Discussion Post

I used chat ChatGPT to answer this question, can you rewrite it where Chat GPT is not detected

Question #1: What is the fall rate at XXX hospital?

1. What information does the team need to address the question? Where will they get it?

Information needed:

• Total number of patient falls on the telemetry unit
• Total number of patient-days during the defined time period
• Number of falls with injury
• Fall risk scores for patients (e.g., Morse Fall Scale or facility-specific tool)
• Identification of high-risk patients
• Documentation of modifiable risk factors (medications, mobility status, cognition, toileting needs)
• Staff compliance with the new fall prevention protocol

Where the team will obtain the information:

• Electronic Health Record (EHR)
• Hospital incident reporting system
• Quality improvement department reports
• Risk management database
• Nursing documentation audits
• Pharmacy records (for high-risk medications)

1. How will the team get the information needed to answer the question? (Methods/Tools)

• Conduct a retrospective chart review for baseline (pre-intervention) data
• Collect prospective data following implementation of the new protocol
• Request fall reports and patient-day data from the quality department
• Use EHR data extraction tools to identify fall risk scores and documentation compliance
• Perform audits of nursing documentation to assess adherence to the communication strategy and risk assessment protocol
• Calculate the fall rate using the formula:
• (Number of Falls Total Patient-Days) 1,000

1. What are the design/data collection limitations and how will they affect what the team obtains?

• Underreporting of falls: Incident reports may not capture all falls, leading to underestimated fall rates.
• Inconsistent documentation: Variability in charting practices may affect accuracy of risk assessments and protocol compliance data.
• Small sample size: Data from a single telemetry unit may limit generalizability.
• Confounding variables: Changes in staffing ratios, patient acuity, or census could influence fall rates independent of the intervention.
• Hawthorne effect: Staff awareness of monitoring may temporarily improve compliance and artificially lower fall rates.
• Short evaluation period: Limited post-intervention timeframe may not reflect long-term sustainability.

1. What are the expected results of the work?

• Reduction in overall fall rate (falls per 1,000 patient-days)
• Decrease in falls among high-risk patients
• Improved compliance with fall risk assessments and documentation
• Better identification and management of modifiable risk factors
• Reduction in fall-related injuries