Insights Archives – Ensemble Health Partners https://www.ensemblehp.com/blog/category/insights/ Your modern revenue cycle solution Wed, 03 Dec 2025 20:36:28 +0000 en-US hourly 1 https://www.ensemblehp.com/wp-content/uploads/2023/10/Logo-Chevron-80x80.png Insights Archives – Ensemble Health Partners https://www.ensemblehp.com/blog/category/insights/ 32 32 Where LLMs Make Sense — and Where They Don’t https://www.ensemblehp.com/blog/llms-use-rcm/ Wed, 03 Dec 2025 20:17:55 +0000 https://www.ensemblehp.com/?p=20327 Understanding when to use an open reasoning model versus a deterministic or predictive system is the new systems-thinking challenge. … Read More

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Hospitals and health systems face constant pressure to balance innovation with financial stewardship. Relying on the right revenue cycle management partner to pilot and validate emerging technologies allows hospitals to sidestep the high costs, operational risks and distraction of building in-house “start-up” capabilities.

An end-to-end RCM partner like Ensemble brings specialized expertise, proven frameworks and the ability to absorb early-stage errors, so hospitals don’t have to invest in expensive infrastructure or retraining. This approach protects capital and reduces the risk of unsustainable expenses while keeping the organization’s focus on delivering high-quality clinical care.

But what are the tools that are being assessed?

Every technology shift in the healthcare industry creates a temptation to apply the new tool to every problem. That’s what we’re seeing with large language models (LLMs) today. The truth is, not every workflow benefits from a model that “reasons.” Some problems need prediction; others need precision. Some need exploration; others need control.

Understanding when to use an open reasoning model versus a deterministic or predictive system is the new systems-thinking challenge. Let’s break that down.

The three lenses: effectiveness, efficiency and cost

Lens

Effectiveness

Efficiency

Cost

Core Question

Does it improve the outcome quality?

Does it reduce cycle time or human effort?

Does it justify the compute, integration and error cost?

Example Metric

Accuracy, recall, relevance

Task completion time, agent handoff rate

Cost per 1K tokens, rework time, supervision hours

If it’s high-value but low-tolerance for error (like financial reconciliation), deterministic systems win. If it’s ambiguous, language-based or multi-factorial (like summarizing clinical notes or writing appeals), reasoning models add value. If it’s highly repetitive, rule-bound and measurable (like claim edits), predictive or deterministic systems outperform reasoning models on cost and reliability.

The framework: "R.E.A.L."

Step

R — Reasoning needed?

E — Error tolerance defined?

A — Available data type?

L — Latency vs. learning tradeoff

Description

Does the problem require contextual synthesis, judgment, or multi-variable reasoning?

How much error can the system absorb before cost or compliance risk outweighs speed?

Do you have structured, labeled data or mostly unstructured narratives?

Is it more important to get to an output quickly or to improve over time?

Example

Interpreting denial letters or coding documentation.

Appeals generation can tolerate 10% edits; payment posting cannot.

Eligibility checks use structured data; prior auth notes do not.

A chatbot can iterate; a claims router must decide instantly.

If three of the four lean toward “Reasoning / Context,” use an LLM or open reasoning model. If three lean toward “Control / Determinism,” stay with algorithmic or predictive logic.

Practical use cases in revenue cycle management

Revenue cycle example: Denial prevention vs. Denial appeals

Denial prevention: Rules-based, deterministic systems are optimal. You know the payer rules, and you can code deterministic edits. Adding a reasoning model increases cost and potential drift without clear benefit. However, you can use reasoning models to explore large datasets and look for potential new rules. You can also use machine learning classification models such as regression, random forest or gradient boosting if the rule set is not easily written as “If X then Y”. These models are still much more efficient than broad-based LLM models.

Denial appeals: Context matters — clinical justification, payer policy and tone. An LLM with reasoning and retrieval capabilities can draft appeal letters 3–4x faster than humans, with a small manual review loop.

Ensemble’s data shows 40%–60% cycle time reduction for appeal generation using Generative AI.

Cost and control: The hidden variables

Model Type

Deterministic

Predictive

Reasoning (LLM)

Unit Cost

Low

Medium

High

Error Cost

Low

Medium

Variable

Control Level

High

Medium

Low-Medium

Ideal Use Case

Compliance, validation, automation at scale

Forecasting, triage, prioritization

Interpretation, communication, synthesis

When evaluating AI in revenue cycle, the total cost equation matters — not just model performance. That equation should include compute, supervision time, correction rework, regulatory or reputational risk and the costs of model retraining or context injection. For example, running GPT‑4 Turbo on 10 million claims would exceed $1 million per month in token cost alone, while deterministic logic could accomplish the same work for <$10K. Overlooking hidden costs like this can turn a promising AI initiative into an unsustainable expense, eroding ROI and slowing adoption.

The decision tree

If the input is structured, use deterministic or predictive models. If it is not, the next question is whether the outcome is binary or open-ended. If binary, use predictive models. If open-ended, use reasoning models. If the error cost is high, a deterministic model is a good fit. If not, use reasoning or hybrid models. Finally, consider if the task requires contextual synthesis or judgment. If yes, use a reasoning model. If not, choose a predictive model.

Bringing it together: Hybrid systems win

The best architectures combine reasoning, predictive and deterministic logic — not as competing models, but as layers of trust and speed.

  • Layer 1: Deterministic filters — data validation, policy edits.
  • Layer 2: Predictive triage — probability of denial, next-best action.
  • Layer 3: Reasoning model — narrative generation, summarization, contextual insight.

Each layer narrows the field, improving both efficiency and controllability. You get the speed of automation without the chaos of unbounded reasoning.

The goal isn’t to use LLMs everywhere — it’s to use them where human reasoning is the bottleneck. And remember: if you can define the outcome with a clear rule, code it. If you can’t, predict it. If you still can’t, reason it.

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]]> Payer Trendscape 2025: 3 Trends to Track  https://www.ensemblehp.com/wp-content/uploads/2025/11/Payer-Trendscape-2025.pdf#new_tab Thu, 13 Nov 2025 17:46:02 +0000 https://www.ensemblehp.com/?p=20250 Payers are reshaping hospital reimbursement at the expense of compliance + cash flow. We dig into the data + offer tips to boost performance. … Read More

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]]> Payers are reshaping hospital reimbursement at the expense of compliance + cash flow. We dig into the data + offer tips to boost performance.

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]]> The WISeR Model: Using AI in a New Era of Prior Authorizations for Medicare https://www.ensemblehp.com/blog/the-wiser-model/ Wed, 05 Nov 2025 19:11:52 +0000 https://www.ensemblehp.com/?p=20165 The Wasteful and Inappropriate Service Reduction (WISeR) Model introduces prior auths for select services at risk of fraud, waste and abuse. … Read More

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November 10 update: Since this article was published, CMS has shared key details of the WISeR Model that were previously pending. On the evening of Nov. 6, CMS revealed the technology companies selected as Model Participants — companies that will use enhanced technology like artificial intelligence to support medical necessity coverage determinations. These companies include Cohere Health, Inc., Genzeon Corporation, Humata Health, Inc., Innovaccer Inc., Virtix Health LLC and Zyter Inc. The following day, Democrats in the U.S. House of Representatives introduced legislation to repeal the model. With the January 1 effective date approaching, Ensemble will continue to monitor these developments as our operators prepare our clients for success under the model.

The Centers for Medicare & Medicaid Services (CMS) is launching the Wasteful and Inappropriate Service Reduction (WISeR) Model on January 1, 2026 — a bold, six-year initiative designed to tackle fraud, waste and abuse (FWA) in Medicare Fee-for-Service (FFS) by using advanced technologies — artificial intelligence (AI) and machine learning (ML) — to introduce prior authorization for select services at higher risk of FWA in certain selected states.

This model arrives at a critical moment where there’s heightened industry interest in incorporating AI into workflows along with heighted Federal interest in reducing FWA spending generally across the government. Its importance to FWA is further highlighted by a September 2025 Health and Human Services (HHS) Office of Inspector General (OIG) report, which found that Medicare Part B spending on one of the targeted services, skin substitutes, exceeded $10 billion in 2024, with alarming trends in utilization, pricing and fraud schemes.

The model, however, faces practical and political obstacles to its January 1 launch date. Practically, key details about the program remain unknown, and the ongoing government shutdown likely delays final decisions and communications about it from CMS.

Politically, several members of Congress have criticized WISeR, warning that its AI-driven prior authorization process could delay or deny necessary care for Medicare beneficiaries. Lawmakers argue the model threatens patient access and mirrors problematic practices in Medicare Advantage. A House resolution was introduced in September to halt the model, followed by a proposed amendment to the HHS funding bill to block funding of the model. The status of this opposition remains unresolved during the ongoing government shutdown. The American Hospital Association also recently voiced its concerns with the model and urged CMS to delay its launch by six months.

What is the WISeR Model?

WISeR is a CMS Innovation Center initiative focused on reducing unnecessary and inappropriate services in Medicare FFS by using AI and ML to streamline prior authorization (PA) and medical review processes for items and services vulnerable to FWA, such as skin substitutes, electrical nerve stimulators and knee arthroscopy for osteoarthritis.

WISeR’s implementation is driven by the vulnerability of certain Medicare services to FWA, rising concerns of overuse and patient safety. With significant wasteful spending — up to 25% of U.S. healthcare costs per CMS — and documented fraud in areas like skin substitutes, CMS seeks to leverage AI and ML to modernize oversight and ensure care is both clinically beneficial and safe for patients while also ensuring payment complies with Medicare rules.

WISeR is not a mandatory model for Medicare providers in the selected states of Arizona, New Jersey, Ohio, Oklahoma, Texas, Washington. Providers in these states will have the option to submit a prior authorization request or go through a post-service/pre-payment review. WISeR does not change Medicare coverage or payment policy.

How does WISeR work?

  1. Model Participants: Companies selected by CMS with expertise in AI and ML tech-enabled PA will perform reviews and issue a prior authorization decision (affirmation or non-affirmation) of the requested procedure. Non-affirmation decisions require the review of a licensed clinician prior to issuance. The Model Participants’ compensation is controversially tied to the amount of savings associated with their denials. These AI vendors have not yet been announced by CMS.
  2. Targeted services: WISeR identifies high-cost, high-risk Medicare Part B services for review, including skin and tissue substitutes, electrical nerve stimulators, knee arthroscopy and more. Excludes inpatient, emergency and risky delayed services.
  3. Provider participation: As previously stated, the model is optional, so providers in selected states (Arizona, New Jersey, Ohio, Oklahoma, Texas, Washington) can choose to submit PA requests for targeted services or proceed with rendering the services understanding the claim will undergo pre-payment review.
  4. Submitting a prior authorization request: Providers in designated regions who choose to submit a PA request will submit supporting documentation for the targeted service to either their regional MAC with the MAC routing to the Model Participant or directly to the Model Participant who will then use AI and ML tools to perform its review to make a coverage decision.
  5. Decision issued: The Model Participant notifies the provider of its decision to affirm or not affirm the service. If affirmed, the Model Participant will provide a unique tracking number to inform a payment determination when the claim is submitted. If not affirmed, the provider may either resubmit its request (unlimited opportunities to do this) or request a peer-to-peer review.
  6. Gold Carding: Providers with demonstrated records of compliance may receive exemption from PA requirements, subject to compliance monitoring.
  7. Safeguards: All data sharing is HIPAA-compliant, and the appeals process remains unchanged for denied claims.
  8. Medicare coverage and payment policies remain the same. WISeR does not change Medicare coverage or payment policy.

How is Ensemble addressing WISeR's implications for providers?

The WISeR Model has key implications for providers:

  1. Providers in the selected states must choose whether to adopt these new PA processes or risk claims for targeted services being pended for pre-payment review or potentially denied.
  2. High performers may benefit from reduced administrative burden through gold-carding.

WISeR represents a pivotal shift in CMS oversight by introducing prior authorization requirements to Medicare FFS services. For CFOs and financial leaders of healthcare providers, proactive engagement with WISeR’s design and opportunities will be key to driving success with the model’s requirements.

At Ensemble, we are actively working to position our clients for success under WISeR. For states impacted by WISeR where we have a client footprint, we are focusing on identifying impacted procedures, engaging vendor partners and building automation into prior authorization workflows. Our teams are currently mapping these areas and initiating discussions with vendors to align planning and next steps.

This approach ensures that when CMS announces approved AI vendors (i.e., Model Participants), we will be ready to integrate prior authorization processes quickly and effectively, so as to avoid pre-payment medical reviews and potential denials. This approach also positions our clients for success in qualifying for gold-carding.

Our goal is to automate as much as possible across all client platforms. In this way, we can reduce administrative burden and accelerate approvals through configuration of existing systems, streamlined routing logic for documentation and integration with external authorization solutions and approved CMS vendor solution partners.

By acting now, we aim to ensure our clients are prepared, compliant and positioned to leverage automation for efficiency and cost savings under the WISeR Model.

For more information:

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]]> Ensemble Outperforms in Latest KLAS End-to-End RCM Report https://www.ensemblehp.com/blog/ensemble-outperforms-in-latest-klas-end-to-end-rcm-report/ Thu, 11 Sep 2025 12:40:09 +0000 https://www.ensemblehp.com/?p=19417 Ensemble received the highest client satisfaction across all metrics and a top overall performance score of 95.1 on a 100-point scale. … Read More

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Facing limitations in internal expertise, resources and technology, many healthcare organizations have turned to end-to-end revenue cycle outsourcing (RCO) firms for support. Most are looking for a true partner, one who can provide more than just third-party vendor aid.

I strongly encourage folks to not use the word outsourcing. If you think this type of engagement is outsourcing, you probably ought to just stick with what you have. You are going to need a partnership that feeds the lifeblood of your organization, namely your revenue...If you can’t get your mind around the fact that this is a partnership and that each party is an extension of the other, then I think the experience will be difficult.

C-suite executive, KLAS End-to-End Revenue Cycle Outsourcing September 2025 Report

Key factors driving the choice of a partner in the revenue cycle include a firm’s:

  • Model or approach
  • Expertise + regional familiarity
  • Technology
  • Partnership
  • Contract terms/price
  • Reputation

Research and insights firm KLAS recently released its biannual End-to-End Revenue Cycle Outsourcing Report to assess the market impacts of these decisions, asking the question “Which firms are delivering superior outcomes through innovation and collaboration?”

Ensemble, the 2025 Best in KLAS winner for End-to-End Revenue Cycle Outsourcing and a five-time Best in KLAS winner, also received the highest client satisfaction across all metrics and a top overall performance score of 95.1 on a 100-point scale.

Our clients partner with us because our clients succeed with us.

Ensemble’s approach fuses performance excellence with strong, enduring partnerships, delivering results that matter and relationships that last.

I know every firm in the revenue cycle space, and I know the difference between Ensemble and every other firm. Quite honestly, there is no comparison. Things with Ensemble have been fantastic. From a client perspective and a services perspective, the responsiveness, the expertise, the support, and the performance against KPIs have all been extraordinary since day one.

CEO/President, KLAS Research Interview, March 2025

This isn’t lip service — the proof comes directly from our clients. When surveyed by KLAS:

  • 100% would buy again
  • 94% say Ensemble exceeds expectations

That’s because we don’t just make promises. We deliver proven results across critical performance metrics.

Read the full KLAS End-to-End Revenue Cycle Outsourcing 2025 Report

In the KLAS report, nearly 88% of clients report being satisfied or highly satisfied with Ensemble’s impact across all key areas surveyed:

• 83% AR days
• 92% cash collections
• 92% denial rates
• 83% patient experience

We’re investing heavily in AI so our clients don’t have to.

We’ve repeatedly proven that we can deliver top results for our clients, but we’re determined to stay one step ahead of the market. This is just one of the reasons why we’re leading the industry in AI innovation and investment in RCM.

No E2E RCM firm is investing more in AI than Ensemble — it’s that simple. Respondents to the KLAS report expressed excitement about our significant investment in AI and expansion into payer strategy.

We see Ensemble as a pioneer in AI. Ensemble really has embraced AI from day one. They use it a lot in current technology, and they are always exploring new ways to use AI to help improve efficiency.

CEO/President, Klas Research Interview, May 2025

When it comes to RCM market growth, Ensemble has no peers.

The numbers don’t lie. Ensemble has experienced unrivaled growth in the end-to-end revenue cycle outsourcing space. Since the last KLAS report, Ensemble was selected in more validated new end-to-end RCM partnerships than any other firm in the sample.

This rapid growth is a vote of confidence from the organizations that sit at the heart of the revenue cycle, the providers on the frontlines with patient care. The ready expansion of Ensemble’s client base solidifies our position as the partner of choice for healthcare organizations seeking transformative RCM solutions.

The bottom line

Throughout the KLAS survey and in repeated testimonials, clients consistently highlight their deep, trust-based partnerships with Ensemble. These are built on:

  • Transparent expectations set early in the sales process
  • Structured governance and collaborative leadership post-implementation
  • Frequent, purposeful communication

At Ensemble, it’s our partnerships with incredible hospitals and health systems that power our performance.

…Anytime we have a fire, such as a patient experience issue, Ensemble is willing to jump in and help solve the problems for us. If I call with a facility issue, they will have somebody on the ground the next week working with that facility. Ensemble has been very engaged and responsive. Ensemble has our long-term interests at heart…

CFO, KLAS Research Interview, May 2025

The right end-to-end partnership is not just helpful or a “nice to have” option; it is an essential support mechanism for the lifeblood of a health system — its revenue cycle.

By grounding our efforts in measurable outcomes, offering comprehensive operational support and relying on a seasoned team backed by top talent, technology and transformation, Ensemble has proven repeatedly why we’re the top choice of healthcare organizations nationwide.

Read the full KLAS End-to-End Revenue Cycle Outsourcing 2025 Report.

Get the Report

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]]> Ensemble’s Always-On Management of Uninsured + Underinsured Populations https://www.ensemblehp.com/blog/ensembles-always-on-management-of-uninsured-underinsured-populations/ Thu, 14 Aug 2025 19:36:09 +0000 https://www.ensemblehp.com/?p=19320 Ensemble treats underinsurance as a perpetual, complex challenge, not a one-off crisis. Our end-to-end model easily scales to the OBBA era. … Read More

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Congress’ newly enacted One Big Beautiful Bill Act (OBBA) introduces work requirements, caps on state-directed payments and other measures that will slash roughly $1 trillion from Medicaid over ten years, leaving millions more patients potentially uninsured or under-insured according to the American Hospital Association.

While this has generated headlines, coverage churn is not new. State “Medicaid unwinding” began in April 2023 when unenrollments and reverification that had been suspended due to the Covid pandemic were lifted, and people fell off the rolls more quickly than they would have historically. This has already led to approximately 25 million disenrollments.

Ensemble has long treated under-insurance as a perpetual and complex challenge, not a one-off crisis. The same end-to-end operating model we deployed for the Medicaid unwinding easily scales to the OBBA era — protecting hospital revenue, safeguarding patient coverage and continuing to deliver a consumer-grade experience.

Why the industry is buzzing about OBBA

OBBA will bring significant impacts in the near future, including:

  • Medicaid cuts + work requirements: OBBA introduces nationwide work verification and tightens eligibility redeterminations. States that exceed the 3% limit on eligibility errors face fiscal penalties such as a reduction in matching federal funds.
  • Provider payment constraints: New caps on supplemental payments and limits on provider taxes intensify margin pressure for safety-net hospitals.
  • Timeline shock: Major provisions phase in beginning January 1, 2026, giving hospitals less than 18 months to prepare before these provisions are effective.

OBBA magnifies an already-underway shift from insured to self-pay. Success hinges on proactively qualifying patients for coverage and crafting frictionless payment pathways.

Coverage + conversations at every step

At Ensemble, we provide always-on management of uninsured and underinsured populations , another benefit of our end-to-end approach. Our interactions with patients at every stage enable us to have a greater impact and to keep sight of coverage issues throughout the entire process. By engaging with patients from scheduling all the way to post-service billing and payment, we also have the ability to handle challenges that arise at many different stages, rather than just one based on a single point solution deployment.

Our approach is:

  • Comprehensive, not episodic: Our model addresses every coverage disruption (e.g., policy change, life event or data error) through continuous analytics and advocacy.
  • Patient equity- and advocacy-first: Financial conversations emphasize benefits eligibility before payment collection, preserving community trust.
  • Digital by default, human by design: Tailored agentic AI automation handles routine eligibility and coverage checks as well as estimate creation. Trained financial advocates intervene where human judgment and care for the patients matter most.

Ensemble’s end-to-end patient-financial flow is already ready for OBBA, continually screening for coverage and centering the patient’s experience at every step.

Pre-service auto-screening

At scheduling, every patient record runs through Ensemble’s rules engine and 200+ data feeds to check Medicaid/Marketplace eligibility, commercial coordination of benefits, local charity and a propensity-to-pay score after an estimate is generated.

Digital estimate + financial clearance information

The patient receives a consolidated packet via preferred channel (text, email, portal) containing:

  • Accurate cost estimate
  • Real time coverage status and gaps
  • Simple task list (e-sign forms, document uploads, prompt-pay discount window)

Arrival + Point-of-Service advocacy

Fast-track check-in exists for financially cleared patients. If coverage or payment is pending, financial advocates engage pre-service. Emergency department or unscheduled inpatients get bedside assistance (where allowed by policy) to secure coverage and set up liability arrangements before discharge.

Continuous eligibility search + auto-populated applications

The platform keeps scanning for new coverage and can auto-qualify for charity. Our comprehensive database and connections not only look at Medicaid options but also COBRA, exchange plan options, local funding and special programs such as crime victim funds, searching all avenues for coverage so patients aren’t left to bear the financial burden on their own. If additional data is needed, it triggers pre-filled forms sent to the patient. They simply review and e-sign or snap photos of proofs of income/ID.

Customized payment solutions

Ensemble’s post-care outreach begins with the patient’s chosen channel (including email, text, agent or human call), then expands based on engagement analytics. Plans include:

  • Prompt-pay discounts for settlement within 15 days
  • Interest-free installments over a number of months, depending on the balance
  • Sliding-scale terms that mirror third-party financing without the 8%-15% merchant fees that siphon revenue from our providers

Auto-reverification + compliance reminders

For benefits subject to work-verification or annual proof-of-income, Ensemble triggers reminders 30/15/5 days before lapse. Patients respond by uploading documents (camera capture in app or web), keeping coverage — and revenue — intact.

Post-cycle analytics + bad debt reclass

If coverage still isn’t found, analytics rerun eligibility logic; newly identified payers prompt rebilling, or accounts convert to presumptive charity, as appropriate, to avoid bad debt write-off.

The bottom line

OBBA may feel like the latest earthquake in health-policy land, but for Ensemble and our clients it is simply another tremor our end-to-end model was built to absorb. Our model:

  • Mitigates coverage volatility: Automated screens and reverification reminders cut avoidable self-pay conversions triggered by OBBA’s new rules.
  • Protects hospital margin: Direct payment plans retain every dollar, avoiding fintech “skim” and preserving goodwill.
  • Elevates patient experience: One digital journey, from estimate to zero balance, reduces anxiety and boosts loyalty in an era of heightened financial sensitivity.

Continuous eligibility analytics, advocacy-centered workflows and fee-free payment flexibility keep patients covered and hospitals financially whole, no matter how the ground shifts next.

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]]> The Two Midnight Rule  https://www.youtube.com/watch?v=ialUSmCfLhQ#new_tab Thu, 24 Jul 2025 14:22:10 +0000 https://www.ensemblehp.com/?p=19239 Dr. Khiet Trinh + Dr. Maria Johar explain the Medicare Two Midnight rule, demonstrating how to determine inpatient versus observation status. … Read More

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]]> Dr. Khiet Trinh + Dr. Maria Johar explain the Medicare Two Midnight rule, demonstrating how to determine inpatient versus observation status.

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]]> What Is a Physician Advisor?  https://www.youtube.com/watch?v=s9mmVX8w_kg#new_tab Thu, 24 Jul 2025 14:15:31 +0000 https://www.ensemblehp.com/?p=19235 Dr. Khiet Trinh and Dr. Maria Johar explain the role of physician advisors in supporting clinicians with billing, status and denial issues. … Read More

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]]> Dr. Khiet Trinh and Dr. Maria Johar explain the role of physician advisors in supporting clinicians with billing, status and denial issues.

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]]> Inside the RCM Model Outperforming the Industry https://www.ensemblehp.com/wp-content/uploads/2025/07/Ensemble-Frictionless-RCM_eBook.pdf#new_tab Fri, 11 Jul 2025 15:51:30 +0000 https://www.ensemblehp.com/?p=19154 Don’t automate tasks; orchestrate the entire revenue cycle. Look inside the end-to-end model driving a 3% first-year revenue boost. … Read More

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]]> Don’t automate tasks; orchestrate the entire revenue cycle. Look inside the end-to-end model driving a 3% first-year revenue boost.

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]]> Cyber or System Downtime — Strategies for Staying Operational https://www.ensemblehp.com/blog/staying-operational-system-downtime/ Mon, 30 Jun 2025 14:23:25 +0000 https://www.ensemblehp.com/?p=19003 Epic Business Continuity Access + an Incident Recovery Application strategy help maintain operations during an incident + recover afterward. … Read More

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Why you need Epic Business Continuity Access and an Incident Recovery Application

Downtime is inevitable. Disruption doesn't have to be.

Whether caused by planned maintenance, unexpected outages, or cyber security incidents, system downtime is a reality every healthcare organization must face. But patient care can’t wait. That’s why having both Epic Business Continuity Access (BCA) and an Incident Recovery Application (IRA) strategy is essential. Together, they ensure your organization can maintain
operations and patient care during an incident and effectively recover afterward.

What is Epic Business Continuity Access (BCA)?

Epic BCA is a suite of tools that ensures users can access critical patient information even when the main Epic system is offline. It includes:

  • BCA PC: Standalone computers deployed across ambulatory clinics and throughout hospitals to print physical copies of patient info for use in conjunction with downtime procedures — even without network or power. This is a minimum requirement to maintain patient care.
  • BCA Web and Web Data Entry: A web-based portal for viewing reports, printing patient labels and entering essential data like ADT events during downtime so an up-to-date census is available. It also allows events and notes to file back into Epic, reducing manual work during recovery.
  • Isolated Recovery Environment: A pre-configured environment with a limited version of Epic that is accessed via a web browser to allow basic ADT and clinical note access along with secure chat, In Basket and basic appointment scheduling. This requires the use of Epic software called Harbor, which is available with the Epic November 2024 release and can be made available back to the February 2024 version with Special Updates.

Why BCA matters

BCA ensures that the hospital can continue to function at a basic level and access important information while IT and security teams work on recovery measures.

  • Continuity of Care: Clinicians can still access vital patient data to make informed decisions.
  • Operational Resilience: Keeps workflows moving during outages or cyber events.
  • Regulatory Compliance: Supports paper-based documentation to ensure nothing is missed.

What is Incident Recovery Application (IRA)?

IRA refers to the post-downtime recovery process that ensures all data captured during the
outage is safely and accurately integrated back into the Epic system.

Key IRA functions

  • Data Reconciliation: Transfers downtime records into the live system without data loss.
  • System Restoration: Verifies data integrity and supports safe reactivation of Epic.
  • Audit Readiness: Ensures complete and accurate records for compliance and reporting.

Why you need both: A dual strategy for resilience

During the Incident

BCA keeps patient care going with access to critical data.

Prevents chaos and delays in care.

Supports clinicians with tools like SRO, BCA PC, and Web Entry.

After the Incident

IRA ensures all downtime data is reconciled and restored accurately.

Protects data integrity and supports regulatory compliance.

Helps IT teams safely bring systems back online.

Best practices for implementation

  • Deploy BCA PCs across all care sites.
  • Set up BCA Web servers and ensure users have specific security added to their Epic template to allow them to access the web portal and enter data.
  • Configure CSN and MRN assignments to avoid duplicates in the Epic system.
  • Establish clear downtime protocols by site/department for data reconciliation and system restoration.
  • Conduct regular drills to ensure readiness across clinical and IT teams.
  • Create a workflow to send special downtime reports daily.
  • Create a separate cloud server environment with a secure connection to the primary data center. Epic Hosting offers this service.

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]]> How We’re Addressing Patient Referral Leakage https://www.ensemblehp.com/blog/how-were-addressing-patient-referral-leakage/ Fri, 16 May 2025 13:15:10 +0000 https://www.ensemblehp.com/?p=18297 By understanding the causes of referral leakage, we can develop strategies to mitigate it, ensuring patients receive coordinated care. … Read More

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Referral leakage, also occasionally referred to as network leakage, occurs when a healthcare provider directs a patient to receive care outside of their affiliated hospital network.
This phenomenon can detract from the patient’s overall care experience in numerous ways:

  • Medical records may not transfer seamlessly, leading to gaps in information
  • Patients may not schedule appointments due to confusion about who initiates the process
  • Duplicate tests may be ordered if the new provider doesn’t have access to prior results
  • Out-of-network care can lead to higher out-of-pocket costs for patients
  • Lack of follow-up and coordination can result in worsened health conditions

In addition to being detrimental to the patient experience, patient referral leakage can also result in substantial financial losses for healthcare organizations and disrupt the continuity of patient care. Consider this:

  • The average cost per claim for MRI, CT, PET, mammogram, ultrasound and cardiac testing is approximately $1,500.
  • If one provider refers these tests externally four times per month, it could result in an annual revenue loss of $72,000.
  • When this figure is multiplied by a group of 100 providers, it increases to a potential loss of $7.2 million in revenue.

By comprehensively understanding the causes and consequences of referral leakage, we can develop and implement strategies to mitigate it, thereby ensuring that patients receive coordinated and efficient care within our network.

What causes patient leakage?

Referral leakage can occur due to several factors, including ineffective patient retention initiatives, a lack of physician expertise within the network, negative patient experiences or difficulties in scheduling appointments.

Specifically, providers may refer patients to external organizations due to:

  • Cost of care: External facilities may offer more affordable rates or better payment plans, affecting referral decisions.
  • Geographic preference: Patients often choose healthcare providers that are conveniently located near their home or workplace.
  • Provider satisfaction: Factors such as quick turnaround times, established professional relationships and high-quality diagnostic images can influence referral choices.
  • Service availability: The absence of internal services or scheduling constraints may require referrals to external facilities.
  • Workflow inefficiencies: Complex or time-consuming internal referral processes can result in providers opting for external referrals.

Why reduce referral leakage?

Addressing referral leakage is critical for healthcare systems for multiple reasons — it not only helps improve revenue but also enhances patient care continuity and strengthens patient-physician relationships. Reducing referral leakage affects:

Revenue impact

Referral leakage can result in significant revenue reduction. When patients are referred outside the network, the organization loses potential income from services that could have been provided internally.

Patient retention

Keeping patients within the network ensures continuity of care, which can improve patient outcomes and satisfaction. High referral leakage rates may indicate issues in care coordination or patient satisfaction.

Care coordination

Effective management of referrals within the network enhances care coordination. This ensures patients receive timely and appropriate care, reducing the risk of medical errors and improving overall health outcomes.

Resource utilization

By minimizing referral leakage, provider groups can better utilize their resources, including specialists and facilities. This can lead to more efficient operations and better allocation of healthcare resources.

Market share

Reducing referral leakage helps maintain and grow the organization’s market share. Keeping patients within the network strengthens the organization’s position in the competitive healthcare market.

What are best practices to address patient referral leakage?

We support hundreds of hospitals with operational oversight and data analytics to improve revenue cycle performance and patient experience. Through those partnerships, we’ve crafted proven strategies to monitor referral patterns and leakage rates, identify trends, understand patient needs and improve retention and care delivery.

These strategies include:

  • Analyzing feedback: We use feedback from patients and providers to determine causes of leakage, such as negative experiences or scheduling difficulties.
  • Identifying resource gaps: We assess whether internal providers have adequate availability for referrals and identify any gaps in resources or scheduling.
  • Focusing on the highest rates: We aim to address high referral leakage rates, particularly those exceeding 20%, to enhance care coordination and patient satisfaction.

Once strategy is set, we’ll recommend and help implement best-practice procedures to reduce referral leakage. This might look like:

Software optimization

  • Structuring and configuring referral workqueue
  • Setting required fields in the ordering process
  • Optimizing provider preference lists and network levels

Documentation and training enhancements

  • Creating and distributing templates to all employed providers listing in-house services and specialists, including service/specialist names, phone numbers, locations, and hours of operation
  • Establishing e-learning platforms and referral tip sheets for providers and staff

Analytics and reporting improvement

  • Reporting identified missing services to C-suite leadership
  • Implementing reporting tools and processes to be followed by managers to improve referral monitoring
  • Adding tasks to end-of-day checklists

Getting started

At every stage, client systems can support and partner with us to help their organization engage with the initiative:

  • Immediately, start conversations with leaders, practice managers and providers about the importance of referral retention. This proactive measure can help raise awareness and set the stage for more effective collaboration.
  • Up front, share existing referral retention initiatives and reporting.
  • Over time, adopt Ensemble’s best practices around referral leakage, allowing our teams to collaboratively work towards identifying the gaps and inefficiencies that cause this trend.

Implementing these strategies helps organizations retain more patients within their own networks, enhancing both patient care and financial stability.

The bottom line

Addressing the underlying causes of referral leakage will ensure patients receive consistent care within one network. By adhering to best practices procedures, we’ve proven that it is possible to reduce referral leakage, improve patient care and retain revenue within a healthcare system.

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