Evidence map›Paper›PMID 38170936›Full record

ArticleBiomedical instrumentation & technology2023

Validation of the Device Feature Approach for Reusable Medical Device Cleaning Evaluations.

Terra A Kremer, Jeff Felgar, Neil Rowen, Gerald McDonnell

Abstract read
In one paragraph

Article in Biomedical instrumentation & technology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
  2. Processing Reusable Medical Devices and End-of-Life Investigation.Biomedical instrumentation & technology · 2025
    Article
  3. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Terra A Kremer
Jeff Felgar
Neil Rowen
Gerald McDonnell

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The identification of worst-case device (or device set) features has been a well-established validation approach in many areas (e.g., terminal sterilization) for determining process effectiveness and requirements, including for reusable medical devices. A device feature approach for cleaning validations has many advantages, representing a more conservative approach compared with the alternative compendial method of testing the entirety of the device. By focusing on the device feature(s), the most challenging validation variables can be isolated to and studied at the most difficult-to-clean feature(s). The device feature approach can be used to develop a design feature database that can be used to design and validate device cleanliness. It can also be used to commensurately develop a quantitative cleaning classification system that will augment and innovate the effectiveness of the Spaulding classification for microbial risk reduction. The current study investigated this validation approach to verify the efficacy of device cleaning procedures and mitigate patient risk. This feature categorization approach will help to close the existing patient safety gap at the important interface between device manufacturers and healthcare facilities for the effective and reliable processing of reusable medical devices. A total of 56,000 flushes of the device features were conducted, highlighting the rigor associated with the validation. Generating information from design features as a critical control point for cleaning and microbiological quality will inform future digital transformation of the medical device industry and healthcare delivery, including automation.

Indexed as

Equipment ReuseSterilizationAutomationHealth FacilitiesHumansPatient Safety

Identifiers

PMID38170936
PMCPMC10764062

What OpenQuestion holds

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Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.