Making the Case for Business Process Re-engineering in

Health Informatics

Focusing on MDRTB in South Africa

Harsha Desai

and Rosemary Quilling

Discipline of Telemedicine, Nelson Mandela Medical School, University of KwaZulu-Natal, KwaZulu-Natal, South Africa

Discipline of Information Systems & Technology, University of KwaZulu-Natal, KwaZulu-Natal, South Africa

Keywords: Business Process Engineering, MDRTB, Process Analysis.

Abstract: The potential misalignment between new technologies entering healthcare requires attention. This paper will

compare the fit between an Open Source Electronic Medical Record Solution (OpenMRS) and a clinical

guideline that outlines the requirements for the care of a patient. Design/methodology: A process analysis

technique is used to construct and analyse the fit between the processes as stipulated by the South African

clinical guidelines for Tuberculosis (TB) and that of the OpenMRS. This technique has been used to identify

inefficiencies and opportunities. Lean principles are applied in the analysis to identify waste in the process.

Findings: Process analysis has provided valuable insight into the working of both the system and the

provision of this healthcare service. The OpenMRS solution has a good fit to the South African healthcare

context with some minor gaps between the system processes and that of the clinical guidelines. In addition,

wasteful tasks have been flagged within the clinical guideline processes which appear to be due to limited

consideration being paid to the patient's end-to-end care process.

1 INTRODUCTION

The Internet revolution has resulted in exciting new

information systems with the potential to improve

healthcare (Haux, 2006). The challenge of an aging

population and an increase of chronic illnesses like

diabetes and heart disease have placed demands on

healthcare service to deliver radical change. In

addition, disease burdens such as HIV/AIDS have

forced the health care industry to rethink their

service offering. This study uses as its context the

healthcare approach to Multi-Drug Resistant

Tuberculosis (MDRTB) because a high rate of co-

infection of Tuberculosis and HIV/AIDS has been

noted in the last decade, in South Africa. There has

also been an extensive drive to curb the incidence of

both these communicable diseases during the same

period (WHO, 2009). Unlike HIV/AIDS, TB or

MDRTB is a curable disease given the correct

medication and adherence to treatment guidelines by

both the patient and the healthcare workers. The

potential to improve diagnosis and treatment of

MDRTB as a result of employing a process

engineering intervention could have a meaningful

impact.

There is a critical collaborative relationship

between technology, people and the tasks they

perform (Elske et al., 2006); (Tsiknakis and

Kouroubali, 2009). This relationship has received

limited research attention in the healthcare domain.

This is important because merely implementing a

Health Information Systems (HIS), without

revisiting the business process and its context,

cannot solve challenges and improve inefficiencies

(Berg and Toussaint, 2003); (Ludwicka and

Doucettea, 2009). This study explores the practical

use of process engineering in healthcare services,

thus assessing the process itself and how it can

inform the development of HIS.

2 LITERATURE

The literature survey discusses the research

conducted in Process Management in healthcare,

over the last sixteen years (1994 – 2011). The

discussion focuses on five areas, namely: the

challenges in the implementation and adoption of

HIS, the process management approach, the

144

Desai H. and Quiling R..

Making the Case for Business Process Re-engineering in Health Informatics - Focusing on MDRTB in South Africa.

DOI: 10.5220/0004187801440154

In Proceedings of the International Conference on Health Informatics (HEALTHINF-2013), pages 144-154

ISBN: 978-989-8565-37-2

 2013 SCITEPRESS (Science and Technology Publications, Lda.)



application of process management in healthcare,

MDRTB as a public healthcare crisis and the origins

of OpenMRS.

2.1 Challenge of HIS Implementations

Heeks (2006) has identified 7 gaps between what is

specified in the design of a health information

solution and what is actually delivered in reality.

These gaps, identified as the cause for poor

adoptions and implementation of HIS, are;

Information, Technology, Process, Objectives and

value, Staffing and skills, Management systems and

Structures and other resources (Heeks, 2006).

“Process” is identified as a gap because the solution

often focuses on the data in isolation from the

healthcare delivery process in which the data is

embedded, and associated users,. The importance of

addressing this gap is also stressed by Ludwicka and

Doucette (2009) and Munir and Kay (2005).

2.2 Process Management

As technology has become ubiquitous organisations

have realised that both technology and the

streamlining of their businesses' processes is

required to develop competitive advantage and

improve performance (Trkman, 2010).

Process transformation can be seen to have

occurred in four waves over the last forty years with

each wave inheriting the best aspects of its

predecessor. Wave one, dominated by Total Quality

Management (TQM) focused more on customer

facing processes and little was achieved in back

office improvements (Towers, 2010). In wave two

the focus shifted to Business Process Re-engineering

(BPR) calling for the fundamental rethinking and

redesign of business processes to achieve dramatic

improvements in critical contemporary measures of

performance such as cost, quality, service and speed

(Muthu et al., 1999). The third wave, triggered by

the Lean management technique, saw the focus shift

to customer needs, reduction of waste and value

creation with the focus shifting toward

simultaneously reducing cost and improving revenue

and service (Towers, 2010). The fourth wave (post

2000) embraces a myriad of traditional techniques

with a strong focus on successful customer outcomes

(Towers, 2010).

2.3 Applications of Process

Engineering in Healthcare

Bergman (1994) suggested the introduction of re-

engineering in healthcare and within a decade some

traction in this idea is evident: A study by Anderson

et al. uses the design of processes to determine the

best way to develop HIS to meet user requirements

(Andersson et al., 2003); Berg and Touisant(2003)

realised the mapping of processes allowed the

“fluid” nature of medical knowledge to be easily

expressed; and Lenz and Khun (2004) aim to align

HIS and healthcare processes, by defining a layered

approach that allows for quick deployments using an

integrated “generator tool”, used extensively at the

university hospital at Marburg Germany. A similar

approach was proposed by researchers in Finland in

an effort to design web services for a generic HIS

using a service orientated architecture approach

(Mykka¨nen et al., 2007).

In a systematic review of evidence based re-

engineering in healthcare 87 articles from 1989 to

2003 were analysed (Elkhuizen et al., 2006). They

identify two main weaknesses in this research field:

Firstly, there are few studies focusing on negative

results of process management and, secondly, a large

number of health improvement projects are being

performed by private companies who do not have a

vested interest in publishing this work(Elkhuizen et

al., 2006). However, this is beginning to change as

private companies are publishing results of the

process re-engineering work they have done

(Hartung and Biglin, 2010).

TQM is seen as inadequate to address the

challenges experienced due to the inherent

complexity of healthcare (Patwardhan and

Patwardhan, 2008). On the other hand, process

engineering is being seen as an appropriate

technique as it provides an understanding of the

impact and influence of the process on people and

technology (Lenz and Kuhn, 2004, Elkhuizen et al.,

2006, Boston-Fleischhauer, 2008b, Patwardhan and

Patwardhan, 2008, Trkman, 2010).

Little research is available for healthcare process

management both in SA and other developing

countries. Vine (2007) suggests the South African

health care processes are “fundamentally broken”

(Gerntholtz et al., 2007) and thus research in this

area is much needed. SA’s boldest attempt to

implement an EMR solution across all government

hospitals in Limpopo, failed in 1998. Healthcare

workers were inadequately prepared and a lack of

attention to the intent of processes and their unique

application in South Africa appear to have played a

role in this failure (Littlejohns et al., 2003).

However, by first improving the process before

automating it , led to a successful Electronic Medical

Record implementation in the renal department of

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Chris Hani Baragwanath Hospital (May 2005)

(Gerntholtz et al.,2007). Thus process re-engineering

does seem to suggest one possible way forward.

2.4 Patient Centred Process

Management

It is however necessary to consider where the focus

of such process reengineering needs to be placed.

There are two “user” groups who will benefit from a

HIS; the staff of the medical facility and the patients.

As the patient is in fact the “customer” in these

systems, the focus on patient centred care is

becoming a trend in the healthcare industry

(Tsiknakis and Kouroubali, 2009). By understanding

that the patient is the focal point in the healthcare

system, it becomes evident applications of process

engineering should be patient centred (see for

example Francis and Alley (1996) and Pickles et al.

(2008)

2.5 Open MRS Origins

One of the most widely used Open source EMR

solutions in Africa is OpenMRS (Seerbregts et al.,

2009); (Tierney et al., 2010). OpenMRS is designed

using international standards (HL7, DICOM, and

LOINC) for interfacing and development to support

portability and interoperability of the solution and

universal deployment. The OpenMRS MDRTB

module that is being reviewed in this study was

developed to provide an intuitive “front end” to

support the treatment of MDRTB for World Health

Organisation (WHO) sponsored projects (Thomas,

2008). The module can be customised with some

medium to high level computer skills for specific

geographical or treatment requirements (Choi and

Fraser, undated). OpenMRS positions itself as a

means to enable and empower developing countries

to improve the healthcare administration and thereby

the standard of care of patients. To date OpenMRS

has been deployed in Kenya (2001), Tanzania

(2008) Rwanda (2008), South Africa (2006), and

Uganda (2007) (Seebregts et al., 2006); (Frasier et

al., 2008); (Tierneya et al., 2010).

2.6 MDRTB

MDRTB is a strain of tuberculosis where the

bacteria are resistant to two or more of the drugs

used to treat TB, in particular isoniazid and

rifampicin (WHO, 2010). MDRTB has developed as

a result of patients’ poor compliance to their

tuberculosis treatment regimens. There have been

attempts to address the improvement of the

treatment of TB patients with the Direct Observation

Treatment Short-course (DOTS). DOTS aims to

provide a patient centred care framework, whereby

the patient is provided with the necessary support

such as; travel arrangements to the clinic and active

participation of community care workers, to ensure

adherence with the treatment regimen (2009).

In South Africa many patients die before an

MDRTB case is confirmed, as a result of the

turnaround time in conducting these diagnostic

tests(O'Donnell et al., 2009). It is often more

beneficial in suspected cases to begin MDRTB

treatment, while a diagnosis is being conducted.

While MDRTB patients require hospital based

treatment they are often turned away due to the

limited capacity at the hospitals and the high

prevalence rate, this often creates a risk of the

disease spreading more widely in the

community(Seung et al., 2009). In addition there is a

high rate of co-infection of MDRTB and

HIV(WHO, 2010). Once again one of the major

drivers for the escalations of death among HIV

positive patients is the time to confirm the MDRTB

diagnosis of the patient(Seung et al., 2009). Another

concern in treating an MDRTB patient who is co-

infected with HIV is the potential drug interaction

conflict (Cohen and Maarstens, 2004).

In summary: Once the technology becomes

accessible and reliable, the challenge lies in the fit

between the two dimensions of adoption: Firstly, the

task to be performed and the technology being

employed to achieve it and secondly, the user

performing the technology-enabled task and the task

to be performed (Elske et al., 2006). As highlighted

earlier by process transformation waves, greater

attention is being given to the individual who

derives value from the execution of the process.

3 METHODOLOGY

There has been little research on process analysis in

the developing world context (Harrison, 2009). A

qualitative methodology was thus adopted in order

to “raise awareness and increase insight” (Hancock,

2002). The research study is grounded in the FITT

theoretical framework (Elske et al., 2006). This

model explicitly looks at three dimensions and the

relationship between each: (1) User and Technology,

(2) Task and Technology and (3) User and Task.

While the focus of the methodology is on the task

and the technology fit, it aims to do so while also

considering implications for users in terms of their

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fulfilment of tasks and use of technology.

The study was conducted in four phases. This is

illustrated in figure 1. The first phase focused on the

creation of process models based on the SA clinical

guidelines and the OpenMRS MDRTB module

using Business Process Modelling Notation (BPMN)

(White, 2004). The procedures in the guidelines

(2009d) were translated into business processes. The

tutorial from the OpenMRS MDRTB module

(Thomas, 2008) together with an out-of-the-box

installation were used to create process models that

represent how the health information system should

be used to manage the data of patients diagnosed

with and treated for MDRTB.

A business process model visually illustrates the

sequence of tasks completed to achieve the

organisations objective. Each task is detailed in a

rectangular shape starting with a verb to focus on the

action taken. In order to achieve both a big picture

and finer grained view of processes; a process is

sub-divided into sub-processes. Each Sub-process is

then decomposed into a process map. The process

rules are represented by “gateways” (a diamond

shape symbol). The process is contained by a start

point and end point marked by circle shapes at either

end of the process. The starting point indicates the

trigger that sets off the process and the end points

indicates the attainment of the organisation’s

objective. BPMN is a well-used technique for

illustrating process models in a simple and easily

understandable manner. The process goal for each

process is determined based on the understanding of

the objective of the guideline. The process goal is

used to evaluate whether each task in the process is

contributing to the process goal.

During the second phase the analysis of the

process models provided insight into inefficiencies,

and the alignment of the process as prescribed by the

clinical guidelines and the technology solution as

provided by OpenMRS. 

In the third phase of the study, experts were

engaged in a discussion on the analysis derived in

phase 2. These experts were identified by creating a

list of authors from the literature review conducted

and assessing their potential involvement based on

the following criteria: (1) Published research related

to OpenMRS deployment in Africa or South Africa

in the past five years, (2) Member of the OpenMRS

Implementers’ Community for the past three years,

(3) Published research related to TB or MDRTB

from a South African perspective in the past five

years, (4) Currently or previously a clinician, and (5)

availability of an email address.

The participants group consisted of 28 experts;

15 individuals responsible for implementing EMR

solutions and 13 clinicians practicing or researching

in the field of TB and MDRTB. These experts were

consulted to provide judgment on the process

analysis provided using the Delphi technique. An

email was sent to 28 participants (11 Clinician & 16

OpenMRS implementers) identified to participate in

the study, requesting them to participate. The email

explained the objectives of the study and their role in

the study. 7 Participants responded confirming their

participation in the study within a two week period

(4 clinicians and 4 OpenMRS implementers). As the

timelines for data collection had already been agreed

with those who had agreed to participate, it was not

possible to delay the study further in order to attempt

to secure additional participants. Of the original 28

experts approached to participate in the Delphi

study; Only 5 of the 7 participants who responded

within two weeks of the request, provided responses

to the first round of the study. These 5 participants

formed the Delphi group. The participant’s

responses were then collated. The objectives of the

study together with the responses from the first

round were used to create questions for the second

round. The aim of the second round of questions was

to determine the degree of agreement with a

statement or the frequency with which a particular

risk or gap is experienced. The experts’ comment on

the perceived usefulness of the process analysis was

also requested. The feedback from round two was

collated with Excel and analysed. As no new

responses arose in round 2 there was no need to

conduct a third round (Syed et al., 2009).

In the fourth phase, the opinions from the experts

were analysed according to emergent themes. The

emergent themes were used to determine the points

of contention and consensus with regard to the value

of process engineering when using OpenMRS to

manage patient’s medical data. When a content

analysis statements was performed analysing word

concentration to identify themes, there was a poor

result therefore statements were further analysed to

interpret the actual meaning of the statement

(Thorne, 2000). This culminated in a final review

with experts.

4 RESULTS

The results of the study are presented to highlight

three key aspects, namely: First, the insights gained

from the process analysis of two perspectives of the

MDRTB guidelines; second, the synergies relating

to the co-treatment of MDRTB and HIV/AIDS; and

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third, and the value of process re-engineering as an

analytical and design tool.

4.1 Process Analysis Insights

4.1.1 Process Models

The results from the process analysis highlight

various inefficiencies and waste. Some of these

problems are related to the lack of integration of

upstream processes with downstream processes.

Table 1 provides an overview of the key metrics

evaluated in Phase 2 of the study: Break points

referred to an activity with hand-offs between

departments, people, systems and functions. With

the 54 break points that were identified, steps need

to be put in place to ensure that the transition at the

break points are smooth to support optimal flow of

the process. The 2

metric, Business Rules directs

an individual or machine through a different path

depending on the condition that is met. During the

analysis the applicability of the business rules were

questioned and found to be relevant. The Gaps

identified focused on identifying where the out-of-

the-box instance of OpenMRS did not meet specific

requirements in the South African context. This

meant that some customisation will be required. The

Risks identified highlight potential weaknesses in

the process. During phase 3 of the methodology,

when the risks were put to the Delphi Group, these

were identified as “not significant”. Finally the

Waste identified in the process highlighted the

potential opportunities to streamline the process.

4.1.2 Expert Commentary on Process

Models

The Delphi study was conducted over one month (15

November 2011 – 15 December 2011). Using a

questionnaire, participants profiled themselves as

spending their time doing research, implementing

EMR solutions and performing clinical activities.

Four, out of five, participants has experience in

overcoming challenges of diagnosis and treatment of

MDRTB patients and experience in healthcare

quality improvement projects. All three clinicians in

the group have knowledge of the South African

clinical guidelines. Only one participant refrained

from indicating their level of experience with EMR

solutions, two of the participants expressed "some

experience" and another two expressed a "great deal

of experience". With the exception of the one

participant who practices process analysis on a daily

basis, all other participants had limited exposure to

process analysis. One of the clinicians expressed an

interest to learn process analysis.

In support of existing literature all participants

agreed that the alignment of process, technology and

the individual is very important (Elske et al., 2006);

(Ludwicka and Doucettea, 2009); (Tsiknakis and

Kouroubali, 2009). Participants also indicated that

operational efficiency, quality improvement and

innovation in service delivery of healthcare are

poorly explored subjects in healthcare research

(Elkhuizen et al., 2006). They also identified that

these subjects are becoming more relevant as the

burden on the healthcare system grows (Nathanson

et al., 2006); (Singh and Padayatchi, 2007);

(Keshavjee et al., 2008; 2009), (WHO, 2009);

(WHO, 2010). In the literature reviewed it is evident

that much of the in these subjects is concentrated in

the developed world (Boston-Fleischhauer, 2008a);

(Pickles et al., 2008); (Chan and Kaufman, 2010).

In this study participants raised issues potentially

related to developing countries; issues of poor

capacity development and inefficient turn-around

times as gaps and risks, respectively. Participants

refer to poor capacity both in terms of the

infrastructure; such as diagnostic equipment,

integration of specialized technologies, and in terms

of skilled human resources to execute procedures.

Laboratory results that are used for diagnosis are

conducted by a third party in South Africa, creating

a further disconnect. Turn-around times of processes

thus need to be more tightly managed to support the

efficiency of the diagnostic process. As highlighted

by Seung et al. (2009), there are several cases where

a delayed diagnosis results in treatment being

delayed resulting in a patient’s delayed recovery or

even death. All participants agreed with these and

other wastes identified in the process analysis.

Wastes were stated as improvements, gaps or

risk in the second round of the Delphi study and

tested with the participants. In agreement with

existing research, their responses show that two of

the greatest inefficiencies in current non-EMR

settings are the redundant capture of information and

laborious data analysis (Gerntholtz et al., 2007);

(Vine, 2007); (Blaya et al., 2008); (Clifford et al.,

2008).

The benefit of developing a new guideline was

deemed questionable as expert comments

highlighted that all healthcare workers do not follow

the current prescribed guidelines and suggested any

revisions may remain unimplemented. However,

given the various improvements that have been

recommended by participants in this study and those

noted in recent literature (Seung et al., 2009)

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Table 1: Process analysis summary.

Process analytics Total instances of analytics identified

Break Points: An activity with hand-offs between departments, people, systems and functions 54

Business Rules: Determine behaviour. It directs a person or machine with regard to; what to do

and when.

Gap: A particular function or step that the clinical guideline requires but OpenMRS does not

support.

Moment of truth: The interaction between patient and the health care facility 9

Risk: An unforeseen error that could impact the flow of the process from successfully reaching

its objective.

Waste: Activities in the process that result in inefficiencies that can be avoided. 5

(Albert et al., 2010); (Cegielski, 2010); (O’Donnell

et al., 2010); a new guideline could allow for the

incorporation of best practices. Understanding the

gap between the technology and the process is a

critical exercise that must be conducted to ensure

that there are limited work-a-rounds once the HIS

implementation is completed. The gap analysis

indicates there is a high concentration of gaps

between the process and the technology (14).

As noted by a participant, it is important for a

HIS to be customizable, “The reality of the

operational set up is that the care process is highly

fluid”. A participant, who is an international

OpenMRS implementer, highlighted how nine of the

thirteen gaps between task and technology could be

closed by customisations. OpenMRS has been

customised and integrated with other applications

like Chasqui in Peru (Blaya et al., 2007),

FrontlineSMS in Ghana & AMPATH in clinics in

sub-Saharan Africa (Anokwa, 2010); (Kumar et al.,

2010); (Wei-Chih et al., 2010), and integration with

Google maps in Pakistan (Ford, 2009). Thus

illustrating OpenMRS can be customised for

different contexts; including developing countries.

Given the growing use of technologies to support

clinical decision making (Terazzi et al., 1998);

(Andersson et al., 2003); (Marc Mitchell et al.,

2007); (Isern and Moreno, 2008); (Anokwa, 2010),

it was not surprising that participants, particularly

clinicians, made recommendations with regard to the

need to integrate specialised technologies. This is

further supported by the fact that the majority of

participants responded positively to the technology

improvement in OpenMRS regarding clinical

decision making support to aid healthcare workers.

While there are numerous gaps highlighted in the

out-of-the-box installation of OpenMRS MDRTB

module, it does help to mitigate various identified

risks and eliminate waste; making the diagnosis and

treatment process of MDRTB more efficient.

However it would be better if the gaps identified in

the study were closed before an implementation is

done.

Two process improvements were presented to

participants: Firstly, always taking 3 sputum samples

and secondly, replacing the MDRTB register with

the investigation form. The clinical guideline

specifies that three sputum samples be collected

based on a specified decision tree and the

recommendation was to simplify the process and

always collect 3 sputum samples. Participants

“disagreed” and “strongly disagreed” with the

process modification suggested, although no reason

was provided by participants when this was queried.

The majority of the participants were “undecided”

whether replacing the register with the investigation

form would yield value. Thus, based on the experts’

experience in the field, these interventions appear

likely to have an insignificant impact.

One of the greatest opportunities to enhance the

OpenMRS system is to ensure that the processes that

are supported by the system adequately provide

relevant communication to stakeholders involved in

the process. Quality improvement research

highlights the need for effective communication

among healthcare workers during the clinical care

process to support care co-ordination (Boston-

Fleischhauer, 2008a); (Tanevaa et al., 2010). All

participants did not respond to statements relating to

the need for the system to support communication,

and responses varied widely. An individual’s

perspective on this issue may be dependent on the

environment in which the participant operates. This

form of context dependent analysis did not form part

of this research however it does suggest an area for

future research.

4.2 Synergies for Co-treatment of

MDRTB & HIV

One of the greatest challenges in the developing

world is the dual infection of HIV and MDRTB

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(Cohen and Maarstens, 2004); (O'Donnell et al.,

2009); (Seung et al., 2009). This was supported by

the findings in this study as all participants agreed

that there is a need for the co-treatment of HIV and

MDRTB patients.

Participants highlighted several factors that could

offer synergies for the co-treatment such as;

identifying the reasons for the delay in initiating

HIV treatment of MDRTB patients and the provision

of support to HIV and MDRTB patients to adhere to

their treatment programmes. These are supported by

World Health Organisation (2009) research and by

Perumal et al., (2009). Participants suggested, and

strongly agreed, that it would be preferable to have

one service provider to support the treatment of

patients suffering both conditions. This has not been

explored in any previous study and should be further

explored from both an operational and clinical

perspective.

A participant noted the lack of existing literature

detailing the advantages and disadvantages of a

decentralized model of care (a.k.a community care

or mobile care). As with previous studies,

participants also highlighted the need for MDRTB

patients attending facilities to be tested for HIV

(O’Donnell et al., 2010). The synergies that were

raised, but which participants disagreed on were;

electronic monitoring systems that do not require

specialised data capturers, separate clinic notes and

registers and the provision of isoniazid prophylaxis

for all immune-compromised individuals, especially

post TB treatment.

The participants with a clinical background also

highlighted the need for more synergies in terms of

drug treatments to effectively support the

consequences of drug interaction; as highlighted by

Cohen and Maastens (2004), Calver et al., (2010)

and Cegielski, (2010). Participants reiterated the

point made in previous studies that there is a need

for early treatment of ARV in dually infected

patients (O'Donnell et al., 2009); (Seung et al.,

2009).

The participants with OpenMRS implementation

experience also contributed to the synergies

identified, indicating that electronic monitoring

systems could support patient treatment adherence.

This is not surprising, as OpenMRS implementations

in other African countries have already encountered

such challenges and have worked on solutions such

as SMS reminders (Allen et al., 2007);

(Noormohammad et al., 2010); (Choi and Fraser,

undated).

4.3 Value of Process Engineering

Participants had no substantive disagreement with

the findings presented as a result of the process

analysis. In addition, participants expressed the

value that they had seen in terms of the advantages

noted in the first round of the Delphi review. Thus

the exercise promoted the appreciation of the value

of process analysis. Four out of five participants

agreed that conducting the process analysis was a

time consuming activity. Given that participants

themselves did not conduct the process analysis,

their perception of the time consuming nature of the

activity may be biased.

While there are a few studies that highlight the

value of process models as a medium to teach

healthcare workers (Stausberga et al., 2003), this

potential benefit was ranked lower than most other

advantages noted by participants. The use of process

analysis in the development of clinical protocols has

been noted by Taneva et al., (2010). Participants in

this study both identified this advantage and ranked

it very high. It is a growing trend in healthcare

quality improvement programmes and research to

encourage healthcare workers to initiate

improvement opportunities (Needleman and

Hassmiller, 2009); (Chassin et al., 2010).

Participants identified process analysis as a

technique to realise this advantage and ranked it

very highly.

One of the participants highlighted that there is a

need to measure improvement in clinical outcomes

with the implementation of a HIS and research

indicates that evidence based medicine is strongly

supported by implementations of HIS (Paulus et al.,

2008).

5 CONCLUSIONS

This study has presented an opportunity to

understand how healthcare can be delivered with

operational excellence. Even in the developing

world context, simple process improvement can go a

long way to improving service.

Firstly modelling the process that healthcare

workers are expected to follow in the diagnosis and

treatment of MDRTB (based on the SA clinical

guidelines) and the electronic HIS processes (based

on OpenMRS documentation) it became easier to

understand the main objectives of the diagnosis and

treatment process.

Secondly the process models allowed for the

analysis of wastes, opportunities for improvement

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and the alignment between the SA clinical

guidelines and the functions of OpenMRS. The

process analysis highlighted that there are

inefficiencies in the process related to poor data

management and break-points in the process. There

are also various opportunities to provide value add

to the patient, with reminders for follow-ups and

better reporting requirements to improve assessment

of the processes. There are numerous areas where

the out-of the box OpenMRS MDRTB installation

does not fit the South African context but has the

ability to reduce the inefficiencies that currently

exist.

Thirdly, the process analysis findings were

validated with experts in the field. The experts

confirmed that the findings were valid in terms of

outlining the relevant steps to be followed by

healthcare workers, the need for technology to

enable the process where appropriate and risks and

wastes that make the process inefficient. Participants

disagreed with the need to adjust the sputum

collection tasks and synergies of co-treatment such

as a single service provider and provision of

isoniazid prophylaxis for all immune-compromised

individuals.

The study assists in providing evidence to

illustrate the value of process engineering in the

developing world. The findings support current

trends in quality improvement such as evidence

based medicine. This will help the focus in the

developing world to include operational excellence

to improve the quality of care delivery, clinical

outcomes and the use of technology where

applicable to support these initiatives.

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