DOCUMENTS

reports

Clinical and economic features of categories of patients in defined populations

Published: January 1, 2005
Category: Bibliography > Reports
Authors: Carlsson L
Countries: Sweden
Language: null
Types: Care Management
Settings: Hospital

Stockholm, Sweden: Karolinska Institute (doctoral dissertation).

Department of Clinical Services, Center for Family and Community Medicine, Karolinska Institute, Stockholm, Sweden

This thesis addresses the use of information from health care registers on an individual level, making it possible to elucidate the morbidity and comorbidity patterns in defined populations, and to allocate resources in primary health care (PHC) on this basis.
Study I aimed at assessing the annual direct and indirect costs of skin diseases caused by ultraviolet radiation. This cost-of-illness analysis used data on individual patients in one county council. Direct health care costs for diagnosing, treatment and secondary prevention as well as indirect costs caused by morbidity and mortality were calculated. The total annual cost-of-illness for skin diseases caused by ultraviolet radiation exposure in Stockholm in 1999 was approximately 162.4 MSEK. The indirect costs were about 56% of total costs.
In Study II, patients utilizing PHC in one municipality in Sweden were categorized into 81 groups. Grouping was done by the Johns Hopkins Adjusted Clinical Groups® (ACG) system. Data from two years were used retrospectively and the results were compared with data from other PHC centres in Sweden. The ACG instrument seemed to be a relevant tool for describing the outcome of work done by the PHC centre.
Study III was a one-year retrospective study based on encounters at publicly managed PHC centres in one county council in Sweden. The objective was to elucidate types of morbidity and categories of patients in terms of the ACGs in a large population. Types of morbidity in PHC seemed to be dominated by nearly equal proportions of “Time limited”, “Likely to recur”, “Chronic” and “Signs/Symptoms”. About one third of the patients had a constellation of two or more types of morbidity during a one-year period.
Study IV was a three-year retrospective study based on encounter data from the same centres as in study III. The objective was to monitor the proportion of residents encountering PHC, and to elucidate longitudinal variations in patterns of morbidity in terms of the ACGs. About three fourths of the population had a diagnosis-registered encounter with a general practitioner, and the number of patients encountering a general practitioner was estimated at about 90% of all county residents during the three-year period. The morbidity pattern was stable over the three years on both county and PHC centre levels.
Study V was a cross-sectional observational study where relative weights in terms of the ACGs were calculated to estimate the need for resources for each patient category, and these weights were applied to patients at a PHC centre. About 40% of the variation in patient costs was explained by the ACG weights, and about 10% was attributable to age and gender.
The studies illustrate that the retrieval of clinical data on an individual level can be used for grouping of patients on various levels. The limitations of the studies are mainly related to the quality of data registration.
In conclusion, this thesis illustrates that data on an individual level can b used for both clinical and economic purposes, either for describing characteristics of specific diseases, or for elucidating patients belonging to groups of combined types of morbidity. Patient based comorbidity categories yield a new view of the burden of morbidity in defined populations that provides the basis for further analysis of groups of patients.

Co-morbidity,Morbidity Patterns,Resource Allocation,Sweden,Medical Conditions,Population Markers

Please log in/register to access.

Log in/Register

LinkedIn Facebook Twitter

© The Johns Hopkins University, The Johns Hopkins Hospital, and Johns Hopkins Health System.
All rights reserved. Terms of Use Privacy Statement

Back to top