I am in the final stages of preparing a lecture to deliver at the Sunquest User Group (SUG) this week in Phoenix. The topic that I picked for my lecture is how pathology informatics (PI) can be used to respond to the cost-reduction pressures of the ACA and other healthcare reform initiatives. In the process of thinking about this topic, I become much more aware of how much pathology informatics has been changing recently. My goal in this this short note, is to begin to summarize the changes that I see occurring in PI. I will refer to these changes as a new pathology informatics model.
Let's start this discussion with what I think are the major pressure points on pathology and pathology informatics that are prompting changes:
- Healthcare reform in its various forms including the ACA and ACOs. The challenge here is to perform lab tests faster, better (i.e., higher quality), and less expensively.
- Dramatic advances in the science and technology of genomics and molecular medicine, particularly cancer genomics. This results in an enormous increase in the need for data storage and computerized data analysis.
- The wider adoption of digital pathology that will undoubtedly occur in the next couple of years. This trend, in turn, will increase the need for more data storage and, in time, will lead to a need for image search.
- Wider deployment of EHRs, often paired with a preference for an enterprise-wide-solution (EWS). This shift can sometimes lead to the deployment of a less functional LIS provided by the EHR vendor. This shift is putting pressure on the classic best-of-breed LIS vendors whose long-standing relationships with hospital pathology departments may be disrupted.
As a result of these pressures and the demand for new computerized solutions in pathology, I see pathology informatics expanding and also splitting into three practice areas. For the purpose of this discussion, I will refer to them as: research pathology informatics (RPI), clinical pathology informatics (CPI), and management pathology informatics (MPI). What I call RPI has been previously referred to by Mike Becich as computational pathology. RPI addresses computational problems in bench research. Right now, there is an intense focus in genomics, particularly cancer genomics.
One of the major tasks of CPI practitioners is to help manage the test-ordering and test-reporting relationship between clinicians and the clinical labs. Two of the most challenging issues here are to encourage optimal ordering by clinicians and to improve the formatting of test results in EHR lab reports. MPI addresses lab managerial issues such as how to staff the various labs across the work shifts to accommodate varying test workload. MPI is largely the domain of lab managers, lab scientists, and medical technologists with some pathologist oversight.
In subsequent posts, I will continue to write about various other aspects of the emerging pathology informatics model, always linking back to this original piece.