An Italian Business Case for an eHealth Platform to Provide Remote

Monitoring and Coaching Services for Elderly with Mild Cognitive

Impairment and Mild Dementia

Monika Jurkeviciute

, Lex van Velsen

, Pietro Davide Trimarchi

, Ladan Sarvari

and Fabrizio Giunco

Centre for Healthcare Improvement, Chalmers University of Technology, Vera Sandbergs allé 8, Gothenburg, Sweden

Telemedicine cluster, Roessingh Research and Development, Roessinghsbleekweg 33b, Enschede, The Netherlands

IRCCS Fondazione Don Carlo Gnocchi, Via Don Luigi Palazzolo 21, Milan, Italy

Jonköping International Business School, Jönköping University, Gjuterigatan 5, Jönköping, Sweden

fgiunco@dongnocchi.it

Keywords: Business Case, eHealth Platform, Mild Cognitive Impairment, Mild Dementia, Elderly.

Abstract: The purpose of this study was to define a business case for an eHealth platform to provide remote monitoring

and coaching services for elderly with mild cognitive impairment and mild dementia in the Italian context.

107 patients with mild cognitive impairment and mild dementia were divided into the intervention and control

groups. The data was collected using standardized instruments Clinical Dementia Rating Scale (CDR) and

EuroQoL-5D-5L, and tailor-made instruments, such as surveys to technology and healthcare providers, and

semi-structured interviews to patients and healthcare professionals. The data that was not collected in the

study, was obtained from the scientific literature. Benefit/cost ratio was calculated for three years. The study

shows that a digital platform to provide remote monitoring and coaching services for elderly with mild

cognitive impairment and mild dementia can be cost-effective from the first year, and can improve care

without monetary loss for the healthcare provider. The key benefits show that the deterioration of the illness

is postponed, and that the satisfaction of the patients and the healthcare professionals increases. Therefore,

such an eHealth platform can be a worthy investment in Italy, and could be considered for wider nation-wide

adoption.

1 INTRODUCTION

The number of people living with dementia increases.

It is currently estimated to affect more than 40 million

people globally, whose care generates more than 800

billion USD in cost (Prince et al., 2015). This growth

will continue to strain healthcare systems worldwide.

One solution to cope with this situation could be to

widely use digital technologies (hereafter – eHealth)

that aim to improve outcomes (both clinical and

quality of life) and to save costs. While there is a

growing body of literature that examines effects of

eHealth to elderly patients with various levels of

severity of cognitive impairment, adoption of eHealth

into routine care is lagging (Swinkels et al., 2018).

One barrier concern limited resources in healthcare.

eHealth initiatives compete against one another and

other options for investment, while the return-on-

investment for this type of eHealth service remains

unclear. Before allocating funds, decision-makers

will create a thorough overview of which investments

can maximize impact on health and efficiency. If the

business case for eHealth in this context remains

vague, its adoption will falter.

Different reviews (Goldzweig et al., 2009; Kim et

al., 2017) reported a lack of published evaluations of

costs and benefits of eHealth implementations. A

similar gap of missing cost-benefit evaluations has

been noted for technology implementations in the

area of dementia (Westphal et al., 2010). Still in 2016,

it was reported that majority of the evaluations of

technology for people with dementia focus on usage,

usability, and adoption (Knapp et al., 2016). The

paucity of economic data is one of the biggest barriers

to the creation of business cases that are essential for

eHealth adoption.

Jurkeviciute, M., van Velsen, L., Trimarchi, P., Sarvari, L. and Giunco, F.

An Italian Business Case for an eHealth Platform to Provide Remote Monitoring and Coaching Services for Elderly with Mild Cognitive Impairment and Mild Dementia.

DOI: 10.5220/0007657700280037

In Proceedings of the 5th International Conference on Information and Communication Technologies for Ageing Well and e-Health (ICT4AWE 2019), pages 28-37

ISBN: 978-989-758-368-1

A business case, as defined by Gambles (2017, p.

1), is “A recommendation to decision makers to take

a particular course of action for the organization,

supported by an analysis of its benefits, costs and

risks compared to the realistic alternatives, with an

explanation of how it can best be implemented”. In

this paper, we describe a business case for investment

in an eHealth platform to provide remote monitoring

and coaching services for elderly with mild cognitive

impairment (MCI) and mild dementia (MD). We

examine whether it could improve quality of care by

enhancing care outcomes and saving costs in Italy.

Hereby, we aim to add knowledge to the scarce body

of literature on which eHealth interventions have a

positive business case.

2 RELATED WORK

Cost-effectiveness or business case development

studies of non-pharmacological eHealth interventions

for treating MCI and MD are scarce. Most eHealth

studies have focused on clinical and social outcomes

(e.g. Van Mierlo et al., 2015; Ben-Sadoun et al.,

2016) and have shown positive outcomes to

caregivers, such as relatives, healthcare professionals,

or a healthcare organization. Less evidence is

available on clinical effectiveness of eHealth for the

elderly patients themselves, with various levels of

severity of cognitive impairment (Knapp et al., 2016).

Similarly, there are cost-effectiveness studies that

focus on non-pharmacological interventions without

involvement of eHealth (e.g. Gitlin et al., 2010; Willis

et al., 2018). The following paragraphs will

summarize the cost-effectiveness outcomes of non-

pharmacological eHealth interventions, obtained

from a small number of published studies.

The ISISEMD (Intelligent System for

Independent living and Self-care of seniors with

cognitive problems or Mild Dementia) project

introduced assistive technology for elderly people

with mild dementia living in the community. The

business case concluded that the system can only be

sustainable if provided at a large scale, at the level of

municipality or region (Mitseva et al., 2009).

On a general level, an economic modelling study

for dementia conducted by Knapp et al. (2016)

modelled three scenarios. The first scenario

considered postponement of care home admission. It

assumed that assistive and safety technologies can

delay care home admissions by 8 months (based on

Riikonen et al., 2010). Under this scenario, the

technology intervention would be cost-effective if it

postponed care home admissions by 8 months, and

reduced hours spent on care by the informal caregiver

by 20%. The second scenario considered reduction of

career’s stress. Impact in quality-adjusted life years

(QALY) was examined. It was assumed that

technology could reduce career’s stress and improve

career’s quality of life by 0,05 EQ-5D tariff that lasts

for 3 years (time of patient’s living in a community).

The technology intervention would be cost-effective

if it cost less than 13.000 British pounds, delayed care

home admissions by 8 months, reduced career’s

weekly hours by 15%, and increased career’s quality

of life by 0,05 QALY per year. The third scenario

aimed to find out how much benefit that is relative to

costs, the technology needs to generate in order to be

deemed cost-effective (from societal and health

perspectives). It was considered that the technology

costs 5000 British pounds over 4.5 years (time of

patient’s living in a community). Under this scenario,

the technology intervention would be cost-effective if

it postponed care home admission by 3 months and

reduced career’s weekly hours by 8%, and increased

career’s quality of life by 0,06-0,08 QALYs per year.

As it can be seen from the overview of the related

work, the cost-effectiveness studies on eHealth

intervention in dementia care are fragmented and

have not reached saturation of knowledge. It is

challenging to draw conclusions from the published

studies not only because the types of eHealth

analyzed are different and applied in different

contexts, but also the pace of technology

development is fast and monetary values (e.g. prices,

hourly tariffs) fluctuate over time. This leads to a

need for more cost-effectiveness studies related to

eHealth interventions in dementia care.

3 MATERIAL AND METHODS

3.1 Empirical Study

The business case was developed within a 3-year

project “Digital Environment for Cognitive

Inclusion” (DECI) funded by the European Union

(EU). The study was carried out in four countries, and

the study design was comparative, randomized,

stratified and prospective. The case analyzed in this

paper focuses on a business model to provide in-

house remote assistance services in the Italian

context, promoting independent living for elderly

people diagnosed with mild cognitive impairment and

mild dementia. The population was divided into an

intervention group and a control group. In Italy, 53

persons were randomized into the intervention group

(10 dropped-out), and 54 persons in the control group

An Italian Business Case for an eHealth Platform to Provide Remote Monitoring and Coaching Services for Elderly with Mild Cognitive

Impairment and Mild Dementia

that followed care as usual (5 dropped-out). The

intervention lasted for 6 months. Measurements took

place at a baseline and after 6 months.

The Intervention group received a technology-

supported DECI care model, consisting of:

1. An integrated platform, installed on a tablet

that enables professionals to share information

about the patients, as well as patient-to-

professional communication.

2. Web-based physical and cognitive exercise

applications (an OTAGO-based falls

prevention program by Roessingh Research

and Development (The Netherlands) and

SmartBrain (Spain).

3. An activity monitoring system, supported by a

wearable device that records the number of

steps and the duration of active hours

throughout the day (Adamo watch by Consoft

Sistemi s. p. a.).

4. A case manager, in Italian case a social worker,

responsible for coordinating the care,

introducing and supporting a patient in using

the technology.

Figure 1: The DECI services.

The inclusion criteria for patients:

1. Age ≥ 60

2. Diagnosis of MCI or diagnosis of

Dementia according to DSM V criteria

3. Clinical Dementia Rating (CDR) ≤ 1

4. Living at home

5. Ability to provide informed consent or

availability of a proxy for informed

consent

3.2 Business Case Creation

The approach towards creating the business case was

based upon the TNO Business case model for

innovation in long-term care, created by an

organization TNO that aims to assess an innovation

and to demonstrate its value to government and

industry. The approach allows a multi-dimensional

assessment of changes in variables before and after

introduction of the innovation, and is intended to

inform decision makers of the added value of the

innovation.

The business case development starts with the

description of the innovation (also called as

boundaries of the innovation in the TNO approach).

Then, risks are discussed. Afterwards, it is necessary

to determine which of the variables are relevant to the

investigation and how to obtain the data. Variables

proposed by TNO to assess the before and after

situations include:

 The cost of spent time by healthcare

professionals.

 Consequences of using the innovation on the

quality of care (e.g., patient satisfaction,

quality of life, safety).

 The impact of the innovation on prevention or

postponement of the health issue.

 Income generated by providing the service

based on the innovation.

 Investment for starting the innovation.

 Operating expenses for using the innovation,

after initial investment.

 Changes in quality of work by healthcare

professionals (e.g., job satisfaction)

In this study, we approached the business case from

the perspective of the healthcare organization (in this

case, a Memory clinic).

3.3 Data Collection and Analysis

Spent time (operationalized as the cost of time spent

by healthcare professionals for direct treatment) was

collected via a survey to the healthcare provider. A

total number was calculated by multiplying the

number of spent hours by the applicable hourly tariff.

Quality of care consisted of the time spent on

multi-disciplinary meetings for defining and refining

treatment plans, patient satisfaction, safety, and

quality of life. Data for time spent on multi-

disciplinary meetings for defining and refining

treatment plans was collected via a survey to the

healthcare provider. A total number was created by

multiplying the number of spent hours by hourly

tariffs. Multi-disciplinary team meetings and

refinement of care plans were not applicable to a

control group. Patient satisfaction was assessed via

semi-structured interviews with patients (purposeful

sample of n=10 for the intervention group and n=10

for the control group). Data was thematically

analyzed. Data regarding willingness to use the DECI

services in the future was collected through a

willingness-to-pay survey to the patients and their

informal caregivers. Third, quality of life of the

ICT4AWE 2019 - 5th International Conference on Information and Communication Technologies for Ageing Well and e-Health

patients was assessed using a questionnaire

EuroQoL-5D-5L (EuroQoL Group, 1990; Wolfs et

al., 2007; Janssen et al., 2013). Data was analyzed

using SPSS software, Chi-square and one-way Anova

statistical tests. The confidence level was set at 0.05.

Safety data was collected using qualitative semi-

structured interviews with the patients of the

intervention group (n=10) supplemented by semi-

structured interviews with healthcare professionals

(n=4). Since safety aspects concerned the DECI

solution, this element was not applicable to a control

group. Data was thematically analyzed.

Prevent and postpone care consists of prevention

of falls due to the DECI services and postponement

of mild dementia. Since the falls data were not

collected in the project, assumptions were extracted

from relevant literature. People above 65 years fall,

on average, 0.33 times per year (Gillespie et al.,

2012). 9% of the falls require a GP visit, and 5% of

the falls lead to an emergency visit (Berg et al., 1997).

3% of the falls end in a fracture (assumed by the

project team). Completion of the OTAGO program

leads to prevention of 68% of falls (Thomas et al.,

2010). During analysis, a number of falls prevented is

calculated (% of falls prevented (68%) multiplied by

a targeted population size). Then, the total saved cost

due to prevented falls is calculated by summing up:

a) prevented GP consults (a number of falls prevented

multiplied by 9% and by the cost of a single GP

consult; b) prevented emergency room visits (a

number of falls prevented multiplied by 5% and by

the cost of a single emergency room visit; c)

prevented fractures (a number of falls prevented

multiplied by 3% and by the cost of a fracture

treatment. Data for the cost of a GP consult (15

euros), an emergency room visit (241 euros), and a

fracture treatment (2949 euros) were obtained

through a survey to the healthcare provider.

Data for postponement of mild dementia was

collected using Clinical Dementia Rating Scale

(CDR) (Morris et al., 1997) on patients at the baseline

and follow-up. Annual costs of treating MD were

obtained through a survey to the healthcare provider

and equals to 18.941 euros. During analysis, a

proportion of people who converted from MCI to MD

was calculated using changes in CDR from baseline

to follow-up. The conversion rate was assumed to

stay stable after 12 months. The saved costs due to the

postponement of MD were calculated by multiplying

the following elements: conversion rate from MCI to

MD, annual target population, and annual MD

treatment costs.

Income of a healthcare provider consists of annual

insurance reimbursement for healthcare services

provided. Data was obtained through a survey to the

healthcare provider. Hypothetical income related to

willingness to pay by a patient or an informal

caregiver was collected through a survey to the

patients and their informal caregivers. Data was

analyzed by calculating the average amounts that

would be paid by the patient or the informal

caregiver.

Investment relates to the cost of personnel for

server installation and configuration related to the

DECI services. Data was obtained through a survey

to the healthcare provider.

Operating expenses refer to the annual operating

expenses for the technology in the DECI services, to

be incurred by the healthcare provider (usage fees,

hardware, servers, maintenance, helpdesk, etc.). Data

was obtained through a survey to the technology

providers and the healthcare provider. Usage fees for

all the technologies are constant, except for the

smartwatch fee, which increases with the size of

patient population.

Quality of work refers to the satisfaction of

healthcare professionals using the innovation. Data

was obtained through semi-structured interviews with

the healthcare professionals (n=4). Same

professionals were involved in the care of the

intervention and control groups. Data was

thematically analyzed.

All benefits and costs that were possible to

convert into monetary magnitudes were entered into

the model which was set up in the MS Excel. Then,

the ratio between the monetary benefits and costs of

implementing DECI services were calculated for

situations after year 1, year 2, and year 3.

Ratio = Benefits / Costs

(1)

Consideration of all outcome categories determine

whether or not implementing the DECI service is a

worthy investment. The business case for the usual

care in the control group equals to zero, since several

categories of evaluation that result in monetary values

are not applicable, while other categories of costs and

benefits compensate each other. First, the usual care

does not involve technology innovation, which makes

the categories of investment and operating expenses

not applicable. Second, prevention of MD, GP

consults, falls, emergency room visits, and fractures

concern the innovation introduced, and are not

applicable to the control group. The only applicable

methodological categories that result in monetary

values are spent time and income. However, the cost

of time spent by the professionals are reimbursed

(income). Therefore, the business case for the usual

An Italian Business Case for an eHealth Platform to Provide Remote Monitoring and Coaching Services for Elderly with Mild Cognitive

Impairment and Mild Dementia

care in the control group equals to zero. However,

non-monetary qualitative results for the control group

are discussed, where applicable.

4 RESULTS OF A BUSINESS

CASE IN ITALY

In Italy, healthcare services are free-of-charge and

funded from tax payments. DECI services were an

extension of service offered by Centers for Cognitive

Disorders and Dementia in the region of Lombardy

(Milan) which have a primary responsibility to

diagnose and assess the stage of illness and to

determine the therapy. Every patient that met the

inclusion criteria visited the healthcare professionals

two times at the Memory Clinic of Istituto Palazzolo,

Fondazione Don Carlo Gnocchi Onlus (FDG) in

Milan: for inclusion and follow-up. Five

professionals were involved in the DECI services: a

geriatrician, two neuropsychologists, a social worker

(also acting as a case manager), and an engineer. The

case manager was engaged full-time in the study and

had a role to coordinate patient’s care with other

professionals, to answer the incoming messages

through the DECI platform, to check patient’s

adherence to prescribed physical and cognitive

therapies, to send reminders, to monitor the status of

the battery of the smartwatch, and to organize its

replacement. The geriatrician worked with tailoring

the physical activity program to fit the specific needs

of the patients. The neuropsychologists designed

therapies delivered via the cognitive stimulation

program.

It is important to note that we evaluate the

intervention as a whole, i.e. organizational and

therapeutic inputs, and not just technology.

Therefore, the outcomes reported cannot be attributed

to the technology only.

Table 1 shows the demographics of the patients

included in the study.

Projected Population Size

Based on the estimation of the project team, the

population size in Italy can be targeted at 100 patients

for year 1, 150 patients for year 2, and 175 patients

for year 3.

Table 1: Patient characteristics at baseline.

Intervention group

N=53

Age

77.64±5.27

Gender (F/M)

27/26

Diagnosis (MCI/MD)

39/14

MCI type (Amn/N-Amn)

19/20

Education years

9.21±4.27

MMSE (range 0-30)*

26.56±2.87

CDT (range 0-5)*

3.30±1.38

ADL *

5.64±0.92

I-ADL*

6.13±2.19

Control group

N=54

Age

78.98±5.98

Gender (F/M)

31/23

Diagnosis (MCI/MD)

36/18

MCI type (Amn/N-Amn)

16/20

Education years

9.02±4.15

MMSE (range 0-30)

26.18±2.96

CDT (range 0-5)

3.13±1.33

ADL

5.59±0.81

I-ADL

6.09±2.09

*CDT = Clock drawing test (Shulman, 2000)

MMSE (Mini-Mental State Examination) (Folstein et al.,

1975)

ADL (Activities of Daily Living) (Katz et al., 1970)

I-ADL (Instrumental Activities of Daily Living)

(Lawton et al., 1969)

4.1 Benefits

Prevent and Postpone Care

16% of the control sample and 6% of the intervention

sample converted to MD at a follow-up after 6

months. The rate of conversion is quite high since the

samples are small and the mean age of the patients in

the study was high, which affected the rate of

conversion (Visser et al., 2006). Hence, the data

shows that 10% fewer MCI patients converted to MD

in the intervention group, compared to the control

group. The costs that are prevented using the DECI

services relate to 10% additional prevention from

turning from MCI to MD. Hence, the preventable

costs equal to 196.337,16 euros in year 1. Every

consecutive year, the prevented costs rise due to a

rising number of patients who would use the DECI

services. The prevented cost in year 2 equals to

294.505,74 euros and 343.590,03 euros in year 3.

Income

Italian healthcare system does not reimburse the costs

incurred by using eHealth. Therefore, insurance

reimbursement would not differ between the DECI

services and usual care. In this study, income in the

ICT4AWE 2019 - 5th International Conference on Information and Communication Technologies for Ageing Well and e-Health

intervention group will be interpreted as the insurance

reimbursement for the time spent by the healthcare

professionals providing usual care, and equals to

26.458 euros in year 1, 39.687 euros in year 2, and

46.301,50 euros in year 3.

Willingness-to-pay analysis showed that 60% of

the patients in the intervention group were willing to

pay, on average, 47 euros monthly for the DECI

services. It comprises, on average, 28,20 euros per

patient. 70% of their informal caregivers were willing

to pay, on average, 33 euros monthly. It comprises,

on average, 23,10 euros per informal caregiver.

However, the income that would come from the

patients or informal caregivers is not included in the

business case analysis in this study, since healthcare

is supposed to be free-of-charge in Italy.

Patient Satisfaction

All the control group patients expressed trust in

competence of the professionals and appreciated kind

approach that made them feel good. However, one

patient disliked to be charged for the visits, two

patients thought that the waiting time between a

contact and a visit was too long, and one patient found

the process too bureaucratic.

Patients in the intervention group perceived that

the key strengths of the DECI services were the

simplicity of its features and the stimulating physical

and cognitive exercises that helped them keep active.

The main challenges concerned starting using the

DECI technology and to learn navigating it.

Therefore, an IT helpdesk was identified as a

necessary addition to the service, that could reduce

the need for clinical staff and family members to

provide extra time for helping the patients learn the

IT system (a helpdesk is estimated to cost 10.800

euros for a population of 100 patients in year 1). Also,

the difficulty level of the physical and cognitive

exercises needs to be customized, based on the state

of the condition of the patient. The exercises were

often perceived as too easy. Since the cognitive and

physical training systems contain various levels of

difficulty, it was deemed to be a learning point for

clinical staff to select the right level for the patient.

Design and size of the activity monitoring device (a

wrist watch) needs to be improved to better suit the

routines and aesthetic preferences of the elderly

population (the watch was deemed to make people

feel they look sick, and the design was too youthful).

A willingness-to-pay survey showed that 83% of

the patients and 86% of the informal caregivers are

willing to use the DECI services in the future. Also,

90% of the patients and 89% of their informal

caregivers would recommend DECI to others.

Quality of Life

Analysis of proportions in each dimension, inside of

each group, to locate changes between the baseline

and the follow-up, did not yield statistically

significant results. In the intervention group: mobility

𝜒

(1)=0,051, p=0.822; self-care 𝜒

(1)=0,212,

p=0,645; usual activity 𝜒

(1)=0,080, p=0,777;

pain/discomfort 𝜒

(1)=0,720, p=0,396; anxiety

𝜒

(1)=0, p=1. In the control group: mobility

𝜒

(1)=0,809, p=0.368; self-care 𝜒

(1)=1,359,

p=0,244; usual activity 𝜒

(1)=0,970, p=0,325;

pain/discomfort 𝜒

(1)=2,256, p=0,133; anxiety

𝜒

(1)=1,142, p=0,285.

Analysis of changes in the EQ visual analogue

scale (VAS) between the baseline and follow-up did

not yield statistically significant results too:

intervention group p=0,450; control group p=0,910.

In-between groups analysis using one-way Anova to

locate a difference between the control and the

intervention groups did not yield statistically

significantly results, p=0,558.

Analysis of EQ index values used a Spanish value

set. Analysis of changes in the index values between

the baseline and the follow-up in each group did not

yield statistically significant results: intervention

group p=0,458; control group p=0,075. In-between

groups analysis of the index values using one-way

Anova to locate a difference between the control and

intervention groups did not yield statistically

significantly results, p=0,219. Intervention group,

mean QALY=-0,0139± 0,0903; control group, mean

QALY=-0,0448636±0,1404.

Quality of Work

In Italy, both groups were attended by the same

healthcare professionals involved in the study. All the

professionals indicated that introducing the case

manager role was highly beneficial, since it is a

dedicated contact person guiding the patients and

answering their questions. The role was deemed

useful for strengthening relationships between the

patients, informal caregivers, and healthcare

professionals. Professionals also appreciated the

infrastructure and technological features of DECI,

especially the ability to monitor the exercise and

performance of the patients remotely.

The DECI study demanded healthcare

professionals to spend, on average, 29,3 hours per

week. All the professionals reported an increased

workload, but it was deemed to be related to the

administration of the study. However, the quality of

work was perceived to have increased due to the

higher empowerment of the professionals by being

able to provide patients with useful tools. Healthcare

An Italian Business Case for an eHealth Platform to Provide Remote Monitoring and Coaching Services for Elderly with Mild Cognitive

Impairment and Mild Dementia

professionals also reported to have increased their

knowledge about cognitive impairment and patients’

statuses and needs. Moreover, the DECI services

made it easier to work cross-functionally through

facilitated data sharing in the DECI platform.

4.2 Costs

Spent Time and Quality of Care in Italy concerned the

following professional categories engaging with the

DECI services and multi-disciplinary meetings

(please note that this time does not overlap): doctor,

nurse practitioner, physiotherapist, technician, case

manager, psychologist. In total, the cost of time spent

by the professionals for the intervention group is

projected to 66.325,27 euros in year 1, 99.487,90

euros in year 2, and 116.069,22 euros in year 3. The

cost of time spent by professionals for the control

group is projected to 26.458 euros in year 1, 39.687

euros in year 2, and 46.301,50 euros in year 3.

Average costs per patient remain stable.

Investment (one-time) for the DECI services is

relatively small on the side of the hospital. The

investment includes the cost of staff of 140 euros for

establishing the ICT infrastructure.

Operating Expenses consist of the annual usage fees

for the DECI technology and the operating costs for

hosting the technology in the hospital.

The annual usage fee for all DECI technologies is

52.100 euros (including tax). The highest fee is paid

to the smartwatch provider due to the lease of

hardware. The usage fee for year 2 equals to 70.400

euros, and 79.550 euros for year 3.

The annual operating costs for all DECI

technologies equal to the total of 74.646 euros in year

1 and consists of the cost related to purchasing the

hardware (depreciation in 12 months), server hosting,

configuration of the tablets, personnel cost for

maintenance and helpdesk, licenses, 4G connectivity.

The annual operating costs for year 2 equals to

101.496 euros, and 114.921 euros for year 3.

Total annual operating expenses of the DECI

technology equal to 126.746 euros for year 1, then

171.896 euros for year 2, and 194.471 euros for year

4.3 Safety

The majority of the interviewed patients and

healthcare professionals did not express any concerns

or observations the DECI services might be not safe.

However, two safety-related risks were reported.

First, the physical activity program OTAGO might

require supervision for an older population. One

healthcare professional expressed concerns that some

exercises put too high pressure on these patients. One

patient has also mentioned that some interaction with

a professional during the exercise session would have

been helpful, in order to make sure the exercises are

performed in a safe way. Second, one patient reported

that Adamo activity monitoring sensor caused an

allergic reaction to nickel and plastic.

4.4 Benefit/Cost Ratio

Table 2: Summary of the DECI scenario in monetary terms

(euros).

Total benefits

Total costs

Benefit/Cost

ratio

Year 1

222.795,16

193.211,27

1,15

Year 2

334.192,74

271.383,9

1,23

Year 3

389.891,53

310.540,22

1,25

As it can be seen from the Table 2, the business case

of the DECI services in Italy is positive from the first

year. Benefits in year 1 comprise 222.795,16 euros

and consist of preventable care costs 196.337,16

euros, and insurance reimbursement for the usual care

(income) 26.458 euros. Other categories of the

benefits were non-monetary, and therefore they were

not included in the calculation of the benefits.

Benefits for the year 2 and year 3 were calculated in

the same way.

The costs in year 1 comprise 193.211,27 euros and

consist of the cost of time spent by the professionals

66.325,27 euros, a one-time investment 140 euros,

and annual operating expenses 126.746 euros. Costs

for the year 2 and year 3 were calculated in the same

way, except the investment cost of 140 euros was not

included in the subsequent years, since it was a one-

time expense.

The benefit/cost ratio was calculated by dividing

the total cash benefits of the DECI services by the

total cash costs of the DECI services.

5 DISCUSSION

Future predictions of an increase in dementia patients

makes it important to assess new non-

pharmacological forms of care. In this study, we

assessed a business case of an eHealth platform to

provide remote monitoring and coaching services for

elderly with mild cognitive impairment and mild

dementia (DECI). We compared two different

ICT4AWE 2019 - 5th International Conference on Information and Communication Technologies for Ageing Well and e-Health

scenarios, DECI and the usual care. The comparison

showed that the DECI services can be cost-effective

from the first year, and it is a more beneficial

alternative to usual care for elderly with mild

cognitive impairment and mild dementia. In the DECI

scenario, the cost increases compared to the usual

care due to a different care model that includes multi-

disciplinary work, usage of technology, and

coordination activities performed by the case

manager. However, the cost is partially reimbursed by

insurers and outweighed by both monetary and non-

monetary benefits.

From the patients’ point of view, DECI helped to

postpone a need for institutional care by reducing the

rate of conversion from MCI to MD. Such

postponement brings positive economic impact. The

study adds knowledge on how such non-

pharmacological intervention reduces the long-term

costs of care (Lin and Neumann, 2013). The findings

of this study were produced on a relatively small

sample of patients. In the future, the effects of similar

interventions to the costs for dementia management

could be investigated on a larger scale. However,

there was not enough evidence to suggest that there

were statistically significant changes in quality of life

of the patients. This result could be influenced by a

sample size, or a rather short duration of the

intervention that lasted for 6 months. In the future, it

might be worthwhile to explore other aspects of

quality of life than the ones covered by the instrument

EuroQoL-5D-5L.

Healthcare professionals felt more empowered by

a possibility to provide useful ICT tools of the DECI

services to patients so that they feel more in control

over their condition. Moreover, the DECI service has

the ability to save time for home visits by monitoring

patient’s performance remotely. The case manager

role, as part of DECI scenario, was perceived as a

must-have in the care process, as it helps to build

relationships with patients and facilitates

coordination of care.

Hence, it can be concluded that such an eHealth

platform, providing remote monitoring and coaching

services, is a worthwhile investment in the Italian

context, as care can be improved at no monetary loss

for the healthcare provider. Furthermore, Italian

authorities could consider assessing the possibility of

a region-wide implementation of the DECI solution.

When comparing this study with other published

cost-effectiveness studies on eHealth for elderly with

mild cognitive impairment and mild dementia, it is

challenging to draw conclusions. This is because the

types of eHealth analyzed are different and applied in

different contexts. Also, the pace of technology

development is fast and monetary values (e.g. prices,

hourly tariffs) are not stable over time. For example,

the ISISEMD project (Mitseva et al., 2009)

implementing assistive eHealth technologies

concluded that cost-effectiveness can only be reached

if it is provided at a large scale. The DECI services,

applying a different technology, can be cost-effective

on a scale of one organization and from year 1 itself.

Our study added knowledge about cost-effective

eHealth solutions that provide added value to elderly

with mild cognitive impairment and mild dementia.

5.1 Future Plans in the Italian Site

From 2019, a new model of Lombardy region health

system is going to be introduced. It will allow

reimbursement and delivery of home healthcare

services for elderly chronic patients suffering from

cognitive decline. This will enable to deliver services

also through ICT technologies (although the

hardware and software technology will not be

reimbursed). Based on this model, reimbursement for

the delivery of home care services with ICT tools will

exceed the usual care reimbursement. Such

developments at regional level will create an

opportunity to implement the DECI concept in the

usual care system.

Being part of the DECI research, the Memory

Clinic of Istituto Palazzolo, Fondazione Don Carlo

Gnocchi Onlus (FDG) has appreciated the DECI

concept and considers it beneficial compared to the

usual care. The site aims to ensure that chronic elderly

patients are followed in their clinical path, and more

patients in need of assistance can be reached.

Therefore, FDG has decided to adopt the DECI

approach. However, even though the business case

was positive, the site aims to reduce the cost of

technology even more. At first, the site will re-use the

hardware (tablets) that have already been used during

the DECI study. Since ICT will not be reimbursed and

will have to be covered at own expense by the site,

the strategy is to consider other similar and cheaper

software technologies that are already tested by the

site in other research projects. To manage the costs,

the site will create a strategy to balance the number of

patients in need of the service and the duration of the

service using technology. This way, the site expects

to maximize the reach and benefits for the patients in

need.

The principal risk for this future scenario is the

under- or no-use of the technologies from care staff

and patients, when they are implemented. This risk

could emerge because the use of ICT tools requires

changes in daily routines and activities for all the

An Italian Business Case for an eHealth Platform to Provide Remote Monitoring and Coaching Services for Elderly with Mild Cognitive

Impairment and Mild Dementia

stakeholders – healthcare providers, patients, and

their informal caregivers.

6 RECOMMENDATIONS AND

CONCLUSIONS

The aim of this study was to assess a business case for

an eHealth platform to provide remote monitoring

and coaching services for elderly with mild cognitive

impairment and mild dementia. A lack of economic

evidence leads to difficulties to decision-makers in

investing in eHealth solutions for dementia. Findings

from this study demonstrate that the eHealth platform

containing remote monitoring and coaching

functionalities is a worthwhile investment, with

benefits for people with mild cognitive impairment

and mild dementia, and also for the healthcare

provider.

To further enhance the business case, several

changes could be implemented to the DECI services:

(1) Patient or informal caregiver contribution.

Willingness-to-pay analysis showed that the

average monetary contribution by the

patients could comprise 28,20 euros. The

average contribution by the informal

caregivers could comprise 23,10 euros per

month.

(2) Healthcare insurance contribution. Financial

burden could be shared with insurers.

However, negotiations for eHealth

reimbursement would need to be started.

Since the positive monetary benefits of

DECI affect insurers, achieving contribution

from the insurers is deemed to be of good

potential.

Delimit the technology of the DECI solution to

software-only. Currently, the biggest part of the cost

is caused by the smartwatch technology and its usage

fees. And patients were not as satisfied with the

smartwatch as with the software technologies (mainly

due to the design issues). Eliminating the smartwatch

would substantially reduce the cost, thus making the

solution even more attractive for investment. For

activity monitoring, one could also resort to using the

accelerometers in patients' smartphones, which are

equally capable of registering physical activity.

7 LIMITATIONS

The main limitation of the study was the follow-up

period of 6 months, which affected the observed

outcomes in terms of health and quality of life. A

longer period could have possibly provided a more

meaningful evaluation. Another limitation was

related to the outcomes that could not be turned into

monetary values (both for costs and benefits). In such

cases, qualitative discussion is provided. Lastly, there

was a lack of preventable falls data since this data was

not collected in the study and had to be obtained from

the literature. However, the literature used is based on

the same OTAGO program in other studies.

ACKNOWLEDGEMENTS

The authors would like to express gratitude to

research consortium of the DECI project, financed by

European Union’s Horizon 2020 research and

innovation programme under grant agreement No

643588: Fondazione Politecnico di Milano, Consoft

Sistemi SpA, Fondazione Don Carlo Gnocchi Onlus

(Italy), Centre for Healthcare Improvement –

Chalmers University of Technology, Västra

Götalandsregionen (Sweden), Hospital Universitario

de Getafe - Servicio de Geriatría (Spain), Maccabi

Healthcare Services (Israel), Roessingh Research and

Development (The Netherlands).

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An Italian Business Case for an eHealth Platform to Provide Remote Monitoring and Coaching Services for Elderly with Mild Cognitive

Impairment and Mild Dementia