Impact of comorbidity on colorectal cancer screening in the veterans healthcare system.
ABSTRACT The quality assessment measure of colorectal cancer screening in the veteran's health system reports the proportion of patients aged 52-80 years who were tested. This approach does little to assess for comorbid illnesses, which might limit the utility of screening. Our aim was to determine the relationship between patient comorbidity and screening by fecal occult blood test in a national sample of veterans.
We examined the Veterans Health Administration's national databases (October 2003-February 2005) for a random sample of primary care patients, aged > or = 50 years. The Charlson score, a validated measure of comorbidity burden, was calculated from diagnosis codes by the Deyo method. The association between Charlson score and colorectal cancer screening was assessed with logistic regression.
The sample of 77,268 was 97% men; mean age was 67 years. Charlson score distribution was 0, 45%; 1, 24%; 2, 14%; 3, 7%; 4, 4%; 5, 2%; 6, 1%; 7, 0.8%; 8, 0.6%; 9, 0.4%; > or = 10, 1%. Overall there was no consistent significant association between Charlson score and use of fecal occult blood testing except in the sickest 1%. There was a strong and incremental relationship between Charlson score and 1-year mortality.
Although there was a strong relationship in the veteran population between the Charlson score and survival, colorectal cancer screening utilization was not impacted by Charlson score. Instead, resources were expended evenly throughout the population, rather than directed toward screening the patients with the most life-years at stake. The quality measure for colorectal cancer screening should be modified to account for patient comorbidity.
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- "Indirect association Impact by type of comorbidity was not explored. Fisher, 2007 (22) Cancer (colorectal) Comorbidity measured with an adaptation of the Charlson comorbidity index. "
ABSTRACT: The simultaneous presence of multiple conditions in one patient (multi-morbidity) is a key challenge facing healthcare systems globally. It potentially threatens the coordination, continuity and safety of care. In this paper, we report the results of a scoping review examining the impact of multi-morbidity on the quality of healthcare. We used its results as a basis for a discussion of the challenges that research in this area is currently facing. In addition, we discuss its implications for health policy and clinical practice. The review identified 37 studies focussing on multi-morbidity but using conceptually different approaches. Studies focusing on 'comorbidity' (i.e. the 'index disease' approach) suggested that quality may be enhanced in the presence of synergistic conditions, and impaired by antagonistic or neutral conditions. Studies on 'multi-morbidity' (i.e. multiplicity of problems) and 'morbidity burden' (i.e. the total severity of conditions) suggested that increasing number of conditions and severity may be associated with better quality of healthcare when measured by process or intermediate outcome indicators, but with worse quality when patient-centred measures are used. However, issues related to the conceptualization and measurement of multi-morbidity (inconsistent across studies) and of healthcare quality (restricted to evaluations for each separate condition without incorporating considerations about multi-morbidity itself and its implications for management) compromised the generalizability of these observations. Until these issues are addressed and robust evidence becomes available, clinicians should apply minimally invasive and patient-centred medicine when delivering care for clinically complex patients. Health systems should focus on enhancing primary care centred coordination and continuity of care.The European journal of general practice 07/2015; · 0.81 Impact Factor
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ABSTRACT: The problem of detecting abrupt changes in a set of synthetic aperture radar (SAR) images is carried out by comparing the results of segmentation between images with different modalities acquired before and after a disaster. Individual segmentations are not considered by themselves since they yield surface map characterization while the goal is to detect a temporal evolution of soil characteristics. Hence, we propose to use the modification of class statistics in the images in order to characterize potential changes and to prevent from false alarms that may be induced by the specific modality of each SAR acquisition. The change detection process is divided in two steps; 1) segmentation of the observations in order to have an estimation of the marginal probability distribution function (pdf) of each class; 2) comparison of the pdf from different images to detect changes by means of evidential and paradoxical reasoning. This two-stages process has been applied on Radarsat images (F2 and F5) of the Nyiragongo volcano, DR Congo, erupted on January 2002. The results obtained outperform simple strategies based on image differencing/ratioingGeoscience and Remote Sensing Symposium, 2004. IGARSS '04. Proceedings. 2004 IEEE International; 10/2004