A Novel Blockchain based Platform to Support Chronic Care Model

Information Management

Luigi Lella and Sergio Piersantelli

Azienda Sanitaria Unica Regionale delle Marche, via Oberdan n.2, 60122 Ancona, Italy

Keywords: eHealth, eHealth Applications, Design and Development of Methodologies for Healthcare IT.

Abstract: Blockchain technology has been successfully used in many healthcare contexts, guaranteeing not only high

security and privacy levels in clinical data management, but also the continuous updating of patient clinical

pictures, to ensure the continuity of care and the reliability of data sources in statistical processing. These results

are related to the peculiar features of this technology such as the distributed ledger, the chaincode, the encryption

algorithms used to cypher information, the technological solutions used for block validation and the use of smart

contracts. This article aims to present a possible solution based on blockchain technology to the problem of

information management in the Chronic Care Model. The use of the blockchain makes it possible to create a

patient-centred system that not only allows patients, or authorized people, to exercise a constant control over

their health data, but it is also able to "contractualize" the agreements made in this regard together with the

collection of consent for the processing of health data. The blockchain also allows the preparation of validated

data sources for the subsequent statistical processing to update process and outcome indicators and the risk

prospects related to the care pathways activated for patients suffering from chronic pathologies.

1 INTRODUCTION

Patients involvement within the health information

system can lead to a marked improvement in individual

and social health outcomes (Kushniruk and Nøhr,

2016). These results are even more evident when

strategies are adopted to address the education of

patients in order to create a sort of partnership with

health professionals and other caregivers (Batalden et

al., 2016; Bodenheimer et al. 2002).

Designing an information system to support

healthcare activities can however be an extremely

complex activity, especially in the case of the treatment

of patients suffering from chronic pathologies that

require long and prolonged interactions with various

actors of the information system. These actors can be

not only professionals and caregivers, but also IoMT

devices that must constantly monitor vital parameters.

This is the case of the Chronic Care Model (CCM),

a model of health care for chronically ill patients

developed by Professor Wagner and his colleagues at

the McColl Institute for Healthcare Innovation, in

California (Wagner et al., 2001; Wagner et al., 1999).

The model proposes a series of changes at the level of

health systems useful in favouring the improvement of

the condition of chronic patients and suggests a

"proactive" approach between health personnel and the

patients themselves, with the latter becoming an

integral part of the care process (Coleman et al., 2009).

The CCM model is characterized by six

fundamental characteristics (Wagner et al.,1996).

Delivery System Design: the care activity is provided

with a clear subdivision of the tasks and

responsibilities between the various caregivers and

health professionals that take care of the patient,

making a clear distinction between planned assistance

(e.g.: follow up) and assistance in the acute phase

(acute care);

Self-management Support: that consists in assisting in

a collaborative way the patients and their families in

the acquisition of the necessary skills for the treated

disorders and diseases. The information system

intervenes in this phase by making available self-care

tools, references to community resources and tools for

assessing therapeutic compliance;

Decision Support: the presence of evidence based

decision support tools that can also be used by patients

to agree with their GPs the therapeutic or

pharmacological pathway to follow;

Clinical Information System: the information system

must mainly provide tools to support therapeutic

compliance, a system of indicators for the assessment

Lella, L. and Piersantelli, S.

A Novel Blockchain based Platform to Support Chronic Care Model Information Management.

DOI: 10.5220/0008869003030309

In Proceedings of the 13th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2020) - Volume 5: HEALTHINF, pages 303-309

ISBN: 978-989-758-398-8; ISSN: 2184-4305

303

of outcomes and care benefits and agendas for

assistance activities planning;

Community Resources: connection to territorial and

hospital resources for the training of the assisted and

for the reporting of care managers;

Health Care Organizations: connection to the

organizational structure, objectives and values of the

health system that takes care of the patient.

To date, within the CCM, adequate information

systems have not yet been defined that can support

patients in all their needs and actively involve them in

the care process. Indeed, it was noted that most of these

patients were marginalized if not even excluded from

any initiative of active involvement (Marmot et al.,

2012). These cases have led to a substantial worsening

of care outcomes and to an increase in care costs

compared to the average (Coulter et al., 2018) and to a

worsening of the quality of the assistance given to

disadvantaged patients (Mackert et al., 2016).

Difficulties have also been encountered in the

exchange of data in a secure and scalable manner

between the various system actors, in the support of

clinical communications especially in the cases of

patients living in remote areas, producing in this case

also a deterioration in efficacy and quality of care

services that should be supported by adequate

information systems (Zhang et al., 2018; Castaneda et

al., 2015; Berman and Fenaughty, 2005).

In general, the process of clinical information

retrieval is slow as health data, when not present in the

Electronic Health Record, must be recovered from

various sources, prepared in order to respect certain

schemas and sent to the recipient through appropriate

channels characterized by high levels of security and

reliability (Nourie, 2015). The process of clinical

information retrieval is also incomplete precisely

because of the extreme fragmentation of produced data

and the lack of those produced by the same patient, and

it is decontextualized because all the data are provider-

centred and not patient-centred. Furthermore health

information systems do not allow patients to know how

and by whom data is processed and do not allow to

govern access policies to them (Schoenberg, 2013).

The data are also not updated in real time (Ash et al.

2004).

In assisting patients suffering from chronicity, and

therefore also in CCM, remote patient monitoring

(RPM) is of fundamental importance, because it allows

to move some care services outside the traditional

clinical setting (typically at home care recipients). The

use of RPM can help to further reduce the cost of

assistance and improve the outcomes achieved. The

currently used tele-monitoring devices have now

become unobtrusive, user-friendly and equipped with

advanced features such as alerting and patient feedback

collection systems directly implemented at the device

level.

Currently no solutions have been defined that

allow secure management of the data in Internet of

Medical Things (IoMT) networks (Linn and Koo,

2017) and the sharing of data between authorized

devices in order to provide a complete information

framework to allow them to carry out automatic

operations safely through their actuators (Bolduc,

2017).

Finally, precisely because of the innumerable

sources of health data (most of which derive directly

from IoMT devices and the direct feedback of

patients), it is particularly difficult to bring them all

back into a single framework to generate a valuable

population level insight (Asokan and Asokan, 2015).

The blockchain technology (BC) can provide a

viable implementation solution that guarantees secure

access to health data, system scalability, privacy of

clinical data, and data collection to conduct evidence-

based studies of population medicine.

The aim of this article is to suggest a possible

solution for the implementation of a CCM support

information system which is based on the BC

technology. After a rapid examination of the main

characteristics of this technology (Section 2), the main

applications of the BC in medical and healthcare field

will be reviewed, with respect to the management and

sharing of clinical and remote control devices

information (Section 3). The architecture of CCM

support platform designed by ASUR will then be

illustrated together with a business case related to the

context of AV2 local health system of Marche Region

(Section 4).

2 BLOCKCHAIN TECHNOLOGY

MAIN FEATURES

A BC system can be considered as a distributed and

potentially incorruptible cryptographic database,

where it is possible to store sensitive and health data.

Technically it is essentially a peer-to-peer network

with an open and distributed ledger, whose updating is

based on appropriate consensus rules for the transfer of

blocks of information between entities that can be

people, organizations and devices.

BCs can be permissionless and permissioned. A

permissioned BC limits the number of actors who can

participate in the consensus validation process.

The data related to a new block contained in the

ledger spread through the peer-to-peer network as soon

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as it is possible to establish a communication between

each couple of authorized nodes. Each of the

authorized nodes, following the one that generated the

block, has the right to verify the validity of the block

and the correspondence with the network policies. If

the transaction is accepted, it is digitally signed and

stored in the distributed ledger. All rejected

transactions are entered into a temporary archive.

A register can be seen as an ordered sequence of

transactions divided into blocks. Each block can

represent a set of transactions (for example the transfer

of clinical data or information) and contains two

elements. The first is the header that includes a

timestamp and the hash code of the header of the

previous block. The second is the body that contains all

the transaction data properly encrypted.

The link that connects a header to the previous one

(starting from the first chronologically inserted that is

called “Genesis”) allows to set up the BC ensuring that

nobody can tamper the inserted data. The only way to

do this would be to control more than 51% of the nodes

before modifying the data in the distributed ledger.

This situation is attributable to the Byzantine Generals

Problem (BGP) (Melnyk et al., 2018). In these cases

the protocol to be used to manage the consent must be

Byzantine Fault Tolerant (BFT).

The distributed register can also contain smart

contracts (Szabo, 1997) that can help to regulate the

access to the data contained in the blocks and to

validate them. For example a smart contract can be

used to define privacy policies or to define appropriate

alerting rules linked to certain data-driven conditions.

3 RELATED WORK

With regard to the processing of personal and sensitive

data in the health field, there has always been a conflict

between data privacy (Pavlou, 2011) and data

accessibility that is the sharing of data between the

professionals who take charge of the patient (Culnan,

1984).

In contexts such as the CCM, professionals from

different fields and disciplines should be able to access

the contents of clinical records they need (Reti et al.,

2010). In the operative reality, interoperability between

information systems belonging to different healthcare

organizations or based on different technologies is

often not guaranteed (Detmer et al., 2008). This

problem is well known in the health field under the

name of care coordination (Klein et al., 2015).

In general, in the health sector there is a need to

implement secure and scalable systems capable of

ensuring access to data on a large scale, guaranteeing

trust and the compliance with the policies on sensitive

and personal data.

The first solutions for the management of health

data privacy and accessibility in the presence of multi-

professional teams or multiple health organizations

resort to multi-agent solutions (Isern and Moreno,

2016; Barrue et al., 2015; Wimmer, 2014). More

recently, solutions based on BC technology based on

the Electronic Health Record model have begun to be

considered. Some first implementations make use of

the distributed ledger of the BC, of a secure

management system of encryption keys and of a

characteristic system for blocks validation (Wood et

al., 2016), other solutions resort to the so-called

miners, or groups of nodes of the peer-to-network peer

that constitutes the BC, which are given the task of

validating new transactions (Azaria et al., 2016;

Ekblaw et al., 2016). Other more recent

implementations make use of BC cloud services to

ensure the secure and unalterable exchange of

information between multiple healthcare

organizations, in order to constantly update the

patient's clinical picture and to ensure continuity of

care (Xia et al., 2017). Such systems prove to be

particularly effective in contexts such as the treatment

of patients suffering from chronic disorders (e.g. HIV

and cancer). For chronic patients, permissioned BC-

based solutions have also been adopted, especially to

ensure privacy and data security (Dubovitskaya et al.,

2017). Also characteristic is the choice made by

(Benchoufi et al., 2017) to manage the patients'

informed consent through a CB to make it

unfalsifiable.

In general, however, for the management of

clinical data by multidisciplinary teams of

professionals, the tendency is currently to resort to the

Personal Health Record model where patients

themselves or their representatives are responsible for

managing the access policies to their data, monitoring

constantly their accesses and the uses made of them

(Chen et al. 2018; Yue et al., 2016; Ivan, 2016). This

choice is well suited to the CCM model, which

provides for a high level of involvement of the patient

who actively and consciously participates in the choice

of the therapeutic path.

With regard to remote monitoring systems using

IoMT devices, in recent times there has been the choice

of implementing solutions based on the BC (Griggs et

al.,2018; Wu et al., 2019).

For RPM through IoMT devices, it is generally not

recommended to use computationally heavy

algorithms such as Proof of Work (PoW) for block

validation and symmetric-type encryption algorithms

are used (Dorri et al. 2016, Dorri et al. 2017).

A Novel Blockchain based Platform to Support Chronic Care Model Information Management

305

Furthermore smart contracts for data processing are

implemented in order to identify critical situations and

to send alerts to the nodes associated with health

professionals (Griggs et al., 2018).

Overall, what emerges from the literature seems to

validate the choice of the BC for the safe and reliable

management not only of the communications between

professionals who take care of chronic diseases but

also of communications coming from or exchanging

IoMT devices (Dwivedi, 2019).

4 ASUR CCM MANAGEMENT

FRAMEWORK

A patient-centred CCM management framework

(CCMMF) will be implemented at the Area Vasta 2,

throughout the territory that revolves around the

community hospitals of Jesi, Loreto and Chiaravalle.

The CCMMF will interface with other systems

already used at regional level such as the regional

authentication system called FedCohesion, the Policy

Manager and the Regional Attribute Authority to give

the actors involved in the CCM the appropriate access

rights to the CCMMF platform. The regional reference

database for patients anagraphical data called ARCA

will be used together with the Electronic Health Record

called SIRTE and the regional catalogs containing the

updated data of the organizational structures.

The CCMMF will consist of a permissioned

blockchain (BC) based on the HyperLedger Fabric

(HLF) platform. The various nodes must first undergo

an authentication procedure before performing the

creation or validation of new blocks. The approval

(endorsement) of a set of transactions (sending

multiple clinical information) present in a new block

will follow a process characterized by various phases

(proposal, approval, ordering, validation and commit)

and will follow certain approval policies. In particular

these policies will identify which nodes must give the

endorsement for a given transaction class, while the

chaincode will guarantee that these policies have been

implemented.

Before committing, peers will execute the

chaincode to ensure that there are sufficient

endorsements and that they have been obtained from

the appropriate entities (those defined at the policy

level). In the end, a check will also be carried out on

the version of the registry before inserting the new

blocks to avoid attacks such as double spending

operations. Each transaction in a block contains its

read/write set or the set of cryptographic keys that have

been read or written at endorsement time.

The HLF framework introduces the channel

element. In HLF the channels are the first level of

segregation and information confinement. A ledger is

logically associated with a channel (a register itself

replicated as many times as there are peers associated

with that channel). Therefore peers that do not

participate in a channel do not have visibility on the

data written in it.

For a more accurate management of access within

a channel it is possible to define ACLs (Access Control

Lists). Access policies are written in blocks but on a

separate channel from the application data. Writing

within a channel the authorization logics there remains

an indelible auditable trace over time of all the

definitions made and all their modifications.

In this way it is possible to solve the problem of

managing access policies in a lightweight and scalable

manner, complying with the current provisions of the

GDPR (General Data Protection Regulation, 2016). By

accessing the channel dedicated to data access policies

produced by the peer-to-peer network, the patient, or a

person in charge thereof, can modify these policies at

any time, guaranteeing the traceability of accesses, the

data obscuration as well as the obscuration of

obscuration. In other words, not only unauthorized

nodes will not be able to access the contents of a file,

but they will also ignore their existence. It will also be

possible to recover all the health information produced

by the peer-to-peer network by going back along the

chaincodes associated with the various channels,

storing them in an exportable format and it will also be

possible to process all the information made available

by the client for statistical purposes.

The chaincode, at the time of accessing the data,

will perform a check on the authorization criteria

currently available and will apply them in response to

a request for a node. For the encryption of clinical data,

symmetric algorithms will be used to facilitate

transactions with and between IoMT device nodes.

In the CCMMF solution implemented by the

ASUR, smart contracts will also be used for the

purpose of processing data, and implementing alerting

systems in order to proactively alert caregivers and all

professionals who have taken care of the client of

important changes in the relative clinical picture.

The activities of the professionals operating within

the CCM will be managed through a workflow

management system (WMS). Thanks to this WMS

through an app that can be installed on the smartphone,

the assisted and its caregivers will have a complete

picture of the care path to follow and will receive alerts

on scheduled events (such as taking a drug, carrying

out an outpatient visit or of a therapeutic treatment) or

on critical events to be managed promptly by following

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the appropriate guidelines prepared by the

multidisciplinary team that took care of the client.

The CCMMF will initially be tested on care

pathways aimed at patients suffering from chronic

cardiovascular diseases and will provide real-time

monitoring of some vital parameters of the patient

(heart rate, blood pressure, ECG) using IoMT devices.

The figure shows a typical scenario relating to the

CCM. The main actors are the cardiac patient, the

general practitioner (GP), the family nurse

practictioner (FNP), the local professional (dietitian,

nutritionist, social worker, geriatrician, physiatrist,

wellness coach etc.), the drugstore (which can also

provide services in addition to the administration of

drugs, counselling services or registration of

parameters such as weight, body mass index, pressure

etc.), IoMT monitoring devices wearable by the

patients and any affiliated shops where patients can

purchase food monitoring the ingredients and

quantities purchased to check if the purchased product

is in line with the diet that patients must respect.

All these actors can create blocks or access blocks

belonging to their own channel, in compliance with the

access policies to the data established by the patient.

To ensure that the CCM is effectively applied, the

workflow of the entire care process must follow the so-

called ‘5As’ model (Glasgow et al., 2006). Following

the recruitment of the assisted by the GP, the path

followed by the CCM is started. The first phase

(1.assess) consists in the recovery, through

appropriate questionnaires, of the knowledge of the

patients about their chronicity, of their behavioural

habits and of their expectations of improvement. This

phase mainly involves the patient and the FNP who

administers the questionnaires. In the second phase (2.

advise) the FNP helps the client to understand what are

the possible therapeutic and pharmacological pathways

that can be followed. The ultimate aim is to allow the

patient to make an informed choice of the care pathway

registering it in the third phase (3.agree) within a

specific smart contract. This will allow the entire

assistance system to safeguard itself also from the legal

point of view. In the smart contract, the consent will

also be recorded in relation to the data processed in the

various channels activated, released in an informed

manner by the user.

In the fourth phase (4.assist) assistance is provided

following the pathway agreed with the patient. The

vital parameters of patient are also monitored in order

verify whether the chosen care pathway is giving

rise to objectively verifiable improvements. In this

patient-centred record patients can incorporate patient-

reported experience measures (PREM) and patient-re-

ported outcome measures (PROM) in addition to data

Figure 1: CCMMF communication diagram.

provided by wearable monitoring devices [16].

In the fifth phase (5.arrange) the FNP, in

agreement with the multidisciplinary team (GP,

dietician, nutritionist, social worker, geriatrician,

physiatrist, wellness coach etc.) who takes care of the

client, decides the modalities in which to conduct any

follow-up activities.

The main actors presented in the communication

diagram of Figure 1 will interface to an Enterprise

Service Bus which has the task of managing

communications between the healthcare IT platforms

used in the regional context and the main IT systems

that make up the backbone of the platform to be

realized.

The system components are shown in figure 2. The

circles represent the interfaces used by the system

actors. The professionals who take charge of the care

recipient have been divided into two groups consisting

of regional health personnel (who authenticate

themselves through the FedCohesion regional

authentication system) and non-healthcare personnel

operating in the regional territory (physiatrist, social

worker, dietician, nutritionist, wellness coach etc.) that

uses another strong authentication system included in

the interface.

The interfaces used by the main actors (with the

exception of the IoMT devices) have an adequate GUI

that guarantees adequate levels of usability /

accessibility considering the relative user categories.

The blockchain is implemented using the open

source framework HLF, which also allows the channel

mechanism to be implemented.

For the management of consent data, a special channel

must be used within the network that constitutes the

blockchain. A node must be created and managed

for each of the types of actors involved in the business

process of Figure 1.

A Novel Blockchain based Platform to Support Chronic Care Model Information Management

307

Figure 2: CCMMF architecture.

At the end of the route, all the sensitive and health

data produced must be recovered using the chaincode

associated with the route, in order to ensure its

completeness and validation.

5 CONCLUSIONS

After a brief summary of the BC technology features

and an examination of the main implementation

solutions relating to the IT support systems for care

activities aimed at patients suffering from diseases and

chronic disorders, a possible computerization solution

of the CCM based on BC technology was presented.

This platform will be used on an experimental level

for a year in a restricted territorial reality of the Marche

Region, and if it will present concrete and encouraging

levels of results it will soon be extended to the whole

regional territorial reality.

The outcome measures collected at the end of the

trial period will be used to evaluate the effectiveness of

the technological solution chosen to support the care

activities related to the CCM.

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