Understanding Preprocedure Patient Flow in IR

Abdul Mueed Zafar, Rajeev Suri, Tran Khanh Nguyen, Carson Cope Petrash, Zanira Fazal

Research output: Contribution to journalArticlepeer-review

6 Scopus citations


Purpose To quantify preprocedural patient flow in interventional radiology (IR) and to identify potential contributors to preprocedural delays. Materials and Methods An administrative dataset was used to compute time intervals required for various preprocedural patient-flow processes. These time intervals were compared across on-time/delayed cases and inpatient/outpatient cases by Mann–Whitney U test. Spearman ρ was used to assess any correlation of the rank of a procedure on a given day and the procedure duration to the preprocedure time. A linear-regression model of preprocedure time was used to further explore potential contributing factors. Any identified reason(s) for delay were collated. P <.05 was considered statistically significant. Results Of the total 1,091 cases, 65.8% (n = 718) were delayed. Significantly more outpatient cases started late compared with inpatient cases (81.4% vs 45.0%; P <.001, χ2 test). The multivariate linear regression model showed outpatient status, length of delay in arrival, and longer procedure times to be significantly associated with longer preprocedure times. Late arrival of patients (65.9%), unavailability of physicians (18.4%), and unavailability of procedure room (13.0%) were the three most frequently identified reasons for delay. The delay was multifactorial in 29.6% of cases (n = 213). Conclusions Objective measurement of preprocedural IR patient flow demonstrated considerable waste and highlighted high-yield areas of possible improvement. A data-driven approach may aid efficient delivery of IR care.

Original languageEnglish (US)
Pages (from-to)1189-1194
Number of pages6
JournalJournal of Vascular and Interventional Radiology
Issue number8
StatePublished - Aug 1 2016

ASJC Scopus subject areas

  • Cardiology and Cardiovascular Medicine
  • Radiology Nuclear Medicine and imaging


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