Preventing ageing-related loss of autonomy by new technologies: - PowerPoint PPT Presentation

Preventing ageing-related loss of autonomy by new technologies: evidence-based mutidisciplinary assessment Pr. Thierry DANTOINE Research team EA 6310 HAVAE Laboratory University of Limoges, France INRIA Workshop PAL 2012, Nancy November 19-20, 2012

Plan  Introduction o Geriatric population: status and prospects o Loss of autonomy and dependence problems in older people o Consequences of falls in older people o Understanding falls and falls Management in older people having lost autonomy  How to handle with complexity of ageing?: Pluridisciplinary assessment o Medical, psychological and economics o Technological: accuracy at home o Sociological: acceptability  Example of the ESOPPE pilot study o Purpose o Methods o Results o Discussion 2 o What this study adds

Ageing and Dependence • Ageing epidemiology – Industrialized countries are aging (WHO) – In France: > 65 year-old: 21% (2002), 30% (2050) – In Limousin: > 65 year-old: 30% (2002), 40% (2050) • Problems of losing autonomy (France) – 1150 000 dependent (2005), +50% (2040) (Insee, 2009) – Public burden:19 billions € : 1 % GDI (2005) & 1,5 % GDI (2025) (Cour des comptes 2005) 3 – Social security deficit

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Falls epidemiology  Fall at home = Public Health Challenge (Insee, 2009) – As a major loss of autonomy factor – With very High yearly Incidence : 1/3 after 65 yo & ½ after 80 yo ( Tinetti, N Engl J Med 1988; Painter et al, J Allied Health. 2009) – By falls’ injuries: 55000 fractures/y, 9000 death/y, 1 million falls /y (Dress, 2009) – Medical cost: 2 billions € a year (Dress, 2009)  Gerontechnologies ways: – Fall prevention – Early fall detection 6

Consequences of falls in older people  Mortality – Falls and their consequences are a leading cause of death in people 65 years old and older (Davis et al, 1995) – The risk of dying from a fall increases as people age – Fall-related death rates among people 65 years old and older are 10 – 150 times higher than those in younger age groups – Of all deaths due to falls, 66% involve 75 or 65 – 75 year old people (Stevens et al, 2006 ) – Of people admitted to the hospital after a fall at home, only about 50% will be alive one year later 7

Understanding falls and falls Management (questions?)  Causes of falling and fall risk  Clinical assessment and evaluation  Preventive strategies to reduce fall risk  Environmental modifications  Home-based technology and teleassistance 8

Interventio n DSTA (HBTec) Longer Longer Longer Longer ground ground ground ground station station station station Fall at home complications model 9

How to handle with complexity of ageing?: Pluridisciplinary assessment • Assessing new technologies in health and autonomy requires – Physiological relevance to offer the appriopriate technology for the good purpose/need – To demonstrate the preventive benefit on health and autonomy using unbiased criteriae – To pay attention to the users’ opinion and appropriation of these technologies (acceptability) – To measure the economical / financial preventive-effect- related benefit (society benefit by reduction of costs) • 3 Disciplines : – Medical/Medico-économics – Technology – Sociology => TO ENSURE ETHICS

PLURIDISCILINARY ASSESSMENT: A REAL INNOVATION • No study before ESOPPE • Specific approach: To give evidence of Human benefit (better ageing) with lower public costs and economic / industrial development

Why is it possible in Limousin? At home assessment availability • To exhaustively and precisely assess the impacts of tehnologies or oragnizations: Public health Regional agency developped «Loss of Autonomy Preventive Units » who visit seniors at their home to deliver assessments and propose preventive plans • Since 2009:Première in France • Interesting public heath and research tool

Purpose  Evaluate a pack of various technologies or products available to assist with fall prevention and injury reduction efforts  Focus here on specialized equipment that may be commercially acquired 13

Methods  Design : Longitudinal prospective cohort study – Exposed group with technologies – Unexposed group without these technologies  Follow-up: one year  Persons eligible for inclusion: – Individuals registered on autonomy allocation list – Aged 65 years of age or older – Able to provide written consent – Meeting frailty criteria according to Fried frailty criteria – Losing functional autonomy status  Exclusion criteria: Severe stage of dementia 14

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Methods  Main outcome measures – Primary outcome • Cumulative incidence of falls at home in elderly over 12 months, ascertained from monthly diaries of the two groups. – Secondary outcomes • Hospitalization following falls at home requiring • Acceptability Rate Of these free Technologies in the exposed group (The Free AROT)  StatIstics – Multivariate logistic regression model analysis for comparative statistics 16

Materials  Home automation pack – light path – Smoke and Gas detector  T eleassistance devices – Electronic bracelet or pendentive – Bathroom alarm zipper  T eleassistance platform – Functional at all times. – All electronic devices are connected 17

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Results: Descriptive Analysis Criteriae Equipped Non equipped P-value n= 94 (%) n= 96 (%) Mean Age (SD) years 84,9±6,5 82,0±5,7 0,0013* Women 72 (76,6) 75 (78,1) 0,8011 Home 0,0719 Individual 67 (71,3) 79 (82,3) Collectivity 27 (28,7) 17 (17,7) Living Location 0,9828 Rural 40 (42,6) 41 (42,7) Urban 54 (57,5) 55 (57,3) Dependence level 0,2913 GIR3 9 (9,6) 12 (12,5) GIR4 22 (23,4) 15 (15,6) GIR5 18 (19,2) 13 (13,5) GIR6 45 (47,9) 56 (58,3) 19

Results : Descriptive Analysis Criteriae Equipped Non equipped P-value n= 94 (%) n= 96 (%) Couple 17 (18,1) 32 (33,3) 0,0526 House Help 86 (91,5) 78 (81,3) 0,0400 57 (60,6) 56 (58,3) Low study level 0,0719 Polymedication 85 (88,5) 78 (81,3) 0,0001 Polypathology 7 (7,5) 19 (19,8) 0,0133 Cognitive Impairment 34 (36,2) 33 (34,4) 0,7957 Malnutrition 40 (42,6) 28 (29,2) 0,0543 Depression 68 (72,3) 62 (64,6) 0,2501 Hypertension 61 (64,9) 57 (59,4) 0,4331 20

Results : Univariate Analysis Variables RC IC à 95% P-value Domotics exposure 0,45 [0,25 - 0,81] 0,0076 Age by year 1,07 [1,02 - 1,12] 0,0105 Single Habitation 2,14 [1,02 - 4,48] 0,0437 Polymedication 0,57 [0,29 – 1,14] 0,0999 Polypathology 1,87 [0,81 - 4,30] 0,1406 Cognitive impairments 1,59 [0,87 - 2,90] 0,1329 Hypertension 0,71 [0,39 - 1,27] 0,2452 Dependance level 0,1140 GIR 6 (reference = GIR 3) 0,42 [0,16 - 1,08] 21

Results  Exposed group (with technology) n= 96  Unexposed group (without technology) n= 98  Acceptance Rate of the free Technologies (AROT) The Free AROT= 97.3%  Falls incidence 50% CI 95% [30-70]= High risk of falls AT HOME Percentage 60 50 40 30 Exposed group Unexposed group 20 10 0 22 Elderly falling at home Elderly hospitalized for falling at home

primary endpoint technologies effect on incidence of elderly falls at home NNT= NNT= 5 5 OR= 0. 33 95%IC [0.17 – 0.65] P= 0.0012 OR= 0. 33 95%IC [0.17 – 0.65] P= 0.0012 Characteristics Odds ratio 95% IC P-value Home automation pack 0.33 [0.17 – 0.65] 0.0012 Aging by ten years 2.82 [1.57 – 5.01] 0.0005 Type of housing 0.0329 Residence for senior (collective) 1.00 - Individual (private) 2.14 [1.02– 4.48] 23

Secondary endpoint technologies effect on INCIDENCE OF ELDERLY FALLS AT HOME WITH injuries and HOSPITALIZATION NNT= NNT= OR= 0. 33 95%IC [0.17 – 0.65] P= 0.0091 OR= 0. 33 95%IC [0.17 – 0.65] P= 0.0091 6 6 Characteristics Odds ratio 95% IC P-value Home automation pack 0.33 [0.17 – 0.65] 0.0091 Aging by ten years 2.37 [1.15 – 4.86] 0.0190 Type of housing 0.0371 Residence for senior (collective) 1.00 - Individual (private) 3.61 [1.08– 12.06] 2.78 [1.02– 7.55] At least 3 Comorbidities 0.0456 Residence 0.0511 Rural 1.00 - Urban 2.42 [1.00– 5.86] 24

Discussion  Weaknesses – Non randomised study – Main endpoint was declarative  Strengths – Population based study – Longitudinal study – Population with high risk of falls at home – Multidisciplinary assessment – News perspectives 25

What this study adds  Simple home automation pack coupled with tele- assistance service significantly reduced the home falls in a frail elderly population  Gerontechnology contributed to prevent and manage falls in elderly population.  Confirmation of these results is sought in a larger randomized trial (DOMOLIM Study with 1200 PARTICIPANTS) 26

DOMOLIM Clinical Trial N=1200 NCT 01697553 Model of Assessment of HBTec Elderly Falls and Loss Autonomy Research Program (EFAR-HBTec)

THANKS 28