Format

Send to

Choose Destination
AIDS Behav. 2019 Feb;23(2):418-426. doi: 10.1007/s10461-018-2215-1.

Who Will Show? Predicting Missed Visits Among Patients in Routine HIV Primary Care in the United States.

Author information

1
Department of Epidemiology, Gillings School of Global Public Health, The University of North Carolina at Chapel Hill, 2101 McGavran-Greenberg Hall, Chapel Hill, NC, 27599, USA. bpence@unc.edu.
2
Department of Epidemiology, Brown University, Providence, RI, USA.
3
Fenway Health, Boston, MA, USA.
4
Division of HIV, ID and Global Medicine, Zuckerberg San Francisco General Hospital, University of California San Francisco, San Francisco, CA, USA.
5
Department of Medicine, School of Medicine, University of Washington, Seattle, WA, USA.
6
Department of Medicine, School of Medicine, Johns Hopkins University, Baltimore, MD, USA.
7
Department of Medicine, School of Medicine, University of California, San Diego, San Diego, CA, USA.
8
Department of Medicine and UAB Center for AIDS Research, University of Alabama at Birmingham, Birmingham, AL, USA.

Abstract

Missed HIV medical visits predict poor clinical outcomes. We sought to identify patients at high risk of missing visits. We analyzed 2002-2014 data from six large US HIV clinics. At each visit, we predicted the likelihood of missing the next scheduled visit using demographic, clinical, and patient-reported psychosocial variables. Overall, 10,374 participants contributed 105,628 HIV visits. For 17% of visits, the next scheduled appointment was missed. The strongest predictor of a future missed visit was past-year missed visits. A model with only this predictor had area under the receiver operator curve = 0.65; defining "high risk" as those with any past-year missed visits had 73% sensitivity and 51% specificity in correctly identifying a future missed visit. Inclusion of other clinical and psychosocial predictors only slightly improved performance. Past visit attendance can identify those at increased risk for future missed visits, allowing for proactive allocation of resources to those at greatest risk.

KEYWORDS:

Appointment attendance; HIV; Missed visits; Predictive models; Retention in care

PMID:
30006790
PMCID:
PMC6330260
[Available on 2020-02-01]
DOI:
10.1007/s10461-018-2215-1
[Indexed for MEDLINE]

Supplemental Content

Full text links

Icon for Springer
Loading ...
Support Center