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Implementation Report

Ten Years of Experience With a Telemedicine Platform Dedicatedto Health Care Personnel: Implementation Report
Claudio Azzolini1,2,3, MD; Elias Premi3,4, MD; Simone Donati3,5, MD; Andrea Falco2,6, MEng; Aldo Torreggiani7,
MEng; Francesco Sicurello3,8, BSc; Andreina Baj5, MD; Lorenzo Azzi5, MD; Alessandro Orro2,3,8, MEng; GiovanniPorta5, MD; Giovanna Azzolini2, BSc; Marco Sorrentino2,9, JD; Paolo Melillo10, MEng; Francesco Testa10, MD;
Francesca Simonelli10, MD; Gianfranco Giardina11, MEng; Umberto Paolucci12, MEng
1

Advisory Council of e-Health and Telemedicine, University of Insubria of Varese-Como, Varese, Italy2

TM95 Srl, Milan, Italy

3

Italian Association of Telemedicine and Medical Informatics, Milan, Italy

4

Department of Life Sciences and Biotechnologies, University of Insubria, Varese-Como, Italy

5

Department of Medicine and Surgery, University of Insubria, Varese-Como, Italy6

Alfa Design Studio, Milan, Italy

7

T&C Srl, Milan, Italy

8

Institute of Biomedical Technologies, National Research Council, Milan, Italy

9

Bms Farm Law Firm, Milan, Italy

10

Multidisciplinary Department of Medical, Surgical and Dental Sciences, University of Campania Luigi Vanvitelli, Naples, Italy

11

DDay.it, Milan, Italy

12

Up Invest Srl, Milan, Italy

Corresponding Author:
Claudio Azzolini, MD
Advisory Council of e-Health and Telemedicine
University of Insubria of Varese-Como
Via Guicciardini 9
Varese, 21100
Italy
Phone: 39 0332393603
Email: claudio.azzolini@uninsubria.it

Abstract
Background: Telemedicine, a term that encompasses several applications and tasks, generally involves the remote management
and treatment of patients by physicians. It is known as transversal telemedicine when practiced among health care professionals(HCPs).
Objective: We describe the experience of implementing our telemedicine Eumeda platform for HCPs over the last 10 years.
Methods: A web-based informatics platform was developed that had continuously updated hypertext created using advanced
technology and the following features: security, data insertion, dedicated software for image analysis, and the ability to export
data for statistical surveys. Customizable files called “modules” were designed and built for different fields of medicine, mainlyin the ophthalmology subspecialty. Each module was used by HCPs with different authorization profiles.
Implementation (Results): Twelve representative modules for different projects are presented in this manuscript. These modules
evolved over time, with varying degrees of interconnectivity, including the participation of a number of centers in 19 cities acrossItaly. The number of HCP operators involved in each single module ranged from 6 to 114 (average 21.8, SD 28.5). Data related
to 2574 participants were inserted across all the modules. The average percentage of completed text/image fields in the 12 modules
was 65.7%. All modules were evaluated in terms of access, acceptability, and medical efficacy. In their final evaluation, theparticipants judged the modules to be useful and efficient for clinical use.
Conclusions: Our results demonstrate the usefulness of the telemedicine platform for HCPs in terms of improved knowledge
in medicine, patient care, scientific research, teaching, and the choice of therapies. It would be useful to start similar projects
across various health care fields, considering that in the near future medicine as we know it will completely change.
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KEYWORDS
telemedicine; ophthalmology; eHealth; informatics platform; health care professional; patient care; information technology; data
warehouse

Introduction
Context
Medicine has typically involved physicians engaging face toface with patients. However, many teleconsultation projects
have now been developed, particularly during the COVID-19
pandemic era, which has boosted teleconsultations in all medical
specialties [1-4].
Alongside telemedicine between physicians and patients, there
is also transversal telemedicine, which is conducted between
health care professionals (HCPs). Our experience with this topic
started in 1996 and has demonstrated the feasibility of training
young ophthalmic vitreoretinal surgeons working in nonoptimal
environments (postwar Bosnia), using telemedicine (via asatellite link) in Milan and Sarajevo [5,6]. Input from the above
experiences [7,8] constituted the basis for our understanding of
the needs of HCPs and the developmental direction of thededicated telemedicine platform, giving users access, withappropriate personal authorization, from anywhere and at any
time.

Problem Statement
The problem to be solved is the difficulty of sharing patients’clinical data and images among health personnel for efficientevaluation. This process should be multidisciplinary, involving
actors such as physicians from different specialties, nurses,
technicians, orthoptists, geneticists, residents, and tutors whoneed access to a common database holding key patient
information.

Similar Interventions
Our scientific literature analysis identified a number ofpublications about implementation projects involving
telemedicine platforms. These projects were mainly based on
COVID-19 management and aimed to support different systems
to provide health care in emergency conditions [9-11]. The
purpose of these initiatives is to foster telecare andtelemonitoring and to reduce the need for patients to visit
hospitals or medical centers [12-17]. Our program is oriented
in a different direction: the Eumeda web-based medical platform
was developed for sharing patients’ medical data among
physicians. The platform has expanded its services to many
HCPs. This paper describes how database modules for theclinical databank and trials, as well as second opinion services,were created and have now been implemented.

Methods
Aims and Objectives
The aim of this implementation program was to broaden theapplications of our telemedicine platform with a transversal
approach targeted at health care personnel. This process took
place over the last 10 years with the creation of different projects
aimed at clinical data collection, teleconsultation, and gathering
second opinions. Various modules have been built for theplatform (Textbox 1) for use by HCPs at different times. Twelve
representative modules for different clinical projects aredescribed in Table 1 [18-23].
We identified outcome measures and evaluated overall
parameters for access, acceptability, and medical efficacy ofthe platform (Textbox 2).

Textbox 1. Building a module in 8 steps. The time required for the final release varies between modules (from 1 to 3 months for more complex ones).
The original source code for the modules created belongs to the medical platform.
1. Initial agreement between the entity applying the module (university, company, institution, or representative association) and the manager of the
medical platform (MP)2. Signing of detailed operational form (with project requirements, such as the type of project, number of health care professionals and structures
involved, and the importance of images) by the main users of the module and the scientific coordinator (who has knowledge of medicine planningand the potentiality and limits of medical informatics) of the MP
3. “Shoulder-to-shoulder” work by the scientific coordinator of the MP and main team programmer of the MP
4. Development of alpha software (not yet stable and still incomplete) to be shown to the entity that will use the module for changes and additions
5. Development of beta software with almost all functionalities
6. Massive data entry by the MP programmer to find bugs or software incompatibilities
7. Completion of beta software with automatic control functionalities (eg, alert icons to prevent inappropriate data from being entered, numericallimitations, and priorities to be respected in data entry or blocking of inappropriate saving) for users to check and identify any small changes required
8. Release of final version in a meeting with users, with explanatory text embedded in the module

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Table 1. The left-hand column lists the 12 representative projects for which many modules have been built for the medical platform. The modules
designed have been managed by health care personnel over the last 10 years in different locations in Italy.

aModuleDescription

Module type1

Teleconsultation in retinal
diseases [18]2

PurposeTimeframe of
project activity

HolderSponsor

Second opinionsa Feasibility of second 1 Month (during
opinions among
2011)
physicians

Insubria University,
Varese-Como

Comed Research
nonprofit association, Milan

Age-related maculopathy[19]

Groupb (10 locations)

Acceleration of an- 19 Months (2011ti–vascular endothe- 2012)
lial growth factor
therapy

T&C Srl, Milan,
Italy

Novartis Pharma
SpA, Origgio, Italy

3

Retinal pathology samples
and correlated genes [20]Datac

Collection of data on 4 Months (2012gene expression
2013)

Insubria University,
Varese-ComoInsubria University,
Varese-Como

4

Epiretinal macular membrane [21]Data

Collection of data on 10 Months (2015disease morphology 2016)
and functionality

Insubria University,
Varese-ComoInsubria University,
Varese-Como

5

Inherited eye diseases

Data

Collection of data on 2017-present
genetic eye diseases

Ophthalmological
Unit II, Universityof Naples

Ophthalmological
Unit II, Universityof Naples; RomeFoundation

6

Retinal dystrophy due torare RPE65 gene mutation[22]

Group (9 locations)Collection of data on 16 Months (2018disease
2020)

Ophthalmological
Unit II, Universityof Naples

Retina Italia nonprofit association, Milan

7

Second opinions among res- Second opinions
ident physicians

Feasibility of second 4 Months (during
opinions in didactics 2019)

Comed Research
nonprofit association, Milan

Bayer Italy SpA,
Milan

8

Instrumental data in multiple Group (2 locasclerosis
tions)

Collection of multidisciplinary data on
disease2019-present

Neurological Unit,
Insubria, University
Varese-ComoInsubria University,
Varese-Como

9

Epidemiological data on
COVID-19 in workers

Group (2 locations)Search for COVID19 in throat, saliva,
and tears

3 Months (during
2020)

SEA Company, Mi- SEA Company, Milan Linate-Malpensa lan Linate-Milan
Airports
Malpensa Airports

10

SARS-CoV-2 on throat andocular surfaces [23]Group (2 locations)Search for SARSCoV-2 in throat andtears in COVID-19
patients

1 Month (during
2020)

T&C Srl, Milan.
Italy

Insubria University,
Varese-Como

11

Potential malignant oral lesions

Group (2 locations)Collection of data on 2021-present
disease

Orthodontics Unit,
Insubria University,
Varese-ComoInsubria University,
Varese-Como

12

Maculopathies and anti-aging medicine

Data

Collection of data on 2022-present
diseases and followup

Claude Boscher,MD

Claude Boscher,
MD

Second opinions: second opinions from health care professionals at the same or a different institution.

bGroup: shared database used by health care professionals at more than one institution.

c

Data: shared database used by health care professionals at a single institution.

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Textbox 2. Result options for the questionnaire for each health care professional, with relative scores. The final score is given by the sum of the partial
scores (maximum 9, minimum 3). Scores equal to or higher than 6 are considered to indicate approval.
Access to the network by computer or mobile devices- Poor: score of 1
- Good: score of 2
- Very good: score of 3
Acceptability of the procedures- Poor: score of 1
- Good: score of 2
- Very good: score of 3
Medical efficacy- Poor: score of 1
- Good: score of 2
- Very good: score of 3

Blueprint Summaryand overlapping, and SMS and email notification, whennecessary, for fast interactivity.

Design of Key Features and Roadmap

Customizable Modules

The design of the implementation program was oriented todevelop three types of operational modules, integrated with one
another where necessary: (1) a databank of diseases for clinicalor scientific studies, (2) a database for groups of HCPs in
different locations, giving them access to shared data from trial
studies, and (3) a functionality enabling physicians to seek
second opinions. The key points of the implemented modules
were easy accessibility, complete acceptability for HCPs, datareliability, and overall medical efficacy considering all healthspecialties. The roadmap followed these principles and several
new projects involving HCPs produced specific modules, whichwere created for the platform and take advantage of its benefits
as a whole.

The platform includes customizable files called “modules” thatare designed and built for each project according to its needs incollaboration with professionals from different knowledge areas(Textbox 1). Each module functions to support the features andadvantages of the entire platform. No data are sent directly toor from HCPs’ hardware. HCPs are able to see data in the central
database, accessing this information remotely. All HCPs havea personal access code depending on their authorization level,
enabling them to view, insert, or modify data in specific fields,
close the electronic medical record (EMR) data temporarily or
permanently, and export data for statistical surveys. The
platform allows for individual and group interaction among
HCPs at different sites. A remote “prompt assistance” service
is provided for each module when necessary.

Technological Design and Infrastructure
Since 2010, the Eumeda platform has used continuously updated
versions of PHP, an HTML-embedded web scripting language
built to a high standard using advanced technology [24], which
has the advantage of speed, flexibility, low use of resources,
and compatibility with all web servers. PHP does not require ahigh level of machine resources to run and is therefore very fastand lends itself to applications with external integration.

Main Features of the Platform
Information technology services can be accessed via monitors
or mobile devices and include current advanced technologies,
such as the following: 24-7, 365-day-a-year access, easy data
image insertion in electronic medical records, image comparison

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Module Functionality
Several functions can be activated, with open pop-ups showing
the rationale of each study, its population, the provenance ofresources, and the operating HCPs with various authorization
profiles. The data entry procedure is quick, intuitive (Figure 1),
and guided by many system alerts in the case of errors. Whennecessary, warning notifications are sent to users via SMS or
email. Special software can be created, if requested, to support
HCPs’ data evaluation and clinical decisions [25-27] (Figure2). Data extraction for statistical surveys is immediate (Figure1). At the end of each study period, the HCPs evaluated the
project using a 3-point scoring system (Textbox 2).

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Figure 1. Example of the main tasks and procedures for a module (module 6 in Table 1) on the medical platform: (1) entry to the system by the healthcare professional with their personal access key, after which they select the modules that they are qualified and authorized to use; (2) access to a list ofoperative centers with their own lists of patients and respective electronic medical records relating to the first and follow-up visits; (3) individual patientelectronic medical record folder, which allows for the easy and quick insertion of data and multiple images at any time, as well as access to successive
masks (a repository of images is available that allows image overlapping and comparison; Figure 3); (4) quick data extraction for statistical purposes.

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Figure 2. Examples of 2 special software programs designed to support health care professional activity. (1) For medical care decisions, each diagnostic
variable of a disease is given a numeric value, and the software automatically provides a total score (shown by the arrow). If the value exceeds a definedscore, the software advises general physicians to send the patient to an appropriate center at the next available appointment (module 2 in Table 1). (2)For tracking patients’ clinical course, visual acuity data (or any other numerical data) are inserted into a patient’s electronic medical record and thegraph is updated in real time. The health care professional can see at a glance the functional course of the disease. RE: right eye; LE: left eye.

Images
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all images is available for each module. Image magnificationand comparison software enables morphological changes to beobserved over time in detail (Figure 3).

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Figure 3. Example of image comparison: (1) selection of 2 images from a patient’s electronic medical record (in this case, the patient had degenerative
retinal maculopathy) uploaded at the 6-month follow-up (shown by the arrows); (2) creation of an overlap image that can be adjusted by clicking andmoving the white cross; a special transparency application allows the images to be accurately superimposed on each other (shown by the white rings);(3) evaluation of morphological changes in the disease over time (within the white rings) by moving the overlap line back and forth (shown by the whiteline) using the red button.

Type of Technology
The Eumeda software platform is closed-source and owned bya private company that grants access through contracts. The
platform was developed with the Wappler (Wappler.io)
integrated development environment.

all of whom rely on access to a common database holding key
patient information.
The target sites are hospitals, private offices, and medical hub
centers working with spoke-peripheral centers. We involved
medical structures equipped with technology and staff prepared
to use hardware and software (Figure 4).

Targets
The target user base includes physicians of different specialties,
nurses, technicians, orthoptists, geneticists, residents, and tutors,

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Figure 4. Locations of health care professionals (round dots) in Italy who have used the platform over the years (the map shows the Italian names of
the cities). The Supervisory Center (SC) in Milan has responsibility for the data warehouse and help desk as well as a general coordination role.

Data
Data Location
All data were uploaded and stored in a data warehouse in Milan,
Italy (Datasys Srl from 2001 to 2012; then Aruba Business Srl,
provided by IRQ10 Srl, from 2013 until the present), to ensure
data security and uninterrupted availability. Automated daily
backups are a security measure guarding against the loss of data.
Data Entry Policy
HCPs must agree to the liability agreement, ownershipagreement, and a code of conduct before using the platform. In
all modules, data entry is performed in accordance with theguidelines of the Declaration of Helsinki and its subsequent
revisions [28]. Informed consent forms are collected by thehealth facilities. In cases where data analysis included atherapeutic choice, approval from the relevant ethics committee
or a qualified local committee was obtained, as in modules 6
and 11 in Table 1.
Data Security and Privacy
Data security and privacy are guaranteed by the latest generationof servers with secure backups. Data are protected on several
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levels: (1) individual HCPs receive access keys generated by
the system; (2) subjects’ personal data are encrypted and stored
in a separate table in the cloud; (3) the system binds clinicaldata to personal data only when accessing hardware with a
special algorithm; and (4) if necessary, a ready-to-use informed
consent form can be downloaded for signature.
Responsibility for and Ownership of Data
According to European Union (EU) and Italian rules, liability
for entered medical data, including cloud storage, lies with the
HCP entering such data (acting as the “controller,” as clearly
defined in EU Regulation 679/16) and the manager of the
medical platform and server farm (acting as “processors,” asclearly defined in EU Regulation 679/16). Ownership of thedata, including the purpose and methods for processing the data,
belongs to the entity applying the module, who acts as the“controller.”Interoperability
The Eumeda software platform is not accessible from specificapplication programming interface clients by users, so it does
not use data standards such as Health Level Seven. However,it implements the International Classification of Diseases, 10th
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Azzolini et alrevision, system internally to classify pathologies. Clinicalimaging is managed with current standard protocols.

Implementation (Results)

Participating Entities

Coverage

A nonprofit organization (Comed Research) initially
implemented (from 2001) the projects. Subsequently, a joint
venture between 2 for-profit companies (T&C Srl and TM95
Srl) managed the platform. These partners supply hardware,
create software, or participate as web designers, hosting
companies, or law firms. The funders of the implementation
projects are public universities, hospitals and foundations,nonprofit medical associations, private companies, andphysicians working in private offices (Table 1).

The projects developed during the implementation phase havenational coverage, encompassing a large number of Italianregions and their referent hospitals. The developed modules
evolved over time, with varying degrees of interconnectivity,
in different centers in 19 cities across Italy (Figure 4). In 2
modules (modules 1 and 2 in Table 1), HCPs from the referring
regional areas were closely involved. The number of HCPs (atdifferent levels) using individual modules ranged from 6 to 114(average 21.8, SD 28.5).

The society that created the main platform is the owner of all
the implementations. The entities that applied the modules holdthe ownership and the intellectual property.

Outcomes

Budget Planning
The total budget covered different phases according to
implementation progression and project type for a period of 1
to 3 years. The costs included preliminary planning and the final
draft (up to 30%), programming for final front view on thecomputer screen (30%), and user training (10%), as well as thepilot phase (5%), operation (10%), initial service (10%), andongoing reports (5%). Selected projects could be conducted forfree based on their importance or visibility for the platform.

Sustainability
The projects were initially funded (from 2001) by a nonprofit
organization (Comed Research), which relies on donations fromcompanies or nonprofit medical associations. Since January 1,
2017, the platform has been managed by a joint venture between
2 for-profit companies. The business model is based on the typeand duration of the projects developed during theimplementation phase, financed by different entities. The endof the project foresees the dissemination of the results withpotential permanent effects.

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Implementing the telemedicine platform allowed us to build
several modules that could be used by HCPs at different times.
The characteristics of 12 representative modules used over thelast 10 years for different clinical projects are shown in Table
1.
Over time, our experience has led us to concentrate on three
types of operational modules, integrated with one another ifnecessary: (1) a databank of diseases for clinical or scientificstudies (eg, module 4; Table 1), (2) a database for groups of
HCPs in different locations, giving them access to shared data(eg, module 6; Table 1), and (3) a functionality enabling
physicians to seek second opinions (eg, module 7; Table 1).
The overall outcomes are reported in Table 2. Up to now, morethan 250 HCPs have used the platform for several effective andoperational projects. The total number of participants inserted
in the modules is 2574. The percentage of data entered in the
text or image fields for each module ranged from 20% to 95%(with an average of 65.7%). The evaluation score for each
module was calculated as the sum of 3 partial scores (Textbox2): out of all the modules, the first (module 1, the first to becreated) was the one with the lowest evaluation score (Table2). The average number of requests for technological support
varied from 5 per month (in the case of simpler modules) to 9
(for more complex ones).

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Table 2. Results pertaining to the designed modules shown in Table 1.
Centers involved, HCPsa in- Participants
Text/image fields for Beneficial effectsnvolved, n whose data
each EMRb, n (fields
were inserted, n that were filled in, %)Evaluation scorec(minimum positivescore)

ModuleDescription

1

Teleconsulta- 1 Retina center,tion in reti17 territorial ofnal diseases fices
[18]

18

52

30 (60)Useful teleconsultation
among doctors

2

Age-related 11 Retina centers 114
maculopathy
[19]

678

65 (85)

Improvements in patients’ 803 (684)functional final outcomes3

Retinalpathology
samples andcorrelated
genes [20]1 Ophthalmologi- 11
cal center, 1 genetic center

12

65 (80)Better understanding ofmolecular mechanisms

4

Epiretinal
macularmembrane[21]

2 Ophthalmolog- 11
ic centers, 1 human anatomy
center28

25 (65)

Identification of ultramicro- 80 (66)scopic features of membranes

5

Inherited eye 1 Ophthalmologi- 14
cal center, 1 gediseasesd
netic center

1145e

480e (20)Increased knowledge ofgenetic eye diseases

In progress

6

Retinal dystrophy due
to rare
RPE65 genemutation[22]

9 Retinal-genetic 28
centers60

260 (65)

Identification of suitablepatients for therapy

200 (168)

7

Second opin- 4 University oph- 19
ions among thalmological deresident
partments

110

12 (85)Resident physicians’
learning accelerated

140 (114)58e

450e (18)

Recognition of the disease In progressin the subclinical stage

9298

30 (90)

Collection of useful diagnostic data on COVID-19
and how the disease istransmitted

75 (54)109 (108)

Not acquired

physiciansd
8

Instrumental 2 Neurological6
data in multi- centers, 2 ophthalple scleromological centerssisd

9

Epidemiolog- 2 Care offices at
ical data on 2 airports
COVID-19
in workersd

10

SARS-CoV- 14 Medical units
2 on throat
and ocularsurfaces [23]

20

108

34 (95)

Increased knowledge of
COVID-19

165 (120)

11

Potential ma- 4 Medical units
lignant oral
lesions615e50e (68)

Better prevention andtherapy

In progress

12

Macu1 Retina center
lopathies andanti-aging
medicine610e110e (58)Significantly better care

In progressa

HCP: health care professional (physicians from different specialties, nurses, technicians, orthoptists, geneticists, residents, tutors [employees were
excluded]).
b

EMR: electronic medical record (for each patient, considering first visit and all follow-ups).

c

Sum of 3 partial scores for access, acceptability, and medical efficacy at end of the active working period (described in Textbox 2).

d

Unpublished data.

eAt the time of writing this paper.

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Clinical fallout can be identified more easily with the use ofthis telemedicine platform because of the visibility of a databaseshared by HCPs (modules 3, 4, 5, 8, and 9; Table 2).
Furthermore, data on rare diseases (collected from a large
number of centers) can be used to identify patients who would
benefit from expensive new therapies (module 6; Table 2). By
sharing medical data, physicians and residents can learn betterand faster (modules 1 and 7; Table 2), and the possibility of
having a databank helps them to discover potential, as yet
unknown disease complications (module 10; Table 2). Patient
follow-up with dedicated software helps HCPs to locate better
treatment options, identify preventive interventions (modules
2 , 11 and 12; Table 2) and track patients and their outcomes inreal time.

Lessons Learned
Our program has multiple success factors that may be consideredin future implementations or in the creation of similar
telemedicine platforms and modules. First, the technologicalinfrastructure of the platform is modern, highly versatile, andcontinuously updated by technical staff. The use of the latest
generation of servers with secure, daily backups guarantees thatno data loss occurs, while data security and privacy are protected
on several levels, as specified in the Methods section. Second,
data entry and retrieval in each module are immediate. Each
module has different blocks of information that are well
separated, including an explanation of the rationale of the study
and practical guidance on how to insert data, as well as different
HCP access profiles, patient IDs, EMRs, images, and statisticalsurveys. Third, no images are transmitted among HCPs. All
images are stored on the main server and are viewed remotely
without any deterioration. A dedicated procedure even allows
the insertion of high-resolution images (through common
connection links) immediately or very quickly. Rapid viewing
is greatly appreciated by users, in addition to the possibility ofenlarging, comparing, and superimposing, as well as being able
to see in detail the morphological changes, even minimal ones,of a pathology over time (Figure 3). Lastly, different
authorization profiles are given to HCPs, which enables themto access modules on the central server once they have agreed
to abide by the terms of the liability and ownership agreements
and the code of conduct, using personal passwords to view,
change, or modify data and images. Module coordinators usually
have total control of their respective modules and can compile
statistical surveys using all the data, while other HCPs may only
be able to enter data and images in accordance with their remit
and authorized access level. A great amount of work has been
undertaken to ensure that the user-friendly platform is up andrunning. A remote service is available by mail or telephone. All
modules are visible both from monitors and mobile devices. In
particular, the second opinion module may be suitable for use
with mobile health (mHealth).
We consider the following points more as challenges than limits
to implementation. The construction phase of each module isof critical importance, and a single medical interlocutor must
be the voice of all HCPs (Textbox 1). The main mandatory
factors involved in building a module include a scientificcoordinator as the central figure and the participation of someone
with both medical and IT skills. Finally, older HCPs tended tohttps://medinform.jmir.org/2024/1/e42847

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Azzolini et al
struggle with working on the platform, while the younger
operators adapted quickly, were not disconcerted by thetechnology, and showed interest and satisfaction with the
projects they carried out [29-34].
The presumed budgets of each project, divided into direct (eg,coordinators, IT programmers, law firms) and indirect (eg,travel, equipment, insurance) costs have been considered in the
final balance.
The following recommendations may assist in overcoming many
barriers to telemedicine practice among HCPs. First, the amountof preparatory work needed (Textbox 1) tends to beunderestimated. Second, it is difficult to create systems forsharing text and images with appropriate levels of usability.
Third, bureaucracy is often an obstacle, and self-regulation
codes in telemedicine need official authorization. Fourth, asuitable “network culture” is still lacking in medicine, due tomultiple technical and human factors. The success oftelemedicine among HCPs requires participation, responsibility,
and a desire for effective collaboration to develop knowledge
for the benefit of professionals and patients.

Discussion
Principal Findings
The technological infrastructure of telemedicine intended strictlyfor HCPs is specific to this field, is not easy to implement, andmust be customized for each individual project. Key persons
such as scientific coordinators (with specific knowledge of
medicine and IT) and program managers must be well chosen
for projects to succeed. The results of our projects have showna range of benefits, including increased medical efficacy andclinical knowledge, improved patient care, enhanced teaching
and integration among hospitals, and a more effective choiceof therapies. It is necessary for work to be carried out onorganizational, bureaucratic, and network culture issues wherethese are not yet fully accepted and on sustainable businessplans.
We identified some difficulties and limitations in our
implementation project that may also be considered useful for
future or similar telemedicine projects. Building a module in
the absence of straightforward ideas forced us to make majorchanges during construction, meaning that the preliminary work
completed had to be discarded and redone. All the software
involved in the platform modules must be customized according
to the needs of the HCPs, which requires time and hard work.
Too many text or image fields to fill out and include in EMRs
make the system difficult to use and produce a very large final
database that is not fully used (as happened with module 5).

Conclusion
In conclusion, our experience was that both physicians andpatients were always satisfied to be part of this “community ofhealth” supported by groups of HCPs working for their benefit
and making them feel cared for. The detailed description of our
implementation program may be useful to shorten the learning
curve for others seeking to implement similar projects in many
fields of medicine, which must be able to adapt to thecontinuously changing nature of medicine now and in the future.
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Acknowledgments
We would like to thank the hundreds of health care professionals who have used and contributed over time to the developmentof the platform. Special thanks go to all engineers, programmers, and other personnel who in their various capacities have worked
to improve the platform over the last 10 years, especially Francesco Oggionni (IT professional) and Valerio Tartaglia (ITprofessional). We are grateful to Ferruccio Fazio, MD, former Italian minister of health, and Gianfranco Ferla, MD, for theirsupport and advice. We would also like to thank Roberta Romagnolo (Lexikon) for editing the manuscript.

Data Availability
The data on which this manuscript is based are available upon request to the corresponding author.

Conflicts of Interest
None declared.

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Abbreviations
EU: European Union
EMR: electronic medical record
HCP: health care professional
mHealth: mobile healthhttps://medinform.jmir.org/2024/1/e42847

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Edited by C Perrin; submitted 13.10.22; peer-reviewed by J Gurp, van, M Venturini, S Pesälä, V Ramos; comments to author 27.01.23;
revised version received 13.07.23; accepted 29.11.23; published 26.01.24
Please cite as:
Azzolini C, Premi E, Donati S, Falco A, Torreggiani A, Sicurello F, Baj A, Azzi L, Orro A, Porta G, Azzolini G, Sorrentino M, Melillo
P, Testa F, Simonelli F, Giardina G, Paolucci U
Ten Years of Experience With a Telemedicine Platform Dedicated to Health Care Personnel: Implementation Report
JMIR Med Inform 2024;12:e42847
URL: https://medinform.jmir.org/2024/1/e42847
doi: 10.2196/42847
PMID: 38277199©Claudio Azzolini, Elias Premi, Simone Donati, Andrea Falco, Aldo Torreggiani, Francesco Sicurello, Andreina Baj, Lorenzo
Azzi, Alessandro Orro, Giovanni Porta, Giovanna Azzolini, Marco Sorrentino, Paolo Melillo, Francesco Testa, Francesca
Simonelli, Gianfranco Giardina, Umberto Paolucci. Originally published in JMIR Medical Informatics (https://medinform.jmir.org),
26.01.2024. This is an open-access article distributed under the terms of the Creative Commons Attribution License(https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium,provided the original work, first published in JMIR Medical Informatics, is properly cited. The complete bibliographic information,a link to the original publication on https://medinform.jmir.org/, as well as this copyright and license information must be included.

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