Measuring care trajectories using health administrative databases: a population-based investigation of transitions from emergency to acute care

Care trajectories and transitions at the end of life: a population-based cohort study

BACKGROUND

End-of-life periods are often characterised by suboptimal healthcare use (HCU) patterns in persons aged 65 years and older, with negative effects on health and quality of life. Understanding care trajectories (CTs) and transitions in this period can highlight potential areas of improvement, a subject yet only little studied.

OBJECTIVE

To propose a typology of CTs, including care transitions, for older individuals in the 2 years preceding death.

DESIGN

Retrospective cohort study.

METHODS

We used multidimensional state sequence analysis and data from the Care Trajectories-Enriched Data (TorSaDE) cohort, a linkage between a Canadian health survey and Quebec health administrative data.

RESULTS

In total, 2080 decedents were categorised into five CT groups. Group 1 demonstrated low HCU until the last few months, whilst group 2 showed low HCU over the first year, followed by a steady increase. A gradual increase over the 2 years was observed for groups 3 and 4, though more pronounced towards the end for group 3. A persistent high HCU was observed for group 5. Groups 2 and 4 had higher proportions of cancer diagnoses and palliative care, as opposed to comorbidities and dementia for groups 3 and 5. Overall, 68.4% of individuals died in a hospital, whilst 27% received palliative care there. Care transitions increased rapidly towards the end, most notably in the last 2 weeks.

CONCLUSION

This study provides an understanding of the variability of CTs in the last two years of life, including place of death, a critical step towards quality improvement.

Multimorbidity and determinants for initiating outpatient trajectories: A population-based study

INTRODUCTION

Individuals with multimorbidity often receive high numbers of hospital outpatient services in concurrent trajectories. Nevertheless, little is known about factors associated with initiating new hospital outpatient trajectories; identified as the continued use of outpatient contacts for the same medical condition.

PURPOSE

To investigate whether the number of chronic conditions and sociodemographic characteristics in adults with multimorbidity is associated with entering a hospital outpatient trajectory in this population.

METHODS

This population-based register study included all adults in Denmark with multimorbidity on January 1, 2018. The exposures were number of chronic conditions and sociodemographic characteristics, and the outcome was the rate of starting a new outpatient trajectory during 2018. Analyses were stratified by the number of existing outpatient trajectories. We used Poisson regression analysis, and results were expressed as incidence rates and incidence rate ratios with 95% confidence intervals. We followed the individuals during the entire year of 2018, accounting for person-time by hospitalization, emigration, and death.

RESULTS

Incidence rates for new outpatient trajectories were highest for individuals with low household income and ≥3 existing trajectories and for individuals with ≥3 chronic conditions and in no already established outpatient trajectory. A high number of chronic conditions and male gender were found to be determinants for initiating a new outpatient trajectory, regardless of the number of existing trajectories. Low educational level was a determinant when combined with 1, 2, and ≥3 existing trajectories, and increasing age, western ethnicity, and unemployment when combined with 0, 1, and 2 existing trajectories.

CONCLUSION

A high number of chronic conditions, male gender, high age, low educational level and unemployment were determinants for initiation of an outpatient trajectory. The rate was modified by the existing number of outpatient trajectories. The results may help identify those with multimorbidity at greatest risk of having a new hospital outpatient trajectory initiated.

Healthcare utilization after a first hospitalization for COPD: a new approach of State Sequence Analysis based on the '6W' multidimensional model of care trajectories

Background

Published methods to describe and visualize Care Trajectories (CTs) as patterns of healthcare use are very sparse, often incomplete, and not intuitive for non-experts.

Our objectives are to propose a typology of CTs one year after a first hospitalization for Chronic Obstructive Pulmonary Disease (COPD), and describe CT types and compare patients’ characteristics for each CT type.

Methods

This is an observational cohort study extracted from Quebec’s medico-administrative data of patients aged 40 to 84 years hospitalized for COPD in 2013 (index date). The cohort included patients hospitalized for the first time over a 3-year period before the index date and who survived over the follow-up period. The CTs consisted of sequences of healthcare use (e.g. ED-hospital-home-GP-respiratory therapists, etc.) over a one-year period. The main variable was a CT typology, which was generated by a ‘tailored’ multidimensional State Sequence Analysis, based on the “6W” model of Care Trajectories. Three dimensions were considered: the care setting (“where”), the reason for consultation (“why”), and the speciality of care providers (“which”). Patients were grouped into specific CT types, which were compared in terms of care use attributes and patients’ characteristics using the usual descriptive statistics.

Results

The 2581 patients were grouped into five distinct and homogeneous CT types: Type 1 (n = 1351, 52.3%) and Type 2 (n = 748, 29.0%) with low healthcare and moderate healthcare use respectively; Type 3 (n = 216, 8.4%) with high healthcare use, mainly for respiratory reasons, with the highest number of urgent in-hospital days, seen by pulmonologists and respiratory therapists at primary care settings; Type 4 (n = 100, 3.9%) with high healthcare use, mainly cardiovascular, high ED visits, and mostly seen by nurses in community-based primary care; Type 5 (n = 166, 6.4%) with high healthcare use, high ED visits and non-urgent hospitalisations, and with consultations at outpatient clinics and primary care settings, mainly for other reasons than respiratory or cardiovascular. Patients in the 3 highest utilization CT types were older, and had more comorbidities and more severe condition at index hospitalization.

Conclusions

The proposed method allows for a better representation of the sequences of healthcare use in the real world, supporting data-driven decision making.

The '6W' multidimensional model of care trajectories for patients with chronic ambulatory care sensitive conditions and hospital readmissions

OBJECTIVES

To synthesize concepts and approaches related to the analysis of patterns or processes of care and patient's outcomes into a comprehensive model of care trajectories, focusing on hospital readmissions for patients with chronic ambulatory care sensitive conditions (ACSCs).

STUDY DESIGN

Narrative literature review.

METHODS

Published studies between January 2000 and November 2017, using the concepts of 'continuity', 'pathway', 'episode', and 'trajectory', and focused on readmissions and chronic ACSCs, were collected in electronic databases. Qualitative content analysis was performed with emphasis on key constituents to build a comprehensive model.

RESULTS

Specific common constituents are shared by the concepts reviewed: they focus on the patient, aim to measure and improve outcomes, follow specific periods of time and consider other factors related to care providers, care units, care settings, and treatments. Using these common denominators, the comprehensive '6W' multidimensional model of care trajectories was created. Considering patients' attributes and their chronic ACSCs illness course ('who' and 'why' dimensions), this model reflects their patterns of health care use across care providers ('which'), care units ('where'), and treatments ('what'), at specific periods of time ('when').

CONCLUSIONS

The '6W' model of care trajectories could provide valuable information on 'missed opportunities' to reduce readmission rates and improve quality of both ambulatory and inpatient care.