Clinical laboratory tests play a vital role in diagnosing and managing a broad range of conditions, from COVID-19 and the flu to diabetes and cancer, and in the process, these tests generate a wealth of data on patients.
Fremont, CA: Artificial intelligence (AI) and data analytics are crucial to making personalized medicine a reality, but many hurdles still need to be overcome before these technologies can reach their full potential in the healthcare realm. AACC released a position statement urging federal agencies to implement policies that will enable the healthcare community to fully harness the power of AI and data analytics to transform patient care.
With the emergence of AI technology, it's now possible for clinical labs to analyze this data with greater precision and mine it for new insights into patient physiology and population health. These insights, in turn, could lead to the development of the personalized treatments that are needed to drive healthcare forward. Many challenges still need to be solved, though, before clinical labs and the medical community at large can widely implement AI and data analytics in a way that is both effective and equitable. These challenges include combating financial incentives that encourage healthcare organizations to withhold their data for proprietary uses and inconsistencies in how lab data is collected that make it difficult for institutions to exchange data.
To pave the way for the broad use of AI and data analytics, first and foremost, AACC calls on federal agencies to provide resources and incentives that encourage healthcare providers to develop and adopt these technologies. The federal government should also increase funding for CDC's ongoing effort to harmonize laboratory test results, which is vital to improving the interoperability of lab data. In tandem with this, federal policy should prioritize payment reforms that promote secure, ethical, and reciprocal data sharing among health systems and providers. Additionally, AACC recommends that the clinical laboratory and healthcare communities collaborate to develop and promulgate standardized rules for data collection, sharing, and utilization.
"AACC strongly encourages policymakers and the healthcare community to promote the adoption of AI and data analytics tools, to incentivize data sharing between organizations, and to simplify data collection by supporting data interoperability," said AACC President Dr. David G. Grenache. "Together, these measures will enable the medical community to leverage the vast amounts of data generated by clinical laboratories, which is a crucial step toward developing new interventions that will improve the quality of patient care and lower healthcare costs."