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Partners healthcare case study analysis

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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 provider of healthcare in the Boston area. It consists of 12 hospitals, with morethan 7,000 affiliated physicians. It has 4 million outpatient 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 autonomy at each of its member hospitals. While some information systems(the electronic medical record, for example) are standardized across Partners, other systems and data, such as patient scheduling, arespecific to particular hospitals. Analytical activities also take place both at the centralized Partners level and at individual 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 hospital-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 clinical data repository, which contains information on all patients, theirconditions, and the treatments they have received. The inpatient clinical data repository for Partners was initially implemented at theBrigham during the 1980s. Richard Nesson, the Brigham and Women’s CEO, and John Glaser, the hospital’s chief information officer,initiated an outpatient electronic medical record (EMR) at the Brigham in 1989.1 This EMR contributed outpatient data to the clinical datarepository. The hospital was one of the first to embark on an EMR, though MGH had begun to develop 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 repository and anoutpatient EMR, the Brigham—and Partners after 1994, when Glaser became its first CIO—needed facilities for doctors to input onlineorders for drugs, tests, and other treatments. Online ordering (called CPOE, or Computerized 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 reactions in the past to it? Had the same test been prescribed six times 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 into 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 reducing medical error than CPOE. Some provider institutions, such asIntermountain Healthcare in Utah, were focused on close adherence by physicians to well-established medical protocols. Others, like KaiserPermanente in California and the Cleveland Clinic, combined insurance and medical practices in ways that incented all providers to workjointly on behalf of patients. Nesson and Glaser admired those approaches, but felt that their impact would be less in an academic medicalcenter such as Partners, where physicians were somewhat autonomous, and individual departments prided themselves on their separatereputations for research and practice innovations. Common, intelligent systems seemed like the best way to improve patient care atPartners.

In 1994, when the Brigham and Mass General combined as Partners HealthCare System, there was still considerable autonomy forindividual hospitals in the combined organization. However, from the onset of the merger, the two hospitals agreed to use a commonoutpatient EMR called the longitudinal medical record (LMR) and a CPOE system, both of which were developed at the Brigham. This waspowerful testimony in favor of the LMR and CPOE systems, since there was considerable rivalry between the two hospitals, and MassGeneral had its own EMR.

Perhaps the greatest challenge was in getting the extended network of Partners-affiliated physicians up on the LMR and CPOE. Thephysician network of more than 6,000 practicing generalist and specialist physician groups was scattered around the Boston metropolitanarea, and often operated out of their own private offices. Many lacked the IT or telecom infrastructures to implement the systems on theirown, and implementation of an outpatient EMR cost about $25,000 per physician. Yet full use of the system across Partners-affiliatedproviders was critical to a seamless patient experience across the organization.

Glaser and the Partners information systems (IS) organization worked diligently to spread the LMR and CPOE to the growing number ofPartners hospitals and to Partners-affiliated physicians and medical practices. To assist in bringing physicians outside the hospitals onboard, Partners negotiated payment schedules with insurance companies that rewarded physicians 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 entered through the CPOE system across Partners.

The combination of the LMR and the CPOE proved to be a powerful 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 by about 14 of every1,000 inpatients. At the Brigham before LMR and CPOE, the number was about 11. After the widespread implementation of these systems atBrigham and Women’s, there were 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) group, headed by Blackford Middleton, is one of the key centralized resources forhealthcare analytics at Partners. Many of CIRD’s staff, like Middleton, have multiple advanced degrees; Middleton has an MD, a Master ofPublic Health degree, and a Master of Science in Health Services Research.

The mission of CIRD is

to improve the quality and efficiency of care for patients at Partners HealthCare System by assuring that the most advancedcurrent knowledge about medical informatics (clinical computing) is incorporated into clinical information systems at PartnersHealthCare.2

CIRD is part of the Partners IS organization. It was CIRD’s role to help create the strategy for how Partners used information systems inpatient care, and to develop both production systems capabilities and pilot projects that employ informatics and analytics. CIRD’s work hadplayed a substantial role in making Partners a worldwide leader in the use of data, analysis, and computerized knowledge to improvepatient care. CIRD also has had several 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, and translate healthcare research findings into daily medical practice atPartners. In addition to facilitating adoption of the LMR and CPOE, Partners faced a major challenge in getting control of the clinicalknowledge that was made available to care providers through these and other systems. The “intelligent CPOE” strategy demanded thatknowledge be online, accessible, and easily updated so that it could be referenced by and presented to care providers in real-timeinteractions with patients. There were, of course, a variety of other online knowledge tools, such as medical literature searching, available toPartners personnel; in total they were referred to as the “Partners Handbook.” At one point after use of the CPOE had become widespreadat Brigham and Women’s, a comparison was made between online usage of the Handbook and usage of the knowledge base from orderentry. There were more than 13,000 daily accesses through the CPOE system at the Brigham alone, and only 3,000 daily accesses of theHandbook by all Partners personnel at all hospitals. Therefore, there was an ongoing effort 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 physician with anMBA degree who was charged with managing knowledge at Partners, counted the number of places around Partners 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 contained in a variety of formats: paper documents, computer “screen shots,” process flow diagrams, references, and data or reportson clinical outcomes—all in a variety of locations, and only rarely shared.

Hongsermeier set out to create a “knowledge engineering and management” factory that would capture the knowledge at Partners, 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 that constituted the knowledge, but an extensive human system for gathering, certifying, andmaintaining the knowledge. It consisted 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 TherapyCommittee, which reviewed and sanctioned the knowledge as correct or best known practice

• A group of subject matter experts who, using online collaboration systems, debated and refined knowledge such as the best drug fortreating high cholesterol under various conditions, or the best treatment protocol for diabetes patients

• A cadre of “knowledge editors” who took the approved knowledge from these groups and put it into a rule-based form that wouldbe accepted by the online knowledge repository

High Performance Medicine at Partners

Glaser and Partners IS had always had the support of senior Partners executives, but for the most part their involvement in the activitiesdesigned to build Partners’ informatics and analytics capabilities was limited to some of the hospitals and those physician practices thatwanted to be on the leading edge. Then Jim Mongan moved from being president of MGH (a role he had occupied since 1996, shortly afterthe creation of Partners) to being CEO of Partners overall in January 2003. Not since Dick Nesson had Glaser had such a strong partner inthe executive suite.

Mongan had come to appreciate the value of the LMR and CPOE, and other clinical systems, while he headed Mass General. But 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 to think about what makes a health system. One of the keys thatwould unite us was the electronic record. I saw it as the connective tissue, the thing we had in common, that could help us get ahandle on utilization, quality, and other issues.

Together Mongan and Glaser agreed that while Partners already had strong clinical systems and knowledge management compared toother institutions, a number of weaknesses still needed to be addressed (most importantly that the systems were not universally usedacross Partners care settings), and steps needed to be taken to get to the next level of capability. Working with other clinical leaders atPartners, they began to flesh out the vision for what 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 the details of the HPM initiative:

Shortly after he took the reins at Partners, however, Jim had a clear idea on where he wanted this to go. To help refine that vision,several of us went on a road trip, to learn from other highly integrated health systems such as Kaiser, Intermountain Healthcare,and the Veterans Administration about ways we might bring the 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 or 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 Initiatives.

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 the other hospitals and physician practices in the Partners network and maintained. This project alsoaddressed patient data quality reporting, further enhancement of knowledge management processes, and a patient data portal togive patients access to their own health information.

• Enhancing patient safety—The team addressing patient safety issues focused on four specific projects: 1) providing decisionsupport about what medications to administer in several key areas, including renal and geriatric dosing; 2) communicating “clinicallysignificant test results,” particularly to physicians after their patients have left the hospital; 3) ensuring effective flow of informationduring patient care transitions and handoffs in hospitals and after discharge; 4) providing better decision support, patient education,and best practices and metrics for anticoagulation management.

• Uniform high quality—This team addressed quality improvement in the specific domains of hospital-based cardiac care,pneumonia, diabetes care, and smoking cessation; it employed both registries and decision support tools to do 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 coaching 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 physicians’ imaging behaviors relative to peers) to begin to make use 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 them. To track progress, a Partners-wide report, called the HPM Close, was developedthat shows current and trend performance on the achievement of quality, efficiency, and structural goals. The report was publishedquarterly to ensure timely feedback for measuring performance and supporting accountability across Partners.

New Analytical Challenges for Partners

Partners had made substantial progress on many of the basic approaches 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 based on their genomic, proteomic, and metabolic information. Partners 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 Partners 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 LMR.

Partners was also attempting to use clinical information for postmarket surveillance—the identification of problems with drugs and medicaldevices in patients after they have been released to the market. Some Partners researchers had identified dangerous side effects fromcertain drugs through analysis of LMR data. Specifically, research scientist John Brownstein’s analyses suggested that the level of patientswith heart attack admissions to Mass General and the Brigham had increased 18% beginning in 2001 and returned to its baseline level in2004, which coincided with the timeframe for the beginning and end of Vioxx prescriptions. Thus far the identification of problems hadtaken place only after researchers from other institutions had identified them, but Partners executives believed it had the ability to identifythem at an earlier stage. The institution was collaborating with the Food and Drug Administration and the Department of Defense toaccelerate the surveillance process. John Glaser noted:

I don’t know that we’ll get as much specificity as might be needed to really challenge whether a drug ought to be in a market, but Ialso think it’s fairly clear that you can be much faster and involve 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 technologies 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 setting. The Center wasalso exploring combinations of remote monitoring technologies, sensors (for example, pill boxes that know whether today’s dosage hasbeen taken), and online communications and intelligence to improve patient adherence to medication regimes, engagement in personalhealth, and clinical outcomes.

In the clinical knowledge management area, Partners had done an impressive job of organizing and maintaining the many rules andknowledge 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 Rocha—that it made little sense for each medicalinstitution to develop its own knowledge base. Therefore, Partners was actively engaged in helping other institutions with the managementof clinical knowledge. Middleton (the principal investigator), Hongsermeier, Rocha, and at least 13 other Partners employees were involvedin a major Clinical Decision Support Consortium project funded by the U.S. Agency for Healthcare Research and Quality. The consortiuminvolved a variety of other research institutions and healthcare companies, and was primarily focused on finding ways to make clinicalknowledge widely available to healthcare providers through EMR and CPOE systems furnished by leading vendors.

Despite all these advances, not all Partners executives and physicians had fully bought into the vision of using smart information 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 example, argued in an interview [with the author] that:

I have a problem with the algorithmic approach to medicine. People end up making rote decisions that don’t fit the patient, and itcan also be medically quite wasteful. I don’t have any choice here if I want to write prescriptions—virtually all of them are doneonline. But I must say that I am getting alert fatigue. Every time I write a prescription for nitroglycerine, 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 for online treatment guidelines, Ibelieve in them up to a point. But 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, because you have to cover a wide variety of medical issues.

Many of the people involved in developing computer systems for patient care at Partners regarded these as valid concerns. “Alert fatigue,”for example, had been recognized as a problem within Blackford Middleton’s group for several years. They had tried to eliminate the moreobvious alerts, and to make changes in the system to allow physicians to modify the types of alerts they received. There was a difficult lineto draw, however, between saving 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 progress onbusiness analytics. The primary focus of these efforts is on financial reporting and analysis.

For several years, for example, Partners has employed an external “software as a service” tool to provide reporting on the organization’srevenue cycle. It has also developed several customized analytics applications in the areas of cash management, underpayments, bad debtreserves, and charge capture. These activities primarily took place in the Partners Revenue Finance function.

The Partners Information Systems organization is also increasing its focus on administrative and financial analytics. It is putting 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 modifying financial and administrative data. Further, as one article put it:

At Partners, John Stone, corporate director for financial and administrative systems, is developing a corporate center of businessanalytics and business intelligence. Some 12 to 14 financial executives will oversee the center, define Partners’ strategy for datamanagement, and determine data-related budget priorities. “Our analysts spend the majority of their time gathering, cleaning, andscrubbing administrative data and less time providing value-added analytics and insight into what the data is saying,” says Stone.“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 research and the resulting clinicalinformatics and analytics. In addition to the LMR and CPOE systems used by Partners overall, MGH researchers and staff have developed anumber of IT tools to analyze and search clinical data, one of which was a tool that searched across multiple enterprise clinical systems,including the LMR.

While historically, the research, clinical, information systems, and the analytically focused business arms of MGH tended to operate in stovepipes, the challenges of an evolving healthcare landscape have forced a change in that paradigm. For instance, a strong current focus withinMGH is on how to achieve federal “meaningful use” reimbursement for the organization’s expenditures on EMR. Because achievingmeaningful use objectives is predicated on a high level of coordination among information systems, the physicians, and businessintelligence, people like David Y. Ting, the associate medical director for Information Systems for MGH and Massachusetts GeneralPhysicians Organization, and Chris Hutchins, the director of Finance Systems and deputy CIO, are beginning to collaborate extensively.

The HITECH/ARRA criteria for Stage 1 EMR meaningful use prescribe 25 specific objectives to incentivize providers to adopt and 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, MGH has arrivedat a novel funds distribution model. They determined that the physicians organization will reserve a portion of the pool of $44,000 perphysician toward IT and analytics infrastructure, then distribute the remaining incentive payment across all providers, proportional to theamount of data a particular physician is charged with entering. An internal quality incentive program 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 per-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 receivethe full amount of $44,000. The incentive from the federal government is up to $44,000 for each eligible provider who fulfills themeaningful use criteria. MGH has examined the objectives and broken them down into ten major pieces of patient data that physicians needto record in the EMR. However, many are not relevant for all of its physicians. For example, a primary care physician would logically entersuch data as demographics, vital signs, and smoking status, but these would be less relevant for certain specialists to enter.

Clearly, such a complex quality incentive model requires an unprecedented level of analytics. Currently, Ting, Hutchins, and others at MGHare working to map the myriad clinical and finance data sources that are scattered among individual departments, exist at a hospital sitelevel, or exist at the Partners enterprise level. Simultaneously, they must negotiate data governance agreements 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 available for MGH analytics purposes.

MGH has some experience with reimbursement metrics based on physician behaviors, having used them in Partners CommunityHealthCare, Inc. (PCHI), its physician network in the Boston area. Physician incentives have been provided through PCHI on the basis ofadmission rates, cost-effective use of pharmacy and imaging services, and screening for 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 otherproviders, struggles with developing clear and transparent metrics across the institution that can help to drive awareness and newbehaviors. If MGH could create broadly accessible metrics on individual physicians’ frequency of prescribing generic drugs, for example, 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 capabilities in business intelligence and analytics. A BusinessIntelligence/Performance Management group has recently been created under the direction of Chris Hutchins, deputy CIO and director offinance systems for the Mass General Physicians Organization (MGPO). The group is generating reports on such financial and administrativetopics as

• Billing efficiency, claims adjudication, rejection rates, and times to resolve billing accounts, both at MGH overall and across practices

• Improving patient access, average wait times to see a physician, and cancellation and no show rates

• Employer attrition as an MGH customer

MGH is also working with CMS on the Physician Quality Reporting Initiative. To combine all these measures in a meaningful fashion, 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, exceptionreporting, and predictive models. The MGH Physicians Organization is implementing capabilities for statistical and predictive analytics thatwould be applied to several topics. For example, one key area in which better prediction would be useful involves 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 development 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 addressing much ofthe same business, operational, and meaningful use issues that MGH is. Many of the analytical activities at the Brigham are pursued by theCenter for Clinical Excellence (CCE), which was founded by Dr. Michael Gustafson in 2001. The center has five functionally interrelatedsections, including

• Quality programs

• Patient safety

• Performance improvement

• Decision support systems (including all internal and external data management and reporting activities)

• Analysis and planning (which oversees business plan development, ROI assessments for major investments, cost benchmarking,asset utilization reporting, and support for strategic planning)

The CCE has close working relationships with the Brigham’s CFO and finance organizations, the Brigham’s information systemsorganization, the Partners Business Development and Planning function, and other centers and medical departments at the Brigham.

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 metrics throughout thehospital. Richard Nesson, the Brigham CEO who 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 of the hospital. The original systems thatNesson and Glaser had established also incorporated a reporting tool called EX, and a data warehouse called CHASE (ComputerizedHospital Analysis System 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 management.One analysis discovered, for example, that there were five different definitions of the length of a patient stay circulating in 11 differentreports. The chief medical officer at the time, Dr. Andy Whittemore, and the CCE’s Dr. Gustafson, a surgeon who had just taken on qualitymeasurement issues at the Brigham, addressed these data issues with a senior executive steering committee and decided to present thedata in an easy-to-digest scorecard.

Under the ongoing management of the CCE, the scorecard contains a variety of financial, operational, and clinical metrics from across thehospital. The choice of metrics is driven by a “strategy map”7 specifying the relationships among key variables that drive the performance ofthe hospital (see Figure 18.1). Unlike most corporate strategy maps, financial performance variables are at the bottom of the map ratherthan the top. In the scorecard itself, there are more than 50 specific measures in the hospital-wide scorecard, and more detailed scorecardsfor particular departments, such as Nursing and Surgery. The scorecard has also been extended to Faulkner Hospital, a Partners institutionthat is managed jointly with the Brigham.

image

Figure 18.1 Strategy map for Brigham & Women’s balanced scorecard

Dr. Gary Gottlieb, the Brigham president from 1992 to 2009, was the most aggressive user of the scorecard. He noted:

I review the balanced scorecard on a regular basis, because there 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 differentperspective 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 Partners overall in 2010. One of the primary initiatives in his new Partners role isto expand the degree of common systems throughout Partners, so that there can be common data and analytics throughout theorganization. Perhaps one day all of Partners HealthCare 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:Transforming Healthcare Services Delivery Through Information Management,” 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/Leadership-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 Provider: ‘Meaningful Use’ Criteria,” by Jack Beaudoin, Healthcare IT News,December 30, 2009, http://www.healthcareitnews.com/news/eligible-provider-meaningful-use-criteria.

6 . Robert S. Kaplan and David P. Norton, “The Balanced Scorecard: Measures that Drive Performance,” Harvard Business Review (January– February 1992).

7 . Robert S. Kaplan and David P. Norton, “Having Trouble With Your Strategy? Then Map It,” Harvard Business Review (September –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

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