Dataset Information


Latent composite indicators for evaluating adherence to guidelines in patients with a colorectal cancer diagnosis.

ABSTRACT: Evidence-based guidelines for the correct management of cancer patients are developed on the idea that timely care can improve health prognoses and quality of life.The aim of this paper is to evaluate the adherence of clinical pathways to clinical guidelines provided at the hospital level, for colorectal cancer care.By using a retrospective observational study, we proposed a method for associating each patient to a healthcare provider and modeling adherence as a latent construct governed by a set of 10 influential indicators. These indicators measure the adherence to specific guidelines for diagnosis, surgical treatment, chemotherapy, and follow-up. The model used was that of the item response theory (IRT). When evaluating providers, the IRT allows for a comparison of indicators in terms of their discriminating ability and difficulty, and in terms of their adherence to guidelines. The IRT results were compared with non-latent methods: numerator-based weight and denominator-based weight.A strong degree of coherence of the indicators in measuring adherence, and a high level of overall agreement between latent and non-latent methods were noted. The IRT approach demonstrated similar providers' evaluations between endoscopy and histological assessment indicators. The greatest discriminating ability among providers could be attributed to all diagnostic exams, while the lowest was associated with follow-up endoscopies. The most difficult indicator to achieve was fecal occult blood test, while follow-up imaging was the easiest.In a decision-making framework, valuable indications can be derived from the use of IRT models rather than weighting methods. Using IRTs, we were able to highlight the principal indicators in terms of strength of discrimination, and to isolate those that merely duplicated information.


PROVIDER: S-EPMC7034649 | BioStudies | 2020-01-01

REPOSITORIES: biostudies

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