Utility of routine data sources for feedback on the quality of cancer care: An assessment based on clinical practice guidelines
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This article is published under the Open Access publishing model and distributed under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/2.0/. Please refer to the licence to obtain terms for any further reuse or distribution of this work.
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Background: Not all cancer patients receive state-of-the-art care and providing regular feedbackto clinicians might reduce this problem. The purpose of this study was to assess the utility of variousdata 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 ofinterest to clinicians. These were assigned to one of four data categories according to theiravailability and the marginal cost of using them for feedback.Results: Only 8 (3%) of 243 processes-of-care could be measured using population-based registryor administrative inpatient data (lowest cost). A further 119 (49%) could be measured using a coreclinical registry, which contains information on important prognostic factors (e.g., clinical stage,physiological reserve, hormone-receptor status). Another 88 (36%) required an expanded clinicalregistry or medical record review; mainly because they concerned long-term management ofdisease 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 inpatientdata are wide coverage and low cost. The disadvantage is that they currently contain informationon only a few processes-of-care. In most jurisdictions, clinical cancer registries, which can be usedto report on many more processes-of-care, do not cover smaller hospitals. If we are to providefeedback about all patients, not just those in larger academic hospitals with the most developeddata systems, then we need to develop sustainable population-based data systems that captureinformation on prognostic factors at the time of initial diagnosis and information on management of disease progression.
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