What Does It Really Take to Prepare Nurses for Practice?

Elsevier researchers shared five new studies at INACSL 2026 — here's what they found about Practice Readiness, Flipped Simulation, Clinical Judgment, Simulation Accessibility, and Licensure Prediction.

Every year, thousands of new nurses graduate from rigorous programs and are still underprepared for the complexity of real patient care. It's not a failure of effort or intelligence; it is a gap between the traditional progression of nursing education. From lecture, to skills lab, to simulation, and ultimately to patients on the clinical floor — and the complexity of clinical practice, where knowledge, skills, communication, and judgment must come together in real time.

At the INACSL 2026 Conference in Oklahoma City, Elsevier's Learning Research and Design Team presented five sessions — two educational workshops and three research posters — addressing that gap head-on. Together, the sessions show how programs can strengthen the full transition-to-practice pathway: preparing students before simulation, making readiness and clinical judgment more visible, identifying licensure risk earlier, and designing accessible simulations so every learner can participate meaningfully.

Here's a look at what the research showed and what it means for nursing programs working to close the practice readiness gap.

1. Educational Session: Flipped Simulation — Using Case Study Videos to Prepare Nursing Students for High-Fidelity Scenarios

Authored and presented by: Maria Pfrommer, PhD, DNP, FNP-BC, RN; Elizabeth Lucas, EdD, RN, CNE; and Raman Kaur, MSN, AGNP-C, RN-BSN Additional authors: Mamta Shah, PhD; and Kelsey LaFayette, DNP, RN, FNP-C

Simulation time is scarce. When students arrive underprepared, faculty end up reviewing basic concepts instead of observing and developing clinical judgment which means a high-value learning opportunity is wasted.

The flipped simulation model solves this by shifting foundational preparation to before the lab. Students watch a relevant case study video from Osmosis from Elsevier and complete a structured prep sheet that includes recognizing clinical cues, forming hypotheses, planning actions, and drafting an SBAR before they ever step into the simulation. When they arrive, the scenario time is freed for the application, communication, and debriefing that simulation does best.

This session introduced a complete Flipped Simulation Toolkit: student prep materials, AI support prompts, faculty guides, structured debrief tools, a clinical judgment rubric, and a remediation planner. The toolkit is designed to be implemented incrementally and adapted to different program needs.

Access the Flipped Simulation Toolkitopens in new tab/window

The outcome: students who arrive better prepared, faculty who can actually observe how students think, and debriefing discussions that go deeper because there's something real to reflect on.

2. Educational Session: Advancing Practice Readiness with the Clinical Practice Readiness Assessment (CPRA)

Authored and presented by Elizabeth Lucas, EdD, RN, CNE Additional authors: Shannon Butts, PhD; Brittny Chabalowski, DNP, AGACNP-BC, CHSE, CNE; Michael Roth; Joy Loy; Crissy Halterman; and Mamta Shah, PhD

Research has found that only 14% of recently graduated RNs meet acceptable clinical assessment standards, and that 91% struggle to make sound decisions in clinical settings (Kavanagh & Sharpnack, 2021). Yet the tools nursing programs use to evaluate readiness remain inconsistent, subjective, and impossible to benchmark across institutions.

The Clinical Practice Readiness Assessment (CPRA) was designed to address that. Built on five high-fidelity, screen-based virtual patient scenarios with Next Generation NCLEX (NGN)-style questions, the CPRA places students into one of four competency levels: Emerging, Developing, Proficient, and Advanced — using a validated, standardized rubric.

Early research supports the CPRA's validity. In a benchmarking study across six schools and 295 learners, CPRA scores aligned accurately with established competency criteria. Notably, 67% of students scored at the Emerging or Developing level, consistent with existing readiness research, and a finding that gives programs a clearer, data-driven starting point for intervention rather than a reason for alarm.

A separate efficacy study at Bowling Green State University also revealed a striking finding: existing clinical evaluation methods showed no meaningful correlation with each other, confirming that a standardized tool like the CPRA fills a real measurement gap.

3. Poster: Enhancing Medical-Surgical Virtual Simulations with CJMM Scoring

Authored and presented by Elizabeth Lucas, EdD, RN, CNE; and Raman Kaur, MS, MSN-AGNP, BSN-RN Additional authors: Max Sommer, PhD; Mamta Shah, PhD; Shannon Butts, PhD; Brittny Chabalowski, DNP, AGACNP-BC, CHSE, CNE; and Krystal Pfleegor

Many students complete simulation scenarios without understanding how their decisions map to the cognitive processes of clinical reasoning. Without that connection, the learning stays surface-level.

Elsevier redesigned four undergraduate Medical-Surgical virtual patient scenarios to align with Layer 3 of the NCSBN Clinical Judgment Measurement Model (CJMM), the established framework for assessing clinical judgment. The enhanced scenarios embed NGN-style assessment items and include a new post-simulation results page that maps each student's performance to all six CJMM cognitive components: Recognize Cues, Analyze Cues, Prioritize Hypotheses, Generate Solutions, Take Actions, and Evaluate Outcomes.

Performance is reported on a three-point scale: Needs Improvement, Developing, Successful — and feedback is designed to guide students toward clear next steps, not just a score.

Development was informed by interviews with faculty and students, and early testing confirmed CJMM alignment. One important design insight emerged: complex decision-making scenarios, like an unresponsive patient or end-stage heart failure case, are better suited to full CJMM integration than procedural simulations, pointing to how simulation design needs to match assessment goals.

4. Poster: From Simulation to Licensure Readiness — Shadow Health Mastery as a Predictor of HESI Exam Performance

Authored and presented by Elizabeth Lucas, EdD, RN, CNE Additional authors: Mamta Shah, PhD; Ryan Baker, PhD; Lina Lander, MBA ScD; Max Sommer, PhD; and Shannon Butts, PhD

Building on prior research showing that HESI Exit Exam scores at or above 850 predict a 98% first-time NGN-RN pass rate, this study asked a deeper question: can Shadow Health simulation data serve as an early signal of licensure readiness before students ever sit for the HESI?

The retrospective study examined 143 ADN students across four U.S. programs and analyzed six Shadow Health engagement indicators, including mastery scores for objective and subjective data collection, time on task, and post-exam review behavior, in relation to HESI performance.

The findings were clear: quality of engagement consistently outperformed quantity. Mastery scores instead of time spent were the strongest predictors of HESI performance. In Medical-Surgical simulations, effect sizes were among the highest in the study, making Med-Surg simulation performance the most powerful early indicator of licensure readiness identified.

One counterintuitive finding: students with excessively high patient interaction ratios in Psych/Mental Health scored lower on HESI suggesting that more attempts without reflection can signal confusion rather than mastery.

5. Poster: Designing Screen-Reader-Accessible Virtual Patients — A Shadow Health Blueprint for Nursing Simulation

Authored and presented by Elizabeth Lucas, EdD, RN, CNE; Raman Kaur, MSN-AGNP; and Sneha Shenoy Additional authors: Max Sommer, PhD; Mamta Shah, PhD; Krystal Pfleegor; and Shannon Butts, PhD

Equitable access to simulation isn't just an ethical imperative, it's an educational one. Yet many virtual simulation platforms remain inaccessible to students who rely on screen readers, keyboard navigation, or other assistive technologies.

Elsevier's team approaches accessibility as a fundamental redesign, not an accommodation bolted on after the fact, and undertook a comprehensive redesign of Shadow Health's Medical-Surgical simulations to meet Web Content Accessibility Guidelines (WCAG) 2.2 AA standards.

The process began with user testing involving participants with low-vision impairments and keyboard-only navigation needs. Their feedback shaped a set of targeted design principles including authored audio descriptions for all animations and device readings, keyboard-first navigation parity, and an internal screen reader with simulation-specific audio content.

The result is a replicable blueprint for nursing simulation design: equity built in from the beginning, without compromising clinical fidelity, scoring integrity, or competency mapping.

The Common Thread and Looking Ahead

Elsevier's participation in INACSL 2026 underscored a commitment to evidence-based innovation in nursing simulation. Across the full arc of student development, this work showed how pre-simulation preparation can bridge classroom learning to simulation, scaffold curriculum, and strengthen clinical judgment before students enter the lab. It also demonstrated how objective assessment, predictive analytics, and accessible design can support practice readiness for every learner.

Across all five presentations and posters, a few themes emerged consistently: the importance of making clinical judgment visible and assessable; the value of designing with the learner in mind; and the responsibility of nursing education to close the readiness gap with data, not assumptions. Nursing education is at a pivotal moment. The tools and frameworks to do better already exist — and the research is showing us how.