Matthew J. Hawkins is the Former President/CEO of Sunquest Information Systems. With more than a decade of experience in health IT leadership, Hawkins is passionate about technology’s role in improving the quality of patient care.
By now it’s a truism to say that the healthcare landscape is in flux, and renewed debate over federal healthcare policy has only increased the uncertainty. For most healthcare organizations however, primary objectives will remain the same: Controlling costs while improving patient outcomes. Genetic testing offers exciting possibilities to deliver on both of these goals.
Once the sole province of the research lab, genetic testing has increasingly found a home in healthcare facilities looking to bring the highest standards of 21st-century healthcare to their patients. This move into hospitals puts a premium on accuracy and timeliness. Errors and delays in research are unfortunate, but an error in diagnostics can be life-threatening.
In this setting, informatics that support the promise of genomic medicine and provide confidence for clinicians and patients are crucial. Labs in the process of developing this level of diagnostics should guide their efforts with a focus on four essential factors: integration, knowledge base, usability, and reliability.
Integration
Flexible integration is a primary issue for labs expanding their capabilities. A prudent lab director has two concerns in mind. First, a standard pathology lab has a carefully designed workflow created to ensure both accuracy and timely delivery of results. When adding complex molecular lab processes, maintaining this smooth workflow is critical. Quick implementation and fit with elements of the current system should be high priorities. End-to-end integration will also provide the accuracy that allows for confident clinical decision making.
Second, putting genetic testing on the menu is likely to increase the volume in the lab as more tests become available and more patients seek this level of care. The ability to scale along with clinical demand will determine which labs stay on the leading edge of healthcare.
Knowledge base
The rapid development of genetic knowledge is exciting news for patients, as long as clinicians are able to apply this new knowledge to individual cases. An interpretation that was optimal last year may be incorrect the next. Knowledge-sharing initiatives among labs enable each healthcare facility to leverage the most up-to-date knowledge from multiple labs. This type of network enhances the expertise of each participating lab, prevents information silos, and generates better interpretations.
Usability
One of the key changes when moving genetic testing from the research lab to the hospital is the importance of usability. A research analysis may highlight the spectrum of variants for further study, but the clinician and patient need understandable answers to key questions: Of all variants discovered and classified, which are actually relevant to the patient’s current concern? And are there drugs or treatments that are known to help, or harm, in this specific instance?
The way this complex information is presented makes a dramatic difference in physicians’ ability to apply it in a clinical setting. Effective, efficient reporting templates designed for molecular medicine will automatically highlight the most important results and format supporting information to allow drilling down as needed. Having those reports directly translated into the electronic medical record via interoperable technology can further save time and lead to faster treatment.
Reliability
Often when healthcare facilities begin genetic testing, they start small, adapting informatics and pipelines designed for standard clinical testing to molecular processes. At this stage, notebooks and Excel spreadsheets may be the primary method of documentation. From tracking the chain of custody to managing millions of possible variants, it doesn’t take long to discover that manual, homegrown solutions can’t keep up with the complexity, volume, or need for medical accuracy essential to the genetics lab.
At the early stages, labs may wonder whether building or buying will best meet these four important criteria. Sunquest’s white paper Build or Buy: Optimizing Informatics for Genetic Testing can help sort through the pros and cons of each approach.
As labs look for solutions to meet these needs, they should remember that they are not merely upgrading their technology—they’re upgrading their diagnostics. Tools should be clinical grade, ready on day one to deliver reliable information that creates better outcomes for patients, and give every patient the best chance at good health.
