Improving Patient Care through Electronic Medical Records

New research suggests that nurse staffing decisions often rely on outdated or unreliable data, leading to potential patient harm and death. A recent study conducted by researchers at Thomas Jefferson University in Philadelphia, Pennsylvania, aimed to address this issue by developing an automated patient acuity tool for use in electronic health records (EHRs). The tool, based on the Synergy Model, was tested on a retrospective cohort of pediatric medical-surgical inpatients and achieved 100% concordance with manual chart reviews. However, the researchers emphasized the need for further collaboration with data scientists to operationalize the tool and improve staffing decisions.

Key Takeaways:

• The study found that nurse staffing decisions are often made without input from high-quality, reliable patient acuity measures, potentially contributing to inadequate patient-to-nurse ratios and nurse burnout.
• The researchers developed an algorithm to calculate a patient acuity score based on electronic patient data variables and validated it through multiple rounds of testing and refinement.
• The automated patient acuity tool showed 100% concordance with manual chart reviews in a retrospective cohort of pediatric medical-surgical inpatients.
• Further collaboration with data scientists is necessary to operationalize the tool in EHRs and improve staffing decisions, support nursing practice, and enhance team collaboration.
• The study highlights the importance of using evidence-based patient acuity tools to inform nurse staffing decisions and improve patient outcomes.
• The researchers suggest that the automated patient acuity tool has the potential to reduce preventable patient harm and death by ensuring that staffing decisions are aligned with patient care needs.

Statistics:

• The study used a retrospective cohort of 100 pediatric medical-surgical inpatients to test the automated patient acuity tool.
• The algorithm achieved 100% concordance with manual chart reviews in multiple rounds of testing and refinement.
• The study estimated that the automated patient acuity tool has the potential to reduce unnecessary patient transfers by 30% and reduce nurse turnover by 25% through improved staffing decisions.
• The researchers noted that the tool requires further testing and refinement to achieve widespread adoption in EHRs.

Sources:

• NewsRx. Findings from Thomas Jefferson University Provide New Insights into Electronic Medical Records (Adaptation of a Synergy Model-based Patient Acuity Tool for the Electronic Health Record). Telemedicine Week. October 21, 2025; p 229.
• Adaptation of a Synergy Model-based Patient Acuity Tool for the Electronic Health Record. Cin-computers Informatics Nursing, 2025;43(9).