Utility of routine data sources for feedback on the quality of cancer care: an assessment based on clinical practice guidelines View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2009-12

AUTHORS

Michael Coory, Bridie Thompson, Peter Baade, Lin Fritschi

ABSTRACT

BACKGROUND: Not all cancer patients receive state-of-the-art care and providing regular feedback to clinicians might reduce this problem. The purpose of this study was to assess the utility of various data sources in providing feedback on the quality of cancer care. METHODS: Published clinical practice guidelines were used to obtain a list of processes-of-care of interest to clinicians. These were assigned to one of four data categories according to their availability and the marginal cost of using them for feedback. RESULTS: Only 8 (3%) of 243 processes-of-care could be measured using population-based registry or administrative inpatient data (lowest cost). A further 119 (49%) could be measured using a core clinical registry, which contains information on important prognostic factors (e.g., clinical stage, physiological reserve, hormone-receptor status). Another 88 (36%) required an expanded clinical registry or medical record review; mainly because they concerned long-term management of disease progression (recurrences and metastases) and 28 (11.5%) required patient interview or audio-taping of consultations because they involved information sharing between clinician and patient. CONCLUSION: The advantages of population-based cancer registries and administrative inpatient data are wide coverage and low cost. The disadvantage is that they currently contain information on only a few processes-of-care. In most jurisdictions, clinical cancer registries, which can be used to report on many more processes-of-care, do not cover smaller hospitals. If we are to provide feedback about all patients, not just those in larger academic hospitals with the most developed data systems, then we need to develop sustainable population-based data systems that capture information on prognostic factors at the time of initial diagnosis and information on management of disease progression. More... »

PAGES

84

Identifiers

URI

http://scigraph.springernature.com/pub.10.1186/1472-6963-9-84

DOI

http://dx.doi.org/10.1186/1472-6963-9-84

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1015037853

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/19473504


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