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  • American Society of Clinical Oncology (ASCO)  (2)
  • Matulonis, Ursula A.  (2)
Medientyp
Verlag/Herausgeber
  • American Society of Clinical Oncology (ASCO)  (2)
Sprache
Erscheinungszeitraum
Fachgebiete(RVK)
  • 1
    In: Journal of Clinical Oncology, American Society of Clinical Oncology (ASCO), Vol. 36, No. 30_suppl ( 2018-10-20), p. 129-129
    Kurzfassung: 129 Background: Many factors contribute to long wait times for cancer patients on the day of their infusion. At Dana-Farber Cancer Institute (DFCI), a contributing factor is patient flow between exam and infusion. Order verification affects patient flow and begins when the following two criteria are met: provider signed an order and the patient’s scheduled infusion appointment arrives. Patients often check-in to infusion before their scheduled infusion appointment. Order verification has three sequential steps: nurse verification, pharmacist 1 verify (V1), and pharmacist 2 verify (V2). Methods: A team of pharmacists, nurses, providers, and process improvement leads designed a pilot in which V1 moved before nurse verification, concurrent with patient check-in to infusion. Further, V1 began as soon as an order was signed; the pharmacist did not wait for a patient’s scheduled infusion appointment. Nurse verification and V2 occurred in sequence after V1. Timestamp data were extracted from Epic and analyzed via Tableau to assess reduction in verification throughput, defined as time between infusion check-in and V2. Fourteen providers and one pharmacist joined a 6-week pilot to adopt the redesigned workflow beginning 4/23/18. Results: At baseline, time between check-in and V2 was consistent for pilot and non-pilot orders. During the pilot, time between check-in and V2 was shorter for pilot orders, showing a sustained decrease of approximately 10 minutes. The table below provides time in minutes between infusion check-in and V2 for pilot and non-pilot orders at baseline (3/12/18-4/20/18) and following workflow redesign (4/23/18-6/1/18). Conclusions: Implementing the pilot workflow reduced order verification throughput time and enabled drug preparation to begin sooner. Expanding this workflow to all medication orders can decrease infusion wait time at DFCI.[Table: see text]
    Materialart: Online-Ressource
    ISSN: 0732-183X , 1527-7755
    RVK:
    RVK:
    Sprache: Englisch
    Verlag: American Society of Clinical Oncology (ASCO)
    Publikationsdatum: 2018
    ZDB Id: 2005181-5
    Bibliothek Standort Signatur Band/Heft/Jahr Verfügbarkeit
    BibTip Andere fanden auch interessant ...
  • 2
    In: Journal of Clinical Oncology, American Society of Clinical Oncology (ASCO), Vol. 36, No. 30_suppl ( 2018-10-20), p. 123-123
    Kurzfassung: 123 Background: Many factors contribute to long wait times for oncology patients on the day of their infusion appointment. At Dana-Farber Cancer Institute (DFCI), one of the main causes of delay to infusion start is providers not signing medication orders in advance of patients checking in for their infusion appointment. We conducted a project to improve provider order signing behavior on the gynecology cancer patient infusion floor at DFCI. Methods: A data working group was formed which consisted of the infusion floor medical leads, nurse lead, pharmacy lead, and analytics and process improvement leads. Starting in February 2018, the working group shared baseline order signing data from September 2017 through January 2018 with the Gynecology Cancer Group. Descriptive and timestamp data from Epic were extracted and cleaned via Tableau to analyze the percentage of non-investigational medication orders, including chemotherapy, that were signed after a patient checked into infusion and the distributions of late order signing times. Results: Gynecology cancer patient providers had higher late order signing percentages at baseline (September 2017 through January 2018) than after sharing those data, which occurred from February through May 2018. The table below provides medication order counts and late order signing percentages by month. Although late signing percentages decreased after sharing the baseline data, the distribution of how late the late orders were signed did not show improvement, staying at an average of 20 minutes late. Conclusions: Sharing late order signing data with providers on a routine basis reduced late signing percentages. Initiating this process with all disease groups is crucial so that downstream workflows can start sooner and patient wait times reduced.[Table: see text]
    Materialart: Online-Ressource
    ISSN: 0732-183X , 1527-7755
    RVK:
    RVK:
    Sprache: Englisch
    Verlag: American Society of Clinical Oncology (ASCO)
    Publikationsdatum: 2018
    ZDB Id: 2005181-5
    Bibliothek Standort Signatur Band/Heft/Jahr Verfügbarkeit
    BibTip Andere fanden auch interessant ...
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