Artificial intelligence (AI) and data analytics are key 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. The AACC has 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.
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. With the emergence of AI technology, it’s now possible for clinical labs to analyze this data with greater precision and to 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, as well as inconsistencies in the way that 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, the AACC is calling on federal agencies to provide resources and incentives that encourage healthcare providers to develop and adopt these technologies. The organization also argues that 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 (i.e., the ability to exchange data consistently and accurately). In tandem with this, the statement continues, 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 David G. Grenache, PhD. “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.”