June 2023
Volume 64, Issue 8
Open Access
ARVO Annual Meeting Abstract  |   June 2023
Determinants of Patient Follow-up Compliance in Ophthalmology Clinic in an Academic Center
Author Affiliations & Notes
  • sara Wetzstein
    Ophthalmology, University of Florida College of Medicine, Jacksonville, Florida, United States
  • Sandeep Grover
    Ophthalmology, University of Florida College of Medicine, Jacksonville, Florida, United States
  • Footnotes
    Commercial Relationships   sara Wetzstein None; Sandeep Grover Takeda Pharmaceuticals, Code C (Consultant/Contractor), DRCR Retina Network, Code F (Financial Support), Foundation Fighting Blindness, Code S (non-remunerative)
  • Footnotes
    Support  None
Investigative Ophthalmology & Visual Science June 2023, Vol.64, 3062. doi:
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      sara Wetzstein, Sandeep Grover; Determinants of Patient Follow-up Compliance in Ophthalmology Clinic in an Academic Center. Invest. Ophthalmol. Vis. Sci. 2023;64(8):3062.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

Purpose : Patients’ follow-up appointments is a critical component of quality of patient care. Clinics often experience difficulty with patients keeping their appointments. This study aims to analyze the characteristics of patients to predict the likelihood of appropriate follow-up.

Methods : This retrospective study identified all patients through an EMR chart review that were seen at the department of Ophthalmology at this academic center in the first 2 weeks of November 2021 and follow-up data were collected for up to 1 year. Patients were characterized as having ‘compromised care’ if they did not schedule a follow up appointment, did not show up for their scheduled appointment, cancelled their appointment and were never rescheduled, or were seen in clinic but outside of an acceptable time frame. Analyses were performed and a logit model was developed for the binary data (a patient either has compromised care or does not) which determined patient characteristics associated with compromised care. The variables included established vs. new patient, time to next appointment, insurance provider, and personal characteristics including age, gender, and ethnicity.

Results : Of 305 modeled patients, 38.7% of patients had ‘compromised care.' Patients who were older, established, had insurance or had follow-up appointment scheduled within 3 months were less likely to have their care compromised. In contrast, patients who were male or white were more likely to have compromised care. Table 1 shows the percentage difference in a patient’s likelihood to receive adequate care, based on each modeled characteristic.
Utilizing this model, it can be predicted that an uninsured, 43-year-old, white male, new patient who schedules a follow-up appointment for more than 3 months, will have an 85% likelihood of his care being compromised. Alternatively, a 73-year-old, nonwhite female who is an established patient with insurance, and whose appointment is scheduled within the next two weeks will have a 91% likelihood of getting uncompromised care.

Conclusions : Analysis of patient characteristics helped the clinic target specific types of patients to improve patient follow-up and their medical care. Practices have been adopted that have improved patient follow-up compliance rates. It also serves as an excellent economic model to cut down the no-show rates.

This abstract was presented at the 2023 ARVO Annual Meeting, held in New Orleans, LA, April 23-27, 2023.

 

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