AI technologies have the potential to dramatically transform healthcare delivery. It is anticipated that AI will help the healthcare “industry tackle some of its largest challenges such as rising costs, increasing service demands and clinician shortages.” By finding ways to increase the efficiency of the existing workforce, AI will “reduce clinician burnout, improve patient experiences and democratize data”.
Consequently, healthcare providers are actively evaluating and using AI technologies. Gartner® recommends that “provider CIOs should use these predictions to prepare for the impact of AI on care delivery”.
The Gartner report offers three key findings:
- Industry pressures are pressing healthcare delivery organization (HDO) CIOs to look for innovative technology solutions to supplement human capacity and address shortcomings.
- AI technologies in healthcare are now approaching a turning point due to greater volumes of high-quality data and advancing computational techniques.
- Various approaches deploying AI-enabled tools and solutions are being used by healthcare providers. These include “investing in best-of-breed solutions, developing AI capabilities in-house, and partnering with third-party service providers and platform vendors”.
HDO CIO Recommendations
- Create an enterprise-wide AI strategy that aligns with and enhances the organization’s mission and vision to bring awareness of the approaching wave of AI healthcare solutions.
- Establish an enterprise-level AI task force to assess proposed solutions and recommend a process and actions to introduce, implement, and operate AI appropriately.
- Identify the easiest-to-implement, lowest-cost use case to demonstrate the measurable value of AI and use these quick wins as a stepping stone to build future success.
Gartner Strategic Planning Assumptions
Gartner outlines three strategic planning assumptions:
1. By 2027, clinicians will have reduced the time spent on clinical documentation tasks by 50%. Integrating generative AI (GenAI) technologies into the EHR will improve clinician and patient experience.
“Clinicians are challenged with balancing optimal patient care with efficiently managing associated documentation and administrative responsibilities.” Studies have found that U.S. and English healthcare practitioners spend an average of 13.5 and 15.5 hours respectively on administrative tasks and clinical documentation. These account for nearly 25% of U.S. healthcare spending.
There is widespread interest that GenAI has the potential to automate and augment many administrative tasks to free clinicians’ time to provide clinical care and reduce burnout.
Early use GenAI cases include “ambient digital scribes to automate clinical encounter documentation; drafting responses to patient messages; summarizing information in the clinical record; drafting other clinical documents, such as referral letters and patient discharge summaries; and automating clinical coding.”
- Take a strategic approach to identify the highest-value use cases for your organization. Work with clinical informatics leaders to identify the greatest areas of digital friction associated with clinical documentation and administrative tasks.
- Understand your EHR vendor’s product development GenAI roadmap. Identify gaps aligned to your organization’s highest value use cases that may require third-party solutions or internal development of capabilities.
- Ensure solutions are deployed safely and responsibly with appropriate governance strategies that address transparency, interpretability, ethics, bias, and regulatory requirements (such as privacy and security). Build organizational readiness by providing training programs for end users to use applications safely and ethically.
- Maximize ROI with a cross-functional lead implementation team of clinicians, informatics, software developers, and AI experts focusing on end-user experience. “Deliver the minimum functionality required to test the use cases, and refine your assumptions on the cost and value of scaling them.”
2. By 2027, 60% of healthcare provider AI-enabled workflow automation will mitigate staffing shortages and clinician burnout versus patient engagement.
“Throughout the healthcare industry, issues of burnout, stress and turnover among clinicians and healthcare professionals, which were pervasive before the pandemic, have escalated to unprecedented levels.”
“Staffing shortages and accompanying employee burnout are a global issue. It is an insidious cycle where burnout leads to staffing shortages, which accelerate burnout.”
Most recently, automation efforts have been largely directed at consumer and patient-facing workflows to improve their experiences, outcomes, and retention. Many patient platforms have emerged with many enabled by interoperability technologies such as robotic process automation, conversational AI, and inference engines. Now the focus is shifting toward the clinician and care team.
Persistent healthcare staffing shortages “will continue to drive up labor costs as healthcare providers pursue short-term and expensive on-demand solutions that consume a larger percentage of their operational budgets.”
Provider, care team, and staff workflows will begin to benefit from automation and optimization initiatives as well as consumer and patient workflows. “Workforce management is being reinvented to deal with an ongoing shortage of qualified personnel and the resulting overwork of the incumbent staff.”
- “Optimize and automate workflows for roles in the shortest supply for your enterprise or those representing your most significant temporary or contract labor costs due to retention issues.”
- “Physicians, nurses and clinician specialists (e.g., radiologists, hospitalists) should identify, optimize and automate workflows that contribute most to burnout and employee morale issues.” Increase healthcare provider freedom and mobility through virtual care options and present more flexible and equitable scheduling options and more competitive salaries.
- Use the Gartner Healthcare Hype Cycles (see Hype Cycle for Healthcare Data, Analytics and AI, 2023) to identify innovative technologies and solutions to reduce clinician and staff burnout and increase workforce productivity and capacity.
3. By 2027, the average daily amount of data collected from inpatient rooms will exceed that of the average ICU bed today.
With increasing interest in GenAI’s capability to help solve healthcare providers’ most urgent issues, the focus is on collecting large quantities of high-quality required data to fuel AI use cases.
Methods to generate clinical and nonclinical use case data are diversifying. HDO CIOs are architecting the “patient room of the future” that introduces as much data-gathering technology for each inpatient bed as possible.
“HDO CIOs are purchasing IoT that supports AI use cases. Growth of IoT endpoints for clinical data collection and chronic condition management is predicted to increase year over year until 2029.”
- Architect patient data solutions to maximize flexibility in functional use to pool and allocate resources dynamically to meet changing demands. These IoT/IoMT groups perform their job within a larger multivendor ecosystem of solutions and must be able to be orchestrated into workflows to support many use cases. Be ready to respond to demands for application function API access.
- Ensure open API solutions allow for open data integration and use data standards. Patient-facing technologies must participate as peers with other capabilities in end-user workflows, and any data collected or created must allow for adaptable usage.
- Maximize AI-enabled performance and scalability by planning for a hybrid cloud and embracing cloud-out and edge-in concepts. Over time, more clinical solutions will be cloud-based as latency issues are resolved, resulting in fewer on-premises solutions. Designs need to cover on-premises, hybrid, and cloud-only infrastructure patterns.
Denis Reynders, Global Business Unit Leader at Stefanini Digital Health Services, comments: “This latest Gartner report confirms that HDOs must create an AI strategy and embrace the approaching wave of AI healthcare solutions. The GenAI hype is raising attention for all AI technologies and large language models (LLMs) are accelerating the development and accuracy of healthcare industry AI solutions. The potential for HDOs is transformative for patient and clinician experiences alike.”
“Success hinges on establishing awareness and trust of AI technologies across the organization and providing a seamless end-user experience. A cross-functional fusion team should be created to identify, optimize, and automate workflows for the highest value use cases and find innovative technologies and solutions to reduce clinician and staff burnout and increase workforce productivity and capacity.”
Gartner, Predicts 2024: Healthcare Delivery, AI’s Proving Grounds, 6 December 2023, Gregg Pessin, Sharon Hakkennes, Barry Runyon.
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