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      The Ecological Fallacy of the Role of Age in Chronic Disease and Hospital Demand

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          To examine the relationship between age and all-cause hospital utilization in the years preceding and following a diagnosis in hospital of heart failure, type 2 diabetes, or chronic obstructive pulmonary disease (COPD).

          Research Design:

          A cohort study of all patients in Western Australia who have had a principal diagnosis of heart failure, type 2 diabetes, or COPD, upon admission to hospital. All-cause hospital utilization 6 years preceding and 4 years following cardinal events, that is, a disease-specific diagnosis upon hospital admission, where such an event has not occurred in the previous 2 years, are examined in specific age groups.


          Six years preceding a cardinal event, all-cause emergency department (ED) presentations are similar in all age groups, from under 55 to over 85 years of age, except in COPD where ED presentation rates are higher in younger groups. All-cause hospital inpatient days are transiently higher in the years preceding and following a cardinal event in older age groups, yet return to similar levels across all age cohorts after 4 years. ED presentations are significantly higher in the 4 years following cardinal events in younger compared with older groups.


          Longitudinal analysis of utilization around cardinal events overcomes the confounding effect of differences in chronic disease rates between age groups, avoiding a source of ecologic bias that erroneously attributes increasing utilization in individuals with chronic disease to age. Programs designed to reduce hospital demand in patients with chronic disease should possibly focus on younger, rather than older, individuals.

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          Most cited references 16

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          Older patients in the emergency department: a review.

          Older patients account for up to a quarter of all emergency department (ED) visits. Atypical clinical presentation of illness, a high prevalence of cognitive disorders, and the presence of multiple comorbidities complicate their evaluation and management. Increased frailty, delayed diagnosis, and greater illness severity contribute to a higher risk of adverse outcomes. This article will review the most common conditions encountered in older patients, including delirium, dementia, falls, and polypharmacy, and suggest simple and efficient strategies for their evaluation and management. It will discuss age-related changes in the signs and symptoms of acute coronary events, abdominal pain, and infection, examine the yield of different diagnostic approaches in this population, and list the underlying medical problems present in half of all "social" admission cases. Complete geriatric assessments are time consuming and beyond the scope of most EDs. We propose a strategy based on the targeting of high-risk patients and provide examples of simple and efficient tools that are appropriate for ED use. Copyright (c) 2010 American College of Emergency Physicians. Published by Mosby, Inc. All rights reserved.
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            Ecologic studies in epidemiology: concepts, principles, and methods.

            An ecologic study focuses on the comparison of groups, rather than individuals; thus, individual-level data are missing on the joint distribution of variables within groups. Variables in an ecologic analysis may be aggregate measures, environmental measures, or global measures. The purpose of an ecologic analysis may be to make biologic inferences about effects on individual risks or to make ecologic inferences about effects on group rates. Ecologic study designs may be classified on two dimensions: (a) whether the primary group is measured (exploratory vs analytic study); and (b) whether subjects are grouped by place (multiple-group study), by time (time-trend study), or by place and time (mixed study). Despite several practical advantages of ecologic studies, there are many methodologic problems that severely limit causal inference, including ecologic and cross-level bias, problems of confounder control, within-group misclassification, lack of adequate data, temporal ambiguity, collinearity, and migration across groups.
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              Population-based linkage of health records in Western Australia: development of a health services research linked database.

              To introduce the Western Australian Health Services Research Linked Database as infrastructure to support aetiologic, utilisation and outcomes research. To compare the study population, data resources, technical systems and organisational supports with international best practice in record linkage and health research. The WA Linked Database systematically links the available administrative health data within an Australian State of 1.7 million people. It brings together, initially, six core data elements (birth records, midwives' notifications, cancer registrations, in-patient hospital morbidity, in-patient and public out-patient mental health services data and death records). It will be updated regularly and is designed, in future extensions, to include data on primary, residential and domiciliary care and health surveys. Linkage uses probabilistic matching of patient names and other identifiers. Geocodes for spatial analysis are assigned using address linkage and mapping software. By June 1997, the project had taken 2 1/2 years to develop the system and link seven million core data records from 1980 to 1995. The system is consistent with international benchmarks, from four centres of excellence, for the study population, core datasets, matching and geocoding, and collaborative networks. There are prospects to redress deficiencies in primary medical contact and other data resources, validation studies, tracing systems and a more supportive legal framework. The WA Linked Database will be used in combination with medical record audits to provide a comprehensive evaluation of health system performance.

                Author and article information

                Med Care
                Med Care
                Medical Care
                Lippincott Williams & Wilkins
                October 2014
                15 September 2014
                : 52
                : 10
                : 891-900
                [* ]School of Primary, Aboriginal, and Rural Health Care, Faculty of Medicine, Dentistry and Health Sciences
                []School of Mathematics and Statistics, Faculty of Engineering, Computing and Mathematics
                []School of Population Health, Faculty of Medicine, Dentistry and Health Sciences, The University of Western Australia, Crawley, WA
                [§ ]Illawarra Health and Medical Research Institute, University of Wollongong, Haymarket, NSW, Australia
                Author notes
                Reprints: David Whyatt, PhD, School of Primary, Aboriginal and Rural Health Care, Faculty of Medicine, Dentistry and Health Sciences, The University of Western Australia, M706, 35 Stirling Highway, Crawley, WA 6009, Australia. E-mail: david.whyatt@ .
                Copyright © 2014 by Lippincott Williams & Wilkins

                This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivitives 3.0 License, where it is permissible to download and share the work provided it is properly cited. The work cannot be changed in any way or used commercially.

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