AdoBPRIM: Towards a New Healthcare Risk-aware Business Process

Management Tool

Raﬁka Thabet

1,2

, Amine Boufaied

, Elyes Lamine

, Dominik Bork

4 a

, Ouajdi Korbaa

1 b

and Herv

e Pingaud

University of Sousse, ISITCom, MARS Research Lab, Route G.P.1, 4011, Hammam Sousse, Tunisia

University of Toulouse, INP, CNRS, LGC, F-31432 Toulouse Cedex 04, France

University of Toulouse, IMT Mines Albi, Department of Industrial Engineering, Route de Teillet, 81013 Albi Cedex 9, France

University of Vienna, Faculty of Computer Science, W

ahringer Street 29, 1090 Vienna, Austria

Keywords:

Medication Use Process, Medication Error, Risk-aware Business Process Management, BPRIM, ADOxx.

Abstract:

Performing risk management in healthcare facilities is particularly difﬁcult due to the highly dynamic, complex,

and multi-disciplinary nature of healthcare processes like the Medication Use Process (MUP). Risk-aware

Business Process Management (R-BPM) is a promising approach to obtain a better understanding of such

processes by identifying and analyzing corresponding risks. However, not all R-BPM approaches perform

well in capturing the complexity of clinical processes. In this work, we introduce a new R-BPM framework

called BPRIM that allows the identiﬁcation and the analysis of medication error risks related to the complex

medication use process. BPRIM is implemented using the ADOxx meta-modelling platform and then tested in

a real case study. The tool is speciﬁc to the case study, but the framework can be used also in other healthcare

processes.

1 INTRODUCTION

Patient safety is a priority for several government

agencies, non-proﬁt organizations, and regulatory bod-

ies considering the detrimental and ﬁnancial conse-

quences associated with Medication Errors (MEs) and

Adverse Drug Events (ADEs). A ME is an unintended

failure in the Medication Use Process (MUP) that leads

to, or has the potential to lead to, ADE for the patient.

Indeed, MUP is a complex and multidisciplinary pro-

cess that involves numerous professionals and com-

poses several steps. This complexity causes the occur-

rence of MEs, which can lead to serious health-related

consequences for the patients. In 2015, the French Na-

tional Authority for Health considered that 40% of the

serious adverse events are of medication origin (HAS,

2013).

Many international studies and reports recognized

that the majority of errors were not the result of reck-

less behavior on the part of healthcare providers, but

occurred as a result of the speed and complexity of

https://orcid.org/0000-0001-8259-2297

https://orcid.org/0000-0003-4462-1805

the MUP. Reports concluded that many patients die

during hospital admission as well as during primary

care, simply due to medication errors (Moyen et al.,

2008). Most of these errors are not coincidental but

systematic in origin. Although most available studies

originate from the USA, studies conducted in other

countries such as the United Kingdom (Leape et al.,

1991) and the Netherlands (Barker et al., 2002) have

shown similar results. This strongly implies that med-

ication errors are a major public health problem in

many western as well as developing countries.

Reducing the MEs risk is a shared responsibility

between patients, healthcare professionals, regulators,

and the pharmaceutical industry at all levels of health-

care delivery. (Kane-Gill et al., 2017) recognizes that

preventing harm resulting from adverse drug events

may be circumvented by averting medication errors

with appropriate risk management approaches.

What needs to change is the way in which health-

care risk management methods are orientated. Indeed,

in the healthcare ﬁeld, several risk management meth-

ods exist (HAS, 2013). However, these methods do

not consider the complexity of MEs, its strong con-

498

Thabet, R., Boufaied, A., Lamine, E., Bork, D., Korbaa, O. and Pingaud, H.

AdoBPRIM: Towards a New Healthcare Risk-aware Business Process Management Tool.

DOI: 10.5220/0008977604980505

In Proceedings of the 13th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2020) - Volume 5: HEALTHINF, pages 498-505

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

Figure 1: Medication Use Process as BPMN model (based on the French National Authority for Health report (HAS, 2013)).

nection to the MUP activities, and the inﬂuence of

organizational and human factors. Following these

observations, it would be essential for the healthcare

facilities to explore new risk management approaches

which consider all related concepts to the ME risk oc-

currence as well as their dependencies inherent to the

steps and activities of the MUP.

To alleviate the shortcoming of existing ap-

proaches, we propose studying the potential of

the Business Process-Risk Management - Integrated

Method (BPRIM) (Lamine et al., 2019; Thabet et al.,

2018) to manage MEs risks related to the com-

plex MUP. BPRIM is an integrated management ap-

proach of risk and business processes following the

Risk-aware Business Process Management (R-BPM)

paradigm (Suriadi et al., 2014; Lamine et al., 2019;

Thabet et al., 2018). R-BPM aims to integrate the

traditionally separated domains of risk management

and business process management. This integration

allows increasing efﬁciency of the risk identiﬁcation,

detection, and assessment in relation to the business

processes.

This paper is structured as follows. First, Section 2

provides an overview of the MUP and the impact and

the frequency of the ME occurrence in this process.

In Section 3, we propose a comparative study of the

current risk management methods in healthcare. Our

adopted framework and methodology are presented in

Section 4. An overview of the ﬁrst results obtained

after the implementation of our framework is given in

Section 5. Finally, Section 6 concludes the paper and

outlines future perspectives.

2 BACKGROUND

In (Vest et al., 2019), the Medication Use Process is

deﬁned as “the fundamental system that provides the

basis for safe medication use within the healthcare en-

vironment.” Thus, ensuring medications are used and

secured in the most appropriate manner and across all

settings. The MUP consists of a complex and multi-

disciplinary process, involving numerous practitioners

and several major steps (i.e., prescribing, dispensing,

administration and medication monitoring).

Figure 1 represents the macro-steps and related ac-

tivities of the MUP as deﬁned in the French National

Authority for Health report (HAS, 2013) by means of a

Business Process Model and Notation (BPMN) model.

Obviously, these activities do not reﬂect the reality.

In reality, the MUP may involve up to 46 activities

from the moment a doctor considers prescribing medi-

cation to the moment when this medication is actually

administered or taken by the patient.

The complexity of this process increases the likeli-

hood and number of occurrences of Medication Error

(ME) risks. There is no consensus about the deﬁni-

tion of a medication error. A systematic literature

review found 26 different terminologies employed for

a Medication Error (Lisby et al., 2010). As deﬁned

by the United States National Coordinating Council

for Medication Error Reporting and Prevention (NCC

MERP) (NCC MERP and Prevention, 2019), a medi-

cation error is: “any preventable event that may cause

or lead to inappropriate medication use or patient harm

while the medication is in the control of the health care

professional, patient, or consumer. Such events may

be related to professional practice, health care prod-

ucts, procedures, and systems, including prescribing,

order communication, product labelling, packaging,

and nomenclature, compounding, dispensing, distribu-

tion, administration, education, monitoring, and use”.

This deﬁnition is broad and suggests that errors are

preventable at different levels.

These risks can be at the origin of Adverse Drug

Event (ADE) with potentially severe clinical conse-

quences for the patient. ADEs were deﬁned as injuries

resulting from medical interventions related to a drug.

Adverse drug events may result from medication errors

or from adverse drug reactions in which there was no

error (Bates et al., 1995). ADEs consequences can be

substantial, including hospital admission, prolonged

hospital stay, additional resource utilization, and lower

AdoBPRIM: Towards a New Healthcare Risk-aware Business Process Management Tool

499

patient satisfaction (Caporossi et al., 2014). In this con-

text, many publications have described the frequency

and the cost of MEs and ADEs in the MUP (Bates,

2007). Starting in 2000, the Institute of Medicine be-

gan publishing a series of reports on quality in health-

care. The ﬁrst one, “To Err is Human”, increased

the awareness of unacceptably high rates of MEs and

sentinel events in U.S. hospitals with about 44,000 –

98,000 deaths annually attributed to these preventable

mishaps (Committee on Quality of Health Care in

America and Institute of Medicine, 2000). The sec-

ond one, “Crossing the Quality Chasm”, made four

major points: errors are common and costly; systems

cause errors; errors can be prevented and safety can

be improved; and medication-related adverse events

are the single leading cause of injury (Committee on

Quality of Health Care in America and Institute of

Medicine Staff, 2001). The most recent one, “Pre-

venting Medication Errors”, attempts to think about

what needs to be done to reach the next level of med-

ication safety (Committee on Quality of Health Care

in America and Institute of Medicine, 2006). In this

work, ﬁrst, an epidemiological review showed that, es-

timated very conservatively, medications harm at least

1.5 million people per year. In hospitals, there are at

least 400,000 preventable adverse drug events per year,

or approximately one medication error per patient per

day. That ﬁnding probably had the greatest impact on

the general public (Committee on Quality of Health

Care in America and Institute of Medicine, 2006).

The occurrence of these errors questions the ro-

bustness of the management methods actually used to

secure the MUP in the healthcare facilities especially

that knowledge and practices evolve and the organiza-

tion must remain vigilant.

Facing the high frequency and impact of MEs and

ADEs, healthcare facilities have to set up a risk man-

agement approach aiming to ensure patient safety, and

speciﬁcally, to decrease ME occurrence related to the

complex MUP. Section 3 provides an overview of some

existing healthcare risk management methods.

3 RISK MANAGEMENT IN

HEALTHCARE FACILITIES

In France, ten years ago, Experience Feedback Com-

mittees (EFCs), were created to analyze ADEs within

a medical ward (Francois et al., 2013). An EFC is a

multidisciplinary team representing the diversity of the

functions encountered in the medical ward. The EFC

members meet regularly to examine reported ADEs

related to their medical ward. They prioritize ADEs

either on the gravity of the event or on the frequency of

occurrence and propose corrective actions. To analyze

the ADE facts, the committee uses one or many of

the existing risk management methods in healthcare

facilities.

A comparative study of the most relevant risk as-

sessment methods currently used in the healthcare do-

main is summarized in Table 1. This comparison is

carried out in accordance with the following criteria:

• Process/Activity based:

whether the method de-

scribes in which system process or activity the

causes occurred;

• Reactive/Proactive:

whether the method is reac-

tive (risk considered ex post) or proactive (ex ante

consideration of risk);

• Qualitative/Quantitative:

whether the method

follows qualitative and/or quantitative analysis;

• Input:

the reasons for which the method has to

start being applied;

• Causes Ranking:

whether the method classiﬁes

different causes;

• Logical Relationships:

whether the method de-

scribes relationships between multiple causes us-

ing logical operators to describe risk scenarios;

• Causes Chronology:

whether the method pro-

vides a chronological reconstruction of causes;

• Causes Description:

which description type is

used to represent causes.

Generally, healthcare risk management methods

can be categorized according to the used risk assess-

ment type: Reactive risk assessment and Proactive

risk assessment (see Table 1). Reactive risk assess-

ment methods are Root Cause Analysis methods based

on systematic questioning to identify the underlying

causes of adverse occurrences.

According to Table 1, only few methods (three

out of 10) tried to integrate system process or activ-

ity where the causes occurred in the analysis process.

However, among these approaches, none provides a

graphical description to represent system activities and

relationships between multiple risk causes using logi-

cal operators. In fact, working with graphs allows to

capture a large analysis scope.

In an organisation, all presented methods will set

up brainstorming meetings with a team of healthcare

providers, as well as quality/risk managers, to reduce

the number of MEs and ADEs. However, from our

point of view, none of these methods is able to satisfy

all the following requirements:

•

Deal with the complex MUP at the correct level by

describing all related and collaborative activities

that compose the process (Rq1);

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500

Table 1: Comparing current healthcare risk assessment methods.

Method

Process/

Activity based

Reactive

Proactive

Qualitative

Quantitative

Input

Causes

ranking

Logical

relationships

Causes

chronology

Causes

description

Five Whys ? 2 2 2 2 2

Questioning

2 2 2

Schema/

Table

Ishikawa 2 2 2 2 2

Questioning

2 2 2 Graph

Human Factor Analysis and

Classiﬁcation System (HFACTS)

2 2 2 2 2

Questioning

2 2 2

Graph/

Grid

Association of Litigation And Risk

Management (ALARM)

2 2 2 2 2

Questioning

2 2 2

Form/

Report

Causal Tree Analysis (CTA) 2 2 2 2 2

Questioning

2 2 2 Tree

ORION 2 2 2 2 2

Questioning

2 2 2

Table/

Report

Failure, mode, effects, and criticality

analysis (FMECA)

2 2 2 2 2 Identiﬁed

causes

2 2 2 Table

Fault Tree Analysis (FTA) 2 2 2 2 2 Identiﬁed

causes

2 2 2 Graph

Event Tree Analysis (ETA) 2 2 2 2 2 Identiﬁed

causes

2 2 2 Tree

Preliminary Risk Analysis (PRA) 2 2 2 2 2 Identiﬁed

causes

2 2 2 Table

•

Identify and classify potential and reported ADEs

and MEs (Rq2);

•

Express ADEs in terms of combining potential fac-

tors, situations, events, and consequences (Rq3);

•

Understand the strong relationships between the

ME and activities of the MUP (Rq4);

•

Consider the organizational and human factors

which intervene the ME occurrence (Rq5);

• Produce a dynamic map ranking all ADEs (Rq6);

•

Offer a well designed risk-process knowledge man-

agement repository (Rq7).

•

Provide the EFC team a modeling tool that also

adheres to usability, performance, reliability, scala-

bility, and availability requirements (Rq8).

Consequently, to advance the patient safety, health-

care facilities are required to implement an effective

detection policy, prevention and control of MEs risks

related to the complex MUP. To tackle this situation

we suggest the exploration of new research domains,

in particular the integrated management of risks and

business processes.

4 BPRIM FRAMEWORK

Since several years a major research interest is given

to integrate the two traditionally separated ﬁelds of

risk management and business process management

in a common concept known as R-BPM. The impor-

tance of this integration was conﬁrmed by the research

community (Zur Muehlen and Ho, 2005), in industry

guidelines (COSO 2004), and in many literature re-

views (Suriadi et al., 2014; Thabet et al., 2018; Lamine

et al., 2019).

Business Process-Risk Management - Integrated

Method (BPRIM) (Lamine et al., 2019; Thabet et al.,

2018; Sienou, 2009) is one of the important approaches

proposed in the R-BPM context. The method suggests

an integrative approach with three components:

•

A conceptual uniﬁcation of risk and business pro-

cess based on the coupling between the ISO/DIS

19440 conceptual model and a new conceptual

model for risk.

•

A BPRIM modeling language composed by ab-

stract and concrete syntax. The abstract syntax is

described by a meta-model extending the ISO/DIS

19440 constructs with a new set of constructs for

AdoBPRIM: Towards a New Healthcare Risk-aware Business Process Management Tool

501

Figure 2: BPRIM Framework (excerpt).

risk modeling. The concrete syntax is proposed by

extending the Event-driven Process Chains (EPC)

notation. Figure 2 shows an extract of the BPRIM

meta-model.

•

A BPRIM lifecycle based on the coupling of the

business process management and the risk man-

agement lifecycles. Considering information ex-

changed between the synchronized lifecycles of

business process design and risk management, a

set of diagrams was identiﬁed (e.g. Context, EPC,

Risk-extended EPC, Risk Taxonomy, Risk, Risk

Analysis, Risks Map) (see Figure 2).

In order to evaluate the potential of BPRIM and the

ADOBPRIM tool, we specify for each part individually

to what extent it satisﬁes the requirements deﬁned in

Section 3.

4.1 ADOBPRIM Tool Development

The modeling tool supporting BPRIM called

ADOBPRIM has been developed as a project within

the Open Models Laboratory (OMiLAB), a worldwide

community of modelers and modeling method devel-

opers (Bork et al., 2019). A free download and further

information on ADOBPRIM are available through the

corresponding project page

To realize the ADOBPRIM tool, respecting non-

functional requirements (Rq8) previously deﬁned in

Section 3, we have chosen the ADOxx meta-modelling

platform (ADOxx.org, 2019). ADOxx has been

widely used in industry and academia. In the past

twenty years, more than 50 domain-speciﬁc model-

ing tools have been successfully realized with ADOxx

(see (Karagiannis et al., 2016) for an overview).

ADOBPRIM project page [online]: http://austria.omilab.

org/psm/content/BPRIM/info, last visited: 16.12.2019

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4.2 ADOBPRIM Models

The main diagrams of our approach are outlined below

and also in Figure 2 b, c, d, and e. Moreover, we

highlight how each ADOBPRIM model contributes to

the identiﬁed requirements:

Risk Taxonomy Diagram:

This diagram aims to

build an inventory of potential risks and to classify

them according to various criteria. Risk identiﬁ-

cation can be performed using literature analysis

and/or brainstorming with teamwork.

→ Fulﬁlling requirement Rq2.

Risks-extended EPC Diagram:

EPC diagrams orig-

inally describe business processes by means of

related and collaborative activities that produce a

speciﬁc service or product. Thereby, EPCs provide

a comprehensive understanding of the system and

enable process improvement. The Risks-extended

EPC diagram aims to assign potential risks, de-

ﬁned in the Risk Taxonomy diagram to individual

activities of the EPC diagram.

→

Fulﬁlling requirements Rq1, Rq4, Rq5, and

Rq7.

Risk Analysis Diagram:

This diagram aims to ana-

lyze and evaluate individual risks. It includes:

(i) Underlying causes and consequences; (ii) Risk

level calculation, and (iii) Risk evaluation. Risk

is a complex concept deﬁned in different ways

depending on the context and the discipline con-

cerned. In our case, a risk R is expressed in terms

of scenario S, likelihood L and severity G as ex-

pressed in Equation 1:

R = (S, L, G) (1)

Risk scenario is expressed in terms of a combi-

nation of potential factors, situations, events, and

consequences. Likelihood level is based on the

expertise, knowledge and actual experience of the

group scoring the likelihood. Severity of impact

indicates the impact of the risk event to values

interested for stakeholders. In this work, we are in-

terested in qualitative risk analysis. A guide to like-

lihood and severity of impact levels is presented

in Table 2. Deﬁnitions for the qualitative values

were based on (BLONDEL and BRUNEL, 2004).

The output risk level is illustrated in a two dimen-

sional risk matrix. The purpose of risk evaluation

is to prioritize the risks, and to decide which risks

require treatment as well as the mode of treatment.

→ Fulﬁlling requirement Rq3.

Risks Map Diagram:

This diagram is a two dimen-

sional risk matrix showing the risk level of each

analyzed risk.

Table 2: Likelihood and severity of impact levels according

to (BLONDEL and BRUNEL, 2004).

Likelihood Severity

1 Very improbable 1 Minor

2 Very unlikely 2 Signiﬁcant

3 Unlikely 3 Major

4 Possible/Likely 4 Critical

5 Very likely to certain 5 Catastrophic

→ Fulﬁlling requirement Rq6.

Consequently, through models and capabilities of

the ADOBPRIM tool of the BPRIM method, all func-

tional and non-functional requirements deﬁned in Sec-

tion 3 are satisﬁed. Next, we will present preliminary

results of the evaluation of the BPRIM framework and

the ADOBPRIM tool in a real case study.

5 PRELIMINARY EXPERIMENT

RESULTS

5.1 Experiment Context

To evaluate capabilities, feasibility, and relevance of

the BPRIM framework and the ADOBPRIM tool, we

use a real-world case study within an existing hospi-

tal. The study was conducted in the Pays d’Autan

Hospital of the InterCommunal Hospital Center of

Castres-Mazamet in France. With more than 388 beds,

this hospital includes 30 wards.

According to the World Health Organization

and (Kane-Gill et al., 2017), MEs and ADEs occur

at a higher frequency and with a greater likelihood for

elderly patients. Improving the quality of medication

use and medication safety for elderly patients is thus

an important public health priority. For this reason,

our case study focuses on ADEs risks management

related to the MUP for elderly patients in the Geriatric

department of the Pays d’Autan Hospital. Our experi-

mentation aims to: (i) check the feasibility of using the

BPRIM framework to manage a serious of ADEs risks

related to the MUP of elderly patients; (ii) experiment

with the ADOBPRIM tool in a real case study; and

(iii) identify potentials for improvement.

The experiment was carried out in collaboration

with several actors of the Pays d’Autan Hospital,

speciﬁcally two doctors, three nurses, two pharmacists,

one pharmacy technician, and the Quality Manager.

AdoBPRIM: Towards a New Healthcare Risk-aware Business Process Management Tool

503

5.2 Preliminary Results

The repository of models developed during the experi-

mentation currently holds around 40 BPRIM models.

These last are created and validated in collaboration

with the experimentation team.

The experimentation followed below steps:

Identify organizational units, roles and values re-

lated to the MUP and describe relationships be-

tween them in the context model. As a result, 8

organizational units, 10 roles and 6 values are pre-

sented in the context model;

Build AS-IS models of the MUP of elderly pa-

tients in the Geriatric department: First a value-

added chain model describing an overview of the

MUP sub-processes is presented, and then each

sub-process is deﬁned by an EPC model. As a

result, 14 EPC models presenting a detailed func-

tional and organizational view of the MUP in the

Geriatric department are presented. The EPC mod-

els involve up to 46 activities.

Identify potential and reported ADEs in the depart-

ment. As a result, 16 ADEs organized in 12 classes

are presented in the Risk Taxonomy model (see

Figure 2 a);

Extend AS-IS models with potential and reported

ADEs in the department. As a result, 14 EPC

models extended with the 16 potential ADEs pre-

viously deﬁned. Figure 2 b) shows an example of

an Risk-extend EPC model;

For each ADE, analyze potential and reported

facts, risk situations and risk events contributing

to the ADE occurrence. We studied 10 serious

ADEs risks, reported by professionals, related to

the MUP of elderly patients and that had analyzed

by the EFC using the ALARM method. As a result,

10 Risk Analysis models and 10 Risk models cor-

responding to reported ADEs are deﬁned. Figure 2

c) shows the Overdose Risk Analysis model;

Evaluate each ADE using the risk matrix accep-

tance deﬁned by (BLONDEL and BRUNEL, 2004)

and produce a Risks Map model ranking all ADEs

by risk level (see Figure 2 d);

Diagnose obtained results looking for potential

improvements of the AS-IS models.

ADOBPRIM is a reactive/proactive integrated man-

agement tool of risk and business process management

dedicated to facilitate and to support the multidisci-

plinary EFC members in their ADEs analysis exercise.

Indeed, the tool supports them in understanding the

MUP activities, identifying ADEs, understanding how

the ADE has occurred, prioritizing remedial interven-

tions, and possibly enhancing the MUP steps.

Moreover, with the ADOBPRIM tool, a database

of potential ADEs, analyzes already carried out during

previous EFCs can be accessed and augmented with

new data. In addition, the tool allows accelerating

the ADEs analysis process which consequently allows

analysing more reported ADEs per EFC meeting. In-

deed, due to the heaviness and the complexity of risk

management methods currently used in healthcare fa-

cilities, the EFC committee chooses only one ADE per

meeting in order to analyze it thoroughly.

The tool usage guidelines are partly deﬁned by the

BPRIM lifecycle. It should also be noted that a training

session on the tool usage is necessary for a ﬁrst use.

Some models obtained by ADOBPRIM are presented

like in ﬁgure 2. The latter effectively illustrates some

of the models applied to the MUP extended to the risks

of occurrence of MEs.

Validation and evaluation of our implementation

results are currently performed in accordance with

the very involved healthcare professionals of the Pays

d’Autan Hospital.

6 CONCLUSIONS

The main contribution of this paper is the implementa-

tion of an effective approach to manage MEs related to

the Medication Use Process based on the R-BPM con-

cept. We presented an R-BPM framework for risk and

business process management comprising the BPRIM

method and the ADOBPRIM modeling tool.

The validity check for our contribution was per-

formed in a real case study. The results motivate us to

pursue the improvement of this method by integrating

additional mechanisms and algorithms of risks analysis

of the ADE related to the Medication Use Process of a

patient within the healthcare facilities and studying the

potential of the application of our framework in other

healthcare processes as part of our future research.

ACKNOWLEDGEMENTS

The authors would like to thank the experimentation

team from the Pays d’Autan Hospital of the Intercom-

munal Hospital Center (CHIC) of Castres-Mazamet

and more speciﬁcally Dr. CUFI, the head of the Geri-

atric Department and Dr. CLEOSTRATE, the head

of Inpatient Pharmacies who allowed us to evaluate

our BPRIM method and ADOBPRIM tool on a real

case and provided insights and expertise that greatly

enhanced this research. We would also like to thank

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504

the OMiLAB team for assistance with the ADOxx plat-

form and for providing a collaborative space on their

OMiLAB portal.

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