Abstract Details

Title Predictors of No-show in Neurology clinics

Topic General Neurology

Presentation(s) P1 - Poster Session 1 (8:00 AM-9:00 AM)

Poster/Presentation
Number 6-032

Objective In this study, we aim to identify predictors of a no-show in neurology clinics at our institution. We conducted a retrospective review of neurology clinics from July 2013 through September 2018.

Background No-show in ambulatory neurology clinics does not only affect the efficiency and quality of workflow, but it also directly impacts the revenue and healthcare resources available to other patients. Moreover, clinic no show has significant implications on patients including delayed diagnosis and treatment, clinical worsening, and affects the management of medications that require close laboratory follow up such as anticonvulsant medications and immunotherapies.

Design/Methods We compared the odds ratio of patients who missed appointments (no-show) to those who were present at appointments (show) in terms of age, lead-time, subspecialty, race, gender, quarter of the year, insurance type, and distance from hospital.

Results There were 60,012 (84%) show and 11,166 (16%) no-show patients. With each day increase in lead time, odds of no-show increased by a factor of 1.0019 (p < 0.0001). Odds of no-show were higher in younger (p ≤ 0.0001, OR = 0.49) compared to older (age ≥ 60) patients and in women (p < 0.001, OR = 1.1352) compared to men. They were higher in Black/African American (p < 0.0001, OR = 1.4712) and lower in Asian (p = 0.03, OR = 0.6871) and American Indian/Alaskan Native (p = 0.055, OR = 0.6318) as compared to White/Caucasian. Patients with Medicare (p < 0.0001, OR = 1.5127) and Medicaid (p < 0.0001, OR = 1.3354) had higher odds of no-show compared to other insurance.

Conclusions Young age, female, Black/African American, long lead time to clinic appointments, Medicaid/Medicare insurance, and certain subspecialties (resident and stroke clinics) are associated with high odds of no show. Possible suggested interventions include better communication and flexible appointments for the high-risk groups as well as utilizing telemedicine.

Authors/Disclosures
Thirumalaivasan Dhasakeerthi, MBBS (UAMS) PRESENTER	Dr. Dhasakeerthi has nothing to disclose.
Hisham G. Elkhider, MD	Dr. Elkhider has nothing to disclose.
Rohan Sharma, MD	Dr. Sharma has nothing to disclose.
Abhilash Thatikala, MD, MBBS, DM (UAMS)	Dr. Thatikala has nothing to disclose.
Krishna Nalleballe, MD, FAAN	Dr. Nalleballe has nothing to disclose.
Sanjeeva R. Onteddu, MD, FAAN (UMass Medical School)	Dr. Onteddu has nothing to disclose.

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