According to the National Academy of Medicine, waste in healthcare is widespread and is estimated to be about $765 billion annually. One of the key areas of waste is unneeded testing or routine tests that are rarely necessary. As stated in ResearchAndMarkets, the global laboratory services market is expected to grow at a compound annual growth rate of 4.21% over the forecast period (2020 -2025), to reach a market size of US$468.249 billion in 2025 from US$365.690 billion in 2019. The number of unnecessary tests result in significant costs that do not necessarily contribute essentially to healthcare quality or positive patient outcomes.
Using Advanced Data Analytics and AI we help clinicians make better decisions by defining the types of tests that are likely to be useful for a patient. One of the advantages of AI is its unique ability to integrate large volumes of data and identify patterns that may be subtle or difficult for humans to recognize. These subtle patterns have an huge potential to alert clinicians to important physiologic changes that need to be addressed. With an AI-driven application we can provide indications of which tests are likely to produce definitive or valuable results based on the patient’s medical history and current symptoms. With this knowledge, the clinician can advise optimal treatments with the best outcomes and minimize the number of tests, which saves time and reduces costs to the patient.