Strategies for care quality improvement in Cystic Fibrosis

Rault, G.

doi:10.1186/s13023-017-0743-9

Cited by 1 publication

(2 citation statements)

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“…Yet only 6/28 (21.4%) of all UK adult CF centres have ≥273 adults [18] . CF QI initiatives focusing on process measures that allow rapid feedback to prompt improvement and subsequent reassessment have been reported, [8] but to date real time adherence data have not been exploited for this purpose. We hope that this study will lay the groundwork for such studies in the future.…”

Section: Discussionmentioning

confidence: 99%

“…Various quality improvement (QI) initiatives have transformed the delivery of CF healthcare [8] . The expertise of CF community in QI can potentially be harnessed to support adherence by creating a learning health system [9] in which objectively measured adherence using data-logging nebulisers such as I-neb® and eTrack® informs benchmarking and shared learning [10] .…”

Section: Introductionmentioning

confidence: 99%

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Exploring the implications of different approaches to estimate centre-level adherence using objective adherence data in an adult cystic fibrosis centre – a retrospective observational study

Hoo

Curley

Walters

et al. 2020

Journal of Cystic Fibrosis

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Background: Accurate centre-level medication adherence measurement allows identification of highly performing CF centres, drives shared learning and informs quality improvement. Self-reported adherence is unreliable but data-logging nebulisers can capture objective data. However, adherence levels in current literature are limited by the use of agreed prescriptions and convenience sampling. In this single-centre retrospective study, we quantified the differences in centre-level adherence with different methods of calculating adherence (unadjusted vs normative adherence) and different data sampling frames (convenience sampling vs including difficult to obtain data). Methods: Adherence data were objectively captured using I-neb® from 2013-2016 in Sheffield Adult CF Centre. Adults on non data-logging devices, on ivacaftor or with previous lung transplantation were excluded. Adherence was calculated based on agreed regimen ('unadjusted adherence') or minimum required regimen ('normative adherence'). I-nebs® not brought to clinic were downloaded during home visits. Adults not on any inhaled therapy but with chronic Pseudomonas aeruginosa infection were included by counting their adherence as "0". Results: Of the 131 included adults, 126 provided I-neb® data. Calculating unadjusted adherence from I-nebs® brought to clinics resulted in the highest centre-level adherence (median 41.8% in 2013). Median adherence reduced after sequentially accounting for minimum required regimen (40.0% in 2013), I-nebs® not brought to clinics (32.9% in 2013) and adults not on any inhaled therapy (31.0% in 2013). Conclusions: Different approaches of calculating adherence produced different adherence levels. Adherence levels based only on agreed regimen among adults who readily brought their nebulisers to clinics can overestimate the effective adherence of CF centres.

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Section: Discussionmentioning

confidence: 99%