July 16, 2025

AI’s Next Healthcare Disruption: Transforming the Patient Experience

The next wave of AI is redefining the patient journey, making it digital, dynamic and data driven.

Healthcare leaders face the challenge of interpreting vast amounts of patient data to improve care outcomes. Current methods often fail to capture the full picture, leaving gaps in understanding patient sentiment.

This report explores how leveraging AI alongside traditional measures like HCAHPS can lead to significant improvements in patient experience. Discover how AI helps in uncovering hidden friction and strengthening marketing strategies.

Key takeaways:

• How AI is reshaping patient experiences beyond clinical settings,
• The advantages of complementing HCAHPS data with real-time AI insights, and
• Preparation strategies for an 1aI-driven future in healthcare

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July 8, 2025

Whitepaper: How Deborah Heart and Lung Cut Device Clinic Workload – and added $663K in Annual Revenue

Managing cardiac device patients shouldn’t overwhelm clinical teams or leave revenue on the table. Yet that was the reality at Deborah Heart and Lung Center – until they transformed their approach to remote monitoring.

This case study shows how Deborah reduced remote transmission review volume by 33 percent, grew managed patients by 44 percent with no added staff, and captured $663,000 in new revenue plus $973,100 in annual cost savings.

Inside, you’ll learn how their team modernized workflows, optimized billing and reclaimed time without adding headcount.

Key Takeaways:

• One change eliminated 27,000-plus unnecessary transmissions annually,
• The billing process drove a $66,000 revenue increase from compliance improvements alone, and enabled heart failure monitoring that added $597,000 in revenue, and
• Smarter alert protocols cut clinician workload and improved patient management

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Whitepaper: How Deborah Heart and Lung Cut Device Clinic Workload – and added $663K in Annual Revenue

July 8, 2025

Survey Results: AI – Burnout Fix or Budget Risk? What Health System Leaders are Really Seeing

Generative AI isn’t on the horizon – it’s already here, influencing decisions form the C-suite to the bedside.

A new Becker’s Healthcare and Microsoft survey of 150 healthcare leaders reveals how executives are deploying AI across strategy, documentation and clinical operations – and what’s coming next.

The insights reflect real-world priorities, from reducing burnout to enhancing diagnostic precision, and what separates organizations driving results from those falling behind.

In the Report:

• Why 42% of health systems plan to boost generative AI investments,
• How AI-driven documentation is reducing burnout and improving care accuracy, and
• What top clinical leaders say about ROI, integration and the future of ambient.

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July 8, 2025

Whitepaper: The Truth About AI Coding: Why Faster Doesn’t Mean Better

Healthcare organizations are under pressure to automate – but automation without outcomes is just overhead. This guide takes a hard look at where AI coding falls short and what revenue cycle leaders need to do differently to actually move the needle.

Built for multi-specialty and high-complexity groups, the guide outlines why AI tools alone can’t resolve documentation gaps, shifting payer logic or specialty-specific denials – and what strategies are working now to drive real results.

In the Whitepaper

• Why early AI adopters saw speed gains but not revenue gains,
• How to assess if your organization needs AI coding or a stronger foundation, and
• What a revenue-driving AI strategy actually looks like for complex specialties.

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July 8, 2025

Whitepaper: How Health Systems Can Assess the Safety of Clinical AI Tools

As clinical AI tools enter hospitals and decision support systems, few come with clear safety guardrails. Without rigorous testing, they risk spreading misinformation or introducing avoidable clinical harm.

A recent large-scale review evaluated more than 400 AI-generated clinical responses from one tool across five dimensions – including helpfulness, correctness and potential harm – using a reproducible, clinician-led framework.

Findings show that the vast majority of responses were rated accurate by independent reviewers – licensed physicians and pharmacists – with only a small portion presenting potential clinical risk.

Inside the whitepaper:

• How to measure AI output using reproducible evaluation methods,
• Lessons from a real-world model that helps mitigate risks of hallucinations and inaccuracy, and
• Best practices for assessing AI tools used in clinical decision support.

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June 25, 2025

Whitepaper: Infusion Care in Crisis: Why 82% of Centers Struggle to Access the Data They Need

As cancer diagnoses rise, infusion centers are navigating a perfect storm: workforce shortages, uneven patient flow and limited visibility into performance. Leaders are struggling to balance staff workloads, manage scheduling bottlenecks and prepare for growth – many without the tools to make informed decisions.

A new survey of nearly 200 cancer center executives identified where operations are breaking down and how centers can adapt. From AI-enabled scheduling to workforce optimization, this report outlines real-world strategies that are already delivering measurable ROI.

Download this report to explore:

• Top 3 operational challenges centers face in 2025 – and what’s driving them
• How new models are reducing burnout and improving staff-to-patient ratios
• What successful growth planning looks like amid limit6ed budgets and workforce constraints

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June 23, 2025

Article: Insurers Pledge Ease to Prior Authorizations

The broader health insurance industry has announced a series of commitments to streamline, simplify and reduce prior authorization requirements across commercial, Medicare Advantage and managed Medicaid plans covering 257 million Americans.

“The health care system remains fragmented and burdened by outdated manual processes, resulting in frustration for patients and providers alike,” AHIP President and CEO Mike Tuffin said June 23. “Health plans are making voluntary commitments to deliver a more seamless patient experience and enable providers to focus on patient care, while also helping to modernize the system.”

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June 9, 2025

Article: Workplace, Community Violence Costs Hospitals $18B annually: AHA

A report from the American Hospital Association (AHA) highlights hospital spending on workplace and community violence.

The report, “The Burden of Violence to U.S. Hospitals: A Comprehensive Assessment of Financial Costs and Other Impacts of Workplace and Community Violence,” was prepared for the AHA by Harborview Injury and prevention Research Center in Seattle, part of the University of Washington School of Medicine.

Three numbers that illustrate the burden of violence to hospitals:

• The AHA estimates the total annual financial cost of violence to hospitals in 2023 to be $18.27 billion.
• The $18.27 billion estimate i8ncludes pre-event costs ($3.62 billion) and included costs for:
  • training security and staffing,
  • policy and procedure development,
  • outreach to build public trust,
  • facility modifications to prevent and mitigate harm, and
  • technology investments to monitor events.
• The $18.27 billion estimate also includes post-event costs ($14.65 billion) and included costs for:
  • healthcare,
  • staffing,
  • replacement and repair of infrastructure and equipment,
  • legal costs, and
  • community and public relations costs.
    • The AHA said post-event healthcare expenses to treat violent injuries was the largest contributor to the total annual financial cost of violence to hospitals.

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June 9, 2025

Article: Redefining Utilization Management: The Role of AI

Artificial intelligence (AI) is transforming industries, and healthcare is no exception. In a high-level exploration during the recent webinar “Redefining Utilization Management: The Role of AI, MCG’s Senior Clinical Integration Analyst, Miriam Moerbe, MS, BSN, RN, provided a basic exploration on what AI is, how it relates to healthcare and utilization management (UM), and key considerations when deciding if it’s right for a hospital, health plan, or government organization.

Three types of AI to consider:

• Machine Learning
  • This is a type of AI that uses algorithms, rules, and data analysis to make data-driven recommendations.
• Natural Language Processing (NLP)
  • This is a computer’s ability to understand text and spoken words in the same way human beings can by extracting symptoms, diagnoses, and treatments from narrative text.
  • In broader terms, it is machine learning to understand text and the spoken word.
• Large Language Models (LLMs)
  • LLMs are fed enormous amounts of data to learn intricate patterns and nuances.
  • By using what it has learned from data, it can predict words and sentences based on probability.

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