Keith D. Moore
Dean C. Coddington
Case studies of three healthcare organizations reinforce the premise that business intelligence-the ability to convert data into actionable information for decision making-is critical to demonstrating improved value.
The results of site visits with the three organizations, conducted under HFMA's groundbreaking Value Project, show how each has made great strides in expanding its use of clinical and financial information. All three organizations are charting paths toward more sophisticated business intelligence to support them in their resolute move from a volume-based to a value-based payment system.
Headquartered in Boston, Partners HealthCare is a not-for-profit health system composed primarily of Massachusetts General Hospital, Brigham and Women's Hospital, and several smaller hospitals in eastern Massachusetts. At its core, Partners is an academic medical center. At the time of the site visit, Partners had just decided to replace its homegrown clinical information system with a vendor solution, which will take five years to implement.
"Our goal is to integrate financial, medical records, and claims data in our warehouse," said Lynne Eickholt, vice president of finance, analytics and planning for Partners. "We should be able to link these data once we implement our new electronic health record [EHR]. This will save us a tremendous amount of time in doing our research and analysis."
Eickholt looks forward to integrating outpatient data in the business intelligence warehouse. "We would also like to include market and competitive information," she said. She noted that the current cost accounting system is sophisticated but decentralized across Partners. "Often, half of our time in analyzing a problem is taken up with just getting the relevant cost data together," she said. "We hope this situation will improve with the data warehouses and our new system." Eickholt adds that the goal is also to enable people across the Partners' system to access clinical and financial information.
Tim Ferris, Partners' vice president of population health management, described the organization's wide range of data-informed decision processes focused on bending the cost curve. Examples included chronic care management in home and outpatient settings, critical care management at the bedside, referrals management, patient engagement via the Internet, physician staffing, and physician compensation. All of these processes are in flux, he noted, as the system seeks to reduce costs sharply while continuing to improve quality.
Nebraska Methodist Health System
This three-hospital system-with its main facility in central Omaha and satellite hospitals in west Omaha and Council Bluffs, Iowa-was an early adopter of electronic nursing documentation in the 1990s. Methodist's clinical system emphasized flexibility, but the organization did not develop an overarching design, creating a challenge to retrieve data. Separate applications were implemented for different purposes. Today, there is a move to integrate the components.
Methodist uses software that can provide risk-adjusted clinical utilization data based on claims data, measure physician adherence to protocols, and report on quality metrics. Methodist also plans to use software for population management. Clinical departments within Methodist also use a variety of medical society databases, including the American College of Surgeons' National Surgical Quality Improvement Program database and the Society of Thoracic Surgeons' database for heart surgery.
Methodist currently uses ratio of cost to charges for costing, but is planning an investment in a new cost accounting system that the health system would implement jointly with its accountable care partner, The University of Nebraska Medical Center.
Methodist is concentrating on improving both dimensions of the value equation-quality and cost-using process improvements, evidence-based protocols, and chronic disease management. Its investments in business intelligence are facilitating efforts in all of these areas.
The health system recently implemented a data mining tool with clinical and revenue information at its core. Because of the different standards for implementation of the clinical applications in different clinical departments, extracting data has been a challenge. The new system attempts to provide meaningful, actionable, consistent data in much less time.
On the clinical side, focusing on its physicians' clinic comprising nearly 170 physicians, Methodist has begun mining data on chronic conditions to identify and contact patients who have quality measures missing in their record and to compare physicians' performance on diabetes metrics. The initial focus has been on diabetes, but the health system will soon also begin mining patient data on hypertension, heart failure, asthma, and coronary disease.
On the financial side, Methodist recently purchased a financial forecasting system that includes a healthcare reform module, which allows modeling of "What if?" scenarios based on assumptions run through the forecasting system.
From interviews with several of Methodist's leaders, it became apparent that the health system regards its efforts to refine data analysis capabilities as key to the future. The next step is to move from collection to analysis and action, which will require investment of additional resources in both information systems and staff.
Geisinger Health System
This mature integrated delivery system serving eastern Pennsylvania has three hospitals, more than 1,000 physicians, and a 300,000-member health plan. The health system's CFO, Kevin Brennan, noted that Geisinger Health System has had a clinical information system since 1995. Geisinger began installing an EHR at its ambulatory sites before implementing it in its hospitals. It has data warehouses-including one for clinical and billing information, and another for claims-with an estimated 200 users.
Janis Bartholomew, senior director, Financial and Clinical Decision Support, said that various departments throughout Geisinger analyze clinical and financial data. "We know our variable and fixed costs for each service," she said. "We can aggregate data across the continuum of care."
Bartholomew listed eight strengths of the Geisinger decision-support capabilities:
- A robust EHR
- Inpatient/outpatient data aggregation
- Hospital/professional data aggregation
- Financial and clinical data aggregation
- Estimation of net revenue and actual payments
- Product costing at the code level
- Historical trending
- Modeling and forecasting
The uses of the data, according to Bartholomew, include financial reporting, expense management, productivity monitoring, and clinical analysis. With the data, Geisinger assesses costs per product and per contract, performs patient analyses, and creates dashboards. Geisinger also calculates estimated net revenue based on contract terms, which is helpful in contract negotiations.
The three organizations have different software vendors, and different approaches to collecting and analyzing clinical, claims, financial, and other information. In general, however, the site visits identified three significant commonalities among these organizations.
First, all three organizations see business intelligence as key to improving value. Business intelligence is helping each of them to transform care delivery to models that are more patient-centered, cost-effective, and coordinated.
Second, business intelligence is contributing to the financial sustainability of these organizations, helping them not only to identify opportunities for value-based payment experimentation, such as bundled payments, but also to refine contracting efforts.
Third, all three organizations invested in information systems and data warehouses first to become data collection organizations but ultimately to become data-driven ones, capable of turning data into actionable information-and they are at various places on this spectrum.
How does investment in business intelligence relate to the shift toward value-based payment? Providers cannot be successful with value-based payment if they do not demonstrate quality and efficiency. Tracking costs by service line and physician is necessary, and likely to become even more important in the future. A healthcare system with these capabilities knows how to control the price of its services. This is what employers and payers expect.
Keith D. Moore is CEO, McManis Consulting, Denver (email@example.com).
Katie Eyestone is a senior consultant, McManis Consulting, Denver, and a member of HFMA's Colorado Chapter (firstname.lastname@example.org).
Dean C. Coddington is a senior consultant, McManis Consulting, Denver, and a member of HFMA's Colorado Chapter (email@example.com).
Publication Date: Monday, October 01, 2012