- Email: [email protected]
Feasibility and Clinical Efficacy of a Multidisciplinary Home-Telehealth Program to Prevent Falls in Older Adults: A Randomized Controlled Trial
JAMDA xxx (2018) 1e7
JAMDA journal homepage: www.jamda.com
Original Study
Feasibility and Clinical Efficacy of a Multidisciplinary Home-Telehealth Program to Prevent Falls in Older Adults: A Randomized Controlled Trial Palmira Bernocchi PhD a, *, Alessandro Giordano MD b, Giuseppe Pintavalle PT a, Tiziana Galli PT a, Eleonora Ballini Spoglia a, Doriana Baratti a, Simonetta Scalvini MD a, b a b
Istituti Clinici Scientifici Maugeri IRCCS, a Care Continuity Unit and Telemedicine Service, Institute of Lumezzane, Brescia, Italy Cardiology Department of the Institute of Lumezzane, Brescia, Italy
a b s t r a c t Keywords: Fall prevention home tele-rehabilitation older adults chronic disease telemedicine
Objectives: The aim of this study was to determine the feasibility and efficacy of a 6-month telerehabilitation home-based program, designed to prevent falls in older adults with 1 or more chronic diseases (cardiac, respiratory, neuromuscular or neurologic) returning home after in-hospital rehabilitation for their chronic condition. Patients were eligible for selection if they had experienced a fall during the previous year or were at high risk of falling. Design: Randomized controlled trial. Tele-rehabilitation consisted of a falls prevention program run by the physiotherapist involving individual home exercise (strength, balance, and walking) and a weekly structured phone-call by the nurse inquiring about the disease status and symptoms and providing patient support. Setting and Participants: Two hundred eighty-three patients (age 79 6.6 years; F ¼ 59%) with high risk of falls and discharged home after in-hospital rehabilitation were randomized to receive home-based program (intervention group, n ¼ 141) or conventional care (control group, n ¼ 142). Measures: Incidence of falls at home in the 6-month period (primary outcome); time free to the first fall and proportion of patients sustaining 2 falls (secondary outcomes). Results: During the 6 months, 85 patients fell at least once: 29 (20.6%) in the Intervention Group versus 56 (39.4%) in the control group (P < .001). The risk of falls was significantly reduced in the intervention group (relative risk ¼0.60, 95% confidence interval: 0.44-0.83; P < .001). The mean standard deviation time to first fall was significantly longer in intervention group than control group (152 58 vs 134 62 days; P ¼ .001). Significantly, fewer patients experienced 2 falls in the intervention group than in the control group: 11 (8%) versus 24 (17%), P ¼ .020. Conclusions: A 6-month tele-rehabilitation home-based program integrated with medical/nursing telesurveillance is feasible and effective in preventing falls in older chronic disease patients with a high risk of falling. Ó 2018 AMDA e The Society for Post-Acute and Long-Term Care Medicine.
Inadvertent falls and consequent injuries are a major public health problem in older adults often requiring medical attention.1,2 A person who has fallen once is at higher risk of falling again3 and has increased morbidity, mortality, and health care utilization.4e6 The authors declare no conflicts of interest. The research reported in this article was supported by a grant (GR-20102310662) from Ministero della Salute “Ricerca Finalizzata Giovani Ricercatori.” URL Ministero della Salute: http://www.salute.gov.it/portale/temi/p2_5.jsp?lingua¼ italiano&area¼Ricerca%20sanitaria&menu¼finalizzata. * Address correspondence to Palmira Bernocchi, PhD, Continuity Care Unit and Telemedicine Service, Istituti Clinici Scientifici Maugeri IRCCS, Via Salvatore Maugeri, 27100 Pavia, Italy. E-mail address: [email protected] (P. Bernocchi). https://doi.org/10.1016/j.jamda.2018.09.003 1525-8610/Ó 2018 AMDA e The Society for Post-Acute and Long-Term Care Medicine.
The importance of the role of comorbidities in predicting falls was reported in a recent published review7: according to the authors, some chronic conditions, such as stroke, arthritis, or diabetes independently predict the risk of first-time falling as well as recurrent falling in the older population, whereas other chronic conditions, such as asthma, chronic obstructive pulmonary disease, and heart attack predict only the risk of recurrent falling. Fall prevention is so important that in 2012 the European Commission set up a joint group of experts on Active and Healthy Aging (AHA) to promote the implementation of a dynamic, holistic, feasible approach for fall prevention Europe-wide, based on social/care interventions at the national and regional levels.8 This integrated approach necessitates an effective, reliable
2
P. Bernocchi et al. / JAMDA xxx (2018) 1e7
communication and coordination between professionals, caregivers, and patients involved. Information and communication technologies are indispensable for a supportive information flow and shared decision making as well as for training and education. The interventions commence with awareness-building, risk identification, and prevention4,9 and proceed to treatment and rehabilitation of patients who have already fallen or are at high risk.10,11 Several fall prevention strategies involving educational support, physical exercise, and modification of environmental factors have been evaluated in older community-dwellers.2,12,13 However, even when programs were successful in a controlled trial, the transfer to the real-world setting did not always result in effectively preventing falls.14 It is known that the risk of falls is increased in the posthospitalization phase. When older patients are discharged home, they have to face important challenges to their frailty.15 Therefore, specific education programs need to be designed to prevent falls.16 In this scenario, our structured home fall prevention program was proposed to older patients with 1 or more chronic diseases returning home after in-hospital rehabilitation for their chronic condition. The aim of this study was to investigate the feasibility and efficacy of a tele-rehabilitation program integrated with medical/nursing telesurveillance (Home-TeleHealth), compared to conventional care, in terms of (1) incidence of falls at home in the 6-month period after randomization (primary outcome), and (2) time free to the first fall event and number of patients sustaining 2 or more falls, as well as changes in functional status, fall risk and gait/balance problems, changes in the fear of falling, and in quality of life (secondary outcomes).
Methods Study Design and Randomization This was a randomized controlled trial with a 6-month prospective follow-up. Detailed methods are reported elsewhere.17 The institutional review board (CEC deliberation No. 973, February 2014) approved the study, which was registered on June 18, 2015, at http:// www.clinicaltrials.gov (NCT02487589) and was conducted according to the CONSORT guidelines, the principles of the Helsinki Declaration, and good clinical practice. All patients admitted to the Rehabilitation Institute of Istituti Clinici Scientifici Maugeri Istituto di Ricovero e Cura a Carattere Scientifico to undergo rehabilitation for their chronic cardiac, respiratory, neurologic, or neuromuscular condition(s), of either sex, aged 65 years or older were screened for inclusion. Patients who had a medium/high fall risk profile before discharge home, defined as a history of fall within the last 12 months and/or Berg Balance Scale (BBS)18 score 45, and/or at least 1 fall event during the hospital stay and who had a Mini-Mental State Examination (MMSE) score >18,19 were considered eligible. Exclusion criteria were low risk of recurrence of falling (BBS score > 45 and no fall during the previous 12 months and/or hospital stay), inability to sign the informed consent, cognitive impairment, living in a nursing home, permanent bedridden state, or full dependence on a wheelchair. We also excluded patients affected by terminal cancer or severe neurologic impairment, including perceptual neglect and language limitations (aphasia).17 Consenting eligible patients were allocated into either the control (CG) or intervention (IG) group (1:1 allocation ratio) using a computer-generated random allocation sequence (blocks of 4) concealed from researchers (http://www.randomization.com).
Intervention Group Prior to discharge, patients in IG received individual educational sessions, explaining the purpose and contents of Home-TeleHealth, conducted by the physiotherapist tutor (PT) and nurse tutor (NT), who followed them during the 6-month program. The program consisted of the following: 1. A fall prevention conducted by the PT involving individual home exercises, including strength, balance, and walking components based on the Otago Exercise Program.20 The PT designed a personalized program (high and low intensity) for each patient before discharge, and instructed patients and their caregivers on how to perform the exercises correctly. The intensity of the training could be adapted according to patients’ progress or modified if problems arose during the 6-month period.17 PT proposed exercises focused on improving balance and muscle strength, recommending that the patient go for regular walks (30 minutes, at least twice a week). Patients received a booklet with instructions for each exercise prescribed and a diary in which to record their activity and falls. The PT followed patients by a phone call at least every 2 weeks and by home visits in case of particular needs. 2. A telesurveillance: the NT made a weekly structured phone call to each patient, collecting information about the disease status, symptoms, and events; offering advice regarding diet, lifestyle, and medications as previously defined with the specialist supervising the program; and providing health education reinforcement on fall prevention for the patient and family. Patients could also contact the NT in the case of urgent need or emergency (24 hours/d 365 days/y). All patient data were recorded on a web platform (TeleMed, HTN, Brescia, Italy) accessible in real time by the physicians and the NT and PT participating in the study. To facilitate adherence to the program, the PT followed patients and caregivers in their exercise sessions through videoconference twice a month at least. The PT could monitor the exercise session in real time, tailoring the assistance to each single patient to minimize injury risk for the high-risk patients and maintain exercise adherence.17 In addition, information about adherence was collected during phone calls by the PT and NT, also asking patients to complete a diary at the end of each activity session. When available, caregivers could help the patients in some activities: helping with videoconference, looking after the patients during the exercise rehabilitation, and collecting signs and symptoms to refer to the NT and the PT. Control Group Patients allocated to CG received usual care by their general practitioner (GP). Usual practice after a fall consists mainly in treatment of the consequence of a fall but does not systematically address the patient’s risk behavior. Before hospital discharge, we also recommended to these patients that they perform exercises focused on improving balance and muscle strength and have a regular walk at least twice a week for at least 30 minutes, and we provided them with written information on fall risk factors. Once a month, participants in CG received a phone call by noncare personnel to check for incidence of falls, any hospitalizations, and related complications. Measurements Feasibility of the program was assessed in terms of side effects related to Home-TeleHealth, the number of patients who completed the program, and the rate of compliance to the prescribed training
P. Bernocchi et al. / JAMDA xxx (2018) 1e7
sessions (% performed). Satisfaction about the assistance was rated by the patient at T1 on a 6-item ad hoc questionnaire, with a score from 0 (not at all satisfied) to 4 (very satisfied); the questionnaire inquired about the service as a whole, the use of the devices, the health care professionals’ willingness, the clarity of the information and suggestions, the feeling of support, and if the service was felt to be a real help or not.
Outcome Measures The primary outcome was the incidence of falls in the 6-month period after randomization. A fall was defined as “inadvertently coming to rest on the ground, floor or other lower level.”1
3
An educational program to recognize falls was conducted for all the patients during the in-hospital rehabilitation and a monthly structured phone interview was done every month both in intervention and control group. Secondary outcomes were the time free to the first fall event, the number of patients sustaining 2 or more falls, and changes (T1-T0) in (1) functional status, with the Activities of Daily Living scale,21 Barthel Index,22 and Instrumental ADL scale23; (2) fall risk, measured by the BBS18; (3) gait and balance, measured by the Timed Up & Go test (TUG)24; (4) fear of falling, measured by the Italian version of the Falls Efficacy Scale (FES)25,26; and (5) quality of life assessed with the EuroQol-5 Dimension (EQ-5D) questionnaire and EuroQol Visual Analog Scale.27,28 In both groups, the T0 and T1 measurements were assessed in the hospital.
Fig. 1. Study flow chart. (MMSE, Mini-Mental State Examination; HF, heart failure; COPD, chronic obstructive pulmonary disease.)
4
P. Bernocchi et al. / JAMDA xxx (2018) 1e7
Sample Size and Statistical Analysis A sample size for independent groups was calculated based on previously published RCT data demonstrating the feasibility and safety of the Otago Exercise Program for older adults to perform at home and its efficacy in reducing falls.29,30 In addition, on the basis of the results of a nonpublished observational study conducted in our Institute in a sample of 179 patients (aged 65 years, with mediumhigh fall risk profile, consecutively discharged from January to June 2013), we considered a probable fall rate of 25%. Consequently, we estimated that 200 patients (100 per group) would be needed to detect a reduction of 40% in fallers in the IG with respect to controls, with a power (1 e beta) of 80%, and alpha of 0.05. Allowing for the probability of dropouts (difficult to quantify because of the chronic diseases of our patient sample), we decided to include at least 140 patients in each group. Data are presented as mean and standard deviation, mean (95% confidence interval, CI), and number (percentage) for categorical and binary variables. Statistical analyses were performed using Stata 13 program (StataCorp, College Station, TX). Differences in baseline characteristics between groups were examined using parametric (t-test) and nonparametric (chi-square) tests. Data were primarily analyzed according to the intention-to-treat principle. An ontreatment analysis was subsequently performed to assess whether protocol deviations had caused bias. Chi-square analysis was used to compare the proportion of fallers versus nonfallers between groups. Fall probability was measured by means of Kaplan-Meier survival analysis of time to first event in 6 months, whereas the time to first event difference between groups was evaluated with the log-rank test. Analysis of variance with repeated measures was used to analyze differences in the secondary outcomes at 6 months between groups. The alpha level for all analyses was set at 0.05. Results A total of 283 patients were enrolled between April 2014 and December 2015 and were randomized: 141 to IG and 142 to CG. Follow-up ended in June 2016. A study flow chart is presented in Figure 1. Patients had a mean age of 79 6.6 years, were mostly female (59%), and had a mean physical burden of illness, as measured by the Cumulative Illness Rating Scale (CIRS), of 2.1 0.44 for the Illness Severity Index and 5.2 2.4 for the Comorbidity Index. Comorbidities were similar between the 2 groups. Patients’ baseline demographic and clinical characteristics are reported in Table 1. Feasibility An equal number of patients, 19 (13%), dropped out from both groups. In IG, 10 patients refused to follow the Home-TeleHealth, 5 patients were hospitalized, and 4 patients died. In CG, 11 patients refused to come to the final visit, 5 patients were hospitalized, and 3 patients died (Figure 1). In IG, no major side effects were observed. The mean duration of the Home-TeleHealth was 169 49 days, during which 6803 sessions, 48 33 per patient, of physical activities at home were performed. Overall mean compliance to the prescribed exercises was 82% 43%. The mean (standard deviation) compliance was 86% (40%) in 134 (95%) patients. Seven patients did not perform any activity at home. Considering only the sessions not supervised via videoconference, the overall mean compliance was 76% (30%). The NT and PT interventions conducted in IG during the 6-month program are reported in Table 2. Patients’ satisfaction with the program was very high in all 122 evaluated patients, with an overall mean score of 22.3 2.2.
Table 1 Demographic and Clinical Characteristics of Patients at Baseline
Age, y Female, n (%) Comorbidities: Respiratory, n (%) Cardiac, n (%) Neurological, n (%) Musculoskeletal, n (%) Diabetes, n (%) Hypertension, n (%) Atrial fibrillation, n (%) CIRS Severity Index CIRS Comorbidities Index MMSE BARTHEL Index ADL IADL Patients with falls in previous year, n (%) No. of falls per patient Walking aid, n (%) BBS TUG FES EQ-VAS EQ-5D EQ-5D Mobility index Moderate problems, n (%) Extreme problems, n (%) EQ-5D Self-care Moderate problems, n (%) Extreme problems, n (%) EQ-5D Usual activities Moderate problems, n (%) Extreme problems, n (%) EQ-5D Pain/discomfort Moderate problems, n (%) Extreme problems, n (%) EQ-5D Anxiety/depression Moderate problems, n (%) Extreme problems, n (%) No. of medications/patient Medication treatment ACE inhibitors/ARB, n (%) Ca2þ-antagonist, n (%) Other hypotensive drugs, n (%) Diuretics, n (%) Nitrates, n (%) Antiarrhythmics, n (%) b-Blockers, n (%) Hypoglycemic drugs, n (%) Benzodiazepines, n (%) SSRI, n (%) NASSA/SARI/TCA n (%) Antiparkinsonian drug Antiepileptic drugs, n (%)
Intervention Group (n ¼ 141)
Control Group (n ¼ 142)
P
77.9 6.0 84 (60)
79.3 7.0 84 (59)
.071 .961
57 (40) 76 (54) 63 (45) 69 (49) 35 (25) 75 (53) 42 (30) 2.0 0.5 5.0 2.5 25.6 3.3 69.4 23.2 4.5 1.7 4.4 2.2 103 (73)
43 (30) 75 (53) 68 (48) 65 (46) 41 (29) 79 (56) 28 (20) 2.1 0.4 5.5 2.5 24.9 3.6 70 21.6 4.7 1.6 4.6 2.1 92 (65)
.068 .949 .593 .679 .526 .769 .068 .183 .120 .092 .822 .218 .453 .169
1.6 1.9 99 (70) 32.3 11.6 3.1 1.2 21.9 6.7 52.4 22.9 0.21 0.52
1.5 1.7 94 (66) 30.1 11.8 3.0 1.1 21.0 6.4 51.5 22.6 0.30 0.46
.539 .550 .113 .559 .244 .764 .127
104 (74) 4 (3)
106 (75) 3 (2)
.990
84 (60) 13 (9)
67 (47) 13 (9)
.749
82 (58) 24 (17)
81 (57) 17 (12)
.443
71 (50) 27 (19)
81 (57) 21 (15)
.324
51 (36) 21 (15) 4.0 2.0
64 (45) 12 (8) 3.8 2.0
.079
73 45 23 85 14 26 65 30 61 40 13 11 17
(52) (32) (16) (60) (10) (18) (46) (21) (43) (29) (9) (8) (12)
91 52 28 78 21 14 57 38 58 43 10 13 23
(64) (37) (20) (55) (15) (10) (40) (27) (41) (30) (7) (9) (16)
.332 .048 .477 .555 .429 .289 .057 .372 .347 .771 .824 .651 .845 .407
ACE, angiotensin converting enzyme; ADL, Activities of Daily Living scale; ARB, angiotensin receptor blockers; CIRS, Cumulative Illness Rating Scale; EQ-VAS, EuroQol Visual Analog Scale; EQ-5D, EuroQol-5 Dimension questionnaire; IADL, Instrumental Activities of Daily Living scale; NASSA, noradrenergic and specific serotonergic antidepressant; SARI, serotonin antagonist and reuptake inhibitor; SSRI, selective serotonin reuptake inhibitor; TCA, tricyclic antidepressants; TUG, Timed Up & Go test. Data are presented as number (%) or mean standard deviation.
Outcomes Primary outcome During the 6-month period after hospital discharge, 85 patients had at least 1 fall at home: 29 (20.6%) in IG and 56 (39.4%) in CG (P < .001). Intention-to-treat analysis showed a significant reduction in the risk of fall in IG with respect to CG (RR ¼ 0.60, 95% CI: 0.44-0.83;
P. Bernocchi et al. / JAMDA xxx (2018) 1e7 Table 2 Nursing/Physiotherapist Interventions Carried out in the Intervention Group During the 6-Month Program Interventions Performed
Mean SD per Patient; Total Number (Percentage)
Scheduled contacts by NT Actions undertaken during scheduled contacts Disease status, symptoms verification and events verification, counseling Therapeutic compliance verifications Therapeutic changes Contacts with specialists Contacts with GP Unscheduled contacts with NT Actions undertaken during unscheduled contacts Disease status, symptoms and events verification, counseling Therapeutic compliance verifications Therapeutic changes Contacts with specialists or GP Suggested sending to the ER Scheduled contacts by PT Home visits by PT Videoconferences by PT
25 11; 3507 3507 (100) 2655 (76) 127 (4) 297 (8) 50 (1.4) 1.7 2.5; 234
150 (64) 28 (12) 9 (4) 39 (17) 12 (5) 16 9; 2179 0.5 1.1; 69 12 9; 739
ER, emergency room; SD, standard deviation.
P < .001). The analysis by protocol confirmed the positive effect of Home-TeleHealth (RR ¼ 0.59; 95% CI: 0.42-0.81; P < .001). Secondary outcomes Figure 2 shows results of the Kaplan-Meier survival analysis of time to event. Mean time to fall was significantly longer in IG than CG: 152 58 versus 134 62 days (P ¼ .001, log-rank test). The number of patients who experienced 2 or more falls was 11 (8%) in IG versus 24 (17%) in CG (P ¼ .020). Table 3 shows the changes after 6 months in all parameters. Functional status improved much more in IG. BBS significantly improved and Timed Up & Go test significantly decreased only in IG. FES significantly increased in CG and was unchanged in IG. Analyzing the percentage of patients by different levels of fear of falling (no fear: FES ¼ 16; low fear: FES 17-19; medium fear: FES 2027; high fear: FES 28-64), patient distribution among the different
Fig. 2. Kaplan-Meier survival analysis of time to first fall. Survival difference between groups was evaluated with the log rank test. The solid line represents the control group and dotted line represents the intervention group.
5
categories was similar at T0 in the 2 groups (P ¼ .130). But whereas in CG the percentage of patients with high fear doubled (P ¼ .006), in IG the percentage of patients who expressed no fear increased, though not significantly (P ¼ .060) with respect to T0. EQ-5D and EuroQol Visual Analog Scale significantly improved only in IG. Analysis of variance for repeated measures (times and groups) confirmed the significant improvement in IG compared to CG for Barthel Index, BBS, Timed Up & Go test, and EuroQol Visual Analog Scale scores. EQ-5D did not significantly differ for time and group but, analyzing each individual component, the mobility index of EQ5D was significantly improved only in IG: the mean (95% CI) delta (T1-T0) was 0.33 (0.44 to 0.22) in IG and 0.06 (1.77 to 0.05) in CG, P ¼ .001. Discussion In this study, we tested the feasibility and efficacy of a telerehabilitation home-based program integrated with medical/ nursing telesurveillance in preventing falls in older chronic disease patients at high risk of falling who were discharged home after a period of in-hospital rehabilitation. The feasibility and safety of the program were demonstrated by the absence of side effects and by the high compliance and patient satisfaction with the program. The efficacy was demonstrated by the significant reduction in risk of falls at 6 months in IG compared to CG and by the fact that the only variable related to the fall event was the treatment group. Moreover, Kaplan-Meier survival curves showed that, while in CG fall events continued over time, in IG there was a significant decline in the trend to fall already evident from month 2. The percentage of patients experiencing 2 or more falls in the study period was significantly lower in IG. Functional status improved in both groups, but more significantly in IG, whereas both risk of falling and balance-related problems improved significantly only in IG. Conversely, fear of falling and the number of patients with high values of FES increased in CG during the 6 months, whereas in IG, the overall value was unchanged but there was an increase in the number of patients with lesser fear of falling, perhaps because of greater patient awareness after the home rehabilitation. Quality of life significantly improved only in IG, in particular, the mobility index. These findings highlight the need for continuous motivational and educational input, provided here as remote reinforcement by the NT and PT through scheduled phone calls and videoconference. Patients need both to be continually encouraged to perform physical exercise in order to maintain an adequate level of independence in activities of daily living and to be sensitized and equipped to recognize early signs/ symptoms of worsening. At the moment of discharge, we advised all patients to continue at home the activity learnt in the rehabilitation hospital, and gave them some educational material on home physical activity. We knew that in real life, however, only a small number of patients would continue performing the physical activity prescribed at discharge; a great number of patients started but then gave up, and the gains achieved during in-hospital rehabilitation were lost after a few weeks. For this reason, we think that it is important to carry out home multidisciplinary programs convincing patients to continue the activity at home. The results of our integrated NT and PT program received a very high response from patients with an overall compliance to the prescribed exercise of 82%. In older adults, often suffering from 1 or more chronic diseases, the use of multiple drugs, lack of exercise, inadequate housing, and inappropriate footwear lead to a high risk of falling, which is often underestimated by the patients themselves as well as by those they live with and the GP. Behavioral modification for a healthier lifestyle is a key ingredient to encourage healthy aging and avoid falls,29 but too
6
P. Bernocchi et al. / JAMDA xxx (2018) 1e7
Table 3 Results on Changes at 6 Months in the Studied Parameters Intervention Group
Barthel ADL IADL BBS TUG FES No fear (FES ¼ 16), n (%) Low fear (FES 17-19), n (%) Medium fear (FES 20-27), n (%) High fear (FES 28-64), n (%) EQ-VAS EQ-5D
Control Group
P (Time/Group)
Pre (n ¼ 141)
Post (n ¼ 122)
P (Pre-Post)
Pre (n ¼ 142)
Post (n ¼ 123)
P (Pre-Post)
69.4 4.5 4.4 32.3 3.1 21.9 35 29 53 24 52.4 0.21
84.6 4.9 4.8 38.5 2.5 22.5 44 15 35 28 63.8 0.42
<.001 .02 .16 <.001 <.001 .46 .004
70.0 4.7 4.6 30.1 3.0 21.0 37 37 51 17 51.5 0.30
76.2 4.5 4.6 32.8 2.8 23.5 29 19 43 32 53.5 0.18
.02 .29 .90 .09 .15 .004 .001
<.001 .5914 .6914 <.001 <.001 .040
.50 .10
<.001 .258
(65.5-73.3) (4.2-4.7) (4.1-4.8) (30.4-34.3) (2.9-3.3) (20.8-23.0) (25) (20) (38) (17) (48.5-56.2) (0.13-0.30)
(81.6-87.6) (4.7-5.2) (4.5-5.2) (36.4-40.7) (2.3-2.7) (21.2-23.9) (36) (12) (29) (23) (59.8-67.8) (0.33-0.50)
<.001 .001
(66.4-73.6) (4.4-5.0) (4.3-5.0) (28.2-32.1) (2.9-3.2) (20.0-22.1) (26) (26) (36) (12) (47-55.3) (0.22-0.38)
(72.3-80.1) (4.2-4.8) (4.2-5.0) (30.3-35.3) (2.6-3.1) (22.2-24.9) (24) (15) (35) (26) (49.2-57.6) (0.07-0.29)
ADL, Activities of Daily Living scale; BS, Berg Balance Scale; EQ-5D, EuroQol-5 Dimension questionnaire; EQ-VAS, EuroQol Visual Analog Scale; FES, Falls Efficacy Scale; IADL, Instrumental Activities of Daily Living scale; TUG, Timed Up & Go test. Data are presented as number (%) or as mean and 95% confidence interval. Analysis of variance with repeated measures was used to analyze differences in the secondary outcomes at 6 months between groups.
often these decisions are made when one or more falls have already occurred. It is important that the risk of falling be perceived as a problem that needs to be faced when the patient is still at home.31 Multifactorial personalized interventions need to be undertaken, as well as prevention and education programs involving all in a proactive way, from the patient to the GP.9,11,32,33 We chose in this study, focused on falls reduction, to combine an individual home exercise program featuring strength, balance, and walking components, adapted from the Otago Exercise Program,20 with our proven model of tele-rehabilitation and home surveillance, already tested and adopted in the management and home rehabilitation of chronic and complex older patients.34 We have shown that a structured physician-directed, nurse, and physiotherapist-managed telephone/videoconference support and telemonitoring program for chronic patients can be better than the standard of care. Disabled older adults, if supported by a structured program, and even with limited prior experience using computers, are not resistant to using technology to access new types of health care service.35,36 We decided to set up this long-term tele-health service, with the physiotherapist and nurse playing the key role and using information and communication technologies as a support to empower the patient, in order to achieve optimal patient adherence both to physical and medical therapy, and to provide the patient with tools to better recognize signs/symptoms of deterioration and learn how to avoid falls. Limitations Notwithstanding its prospective design, this study has several limitations. First, because of the nature of the trial, it was not possible to blind patients and health care personnel to the group allocation. However, outcome assessors and data analysts were blinded. Second, this was a single-center study. Third, fallsdboth prehospitalization and occurring during the 6-month follow-up at homedwere selfreported: falls without injury at home may have been less reported than falls causing injury, although the presence of the caregiver should have minimized this bias in both groups. Conclusions In summary, our tele-rehabilitation program, integrated with medical/nursing tele-surveillance, was feasible, safe, and effective in preventing falls in older chronic disease patients.
Acknowledgments The authors thank Rosemary Allpress for the English revision. A special thanks to Dr. Amerigo Giordano for the scientific support. We also thank the following people: nurses: Giuliano Assoni, Margherita Zanardini, Marta Giunta; physiotherapists: Mara Paneroni, Alessandra Goffi, Fabio Vanoglio, Gian Pietro Bonometti, Francesca Capatori, Palini laura, Alessandra Montini; physicians: Emanuela Zanelli, Michele Vitacca, Alberto Luisa, Bernardo Gialanella; psychologists: Silvana Rocchi, Alessandra Pezzini, Lidia Gazzi; technicians: Roberta Ardesi, Patrizia Martina, Adriana Olivares, Gloria Francolini. References 1. World Health Organization. WHO Global Report on Falls Prevention in Older Age 2007. Available at: www.who.int/violenceinjuryprevention/publications/ otherinjury/fallspreventionpdf?ua¼1. Accessed December 19, 2017. 2. Gillespie LD, Robertson MC, Gillespie WJ, et al. Interventions for preventing falls in older people living in the community. Cochrane Database Syst Rev; 2012:CD007146. 3. Close J, Ellis M, Hooper R. Prevention of Falls in Elderly Trial (PROFET): A randomised controlled trial. Lancet 1999;353:93e97. 4. Rubinstein LZ. Falls in older people: Epidemiology, risk factors and strategies for prevention. Age Aging 2006;35:ii37eii41. 5. Chang JT, Morton SC, Rubenstein LZ, et al. Interventions for the prevention of falls in older adults: Systematic review and meta-analysis of randomised clinical trials. BMJ 2004;328:680. 6. Murray CJ, Vos T, Lozano R, et al. Disability-adjusted life years (DALYs) for 291 diseases and injuries in 21 regions, 1990e2010: A systematic analysis for the Global Burden of Disease Study 2010. Lancet 2012;380:2197e2223. 7. Paliwal Y, Slattum PW, Ratliff SM. Chronic health conditions as a risk factor for falls among the community-dwelling US older adults: A zero-inflated regression modeling approach. Biomed Res Int 2017;2017:5146378. 8. European Innovation Partnership (EIP) on Active and Healthy Aging (AHA). Personalised Health Management and Falls Prevention. State of play of Action Group A2. Available at: https://ec.europa.eu/eip/ageing/library/state-playaction-group-a2-0_en. Accessed December 19, 2017. 9. NICE clinical guideline 161. Assessment and prevention of falls in older people. Available at: https://www.nice.org.uk/guidance/cg161/evidence/falls-fullguidance-190033741; 2013. Accessed December 19, 2017. 10. Matchar DB, Duncan PW, Lien CT, et al. Randomized controlled trial of screening, risk modification, and physical therapy to prevent falls among the elderly recently discharged from the emergency department to the community: The steps to avoid falls in the elderly study. Arch Phys Med Rehabil 2017; 98:1086e1096. 11. Hill AM, Etherton-Beer C, Haines TP. Tailored education for older patients to facilitate engagement in falls prevention strategies after hospital dischargeda pilot randomized controlled trial. PLoS One 2013;23:e63450. 12. Brach JS, Perera S, Gilmore S, et al. Effectiveness of a timing and coordination group exercise program to improve mobility in community-dwelling older adults. A randomized clinical trial. JAMA Intern Med 2017;177:1437e1444. 13. Sherrington C, Michaleff ZA, Fairhall N, et al. Exercise to prevent falls in older adults: An updated systematic review and meta-analysis. Br J Sports Med 2017; 51:1749e1757.
P. Bernocchi et al. / JAMDA xxx (2018) 1e7 14. Elley CR, Robertson MC, Garrett S, et al. Effectiveness of a falls-and-fracture nurse coordinator to reduce falls: A randomized, controlled trial of at risk older adults. J Am Geriatr Soc 2008;56:1383. 15. Kripalani S, Jackson AT, Schnipper JL, Coleman EA. Promoting effective transitions of care at hospital discharge: A review of key issues for hospitalists. J Hosp Med 2007;2:314e323. 16. Hill AM, Hoffmann T, Beer C, et al. Falls after discharge from hospital: Is there a gap between older peoples’ knowledge about falls prevention strategies and the research evidence? Gerontologist 2011;51:653e662. 17. Giordano A, Bonometti GP, Vanoglio F, et al. Feasibility and cost-effectiveness of a multidisciplinary home-telehealth intervention programme to reduce falls among elderly discharged from hospital: Study protocol for a randomized controlled trial. BMC Geriatr 2016;16:20. 18. Mackintosh SF, Hill KD, Dodd KJ, et al. Balance Score and a history of falls in hospital predict recurrent falls in the 6 months following stroke rehabilitation. Arch Phys Med Rehabil 2006;87:1583e1589. 19. Brucki SM, Nitrini R, Caramelli P, et al. Suggestions for utilization of the MiniMental State Examination in Brazil. Arq Neuropsiquiatr 2003;61:777e781. 20. Otago Exercise Programme. Available at: http://www.acc.co.nz/PRD_EXT_ CSMP/groups/external_providers/documents/publications_promotion/prd_ ctrb118334.pdf. Accessed December 20, 2017. 21. Katz TF. A.D.L. Activities of Daily Living. JAMA 1963;185:914. 22. Mahoney FI, Barthel DW. Functional evaluation: The Barthel Index. Md State Med J 1965;14:61e65. 23. Lawton MP, Brody EM. Assessment of older people: Self-maintaining and instrumental activities of daily living. Gerontologist 1969;9:179e186. 24. Podsiadlo D, Richardson S. The Timed “Up & Go”: A test of basic functional mobility for frail elderly persons. J Am Geriatr Soc 1991;39:142e148. 25. Tinetti ME, Mendes de Leon CF, Doucette JT, Baker DI. Fear of falling and fallrelated efficacy in relationship to functioning among community-living elders. J Gerontol 1994;49:M140eM147.
7
26. Elmo A, Ruggiero C, Mariani T, et al. Validazione della FES-I e della FES-I breve in anziani viventi in comunità. J Gerontol Geriatr 2010;58: 259e263. 27. Brooks R, Rabin R, de Charro F, editors. The Measurement and Valuation of Health Status Using EQ-5D: A European Prospective. London: Kluwer Academic; 2003. 28. Balestroni G, Bertolotti G. EuroQol-5D (EQ-5D): An instrument for measuring quality of life. Monaldi Arch Chest Dis 2012;78:155e159. 29. Robertson MC, Campbell AJ, Gardner MM, Devlin N. Preventing injuries in older people by preventing falls: A meta-analysis of individual-level data. J Am Geriatr Soc 2002;50:905e911. 30. Sherrington C, Whitney JC, Lord SR, et al. Effective exercise for the prevention of falls: A systematic review and meta-analysis. J Am Geriatr Soc 2008;56: 2234e2243. 31. Campbell AJ, Robertson MC, Garder MG, et al. Randomized controlled trial of a general practice programme of home based exercise to prevent falls in elderly women. Br Med J 1997;315:1065e1069. 32. Peel NM, McClure RJ, Hendrikz JK. Health-protective behaviours and risk of fallrelated hip fractures: A population-based case-control study. Age Ageing 2006; 35:491e497. 33. Yardley L, Bishop FL, Beyer N, et al. Older people’s views of fallsprevention interventions in six European countries. Gerontologist 2006; 46:650e660. 34. Bernocchi P, Vitacca M, La Rovere MT, et al. Home-based telerehabilitation in older patients with chronic obstructive pulmonary disease and heart failure: A randomised controlled trial. Age Ageing 2018;47:82e88. 35. Marziali E. E-Health program for patients with chronic disease. Telemed eHealth 2009;15:176e182. 36. Bernocchi P, Vanoglio F, Baratti D, et al. Home-based telesurveillance and rehabilitation after stroke: A real-life study. Top Stroke Rehabil 2016;23: 106e115.
JAMDA journal homepage: www.jamda.com
Original Study
Feasibility and Clinical Efficacy of a Multidisciplinary Home-Telehealth Program to Prevent Falls in Older Adults: A Randomized Controlled Trial Palmira Bernocchi PhD a, *, Alessandro Giordano MD b, Giuseppe Pintavalle PT a, Tiziana Galli PT a, Eleonora Ballini Spoglia a, Doriana Baratti a, Simonetta Scalvini MD a, b a b
Istituti Clinici Scientifici Maugeri IRCCS, a Care Continuity Unit and Telemedicine Service, Institute of Lumezzane, Brescia, Italy Cardiology Department of the Institute of Lumezzane, Brescia, Italy
a b s t r a c t Keywords: Fall prevention home tele-rehabilitation older adults chronic disease telemedicine
Objectives: The aim of this study was to determine the feasibility and efficacy of a 6-month telerehabilitation home-based program, designed to prevent falls in older adults with 1 or more chronic diseases (cardiac, respiratory, neuromuscular or neurologic) returning home after in-hospital rehabilitation for their chronic condition. Patients were eligible for selection if they had experienced a fall during the previous year or were at high risk of falling. Design: Randomized controlled trial. Tele-rehabilitation consisted of a falls prevention program run by the physiotherapist involving individual home exercise (strength, balance, and walking) and a weekly structured phone-call by the nurse inquiring about the disease status and symptoms and providing patient support. Setting and Participants: Two hundred eighty-three patients (age 79 6.6 years; F ¼ 59%) with high risk of falls and discharged home after in-hospital rehabilitation were randomized to receive home-based program (intervention group, n ¼ 141) or conventional care (control group, n ¼ 142). Measures: Incidence of falls at home in the 6-month period (primary outcome); time free to the first fall and proportion of patients sustaining 2 falls (secondary outcomes). Results: During the 6 months, 85 patients fell at least once: 29 (20.6%) in the Intervention Group versus 56 (39.4%) in the control group (P < .001). The risk of falls was significantly reduced in the intervention group (relative risk ¼0.60, 95% confidence interval: 0.44-0.83; P < .001). The mean standard deviation time to first fall was significantly longer in intervention group than control group (152 58 vs 134 62 days; P ¼ .001). Significantly, fewer patients experienced 2 falls in the intervention group than in the control group: 11 (8%) versus 24 (17%), P ¼ .020. Conclusions: A 6-month tele-rehabilitation home-based program integrated with medical/nursing telesurveillance is feasible and effective in preventing falls in older chronic disease patients with a high risk of falling. Ó 2018 AMDA e The Society for Post-Acute and Long-Term Care Medicine.
Inadvertent falls and consequent injuries are a major public health problem in older adults often requiring medical attention.1,2 A person who has fallen once is at higher risk of falling again3 and has increased morbidity, mortality, and health care utilization.4e6 The authors declare no conflicts of interest. The research reported in this article was supported by a grant (GR-20102310662) from Ministero della Salute “Ricerca Finalizzata Giovani Ricercatori.” URL Ministero della Salute: http://www.salute.gov.it/portale/temi/p2_5.jsp?lingua¼ italiano&area¼Ricerca%20sanitaria&menu¼finalizzata. * Address correspondence to Palmira Bernocchi, PhD, Continuity Care Unit and Telemedicine Service, Istituti Clinici Scientifici Maugeri IRCCS, Via Salvatore Maugeri, 27100 Pavia, Italy. E-mail address: [email protected] (P. Bernocchi). https://doi.org/10.1016/j.jamda.2018.09.003 1525-8610/Ó 2018 AMDA e The Society for Post-Acute and Long-Term Care Medicine.
The importance of the role of comorbidities in predicting falls was reported in a recent published review7: according to the authors, some chronic conditions, such as stroke, arthritis, or diabetes independently predict the risk of first-time falling as well as recurrent falling in the older population, whereas other chronic conditions, such as asthma, chronic obstructive pulmonary disease, and heart attack predict only the risk of recurrent falling. Fall prevention is so important that in 2012 the European Commission set up a joint group of experts on Active and Healthy Aging (AHA) to promote the implementation of a dynamic, holistic, feasible approach for fall prevention Europe-wide, based on social/care interventions at the national and regional levels.8 This integrated approach necessitates an effective, reliable
2
P. Bernocchi et al. / JAMDA xxx (2018) 1e7
communication and coordination between professionals, caregivers, and patients involved. Information and communication technologies are indispensable for a supportive information flow and shared decision making as well as for training and education. The interventions commence with awareness-building, risk identification, and prevention4,9 and proceed to treatment and rehabilitation of patients who have already fallen or are at high risk.10,11 Several fall prevention strategies involving educational support, physical exercise, and modification of environmental factors have been evaluated in older community-dwellers.2,12,13 However, even when programs were successful in a controlled trial, the transfer to the real-world setting did not always result in effectively preventing falls.14 It is known that the risk of falls is increased in the posthospitalization phase. When older patients are discharged home, they have to face important challenges to their frailty.15 Therefore, specific education programs need to be designed to prevent falls.16 In this scenario, our structured home fall prevention program was proposed to older patients with 1 or more chronic diseases returning home after in-hospital rehabilitation for their chronic condition. The aim of this study was to investigate the feasibility and efficacy of a tele-rehabilitation program integrated with medical/nursing telesurveillance (Home-TeleHealth), compared to conventional care, in terms of (1) incidence of falls at home in the 6-month period after randomization (primary outcome), and (2) time free to the first fall event and number of patients sustaining 2 or more falls, as well as changes in functional status, fall risk and gait/balance problems, changes in the fear of falling, and in quality of life (secondary outcomes).
Methods Study Design and Randomization This was a randomized controlled trial with a 6-month prospective follow-up. Detailed methods are reported elsewhere.17 The institutional review board (CEC deliberation No. 973, February 2014) approved the study, which was registered on June 18, 2015, at http:// www.clinicaltrials.gov (NCT02487589) and was conducted according to the CONSORT guidelines, the principles of the Helsinki Declaration, and good clinical practice. All patients admitted to the Rehabilitation Institute of Istituti Clinici Scientifici Maugeri Istituto di Ricovero e Cura a Carattere Scientifico to undergo rehabilitation for their chronic cardiac, respiratory, neurologic, or neuromuscular condition(s), of either sex, aged 65 years or older were screened for inclusion. Patients who had a medium/high fall risk profile before discharge home, defined as a history of fall within the last 12 months and/or Berg Balance Scale (BBS)18 score 45, and/or at least 1 fall event during the hospital stay and who had a Mini-Mental State Examination (MMSE) score >18,19 were considered eligible. Exclusion criteria were low risk of recurrence of falling (BBS score > 45 and no fall during the previous 12 months and/or hospital stay), inability to sign the informed consent, cognitive impairment, living in a nursing home, permanent bedridden state, or full dependence on a wheelchair. We also excluded patients affected by terminal cancer or severe neurologic impairment, including perceptual neglect and language limitations (aphasia).17 Consenting eligible patients were allocated into either the control (CG) or intervention (IG) group (1:1 allocation ratio) using a computer-generated random allocation sequence (blocks of 4) concealed from researchers (http://www.randomization.com).
Intervention Group Prior to discharge, patients in IG received individual educational sessions, explaining the purpose and contents of Home-TeleHealth, conducted by the physiotherapist tutor (PT) and nurse tutor (NT), who followed them during the 6-month program. The program consisted of the following: 1. A fall prevention conducted by the PT involving individual home exercises, including strength, balance, and walking components based on the Otago Exercise Program.20 The PT designed a personalized program (high and low intensity) for each patient before discharge, and instructed patients and their caregivers on how to perform the exercises correctly. The intensity of the training could be adapted according to patients’ progress or modified if problems arose during the 6-month period.17 PT proposed exercises focused on improving balance and muscle strength, recommending that the patient go for regular walks (30 minutes, at least twice a week). Patients received a booklet with instructions for each exercise prescribed and a diary in which to record their activity and falls. The PT followed patients by a phone call at least every 2 weeks and by home visits in case of particular needs. 2. A telesurveillance: the NT made a weekly structured phone call to each patient, collecting information about the disease status, symptoms, and events; offering advice regarding diet, lifestyle, and medications as previously defined with the specialist supervising the program; and providing health education reinforcement on fall prevention for the patient and family. Patients could also contact the NT in the case of urgent need or emergency (24 hours/d 365 days/y). All patient data were recorded on a web platform (TeleMed, HTN, Brescia, Italy) accessible in real time by the physicians and the NT and PT participating in the study. To facilitate adherence to the program, the PT followed patients and caregivers in their exercise sessions through videoconference twice a month at least. The PT could monitor the exercise session in real time, tailoring the assistance to each single patient to minimize injury risk for the high-risk patients and maintain exercise adherence.17 In addition, information about adherence was collected during phone calls by the PT and NT, also asking patients to complete a diary at the end of each activity session. When available, caregivers could help the patients in some activities: helping with videoconference, looking after the patients during the exercise rehabilitation, and collecting signs and symptoms to refer to the NT and the PT. Control Group Patients allocated to CG received usual care by their general practitioner (GP). Usual practice after a fall consists mainly in treatment of the consequence of a fall but does not systematically address the patient’s risk behavior. Before hospital discharge, we also recommended to these patients that they perform exercises focused on improving balance and muscle strength and have a regular walk at least twice a week for at least 30 minutes, and we provided them with written information on fall risk factors. Once a month, participants in CG received a phone call by noncare personnel to check for incidence of falls, any hospitalizations, and related complications. Measurements Feasibility of the program was assessed in terms of side effects related to Home-TeleHealth, the number of patients who completed the program, and the rate of compliance to the prescribed training
P. Bernocchi et al. / JAMDA xxx (2018) 1e7
sessions (% performed). Satisfaction about the assistance was rated by the patient at T1 on a 6-item ad hoc questionnaire, with a score from 0 (not at all satisfied) to 4 (very satisfied); the questionnaire inquired about the service as a whole, the use of the devices, the health care professionals’ willingness, the clarity of the information and suggestions, the feeling of support, and if the service was felt to be a real help or not.
Outcome Measures The primary outcome was the incidence of falls in the 6-month period after randomization. A fall was defined as “inadvertently coming to rest on the ground, floor or other lower level.”1
3
An educational program to recognize falls was conducted for all the patients during the in-hospital rehabilitation and a monthly structured phone interview was done every month both in intervention and control group. Secondary outcomes were the time free to the first fall event, the number of patients sustaining 2 or more falls, and changes (T1-T0) in (1) functional status, with the Activities of Daily Living scale,21 Barthel Index,22 and Instrumental ADL scale23; (2) fall risk, measured by the BBS18; (3) gait and balance, measured by the Timed Up & Go test (TUG)24; (4) fear of falling, measured by the Italian version of the Falls Efficacy Scale (FES)25,26; and (5) quality of life assessed with the EuroQol-5 Dimension (EQ-5D) questionnaire and EuroQol Visual Analog Scale.27,28 In both groups, the T0 and T1 measurements were assessed in the hospital.
Fig. 1. Study flow chart. (MMSE, Mini-Mental State Examination; HF, heart failure; COPD, chronic obstructive pulmonary disease.)
4
P. Bernocchi et al. / JAMDA xxx (2018) 1e7
Sample Size and Statistical Analysis A sample size for independent groups was calculated based on previously published RCT data demonstrating the feasibility and safety of the Otago Exercise Program for older adults to perform at home and its efficacy in reducing falls.29,30 In addition, on the basis of the results of a nonpublished observational study conducted in our Institute in a sample of 179 patients (aged 65 years, with mediumhigh fall risk profile, consecutively discharged from January to June 2013), we considered a probable fall rate of 25%. Consequently, we estimated that 200 patients (100 per group) would be needed to detect a reduction of 40% in fallers in the IG with respect to controls, with a power (1 e beta) of 80%, and alpha of 0.05. Allowing for the probability of dropouts (difficult to quantify because of the chronic diseases of our patient sample), we decided to include at least 140 patients in each group. Data are presented as mean and standard deviation, mean (95% confidence interval, CI), and number (percentage) for categorical and binary variables. Statistical analyses were performed using Stata 13 program (StataCorp, College Station, TX). Differences in baseline characteristics between groups were examined using parametric (t-test) and nonparametric (chi-square) tests. Data were primarily analyzed according to the intention-to-treat principle. An ontreatment analysis was subsequently performed to assess whether protocol deviations had caused bias. Chi-square analysis was used to compare the proportion of fallers versus nonfallers between groups. Fall probability was measured by means of Kaplan-Meier survival analysis of time to first event in 6 months, whereas the time to first event difference between groups was evaluated with the log-rank test. Analysis of variance with repeated measures was used to analyze differences in the secondary outcomes at 6 months between groups. The alpha level for all analyses was set at 0.05. Results A total of 283 patients were enrolled between April 2014 and December 2015 and were randomized: 141 to IG and 142 to CG. Follow-up ended in June 2016. A study flow chart is presented in Figure 1. Patients had a mean age of 79 6.6 years, were mostly female (59%), and had a mean physical burden of illness, as measured by the Cumulative Illness Rating Scale (CIRS), of 2.1 0.44 for the Illness Severity Index and 5.2 2.4 for the Comorbidity Index. Comorbidities were similar between the 2 groups. Patients’ baseline demographic and clinical characteristics are reported in Table 1. Feasibility An equal number of patients, 19 (13%), dropped out from both groups. In IG, 10 patients refused to follow the Home-TeleHealth, 5 patients were hospitalized, and 4 patients died. In CG, 11 patients refused to come to the final visit, 5 patients were hospitalized, and 3 patients died (Figure 1). In IG, no major side effects were observed. The mean duration of the Home-TeleHealth was 169 49 days, during which 6803 sessions, 48 33 per patient, of physical activities at home were performed. Overall mean compliance to the prescribed exercises was 82% 43%. The mean (standard deviation) compliance was 86% (40%) in 134 (95%) patients. Seven patients did not perform any activity at home. Considering only the sessions not supervised via videoconference, the overall mean compliance was 76% (30%). The NT and PT interventions conducted in IG during the 6-month program are reported in Table 2. Patients’ satisfaction with the program was very high in all 122 evaluated patients, with an overall mean score of 22.3 2.2.
Table 1 Demographic and Clinical Characteristics of Patients at Baseline
Age, y Female, n (%) Comorbidities: Respiratory, n (%) Cardiac, n (%) Neurological, n (%) Musculoskeletal, n (%) Diabetes, n (%) Hypertension, n (%) Atrial fibrillation, n (%) CIRS Severity Index CIRS Comorbidities Index MMSE BARTHEL Index ADL IADL Patients with falls in previous year, n (%) No. of falls per patient Walking aid, n (%) BBS TUG FES EQ-VAS EQ-5D EQ-5D Mobility index Moderate problems, n (%) Extreme problems, n (%) EQ-5D Self-care Moderate problems, n (%) Extreme problems, n (%) EQ-5D Usual activities Moderate problems, n (%) Extreme problems, n (%) EQ-5D Pain/discomfort Moderate problems, n (%) Extreme problems, n (%) EQ-5D Anxiety/depression Moderate problems, n (%) Extreme problems, n (%) No. of medications/patient Medication treatment ACE inhibitors/ARB, n (%) Ca2þ-antagonist, n (%) Other hypotensive drugs, n (%) Diuretics, n (%) Nitrates, n (%) Antiarrhythmics, n (%) b-Blockers, n (%) Hypoglycemic drugs, n (%) Benzodiazepines, n (%) SSRI, n (%) NASSA/SARI/TCA n (%) Antiparkinsonian drug Antiepileptic drugs, n (%)
Intervention Group (n ¼ 141)
Control Group (n ¼ 142)
P
77.9 6.0 84 (60)
79.3 7.0 84 (59)
.071 .961
57 (40) 76 (54) 63 (45) 69 (49) 35 (25) 75 (53) 42 (30) 2.0 0.5 5.0 2.5 25.6 3.3 69.4 23.2 4.5 1.7 4.4 2.2 103 (73)
43 (30) 75 (53) 68 (48) 65 (46) 41 (29) 79 (56) 28 (20) 2.1 0.4 5.5 2.5 24.9 3.6 70 21.6 4.7 1.6 4.6 2.1 92 (65)
.068 .949 .593 .679 .526 .769 .068 .183 .120 .092 .822 .218 .453 .169
1.6 1.9 99 (70) 32.3 11.6 3.1 1.2 21.9 6.7 52.4 22.9 0.21 0.52
1.5 1.7 94 (66) 30.1 11.8 3.0 1.1 21.0 6.4 51.5 22.6 0.30 0.46
.539 .550 .113 .559 .244 .764 .127
104 (74) 4 (3)
106 (75) 3 (2)
.990
84 (60) 13 (9)
67 (47) 13 (9)
.749
82 (58) 24 (17)
81 (57) 17 (12)
.443
71 (50) 27 (19)
81 (57) 21 (15)
.324
51 (36) 21 (15) 4.0 2.0
64 (45) 12 (8) 3.8 2.0
.079
73 45 23 85 14 26 65 30 61 40 13 11 17
(52) (32) (16) (60) (10) (18) (46) (21) (43) (29) (9) (8) (12)
91 52 28 78 21 14 57 38 58 43 10 13 23
(64) (37) (20) (55) (15) (10) (40) (27) (41) (30) (7) (9) (16)
.332 .048 .477 .555 .429 .289 .057 .372 .347 .771 .824 .651 .845 .407
ACE, angiotensin converting enzyme; ADL, Activities of Daily Living scale; ARB, angiotensin receptor blockers; CIRS, Cumulative Illness Rating Scale; EQ-VAS, EuroQol Visual Analog Scale; EQ-5D, EuroQol-5 Dimension questionnaire; IADL, Instrumental Activities of Daily Living scale; NASSA, noradrenergic and specific serotonergic antidepressant; SARI, serotonin antagonist and reuptake inhibitor; SSRI, selective serotonin reuptake inhibitor; TCA, tricyclic antidepressants; TUG, Timed Up & Go test. Data are presented as number (%) or mean standard deviation.
Outcomes Primary outcome During the 6-month period after hospital discharge, 85 patients had at least 1 fall at home: 29 (20.6%) in IG and 56 (39.4%) in CG (P < .001). Intention-to-treat analysis showed a significant reduction in the risk of fall in IG with respect to CG (RR ¼ 0.60, 95% CI: 0.44-0.83;
P. Bernocchi et al. / JAMDA xxx (2018) 1e7 Table 2 Nursing/Physiotherapist Interventions Carried out in the Intervention Group During the 6-Month Program Interventions Performed
Mean SD per Patient; Total Number (Percentage)
Scheduled contacts by NT Actions undertaken during scheduled contacts Disease status, symptoms verification and events verification, counseling Therapeutic compliance verifications Therapeutic changes Contacts with specialists Contacts with GP Unscheduled contacts with NT Actions undertaken during unscheduled contacts Disease status, symptoms and events verification, counseling Therapeutic compliance verifications Therapeutic changes Contacts with specialists or GP Suggested sending to the ER Scheduled contacts by PT Home visits by PT Videoconferences by PT
25 11; 3507 3507 (100) 2655 (76) 127 (4) 297 (8) 50 (1.4) 1.7 2.5; 234
150 (64) 28 (12) 9 (4) 39 (17) 12 (5) 16 9; 2179 0.5 1.1; 69 12 9; 739
ER, emergency room; SD, standard deviation.
P < .001). The analysis by protocol confirmed the positive effect of Home-TeleHealth (RR ¼ 0.59; 95% CI: 0.42-0.81; P < .001). Secondary outcomes Figure 2 shows results of the Kaplan-Meier survival analysis of time to event. Mean time to fall was significantly longer in IG than CG: 152 58 versus 134 62 days (P ¼ .001, log-rank test). The number of patients who experienced 2 or more falls was 11 (8%) in IG versus 24 (17%) in CG (P ¼ .020). Table 3 shows the changes after 6 months in all parameters. Functional status improved much more in IG. BBS significantly improved and Timed Up & Go test significantly decreased only in IG. FES significantly increased in CG and was unchanged in IG. Analyzing the percentage of patients by different levels of fear of falling (no fear: FES ¼ 16; low fear: FES 17-19; medium fear: FES 2027; high fear: FES 28-64), patient distribution among the different
Fig. 2. Kaplan-Meier survival analysis of time to first fall. Survival difference between groups was evaluated with the log rank test. The solid line represents the control group and dotted line represents the intervention group.
5
categories was similar at T0 in the 2 groups (P ¼ .130). But whereas in CG the percentage of patients with high fear doubled (P ¼ .006), in IG the percentage of patients who expressed no fear increased, though not significantly (P ¼ .060) with respect to T0. EQ-5D and EuroQol Visual Analog Scale significantly improved only in IG. Analysis of variance for repeated measures (times and groups) confirmed the significant improvement in IG compared to CG for Barthel Index, BBS, Timed Up & Go test, and EuroQol Visual Analog Scale scores. EQ-5D did not significantly differ for time and group but, analyzing each individual component, the mobility index of EQ5D was significantly improved only in IG: the mean (95% CI) delta (T1-T0) was 0.33 (0.44 to 0.22) in IG and 0.06 (1.77 to 0.05) in CG, P ¼ .001. Discussion In this study, we tested the feasibility and efficacy of a telerehabilitation home-based program integrated with medical/ nursing telesurveillance in preventing falls in older chronic disease patients at high risk of falling who were discharged home after a period of in-hospital rehabilitation. The feasibility and safety of the program were demonstrated by the absence of side effects and by the high compliance and patient satisfaction with the program. The efficacy was demonstrated by the significant reduction in risk of falls at 6 months in IG compared to CG and by the fact that the only variable related to the fall event was the treatment group. Moreover, Kaplan-Meier survival curves showed that, while in CG fall events continued over time, in IG there was a significant decline in the trend to fall already evident from month 2. The percentage of patients experiencing 2 or more falls in the study period was significantly lower in IG. Functional status improved in both groups, but more significantly in IG, whereas both risk of falling and balance-related problems improved significantly only in IG. Conversely, fear of falling and the number of patients with high values of FES increased in CG during the 6 months, whereas in IG, the overall value was unchanged but there was an increase in the number of patients with lesser fear of falling, perhaps because of greater patient awareness after the home rehabilitation. Quality of life significantly improved only in IG, in particular, the mobility index. These findings highlight the need for continuous motivational and educational input, provided here as remote reinforcement by the NT and PT through scheduled phone calls and videoconference. Patients need both to be continually encouraged to perform physical exercise in order to maintain an adequate level of independence in activities of daily living and to be sensitized and equipped to recognize early signs/ symptoms of worsening. At the moment of discharge, we advised all patients to continue at home the activity learnt in the rehabilitation hospital, and gave them some educational material on home physical activity. We knew that in real life, however, only a small number of patients would continue performing the physical activity prescribed at discharge; a great number of patients started but then gave up, and the gains achieved during in-hospital rehabilitation were lost after a few weeks. For this reason, we think that it is important to carry out home multidisciplinary programs convincing patients to continue the activity at home. The results of our integrated NT and PT program received a very high response from patients with an overall compliance to the prescribed exercise of 82%. In older adults, often suffering from 1 or more chronic diseases, the use of multiple drugs, lack of exercise, inadequate housing, and inappropriate footwear lead to a high risk of falling, which is often underestimated by the patients themselves as well as by those they live with and the GP. Behavioral modification for a healthier lifestyle is a key ingredient to encourage healthy aging and avoid falls,29 but too
6
P. Bernocchi et al. / JAMDA xxx (2018) 1e7
Table 3 Results on Changes at 6 Months in the Studied Parameters Intervention Group
Barthel ADL IADL BBS TUG FES No fear (FES ¼ 16), n (%) Low fear (FES 17-19), n (%) Medium fear (FES 20-27), n (%) High fear (FES 28-64), n (%) EQ-VAS EQ-5D
Control Group
P (Time/Group)
Pre (n ¼ 141)
Post (n ¼ 122)
P (Pre-Post)
Pre (n ¼ 142)
Post (n ¼ 123)
P (Pre-Post)
69.4 4.5 4.4 32.3 3.1 21.9 35 29 53 24 52.4 0.21
84.6 4.9 4.8 38.5 2.5 22.5 44 15 35 28 63.8 0.42
<.001 .02 .16 <.001 <.001 .46 .004
70.0 4.7 4.6 30.1 3.0 21.0 37 37 51 17 51.5 0.30
76.2 4.5 4.6 32.8 2.8 23.5 29 19 43 32 53.5 0.18
.02 .29 .90 .09 .15 .004 .001
<.001 .5914 .6914 <.001 <.001 .040
.50 .10
<.001 .258
(65.5-73.3) (4.2-4.7) (4.1-4.8) (30.4-34.3) (2.9-3.3) (20.8-23.0) (25) (20) (38) (17) (48.5-56.2) (0.13-0.30)
(81.6-87.6) (4.7-5.2) (4.5-5.2) (36.4-40.7) (2.3-2.7) (21.2-23.9) (36) (12) (29) (23) (59.8-67.8) (0.33-0.50)
<.001 .001
(66.4-73.6) (4.4-5.0) (4.3-5.0) (28.2-32.1) (2.9-3.2) (20.0-22.1) (26) (26) (36) (12) (47-55.3) (0.22-0.38)
(72.3-80.1) (4.2-4.8) (4.2-5.0) (30.3-35.3) (2.6-3.1) (22.2-24.9) (24) (15) (35) (26) (49.2-57.6) (0.07-0.29)
ADL, Activities of Daily Living scale; BS, Berg Balance Scale; EQ-5D, EuroQol-5 Dimension questionnaire; EQ-VAS, EuroQol Visual Analog Scale; FES, Falls Efficacy Scale; IADL, Instrumental Activities of Daily Living scale; TUG, Timed Up & Go test. Data are presented as number (%) or as mean and 95% confidence interval. Analysis of variance with repeated measures was used to analyze differences in the secondary outcomes at 6 months between groups.
often these decisions are made when one or more falls have already occurred. It is important that the risk of falling be perceived as a problem that needs to be faced when the patient is still at home.31 Multifactorial personalized interventions need to be undertaken, as well as prevention and education programs involving all in a proactive way, from the patient to the GP.9,11,32,33 We chose in this study, focused on falls reduction, to combine an individual home exercise program featuring strength, balance, and walking components, adapted from the Otago Exercise Program,20 with our proven model of tele-rehabilitation and home surveillance, already tested and adopted in the management and home rehabilitation of chronic and complex older patients.34 We have shown that a structured physician-directed, nurse, and physiotherapist-managed telephone/videoconference support and telemonitoring program for chronic patients can be better than the standard of care. Disabled older adults, if supported by a structured program, and even with limited prior experience using computers, are not resistant to using technology to access new types of health care service.35,36 We decided to set up this long-term tele-health service, with the physiotherapist and nurse playing the key role and using information and communication technologies as a support to empower the patient, in order to achieve optimal patient adherence both to physical and medical therapy, and to provide the patient with tools to better recognize signs/symptoms of deterioration and learn how to avoid falls. Limitations Notwithstanding its prospective design, this study has several limitations. First, because of the nature of the trial, it was not possible to blind patients and health care personnel to the group allocation. However, outcome assessors and data analysts were blinded. Second, this was a single-center study. Third, fallsdboth prehospitalization and occurring during the 6-month follow-up at homedwere selfreported: falls without injury at home may have been less reported than falls causing injury, although the presence of the caregiver should have minimized this bias in both groups. Conclusions In summary, our tele-rehabilitation program, integrated with medical/nursing tele-surveillance, was feasible, safe, and effective in preventing falls in older chronic disease patients.
Acknowledgments The authors thank Rosemary Allpress for the English revision. A special thanks to Dr. Amerigo Giordano for the scientific support. We also thank the following people: nurses: Giuliano Assoni, Margherita Zanardini, Marta Giunta; physiotherapists: Mara Paneroni, Alessandra Goffi, Fabio Vanoglio, Gian Pietro Bonometti, Francesca Capatori, Palini laura, Alessandra Montini; physicians: Emanuela Zanelli, Michele Vitacca, Alberto Luisa, Bernardo Gialanella; psychologists: Silvana Rocchi, Alessandra Pezzini, Lidia Gazzi; technicians: Roberta Ardesi, Patrizia Martina, Adriana Olivares, Gloria Francolini. References 1. World Health Organization. WHO Global Report on Falls Prevention in Older Age 2007. Available at: www.who.int/violenceinjuryprevention/publications/ otherinjury/fallspreventionpdf?ua¼1. Accessed December 19, 2017. 2. Gillespie LD, Robertson MC, Gillespie WJ, et al. Interventions for preventing falls in older people living in the community. Cochrane Database Syst Rev; 2012:CD007146. 3. Close J, Ellis M, Hooper R. Prevention of Falls in Elderly Trial (PROFET): A randomised controlled trial. Lancet 1999;353:93e97. 4. Rubinstein LZ. Falls in older people: Epidemiology, risk factors and strategies for prevention. Age Aging 2006;35:ii37eii41. 5. Chang JT, Morton SC, Rubenstein LZ, et al. Interventions for the prevention of falls in older adults: Systematic review and meta-analysis of randomised clinical trials. BMJ 2004;328:680. 6. Murray CJ, Vos T, Lozano R, et al. Disability-adjusted life years (DALYs) for 291 diseases and injuries in 21 regions, 1990e2010: A systematic analysis for the Global Burden of Disease Study 2010. Lancet 2012;380:2197e2223. 7. Paliwal Y, Slattum PW, Ratliff SM. Chronic health conditions as a risk factor for falls among the community-dwelling US older adults: A zero-inflated regression modeling approach. Biomed Res Int 2017;2017:5146378. 8. European Innovation Partnership (EIP) on Active and Healthy Aging (AHA). Personalised Health Management and Falls Prevention. State of play of Action Group A2. Available at: https://ec.europa.eu/eip/ageing/library/state-playaction-group-a2-0_en. Accessed December 19, 2017. 9. NICE clinical guideline 161. Assessment and prevention of falls in older people. Available at: https://www.nice.org.uk/guidance/cg161/evidence/falls-fullguidance-190033741; 2013. Accessed December 19, 2017. 10. Matchar DB, Duncan PW, Lien CT, et al. Randomized controlled trial of screening, risk modification, and physical therapy to prevent falls among the elderly recently discharged from the emergency department to the community: The steps to avoid falls in the elderly study. Arch Phys Med Rehabil 2017; 98:1086e1096. 11. Hill AM, Etherton-Beer C, Haines TP. Tailored education for older patients to facilitate engagement in falls prevention strategies after hospital dischargeda pilot randomized controlled trial. PLoS One 2013;23:e63450. 12. Brach JS, Perera S, Gilmore S, et al. Effectiveness of a timing and coordination group exercise program to improve mobility in community-dwelling older adults. A randomized clinical trial. JAMA Intern Med 2017;177:1437e1444. 13. Sherrington C, Michaleff ZA, Fairhall N, et al. Exercise to prevent falls in older adults: An updated systematic review and meta-analysis. Br J Sports Med 2017; 51:1749e1757.
P. Bernocchi et al. / JAMDA xxx (2018) 1e7 14. Elley CR, Robertson MC, Garrett S, et al. Effectiveness of a falls-and-fracture nurse coordinator to reduce falls: A randomized, controlled trial of at risk older adults. J Am Geriatr Soc 2008;56:1383. 15. Kripalani S, Jackson AT, Schnipper JL, Coleman EA. Promoting effective transitions of care at hospital discharge: A review of key issues for hospitalists. J Hosp Med 2007;2:314e323. 16. Hill AM, Hoffmann T, Beer C, et al. Falls after discharge from hospital: Is there a gap between older peoples’ knowledge about falls prevention strategies and the research evidence? Gerontologist 2011;51:653e662. 17. Giordano A, Bonometti GP, Vanoglio F, et al. Feasibility and cost-effectiveness of a multidisciplinary home-telehealth intervention programme to reduce falls among elderly discharged from hospital: Study protocol for a randomized controlled trial. BMC Geriatr 2016;16:20. 18. Mackintosh SF, Hill KD, Dodd KJ, et al. Balance Score and a history of falls in hospital predict recurrent falls in the 6 months following stroke rehabilitation. Arch Phys Med Rehabil 2006;87:1583e1589. 19. Brucki SM, Nitrini R, Caramelli P, et al. Suggestions for utilization of the MiniMental State Examination in Brazil. Arq Neuropsiquiatr 2003;61:777e781. 20. Otago Exercise Programme. Available at: http://www.acc.co.nz/PRD_EXT_ CSMP/groups/external_providers/documents/publications_promotion/prd_ ctrb118334.pdf. Accessed December 20, 2017. 21. Katz TF. A.D.L. Activities of Daily Living. JAMA 1963;185:914. 22. Mahoney FI, Barthel DW. Functional evaluation: The Barthel Index. Md State Med J 1965;14:61e65. 23. Lawton MP, Brody EM. Assessment of older people: Self-maintaining and instrumental activities of daily living. Gerontologist 1969;9:179e186. 24. Podsiadlo D, Richardson S. The Timed “Up & Go”: A test of basic functional mobility for frail elderly persons. J Am Geriatr Soc 1991;39:142e148. 25. Tinetti ME, Mendes de Leon CF, Doucette JT, Baker DI. Fear of falling and fallrelated efficacy in relationship to functioning among community-living elders. J Gerontol 1994;49:M140eM147.
7
26. Elmo A, Ruggiero C, Mariani T, et al. Validazione della FES-I e della FES-I breve in anziani viventi in comunità. J Gerontol Geriatr 2010;58: 259e263. 27. Brooks R, Rabin R, de Charro F, editors. The Measurement and Valuation of Health Status Using EQ-5D: A European Prospective. London: Kluwer Academic; 2003. 28. Balestroni G, Bertolotti G. EuroQol-5D (EQ-5D): An instrument for measuring quality of life. Monaldi Arch Chest Dis 2012;78:155e159. 29. Robertson MC, Campbell AJ, Gardner MM, Devlin N. Preventing injuries in older people by preventing falls: A meta-analysis of individual-level data. J Am Geriatr Soc 2002;50:905e911. 30. Sherrington C, Whitney JC, Lord SR, et al. Effective exercise for the prevention of falls: A systematic review and meta-analysis. J Am Geriatr Soc 2008;56: 2234e2243. 31. Campbell AJ, Robertson MC, Garder MG, et al. Randomized controlled trial of a general practice programme of home based exercise to prevent falls in elderly women. Br Med J 1997;315:1065e1069. 32. Peel NM, McClure RJ, Hendrikz JK. Health-protective behaviours and risk of fallrelated hip fractures: A population-based case-control study. Age Ageing 2006; 35:491e497. 33. Yardley L, Bishop FL, Beyer N, et al. Older people’s views of fallsprevention interventions in six European countries. Gerontologist 2006; 46:650e660. 34. Bernocchi P, Vitacca M, La Rovere MT, et al. Home-based telerehabilitation in older patients with chronic obstructive pulmonary disease and heart failure: A randomised controlled trial. Age Ageing 2018;47:82e88. 35. Marziali E. E-Health program for patients with chronic disease. Telemed eHealth 2009;15:176e182. 36. Bernocchi P, Vanoglio F, Baratti D, et al. Home-based telesurveillance and rehabilitation after stroke: A real-life study. Top Stroke Rehabil 2016;23: 106e115.