Optimal Matching Analysis in Career Research: A Review and Some Best-practice Recommendations

Dlouhy, Katja

doi:10.5465/ambpp.2015.14674abstract

Cited by 20 publications

(38 citation statements)

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“…In step 3, we chose optimal matching, a method largely used in social sciences [32,[40][41][42] to measure the distance (or dissimilarity) between patients' CT sequences for each of the three dimensions. For each pair of CT sequences, this method measures the minimal cost of transforming one sequence into the other.…”

Section: Discussionmentioning

confidence: 99%

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

Vanasse

Courteau

et al. 2020

BMC Health Serv Res

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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.

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Section: Discussionmentioning

confidence: 99%

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

Vanasse

Courteau

et al. 2020

BMC Health Serv Res

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“…Dlouhy et al recommended using sequences with at least 25 states. They also showed that the number of sequences only has a small effect on the final typology 25 . It is known that missing values can occur at the beginning of some sequences, due to data availability and the data source.…”

Section: The 1 St Step Of Ssa: Identification Of States and Sequencesmentioning

confidence: 99%

“…In general (not in our case study due to the characteristics of the database), missing values inside sequences can be considered using an additional state, coded as nonattributed (NA). However, it is recommended to exclude sequences when more than 30% of the states are missing 25 .…”

Section: The 1 St Step Of Ssa: Identification Of States and Sequencesmentioning

confidence: 99%

“…Ward's criterion is the most used in social sciences 25 with dissimilarity measures 36,37 , and it produces the best results in clustering 25 . Unweighted pair-group using arithmetic averages (UPGMA) and weighted pair-group using arithmetic averages (WPGMA) methods can also be considered for agglomerative clustering 25 . In regard to the k-medoids algorithm, the one that we favour is the partitioning around medoids (PAM) algorithm 38 .…”

Section: The 3 Rd Step Of Ssa: Clustering Sequencesmentioning

confidence: 99%

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Use of state sequence analysis for care pathway analysis: The example of multiple sclerosis

Roux

Grimaud

Leray

2018

Stat Methods Med Res

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The concept of care pathways is increasingly being used to enhance the quality of care and to optimize the use of resources for health care. We here propose an innovative method in epidemiology that is derived from social sciences: state sequence analysis (SSA). This method takes into account the chronology of care consumption and allows for identification of specific patterns. A process for using SSA in the health area is proposed and discussed. The main steps are: data coding, measurement of dissimilarities between sequences (focusing on optimal matching methods and the choice of related costs), and application of a clustering method to obtain a typology of sequence patterns. As an example of its use in the health area, SSA was employed to analyse care pathways of a random sample of patients with multiple sclerosis. This sample has been selected from the main French healthcare database covering the period 2007 to 2013 ( n = 1 000). A five-cluster typology was obtained which allowed distinction of care consumption groups. Overall, about half of the patients had low care consumption, about one quarter had medium to high consumption, and another quarter had high consumption. We conclude that state sequence analysis is an innovative and flexible methodology that is worth considering in health care research.

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“…Increased availability of longitudinal datasets and methodological advances in the social sciences, however, such as the use of sequence analysis techniques, have started to allow an examination of more holistic trajectories (see Dlouhy and Biemann, [2015] for a summary of studies on careers and occupational trajectories using optimal matching analysis). Cebulla and Whetton (2018), building on the work of Fry and Boulton (2013), provide a recent example of the use of optimal matching and cluster analysis to examine labour market pathways of young Australians.…”

Section: Methodology and Methodsmentioning

confidence: 99%

Youth transitions to employment: longitudinal evidence from marginalised young people in England

Sanderson

2019

Journal of Youth Studies

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This paper uses empirical evidence to explore the nature of employment transitions for a cohort of marginalised young people in England. The findings presented reveal the importance of past experiences, largely determined by prevailing opportunity structures, in shaping the present and reiterate the need to see transition as a historical process. Longitudinal data collected as part of an evaluation of a youth employment programme called Talent Match provides the evidence for the paper. The routes participants took in terms of securing and sustaining employment are examined. The paper develops a typology of different transitional groups to explore these routes based on the movement (or lack of) into and out of employment. The relative importance of different factors in explaining the groupings are assessed, with results underlining how the ongoing change participants were encountering in the present was inextricably linked to their past. In response, this paper suggests a reemphasis on understanding youth as both a stage of 'being' and 'becoming', seeing youth as both a condition in its own right but also part of the life course process, and calls for a more dynamic understanding of youth transitions among policymakers and those designing youth employment programmes. ARTICLE HISTORY

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Optimal Matching Analysis in Career Research: A Review and Some Best-practice Recommendations

Cited by 20 publications

References 0 publications

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

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

Use of state sequence analysis for care pathway analysis: The example of multiple sclerosis

Youth transitions to employment: longitudinal evidence from marginalised young people in England

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