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Top 10 Challenges With Tracking Patient Acuity

How sick is my patient? That is the question that patient acuity tries to answer. Patient acuity is typically defined as “the measure of a patient’s severity of illness or medical conditions,” which includes medical stability and how much clinical care they require. Not only does patient acuity optimize patient care, but it also helps hospitals manage nursing resources and costs. 

 

There are numerous different indices or tools used to measure patient acuity. These tools, previously called patient classification systems (PCSs), have been around since the 1980s. At that time, they were mostly designed for medical-surgical patients in critical care units. Currently, patient acuity is useful in many other areas from the emergency department to long-term care. However, measuring patient acuity still isn’t standardized, and it’s often challenging for clinicians to adopt and trust these tools. 

 

Why is patient acuity still so hard to measure? Here are ten challenges with creating effective patient acuity: 

 

  1. Subjectivity and Variability: Determining patient acuity can be subjective, as different healthcare providers may have varying interpretations of patient conditions and needs. This subjectivity can lead to inconsistency in assigning acuity levels.
  2. Lack of Standardization: There is often a lack of standardized acuity measurement systems across healthcare facilities. This makes it difficult to compare patient acuity levels between hospitals and hinders effective resource allocation.
  3. Limited Resources: Hospitals often have limited resources, including staff, equipment, and beds. Allocating resources based on accurate patient acuity is crucial, but it can be challenging due to competing demands and resource constraints.
  4. Staffing Levels: Assigning appropriate staffing levels based on patient acuity is essential for maintaining patient safety and providing quality care. However, accurately matching staffing to acuity can be difficult, leading to either understaffing or overstaffing situations.
  5. Dynamic Nature of Acuity: Patient acuity levels can change rapidly based on clinical conditions. It can be challenging to continuously monitor and update acuity levels in real-time, leading to delays in resource allocation and care adjustments.
  6. Latency:  Accurate and timely documentation of patient acuity is vital for effective communication among healthcare providers. However, documentation practices can vary, leading to inconsistencies and difficulties in conveying patient acuity information accurately. In some cases, documenting patient assessments can have a delay as long as 8 hours, which impacts the accuracy of patients status/acuity.
  7. Training and Education: Healthcare professionals need proper training and education on assessing and documenting patient acuity. Inadequate training can lead to inconsistencies and inaccuracies in acuity assessment, affecting resource allocation and patient outcomes.
  8. Data Overload: Hospitals generate a vast amount of data, including patient information, vital signs, laboratory results, and more. Effectively integrating and analyzing this data to determine patient acuity levels can be challenging and time-consuming.
  9. Technological Limitations: Some hospitals may face technological limitations, such as outdated or incompatible systems, which hinder the efficient collection and analysis of patient data for acuity determination.
  10. Resistance to Change: Implementing new systems or processes for patient acuity determination can face resistance from healthcare providers who are accustomed to traditional methods. Overcoming this resistance and promoting a culture of change can be a significant challenge.

 

Being able to determine the criticality of each patient is invaluable to the operational success of a hospital. Hospitals do not have unlimited funds and resources, so they must utilize what they have efficiently without compromising on patient care. It’s evident that current patient acuity models have room for improvement. 

 

CalmWave’s Operations Health Platform captures and analyzes data to augment traditional methods of measuring patient acuity. As mentioned above, hospitals have a plethora of data, often in many different places, making it a challenge to truly paint a picture of how each patient is doing. CalmWave’s platform uses the power of AI to aggregate data from multiple sources (including electronic health records) and provide insight into medical incidents that patients have experienced. Demonstrating a compiled view of patient data allows clinicians to make more educated decisions about patient acuity and care needs. Additionally, matching staff to acuity is often challenging, especially in the critical care setting where many patients require around-the-clock care. Our platform also captures staff metrics (such as workload, shift times, etc.) to produce objective measures of clinical workload. This allows nurse managers to optimize staffing so critical patients receive the care that they need. 

 

CalmWave understands the importance of patient acuity, and our platform aggregates data and provides critical insights to maintain an optimal care environment. We know that latent patient information is not useful. That’s why CalmWave captures all of the aforementioned variables in real time, providing a lens into the real-time status of a patient’s acuity. Patient acuity is a complex but essential measure to ensure that the healthcare system functions optimally. CalmWave is here to help.

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