| Title |
Comparison of two methods to report potentially avoidable hospitalizations in France in 2012: a cross-sectional study
|
|---|---|
| Published in |
BMC Health Services Research, January 2015
|
| DOI | 10.1186/s12913-014-0661-7 |
| Pubmed ID | |
| Authors |
Rodolphe Bourret, Grégoire Mercier, Jacques Mercier, Olivier Jonquet, Jean-Emmanuel De La Coussaye, Philippe J Bousquet, Jean-Marie Robine, Jean Bousquet |
| Abstract |
BackgroundPotentially avoidable hospitalizations represent an indirect measure of access to effective primary care. However many approaches have been proposed to measure them and results may differ considerably. This work aimed at examining the agreement between the Weissman and Ansari approaches in order to measure potentially avoidable hospitalizations in France.MethodsBased on the 2012 French national hospital discharge database (Programme de Médicalisation des Systèmes d'Information), potentially avoidable hospitalizations were measured using two approaches proposed by Weissman et al. and by Ansari et al. Age- and sex-standardised rates were calculated in each department. The two approaches were compared for diagnosis groups, type of stay, severity, age, sex, and length of stay.ResultsThe number and age-standardised rate of potentially avoidable hospitalizations estimated by the Weissman et al. and Ansari et al. approaches were 742,474 (13.3 cases per 1,000 inhabitants) and 510,206 (9.0 cases per 1,000 inhabitants), respectively. There are significant differences by conditions groups, age, length of stay, severity level, and proportion of medical stays between the Weissman and Ansari methods.ConclusionsRegarding potentially avoidable hospitalizations in France in 2012, the agreement between the Weissman and Ansari approaches is poor. The method used to measure potentially avoidable hospitalizations is critical, and might influence the assessment of accessibility and performance of primary care. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 39 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 1 | 3% |
| Unknown | 38 | 97% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Postgraduate | 5 | 13% |
| Student > Master | 5 | 13% |
| Student > Doctoral Student | 4 | 10% |
| Professor | 3 | 8% |
| Student > Bachelor | 3 | 8% |
| Other | 11 | 28% |
| Unknown | 8 | 21% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 15 | 38% |
| Unspecified | 2 | 5% |
| Business, Management and Accounting | 2 | 5% |
| Biochemistry, Genetics and Molecular Biology | 1 | 3% |
| Nursing and Health Professions | 1 | 3% |
| Other | 5 | 13% |
| Unknown | 13 | 33% |
Attention Score in Context
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#20,249,662
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Outputs from BMC Health Services Research
#7,090
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Outputs of similar age from BMC Health Services Research
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