Average and longest expected treatment times for ultraviolet light disinfection of rooms

Dexter, Franklin; Birchansky, Bradlee; Epstein, Richard H.; Loftus, Randy W.

doi:10.1016/j.ajic.2021.08.020

Cited by 5 publications

(13 citation statements)

References 35 publications

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“…The data used were the same as for our recent study on how to predict the times for disinfection of single rooms (e.g., one operating room in the middle of the workday) [2]. The studied ultraviolet light disinfection system (Helios®, Surfacide, Waukesha, WI) consisted of one or more towers that were connected by Bluetooth wireless technology to a tablet computer running the Android operating system (Google, Mountain View, CA).…”

Section: Data Used For the Simulationsmentioning

confidence: 99%

“…Details are provided in the Appendix. We used the 133,927 observed disinfection times as a population from which repeated samples were drawn with replacement [2].…”

Section: Data Used For the Simulationsmentioning

confidence: 99%

“…These measures include better-quality environmental cleaning achieved in part by the targeted use of germicidal ultraviolet light disinfection [1]. More work is needed to facilitate the adoption of this enhanced cleaning approach because disinfection times vary substantively among operating rooms and among cycles within rooms [2]. The decision as to how many ultraviolet light disinfection robot systems are needed for a facility's surgical suite(s) and/or procedure suite(s) depends in part on how many rooms need to be disinfected overnight by each robot and how long this will take.…”

Section: Introductionmentioning

confidence: 99%

“…The decision as to how many ultraviolet light disinfection robot systems are needed for a facility's surgical suite(s) and/or procedure suite(s) depends in part on how many rooms need to be disinfected overnight by each robot and how long this will take. The answer needs to be determined separately for each surgical suite and procedure suite because those variables vary both among facilities and among operating rooms or procedure rooms at facilities [2]. The answer is important because buying too many is wasteful and buying too few will not allow the necessary number of rooms to be disinfected nightly.…”

Section: Introductionmentioning

confidence: 99%

“…A one-night trial would be sufficient because the result would apply to all other nights. However, the reality is that the times to clean specified rooms are not constant, but rather are random variables, differing not only among rooms but substantially among disinfections for the same room (e.g., from the heterogeneity of equipment in the room) [2]. Thus, more than one day of observation is necessary.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Statistical Design of Overnight Trials for the Evaluation of the Number of Operating Rooms That Can Be Disinfected by an Ultraviolet Light Disinfection Robotic System

Birchansky

Dexter

Epstein

et al. 2021

Cureus

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Background and objectiveThe number of ultraviolet light disinfection robot systems that are needed for a facility's surgical suite(s) and/or procedure suite(s) depends in part on how many rooms need to be disinfected overnight by each robot and how long this will take. The answer needs to be determined separately for each surgical and procedure suite because those variables vary both among facilities and among operating rooms or procedure rooms within facilities. In this study, we consider statistical designs to assess how many rooms a facility can reliably (≥90% chance) disinfect overnight using an ultraviolet light disinfection robot system. MethodsWe used 133,927 observed disinfection times from 700 rooms as a population from which repeated samples were drawn with replacement in Monte-Carlo simulations. We used eight-hour and 10-hour shift lengths being multiples of 40 hours for full-time hourly employees. ResultsOne possible strategy that we examined was to estimate total disinfection times by estimating the mean for each room and then summing up the means. However, that did not correctly answer the question of how many rooms can reliably be available for the next day's first case. Summing up a percentile (e.g., 90%) instead also was inaccurate, because the proper percentile depended on the number of rooms.A suitable strategy is a brief trial (e.g., nine nights or 19 nights) with the endpoint being the daily number of rooms disinfected. Empirically, the smallest count of rooms disinfected among nine nights or the second smallest count among 19 nights are 10 th percentiles (i.e., ≈90% probability that at least that number of rooms can be disinfected in the future). The drawback is that while this approach gives the probability of a night with fewer rooms disinfected, it does not give information as to how many fewer rooms may either skip ultraviolet decontamination or start late the next workday because disinfection was not completed. Our simulations showed that there is a substantial probability (≥95%) of at most two rooms fewer or one room greater than the 10 th percentile with a nine-night trial and one room fewer or greater with a 19-night trial. ConclusionsBecause probability distributions of disinfection times are heterogeneous both among rooms and among treatments for the same room, each facility should plan to perform its own trial of nine nights or 19 nights. This will provide results that are within two rooms or one room of the correct answer in the long term. This information can be used when planning purchasing decisions, leasing, and technician staffing decisions.

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Section: Data Used For the Simulationsmentioning

confidence: 99%

“…Details are provided in the Appendix. We used the 133,927 observed disinfection times as a population from which repeated samples were drawn with replacement [2].…”

Section: Data Used For the Simulationsmentioning

confidence: 99%