AI-Generated Instructions for Patient Education

Overseen By Jonah Zaretsky

Age: 18+

Sex: Any

Trial Phase: Academic

Sponsor: NYU Langone Health

Disqualifiers: Inpatient hospice, home hospice

No Placebo Group All trial participants will receive the active study treatment (no placebo)

Compensation: Varies

Number of Visits: 1

61 Participants Needed

Trial Summary

Will I have to stop taking my current medications?

The trial information does not specify whether you need to stop taking your current medications.

What data supports the effectiveness of the treatment AI-Generated Discharge Instructions?

Research suggests that making discharge instructions easier to read can reduce patient phone calls and hospital readmissions, indicating that clear, personalized instructions may help patients manage their care better after leaving the hospital. ^{1 2 3 4 5}

Is the AI-Generated Discharge Instructions treatment generally safe for humans?

The research suggests that AI tools, like those used for discharge instructions, have the potential to improve patient safety by reducing adverse events (unwanted side effects or complications) in healthcare. However, specific safety data for AI-Generated Discharge Instructions is not directly available in the studies provided. ^{6 7 8 9 10}

How is the AI-Generated Discharge Instructions treatment different from other treatments?

AI-Generated Discharge Instructions are unique because they are tailored to the patient's reading level, making them easier to understand and follow compared to traditional discharge instructions, which are often too complex and lengthy. ^{3 5 11 12 13}

What is the purpose of this trial?

This will be an open-label, parallel-group, randomized trial. Patients will be randomized to review the patient-friendly discharge instructions at the time of discharge (intervention group) vs the standard of care. The intervention differs from the standard of care in that patients will be given additional medical documentation in the intervention group.

Research Team

Jonah Zaretsky

Principal Investigator

NYU Langone Health

Eligibility Criteria

This trial is for patients who are being discharged from the hospital and need discharge instructions. There aren't specific inclusion or exclusion criteria provided, so it's likely open to a broad range of patients.

Inclusion Criteria

Admitted to Inpatient Medicine unit at NYULH

Able to read and understand English

Willing and able to consent to this research

Exclusion Criteria

I am currently receiving hospice care at home.

I am currently in a hospice program as an inpatient.

Timeline

Screening

Participants are screened for eligibility to participate in the trial

1-2 weeks

Intervention

Patients receive either patient-friendly discharge instructions generated by GPT-4 or standard discharge instructions at the time of discharge

Day 1 (At Discharge)

1 visit (in-person)

Follow-up

Participants are monitored for the readability and understandability of discharge instructions

1 week

Treatment Details

Interventions

• AI-Generated Discharge Instructions

Trial Overview The study is testing if AI-generated discharge instructions help patients better than standard ones. Patients will be randomly placed into two groups: one gets the AI-generated info, while the other receives usual care.

Participant Groups

Group I: Generative AI Discharge Instructions Experimental Treatment 1 Intervention

At the time of discharge, patients will receive patient-friendly discharge instructions generated by GPT-4, an advanced natural language processing model, with the aim of enhancing patient readability and understandability in the discharge information.

Group II: Standard of Care Discharge Instructions Active Control 1 Intervention

At the time of discharge, patients will receive standard discharge instructions (i.e., not generated by GPT-4).

Who Is Running the Clinical Trial?

NYU Langone Health

Lead Sponsor

Trials

1,431

Recruited

838,000+

Findings from Research

In a study of 2,498 acute myocardial infarction patients, those who adhered very carefully to discharge instructions, particularly regarding medication, reported significantly less angina one year later compared to those with poor adherence, indicating that following discharge instructions can improve health outcomes.

Despite high adherence to medication instructions (94% reported very careful adherence), there was no clear link between overall risk factor management behaviors and quality of life, physical functioning, rehospitalization, or mortality, suggesting that while adherence is important, other factors may also influence these outcomes.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Risk factor management after myocardial infarction: reported adherence and outcomes. Decker, C., Ahmad, H., Moreng, KL., et al.[2009]

The SAFER Care framework, which includes standardized written and verbal discharge counseling, significantly improved caregiver comprehension of discharge instructions from 37% to 62% after implementation, based on surveys from 433 caregivers.

This study highlights the effectiveness of structured discharge counseling in a pediatric inpatient setting, suggesting that similar approaches could benefit other patient populations, especially those with limited English proficiency.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

SAFER Care: Improving Caregiver Comprehension of Discharge Instructions. Uong, A., Philips, K., Hametz, P., et al.[2022]

References

1. United States pubmed.ncbi.nlm.nih.gov

Improving the Quality of Inpatient Discharge Instructions: An Evaluation and Implementation of Best Practices. [2021]

2. Netherlands pubmed.ncbi.nlm.nih.gov

[Room for improvement of patient education delivered at time of hospital discharge]. [2023]

3. United States pubmed.ncbi.nlm.nih.gov

A quality improvement initiative for patient knowledge comprehension during the discharge procedure using a novel computer-generated patient-tailored discharge document in cardiology. [2022]

4. United States pubmed.ncbi.nlm.nih.gov

Risk factor management after myocardial infarction: reported adherence and outcomes. [2009]

5. United States pubmed.ncbi.nlm.nih.gov

Enhanced readability of discharge summaries decreases provider telephone calls and patient readmissions in the posthospital setting. [2019]

6. United States pubmed.ncbi.nlm.nih.gov

Patient readmissions, emergency visits, and adverse events after software-assisted discharge from hospital: cluster randomized trial. [2018]

7. United States pubmed.ncbi.nlm.nih.gov

SAFER Care: Improving Caregiver Comprehension of Discharge Instructions. [2022]

8. Canada pubmed.ncbi.nlm.nih.gov

Interactive Digital Health Tools to Engage Patients and Caregivers in Discharge Preparation: Implementation Study. [2020]

9. Netherlands pubmed.ncbi.nlm.nih.gov

The ADE scorecards: a tool for adverse drug event detection in electronic health records. [2013]

10. England pubmed.ncbi.nlm.nih.gov

The potential of artificial intelligence to improve patient safety: a scoping review. [2021]

11. United States pubmed.ncbi.nlm.nih.gov

Improving the Readability of Pediatric Hospital Medicine Discharge Instructions. [2020]

12. United States pubmed.ncbi.nlm.nih.gov

An Improvement Effort to Optimize Electronically Generated Hospital Discharge Instructions. [2020]

13. Netherlands pubmed.ncbi.nlm.nih.gov

Understanding and execution of discharge instructions. [2022]