HIT AND HSR FOR ACTIONABLE KNOWLEDGE:
HEALTH SYSTEM SUMMARY
PARTNER: Geisinger Health System
Organization and IT Infrastructure
Organizational Description and History
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Geisinger Health System is an integrated health care delivery system serving 31 of Pennsylvania’s 67 counties mainly in central and northeast parts of the state.
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The health system comprises the Geisinger Clinic (GC), which provides ambulatory care, three hospitals, a clinical laboratory, and the Geisinger Health
Plan, a risk-bearing HMO with a closed panel of employed physicians.
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The GC includes 780 physicians and physician’s assistants, 41 outpatient community practice sites, and two ambulatory surgery centers.
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The health system treats 350,000 primary care and 700,000 specialty care patients annually.
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Geisinger Health Plan is an independent business with 230,000 members, about
50 percent of whom get most of their care from the GC.
Electronic Health Record (EHR) History
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Geisinger installed the EpicCare EHR in all GC community practice sites between
1996 and 2001.
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The inpatient EpicCare EHR was implemented in 2008 along with an IBMdeveloped enterprise data warehouse (EDW) referred to as the Clinical Decision
Intelligence System (CDIS).
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T o support its culture of continuous improvement, Geisinger maintains the
Research IT Environment (RITE), which is an R&D “sandbox” with restricted access to a clone of the EHR data used to test new clinical software tools.
Research Influence in EHR Design
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The design of Geisinger’s IT systems has evolved in part with input from researchers as part of the organization’s R&D approach to innovation to improve the quality and efficiency of health care (described under “Research Capabilities” below).

Data Management
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Geisinger’s CDIS is used by administrators; business analysts, health services and clinical researchers, and Geisinger’s Innovations Team (see “Research
Capabilities” below).
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CDIS functions as an “operational data store”—a centralized database that connects different data sets, but doesn’t put data from those data sets into a single database.
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A stand-alone, de-identified clone of CDIS that is used to create IRB-approved research data files is managed by the Center for Health Research.
Data Available For Research
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The data available for research include: o Patient demographics, vitals, clinical measures, problem list, medical history, medication history, personal and family histories. o Patient encounter data. o Orders for laboratory tests, medications, imaging and procedures. o Appointments. o Imaging pictures and data. o Test results, clinical notes and summaries. o Claims data. o Additional administrative data for patients enrolled in the Geisinger
Health Plan.
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Web applications and dashboards also allow clinicians to access data for decision support.
IT Support For Research
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The Director of Biostatistics and Research Data Core in the Geisinger Center for
Health Research serves as an “honest broker” in granting access to CDIS.
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De-identified analytic databases are created from CDIS as needed by research centers, Clinical Innovations team, or other Geisinger units.
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IT support of CDIS for research centers and Clinical Innovations resides within the Clinical Innovations team.
How Research Is Organized
Research Environment
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Geisinger employs a translational R&D approach to innovation in which research is part of a process to create value in health care delivery through quality and efficiency improvements.
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At Geisinger, this model is embodied in several organizational units: o three research centers,
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o a Clinical Innovations group, and o Geisinger Ventures.
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The three research centers are: o The Weiss Center, established in 1987, which focuses on basic sciences with a translational focus. Its staff comprises 15 investigators and 65 support staff. o The Center for Health Research, established in 2003, which focuses on health services research (HSR), epidemiologic, community health, and genetic epidemiologic research. The core mission of the Center for Health
Research, which employs 14 investigators and 40 support staff, is to
“transform how research is used to improve health and to reengineer the ways in health care is delivered.” o The Center for Clinical Studies, established in 2006, which focuses on clinical research including trials.
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These research centers collectively represent an R&D continuum - from basic laboratory research through clinical trials and outcomes research, to the point where knowledge is moved into clinical practice.
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Geisinger’s Clinical Innovations team, often in collaboration with the Center for
Health Research, continues the R&D spectrum by implementing new models of care from research and identifying opportunities to improve care delivery.
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Clinical Innovations organizationally sits at the intersection of operations, research, and the Geisinger Health Plan.
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Geisinger Ventures anchors the applied end of the R&D continuum by seeking commercial partnerships to develop and market Geisinger innovations to other health systems.
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A ten-year strategic plan with performance metrics provides a detailed trajectory for the evolution of research at Geisinger and its desired impact on the health care
Geisinger delivers.
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Examples of recently tested and adopted innovations include new methods of eliciting information and preferences from patients, and providing clinical support data to physicians at point of care through dashboard and web applications.
Research Culture
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Geisinger engages in multiple research collaborations with other organizations around the country: o It is a member of the HMO Research Network
(www.hmoresearchnetwork.org).
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Through the HMO Research Network, Geisinger participates in a collaborative effort that is underway to develop a virtual data warehouse to participate in multi-site research through a variety of topic specific research networks. o Geisinger has been designated as a Beacon Community by the Office of the National Coordinator for HIT (ONC). o Geisinger is a part of KeyHIE (Keystone Health Information Exchange).
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o Geisinger maintains ongoing research and research trainee relationships with Johns Hopkins and New York Universities. o Geisinger develops other collaborations with outside organizations and researchers on a project-by-project basis.
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Researchers at Geisinger are expected to engage with the larger research community outside of the health system by securing research funding, publishing and speaking at scientific conferences. Investigators within the Center for Health
Research are evaluated across seven dimensions: o Grant submissions (20 percent) o Funding received (20 percent) o Communications including both Geisinger and non-Geisinger publications. (60 percent allocated at the discretion of the researcher among this and the remaining four dimensions). o Mentoring o Education o Infrastructure development o External relations
Research Funding
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Geisinger conducts approximately $16 million per year in research, of which approximately $9 million comes from external or endowment funds (i.e. not paid for as part of clinical practice or other reimbursed care).
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Fifty-five percent of funding for the Center for Health Research comes from external sources with the remainder supported by internal (“hard funding”) sources. The Center is on a trajectory to reach 75 percent of its funding from outside sources, which is the effective maximum due to legal and training requirements.
Data Stewardship
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Research involving human subjects or identified patient data must be approved by
Geisinger’s IRB, which is administered by the Human Research Protection
Program (HRPP).
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Research involving data and patients from non-Geisinger sites and organizations, including work undertaken as part of the HMO Research Network, also requires review and approval from the other organization’s IRB. All data and analyses remain behind the CDIS firewall.
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CDIS staff audits all uses of the data.
Organization of Quality-Related Functions at Geisinger
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Per Geisinger’s R&D model of innovation in health care delivery, responsibility for quality measurement and improvement organizationally falls across the
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Quality measurement in clinical care draws largely from databases other than
CDIS, thus helping to eliminate potential conflicts over data resources between the research and quality measurement functions.
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