Temporal pacing of outcomes for improving patient flow: Design science research in a National Health Service hospital

• DOI: http://doi.org/10.1002/joom.1077
• Published date: 01 January 2020
• Author: Mark Johnson,Simon Sethi,Nicola Burgess
• Date: 01 January 2020

RESEARCH ARTICLE

Temporal pacing of outcomes for improving patient flow:

Design science research in a National Health Service

hospital

Mark Johnson

1

| Nicola Burgess

1

| Simon Sethi

2

1

Operations Management Group,

Warwick Business School, Coventry, UK

2

Yeovil District Hospital, Yeovil, UK

Correspondence

Mark Johnson, Operations Management

Group, Warwick Business School,

Coventry, CV4 7AL, UK.

Email: mark.johnson@wbs.ac.uk

Handling Editors: Lawrence Fredendall,

Anand Nair, Jeffery Smith and

Anita Tucker

Abstract

Improving patient flow in hospitals is a contemporary challenge in the UK

National Health Service (NHS). When patients remain in a hospital bed for

longer than clinically necessary, hospital performance is dramatically

impacted, quality of care is reduced, and elective surgeries are cancelled at

great cost to both hospital and patient. This research explains how one UK

hospital employed design science research to improve patient flow after other

process improvement techniques had failed. The work focused on improving

patient flow through the creation of a set of interconnected, temporally paced

routines that successfully engaged doctors and nurses in new, outcome-specific

ways of working. These routines were both independent and interdependent,

were relationally coordinated through time, and systematically and unambigu-

ously engaged all levels of staff at specific temporal junctures. We discover that

the successful adoption of these routines was cumulative rather than iterative

and was aligned with ongoing efforts supporting the social aspects of change.

Through this work, our case hospital saw performance improvements that

moved them from being below average to the best in the country, combining

improvements in patient care with savings of over £3 million in the first

12 months. The contribution of this research is twofold; first, we explain how

the development of outcome-specific routines can facilitate process improve-

ment, and second, we illustrate how design science research can successfully

bridge theory and practice to promote swift and even flow in healthcare.

KEYWORDS

design science, healthcare, hospitals, patient flow, process improvement, routines

1|INTRODUCTION

The UK health system is experiencing a humanitarian cri-

sis (Campbell, Morris, & Marsh, 2017). Cuts to social care

provision, funding restraints, an increasingly elderly popu-

lation, and a growing demand for emergency services

(Poteliakhoff & Thompson, 2011) have led to a significant

decline in performance in recent years. Many hospitals

have been operating under a financial deficit since 2012,

and performance against a number of core waiting time

targets has deteriorated to levels analogous to 2007. NHS

providers and commissioners ended 2015/2016 with a defi-

cit of £1.85 billion—the largest in NHS history (NAO,

2016). Accordingly, healthcare providers are being told

they must redouble productivity efforts to deliver £22 bil-

lion of efficiency savings by 2021 (Alderwick, 2016).

Received: 31 October 2017 Revised: 8 November 2019 Accepted: 27 November 2019

DOI: 10.1002/joom.1077

J Oper Manag. 2020;66:35–53. wileyonlinelibrary.com/journal/joom © 2019 Association for Supply Chain Management, Inc. 35

Productivity revolves around two fundamental and

interrelated principles: (a) units flowing as quickly as

possible through the system; and (b) the minimization of

variation from all sources, including quality, quantity,

and timing (Schmenner, 2015; Schmenner & Swink,

1998). In a hospital, productivity broadly translates to the

flow of patients from admission to discharge (Devaraj,

Ow, & Kohli, 2013). However, the desire of policy makers

to redouble productivity efforts is regarded skeptically by

healthcare professionals:

“If patients were cars, we would all be used

cars of different years and models, with dif-

ferent and often multiple problems, many of

which had previously been repaired by vari-

ous mechanics. Moreover, those cars would

all communicate in different languages and

express individual preferences regarding

when, how, and even whether they wanted

to be fixed.”(Hartzband & Groopman,

2016, p. 107)

Moreover, physicians traditionally hold power and

jurisdiction over nurses and managers (Abbot, 1988), and

will commonly resist managerial encroachment so as to

protect their identity as an elite authority (Kellogg, 2010;

Martin, Currie, & Finn, 2009; Nancarrow, 2015). Enhanc-

ing productivity in healthcare requires attending to the

social and political aspects of change as well as the tech-

nical. Healthcare organizations must employ methods

that bind these elements together, engaging managers

and professionals in adopting new practices that align

with the values of the professional core. Here, we

describe how the process of Design Science Research

(DSR) led to a series of interventions and mechanisms in

a UK hospital that successfully brought together a diverse

set of professional and managerial perspectives aimed at

developing solutions that improved productivity. Thus,

the goals of this research were:

1. To employ DSR to improve the productivity of a UK

hospital; and

2. Through DSR, to address the social, political, and

technical aspects of productivity improvement.

We followed the “CIMO”logic of Context–Interven-

tion–Mechanism–Outcome (Denyer, Tranfield, & Van

Aken, 2008) to develop a set of three interventions and

their facilitating mechanisms in order to create, imple-

ment, and embed routines to improve hospital productiv-

ity and performance against national waiting time targets.

Our research makes two contributions to healthcare

operations improvement. The first is the explication of

how and why outcome-specific routines support the tech-

nical aspect of process improvement. The second is an

illustration of how the process of DSR can accommodate

the social element of change to promote swift and even

flow in a multijurisdictional professional service context.

The remainder of this article is organized as follows.

Section 2 presents our literature review. Section 3

describes the design science approach, our empirical con-

text, and our set of three inter-related interventions.

Section 4 describes the DSR project through which our

interventions were deployed, the mechanisms through

which the interventions were facilitated, and the perfor-

mance outcomes the project achieved. In section 5, we

discuss our findings to explicate why the DSR project was

successful. We conclude with an outline of research limi-

tations and implications for healthcare policy and

practice.

2|IMPROVING PRODUCTIVITY

IN HEALTHCARE: PRESCRIPTIONS

FROM OPERATIONS MANAGEMENT

OM practices and process improvement methodologies

can address the productivity problem faced by the NHS

and other healthcare systems. However, their transfer

into practice has been varied (Boyer, Gardner, &

Schweikhart, 2012; Boyer & Pronovost, 2010; Kreindler,

2017). Hospitals are analogous to: “immensely compli-

cated processing plants, with thousands of parallel, often

complex and interlocking, processes”(Rechel, Wright,

Barlow, & McKee, 2010, p. 633). This structural and tech-

nical complexity is compounded by a complex social and

political context that makes managing hospitals extraor-

dinarily difficult (Glouberman & Mintzberg, 2001). Com-

plex social systems require careful application of external

and internal levers of control that can effectively mediate

complex social and political systems to promote a desired

operational response (Netland, Schloetzer, & Ferdows,

2015; Senot, Chandrasekaran, & Ward, 2016; Vogus &

Iacobucci, 2016).

2.1 |The productivity problem and

patient flow

Schmenner (2015) hails productivity as the prerequisite

of all economic success. The theory of swift and even flow

(TSEF) was proposed by Schmenner and Swink (1998) on

the basis that the productivity of any process rises with

the speed by which inputs flow through the process and

falls with increases in variability, whether these are asso-

ciated with the demand on the process or with the steps

36 JOHNSON ET AL.