Complex problems that affect the world of pharmacy, such as the opioid crisis and avoidable hospital readmissions, require multidimensional answers. Artificial intelligence (AI) might be one solution. There are currently firms working to use AI, some through the use of machine learning, in the hope that it will contribute to solving these problems or at least minimize their impact. Taken together, AI and machine learning may have a massive multifaceted impact on pharmacy operational efficiencies, patient-centered care, and outcomes.
In today’s world, AI complements human interaction with patients. Adam Beacham, director of business intelligence at PDX-NHIN, a pharmacy software company, believes that 2019 and 2020 will be pivotal years for AI and predictive models to improve patient health from prescribers to pharmacies.
Sadiqa Mahmood, DDS, MPH, senior vice president of medical affairs for life sciences at Health Catalyst, says pharmacists can be empowered by AI to shift from prescription-filling roles to patient engagement and management of disease. Health Catalyst is a data/analytics vendor that has been working to predict and prevent readmissions through a combination of predictive analytics, machine learning, and new intervention strategies.
“Tools like AI and ML are enabling decision-making processes at the point of care; [and] quicker identification of patients who become high risk due to changes in their diagnoses, condition, or care plan,” she says. “Just as important, AI is optimizing pharmacy operations for inventory and supply chain management to enhance pharmacy productivity, and increase patient satisfaction and outcomes.”
Beachum adds, “AI and technology in the healthcare vertical continue to expand their use cases. As more organizations begin to leverage the available data, continuing to predict outcomes and patient adherence will expand its role.”
AI and machine learning are primary drivers within health systems as a way to lower the risk of readmissions among patients. Samir Manjure, CEO of KenSci, an AI-powered risk prediction platform, says the adoption of electronic health records and the availability of patient data sets have made it possible to predict more accurately which patients are at the highest risk of readmission. This not only offers the ability to intervene early but also mitigate the risk of infectious diseases and other health complications for the patient.
“With the Medicare Payment Advisory Committee (MedPAC) stating that 76% of hospital readmissions are potentially avoidable, AI and machine learning play a critical role in enabling hospitals to prevent cost leaks owing to potential cases of readmission,” he says.
A challenge to implementing AI is that, in its current state, administrative, clinical and financial systems in healthcare are not integrated, and, in some cases, are handled manually. To deploy AI successfully, a single technology platform that integrates and harmonizes data from disparate sources is critical.
“Institutions with such platforms are able to deploy AI successfully and offer hospital, health systems, and pharmacy leaders a more ironclad defense against preventable adverse drug events and avoidable care delays, and effective operational management,” Mahmood says. “Health Catalyst’s Data Operating System is a cloud-based digital platform, which enables health systems to integrate and analyze data from virtually any software system or other data source.”
DOS contains large and comprehensive data assets of its kind with more than 100 million patient records, encompassing trillions of facts sourced from more than 300 distinct siloed sources.
“Because we integrate data from so many highly disparate sources, we’re able to synthesize a single-source-of-truth data feed, and generate high-quality training sets that machine-learning algorithms can use to continuously improve their performance and accuracy,” Mahmood says. “We give the health systems the right validated information needed to support any AI-based pharmacy initiative.”
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