The ability of artificial intelligence to quickly process and interpret large amounts of health data is a valuable tool for clinicians…
How artificial intelligence can improve patient care
The United States healthcare system is at a crossroads. A plethora of challenges – both structural and financial – hinder the operations of the present and threaten the sustainability of the future. Among these:
More than 10,000 Americans turn 65 each day and the aging population is fueling an explosion.
Health care spending is expected to reach approximately $6 trillion by 2027.
The growing physician shortage continues as the Association of American Medical Colleges (AAMC) reports that the U.S. could see a shortage of 37,800 to 124,000 doctors by 2034.
The US Bureau of Labor Statistics reports a decline of nearly 90,000 people in the hospital’s sub-sector workforce since March 2020.
These realities emphasize the critical need to better address and improve the efficiency of our health care delivery system. The old model of fee-for-service is weighing down a system already plagued by enormous challenges, and long-term trends will only add pressure to it.
In contrast, comprehensive and holistic value-based care aligns diverse interests – including payers, administrators, brokers, consultants, providers, self-funded employers, third-party, and patients. Value-based care improved patient outcomes while meaningfully managing health care costs. And advanced technology platforms that leverage forms of artificial intelligence (AI) are well-positioned to support and increase the productivity of health care providers while improving patient outcomes with the ability to identify those most at risk. We do.
Better patient care
Artificial intelligence represents a group of technologies that includes automated systems capable of performing tasks including enhancing visual perceptions, diagnostics and predictions, and processing large amounts of data seamlessly. The work done by AI has promising applications in value-based care, including strengthening patient care and enhancing health outcomes.
Data overload is a growing problem affecting health care systems across the continuum. Interpretive AI processes can simplify vast amounts of complex data and synthesize key aspects of data for analysis by the appropriate expert with recommendations and insights. This ability to digest and streamline data maximizes the valuable time a doctor can spend with patients.
Interpretive artificial intelligence allows providers to quickly access medical data, review medical history, identify patterns, and recommend interventions. These features help to target unique symptoms and stratify risk severity for each patient while focusing on patient well-being and quality of care.
Accessible data brings many capabilities
While interpretive AI has many capabilities, it does not replace human expertise, as feedback from experts and clinicians is essential to building a relationship with the patient. AI can be thought of as an extension of the care team, with the ability of specialists to become more precise while maximizing resources.
A distinctive attraction to the adoption of interpretive AI is its ability to accurately and quickly accomplish tasks that previously required extensive hours of manual data parsing—streamlining compliance workflows and detecting and resolving inconsistent data outliers. , all contained within any of the 60 million electronic health record queries. In an average-sized hospital. To perform this task by hand, a hospital worker would have to review more than 6 million electronic health records, approximately 300,000, every day.
Interpretive AI can help providers expedite response to interventions, streamline workflows, and allow employees to spend less time on lengthy processes and manual tasks. Additionally, the increased efficiencies address the growing and considerable financial expenditure and help lower costs. This ultimately leads to more hours devoted to patient care, efficient hospital administration, and less stress for physicians and all medical staff.
Better population health
Interpretable artificial intelligence can look at a population’s broader community-related factors influencing population health, along with an improved ability to link sources of individual, patient-level data to help predict future outcomes. Can increase data availability. Artificial intelligence-insight data can provide doctors with progress updates, detailed history, and other patient-related information. It has the potential to match a physician’s observations with data that provides targeted insight into the surrounding circumstances, helping to identify missing gaps in care for individuals and communities.
By identifying emerging or high-risk patients driven by specific clinical conditions, comorbidities, or predictive risk models, patients with the greatest need can be targeted first with effective intervention. The result translates into fewer, less severe interventions and fewer hospitalizations. The goal is to avoid costly hospitalizations, readmission rates, and accidental, rapid interventions while improving patient health.
Artificial intelligence-enabled solutions are changing the way healthcare is delivered. These solutions are streamlining diagnostic and treatment processes, focusing on quality care, and offering innovative solutions to relieve an overwhelming burden—a system that emphasizes the importance of value-based care. and sees efficiency but is in transition.
Interpretive artificial intelligence is poised to grow and play a growing and essential role in supporting holistic clinical and health care operations. While delivering proven benefits today, AI’s potential to shape the future as a health care system is focused on improved efficiencies, lower costs, and a structure that educates, engages, and empowers patients.
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