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Chapter 18 Partners HealthCare System
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18 Partners HealthCare System
Thomas H. Davenport
Partners HealthCare System (Partners) is the single largest prov
ider of healthcare in the Boston area. It consists of 12 hospitals,
with morethan 7,000 affiliated physicians. It has 4 million outp
atient visits and 160,000 inpatient admissions a year. Partners is
a nonprofitorganization with almost $8 billion in revenues, and
it spends more than $1 billion per year on biomedical research.
It is a major teachingaffiliate of Harvard Medical School.
Partners is known as a “system,” but it maintains substantial aut
onomy at each of its member hospitals. While some information
systems(the electronic medical record, for example) are standar
dized across Partners, other systems and data, such as patient sc
heduling, arespecific to particular hospitals. Analytical activitie
s also take place both at the centralized Partners level and at ind
ividual hospitals such asMassachusetts General Hospital (MGH)
and Brigham and Women’s Hospital (usually described as “the
Brigham”). In this chapter, bothcentralized and hospital-
specific analytical resources are described. The focus for hospit
al-
specific analytics is the two major teachinghospitals of Partners
—MGH and the Brigham—
although other Partners hospitals also have their own analytical
capabilities and systems.

Centralized Data and Systems at Partners
The basis of any hospital’s clinical information systems is the cl
inical data repository, which contains information on all patient
s, theirconditions, and the treatments they have received. The in
patient clinical data repository for Partners was initially implem
ented at theBrigham during the 1980s. Richard Nesson, the Brig
ham and Women’s CEO, and John Glaser, the hospital’s chief in
formation officer,initiated an outpatient electronic medical reco
rd (EMR) at the Brigham in 1989.1 This EMR contributed outpa
tient data to the clinical datarepository. The hospital was one of
the first to embark on an EMR, though MGH had begun to deve
lop one of the first full-function EMRs asearly as 1976.
A clinical data repository provides the basic data about patients.
Glaser and Nesson came to agree that in addition to a repositor
y and anoutpatient EMR, the Brigham—
and Partners after 1994, when Glaser became its first CIO—
needed facilities for doctors to input onlineorders for drugs, test
s, and other treatments. Online ordering (called CPOE, or Comp
uterized Provider Order Entry) would not only solvethe time-
honored problem of interpreting poor physician handwriting, but
could also, if endowed with a bit of intelligence, check whether
aparticular order made sense or not for a particular patient. Did
a prescribed drug comply with best-
known medical practice, and did thepatient have any adverse rea
ctions in the past to it? Had the same test been prescribed six ti
mes before with no apparent benefit? Was thespecialist to whom
a patient was being referred covered by his or her health plan?
With this type of medical and administrative knowledgebuilt int
o the system, dangerous and time-
consuming errors could be prevented. The Brigham embarked on
its CPOE system in 1989.
Nesson and Glaser knew that there were other approaches to red
ucing medical error than CPOE. Some provider institutions, suc
h asIntermountain Healthcare in Utah, were focused on close ad
herence by physicians to well-
established medical protocols. Others, like KaiserPermanente in

California and the Cleveland Clinic, combined insurance and m
edical practices in ways that incented all providers to workjointl
y on behalf of patients. Nesson and Glaser admired those approa
ches, but felt that their impact would be less in an academic me
dicalcenter such as Partners, where physicians were somewhat a
utonomous, and individual departments prided themselves on th
eir separatereputations for research and practice innovations. Co
mmon, intelligent systems seemed like the best way to improve
patient care atPartners.
In 1994, when the Brigham and Mass General combined as Partn
ers HealthCare System, there was still considerable autonomy fo
rindividual hospitals in the combined organization. However, fr
om the onset of the merger, the two hospitals agreed to use a co
mmonoutpatient EMR called the longitudinal medical record (L
MR) and a CPOE system, both of which were developed at the B
righam. This waspowerful testimony in favor of the LMR and C
POE systems, since there was considerable rivalry between the t
wo hospitals, and MassGeneral had its own EMR.
Perhaps the greatest challenge was in getting the extended netw
ork of Partners-
affiliated physicians up on the LMR and CPOE. Thephysician n
etwork of more than 6,000 practicing generalist and specialist p
hysician groups was scattered around the Boston metropolitanar
ea, and often operated out of their own private offices. Many lac
ked the IT or telecom infrastructures to implement the systems
on theirown, and implementation of an outpatient EMR cost abo
ut $25,000 per physician. Yet full use of the system across Partn
ers-
affiliatedproviders was critical to a seamless patient experience
across the organization.
Glaser and the Partners information systems (IS) organization w
orked diligently to spread the LMR and CPOE to the growing nu
mber ofPartners hospitals and to Partners-
affiliated physicians and medical practices. To assist in bringin
g physicians outside the hospitals onboard, Partners negotiated
payment schedules with insurance companies that rewarded phy

sicians for supplying the kind of informationavailable from the
LMR and CPOE. By 2007, 90% of Partners-
affiliated physicians were using the systems, and by 2009, 100%
were. By2009, more than 1,000 orders per hour were being ente
red through the CPOE system across Partners.
The combination of the LMR and the CPOE proved to be a powe
rful one in helping to avoid medical error. Adverse drug events,
or the useof the wrong drug for the condition or one that caused
an allergic reaction in the patient, typically were encountered b
y about 14 of every1,000 inpatients. At the Brigham before LM
R and CPOE, the number was about 11. After the widespread im
plementation of these systems atBrigham and Women’s, there w
ere just above five adverse drug events per 1,000 inpatients—
a 55% reduction.
Managing Clinical Informatics and Knowledge at Partners
The Clinical Informatics Research & Development (CIRD) grou
p, headed by Blackford Middleton, is one of the key centralized
resources forhealthcare analytics at Partners. Many of CIRD’s st
aff, like Middleton, have multiple advanced degrees; Middleton
has an MD, a Master ofPublic Health degree, and a Master of Sc
ience in Health Services Research.
The mission of CIRD is
to improve the quality and efficiency of care for patients at Part
ners HealthCare System by assuring that the most advancedcurr
ent knowledge about medical informatics (clinical computing) is
incorporated into clinical information systems at PartnersHealt
hCare.2
CIRD is part of the Partners IS organization. It was CIRD’s role
to help create the strategy for how Partners used information sy
stems inpatient care, and to develop both production systems ca
pabilities and pilot projects that employ informatics and analyti
cs. CIRD’s work hadplayed a substantial role in making Partner
s a worldwide leader in the use of data, analysis, and computeri
zed knowledge to improvepatient care. CIRD also has had sever
al projects funded by U.S. government health agencies to adapt
some of the same tools andapproaches it developed for Partners

to the broader healthcare system.
One key function of CIRD was to manage clinical knowledge, a
nd translate healthcare research findings into daily medical prac
tice atPartners. In addition to facilitating adoption of the LMR a
nd CPOE, Partners faced a major challenge in getting control of
the clinicalknowledge that was made available to care provider
s through these and other systems. The “intelligent CPOE” strat
egy demanded thatknowledge be online, accessible, and easily u
pdated so that it could be referenced by and presented to care pr
oviders in real-
timeinteractions with patients. There were, of course, a variety
of other online knowledge tools, such as medical literature searc
hing, available toPartners personnel; in total they were referred
to as the “Partners Handbook.” At one point after use of the CP
OE had become widespreadat Brigham and Women’s, a compari
son was made between online usage of the Handbook and usage
of the knowledge base from orderentry. There were more than 1
3,000 daily accesses through the CPOE system at the Brigham a
lone, and only 3,000 daily accesses of theHandbook by all Partn
ers personnel at all hospitals. Therefore, there was an ongoing e
ffort to ensure that as much high-
quality knowledgeas possible made it into the CPOE.
The problem with knowledge at Partners was not that there wasn
’t enough of it; indeed, the various hospitals, labs, departments,
andindividuals were overflowing with knowledge. The problem
was how to manage it. At one point, Tonya Hongsermeier, a phy
sician with anMBA degree who was charged with managing kno
wledge at Partners, counted the number of places around Partner
s where there wassome form of rule-
based knowledge about clinical practice that was not centrally
managed. She found about 23,000 of them. The knowledgewas c
ontained in a variety of formats: paper documents, computer “sc
reen shots,” process flow diagrams, references, and data or repo
rtson clinical outcomes—
all in a variety of locations, and only rarely shared.
Hongsermeier set out to create a “knowledge engineering and m

anagement” factory that would capture the knowledge at Partner
s, put it ina common format and central repository, and make it
available for CPOE and other online systems. This required not
only a new computersystem for holding the thousands of rules t
hat constituted the knowledge, but an extensive human system f
or gathering, certifying, andmaintaining the knowledge. It consi
sted of the following roles and organizations:
• A set of committees of senior physicians who oversaw clinical
practice in various areas, such as the Partners Drug TherapyCo
mmittee, which reviewed and sanctioned the knowledge as corre
ct or best known practice
• A group of subject matter experts who, using online collaborat
ion systems, debated and refined knowledge such as the best dru
g fortreating high cholesterol under various conditions, or the b
est treatment protocol for diabetes patients
• A cadre of “knowledge editors” who took the approved knowle
dge from these groups and put it into a rule-
based form that wouldbe accepted by the online knowledge repo
sitory
High Performance Medicine at Partners
Glaser and Partners IS had always had the support of senior Part
ners executives, but for the most part their involvement in the a
ctivitiesdesigned to build Partners’ informatics and analytics ca
pabilities was limited to some of the hospitals and those physici
an practices thatwanted to be on the leading edge. Then Jim Mo
ngan moved from being president of MGH (a role he had occupi
ed since 1996, shortly afterthe creation of Partners) to being CE
O of Partners overall in January 2003. Not since Dick Nesson ha
d Glaser had such a strong partner inthe executive suite.
Mongan had come to appreciate the value of the LMR and CPO
E, and other clinical systems, while he headed Mass General. B
ut when hecame into the Partners CEO role, with responsibility
over a variety of diverse and autonomous institutions, he began
to view it differently.Mongan said:
So when I was preparing to make the move to Partners, I began t
o think about what makes a health system. One of the keys that

would unite us was the electronic record. I saw it as the connect
ive tissue, the thing we had in common, that could help us get a
handle on utilization, quality, and other issues.
Together Mongan and Glaser agreed that while Partners already
had strong clinical systems and knowledge management compar
ed toother institutions, a number of weaknesses still needed to b
e addressed (most importantly that the systems were not univers
ally usedacross Partners care settings), and steps needed to be ta
ken to get to the next level of capability. Working with other cli
nical leaders atPartners, they began to flesh out the vision for w
hat came to be known as the High Performance Medicine (HPM)
initiative, which took placebetween 2003 and 2009.
Glaser commented on the process the team followed to specify t
he details of the HPM initiative:
Shortly after he took the reins at Partners, however, Jim had a cl
ear idea on where he wanted this to go. To help refine that visio
n,several of us went on a road trip, to learn from other highly in
tegrated health systems such as Kaiser, Intermountain Healthcar
e,and the Veterans Administration about ways we might bring th
e components of our system closer together.
Mongan concluded:
We also were working with a core team of 15-
20 clinical leaders and eventually came up with a list of seven o
r eight initiatives,which then needed to be prioritized. We did a
“Survivor”-
style voting process, to determine which initiatives to “kick off
the island.”That narrowed down the list to five Signature Initiati
ves.
The five initiatives consisted of the following specific programs
, each of which was addressed by its own team:
• Creating an IT infrastructure—
Much of the initial work of this program had already been done;
it consisted of the LMR and theCPOE, which was extended to t
he other hospitals and physician practices in the Partners networ
k and maintained. This project alsoaddressed patient data qualit
y reporting, further enhancement of knowledge management pro

cesses, and a patient data portal togive patients access to their o
wn health information.
• Enhancing patient safety—
The team addressing patient safety issues focused on four specif
ic projects: 1) providing decisionsupport about what medication
s to administer in several key areas, including renal and geriatri
c dosing; 2) communicating “clinicallysignificant test results,”
particularly to physicians after their patients have left the hospit
al; 3) ensuring effective flow of informationduring patient care t
ransitions and handoffs in hospitals and after discharge; 4) prov
iding better decision support, patient education,and best practic
es and metrics for anticoagulation management.
• Uniform high quality—
This team addressed quality improvement in the specific domain
s of hospital-
based cardiac care,pneumonia, diabetes care, and smoking cessa
tion; it employed both registries and decision support tools to d
o so.
• Chronic disease management—
The team addressing disease management focused on prevention
of hospital admission byidentifying Partners patients who were
at highest risk for hospitalization, and then developed health co
aching programs to addresspatients with high levels of need, for
example, heart failure patients; the team also pulled together a
new database of informationabout patient wishes about end-of-
life decisions.
• Clinical resource management—
At Jim Mongan’s suggestion, this team focused on how to lower
the usage of high-cost drugs andhigh-
cost imaging services; it employed both “low-
tech” methods (e.g., chart reviews) and “high-
tech” approaches (e.g., a datawarehouse making transparent phy
sicians’ imaging behaviors relative to peers) to begin to make u
se of scarce resources moreefficiently.
Overall, Partners spent about $100 million on HPM and related
clinical systems initiatives, most of which were ultimately paid

for by thePartners hospitals and physician practices that used th
em. To track progress, a Partners-
wide report, called the HPM Close, was developedthat shows cu
rrent and trend performance on the achievement of quality, effic
iency, and structural goals. The report was publishedquarterly t
o ensure timely feedback for measuring performance and suppor
ting accountability across Partners.
New Analytical Challenges for Partners
Partners had made substantial progress on many of the basic app
roaches to clinical analytics, but there were many other areas at
theintersection of health and analytics that it could still address.
One was the area of personalized genetic medicine—
the idea that patientswould someday receive specific therapies b
ased on their genomic, proteomic, and metabolic information. P
artners had created the i2b2(Informatics for Integrating Biology
and the Bedside), a National Center for Biomedical Computing
that was funded by the NationalInstitutes of Health. John Glaser
was co-
director of i2b2 and developed the IT infrastructure for the Part
ners Center for PersonalizedGenetic Medicine. One of the many
issues these efforts addressed in personalized genetic medicine
was how relevant genetic informationwould be included in the L
MR.
Partners was also attempting to use clinical information for post
market surveillance—
the identification of problems with drugs and medicaldevices in
patients after they have been released to the market. Some Partn
ers researchers had identified dangerous side effects fromcertain
drugs through analysis of LMR data. Specifically, research scie
ntist John Brownstein’s analyses suggested that the level of pati
entswith heart attack admissions to Mass General and the Brigh
am had increased 18% beginning in 2001 and returned to its bas
eline level in2004, which coincided with the timeframe for the b
eginning and end of Vioxx prescriptions. Thus far the identifica
tion of problems hadtaken place only after researchers from oth
er institutions had identified them, but Partners executives belie

ved it had the ability to identifythem at an earlier stage. The ins
titution was collaborating with the Food and Drug Administratio
n and the Department of Defense toaccelerate the surveillance p
rocess. John Glaser noted:
I don’t know that we’ll get as much specificity as might be need
ed to really challenge whether a drug ought to be in a market, b
ut Ialso think it’s fairly clear that you can be much faster and in
volve much fewer funds, frankly, to do what we would call the “
canaryin the mine” approach.3
Partners was also focused on the use of communications technol
ogies to improve patient care. Its Center for Connected Health,
headed byDr. Joe Kvedar, developed one of the first physician-
to-
physician online consultation services in an academic medical s
etting. The Center wasalso exploring combinations of remote m
onitoring technologies, sensors (for example, pill boxes that kno
w whether today’s dosage hasbeen taken), and online communic
ations and intelligence to improve patient adherence to medicati
on regimes, engagement in personalhealth, and clinical outcome
s.
In the clinical knowledge management area, Partners had done a
n impressive job of organizing and maintaining the many rules a
ndknowledge bases that informed its “intelligent” CPOE system.
However, it was apparent to Glaser, Blackford Middleton, and
TonyaHongsermeier—
and her successor as head of knowledge management, Roberto R
ocha—
that it made little sense for each medicalinstitution to develop it
s own knowledge base. Therefore, Partners was actively engage
d in helping other institutions with the managementof clinical k
nowledge. Middleton (the principal investigator), Hongsermeier,
Rocha, and at least 13 other Partners employees were involvedi
n a major Clinical Decision Support Consortium project funded
by the U.S. Agency for Healthcare Research and Quality. The c
onsortiuminvolved a variety of other research institutions and h
ealthcare companies, and was primarily focused on finding ways

to make clinicalknowledge widely available to healthcare provi
ders through EMR and CPOE systems furnished by leading vend
ors.
Despite all these advances, not all Partners executives and physi
cians had fully bought into the vision of using smart informatio
n systems toimprove patient care. Some found, for example, the
LMR and CPOE to be invasive in the relationship of doctor and
patient. A seniorcardiologist at Brigham and Women’s, for exa
mple, argued in an interview [with the author] that:
I have a problem with the algorithmic approach to medicine. Pe
ople end up making rote decisions that don’t fit the patient, and
itcan also be medically quite wasteful. I don’t have any choice h
ere if I want to write prescriptions—
virtually all of them are doneonline. But I must say that I am ge
tting alert fatigue. Every time I write a prescription for nitrogly
cerine, I am given an alert thatasks me to ensure that my patient
isn’t on Viagra. Don’t you think I know that at this point? As f
or online treatment guidelines, Ibelieve in them up to a point. B
ut once something is in computerized guidelines it’s sacrosanct,
whether or not the data arelegitimate. Recommendations should
be given with notification of how certain we are about them....
Maybe these things are moreuseful to some doctors than others.
If you’re in a subspecialty like cardiology you know it very well
. But if you are an internist, youmay have shallow knowledge, b
ecause you have to cover a wide variety of medical issues.
Many of the people involved in developing computer systems fo
r patient care at Partners regarded these as valid concerns. “Aler
t fatigue,”for example, had been recognized as a problem within
Blackford Middleton’s group for several years. They had tried t
o eliminate the moreobvious alerts, and to make changes in the
system to allow physicians to modify the types of alerts they rec
eived. There was a difficult lineto draw, however, between savi
ng physician attention and saving lives.
Centralized Business Analytics at Partners
While much of the centralized analytical activity at Partners has
been on the clinical side, the organization is also making progr

ess onbusiness analytics. The primary focus of these efforts is o
n financial reporting and analysis.
For several years, for example, Partners has employed an extern
al “software as a service” tool to provide reporting on the organ
ization’srevenue cycle. It has also developed several customized
analytics applications in the areas of cash management, underp
ayments, bad debtreserves, and charge capture. These activities
primarily took place in the Partners Revenue Finance function.
The Partners Information Systems organization is also increasin
g its focus on administrative and financial analytics. It is puttin
g in placeCompass, a common billing and administrative system
, at all Partners hospitals. At the same time, Partners has created
a set of standardprocesses for collecting, defining, and modifyi
ng financial and administrative data. Further, as one article put i
t:
At Partners, John Stone, corporate director for financial and ad
ministrative systems, is developing a corporate center of busine
ssanalytics and business intelligence. Some 12 to 14 financial e
xecutives will oversee the center, define Partners’ strategy for d
atamanagement, and determine data-
related budget priorities. “Our analysts spend the majority of th
eir time gathering, cleaning, andscrubbing administrative data a
nd less time providing value-
added analytics and insight into what the data is saying,” says S
tone.“We want to flip that equation so our analysts are spending
more time producing a story that goes along with the data.”4
Hospital-Specific Analytical Activities—
Massachusetts General Hospital
MGH, because it was a highly research-
driven institution, had long focused primarily on clinical resear
ch and the resulting clinicalinformatics and analytics. In additio
n to the LMR and CPOE systems used by Partners overall, MGH
researchers and staff have developed anumber of IT tools to an
alyze and search clinical data, one of which was a tool that sear
ched across multiple enterprise clinical systems,including the L
MR.

While historically, the research, clinical, information systems, a
nd the analytically focused business arms of MGH tended to ope
rate in stovepipes, the challenges of an evolving healthcare land
scape have forced a change in that paradigm. For instance, a str
ong current focus withinMGH is on how to achieve federal “mea
ningful use” reimbursement for the organization’s expenditures
on EMR. Because achievingmeaningful use objectives is predica
ted on a high level of coordination among information systems,
the physicians, and businessintelligence, people like David Y. T
ing, the associate medical director for Information Systems for
MGH and Massachusetts GeneralPhysicians Organization, and C
hris Hutchins, the director of Finance Systems and deputy CIO,
are beginning to collaborate extensively.
The HITECH/ARRA criteria for Stage 1 EMR meaningful use pr
escribe 25 specific objectives to incentivize providers to adopt a
nd useelectronic health records.5
To raise the level of EMR use by all its providers, as well as to
provide resources for the work needed to achieve that level, MG
H has arrivedat a novel funds distribution model. They determin
ed that the physicians organization will reserve a portion of the
pool of $44,000 perphysician toward IT and analytics infrastruct
ure, then distribute the remaining incentive payment across all p
roviders, proportional to theamount of data a particular physicia
n is charged with entering. An internal quality incentive progra
m would serve as the distributionmechanism. So, for example, if
you recorded demographics, vital signs, and smoking status for
the requisite number of patients, you wouldreceive 30% of the p
er-
physician payment from the pool. If you fulfilled all ten quality
measures, you would receive 100% of the paymentfrom the pool
. This encourages all physicians to contribute to the meaningful
use program, but it also means that no physicians will receiveth
e full amount of $44,000. The incentive from the federal govern
ment is up to $44,000 for each eligible provider who fulfills the
meaningful use criteria. MGH has examined the objectives and
broken them down into ten major pieces of patient data that phy

sicians needto record in the EMR. However, many are not releva
nt for all of its physicians. For example, a primary care physicia
n would logically entersuch data as demographics, vital signs, a
nd smoking status, but these would be less relevant for certain s
pecialists to enter.
Clearly, such a complex quality incentive model requires an unp
recedented level of analytics. Currently, Ting, Hutchins, and oth
ers at MGHare working to map the myriad clinical and finance d
ata sources that are scattered among individual departments, exi
st at a hospital sitelevel, or exist at the Partners enterprise level.
Simultaneously, they must negotiate data governance agreemen
ts even among other Partnersentities, to ensure that the requisite
data feeds from sources within Partners and pertaining to MGH
, but stored outside MGH’s physical datawarehouses, are availa
ble for MGH analytics purposes.
MGH has some experience with reimbursement metrics based on
physician behaviors, having used them in Partners Community
HealthCare, Inc. (PCHI), its physician network in the Boston ar
ea. Physician incentives have been provided through PCHI on th
e basis ofadmission rates, cost-
effective use of pharmacy and imaging services, and screening f
or particular diseases and conditions, such as diabetes. This was
also the mechanism used to encourage the adoption of the LMR
and CPOE systems by physicians. But MGH, like otherprovider
s, struggles with developing clear and transparent metrics across
the institution that can help to drive awareness and newbehavio
rs. If MGH could create broadly accessible metrics on individua
l physicians’ frequency of prescribing generic drugs, for exampl
e, itwould undoubtedly drive MGH’s competitive physicians to
excel in the rankings.
On the business side, MGH is trying to develop a broad set of c
apabilities in business intelligence and analytics. A BusinessInt
elligence/Performance Management group has recently been cre
ated under the direction of Chris Hutchins, deputy CIO and dire
ctor offinance systems for the Mass General Physicians Organiz
ation (MGPO). The group is generating reports on such financia

l and administrativetopics as
• Billing efficiency, claims adjudication, rejection rates, and tim
es to resolve billing accounts, both at MGH overall and across p
ractices
• Improving patient access, average wait times to see a physicia
n, and cancellation and no show rates
• Employer attrition as an MGH customer
MGH is also working with CMS on the Physician Quality Repor
ting Initiative. To combine all these measures in a meaningful f
ashion, MGPO isalso working on a balanced scorecard.6
While the current analytical activity is largely around reporting,
Hutchins plans to develop more capabilities around alerts, exce
ptionreporting, and predictive models. The MGH Physicians Or
ganization is implementing capabilities for statistical and predic
tive analytics thatwould be applied to several topics. For examp
le, one key area in which better prediction would be useful invo
lves patient volume. They arealso pursuing more general models
that would predict shifts in business over time. At the moment,
however, Hutchins feels that thescorecard is still early in its dev
elopment and current efforts are focused on identifying leading
indicators.
Hospital-Specific Analytical Activities—
Brigham and Women’s Hospital
Like MGH, the Brigham’s analytical activities in the past have
been largely focused on clinical research. Today it is also addre
ssing much ofthe same business, operational, and meaningful us
e issues that MGH is. Many of the analytical activities at the Br
igham are pursued by theCenter for Clinical Excellence (CCE),
which was founded by Dr. Michael Gustafson in 2001. The cent
er has five functionally interrelatedsections, including
• Quality programs
• Patient safety
• Performance improvement
• Decision support systems (including all internal and external d
ata management and reporting activities)
• Analysis and planning (which oversees business plan develop

ment, ROI assessments for major investments, cost benchmarkin
g,asset utilization reporting, and support for strategic planning)
The CCE has close working relationships with the Brigham’s C
FO and finance organizations, the Brigham’s information syste
msorganization, the Partners Business Development and Plannin
g function, and other centers and medical departments at the Bri
gham.
One major difference between the Brigham and MGH (and most
other hospitals, for that matter) is that the Brigham established
a balancedscorecard beginning in 2000. It was based on a well-
established cultural orientation to operational and quality metric
s throughout thehospital. Richard Nesson, the Brigham CEO wh
o had partnered with CIO John Glaser to introduce the LMR and
CPOE systems, was also astrong advocate of information-
driven decision making on both the clinical and business sides o
f the hospital. The original systems thatNesson and Glaser had e
stablished also incorporated a reporting tool called EX, and a da
ta warehouse called CHASE (ComputerizedHospital Analysis Sy
stem for Efficiency). The analyses and data from these systems
formed the core of the Brigham’s balanced scorecard.
Before an effective scorecard could be developed, the Brigham
had to undertake considerable work on data definitions and man
agement.One analysis discovered, for example, that there were f
ive different definitions of the length of a patient stay circulatin
g in 11 differentreports. The chief medical officer at the time, D
r. Andy Whittemore, and the CCE’s Dr. Gustafson, a surgeon w
ho had just taken on qualitymeasurement issues at the Brigham,
addressed these data issues with a senior executive steering com
mittee and decided to present thedata in an easy-to-
digest scorecard.
Under the ongoing management of the CCE, the scorecard conta
ins a variety of financial, operational, and clinical metrics from
across thehospital. The choice of metrics is driven by a “strateg
y map”7 specifying the relationships among key variables that d
rive the performance ofthe hospital (see Figure 18.1). Unlike m
ost corporate strategy maps, financial performance variables are

at the bottom of the map ratherthan the top. In the scorecard its
elf, there are more than 50 specific measures in the hospital-
wide scorecard, and more detailed scorecardsfor particular depa
rtments, such as Nursing and Surgery. The scorecard has also be
en extended to Faulkner Hospital, a Partners institutionthat is m
anaged jointly with the Brigham.
Figure 18.1 Strategy map for Brigham & Women’s balanced sco
recard
Dr. Gary Gottlieb, the Brigham president from 1992 to 2009, wa
s the most aggressive user of the scorecard. He noted:
I review the balanced scorecard on a regular basis, because ther
e is specific data that is of interest to me. There are key metrics
Iexamine for trends and if they develop, then I analyze the data
to better understand what is going right or wrong. It is one view
,but an important one of our hospital. I can look at the balanced
scorecard and get information in another way, from a differentp
erspective than I can when I’m making rounds on a hospital unit
, or sitting in the meeting with chiefs.8
Gottlieb left the Brigham CEO role to become the CEO of Partn
ers overall in 2010. One of the primary initiatives in his new Pa
rtners role isto expand the degree of common systems throughou
t Partners, so that there can be common data and analytics throu
ghout theorganization. Perhaps one day all of Partners HealthCa
re System will be managed through one scorecard.
Notes
1. This and other details of the Partners LMR/CPOE systems are
derived from Richard Kesner, “Partners Healthcare System:Tra
nsforming Healthcare Services Delivery Through Information M
anagement,” Ivey School of Business Case Study (2009).
2. “CIRD, Clinical Informatics Research & Development,” http:
//www.partners.org/cird/.
3. PricewaterhouseCoopers, “Partners HealthCare: Using EHR
Data for Post-
market Surveillance of Drugs” (2009). http://pwchealth.com/cgi
-local/hregister.cgi/reg/partners_healthcare_case_study.pdf.

4. Healthcare Financial Management Association, “Developing
a Meaningful EHR,” http://www.hfma.org/Publications/Leaders
hip-Publication/Archives/Special-Reports/Spring-
2010/Developing-a-Meaningful-
EHR/, Part 3 of “Leadership Spring-
Summer 2010Report: Collaborating for Results.”
5. The 25 meaningful use criteria are described in “Eligible Pro
vider: ‘Meaningful Use’ Criteria,” by Jack Beaudoin, Healthcar
e IT News,December 30, 2009, http://www.healthcareitnews.co
m/news/eligible-provider-meaningful-use-criteria.
6. Robert S. Kaplan and David P. Norton, “The Balanced Scorec
ard: Measures that Drive Performance,” Harvard Business Revie
w (January– February 1992).
7. Robert S. Kaplan and David P. Norton, “Having Trouble With
Your Strategy? Then Map It,” Harvard Business Review (Septe
mber –October, 2000).
8. Ibid.
· Notebook
Davenport, T., & McNeill, D. (2014). Analytics in healthcare
and the life sciences: Strategies,implementation, methods, and
best practices. Retrieved from https://content.ashford.edu
SWOT Analysis Worksheet
Fill out the fields below and review with a mentor. This
information can help you outline goals and strategies for your
business and marketing efforts.
Strengths
Weaknesses
Opportunities
Threats
Product/ Service Offering

Brand/ Marketing
Staff/ HR
Finance
Operations/ Management
Market
Can any of your strengths help with improving your weaknesses
or combating your threats? If so, please describe how below.
Based on the information above, what are your immediate

goals/next steps?
Based on the information above, what are your long-term
goals/next steps?

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