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

J Public Health (Oxf). 2018 Mar 1;40(1):154-162. doi: 10.1093/pubmed/fdx028.

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.

MeSH terms

  • Adult
  • Age Factors
  • Aged
  • Aged, 80 and over
  • Chronic Disease
  • Classification
  • Cohort Studies
  • Comorbidity
  • Databases, Factual
  • Female
  • Hospitalization* / statistics & numerical data
  • Humans
  • Male
  • Middle Aged
  • Patient Admission
  • Proportional Hazards Models
  • Socioeconomic Factors
  • Statistics as Topic
  • Time Factors