Hospital-based cancer centers and service lines face tough competitive pressures from other practices and hospitals competing for market share, reputation, referrals, and managed care contracts. For hospital-based programs, competition also can arise internally, as other service lines and business units compete with oncology for investments and resources at a time when hospital margins are shrinking.
To formulate and make the best possible judgments in strategic planning, business development, and revenue cycle management, oncology managers must maximize the power of the data available to them. The problem has been that existing tools were inadequate for the unique challenges of cancer service lines. At Massey Cancer Center of Virginia Commonwealth University we have found that the typical data systems made available to hospital administrators were not adequate for the complexity of the cancer service line. Simple “cube”-based financial tools were not able to capture the many clinics, units, and ancillary services that are used by cancer patients and providers.
Many tools were too focused on inpatient care, when in oncology at least 50% of charges were driven by ambulatory chemotherapy, radiation, surgery, and imaging. Standard tools also were unable to deliver diseasefocused output so that each cancer type (eg, breast, colorectal, lung) could be analyzed separately. Nor were they able to capture the entire treatment course from diagnosis, through cancer-directed treatments, and include palliative and end-of-life care.
The Cancer Analytics Solution
In response, we created the Massey Data Analysis System that extracts the hospital’s and providers’ claims data, and reconstitutes them in an easy-to-analyze structured query language– based system. Categories of ICD-9-CM codes are stored in reference tables for easy application in any given analysis, for example, giving us the ability to analyze each type of leukemia and lymphoma separately, or to combine them all into a single category of hematopoietic diseases.
Each modality of care is categorized into a handful of key types. Automated programs do the bulk of the extraction, categorization, and “predigestion” of data, allowing our analytic resources to be devoted to producing useful output for clinical, operational, and financial im provements.
The flexibility and power of this system has been invaluable. We have been able to turn one program within our cancer center from an annual loss of $1 million or worse, to a sustained positive net margin. We have developed and implemented strategic plans that are organized around disease-specific centers of excellence. We have combined cancer registry and claims data to analyze utilization patterns and financial outcomes at the patient level by disease type and stage. And we have used this system to develop the financial metrics for our palliative care program.
Making Analytics Work for You Key Questions and Action Steps
Q: Do you have the tools you need to evaluate the costs and revenues of each of your major programs/ centers across modalities of care from screening and diagnosis through all forms of treatment?
A: If not, explore options to access and analyze these data in ways that meet your specific needs. Most hospitals have a decision-support department that would be a good first contact.
Q: Do you have the tools you need to develop and implement disease-focused strategic plans and business development initiatives?
A: If not, you need to identify a cancer data analyst who can bring familiarity and expertise regarding cancer and its treatments to assist you in your planning efforts.
Q: Do you have the tools you need to answer new questions flexibly as they arise, regarding all aspects of your cancer patients’ use of services?
A: Cancer treatments continually are evolving; and cancer programs adapt to keep pace with scientific developments, regulatory changes, and organizational shifts. Make sure your system can adapt accordingly.