Medical Treatment with a Remote Care Technological Solution

Diego Marca-Mariaca, Oscar Medina-Poemape and Willy Ugarte

Universidad Peruana de Ciencias Aplicadas (UPC), Lima, Peru

Keywords:

Remote Care, Mobile Application, Cloud Computing.

Abstract:

The care service for the treatment of diseases is an activity that is performed in person, which uses the usual

ﬂow of appointment reservation and waiting time to access care, so that the diagnosis was provided and

subsequently the appropriate treatment. Here, we present the development of a technological architecture

that will allow you to manage user information to optimize the service in which you can reduce appointment

booking time, attention time and even compliance with treatments remotely. Validation of the work proposal

was carried out through a mobile solution in the test scenario that functioned as a pilot to demonstrate the

feasibility of outpatient care service and to keep remote follow-ups to patients treated against the pathology of

overweight. The results show the feasibility of our proposal.

1 INTRODUCTION

In Peru, the application of therapy in the public sector

is applied to people who are generally adult patients

between 40 and 70 years old, who opt for this method

of treatment

However, the current care model for therapy is car-

ried out in the traditional way, that is, in person so that

allows the diagnosis and identiﬁcation of the appro-

priate treatment for the patient can be completed.

This process requires the face-to-face meeting of

the specialist doctor and the patient for the follow-up

of the treatment, since the material used in the pa-

tient’s data can remain on average eight days (Lee

et al., 2008; Hou et al., 2015).

Given this, for the patient this process implies

non-compliance with the treatments prescribed, since

it requires a signiﬁcant amount time lost in accessing

the service due to the following factors.

First, according to the national institute of statis-

tics and informatics (INEI) published in February

2020, shows the average wait time to set an appoint-

ment can be up to two and a half days regardless if it

is public or private.

The same study also indicates that the average

waiting time for the patient to be seen is approxi-

mately 51 minutes at the national level.

In addition, the average commute time to reach

the health center is calculated to be approximately 31

https://orcid.org/0000-0002-7510-618X

Essalud (in Spanish) - 2016

minutes due to various factors such as the location be-

tween users and vehicular trafﬁc

The beneﬁts of the therapy required signiﬁcant of

monitoring and control to improve the physical and

mental well-being of the patients.

Monitoring patients through telemedicine makes

possible to obtain patterns or make future predictions

for patient treatment.

Our contributions are as follows:

• We develop a mobile solution that provides care

service for treatment of diseases.

• We propose a solution to encourage patients to

comply with the treatments, so that the beneﬁts

of applying this therapy will be performed.

These treatments do not require invasive methods,

and these beneﬁts will empower the patient im-

prove their physical and mental well-being.

• We expect to provide the medical care service re-

motely to patients efﬁciently.

This work is organized as follows. Section 2 presents

the study of the related works. Section 3 describes the

technological proposal and the case study completed.

Finally, experimental results are presented to validate

the feasibility of our proposal.

INEI (in Spanish) - 2020

Marca-Mariaca, D., Medina-Poemape, O. and Ugarte, W.

Medical Treatment with a Remote Care Technological Solution.

DOI: 10.5220/0011041300003188

In Proceedings of the 8th International Conference on Information and Communication Technologies for Ageing Well and e-Health (ICT4AWE 2022), pages 213-219

ISBN: 978-989-758-566-1; ISSN: 2184-4984

213

2 RELATED WORKS

In (Chen et al., 2018), the authors present an intelli-

gent system, called Healthcare System App, for the

health care of university students in Taiwan by estab-

lishing an interactive diet in which users can record

the contents of their diet, nutrients and their exercise

routines anytime, anywhere.

The main result that was identiﬁed in the study

was that the application helped students to achieve the

proposed objectives:

• 75% reached the breakfast goal.

• 90% reached the lunch goal.

• 90% reached the exercise goal.

Unlike them, we have established a treatment that in-

teracts with the specialist doctor through the mobile

solution platform.

The contribution of (Luhanga et al., 2018) was to

present an application that includes the inﬂuences and

interaction of social support with attachments to phys-

ical activities, identifying certain requirements and

speciﬁcations that users require for its use.

The main results of this study were that 63.04%

of the challenges were completed and that the appli-

cation had a rating of 3.04 out of 5 (Luhanga et al.,

2018). Unlike them, we have implemented an evalua-

tion module in the style of a form.

In (Kronborg et al., 2018), the authors analyze pa-

tient data in the Telehomecare trial using home mea-

surements through prediction models based on logis-

tic regression.

The main result that was identiﬁed in the study

was that the optimal combination of predictors (using

three physiological predictors and exacerbations) ex-

cluding the incidence of exacerbation in patients and

populations.

The contribution of (Almeida et al., 2010) is to

implement an alternative application that allows the

monitoring of patients with amyotrophic lateral scle-

rosis using Telehome monitoring devices that ensures

the transmission of data and request for medical as-

sistance.

The work conﬁguration evidenced the number of

hours of use per day, the percentage of spontaneous

respiration, backup respiratory rate, average respira-

tory rates and the percentage of pressures that were

reached contributed to an increase in the respiratory

activation sensitivity, where the patient felt comfort-

able with a normal respiratory rate.

In contrast, we implemented a tracking system

through weekly evaluations where the patient records

user data to track its evolution.

In most of the work, the characteristic is that

through the use of different technological tools they

can maintain continuous monitoring of patients for

the beneﬁt of health.

3 METHOD

In this section we present the main concepts and ar-

chitecture for our proposal.

3.1 Preliminary Concepts

3.1.1 Technological Architecture

This enterprise architecture model presents a more

complete perspective of how you will develop and de-

ploy your application components.

This has four layers, which are business, logic,

data and physics that act as a basis for the efﬁcient

performance of the information systems that support

the service and solution provided users.

The architecture design presents a series of steps

to be considered to determine the structure and orga-

nization of the information systems

These include the components, functions, nodes,

operating systems, data instances and physical de-

vices such as servers computers, mobile equipment,

among others that must be deﬁned (Syynimaa, 2019;

Lugma

na-Hidalgo and Garrido, 2019).

The main components of our proposal are as fol-

lows:

1. Business Architecture: The business architec-

ture is deﬁned as the layer that presents the busi-

ness strategy through a set of requirements speci-

ﬁed in mapping the processes.

To complete, it is important to analyze the pro-

cesses that make up the current state and identify

deﬁciencies that can be improved so that stake-

holders achieve their business objectives (Ma-

suda, 2021; Niemi and Pekkola, 2020).

2. Data Architecture: This layer manages the phys-

ical and logical information, which will present

information through views.

It is responsible for storing the information in in-

stances which must be consulted by the business

stakeholders (Masuda, 2021; Niemi and Pekkola,

2020).

3. Logical Architecture: The architecture layer

shows the technical aspects for the solution cre-

ated, where the functions developed for the appli-

cation that are based on business processes and

requirements are used.

ICT4AWE 2022 - 8th International Conference on Information and Communication Technologies for Ageing Well and e-Health

214

It is important to emphasize that this layer is con-

tained in the technological layer because physi-

cal executions are required for operation (Masuda,

2021; Niemi and Pekkola, 2020).

4. Physical Architecture: In this layer, the lowest-

level components of the solution are presented.

The support the elementary resources for the con-

tinuation of the business such as directories, apps,

databases, emails, etc.

Therefore, this layer is essential for the correct

execution of the implemented solution, guaran-

teeing the correct ﬂow of communication and al-

low for the continuity of the strategic objectives of

the business (Masuda, 2021; Niemi and Pekkola,

2020).

3.1.2 Cloud Service

It is a tool that through its design allows easy access to

applications or resources over the internet without the

need to pay for hardware with dedicated components.

The adoption of services is naturally at the request

of the client or company user.

In this global context, people make use of these

services consciously even if they do not have deep un-

derstandings of the of technologies.

Thus, the management of these cloud services are

provided by experts in the ﬁeld of Cloud Computing

who provide information backup, application hosting,

among others.

Likewise, the services provided to meet customer

needs are called Infrastructure as a Service (IaaS) and

Platform as a Service (PaaS)

1. Infrastructure as a Service (Iaas): Cloud ser-

vice that is oriented for IT system administrators

who require IT resources from providers so as

not to pay for local infrastructure installations and

maintenance (e.g., Amazon Web Services, Google

Compute Engine, and Microsoft Azure

2. Platform as a Service (Paas): Cloud service that

are targeted to application developers, provide ca-

pabilities such as database, operating system, and

a programming language to meet the needs of de-

velopment environments

3.2 Mobile Solution

This proposal consists on implementing a mobile so-

lution that will provide medical care service for peo-

ple who require treatment of diseases.

What is a cloud service? - Citrix - 2020

A series of phases has been identiﬁed that will al-

low us to understand the proper ﬂow of our work.

The phases of the mobile solution are detailed be-

low:

1. Phase 1 (Analysis): The problem was analyzed

and, secondly to complement the data, surveys

were carried out to contextualize the usual tasks

required of the users, so that the service could be

optimized remotely, including the reservation of

the appointment, history of symptoms, means of

health monitoring, waiting time for care and time

during care.

Thus, the analysis of the app stores of Apple and

Android, to locate any apps related to the tasks

required in the environment.

In addition, in order to identify tangibles in our

proposal, we had the need to ﬁnd programming

environments to be used and the Cloud service

that through its characteristics would allow the de-

velopment. of the proposal (e.g., Android Studio

and Microsoft Azure).

2. Phase 2 (Technological Architecture and De-

velopment): This process is presented in Fig 1

and shows the logic application layer found in the

application design, including the part of the sys-

tem with which the user interacts shown.

These interfaces make use of controllers to com-

municate with the back-end and the processing

logic to make the application work.

The data layer is where we store our components

as CRUD operations this includes links to the Mi-

crosoft MySQL database service.

In summary, both the patient interface and the spe-

cialist interface through the use of mobile data or

Wi-Fi network to connect to the API hosted in Mi-

crosoft Azure where the business logic layer and

the Data layer are located, which is ﬁnally linked

with MySQL.

3. Phase 3 (Evaluation Process): This process re-

quires to start with the functional tests that in our

case we validate all the ﬂows that the mobile so-

lution incurs.

Then we have the identiﬁcation of the case study,

considering the recommendations of the clinic

and the inﬂux of patients to collect the sample

group.

After, we have the validation where the volunteers

were instructed their execution of the mobile so-

lution was supervised.

A product satisfaction survey to capture opportu-

nities in how to improve the mobile solution will

be analyzed.

Medical Treatment with a Remote Care Technological Solution

215

Figure 1: Deployment Architecture Model.

As a ﬁnal step, the indicators would be evaluated.

4 EXPERIMENTS

The experimentation of this work had three valida-

tion sources which compare between the average re-

sults shown by outpatient care process in the public

and private places, the results of the compliance of

the treatment remotely and the satisfaction of the user

using the mobile application.

4.1 Experimental Protocol

The solution was developed using the .NET and

Kotlin programming language, which made it possi-

ble to obtain the expected backend and frontend func-

tionalities.

In addition, it requires the CloudinaryAPI, which

enables the solution to manage the upload of images

in the cloud.

The APK of our proposal is publicly available at

https://bit.ly/2HckOU5.

4.2 Test Scenario

The validation of the proposed model was carried out

in a medical center downtown district of Lima, Peru,

with 15 patients and one specialist representing 10%

of the patients for the month during the COVID-19

pandemic.

In this validation, the volunteers used the mo-

bile solution to record the appointments and request

a treatment, allowing a specialist to display applica-

tions and address them through their mobile devices.

The patients underwent a process where they

recorded essential information; height, age, weight

and a photo of their ear, so that the specialist can in-

struct the therapy points and maintain control of the

patient’s treatment evolution.

4.3 Results

Table 1 (columns 2 and 5) shows how greatly reduced

the time to choose the proper attention of the ﬁrst 3

items, where the results of the MINSA (Public Hospi-

tal) months before COVID 19 pandemic started, com-

pared to our proposal where the average time to book

the appointment, waiting time and the time to arrive

at the establishment were reduced by 86.36%, 91.8%

and 100% respectively.

It should be noted that this public information

ICT4AWE 2022 - 8th International Conference on Information and Communication Technologies for Ageing Well and e-Health

216

Table 1: Main results.

(a) Comparison of current situation with our solution.

Public Entity

Service

Private

Entity

(minutes)

Before

Pandemic

(minutes)

After

Pandemic

(minutes)

Our

Solution

(minutes)

Average time

to reserve the

appointment

22 5 5 3

Average wait

time for care

49 24 8 4

Average time

to reach the

establishment

31 50 70 -

(b) Results of the Remote Process.

BMI Average

Age

State

Before

Treatment

After

Treatment

Young 27.94 27.62

Adult 24.86 24.71

Elderly 26.83 26.42

Average 26.69 26.41

does not consider the information during the COVID-

19 pandemic, because the ofﬁcial report was not avail-

able at the time of the study.

In Table 1 (columns 3 and 4), where the data given

by the private establishment before the pandemic is

compared with our proposed solution, it is possible to

reduce the treatment wait time in that order between

40%, 83.3% and 100% respectively.

Additionally in the same establishment during the

pandemic, the reservation time of the appointment,

waiting to receive attention and commuting to the es-

tablishment was reduced by 40%, 50% and 100% re-

spectively.

In Figure 2, there is the result of the treatment for

the overweight where there is evidence of a decrease

in the Body Mass Index (BMI) after the sessions ac-

cording to the person’s life cycle, where the young

person (14 to 29 years old) reduced by 1.17%, the

adult (30 to 34 years) in 0.64% and the elderly (45 to

60 years) in 1.55%.

Other result of the treatment for the overweight is

a decrease in the Body Mass Index (BMI) after the

sessions, where the BMI for young people (14 to 29

years old) reduced by 1.17%, for the adults (30 to 34

years) in 0.64% and for the elderly (45 to 60 years) in

1.55%.

4.4 Discussion

As we can see all the results given by Fig 1, we es-

timate a quantitative improvement, that reduces the

time of care in a public or private establishment that

provides treatments.

In addition, according to the results given by

Fig 1b and 2, the volunteer patients when following

the specialist’s instructions through the mobile solu-

tion were able to stimulate the atrial cavity according

to the recommended points.

And according to their age groups they managed

to decrease the body mass index.

After this, in our mobile solution obtained good

to satisfactory references in the survey completed by

volunteers where 54% corresponding to the Fig 2

were found satisﬁed with the mobile solution.

Fig 2 shows that 67% of the people found the mo-

bile solution process very efﬁcient.

Medical Treatment with a Remote Care Technological Solution

217

(a) Results of the Remote Process.

(b) Satisfaction for the Mobile Solution Function-

alities.

(d) User Experience w.r.t. the Mobile Solution.

Figure 2: Comparison of results for different criteria.

In Fig 2, 40% found the user experience with the

solution excellent.

5 CONCLUSION

In conclusion, our mobile solution based on our tech-

nological architecture improves the patient experi-

ence to maintain control and monitoring the treat-

ments.

On one hand, the deployment of this solution en-

ables to optimize remote care by registering appoint-

ments and going to specialized centers to access care.

On the other hand, the data collected from our vol-

unteers treated against being overweight through our

mobile solution showed that patients were able to de-

crease their BMI during the ﬁrst week of the session,

therefore, our proposal is able to provide follow-up

and control towards patients requiring remote therapy

care.

Our results show that the implementation of tech-

nologies such as Machine Learning and image recog-

nition, would greatly improve the automation the spe-

cialist’s instructions identifying the diseases and leads

to a better diagnosis.

Furthermore, using Genetic information to seek

for historical data about a patients (Arroyo-Mari

nos

et al., 2021) or monitoring symptoms with a simi-

ICT4AWE 2022 - 8th International Conference on Information and Communication Technologies for Ageing Well and e-Health

218

lar technological solution for other diseases (Jorge-

evano et al., 2021).

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