How the Analytics of Care Can Balance Workforce Capacity - MedCity News (2024)

How the Analytics of Care Can Balance Workforce Capacity - MedCity News (1)

U.S. healthcare is experiencing a supply and demand crisis as it races to keep pace with an aging population amidst a workforce shortage and mounting financial pressures. And the situation appears unlikely to improve anytime soon. In fact, recent projections anticipate a shortfall of 139,000 physicians in the next decade, according to the Association of American Medical Colleges.

One limiting factor preventing the efficient management of workforce resources is a lack of data interoperability.

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Disparate datasets – emitting from legacy EMRs, practice management systems and third-party software – have created operational blind spots preventing health systems from precisely managing the allocation of care. And instead of a holistic view, across an ecosystem of care, health systems piecemeal fragmented insights against limited resources.

Data linkages unlock health system capacity

How do we go from myopic to digitally aware? The answer lies in becoming a real-time health system able to achieve the awareness to orchestrate how, when, and where care is accessed. It’s about having the controls to dynamically manage clinics, hospitals, doctors, and system-wide resources, matched against patient needs and capacity – instantly. Only then, can we divert traffic from emergency rooms, route patients to clinics and virtual care, and make time for doctors to treat our aging population.

A transition from a disjointed view of operations to a predictive model starts with data unification.

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Integrated Enrollment Platforms and Consumer Assistance Centers: The Strongest Advantage for State-Based Exchanges

In the ever-evolving landscape of state-based health insurance exchanges, the convergence of technology and customer service is reshaping how these exchanges operate. The increasing advent of automation and artificial intelligence (AI) is rapidly dismantling the traditional business model that relies on the siloing of technology and customer service centers.

The advent of generative AI and machine learning models, in a blink, can ingest, learn, and organize complex, massive datasets. As a result, health systems can operate with the intelligence to inform how to balance workforce resources, to control costs, and to free up capacity.

The always-on, connected health system is not a distant moonshot, but today’s reality. Pragmatic applications of AI can achieve the data fidelity – and clarity – to understand how care is accessed, where needs are growing, and to best match resources to ensure quality outcomes.

The reality is not every patient needs to see a doctor. It’s about matching the right care, at the right time, at the right location that extends resources and realigns how people and services are distributed.

Leveraging real-time data for a new model of care

Data intelligence is no longer a luxury, but an operational imperative to manage an entire portfolio of care. And in healthcare – an industry beset by data isolation – the analytics of care delivery is more important than ever.

Take, for example, a health system that is working to balance the demand for ambulatory care across providers, nurses, retail, and telehealth. To do so, aggregation of cross-functional data, including capacity and utilization, is essential to enable a self-scheduling experience that both increases choice, and has the real-time logic to route patients to the best venues of care.

The unification of data isn’t just about convenience and capacity—it’s about creating a better model of care. The traditional “find-a-doc” features fall short of connecting patients to the right care, at the right time. Achieving data intelligence enables us to move to a “find care” model that shields providers – creating time to treat pressing, chronic conditions – and delivers the operational controls to predict and auto-heal the demand for care against fluctuating needs, while maintaining quality care.

Greater access, a capacity of caregivers, and operational efficiency shouldn’t be tradeoffs. The real hurdle is not technology, but changing how we operate.

Photo: claudenakagawa, Getty Images

How the Analytics of Care Can Balance Workforce Capacity - MedCity News (4)

Derek Streat

Derek is Founder, CEO and Chairman of DexCare. He is an accomplished healthcare technology entrepreneur and executive, having co-founded and/or been at the earliest stages of six venture-backed companies including C-SATS (acquired by Johnson & Johnson), Classmates (acquired by United Online), Medify (acquired by Alliance Health Networks) and AdReady (acquired by CPXi).

Prior to joining Providence as an Entrepreneur-in-Residence to commercialize the DexCare platform, Derek served as VP of Digital Solutions at Johnson & Johnson - a role he assumed after C-SATS was acquired by the world’s largest healthcare company. There he led the charge to transform the organization responsible for training 250,000 surgeons worldwide into a leading healthcare quality improvement and continuous learning institution that directly advanced patient outcomes, provider efficiency, and health system value through digital solutions.

Derek is also actively involved in national healthcare data transparency efforts for the improvement of patient care as a Co-Founder and Board member of two leading data sharing organizations, PEDSnet and the Improving Renal Outcomes Collaborative (IROC).

This post appears through theMedCity Influencers program. Anyone can publish their perspective on business and innovation in healthcare on MedCity News through MedCity Influencers.Click here to find out how.

How the Analytics of Care Can Balance Workforce Capacity - MedCity News (2024)
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