by  John Edwards

Intelligent Automation in Healthcare for Smarter, Leaner Delivery of Care

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Let’s face it. The healthcare industry has some of the most complex challenges and business issues to solve in this century:

  • Rising healthcare costs wrapped up in heavy administrative burdens
  • Slow progress in chronic disease prevention
  • A lack of cohesive communication within the healthcare ecosystem

Healthcare IT leaders tend to feel the weight of responsibility most in addressing them.

In the last few decades, there has been promise in mitigating hospital and provider administrative costs by embracing a quickly evolving digital landscape. For example, the Health Insurance Portability and Accountability Act (HIPAA) sought to reduce administrative costs in healthcare by standardizing electronic transactions between payers and providers. With greater knowledge of patients and members, payers and providers are now personalizing communications.

The Council for Affordable Quality Healthcare (CAQH) tracked the adoption of electronic standards on eight separate processes and claims that the industry saved $122 billion in one year using HIPAA standard transactions. In recent reports, CAQH claims that medical spend increased as utilization rose, and staffing shortages impacted the cost and time to complete tasks. However, automation increased cost savings.

Yet technological advancements in operations within healthcare are painfully slow. The Centers for Medicare and Medicaid concluded that health spending in the U.S. increased in 2021 to $4.3 trillion or $12,914 per capita, slower than the increase of 10.3% in 2020. The slower growth in 2021 was driven by a 3.5% decline in federal government expenditures for healthcare that followed strong growth in 2020 due to the COVID-19 pandemic response. The annual growth in national health spending is expected to average 5.1% over 2021-2030 and to reach nearly $6.8 trillion by 2030.

Lastly, since HIPAA was signed into law there are periodic updates with which healthcare IT leaders must comply. For example, a December 2022 clarification of HIPAA rules sets regulatory expectations for third-party tracking technology use. Healthcare companies now need to perform a risk-based assessment of the technologies used for data mining to determine if HIPAA requires a more restricted view. Failure to comply with the rules can result in significant fines and penalties.


Imagine a world where macro and micro healthcare decisions are made from an environment of massive amounts of rich data mined from an integrated healthcare ecosystem that interacts continuously. This comprehensive level of real-time data is then analyzed from logical sequences set up to inform on health epidemiological research and patient health outcomes. And to effectively address business and administrative-related needs that support healthcare delivery overall.

This type of vision is on every healthcare CTO’s and business analyst’s mind, especially after the 21st Century Cures Act was set in motion. This federal regulation was designed to accelerate the “access, exchange, and use of personal health information” within the healthcare ecosystem. The COVID-19 pandemic placed even more emphasis on the need for change in a system that is already experiencing deep operational and administrative gaps.

Technologies like robotics process automation (RPA) and machine learning (ML) combined with artificial intelligence (AI) that remove the human element from repetitive, mundane administrative tasks and reduce errors exist. They are already used by the industry, as mentioned earlier in the healthcare payer-provider scenario and the standardization of electronic transactions.

Healthcare professionals in environments where these kinds of digital solutions are being used have more time to focus on higher value decision-making such as diagnosis and treatment. Delivering a better patient experience and improving outcomes are achieved by optimizing patient engagement. By providing clinicians with faster access to more information, it enables them to provide targeted and tailored care.

There is also progress shown through these kinds of digital advancements in eliminating potential compliance concerns. Automation technology reduces fraud and error rates and increases accuracy, safety, and security.

Medical errors that can lead to injury and fatality also come with an estimated cost of almost $1 trillion per year in the U.S. Add to that number another $68 billion in billing mistakes and the reasons for transforming the digital landscape in healthcare are painfully obvious. And the problem may be getting worse. This report shows that nearly one-third of respondents reported their number of denials has increased between 10% to 15%.

Intelligent automation is just that, automated, so there is no possibility for fatigue or distraction. By automating human operational tasks that are then optimized through AI and ML algorithms, you can supply extra error-checking steps in transactions and calculations without incurring the costs of ongoing human labor. Time and mental energy are freed up to perform higher-level cognitive tasks that lead to better health and patient experiences.

With all this potential for improved efficiency and reduction in costs tied to health delivery and administrative work, why has the industry been slow to make changes?



In healthcare, varied services and forms of delivery, a complex relationship between payers and providers, and the need for regulatory compliance around personal health data construct an intricate system. Therefore, there is no doubt that the reasons for slower adoption of technological advances are not due to a lack of desire or misperception of need. What chief operating officer or director of IT wouldn’t want to improve their operational efficiencies and patient-health delivery? Or make significant dents in their overall spend on administrative tasks?

The pressure of a pandemic and a digitally smart generation, notwithstanding, is a bigger issue at play. Healthcare, and the industry in general, is a more comprehensive system of delivery than say retail or manufacturing. Situations where newer technologies disrupt how markets operate and change quickly for the better do not translate to an industry that has become even more wide-ranging and disparate.

The changes to the healthcare ecosystem must occur simultaneously and in a coordinated fashion because of:

  • Healthcare’s diverse and numerous disease conditions
  • The number of stakeholders involved with the care delivery
  • The even greater variety of tools and deliverables that require everything from human services and labs to engineering and manufacturing

This can make any kind of change incredibly complicated and time intensive. Add to this the fact that no technology has ever been leveraged across the entire industry at once. This further emphasizes its siloed nature and the inability to capture the kind of patient data that would necessitate a single, game-changing technology.


While one technology that produces rapid-fire changes across the industry has not yet happened, it does not mean that bringing advanced technology like intelligent automation at increased speed is nearly impossible.

The key to rapid change lies in starting with a deeper comprehension of healthcare’s multi-faceted delivery model. As well as a better understanding of how the business relationships between payers, providers, and healthcare vendors are all interwoven. This can then lead to an approach of addressing all distinct players as one rather than siloed.

Viewing the entire ecosystem and how it interrelates, and developing an approach that weaves them all together may be the solution. Building a flexible, coordinated digital healthcare model can lead to the kind of digital disruption where intelligent automation shows tremendous promise.

To be part of the ongoing discussion with your peers about the impact of intelligent automation in healthcare, watch the webinar, “Reduce TCO and Improve Ops with Patient-First Automation.”