Cargando…

Does the impact of case management vary in different subgroups of multimorbidity? Secondary analysis of a quasi-experiment

BACKGROUND: Health systems must transition from catering primarily to acute conditions, to meet the increasing burden of chronic disease and multimorbidity. Case management is a popular method of integrating care, seeking to accomplish this goal. However, the intervention has shown limited effective...

Descripción completa

Detalles Bibliográficos
Autores principales: Stokes, Jonathan, Kristensen, Søren Rud, Checkland, Kath, Cheraghi-Sohi, Sudeh, Bower, Peter
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5543754/
https://www.ncbi.nlm.nih.gov/pubmed/28774296
http://dx.doi.org/10.1186/s12913-017-2475-x
Descripción
Sumario:BACKGROUND: Health systems must transition from catering primarily to acute conditions, to meet the increasing burden of chronic disease and multimorbidity. Case management is a popular method of integrating care, seeking to accomplish this goal. However, the intervention has shown limited effectiveness. We explore whether the effects of case management vary in patients with different types of multimorbidity. METHODS: We extended a previously published quasi-experiment (difference-in-differences analysis) with 2049 propensity matched case management intervention patients, adding an additional interaction term to determine subgroup effects (difference-in-difference-in-differences) by different conceptualisations of multimorbidity: 1) Mental-physical comorbidity versus others; 2) 3+ chronic conditions versus <3; 3) Discordant versus concordant conditions; 4) Cardiovascular/metabolic cluster conditions only versus others; 5) Mental health-associated cluster conditions only versus others; 6) Musculoskeletal disorder cluster conditions only versus others 7) Charlson index >5 versus others. Outcome measures included a variety of secondary care utilisation and cost measures. RESULTS: The majority of conceptualisations suggested little to no difference in effect between subgroups. Where results were significant, the vast majority of effect sizes identified in either direction were very small. The trend across the majority of the results appeared to show very slight increases of admissions with treatment for the most complex patients (highest risk). The exceptions to this, patients with a Charlson index >5 may benefit slightly more from case management with decreased ACSC admissions (effect size (ES): −0.06) and inpatient re-admissions (30 days, ES: −0.05), and patients with only cardiovascular/metabolic cluster conditions may benefit slightly more with decreased inpatient non-elective admissions (ES: −0.12). Only the three significant estimates for the musculoskeletal disorder cluster met the minimum requirement for at least a ‘small’ effect. Two of these estimates in particular were very large. This cluster represented only 0.5% of the total patients analysed, however, so is hugely vulnerable to the effects of outliers, and makes us very cautious of interpreting these as ‘real’ effects. CONCLUSIONS: Our results indicate no appropriate multimorbidity subgroup at which to target the case management intervention in terms of secondary care utilisation/cost outcomes. The most complex, highest risk patients may legitimately require hospitalisation, and the intensified management may better identify these unmet needs. End of life patients (e.g. Charlson index >5)/those with only conditions particularly amenable to primary care management (e.g. cardiovascular/metabolic cluster conditions) may benefit very slightly more than others. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12913-017-2475-x) contains supplementary material, which is available to authorized users.