Background: With the increasing burden of chronic diseases, analyzing and understanding trajectories of care is
essential for efficient planning and fair allocation of resources. We propose an approach based on mining claim data
to support the exploration of trajectories of care.
Methods: A clustering of trajectories of care for breast cancer was performed with Formal Concept Analysis. We
exported Data from the French national casemix system, covering all inpatient admissions in the country. Patients
admitted for breast cancer surgery in 2009 were selected and their trajectory of care was recomposed with all
hospitalizations occuring within one year after surgery. The main diagnoses of hospitalizations were used to produce
morbidity profiles. Cumulative hospital costs were computed for each profile.
Results: 57,552 patients were automatically grouped into 19 classes. The resulting profiles were clinically meaningful
and economically relevant. The mean cost per trajectory was 9,600e. Severe conditions were generally associated
with higher costs. The lowest costs (6,957e) were observed for patients with in situ carcinoma of the breast, the
highest for patients hospitalized for palliative care (26,139e).
Conclusions: Formal Concept Analysis can be applied on claim data to produce an automatic classification of care
trajectories. This flexible approach takes advantages of routinely collected data and can be used to setup
Health-care systems face a crisis of an increasing burden of chronic diseases aggravated by aging populations . It
is of much importance that policy makers and healthcare managers can make decisions based on sufficient knowledge and understanding of chronic care activities. This is especially true in the field of cancer where incidence, therapeutics, practices and costs can vary quickly [2,3]. On the one hand, policy-makers need cost-effectiveness
and cost-of-illness analyzes for planning and fair allocation of funding. On the other hand, care providers
should be able to adapt their resources and costs while they share patients in multidisciplinary and coordinated approaches. Costs can be estimated from a variety of data sources, including insurance claims, billing systems, hospital discharge databases and surveys . However, data sourcesmay vary in a number of important aspects: accessibility, representativeness, level of aggregation, period of observation, availability and accuracy of clinical data. Besides, discrepancies can be observed depending on the source used to identify cases or estimate medical expenditures .
Year : 2013
Publisher : BMC Medical Informatics and DecisionMaking
By : Nicolas Jay , Gilles Nuemi , Maryse Gadreau , Catherine Quantin
File Information : English Language /9 Page / Size : 343 KB
Download : click
سال : 2013
ناشر : BMC Medical Informatics and DecisionMaking
کاری از : Nicolas Jay , Gilles Nuemi , Maryse Gadreau , Catherine Quantin
اطلاعات فایل : زبان انگلیسی / 9 صفحه /حجم : 343 KB
لینک دانلود : روی همین لینک کلیک کنید
نقد و بررسیها
هیچ دیدگاهی برای این محصول نوشته نشده است.