Solutions

Solutions powered by
Learn More.
Frame 586 (1)

Quality Manager formerly known as abaqis®

Mitigate risk and elevate your quality of care. Improving both clinical and business outcomes starts with a smarter, more integrated approach to regulatory training, continuing education and quality management.

Learn More

NEW TO THE STORE

hStream Content Marketplace

Connecting you to the Best Content. Access to 75 Partners and 35,000+ Courses in our Industry-Leading Marketplace. Streamline content purchasing, updates, hosting and connectivity for your organizational needs.

NurseGrid Learn

Online store for Clinical Learners. Individual CE Credit and industry products for Clinical Learners are now available through NurseGrid Learn (Beta). Explore our robust collection of courses that provides an unparalleled level of flexibility and choice.

DEA MATE Opioid and Substance Use for Practitioners

Meet the DEA's new requirement under the Medication Access and Training Expansion (MATE) Act in an online and self-paced 8-hour DEA MATE Act course specifically designed for practitioners, including Physicians, PAs, NPs, Pharmacists, Dentists and others.

LATEST & POPULAR

BLOG

Join Us at Thrive24: The Ultimate HealthStream Credentialing User Group Conference!
BLOG

Gen Z Enters the Workforce: How Healthcare Can Adapt Training Programs for the Next Generation
BLOG

Telehealth: From Pandemic Tool to Preferred Option
On-Demand Webinar

State of the Industry: What’s Next for Healthcare Quality & Safety in 2024?
CUSTOMER STORY

Quantifiable results highlight switch to jane®
ARTICLE

10 Trends for 2024: Absorbing New Technology, Facing New Realities, and Solving Old Problems

< HealthStream Resources

SafeStaffing BlogImage (1)

Safe Staffing in Healthcare – Acuity vs. Ratios

April 3, 2023
April 3, 2023

There has likely never been a time when managing nursing and other allied health staff resources has been more important – or more challenging. Value-based and risk-based reimbursement models have helped to focus even more attention on measures such as quality outcomes and readmissions and, in turn, those staffing models that will yield the best results.

Healthcare leaders are faced with more than one choice when deciding on the best staffing model. They may choose to make decisions based on:

  • Budget: In a budget-based staffing model, nursing schedules are traditionally allocated based on nursing hours per patient day.
  • Nurse-patient ratios: In this model, staffing levels are determined by the number of nurses versus patients. This includes models that are based on state mandates.
  • Patient acuity: This model uses the clinical needs of patients, the skill sets of nurses, and other objective clinical data to determine the staffing requirements for each shift.


Safe staffing considerations must also include the ongoing shortage of nurses and other providers, further complicating decision-making. So which model is the safest and most effective for patients and the nurses and other allied health staff caring for them?

Safe Staffing Considerations

While a budget-based staffing model provides a clear overview of what is needed for each unit, it can fail to account for any special or unique circumstances, including anything from individual patient needs up to a pandemic. For example, nurse-patient ratios are mandated by some states and under consideration by others, but also fail to account for patient acuity, the unique needs of individual departments, and staff skill sets.

In a recent blog, Mary Ann Fuchs, DNP, RN, NEA-BC, FAAN, President of the American Organization for Nursing Leadership, pointed out that nurses and not legislators are in a better position to make decisions on appropriate nurse staffing. She went on to say, “Ratios are a static and ineffective tool that cannot guarantee a safe health care environment. Care is team-based and a lack of flexibility to provide staffing based on the acuity of individual patient needs jeopardized safe patient care.”

An acuity-based model is the best option as it is:

  • Patient-centered: this is the only model that enables leaders to allocate resources based on actual patient needs rather than the number of patients.
  • Flexible: This model allows the assignment of the most critically ill patients to experienced nurses without creating an unfair burden on those nurses. Also, because it is based on current patient and staffing data, leaders have the ability to create staffing assignments based on current patient needs and staff skill sets.
  • Equitable: It allows managers to create a staffing plan based on skill sets, credentials, and regulatory requirements and can easily and objectively identify when individual team members are overburdened and allows nurse leaders to reallocate resources as necessary.
  • Cost-effective: It is more likely to work well with value-based reimbursement systems, which is critical as the continuity of care and containment of staffing costs are critical factors in the current healthcare business environment.


The acuity-based model is the right model for patients and staff, but without the right tools, it can be challenging to execute as it requires that leaders be able to leverage a continuous feed of data that includes patient’s clinical data from the Electronic Medical Record (EMR), admissions, discharges and transfers (ADT) information, and staffing levels along with staff qualifications, experience levels and certifications. It is a significant amount of data, and turning that data into something that is meaningful and actionable for leaders, optimal for patients and fair and equitable for staff is a rather daunting task. Therefore, a technology solution is essential for organizations wishing to implement an acuity-based staffing model.

Acuity-Based Staffing Solution

HealthStream’s Acuity and Assignment Manager helps leaders take the guesswork out of acuity-based staffing by aggregating the required data so that leaders can equitably balance staff workload while meeting the ever-fluctuating needs of the patient population. Further, this makes it possible to make smart decisions about staffing to acuity in real-time. It eliminates labor-intensive and potentially error-prone manual calculations and uses up-to-date staffing and patient data to create safe, equitable staffing assignments.