Process Coordination Within a Health Care Service Supply Network

• Author: Glen Schmidt,John W. Gardner,Scott E. Sampson,Joseph Van Orden
• Date: 01 December 2015
• DOI: http://doi.org/10.1111/jbl.12106
• Published date: 01 December 2015

Process Coordination Within a Health Care Service Supply Network

Scott E. Sampson

1

, Glen Schmidt

2

, John W. Gardner

1

, and Joseph Van Orden

3

1

Brigham Young University

2

University of Utah

3

Arizona State University

There are two manifestations of supply chains in health care. One involves the supply of equipment and materials used in health care deliv-

ery. The other supply chain involves the delivery of health care itself, wherein patients supply their physical conditions and service suppli-

ers deliver health care services. This article considers the latter supply chain, analyzing a case study in which patients have comorbidities and

thus require the services of a network of multiple health care providers. In the case study, we examine three schemes for coordination of care.

In the first scheme, the patient herself is expected to manage the coordination. In the second scheme, physicians are expected to coordinate the

care. In the third scheme, a third-party coordinator manages care across network members. We examine these three possible coordination alter-

natives using a technique known as Process-Chain-Network (PCN) Analysis. PCN Analysis helps us document how coordination schemes are

implemented and where they may fail. Our analysis of the case study leads us to the development of ex post theory about who should initiate

coordination and how it should take place under conditions of comorbidities. Empirical data coming from the case study support the theory. We

describe possible applications of the theory inside and outside of health care, and show how the PCN approach can guide process innovation.

Keywords: health care; service supply chain; service networks; coordination

INTRODUCTION

Health care costs constituted over 17% of U.S. gross domestic

product in 2012, with health care expenditures growing by about

3.7% yearly for the past half-decade (and typically by even lar-

ger percentages in prior decades) (Kaplan and Porter 2011). In

spite of this growing cost burden, it can no longer be taken for

granted that the life expectancy of Americans will continually

grow year-over-year—in fact, in 2008 the life expectancy fell

ever-so-slightly (Lopatto 2010). Thus for the financial health of

our economy, and for the physical health of our citizens, it is

imperative that health care costs be constrained and that health

care outcomes be even further enhanced. These health care con-

cerns are not limited to the United States, but similar issues are

of concern to other countries as well. In this article, we explore

one specific approach that health care might use to help enhance

outcomes—specifically, we examine how one might best coordi-

nate activities across a health care supply network.

Much of the research in supply chain management to date has

dealt with the delivery of physical products. In such a supply

chain goods flow in a more-or-less linear fashion, for example,

from an upstream raw materials supplier to a components manu-

facturer to a final assembly plant to a wholesaler to a retailer to

the downstream consumer, and much of the research has focused

on the dyadic relationship between two supply chain partners.

One of the key findings for these physical supply chains is that

coordination is needed between the supply chain partners—for

example, there is a wealth of literature on the need for “coordinat-

ing contracts”(Cachon and Lariviere 2005). Another key finding

for physical products is that in the design of such products, the

coordination can be achieved either via modular product designs

or via integral product designs (Baldwin and Clark 2000). In the

modular product design, the supply chain entities coordinate via

pre established and well-defined interface specifications. In the

integral product design, the coordination needs to instead be car-

ried out simultaneously between the multiple partners in the sup-

ply chain. In summary, from the study of physical supply chains

we have learned the importance of coordination across the supply

chain, we have identified different mechanisms via which this

coordination can be achieved, and we have found that certain situ-

ations favor one coordination mechanism over another.

The health care industry also relies on such “linear”supply

chains for the physical products that it uses and consumes, such

as medical equipment and pharmaceuticals. However, the deliv-

ery of health care also involves a service supply chain (SSC), in

which the patients present themselves with their physical condi-

tions and the providers deliver health care services. If the patient

experiences multiple ailments (comorbidities), then there may be

a host of health care providers involved in the delivery of that

one patient’s health care and the flow of care will not be linear

as was previously described for the physical product. Instead, the

patient will “flow”back and forth between providers—thus from

hereon we will refer to this as a “service supply network”as

opposed to a supply chain (Tax et al. 2013). It is this service

supply network that we focus on in this article. Because of the

numerous and possibly complex interactions between entities of

the network, coordination across the parties becomes especially

critical in the health care service supply network, as does the

consideration of more than a dyadic relationship between just

two supply chain players. In short, the health care environment

is characterized by significant complexity in patient conditions,

fragmented care processes that often rely on uncoordinated work

by specialists and other professionals, payment systems that cre-

ate incentive misalignment between patient wellness and provider

financial performance, and expanding systems of providers

(Christensen et al. 2008). Hence, we believe that studying the

coordination mechanisms is of critical importance in health care

service supply networks.

Corresponding author:

Dr. Scott E. Sampson, Marriott School of Management, Brigham

Young University, 660 TNRB, Provo, UT 84602, USA;

E-mail: sampson-article@byu.edu

Journal of Business Logistics, 2015, 36(4): 355–373 doi: 10.1111/jbl.12106

© Council of Supply Chain Management Professionals

The health care system has evolved into one involving numer-

ous specialties, where each specialty has its own treatment proto-

cols and may operate somewhat independently from other

specialties. A patient with comorbidities may get a referral to see

multiple specialists, and then be expected to make her own

appointments with each specialist and (for example) be expected

to take the medications that one specialist prescribes and com-

plete the physical exercises that another specialist prescribes. We

call this customer-initiated coordination—the customer is largely

responsible for managing her own interactions with each health

care provider. In the language of product design (e.g., Baldwin

and Clark 2000), this is a “modular”design architecture—each

module of care (each specialist) operates largely independently

of other modules (other specialists). The real-time coordination

across processes (across the episodes of patient care) is minimal

because standard interfaces have been preestablished. For exam-

ple, the surgeon who repairs the tear of the patient’s Achilles

tendon writes a prescription in a format that the pharmacist is

trained to read, and the surgeon sends the patient to a physical

therapist who has a preestablished standard treatment protocol

for this ailment. Coordination is largely achieved through these

preestablished protocols rather than through real-time interaction

—the real-time coordination is reduced because the interfaces

between these process steps have been previously codified (i.e.,

the interfaces between care episodes are standardized). Any

needed real-time coordination is largely left to the patient herself.

An alternative to the modular system of coordination is what

we call “supplier-initiated coordination,”whereby the various

service care providers (i.e., suppliers) interact in real-time. The

advantage of such a system is that the care for each patient can

be customized by the health care suppliers, and interactions

between treatment regimens can be addressed. The downside is

that real-time coordination among these process providers may

be costly and time-consuming.

Another alternative is what we call “third-party-initiated coor-

dination,”whereby someone other than the patient or the suppli-

ers takes responsibility for the coordination between the

providers and the customer (patient). For example, a “care coor-

dinator”(CC) may be responsible for helping a patient navigate

his care across multiple providers.

We examine these three coordination alternatives in a health

care case study involving patients with complex health care

needs. The contribution of our work is to develop theory about

which of these three types of coordination (modular, supplier-

initiated coordination, or third-party-initiated coordination) is

most appropriate in complex health care situations, as a function

of the various characteristics of the specific health care setting.

To do so, we will use a process network visualization methodol-

ogy known as Process-Chain-Network (PCN) Analysis. The

mechanics of PCN Analysis were published previously (Sampson

2012) but without showing how the PCN methodology can be

used to analyze and improve coordination across a network of

service suppliers. The PCN technique, which provides a frame-

work from which we can compare and contrast these coordina-

tion approaches, suggests where and how third-party-initiated

coordination is able to provide an improved health outcome for

patients with comorbidities. We cite empirical evidence to vali-

date this finding. In short, the PCN Analysis provides insights as

to why we observe these empirical outcomes.

The objective of the case study and PCN Analysis is to

develop propositions that can guide management practice as well

as future research. These propositions draw on observations

regarding coordination mechanisms that were attempted by the

studied health care organization, including outcome results

tracked over a three-year period. The propositions constitute an

ex post theory about how different coordination mechanisms will

operate in a complex health care situation.

The article is organized as follows. In the next section, we

provide further background and literature review. We discuss the

PCN Analysis methodology in the second section, and in the

third section, we use PCN Analysis in a case study of coordina-

tion mechanisms that were implemented and assessed in a regio-

nal health care organization. The PCN Analysis of the case study

motivates our development of ex post theory; the ex post

research technique we employ is similar to that used by other

health care supply researchers (e.g., Dixon-Woods et al. 2011).

The fourth section presents case observations as propositions

about coordination in service supply networks such as health

care. We demonstrate the use of the PCN model in exploring

subsequent process innovation. We also provide dialogue regard-

ing future research and possible applications of the theory out-

side of health care. The last section summarizes the research.

LITERATURE AND BACKGROUND

In this section, we review research literature pertaining to model-

ing supply networks, followed by a review of SSC and service

supply network coordination literature. This background is

offered to provide the context within which we study coordina-

tion across the health care service supply network.

Supply network modeling

Normann and Ram

ırez (1993, 69) describe “a world where value

occurs not in sequential chains but in complex constellations”

which are networks. The extant supply chain research presents

various models of coordination within supply networks. Choi

and Wu (2009b) emphasize two key influences within networks:

(1) the importance of how network nodes impact other nodes,

and (2) how links between nodes influence other links. These

inter relationships between nodes and links can range from the

individual actor level to broad social entities and societies (Choi

and Wu 2009b; Li and Choi 2009). In social network research,

these individual or organizational actors function in interdepen-

dent links or ties, as opposed to independent relations (Choi and

Kim 2008), and all actors are embedded within larger social net-

work structures.

Wu et al. (2010) highlight that supply network relationships

often reflect cooperative, competitive, and/or cooperative rela-

tionships and form a basis for other archetypes of relationships

such as those between suppliers of the same buyer (Wu and Choi

2005). Choi and Krause (2006) model supply networks based

upon complexity concepts in which the number, differentiation,

and level of interrelationships between suppliers are fundamental.

Li and Choi (2009) bridge the application of social network

research on supply chain relationships into service networks with

emphasis on structural positions between network actors that do

356 S. E. Sampson et al.