Using Enterprise Ontology for Improving the National Health System

Demonstrated in the Case of a Pharmacy and an Emergency Department

David Dias, Carlos Mendes and Miguel Mira da Silva

Instituto Superior Técnico, Technical University of Lisbon, Avenida Rovisco Pais, Lisboa, Portugal

Keywords: Enterprise Ontology (EO), Enterprise Reengineering, Operational Processes, Design Engineering

Methodology for Organizations (DEMO), Emergency Department (ED), Pharmacy.

Abstract: The global healthcare spending has constantly increased in the last decades, and there is data showing

inefficiency in resource consumption that is not reflected in healthcare improvement. The need to introduce

new ways to do the same thing at a lower cost is rational. To address this, we propose a method based on

Design Engineering Methodology for Organizations (DEMO) to find non value-added transactions that

must be redesigned to simplify processes. This methodology was chosen as a basis for our solution because

it provides a better understanding of the dynamics of an organization, and allows a good alignment between

the enterprise design and operation. A demonstration was accomplished within an Emergency Medical

Service and a Pharmacy, making it possible to find transactions that can be improved or automated.

Evaluation was carried out by means of interviews, the Four Principles from Österle et al., and the Moody

and Shanks Quality Framework. Results prove that the method yields an adequate and clear process view

and is reliable when it comes to improving healthcare operational processes.

1 INTRODUCTION

In a world of growing business dynamics, high rates

of technological advances and organizational

changes, organizations need to be effectively and

continuously redesigned and reengineered in order

to achieve strategic and operational success. The

inefficiency of processes and the lack of innovation

are the main reasons for strategic failures, entailing

serious consequences for business (Kotter, 1996)

(Henriques, Tribolet and Hoogervorst, 2010).

These strong external forces and the need for

innovation also challenge the healthcare system. Its

organizations need to improve treatments, eliminate

non value-added activities, reduce waiting time and

expenses, treat more patients, and implement new

technological services. Besides these challenges, the

healthcare system suffers from problems of

operational management, and its processes are

considered inefficient (Christensen, Grossman and

Hwang, 2009) (Kaplan and Porter, 2011).

A frightening factor is that not only its

expenditure accounts for 10% of the Gross Domestic

Product (GDP) in developed countries, but there is

also an increasing trend, as depicted in Figure 1.

Other than that, there is data indicating that cost and

quality are not correlated, and showing inefficiency

in resource consumption, which is not reflected in

improved quality of care. Consequently, the quality

of life may be affected because of a knock-on effect

on the economy, increase in tax rates and insurance

contributions, disinvestment in other public services,

and increased difficulties to afford healthcare

services (Kaplan and Porter, 2011) (Walshe and

Smith, 2010). Hence, this research stems from the

assumption that many healthcare processes have

become inefficient and unsustainable, which affects

the management of the healthcare system.

Figure 1: Global evolution of healthcare expenditure –

adapted from OECD Website (OECD, 2012).

Although the problem is identified as a need for

redesign and reengineering, some authors argue that

there is no strong and reliable method to solve this

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Dias D., Mendes C. and Mira da Silva M..

Using Enterprise Ontology for Improving the National Health System - Demonstrated in the Case of a Pharmacy and an Emergency Department.

DOI: 10.5220/0004133004410451

In Proceedings of the International Conference on Knowledge Engineering and Ontology Development (SSEO-2012), pages 441-451

ISBN: 978-989-8565-30-3

 2012 SCITEPRESS (Science and Technology Publications, Lda.)

problem (Dietz and Hoogervorst, 2008). It is

estimated that over 70% of strategic initiatives such

as Total Quality Management, Business Process

Reengineering, and Six Sigma, among others, tend

to fail (Mintzberg, 1994) (Lifvergren and et al.,

2010). In this context, we addressed three main

reasons for this: 1) The lack of integration among

the various enterprise elements at the design level;

2) The inability to deal with the enterprise dynamics

at the operational level due to weak enterprise

construction models; and 3) The need to change

management that advocates the development of self-

awareness within the organization (Dias, Lapão and

Silva, 2012) (Dias et al., 2012) (Henriques, Tribolet

and Hoogervorst, 2010).

Following this, our research proposes an

approach based on the theories of Enterprise

Ontology (EO) and the corresponding methodology

– Design and Engineering Methodology for

Organizations (DEMO). We chose this approach as

a foundation for our proposal, because it is

considered to provide a better understanding of an

organization’s dynamics, has a strong and well-

formed theory, allows a good alignment between the

enterprise design and operation, and it also enables a

unified reengineering strategy (Dietz, 2006)

(Reijswoud, Mulder and Dietz, 1999). Therefore, we

enunciate the research problem as: Using EO to

propose improvements in the healthcare system.

This research was conducted by using the Design

Science Research Methodology (DSRM) that aims

at creating and evaluating artifacts to solve relevant

organizational problems (Henver and et al., 2004).

The obtained artifact is a method that provides

guidance on how to find improvements through a set

of steps. In order to demonstrate the proposal, we are

applying it within medical organizations, such as an

Emergency Department (ED) and a Pharmacy.

Besides the possible improvements in each

organization, we are also interested in analyzing the

interactions between these two so that we can

conclude how they can improve cooperation.

To evaluate the proposed artifact we used: 1)

The framework proposed in (Pries-Heje, Baskerville

and Venable, 2004), 2) Demonstrations of the utility

of the method; 3) Interviews with practitioners; 3)

The Four Principles from (Österle et al., 2011) to

evaluate the artifact; and 4) The Moody and Shanks

Quality Management Framework (Moody and

Shanks, 2003) to evaluate the produced models.

The steps from the DSRM are reflected upon in

the sections of this paper, which is structured as

follows. In Section 1 we just introduced our problem

and motivation. Then, a brief overview of the

literature is provided (Section 2). Afterwards, we

identify the objectives of the solution and describe

the proposal to redesign the healthcare processes

(Section 3). Next we present case studies where the

proposal was applied as demonstration (Section 4).

In Section 5, we describe the evaluation strategy and

discuss the results of applying the proposal. Finally,

we draw some conclusions in Section 6.

2 RELATED WORK

This section gives a brief overview of the Quality

Management (QM) and EO Sections 2.1 and 2.2.

2.1 Quality Management

Edwards Deming, one of the main and originator

sources in QM, defended that organizations could

increase quality and reduce costs by adopting

appropriate principles of management. He identified

seven constructs as main drivers: visionary

leadership, internal and external cooperation,

learning, process management, continuous

improvement, employee fulfillment, and customer

satisfaction (Rungtusanatham et al., 1998). Hence,

authors defend that these topics are considered

crucial not only to compete and prosper, but also to

merely survive against external forces (Kotter,

1996). In response to the need of QM and

continuous improvement, different methodologies

and strategies appeared, such as Organization

Design and Engineering methodologies, Lean, Six

Sigma, Total Quality Management, among others

(Mintzberg, 1994) (Lifvergren and et al., 2010).

Lean is considered one of the most used in the

management of the healthcare system (Burgess and

Radnor, 2010). It is typically grounded in the PDCA

Operating Framework, and focus on the waste

removal to deliver an improved flow time. The

PDCA cycle suggests that all work should be

measured and performed to standards, and it is

composed by the following steps: 1) Plan: recognize

an opportunity and plan a change, its needed steps,

and results’ prediction; 2) Do: test the change using

small-scale studies as trials under controlled

conditions; 3) Check or study: changes are tested in

small-scale studies to examine its results, and if

process improvements were verified, it should be

considered the implementation on a broader scale; 4)

Act: implement the changes in a broader scale and

then repeat the cycle again with a differ plan

(Womack and Jones, 2003).

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Some of the benefits of the QM and particularly

Lean in the healthcare management are the reduction

of processing and waiting time, decline in the

mortality rate, increase in quality through a

reduction of errors, decrease in the service costs and

resource expenditure, better warehouse

management, and increased employee motivation

and customer satisfaction (Fillingham, 2007)

(García-Porres, J; et al., 2008) (Radnor, 2010). On

the other hand, some authors point out some

drawbacks, such as the high rate of failed

implementations, the mischaracterization or

degradation of services, and the loss of

organization’s essence (Burgess and Radnor, 2010).

The Improvement Quantification is considered

another topic related with the QM, which helps to

make decisions and prioritize improvements based

on the expected return and feasibility. There are

different approaches that may help a manager to

make informed and just-in-time decisions about

improvements. For example, costing models that

may help to identify the cost from each activity,

allowing for a greater knowledge about its indirect

and variable costs (Kaplan and Porter, 2011).

2.2 Enterprise Ontology

Enterprise Ontology (EO) is a theory that has its

roots in the PSI-Theory (Performance in Social

Interaction), and is perceived as a model for

describing and understanding the enterprise

construction and operation at the level of human

interactions, allowing a better understanding of the

operation. Dietz brings a complementary view of the

EO, in which ontology is viewed as the “highest

level” conceptual model, fully independent of how

the enterprise is implemented. It is an enterprise

context based concept that is considered the highest

conceptual model and helps ensure integrated

enterprise. It also guides the transition from

ontological models to construction models, which

means that it assists in engineering activities (Dietz,

2006) (Henriques, Tribolet and Hoogervorst, 2010).

Unlike other methodologies, EO is considered to

provide a deep understanding of the dynamics of an

organization with a strong and well-formed theory

that allows a good alignment between the enterprise

design and the enterprise operation (Henriques,

Tribolet and Hoogervorst, 2010).

Its particular methodology, DEMO, provides a

structured working approach for modeling,

(re)designing and (re)engineering of organizations

by layering it into three parts, and focusing only on

the one that refers directly to the complete

knowledge of the enterprise – the Ontological or

Essential Layer, which is considered to affect the

other two layers (Informational and Documental), as

illustrated in Figure 2. Focusing only on the essence

conducts to a reduction in the complexity of the

obtained diagrams, considered in over 90%

(Reijswoud, Mulder and Dietz, 1999) (Dietz and

Hoogervorst, 2008).

Figure 2: The layered integration of an enterprise and its

transformation activities (Reijswoud et al., 1999).

Regarding DEMO methodology, it consists of

four interrelated aspect models, represented by

particular diagrams, lists and tables, as illustrated in

Figure 3. The Construction Model (CM) details the

identified transactions types and associated actor

roles, as well as the information links between the

actor roles and the information banks. The Process

Model (PM) specifies the state and transaction

spaces, and it is partially based on the information

defined on the CM concerning which actor roles

perform the coordination acts. In addition, PM also

contains the causal and conditional relationships

between transactions, which determine the possible

trajectories between transactions. The State Model

(SM) specifies the information banks and the state

space of the production world: the object classes, the

fact types, and the result types, as well as the

existential laws that hold. The Action Model (AM)

specifies the action rules that serve as guidelines for

the actors in dealing with every coordination step,

which are grouped according to the distinguished

actor roles. The bottom layers from the ontological

triangle integrate concepts defined in the upper

aspect models, as depicted in Figure 3. For further

reading about the EO, DEMO methodology, and the

four axioms significant to understand the

methodology we refer (Dietz, 2006).

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EmergencyDepartment

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Figure 3: The ontological triangle with aspect models and

diagrams of DEMO (Dietz, 2006).

There are some examples in the healthcare

system in which EO was applied to study its internal

transactions and simplify their analysis. These

contributions validated that EO avoids the lack of

integration among the various enterprise elements at

the design level and produces strong enterprise

construction models (Maij and et al., 2000) (Habing

and et al., 2001) (Maij and et al., 2002). In addition,

we can find examples of using EO to improve

operational processes (Reijswoud, Mulder and Dietz,

1999) due to its differentiated and structured

working approach focused on the essential design of

the organization.

3 PROPOSAL

This section corresponds to the definition of the

objectives for the solution and the design and

development steps of DSRM.

3.1 Objectives of the Solution

In order to overcome the problem statement about

the inefficiency and unsustainability of the

healthcare system, different approaches are

identified. Nevertheless, some authors still argue

that there is not a reliable method to solve these

problems. It is estimated that over 70% of strategic

initiatives such as Total Quality Management,

business process reengineering (BPR), and Six

Sigma, among others, tend to fail (Mintzberg, 1994)

(Dietz and Hoogervorst, 2008) (Lifvergren and et

al., 2010). Furthermore, Dietz also adds that the

current literature on enterprise engineering consists

merely of best practices, without an integrating

theory and a clear definition of the field (Dietz,

2006). Inline with that conclusion, Caetano et al.

demonstrated that when comparing BPMN and

DEMO models, there was a set of implicit and

missing actions in BPMN, proving that it does not

provide means to assess the actual consistency and

completeness of a business process, due to the lack

of formal semantics and unclear construct

description (Caetano, Assis and Tribolet, 2011).

Following this, our research seeks to define an

artifact method based on the theories of EO because

of the strengths described previously, namely the

benefits previously described, the properties of

correctness and completeness it assures in its

models, and the properties of essentialness and

conciseness, which help to construct and analyze

(more) models, making it possible to design the

healthcare system and seek for inter-organizational

cooperation improvements between its units. The

improved alignment between the enterprise design

and operation leads to an improved self-awareness

within healthcare organizations. In addition, EO

clearly defines three notions that we considered

relevant in governing the enterprise dynamics and to

identify improvements in the healthcare system:

competence, authority, and responsibility, as

explained in the Operation Axiom (Dietz, 2006).

Most of these notions are absent or not clear defined

in other enterprise modeling techniques (Dietz,

2006) (Henriques, Tribolet and Hoogervorst, 2010).

To take advantage from some already proven

benefits from Lean for the QM and Continuous

Improvement, particularly in the healthcare system,

we intend to combine the analysis from EO with the

improvement identification from Lean. This way,

the EO may be considered as input for the Plan step

of the PDCA Operating Framework, to help with the

identification of opportunities. In other words, from

DEMO models one may identify improvements (as

suggested in the Plan step), and in the end produce

and Organization Redesign model that reflects the

change plan. To identify improvements one should

consider the existing standards on Healthcare

Management, BPR, and improvement quantification.

The following steps from PDCA cycle are out of the

thesis’ scope, as they need the creation of prototypes

and implementation in a broader scale.

In short, our main objective is to propose a

method based on EO to find non value-added

transactions, and redesign them to improve the

healthcare management. Other goals are to

demonstrate, evaluate and communicate the artifact,

to show its efficiency and efficacy. To do that are

applying the proposal to different units of the

healthcare system. Besides the possible

improvements in each healthcare unit, we are also

interested in analyzing the interactions between

them so that we can conclude how they can improve

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cooperation, as part of the demonstration.

3.2 Proposed Artifact Method

This section belongs to the design and development

step of DSRM, in which we present a different

artifact (Österle et al., 2011) to identify innovations

to improve the healthcare management. It considers

the contributions from EO (Dietz, 2006), some

additional steps from Lean (García-Porres, J; et al.,

2008).

The proposal starts with the Modeling Phase,

which uses EO to study the organization and its

processes. To construct its diagrams, it consists of a

defined sequence of steps (illustrated in Figure 4)

that begins with a textual or process representation

of an organization, and ends with an aspect model.

The sequence of steps is described in previous

publications (Mendes, Ferreira and Silva, 2012).

As result, this phase provides a structured

working approach by layering the organization into

three parts, and focusing only on the one that

directly refers to the complete knowledge of the

organization and independent of the implementation

– the Ontological Layer. In this research we focus

on the Construction and Process Models, which

include the Actor Transaction Diagram (ATD) and

Process Structure Diagram (PSD).

The proposal continues with the Innovation

Phase, which is based on four additional steps from

Lean to assist in the Continuous Improvement and

the QM process. These steps consist on the Plan step

of the Lean PDCA Operating Framework that

recognizes an opportunity and plans the change.

Therefore, this phase identifies possible

improvements from the previous models, prioritizes

them in terms of impact and feasibility, and then

proposes redesigned models for the organization. As

result, this phase gives the appropriate tackle to

handle the transformation process, and helps to

choose the most profitable improvements first.

Figure 4 illustrates the proposal including its inputs

and outputs, and subsequently we describe its steps.

The first step from the Innovation Phase is the

Process Improvement Identification, which identifies

improvements from the organization models

obtained in the Modeling Phase, considering the

contributions and standards from the related work.

Considering the ATD, one can identify transactions

that do not seem essential and may be removed,

changed, or automated. These transactions may be

identified with the help of practitioners or literature.

Then, using the PSD, one can change the network of

communicative commitments to shorten processes,

change precedencies, or move conditional

relationships, which leads to shorten cycle (and

waiting) times. This step is based on (Reijswoud,

Mulder and Dietz, 1999) (Dietz and Hoogervorst,

2008).

Afterwards, the improvements are quantified

using some metrics that must be established in terms

of feasibility and impact. Some common metrics are

the time invested in each transaction compared to

the total time spent on the whole service, people

involved, management frameworks, associated

defect, or other analytical methods (e.g. costing

models, financial analysis, etc.). The chosen theory

or method is not part of this thesis’ scope (one can

choose the most suitable).

Then, the improvements are prioritized in terms

of impact and feasibility, which helps to choose the

most profitable improvements for the available

resources. This is then represented in a map divided

Figure 4: Graphical representation of the proposed method.

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into four quadrants, being the X-axis the feasibility

to accomplish it, and the Y-axis the quantified

impact. Each improvement is placed in a particular

quadrant, being the ones that fit into the superior

diagonal the ones that are more important to

implement (with higher impact and feasibility).

After choosing the most profitable

improvements, the organization is redesigned to

include the decisions. Alternatively, one can deepen

some analysis by including more information in the

Enterprise Description, or producing other aspect

models from DEMO. Having the redesigned

organization models with the results from the

Innovation Phase, it should be prepared a proposal

with specific implementation strategies (i.e. the plan

with the needed steps). Afterwards, one should

continue with the next steps from the PDCA cycle

(Do, Check and Act) to implement the planned

changes, beyond this thesis’ scope.

To sum up, this method replaces the analysis

from Lean by a Modeling Phase based on EO,

incorporating its contributions to achieve models

considered formally correct, easier to analyze, and

enabling a unified reengineering strategy (Dietz,

2006).

4 DEMONSTRATION

This section corresponds to the demonstration step

of DSRM. In the following sections we apply the

proposed method to an ED and to a Pharmacy. We

do not fully apply the six steps of the modeling

phase due to space limitation. Nevertheless, these

steps are demonstrated in previous publications

(Mendes, Ferreira and Silva, 2011) (Mendes,

Ferreira and Silva, 2012).

In this demonstration we will focus more on the

demonstration at the Pharmacy and its possible

improvements to increase cooperation with the ED.

4.1 Emergency Department

To demonstrate the method, we applied it to the

internal operation of an ED in a hospital near Lisbon

with more than 100,000 admissions per year,

expecting that by eliminating wasteful transactions,

it would be possible to improve processes without

compromising the organization. To conduct the

demonstration, we interviewed 5 patients and 10

practitioners (the ED director, physicians and nurses,

and health services researchers), namely to obtain

the enterprise description.

From the enterprise description and after the first

two analyses from the proposed method, we defined

the transactions by clustering the identified acts and

facts in what is denominated by Transaction Pattern

Synthesis. The results are presented below in the

ATD (Figure 5), according to the Transaction

Axiom from EO (Dietz, 2006).

In the ATD, a transaction is represented using a

diamond in a disk. Each transaction is connected to

two boxes, representing the initiator and executor

actor roles. The initiator is connected to the

transaction symbol using a solid line, while the

executor is connected to the transaction using a solid

line ending in a black square. The grey boxes refer

to composite actor roles, i.e. elements whose exact

structure is not known. All the environmental

elements, i.e. elements outside the organization that

we are studying, are represented with grey boxes for

Figure 5: Actor Transaction Diagram (ATD) of the Emergency Department.

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Table 1: Improvements identification in the ED with its corresponding impact and feasibility (from 1 to 5).

that reason. This also means that we can represent

the studied organization with a grey box when

referring to the kernel of the organization, which can

be further specified by using elementary actor roles

represented by white boxes.

As depicted in this model, new patients are

registered to the hospital (T1); then they go through

a triage process (T2); after that, patients’ problems

are handled (T3); and finally, they are discharged

(T11). These four transactions are initiated by an

external actor, the patient. They are respectively

requested to the registrar, triage handler, patient

problem handler, and patient discharger that

execute them.

The handling of the patients’ problems may lead

to the following actions: performing some urgent

internal examinations (T5); performing medical

interventions (T7); performing supplementary

examinations (T9); and consulting another external

specialty (T10). Since these tasks have different

responsibilities, four different actors are discerned:

examiner, intervention performer, external

examiner, and external service or specialist. The

first two are internal actors, used for urgent

examinations and interventions (i.e. specific

interventions may need specialists, such as a surgery

or a psychiatry episode). The last two are used for

non-urgent situations, such as some extended

interventions or supplementary examinations. In

addition, there are two transactions concerning the

delivery of means (T6 and T8), a transaction

concerning the patients’ permission (T4), and finally

the payment transaction (T12).

In the Innovation Phase, one must identify

process improvements from the obtained diagrams.

First, after some analysis from the ATD, one may

conclude that transaction T1 can be removed

(improvement A from Table 1), since the patient can

possible to automate T1 through a computer terminal

with a standardized electronic form (improvement

B). In fact, the secretary performs non-value added

tasks, and consequently this actor could be allocated

to other activities.

With the PSD (obtained from the ATD), one can

conclude that it is not efficient having to go through

several iterations and actors to be forwarded to

another external service (specialist or examiner in

T10). For example, instead of being forwarded

immediately after triage, patients need to be

admitted (T1), triaged (T2), and seen by a physician

(T3) to be finally forwarded to another specialty

outside the ED. This leads to unnecessary

consumption of resources, higher waste of time, and

the patient leaves without being treated in the ED.

There is some related work suggesting strategies of

Fast-Tracking (improvement C) and Provided

Directed Queuing (improvement D) to anticipate the

resolution of some patients’ problems. These

strategies are claimed to improve waiting time,

customer satisfaction, length of stay, and resource

expenditure (Medeiros and et al., 2008).

In Table 1 we quantify the improvements in

which we want to work at. To infer the level of

impact, we consider that the elimination of a

transaction has a higher impact than a precedence

change. Avoiding a transaction conducts to the same

classification as its elimination or automation.

Avoiding an actor has even higher impact, because it

eliminates the transaction and reduces the costs with

human and physical resources. Finally, to assess the

feasibility we considered that more changes to the

service leads to lower feasibility (i.e. hardware,

software or people involved). The presented values

were obtained with the help of the interviewed

practitioners for this demonstration purpose.

Figure 6: Priority Map of the Emergency Department.

# Im

rovement Im

act Feasibilit

act descri

tion Feasibilit

descri

tion

Patient registers in

the triage

4 2

Avoid transaction T1 and

transfer responsibility to A2

Triage should be fast

Automation in the

5 4

Avoid transaction T1 and

actor A1

Computer terminal requires

new hardware and software

Provided Directed

Queuing

5 5

May eliminate transaction

executions and reduce flow

Reallocate only one

physician

D Fast-Track System 4 4

May eliminate transaction

executions and reduce flow

Reallocate physician and a

new space

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The priority map (Figure 6) addresses the impact

and feasibility levels from the last step: D shows

large impact and feasibility, followed by B and C.

We could apply a more formal method for the

improvement quantification, but this would not

change the method itself.

4.2 Pharmacy

Similarly to the previous experiment, we

interviewed 6 practitioners (the pharmacy director,

pharmacists, technicians, and some researchers), to

obtain the enterprise description and validate the

obtained results. These interviews included 50% of

the practitioners from the studied pharmacy, and 2

external and independent practitioners.

In Figure 7 we present the ATD. As depicted in

this mode, patients may choose to create a profile in

the pharmacy (T1), fill a prescription for a medicine

(T2), get advice about medication or health-related

issues (T7), and attend to a consultation with a

specialist (T8). These transactions are initiated by an

external actor, the patient. They are respectively

requested to the registrar and the patient handler

(composite actor role) that execute them.

The handling of patients may in turn lead to the

following transactions: performing examinations

that can go from a simple diagnostic to laboratory

analysis (T3), checking medicine interactions (T4),

dispensing or preparing medicines (T5) and

processing the claim to check for reimbursements

(T6). Since these actions have different

responsibilities, four different actors roles are

discerned: examiner, verifier, dispenser, and

insurance company (external actor role). After

handling patients, they have to pay for the medicines

or the provided services (T9).

In addition, there are transactions concerning the

pharmacy management (T10), the inventory control

(T11), the medicine supply (T12), and their payment

(T13). Three action roles are discerned: pharmacy

manager, inventory controller, and supplier. Finally,

it is possible to schedule some kinds of medical

appointments in the pharmacy with paramedics or

other healthcare professionals. This corresponds to

the transaction T8 executed by the patient handler.

In the Innovation Phase we identified four main

improvements. First, the transaction T11 can be

automated (improvement A from Table 2), since the

inventory control process requires more human

intervention, but does not consider demand

forecasting due to the lack of decision support

systems. In addition, there is a need to verify the

arrival of products manually to check their prices,

Figure 7: Actor Transaction Diagram (ATD) of the

Pharmacy.

quantities and expiration dates.

The second main improvement (improvement B)

is the automation of transaction T5 to use a robot

instead of a human to dispense or prepare medicines.

Despite being a well-known and documented

improvement, our analysis revealed that this was a

bottleneck with great impact in the number of

employees and service time. Without a robot, a

pharmacy needs more employees available and there

is a higher waiting-time to get medicine. They also

help in the storage of the ordered medicines, and

help identifying drugs that are almost expiring

(without any human intervention), which reduces the

waste of products.

The third improvement (improvement C) is the

overlapping of responsibilities between hospitals and

pharmacies in T2, T3 and T8. In spite of

pharmacists’ skills, patients need to seek a physician

or a hospital to have a prescription, even for

recurring or vulgar situations, such as an antibiotic.

In addition, there are other legal restrictions

hampering the existence of medical consultations or

specialties in the pharmacies. This overlapping and

the need to resort to hospitals are considered to

increase the cost of the national healthcare system

(Walshe et al., 2010).

The last improvement (improvement D) is the

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Table 2: Improvements identification with its corresponding impact and feasibility (from 1 to 5).

elimination of the transaction T1, since there should

be a unified Patient Healthcare Record for all

healthcare organizations, to avoid duplication of

information, improve access to information, and

avoid wasting time creating profiles in different

healthcare organizations (Dias et al., 2012).

In Table 2 we quantify the improvements in

which we want to work. To infer the level of impact,

we consider the same assumptions described in

Section 4.1. The priority map (Figure 8) shows that

improvements C and D have a larger impact and

feasibility, followed by B and A. Again we could

apply a formal method for the quantification, but this

would not change the method itself.

Figure 8: Priority Map of the Pharmacy.

To sum up, we may conclude that there is room

for improvements in the ED and the Pharmacy.

Analyzing those results together we also may find

that it is possible to improve their cooperation since

we find some overlapped transactions (Table 3).

Table 3: Overlapped transactions between ED and

Pharmacy.

ED Transactions Pharmacy Transactions

T1 – Register Patient T1 – Creating Profile

T3 – Handling Patient T2 – Filling prescription

T3 – Handling Patient T9 – Medical Consultation

T5 – Performing Examin. T3 – Performing Examin.

T6, T8, T12 – Management

and stock supply transactions

T10 to T12 – Management

and stock supply

transactions

From the previous table we may find that both

organizations would benefit from having a unified

Patient Healthcare Record to avoid the creation of

new registers. In both organizations their

professionals have studies and skills to prescribe

medications, but only physicians may do it due to

legal reasons in Portugal, and both organizations

share some exams and medical specialties.

5 EVALUATION

This section corresponds to the evaluation step of

DSRM.

To evaluate the proposal, we used the framework

proposed in (Pries-Heje, Baskerville and Venable,

2004), which aims to help researchers to build

strategies for evaluating the outcome of a DSRM.

This framework identifies what is actually

evaluated, when the evaluation takes place, and

how it is evaluated. To answer the third question,

we based on different authors to propose a strategy

with steps outlined to evaluate a DSRM artifact

method. The evaluation strategy entails the

following steps: 1) Constructing scenarios to

demonstrate the artifact and how to use it to solve

the research question; 2) Feedback through

interviews with practitioners; 3) The Moody and

Shanks Quality Management Framework to

assess the quality of the produced models (Moody

and Shanks, 2003); and 4) The Four Principles

proposed by (Österle et al., 2011) to evaluate a

DSRM artifact.

This evaluation method follows the design

evaluation guideline within DSRM (Henver and et

al., 2004). In this research we have mainly used the

descriptive evaluation method to assess the artifact,

which uses relevant research to build a convincing

argument for the artifact’s utility, and constructs

detailed scenarios around the artifact to demonstrate

the utility. Nevertheless, the observational and

analytical methods could also be used, but this

would involve introducing observable metrics,

conducting socio-technical experiments, and

selecting modeling tasks that would allow such

measurement (Henver et al., 2004; Caetano, 2008).

Such evaluation is beyond the scope of this research.

# Im

rovement Im

act Feasibilit

act descri

tion Feasibilit

descri

tion

Automation in the

inventory control

3 4

Reduce waste of time, avoid

errors in inventory control

Improve Supply Chain

Management software

Automation in medicine

preparation or dispense

4 3

Avoid human intervention,

reduce waste of time

New hardware (robot)

and software

Avoid overlapping of

responsibilities

5 4

Avoid duplication/overlap of

transactions, reduce spending

Need to change rules,

change resistance

Eliminate profile creation

(unified patient records)

5 4

May eliminate transactions

and reduce flow

Change legal restrictions,

change resistance

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EmergencyDepartment

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The framework proposed in (Pries-Heje et al.,

2004) was formulated as follows:

 What was actually evaluated? The

evaluated artifact was the method described

in Section 3, which is a DSRM artifact

method. This evaluation represents an

artifact design process, since it is defined as

a set of activities, methods and practices that

can be used to guide a procedure workflow to

improve the healthcare management;

 When was it evaluated? It was evaluated

after the artifact construction, and after the

demonstration. Therefore, the evaluation

strategy is ex post, since it was performed

after the design artifact development;

 How is it evaluated? To evaluate the artifact

and its results we used the described strategy,

which are applied below. This represents a

naturalistic evaluation since it is conducted

using a real artifact in a real organization

facing real problems as a case of study.

The demonstration reveled that: A) The

proposal is generic enough to be applied in different

healthcare organizations; B) It is a formal method,

with a list of specific steps to follow; C) From a

given enterprise description anyone can achieve

similar enterprise models, as Dietz suggests (Dietz,

2006); D) From the obtained models it is possible to

find non value-added transactions and from them

suggest and prioritize improvements; and F) It is

possible to obtain a redesigned organization. In other

words, it was possible to demonstrate the artifact’s

utility, and how to use it to solve the research

problem.

The feedback from the interviews (using the

same practitioners referred to in the Demonstration)

was rather positive because: 1) They validated the

importance of the research problem and the

motivations behind the proposal; 2) They understood

and agreed with the obtained models (after

explaining them), which were considered to properly

depict the studied organizations; 3) Improvements

were discussed and the interviewees agreed that the

ones we identified were sometimes similar to those

suggested by them; 4) Practitioners concluded that

the proposal could be applied effectively and

efficiently to solve the research problem, regardless

of whom applies it. Overall, practitioners showed a

good acceptance and enthusiasm for this innovative

approach.

From the Moody and Shanks Quality

Framework, almost all quality factors were

accomplished. Only understandability was partially,

and implementability was not. The first factor as

practitioners find models difficult to interpret

needing an adaptation period. The second one as

models are implementation independent (describing

only the essence of organizations).

The Four Principles from (Österle et al., 2011)

were also accomplished. 1) Abstraction: the artifact

can be applied to any healthcare service from a

given enterprise description; 2) Originality: the

proposed artifact is not present in the body of

knowledge of the domain since it was designed by

relating different subjects, such as healthcare

management, BPR, EO and Lean; 3) Justification:

the artifact is supported by the related work,

described by textual and graphical representations,

and it was justified and validated in different ways;

4) Benefit: the artifact provides a structured working

approach for reengineering, it leads to differentiated

and well-grounded improvements, and provides a

better understanding of the dynamics of an

organization, among other benefits when compared

to existing methodologies.

6 CONCLUSIONS

Considering this research’s objectives and

evaluation, we may conclude that the expectations

were largely achieved since it was possible to: a)

Formulate the method; b) Demonstrate its use in two

real case studies; c) Find non value-added

transactions when applying it; d) Suggest redesign

improvements; and e) Get validation and positive

feedback from practitioners about the method and its

results.

We may also conclude that it is possible to easily

identify redesign innovations to solve overlapping

issues in organizations, since DEMO is regarded as a

methodology that produces models considered

concise and essential, which help to construct and

analyze more models in a shorter period of time. In

addition, because the designs are also considered

coherent, comprehensive and consistent, this gives

strength to the obtained models, as described in

(Dietz, 2006).

To conclude, it is expected that healthcare

organizations may use some of the described

advantages of the proposal to solve the problems of

inefficiency and unsustainability in the healthcare

system. Furthermore, it can also be a contribution

towards helping the healthcare professionals to

validate processes and improve their way of

working, even if the proposed artifact is used

together with other existent methods.

To sum up, we may answer to the raised problem

and objective statements that: 1) It is possible to use

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450

the EO to propose improvements in the National

Health System; and 2) It is possible to create a

DEMO based method to find non value-added

transactions that could be redesigned.

To complete the cycle of the DSRM, the

communication step is being achieved through

scientific publications and their presentation, aimed

at the practitioners and researchers within the

science area.

As future work, further research is being

performed to better quantify the impact and

feasibility of the proposed improvements during the

demonstration, namely by including costing models

to the obtained DEMO diagrams. Furthermore, the

proposal should be expanded to consider the

remaining application of Lean PDCA cycle and

other EO models, such as Action and Interstiction

Models, which can be useful in the redesign of

information systems (inline with previous researches

(Reijswoud et al., 1999)).

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EmergencyDepartment

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