Enterprise Asset

Operational Playbook: Care delivery must adopt AI strategically to survive the 21st century

This operational playbook is for health system, hospital, and ambulatory surgery center CIOs evaluating how to deploy AI strategically across revenue cycle, clinical operations, and patient experience to address four compounding existential threats to care delivery.

This playbook is for care delivery enterprise (health systems, hospitals, and ASCs) CIOs to leverage technology, particularly AI, to address four key existential challenges by their organizations: 1) revenue headwinds, 2) margin deterioration, 3) clinician shortages, and 4) patient expectations for speed, accuracy, and costs. It centers on AI as the core technology enabled by a new delivery paradigm framed by Services-as-Software™ (SaS).

Addressing these challenges with the specific steps in this playbook will yield tangible, quantifiable benefits such as increased revenue, reduced costs, improved clinician productivity, and higher patient engagement rates.

HFS Operational Playbooks are practical guides to solving key enterprise challenges that consume significant costs, time, and resources. The playbook provides enterprise leaders a realistic roadmap with specific “to-dos” to address their everyday challenges so they can clear mental and financial space to deliver next-level value.

The problem: Care delivery enterprises are facing an existential crisis at the nexus of multiple, compounding challenges

The US healthcare delivery landscape, despite the enormity of AI-induced opportunities, is the most economically challenged industry segment. Externally driven headwinds include the One Big Beautiful Bill Act (OBBBA), which reduced Medicaid funding by close to 10% annually, slashed reimbursement rates across the board (primarily for Medicare), and a rapidly aging population with a high prevalence of chronic conditions that will continue to drive up the cost of care. Internally driven challenges include slow and low technology investments that prevent higher productivity and efficiency, unrealized benefits from M&A activities, and slow progress in finding new sources of revenue.

These challenges will manifest into four categories of threats that need immediate remediation. The rationale for urgency lies in the bleak data from the Cecil G. Sheps Center for Health Services Research at UNC, which identified 338 rural hospitals as particularly vulnerable. Other data points suggest that even urban and inner-city hospitals are vulnerable and at risk for closure.

Revenue headwinds

Shrinking reimbursement rates by the Centers of Medicare and Medicaid (CMS), exacerbated by site-neutral payments, increased payer friction seen in higher rates of denied or delayed payments, prior authorization, and increased uninsured rates, are reducing the number of paying patients.

These factors will reduce revenues by 3% to 6% over a 12-month period and by 7% to 14% over a three-year period for those that survive this tsunami of challenges.

Line chart showing two projected trajectories for reimbursement rates over a four-point timeline: now, in one year, in two years, and in three years. The vertical axis runs from 80% to 100%, representing rates as a percentage of current levels. The best-case line (purple) declines gradually from 100% now to approximately 93% in three years. The worst-case line (orange/red) declines more steeply from 100% now to approximately 86% in three years, representing a 14-percentage-point reduction. Source: HFS Research, 2026.

Margin deterioration

Demand for care will continue to rise as the population rapidly ages, bringing with it an increased prevalence of chronic conditions. Yet there will not be a commensurate increase in rates or revenues.

Increased uninsurance will triple the rate of uncompensated care, while the cost to attract and retain clinicians will grow only at rates above nominal inflation. Healthcare does not have a demand problem, just a monetization problem.

Icon-based summary graphic showing five upward-trending factors pressing against a single downward-trending factor. Rising factors are: demand for care, population age, chronic conditions, uncompensated care, and clinician cost. The single contracting factor is rates and revenues, illustrated with a left-pointing arrow indicating compression. The graphic conveys that costs and demand are increasing while the revenue base is shrinking, creating a margin squeeze. Source: HFS Research, 2026.

Clinician shortages

Burnout rates, slow speed to train replacements, and increasing demand for care are just some of the reasons clinician adequacy rates are likely to be in the high 80% range for physicians and in the low 90% range for registered nurses.

That rate will be worse for specialties most needed by the population based on demographics, such as primary care, geriatric care, and cardiology.

Icon-based summary graphic showing three upward-trending factors leading to a single compressed output. Rising factors are: burnout rate, training duration, and demand. The resulting output is clinician adequacy rates, shown at physicians in the high 80% range and registered nurses in the low 90% range. Source: HFS Research, 2026.

Patient expectations

Despite rising uninsurance rates, consumers remain primarily in control of who they see for care and when. In that context, their evolving expectations for speed, accuracy, and cost are critical to understand and address. The Kaiser Family Foundation reported that 36% of adults in the past 12 months have skipped or postponed care they needed because of cost. Other data indicate that up to 50% of consumers will switch doctors if their expectations are not met.

These factors can cost as much as 4% of annual revenue over 12 months and will compound if left unaddressed.

Icon-based summary graphic showing three upward-trending factors leading to a negative revenue outcome. Rising factors are: patient expectations, delaying care, and switching providers. The resulting revenue impact is a 4% decrease that compounds if left unaddressed. Source: HFS Research, 2026.

Exhibit 1: Medicaid cuts will shave up to 20 pts of margins in 2026 alone

Grouped bar chart comparing financial outcomes for health systems with Medicaid expansion versus without Medicaid expansion across 40 states plus DC in 2026. Revenue: $1,128 with Medicaid versus $1,109 without, a 1.7% decrease. Cost: $1,086 with Medicaid versus $1,075 without, a 1% decrease. Margin: 3.75% with Medicaid versus 3.05% without, an 18.6% relative decline. Dollar figures are in billions. Source: Urban Institute, Commonwealth Fund, HFS Research, 2026.

Source: Urban Institute, Commonwealth Fund, HFS Research, 2026

Playbook benefits: Balancing the existential crisis of survival with the future of care delivery

Health system CIOs must lean into the business of care delivery. This playbook takes a programmatic approach, enabling CIOs to execute a strategic roadmap with contained solutions that optimize their existing assets while allowing AI to deliver significant business benefits in quick succession.

Benefit 1: Tangible and quantifiable business outcomes
  • Clear revenues lift through reduced denials and underpayments while accelerating cash realization through denial prevention and recovery, coding support, and contract variance detection.
  • Lower operating costs by reducing waste and unit costs via automation of the back office, supply chain anomaly detection, improving forecasting, and throughput improvements.
  • Higher workforce productivity by returning time to clinicians by cutting pajama time and admin burden through inbox message triage, ambient documentation, and grounded clinical summarization.
Benefit 2: Making AI count with legacy tech
  • Faster ROI by leveraging existing data flows with legacy systems already producing reliable signals such as 835/837, remits, and ADT feeds that AI can leverage without having to rip-and-replace.
  • Modular add-on delivery with tight integration, leveraging Services-as-Software as an AI-enabled delivery paradigm while avoiding getting stuck in platform re-architecture.
  • Maintaining operational control and auditability by developing governance loops so AI is trusted, safe, and scalable inside current operating models.
Benefit 3: Preparing for the future of care delivery
  • A command-center operating model to drive predictive orchestration of discharge barriers, LOS risk, and staffing and bed actions so that systems can manage increasing demand with constrained labor.
  • Digital-first patient with AI-driven access, intake, and front door capabilities to reduce leakage with no-shows, speed time-to-appointment, and improve self-serve completion.
  • More resilient care teams with scaled virtual nursing, AI monitoring, and closed-loop results follow-up to reclaim nurse time, reduce missed follow-ups, and raise patient trust as care shifts to a digital-biased hybrid.
The solution: AI-enabled modularity delivered by SaS

Care delivery CIOs must feel comfortable with an AI-enabled, modular approach to addressing the four key business challenges, rather than relying on legacy platform enablement. Modularity will not preclude tight integration; however, that integration must be considered notional by adopting Services-as-Software™ (SaS) as the delivery paradigm (see Exhibit 2).

Exhibit 2: Services-as-Software will evolve to become the default delivery paradigm to enable AI for the next 25 to 50 years

Process flow diagram contrasting traditional delivery with the Services-as-Software model. On the left, traditional delivery encompasses three elements: people-based execution, process outsourcing, and static annual contracts. A curved arrow labeled "a new delivery paradigm inspired and enabled by AI" flows rightward into the Services-as-Software arrow on the right. The Services-as-Software model encompasses three elements: IP-led execution, outcome orchestration, and dynamic telemetry-driven value realization. Source: HFS Research, 2026.

Source: HFS Research, 2026

The plan to execute practically

This playbook has identified 17 key solutions for delivering the largest bang for the buck in the least amount of time, leveraging existing tech-enabled capabilities and adopting SaS to deliver (see Exhibit 3). These solutions have been laid out in a practical sequence that will allow CIOs to achieve rapid ROI with lower risk, easier governance, and avoid the typical challenges of being stuck in pilot purgatory.

Exhibit 3: Delivering targeted business value with AI in a specific sequence to maximize outcomes

Horizontal swimlane Gantt-style chart mapping 17 AI solutions across a 12-month timeline, organized into four phases and four key challenge categories. Phase 1 (Fund the program, months 1 to 3) addresses revenue headwinds with solutions 1 through 3: denial prevention and recovery, AI-assisted CDI and coding specificity prompts, and contract variance and underpayment detection. Phase 2 (Return time, months 2 to 6) addresses clinician shortage with solutions 4 through 6: in-basket message triage and draft responses, ambient documentation, and clinical summarization copilot. Phase 3 (Create capacity for margins, months 4 to 10) addresses margin deterioration with solutions 7 through 11: predictive capacity command center, perioperative optimization, clinical variation analytics, supply chain forecasting and anomaly detection, and back-office automation; plus solution 12 (virtual nursing and AI-assisted monitoring) and solution 13 (closed-loop results follow-up), which overlap into adjacent phases. Phase 4 (Win the consumer, months 7 to 12) addresses patient expectations with solutions 14 through 17: AI-driven access and leakage prevention, AI digital front door, AI-assisted pre-registration and intake, and cost transparency. Source: HFS Research, 2026.

Source: HFS Research, 2026

The playbook: A roadmap that optimizes legacy with the potential of AI

This playbook has been developed with inputs from tens of practitioners, technologists, and healthcare experts. The intent is to rapidly deliver 17 solutions across four phases to directly address financial headwinds, margin deterioration, clinician shortage, and patient expectations.

Phase 1: Fund the program

Phase 1 addresses revenue headwinds. These four solutions fund the overall program and mitigate the need for capital expense or net new investments. You must implement three of these solutions in Phase 1; you can implement the fourth in Phase 4.

Solution 1: Denial prevention and recovery

Solution 2: AI-assisted clinical documentation improvement (CDI) and coding specificity prompts

Solution 3: Contract variance and underpayment detection

Phase 2: Return time

Given the shortage of clinicians, the idea is to optimize clinician time by returning time to them with these four solutions. We recommend executing the first three in Phase 2 and the fourth in Phase 3.

Solution 4: In-basket and message triage with draft responses

Solution 5: Ambient documentation

Solution 6: Clinical summarization copilot with grounded chart synthesis

Phase 3: Creating capacity for margins

Phase 3 addresses margin deterioration with seven solutions.

Solution 7: Predictive capacity command center (flow, discharge barriers, bed/staff actions)

Solution 8: Perioperative optimization

Solution 9: Clinical variation analytics and pathway nudges

Solution 10: Supply chain forecasting and anomaly detection

Solution 11: Back-office automation

Solution 12: Virtual nursing and AI-assisted monitoring

Solution 13: Closed-loop results follow-up

Phase 4: Patient expectations

Patients’ evolving expectations are biased toward increased digital tool usage. We recommend these four solutions to address patients’ needs for faster care, higher diagnostic accuracy, and lower costs.

Solution 14: AI-driven access and leakage prevention

Solution 15: AI-assisted pre-registration and intake

Solution 16: AI digital front door

Solution 17: Price transparency

Our perspective

The following list includes relevant HFS perspectives on care delivery operations in a shifting market; watch for our series on executing Services-as-Software within a health plan and on selecting the right partner for success.

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