Consumer segmentation and time interval between types of hospital admission: a clinical linkage database study.

Abstract

Background Healthcare policies target unplanned hospital admissions and 30-day re-admission as key measures of efficiency, but do not focus on factors that influence trajectories of different types of admissions in the same patient over time. Objectives To investigate the influence of consumer segmentation and patient factors on the time intervals between different types of hospital admission. Research design, subjects and measures A cohort design was applied to an anonymised linkage database for adults aged 40 years and over (N = 58 857). Measures included Mosaic segmentation, multimorbidity defined on six chronic condition registers and hospital admissions over a 27-month time period. Results The shortest mean time intervals between two consecutive planned admissions were: 90 years and over (160 days (95% confidence interval (CI): 146-175)), Mosaic groups 'Twilight subsistence' (171 days (164-179)) or 'Welfare borderline' and 'Municipal dependency' (177 days (172-182)) compared to the reference Mosaic groups (186 days (180-193)), and multimorbidity count of four or more (137 days (130-145)). Mosaic group 'Twilight subsistence' (rate ratio (RR) 1.22 (95% CI: 1.08-1.36)) or 'Welfare borderline' and 'Municipal dependency' RR 1.20 (1.10-1.31) were significantly associated with higher rate to an unplanned admission following a planned event. However, associations between patient factors and unplanned admissions were diminished by adjustment for planned admissions. Conclusion Specific consumer segmentation and patient factors were associated with shorter time intervals between different types of admissions. The findings support innovation in public health approaches to prevent by a focus on long-term trajectories of hospital admissions, which include planned activity.

DOI: 10.1093/pubmed/fdx028

Cite this paper

@article{Kadam2017ConsumerSA, title={Consumer segmentation and time interval between types of hospital admission: a clinical linkage database study.}, author={Umesh T. Kadam and Claire A Lawson and Dawn K Moody and Lucy Teece and John Uttley and John E Harvey and Zafar Iqbal and Paul W. Jones}, journal={Journal of public health}, year={2017}, pages={1-9} }