What's the Hold-Up?: Late Work Events in Radiation Oncology Reveal Opportunities for Improved Patient Care and Safety

2014 ◽  
Vol 90 (1) ◽  
pp. S743-S744
Author(s):  
T.D. Mullen ◽  
E. Ford ◽  
J. Zeng ◽  
M. Nyflot ◽  
L. Jordan ◽  
...  
2016 ◽  
Vol 34 (26_suppl) ◽  
pp. 83-83 ◽  
Author(s):  
Bansi Savla ◽  
Puja Venkat ◽  
Michael Yu

83 Background: ESAS has been used to examine quality of life and symptom burden of patients undergoing cancer treatment. The purpose of this study is to examine attitudes towards ESAS among patients in a Radiation Oncology clinic in conjunction with the perspective of cancer care professionals, to establish ideal implementation of this tool to improve patient care. Methods: Routine use of ESAS in a single Radiation Oncology Department was initiated in July 2015. Six months after implementation, an anonymous, electronic survey was administered to 50 healthcare providers within this department, including attending physicians, resident physicians, advanced practice nurses, physician assistants, and registered nurses. The survey collected information regarding the value of ESAS with regards to patient care, the numerical value at which an intervention is made, which clinical interventions had been implemented due to patient-reported scores on ESAS, which patient populations benefit from ESAS administration, and how frequently ESAS should be administered. Closed and open questions were included. Results: Out of 50 providers, 36 completed the survey. Of these, 31 reported finding ESAS useful. The most common intervention was questioning the patient further about symptoms (29/36.) ESAS data are being reviewed by clinical teams and stored as part of the patient’s medical record in order to compile longitudinal data. An anonymous paper survey is currently being administered to 50 patients at the end of their radiation treatment or at their first follow-up. The survey will collect information about how well symptoms are being communicated with the clinical team, if symptoms should be added to ESAS, how often ESAS should be administered, which specific clinical interventions were provided due to ESAS, and if ESAS improved the overall patient experience. Conclusions: Our survey from the clinical team supports that ESAS is a useful modality to assess patient symptoms and to improve management for patient symptoms effectively. Our ongoing patient survey will validate these findings. These two surveys will be used to improve systematic collection of symptom data for radiation oncology patients.


2019 ◽  
Vol 37 (27_suppl) ◽  
pp. 79-79
Author(s):  
Shalini Moningi ◽  
Shane Mesko ◽  
Amy Catherine Moreno ◽  
Matthew S. Ning ◽  
Thomas A. Aloia ◽  
...  

79 Background: Since 2010 The University of Texas MD Anderson Cancer Center (UTMDACC) has been using Time Driven Activity Based Costing (TDABC) to assist in tracking and quantifying changes made to clinical processes to improve efficiency of patient care delivery. Radiation Oncology (RO) providers have recently utilized this method to assist in the growing clinical patient volumes and increasing enrollment in clinical trials. UTMDACC contains disease specific multi-disciplinary centers with separate clinics for different disciplines. Resources are limited which can affect clinical providers’ ability to meet the needs of increasing patient volumes. Implementing efficient clinic work flow models will allow clinicians to provide excellent quality of clinical care even with limited resources. Methods: Standard disease-site specific note templates were created and implemented throughout the entire RO department. Additionally, standardized roles for medical assistants, residents, physician assistants (PAs), attending physicians and nurses were implemented to minimize duplication of responsibilities. Using TDABC methodology, process maps for pre and post implementation pathways were created to illustrate areas of change and possible benefit. Results: Process maps were compared for new consult and follow up and on treatment patient visits. Process times for these patient care visits were compared pre- and post-implementation of templates and clinical roles. Time savings of 110, 18 and 34 minutes were observed for consult visits, follow up visits and on-treatment visits when comparing current to baseline process maps. Conclusions: Standardization of note templates and roles for all members of the care team has led to improvements in process flow and efficiency in the RO clinic setting. Our findings suggest that further implementation of TDABC methodology by having all providers work at the top of their license could can improve clinical efficiency and patient care. Further metrics with a larger sample size is recommended to validate our results. [Table: see text]


2013 ◽  
Vol 18 ◽  
pp. S288
Author(s):  
E. Guimón Olaizola ◽  
M. Eguiguren Bastida ◽  
M. Esnaola Arrizabalaga ◽  
A. Querejeta Ayerra ◽  
I. Uranga Aizpurua ◽  
...  

2012 ◽  
Vol 103 ◽  
pp. S475
Author(s):  
E. Guimon ◽  
M. Eguiguren ◽  
M.J. Esnaola ◽  
J. Minguez ◽  
A. Querejeta ◽  
...  

2012 ◽  
Vol 22 (1) ◽  
pp. 77-85 ◽  
Author(s):  
Bhishamjit S. Chera ◽  
Marianne Jackson ◽  
Lukasz M. Mazur ◽  
Robert Adams ◽  
Sha Chang ◽  
...  

2014 ◽  
Vol 32 (30_suppl) ◽  
pp. 231-231
Author(s):  
Nicholas Carl Kukshtel ◽  
Robert Mersereau ◽  
Sarah Kadish ◽  
Spyros Potiris ◽  
Todd Vivenzio ◽  
...  

231 Background: The department of Radiation Oncology at the Dana-Farber/Brigham and Women’s Cancer Center operates seven linear accelerators treating approximately 200 patients per day. These machines are regularly shut-down for upgrades, requiring the redistribution of patients to available machines. Previous machine downtimes have caused disruptions to patient care and required extended operating hours to accommodate displaced patient volume. For the next machine downtime, we sought to create a model to optimize the reassignment of patients to available machines, maximizing treatment type-machine compatibility while minimizing overtime, costs, and patient care impact. Methods: This collaboration between Radiation Oncology and the Process Improvement team retooled the Assignment Problem Method, an Industrial Engineering technique used to assign tasks, in order to solve for case allocation to radiation machines. A spreadsheet model was developed to optimize the allocation of treatment cases for each machine, without violating working hours or treatment type-machine constraints. Input data included case duration, radiation technique, daily demand, and machine compatibility for each treatment type. In addition to finding an optimal case allocation, department administrators created “what-if” scenarios to identify how demand fluctuations would shift cases across machines. Proposed solutions were validated by comparing the model’s output to feasible treatment volumes identified by department administrators. Results: The model revealed that under idealized conditions, the current daily patient volume can be accommodated with two fewer machines and 1.5 fewer operating hours each day. The time it took department administrators to prepare for the next downtime was reduced from several weeks of manual planning, to a few days using the model. Conclusions: Simple industrial engineering tools can help solve complex problems. Developing optimization models can eliminate complex calculations, allowing end-users to refine and implement a suitable solution without fear of mathematical error. A robust model can provide end users the ability to assess the impact of future changes in capacity or demand.


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