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

Center for Research in Health Technologies and Information Systems, Porto, Portugal

Faculty of Medicine, University of Porto, Porto, Portugal

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

 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

, 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

hours – Before (%)

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

admission – Before (n)

2.76

<0.001

Patients waiting longer than 12 hours for

admission – After (n)

0.00

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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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