APPLYING TOC BUFFER MANAGEMENT IN HEALTH
INFORMATION SYSTEMS TO IMPROVE
HOSPITAL PERFORMANCE
Gustavo Marísio Bacelar-Silva
1,2,3
and Pedro Pereira Rodrigues
1,2
1
Center for Research in Health Technologies and Information Systems, Porto, Portugal
2
Faculty of Medicine, University of Porto, Porto, Portugal
3
Faculty of Science, University of Porto, Porto, Portugal
Keywords: Theory of constraints, Buffer management, Patient flow, Health care process, Hospital performance.
Abstract: Health care systems around the world are under pressure, the costs are high and rising, and the population is
growing and ageing. Health information technology is expected to help improving the health care processes
capacity. The aim of this work is to analyze the benefits of the Theory of Constraints (TOC) buffer
management implementation in the health care environment concerning the improvement in the patient flow
and its management. A literature review was conducted, with an automated search on four databases to
identify relevant published articles, written in English language between 2000 and 2010, about the TOC
buffer management applied to the health care patient flow. Only three relevant articles were included. The
analysis was based on the measurements of the implementations realized in seven different hospitals and for
three different purposes: Accident & Emergency department (A&E), admissions and discharge. A statistical
analysis conducted in the A&E and admissions post-implementation results demonstrated a significant
improvement achieved. Four management control functions improvements were also obtained: prioritize,
expedite, escalate and improve. Although few papers were available, TOC buffer management appears to be
a good solution to improve performance and management in health care.
1 INTRODUCTION
Along the years, all countries have been dealing with
similar problems in health care. The high and rising
costs are not followed by improvements in quality.
The services are rationed and the care patients
receive lags currently standards (Porter and
Teisberg, 2006). In addition, the ageing and still
growing population contributes to the perspective of
putting more pressure on the system due to its rising
demand of healthcare services (The Economist,
2009).
The delay of care is a major issue, a persistent
and undesirable feature of current health care
systems (Murray and Berwick, 2003). No country,
regardless its wealth, can ensure immediate access to
every technology and intervention that may improve
health or prolong life to everyone. The fundamental
problem is availability of resources (World Health
Organization, 2010). Although variable, the waiting
times can lead to substantial impact in individuals’
health (Koopmanschap et al., 2005). The pressure
made England adopt an aggressive policy of targets
coupled with publication of hospitals waiting times,
dubbed “target and terror”, with strong sanctions for
poor performing (Rotstein et al., 2002).
Huge investments have been made in health
information technology (HIT), and it is expected to
be a solution to the healthcare rising cost, improving
the workflow, efficiency and quality (Adler-
Milstein, 2009). The advantages of HIT over paper
records are readily discernible. However, HIT
continues to increase expenditure to levels that
nearly all decision makers believe that clear
profitability has not been demonstrated (Meyer and
Degoulet, 2010); (Chaudhry et al., 2006).
The Theory of Constraints (TOC) is an emerging
philosophy born to solve industries problems. It is
based on the idea that any system or organization
has at least one constraint, which limits the
performance of the system as a whole (Goldratt and
Cox, 2004). As it showed to be a powerful solution,
its implementation rapidly spread to other areas,
345
Bacelar-Silva G. and Pereira Rodrigues P..
APPLYING TOC BUFFER MANAGEMENT IN HEALTH INFORMATION SYSTEMS TO IMPROVE HOSPITAL PERFORMANCE.
DOI: 10.5220/0003724703450349
In Proceedings of the International Conference on Health Informatics (HEALTHINF-2012), pages 345-349
ISBN: 978-989-8425-88-1
Copyright
c
2012 SCITEPRESS (Science and Technology Publications, Lda.)
such as project management, financing, services,
education and health care. One of the TOC tools, the
buffer management, is used with success in the shop
floor and project management and has been used in
health care practice to improve the hospitals
workflow. The idea behind this tool is to monitor the
quantity of work in front of a resource and compare
the actual versus the planned performance
(Schragenheim and Ronen, 1991); (Cox III and
Schleier Jr, 2010).
The purpose of this article is to analyze the
benefits of the TOC buffer management
implementation in the health care environment
concerning the improvement in the patient flow and
its management.
2 METHODS
It was conducted an automated literature search on
four databases to identify relevant published articles,
written in English language between 2000 and 2010.
The databases used were Pubmed, Scopus, ISI Web
of Knowledge and Google Scholar. The terms
((“theory of constraints” OR “buffer management”)
AND health care) were used to search in titles,
abstracts and keywords. The last search made was
on January 1
st
, 2011. The total number of found
articles was 1,307, including all the four literature
databases used. But most of them were found in
Google Scholar (1,160), followed by Pubmed (126),
Scopus (13) and ISI Web of Knowledge (8). In this
first stage, by reading the titles and the abstracts,
were excluded the non-articles results (most of them
in Google Scholar), repeated articles and the TOC
not related articles (the ones that just cited the TOC).
The left 15 articles were TOC related articles, but
analyzing the titles and abstracts, were excluded 4
articles related to TOC other issues but buffer
management and patient flow (e.g. thinking
processes). One of them was just an interview and
was excluded as well. The eleven TOC left articles
were analyzed beyond the abstract, it was searched
along the text about TOC and the buffer
management implementation, excluding 7 articles
that did not addressed specifically the TOC buffer
management implementation in the healthcare and
the patient flow. Thus, the final number of papers
included in the review was 3.
3 RESULTS
All the papers included in the present review were
done and published (in three different European
journals) in Europe, two of them in 2006 and one in
2010. Two of them are from United Kingdom and
one from Netherlands.
All these studies say that the TOC buffer
management had a positive impact in the patient
flow in the health care environment and also brought
benefits to better manage the system. But only one
focused in demonstrating the benefits by
measurements. Another one focused in describing
the adverse issues overcame and the other one
focused in explain how and why the TOC buffer
management implementation resulted in success.
3.1 Performance Improvements
The oldest article (Umble and Umble, 2006) is the
one that most detailed describes the results. TOC
buffer management was applied using an
information system developed on Microsoft Access
software to record the actual data about the timing
and content of activities performed in the treatment
of each patient. The purpose was to generate
performance improvements in the Accident and
Emergency (A&E) departments and the hospital
admissions process at three British National Health
Service (NHS) facilities. The main measures were,
(1) the percentage of patients spending more than 4
hours to be processed through the A&E department,
since the government adopted a performance
standard (90% of the patients to be processed within
the time limit of 4 hours, from the time the patient
arrives until the discharge or decision to admittance
to an acute hospital); and (2) the time between the
decision to release the patient and their admittance
to an acute hospital (trolley waits), which was
desired to be within 4 hours, but was recommended
to do not exceed the 12 hours limit.
Before applying TOC buffer management, the
percentage of patients that were processed through
the A&E system under 4 hours varied between 50-
75%. During the subsequent months (2-5 months)
after the implementation, the percentage of A&E
patients processed in less than 4 hours increased to
at least 91% (Table 1). A statistical analysis was
conducted only at the Milton Keynes District
Hospital. The mean percentage for the pre and post-
implementation periods were 69.07 (included 36
weeks) and 83.14 (included 11 weeks), respectively.
After calculating t statistic, the difference of the
means for the two periods was 11.42 (α = 0.01).
Hence, the analysis indicates a statistically
significant reduction after the TOC buffer
management implementation.
HEALTHINF 2012 - International Conference on Health Informatics
346
Table 1: Comparison between the percentage of patients processed in the ED before the TOC buffer management
implementation and after.
Milton Keynes District
Hospital
Oxfordshire Horton
Hospital
Oxfordshire Radcliffe
Hospital
Before In 5 months Before In 4 months Before In 2 months
A&E patients spending less
than 4 hours (%)
60-75% 95% 50-60% 91% 50-60% 95%
A statistical analysis was also conducted to
determine the effectiveness of the TOC buffer
management implementation in reducing the
discharged A&E patient admission waiting time to
the acute hospital. The mean weekly numbers of
A&E patients whose admission delayed 4-12 hours
during the pre and post-implementation periods were
41.45 (included 38 weeks) and 6.36 (included 11
weeks), respectively. The calculated t statistic was -
6.64, (α = 0.01). Next was considered the weekly
number of A&E patients whose acute hospital
admission waiting time delayed more than 12 hours.
The weekly mean numbers of patients during the pre
and post-implementation periods were 2.76 and 0,
respectively. The calculated t statistic was 3.81, (α =
0.01). Thus, there was also statistically significant
reduction in the number of A&E patients waiting to
be admitted to the acute hospital.
The most recent article (Stratton and Knight
2010) included four hospital implementations of the
QFI Jonah software and TOC buffer management
methodology were investigated to establish how
buffer management was applied and why the
reported benefits were achieved. Buffer management
application was implemented in all four hospitals for
discharge of acute-hospital patients and in three
cases for A&E. Although the emphasis was in
determining how and why, this article also shows
some results. The number of patients that breached
the 4-hour limit in the A&E dropped to nearly zero
after the TOC buffer management implementations
at the three hospitals that implemented both the
A&E and discharge systems. After 20 weeks, the
number of patients exceeding the 4-hour limit
decreased noticeably.
3.2 Managerial Improvements
Mur-Veeman and Govers (2006) considered in their
article the possible value and challenges offered by
TOC buffer management applied in health supply
chains, most specifically the Dutch bed-blocking
problem and the intermediate care departments
(ICD). The ICDs were created to act like a buffer
and to solve the bed-blocking problem, but it just
generated an additional link in the care chain and the
problem still continued. Thus the article authors’
suggestion was to implement the TOC buffer
management prior to the ICD. According to the
authors (Mur-Veeman and Grovers 2006; Stratton
and Knight 2010), the TOC buffer management has
many benefits to improve management. They were
grouped in 4 managerial control functions, as
proposed by Stratton and Knight:
Prioritize: Each patient is displayed on a
computer screen, in priority order, and coded with a
color (green, yellow, red and black), so it is easier to
visualize the patients priority order regarding the
discharge target. It is important to state that the
clinical priorities are expected to override the
defined priority order or discharge target.
Expedite: Patients entering in the red zone are
within the last zone before breaching the target time
limit and in the black zone have already done it. As
the patients enter those zones, it is signalizes across
the hospital the need to expedite action by the
resource causing the delay.
Escalate: On a regular basis the delay reasons are
analyzed and it allows escalating resources
according to the fluctuations in the flow, before the
system gets unstable.
Improve: As the reasons for delay are recorded,
it is possible to identify and act on common causes
regularly.
Table 2: Comparison of processing times in the A&E and
acute hospital admission delays before and after the
implementation of buffer management.
Variable Mean p-Value
A&E patients processed in less than 4
hoursBefore (%)
69.07
<0.001
A&E patients processed in less than 4
hours After (%)
83.14
Patients waiting 4-12 hours for admission
Before (n)
41.45
<0.001
Patients waiting 4-12 hours for admission
After (n)
6.36
Patients waiting longer than 12 hours for
admissionBefore (n)
2.76
<0.001
Patients waiting longer than 12 hours for
admissionAfter (n)
0.00
APPLYING TOC BUFFER MANAGEMENT IN HEALTH INFORMATION SYSTEMS TO IMPROVE HOSPITAL
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4 DISCUSSION
The TOC buffer management approach to manage
the patient flow along the health care process seems
to be a powerful solution. The two papers that
analyzed the implementation in the health care
environment showed good results in such a little
time (Mur-Veeman and Grovers, 2006); (Stratton
and Knight, 2010). Despite the fact that the TOC
buffer management was utilized at seven different
hospitals and for three different purposes (i.e. A&E,
admissions and discharge), it showed some evidence
to be powerful enough to improve their capacities. In
addition, it is important to state that at the Milton
Keynes District Hospital, the implementation was
successful even counting with an increasing number
of patients visiting the A&E, from about 1,200
patients per week to over 1,300 patients per week
during the next 3-4 months after the implementation
had started (Umble and Umble, 2006). But, on the
other hand, there was only one hospital that had the
results statically analyzed and described. All the
others, if there were results statically analyzed, they
were not described on any part of the papers,
unfortunately.
Seeing from the patients’ perspective, the results
were worthy. Their waiting time decreased in the
A&E and in the acute hospital admissions. Which in
part means a better service quality, because it is
essential to consider the maintenance of the clinical
service quality. But this issue seemed to be
addressed due to the weekly meetings reported by
the authors (Umble and Umble, 2006); (Stratton and
Knight, 2010). They were important to notice the
function of the system, to analyze the performance
of the resources, identify the most common causes
of delay. These resources commonly causing delay
were constraints and after being adjusted they
improved the performance of the system as a whole.
The obtained improvements were achieved
without any extra resource or expenditure. Since the
TOC has the ability to better use the resources;
optimizing the system so that hidden capacities arise
and balance the flow, instead of balancing the
resources capacities (Goldratt and Cox, 2004).
5 CONCLUSIONS
This paper analyzed and made possible to bring
together the relevant papers about the described
TOC buffer management implementations in the
literature. Addressing two different purposes
implementations (A&E and discharge of acute-
hospital patients), the existing articles showed
significant performance improvements achieved and
explained the main managerial benefits that the TOC
buffer management brought to the hospitals’
departments.
Although the TOC buffer management is a
relatively new managerial approach, it arises as a
good possible solution for the health care systems.
For now, there are only few papers available. It is
expected that the TOC buffer management will be
more utilized in the health care environment and
more papers be written with a more rigorous
statistical analysis about it in the scientific literature.
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