From ‘Solution Shop’ Model To ‘Focused Factory’ In Hospital Surgery: Increasing Care Value And Predictability
By David Cook, Jeffrey E. Thompson, Elizabeth B. Habermann, Sue L. Visscher, Joseph A. Dearani,
Veronique L. Roger, and Bijan J. Borah
From ‘Solution Shop’ Model
To ‘Focused Factory’ In Hospital
Surgery: Increasing Care Value
And Predictability
ABSTRACT The full-service US hospital has been described organizationally
as a “solution shop,” in which medical problems are assumed to be
unstructured and to require expert physicians to determine each course
of care. If universally applied, this model contributes to unwa
anted
variation in care, which leads to lower quality and higher costs. We
purposely disrupted the adult cardiac surgical practice that we led at
Mayo Clinic, in Rochester, Minnesota, by creating a “focused factory”
model (characterized by a uniform approach to delivering a limited set of
high-quality products) within the practice’s solution shop. Key elements
of implementing the new model were mapping the care process,
segmenting the patient population, using information technology to
communicate clearly defined expectations, and empowering nonphysician
providers at the bedside. Using a set of criteria, we determined that the
focused-factory model was appropriate for 67 percent of cardiac surgical
patients. We found that implementation of the model reduced resource
use, length-of-stay, and cost. Variation was markedly reduced, and
outcomes were improved. Assigning patients to different care models
increases care value and the predictability of care process, outcomes, and
costs while preserving (in a lesser clinical footprint) the strengths of the
solution shop. We conclude that creating a focused-factory model within
a solution shop, by applying industrial engineering principles and health
information technology tools and changing the model of work, is very
effective in both improving quality and reducing costs.
S
urgical care in a hospital can be char-
acterized by the term “complexity,”
driven in large part by the fact that
most full-service hospitals operate as
“solution shops.”1,2(p75) These shops
are “structured to diagnose and recommend
solutions to unstructured problems.”2(p xxiv) The
solution-shop concept was originally used to de-
scribemanufacturing.However, it is particularly
appropriate to hospital-based surgical care, in
which decision making usually relies upon sur-
geons’ specific training, intuition, and experi-
ence to define the course of care.
Solution-shop thinking is imbedded in US
physician culture and education and is a critical
component of advanced care delivery. But sys-
tems engineering, process analysis, quality con-
trol, and manufacturing science3 suggest that
the uniform application of what amounts to a
nineteenth-century craftsman model of medi-
cine is insufficient to meet twenty-first-century
health care needs.
doi: XXXXXXXXXX/hlthaff XXXXXXXXXX
HEALTH AFFAIRS 33,
NO XXXXXXXXXX): 746–755
©2014 Project HOPE—
The People-to-People Health
Foundation, Inc.
David Cook (cook.david@
mayo.edu) is a professor in
the Department of
Anesthesiology, Division of
Cardiovascula
Anesthesiology, Center for the
Science of Health Care
Delivery, Mayo Clinic College
of Medicine, in Rochester,
Minnesota.
Jeffrey E. Thompson is
director of operations
management, United Surgical
Partners, in Addison, Texas.
Elizabeth B. Habermann is an
associate professor of health
services research, Center fo
the Science of Health Care
Delivery, Mayo Clinic College
of Medicine.
Sue L. Visscher is an
assistant professor of health
services research, Center fo
the Science of Health Care
Delivery, Mayo Clinic College
of Medicine.
Joseph A. Dearani is a
professor in the Department
of Surgery, Division of
Cardiovascular Surgery, Mayo
Clinic College of Medicine.
Veronique L. Roger is a
professor of epidemiology and
medicine, Center for the
Science of Health Care
Delivery, Mayo Clinic College
of Medicine.
Bijan J. Borah is an assistant
professor of health services
esearch, Center for the
Science of Health Care
Delivery, Mayo Clinic College
of Medicine.
746 Health Affairs May XXXXXXXXXX:5
Hospital Productivity
Downloaded from HealthAffairs.org on November 29, 2021.
Copyright Project HOPE—The People-to-People Health Foundation, Inc.
For personal use only. All rights reserved. Reuse permissions at HealthAffairs.org.
Some care demands solution-shop thinking.
However, its universal application leads to wide
variations in practice and runs counter to stan-
dardized best-practice models.With such think-
ing, the same problemmay be approached in ten
different ways by ten physicians. The resulting
unwa
anted variation increases cost; reduces
quality;4–7 and impedes the acquisition of norma-
tive data on practice, health outcomes, and cost.
The conceptual alternative to the solution
shop is the “focused factory,”1 which is charac-
terized by a uniform approach to delivering a
limited set of high-quality products. Clayton
Christensen and coauthors2 provide multiple
examples of this concept in health care, from
so-called minute clinics to specialty surgical
hospitals.
In primary care, there has been a movement
away from the solution-shop model, with stan-
dardized care increasingly being provided by
nonphysicians. However, in the high-acuity,
full-service hospital—and in hospital-based sur-
gery, in particular—the solution-shop model re-
mains strong. Our experience suggests that the
dominance of the model is co
elated with both
the acuity of the care provided and the length of
training of the surgical provider. Thus, for a full-
service hospital, the critical questions are which
problems or populations of patients are best
addressed by solution-shop models and which
y focused-factory models, and how those mod-
els should interact.
In 2009we—the leaders of a clinical practice at
Mayo Clinic, in Rochester, Minnesota—initiated
apractice redesigneffort to improve the value (in
terms of outcomes divided by cost) of cardiac
surgical care.8 All clinical divisions in the service
line were represented, and the effort was sup-
ported by staff from finance, practice analysis,
health information technology (IT), and project
management.What resulted at a very large aca-
demic hospital serving both a community and a
complex refe
al populationwas the creationof a
focused-factory model that cu
ently manages
more than 60 percent of an annual cardiac sur-
gery population of more than 2,000 patients.
Moving From Solution Shop To
Focused Factory
Our practice redesign began with three parallel
efforts: stakeholder analysis, practice analysis,
and the application of management tools (such
as Lean, Six Sigma, and value-stream mapping)
to the delivery of surgical care.9 We analyzed
esource use in each care environment and each
process step thatwas common toall adult cardiac
surgery patients. A primary focus was variation.
Wemade several critical observations: Practice
variation was high; variation was driven by ex-
pectations that were poorly defined or commu-
nicated; such expectations led to “overcare”—
that is, more care than was needed, and often
care that was provided for too long; the care
process was organized as a series of starts and
stops; data on length-of-stay in the intensive care
unit (ICU) and the hospital indicated that more
than half of patients could be expected to have a
predictable course of care;10 and tools such as
Lean and Six Sigma were poorly suited for use
in changing a practice model based on a culture
of physician-specific decision making.
These observations supported calls by pro-
viders, payers, andhealth policy experts for stan-
dardized practices to reduce unwa
anted varia-
tion, reduce cost, and improve quality.5–7,11
Implementation of the focused-factory model
took place in the following six stages: identifica-
tion and segmentation of the population suited
to the model; creation of a clinical pathway of
linked protocols for the operating room, ICU,
and progressive care unit (PCU) or floor; design,
uilding, and adoption of health IT systems to
communicate care protocols and the identifica-
tion of the focused-factory population; empow-
erment of bedside providers (nurses, respiratory
therapists, and nurse practitioners) to advance
care—that is, tomove the patient through a proc-
ess of de-escalating care—without physician in-
put when appropriate; locating patients with
similar care processes and conditions of simila
clinical complexity near each other, in an at-
tempt to create a “plant within a plant”;12 and
a phased rollout.
Mapping the process of care and its variation
allowed us to estimate the proportion of the pa-
tient population suited to a standardized care
model as well as the process improvement tar-
gets for each major care step. Then, using both a
priori (predesignation) and post hoc (confirma-
tion) methods, we segmented the population
into focused-factory and non-focused-factory
groups for subsequent care. Using predeter-
mined criteria—such as surgical complexity,
the number of major medical mo
idities, and
isk—before surgery, we used our health IT sys-
tem to designate patients who were suitable
for the focused-factory group. To allow for po-
tential changes in patients’ clinical status, con-
firmation of suitability by the anesthesiologist
was required at the end of surgery for patients
to remain in that group. If patients were not
identified before surgery as suitable but met
the criteria after surgery, a provider then as-
signed them to the focused-factory group.
Following our analysis of the process of care,
we reviewed best practices and then built proto-
cols that drove the management of all majo
May XXXXXXXXXX:5 Health Affairs 747
Downloaded from HealthAffairs.org on November 29, 2021.
Copyright Project HOPE—The People-to-People Health Foundation, Inc.
For personal use only. All rights reserved. Reuse permissions at HealthAffairs.org.
steps in the process. Individual protocols for the
ICU and PCUwere subsequently bundled togeth-
er and put into tiers of meta-orders.13 The indi-
vidual ICU protocols included weaning patients
from mechanical ventilation, weaning patients
from hemodynamic infusions, removing in-
dwelling central lines, and preparing patients
for discharge from the ICU. The individual
PCU protocols were for removing patients’ Foley
catheters, chest tubes, and pacemaker wires; ad-
vancing patients’ diet from liquids to semisolids
and then solids; and improving ambulation—fo
example, moving from walking with assistance
to walking independently. All protocols were de-
signed to make care advancement the default
when clinical criteria were met.
We used health IT systems to acquire and
eport data on care process events, identify
focused-factory patients, populate pharmacy
orders, support bed planning and staffing, and
confirm patients’ continued suitability for the
care management strategy. This use of health
IT addressed ba
iers in communicating both
care expectations and responsibility for advanc-
ing the care process.
Identification of the care population and com-
munication of care expectations (by protocol
and health IT systems) empowered bedside
providers to advance care without a physician’s
input when clinical criteria were met.When pa-
tients failed to meet criteria for such advance-
ment, they were managed directly by physicians
(using the solution-shop approach) until thei
clinical status allowed them to return to focused-
factory management.
Our stakeholder analysis showed that having
oth patients with routine conditions and those
with complex conditions in the same care unit
esulted in complex workflows, competition fo
internal resources, inability to acquire and re-
port meaningful unit-specific metrics, and cul-
tural ba
iers related to care management. Iden-
tifying and confirming patients’ focused-factory
status allowed thesepatients tobegrouped in the
same ICU after surgery, and subsequently in the
same PCU.
The model was implemented between late
2009 and mid-2011. Its rollout occu
ed in
stages, with operating room practice changes
primarily in 2009, ICU practice changes in
2010, and PCU care