 9, 2015 Accepted: February 12, 2015 ª MARY ANN LIEBERT, INC. VOL. 21 NO. 12 DECEMBER 2015 TELEMEDICINE and e-health 991
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