Dataset Information

The profile inter-unit reliability.

ABSTRACT: To assess the quality of health care, patient outcomes associated with medical providers (eg, dialysis facilities) are routinely monitored in order to identify poor (or excellent) provider performance. Given the high stakes of such evaluations for payment as well as public reporting of quality, it is important to assess the reliability of quality measures. A commonly used metric is the inter-unit reliability (IUR), which is the proportion of variation in the measure that comes from inter-provider differences. Despite its wide use, however, the size of the IUR has little to do with the usefulness of the measure for profiling extreme outcomes. A large IUR can signal the need for further risk adjustment to account for differences between patients treated by different providers, while even measures with an IUR close to zero can be useful for identifying extreme providers. To address these limitations, we propose an alternative measure of reliability, which assesses more directly the value of a quality measure in identifying (or profiling) providers with extreme outcomes. The resulting metric reflects the extent to which the profiling status is consistent over repeated measurements. We use national dialysis data to examine this approach on various measures of dialysis facilities.

SUBMITTER: He K

PROVIDER: S-EPMC7318309 | biostudies-literature | 2020 Jun

REPOSITORIES: biostudies-literature

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The profile inter-unit reliability.

He Kevin K Dahlerus Claudia C Xia Lu L Li Yanming Y Kalbfleisch John D JD

Biometrics 20191110 2

To assess the quality of health care, patient outcomes associated with medical providers (eg, dialysis facilities) are routinely monitored in order to identify poor (or excellent) provider performance. Given the high stakes of such evaluations for payment as well as public reporting of quality, it is important to assess the reliability of quality measures. A commonly used metric is the inter-unit reliability (IUR), which is the proportion of variation in the measure that comes from inter-provide ...[more]

PMID: 31642521

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Project description:Purpose:Researchers have long noted speech recognition variability that is not explained by the pure-tone audiogram. Previous work (Souza, Wright, Blackburn, Tatman, & Gallun, 2015) demonstrated that a small number of listeners with sensorineural hearing loss utilized different types of acoustic cues to identify speechlike stimuli, specifically the extent to which the participant relied upon spectral (or temporal) information for identification. Consistent with recent calls for data rigor and reproducibility, the primary aims of this study were to replicate the pattern of cue use in a larger cohort and to verify stability of the cue profiles over time. Method:Cue-use profiles were measured for adults with sensorineural hearing loss using a syllable identification task consisting of synthetic speechlike stimuli in which spectral and temporal dimensions were manipulated along continua. For the first set, a static spectral shape varied from alveolar to palatal, and a temporal envelope rise time varied from affricate to fricative. For the second set, formant transitions varied from labial to alveolar and a temporal envelope rise time varied from approximant to stop. A discriminant feature analysis was used to determine to what degree spectral and temporal information contributed to stimulus identification. A subset of participants completed a 2nd visit using the same stimuli and procedures. Results:When spectral information was static, most participants were more influenced by spectral than by temporal information. When spectral information was dynamic, participants demonstrated a balanced distribution of cue-use patterns, with nearly equal numbers of individuals influenced by spectral or temporal cues. Individual cue profile was repeatable over a period of several months. Conclusion:In combination with previously published data, these results indicate that listeners with sensorineural hearing loss are influenced by different cues to identify speechlike sounds and that those patterns are stable over time.

Dataset Information

The profile inter-unit reliability.

Publications

The profile inter-unit reliability.

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