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

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.

Care trajectories around a first dementia diagnosis in patients with serious mental illness

AIM

To develop a typology of care trajectories (CTs) 1 year before and after a first dementia diagnosis in individuals aged ≥65 years, with prevalent schizophrenia or bipolar disorder.

METHODS

This was a longitudinal, retrospective cohort study using health administrative data (1996-2016) from Quebec (Canada). We selected patients aged ≥65 years with an incident diagnosis of dementia between 1 January 2014 and 31 December 2016, and a diagnosis of schizophrenia and/or or bipolar disorder. A CT typology was generated by a multidimensional state sequence analysis based on the "6 W" model of CTs. Three dimensions were considered: the care setting ("where"), the reason for consultation ("why") and the specialty of care providers ("which").

RESULTS

In total, 3868 patients were categorized into seven distinct types of CTs, with varying patterns of healthcare use and comorbidities. Healthcare use differed in terms of intensity, but also in its distribution around the diagnosis. For instance, whereas one group showed low healthcare use, healthcare use abruptly increased or decreased after the diagnosis in other groups, or was equally distributed. Other significant differences between CTs included mortality rates and use of long-term care after the diagnosis. Most patients (67%) received their first dementia diagnosis during hospitalization.

CONCLUSIONS

Our innovative approach provides a unique insight into the complex healthcare patterns of people living with serious mental illness and dementia, and provides an avenue to support data-driven decision-making by highlighting fragility areas in allocating care resources. Geriatr Gerontol Int 2024; 24: 577-586.

Longitudinal trajectories of substance use disorder treatment use: A latent class growth analysis using a national cohort in Chile

BACKGROUND AND AIMS

Longitudinal studies have revealed that substance use treatment use is often recurrent among patients; the longitudinal patterns and characteristics of those treatment trajectories have received less attention, particularly in the global south. This study aimed to disentangle heterogeneity in treatment use among adult patients in Chile by identifying distinct treatment trajectory groups and factors associated with them.

DESIGN

National-level registry-based retrospective cohort.

SETTING AND PARTICIPANTS

Adults admitted to publicly funded substance use disorder treatment programs in Chile from November 2009 to November 2010 and followed for 9 years (n = 6266).

MEASUREMENTS

Monthly treatment use; type of treatment; ownership of the treatment center; discharge status; primary substance used; sociodemographic.

FINDINGS

A seven-class treatment trajectory solution was chosen using latent class growth analysis. We identified three trajectory groups that did not recur and had different treatment lengths: Early discontinuation (32%), Less than a year in treatment (19.7%) and Year-long episode, without recurrence (12.3%). We also identified a mixed trajectory group that had a long first treatment or two treatment episodes with a brief time between treatments: Long first treatment, or immediate recurrence (6.3%), and three recurrent treatment trajectory groups: Recurrent and decreasing (14.2%), Early discontinuation with recurrence (9.9%) and Recurrent after long between treatments period (5.7%). Inpatient or outpatient high intensity (vs. outpatient low intensity) at first entry increased the odds of being in the longer one-episode groups compared with the Early discontinuation group. Women had increased odds of belonging to all the recurrent groups. Using cocaine paste (vs. alcohol) as a primary substance decreased the odds of belonging to long one-episode groups.

CONCLUSIONS

In Chile, people in publicly funded treatment for substance use disorder show seven distinct care trajectories: three groups with different treatment lengths and no recurring episodes, a mixed group with a long first treatment or two treatment episodes with a short between-treatment-episodes period and three recurrent treatment groups.

Variations in COPD Health Care Access and Outcomes: A Rapid Review

Background

Health inequities among individuals with chronic obstructive pulmonary disease (COPD) are often associated with differential access to health care and health outcomes. A greater understanding of the literature concerning such variation is necessary to determine where gaps or inequities exist along the continuum of COPD care.

Methods

A rapid review of the published and grey literature reporting variations in health care access and/or health outcomes for individuals with COPD was completed. Variation was defined as differential patterns in access indicators or outcome measures within sociodemographic categories, including age, ethnicity, geography, race, sex, and socioeconomic status. Emergent themes were identified from the included literature and synthesized narratively.

Results

Thirty-five articles were included for final review; the majority were retrospective cohort studies. Twenty-five studies assessed variation in access to health care. Key indicators included: access to spirometry testing, medication adherence, participation in pulmonary rehabilitation, and contact with general practitioners and/or respiratory specialists. Twenty-one studies assessed variation in health outcomes in COPD and key metrics included: hospital-based resource utilization (length of stay and admissions/readmissions), COPD exacerbations, and mortality. Patients who live in rural environments and those of lower socioeconomic status had both poorer access to care and outcomes at the system and patient level. Other sociodemographic variables, including ethnicity, race, age, and sex were associated with variation in health care access and outcomes, although these findings were less consistent.

Conclusion

The results of this rapid review suggest that substantial variation in access and outcomes exists for individuals with COPD, highlighting opportunities for targeted interventions and policies.

Care trajectories of individuals with anxiety disorders: A retrospective cohort study

BACKGROUND

Anxiety disorders (ADs) are associated with increased healthcare use (HCU), and individuals may seek healthcare through various pathways according to clinical and individual characteristics. This study aimed to characterize care trajectories (CTs) of individuals with ADs.

METHODS

This is a retrospective cohort study using the Care Trajectories - Enriched Data cohort, a linkage between the Canadian Community Health Surveys (CCHS), and health administrative data from Quebec. The cohort included 5143 respondents reporting ADs to the CCHS between 2009 and 2016. We measured CTs over 5 years before CCHS using a state sequence analysis.

RESULTS

The cohort was categorized into five types of CTs. Type 1 (52.7 %) was the lowest care-seeking group, with fewer comorbidities. Type 2 (24.0 %) had higher levels of physical and mental health comorbidities and moderate HCU, mainly ambulatory visits to general practitioners. Type 3 (13.1 %) represented older patients with the highest level of physical illnesses and high HCU, predominantly ambulatory consultation of specialists other than psychiatrists. Types 4 and 5 combined young and middle-aged patients suffering from severe psychological distress. HCU of type 4 (6.7 %) was high, mainly consultations of ambulatory psychiatrists, and HCU of type 5 (3.5 %), was the highest and mostly in acute care.

LIMITATIONS

Administrative and survey data may have coding errors, missing data and self-report biases.

CONCLUSION

Five types of CTs showed distinct patterns of HCU often modulated by physical and mental health comorbidities, which emphasizes the importance of considering ADs when individuals seek care for other mental health conditions or physical illness.

Applying sequence analysis to uncover 'real-world' clinical pathways from routinely collected data: a systematic review

OBJECTIVES

This systematic review aims to elucidate the methodological practices and reporting standards associated with sequence analysis (SA) for the identification of clinical pathways in real-world scenarios, using routinely collected data.

STUDY DESIGN AND SETTING

We conducted a methodological systematic review, searching five medical and health databases: MEDLINE, PsycINFO, CINAHL, EMBASE and Web of Science. The search encompassed articles from the inception of these databases up to February 28, 2023. The search strategy comprised two distinctive sets of search terms, specifically focused on sequence analysis and clinical pathways.

RESULTS

19 studies met the eligibility criteria for this systematic review. Nearly 60% of the included studies were published in or after 2021, with a significant proportion originating from Canada (n = 7) and France (n = 5). 90% of the studies adhered to the fundamental SA steps. The optimal matching (OM) method emerged as the most frequently employed dissimilarity measure (63%), while agglomerative hierarchical clustering using Ward's linkage was the preferred clustering algorithm (53%). However, it is imperative to underline that a majority of the studies inadequately reported key methodological decisions pertaining to SA.

CONCLUSION

This review underscores the necessity for enhanced transparency in reporting both data management procedures and key methodological choices within SA processes. The development of reporting guidelines and a robust appraisal tool tailored to assess the quality of SA would be invaluable for researchers in this field.

Trajectories of Service Contact before Suicide in People with Substance Use Disorders-A National Register Study

OBJECTIVE

This study aimed to identify trajectories of service use during the last year before suicide death and the characteristics associated with the trajectories in patients with substance use disorders.

METHODS

This study used a national registry data linkage, which included all patients with substance use disorders who died by suicide in Norway between 2010 and 2018. In- and outpatient contacts with mental health or substance use services during the last year before suicide death was analyzed by week using Sequence State Analysis and cluster analysis to identify trajectories. Logistic regression was used to measure the association between the characteristics and the trajectories.

RESULTS

We identified four trajectories of service contact. A brief contact trajectory (n = 366) with a low proportion of weeks in contact (M weeks = 8.3), associated with less psychosis or bipolar disorder (aOR = 0.13 (0.08-0.22)) and higher age. A regular contact trajectory (n = 160), with a higher proportion of contact (M weeks = 47.9), associated with psychosis or bipolar disorder (aOR = 3.66 (2.10-6.47)) and depressive or anxiety disorder (aOR = 3.11 (1.93-5.13)). An intermittent contact trajectory (n = 195) with most contacts with outpatient substance use disorder services (M weeks = 9.7). A continuous contact trajectory (n = 109) with a high proportion of inpatient contact (M weeks = 44.5), strongly associated with psychosis or bipolar disorder (aOR = 6.08 (3.26-11.80)).

CONCLUSION

Longitudinal descriptions of service use reveal different trajectories that are important to consider when developing policies or interventions to reduce the risk of suicide death in patients with substance use disorders.

Care pathways of sepsis survivors: sequelae, mortality and use of healthcare services in France, 2015-2018

BACKGROUND

Individuals who survive sepsis are at high risk of chronic sequelae, resulting in significant health-economic costs. Several studies have focused on aspects of healthcare pathways of sepsis survivors but comprehensive, longitudinal overview of their pathways of care are scarce. The aim of this retrospective, longitudinal cohort study is to identify sepsis survivor profiles based on their healthcare pathways and describe their healthcare consumption and costs over the 3 years following their index hospitalization.

METHODS

The data were extracted from the French National Hospital Discharge Database. The study population included all patients above 15 years old, with bacterial sepsis, who survived an incident hospitalization in an acute care facility in 2015. To identify survivor profiles, state sequence and clustering analyses were conducted over the year following the index hospitalization. For each profile, patient characteristics and their index hospital stay and sequelae were described, as well as use of care and its associated monetary costs, both pre- and post-sepsis.

RESULTS

New medical (79.2%), psychological (26.9%) and cognitive (18.5%) impairments were identified post-sepsis, and 65.3% of survivors were rehospitalized in acute care. Cumulative mortality reached 36.6% by 3 years post-sepsis. The total medical cost increased by 856 million € in the year post-sepsis. Five patient clusters were identified: home (65.6% of patients), early death (12.9%), late death (6.8%), short-term rehabilitation (11.3%) and long-term rehabilitation (3.3%). Survivors with early and late death clusters had high rates of cancer and primary bacteremia and experienced more hospital-at-home care post-sepsis. Survivors in short- or long-term rehabilitation clusters were older, with higher percentage of septic shock than those coming back home, and had high rates of multiple site infections and higher rates of new psychological and cognitive impairment.

CONCLUSIONS

Over three years post-sepsis, different profiles of sepsis survivors were identified with different mortality rates, sequels and healthcare services usage and cost. This study confirmed the importance of sepsis burden and suggests that strategies of post-discharge care, in accordance with patient profile, should be further tested in order to reduce sepsis burden.

Discovering patterns in outpatient neurology appointments using state sequence analysis

BACKGROUND

Outpatient services in the UK, and in particular outpatient neurology services, are under considerable pressure with an ever-increasing gap between capacity and demand. To improve services, we first need to understand the current situation. This study aims to explore the patterns of appointment type seen in outpatient neurology, in order to identify potential opportunities for change.

METHODS

We use State Sequence Analysis (SSA) on routinely collected data from a single neurology outpatient clinic. SSA is an exploratory methodology which allows patterns within sequences of appointments to be discovered. We analyse sequences of appointments for the 18 months following a new appointment. Using SSA we create groups of similar appointment sequence patterns, and then analyse these clusters to determine if there are particular sequences common to different diagnostic categories.

RESULTS

Of 1315 patients 887 patients had only one appointment. Among the 428 patients who had more than one appointment a 6 monthly cycle of appointments was apparent. SSA revealed that there were 11 distinct clusters of appointment sequence patterns. Further analysis showed that there are 3 diagnosis categories which have significant influence over which cluster a patient falls into: seizure/epilepsy, movement disorders, and headache.

CONCLUSIONS

Neurology outpatient appointment sequences show great diversity, but there are some patterns which are common to specific diagnostic categories. Information about these common patterns could be used to inform the structure of future outpatient appointments.

Analytical methods for identifying sequences of utilization in health data: a scoping review

BACKGROUND

Healthcare, as with other sectors, has undergone progressive digitalization, generating an ever-increasing wealth of data that enables research and the analysis of patient movement. This can help to evaluate treatment processes and outcomes, and in turn improve the quality of care. This scoping review provides an overview of the algorithms and methods that have been used to identify care pathways from healthcare utilization data.

METHOD

This review was conducted according to the methodology of the Joanna Briggs Institute and the Preferred Reporting Items for Systematic Reviews Extension for Scoping Reviews (PRISMA-ScR) Checklist. The PubMed, Web of Science, Scopus, and EconLit databases were searched and studies published in English between 2000 and 2021 considered. The search strategy used keywords divided into three categories: the method of data analysis, the requirement profile for the data, and the intended presentation of results. Criteria for inclusion were that health data were analyzed, the methodology used was described and that the chronology of care events was considered. In a two-stage review process, records were reviewed by two researchers independently for inclusion. Results were synthesized narratively.

RESULTS

The literature search yielded 2,865 entries; 51 studies met the inclusion criteria. Health data from different countries ([Formula: see text]) and of different types of disease ([Formula: see text]) were analyzed with respect to different care events. Applied methods can be divided into those identifying subsequences of care and those describing full care trajectories. Variants of pattern mining or Markov models were mostly used to extract subsequences, with clustering often applied to find care trajectories. Statistical algorithms such as rule mining, probability-based machine learning algorithms or a combination of methods were also applied. Clustering methods were sometimes used for data preparation or result compression. Further characteristics of the included studies are presented.

CONCLUSION

Various data mining methods are already being applied to gain insight from health data. The great heterogeneity of the methods used shows the need for a scoping review. We performed a narrative review and found that clustering methods currently dominate the literature for identifying complete care trajectories, while variants of pattern mining dominate for identifying subsequences of limited length.

Tactical positioning behaviours in short-track speed skating: A static and dynamic sequence analysis

Tactical positioning is essential for success in short-track speed skating as the race format (direct, head-to-head competition over multiple laps) prioritises finishing position over finishing time. Despite this, current research into tactical positioning treats the race's laps as discrete, independent events. Accordingly, the aggregate metrics used to summarise each lap's tactical positioning behaviour do not allow us to explore the sequential nature of the data, e.g., Lap 2 occurs after Lap 1 and before Lap 3. Here, we capture the sequential relationships between laps to investigate tactical positioning behaviours in short-track speed skating. Using intermediate and final rankings from 500 m, 1,000 m, and 1,500 m elite short-track races, we analyse whole-race and sub-race race sequences of group and winner tactical positioning behaviours. This approach, combined with a large dataset of races collected over eight seasons of competition (n  = 4,135), provides the most rigorous and comprehensive description of tactical positioning behaviours in short-track speed skating to date. Our results quantify the time-evolving complexity of tactical positioning, offer new thoughts on race strategy, and can help practitioners design more representative learning tasks to enhance skill transfer.

Trajectories of care of community-dwelling people living with dementia: a multidimensional state sequence analysis

BACKGROUND

The type and level of healthcare services required to address the needs of persons living with dementia fluctuate over disease progression. Thus, their trajectories of care (the sequence of healthcare use over time) may vary significantly. We aimed to (1) propose a typology of trajectories of care among community-dwelling people living with dementia; (2) describe and compare their characteristics according to their respective trajectories; and (3) evaluate the association between trajectories membership, socioeconomic factors, and self-perceived health.

METHODS

This is an observational study using the data of the innovative Care Trajectories -Enriched Data (TorSaDE) cohort, a linkage between five waves of the Canadian Community Health Survey (CCHS), and health administrative data from the Quebec provincial health-insurance board. We analyzed data from 690 community-dwelling persons living with dementia who participated in at least one cycle of the CCHS (the date of the last CCHS completion is the index date). Trajectories of care were defined as sequences of healthcare use in the two years preceding the index date, using the following information: 1) Type of care units consulted (Hospitalization, Emergency department, Outpatient clinic, Primary care clinic); 2) Type of healthcare care professionals consulted (Geriatrician/psychiatrist/neurologist, Other specialists, Family physician).

RESULTS

Three distinct types of trajectories describe healthcare use in persons with dementia: 1) low healthcare use (n = 377; 54.6%); 2) high primary care use (n = 154; 22.3%); 3) high overall healthcare use (n = 159; 23.0%). Group 3 membership was associated with living in urban areas, a poorer perceived health status and higher comorbidity.

CONCLUSION

Further understanding how subgroups of patients use healthcare services over time could help highlight fragility areas in the allocation of care resources and implement best practices, especially in the context of resource shortage.

Clustering of prostate cancer healthcare pathways in the French National Healthcare database

Background

Healthcare pathways of patients with prostate cancer are heterogeneous and complex to apprehend using traditional descriptive statistics. Clustering and visualization methods can enhance their characterization.

Methods

Patients with prostate cancer in 2014 were identified in the French National Healthcare database (Système National des Données de Santé-SNDS) and their data were extracted with up to 5 years of history and 4 years of follow-up. Fifty-one-specific encounters constitutive of prostate cancer management were synthesized into four macro-variables using a clustering approach. Their values over patient follow-ups constituted healthcare pathways. Optimal matching was applied to calculate distances between pathways. Partitioning around medoids was then used to define consistent groups across four exclusive cohorts of incident prostate cancer patients: Hormone-sensitive (HSPC), metastatic hormone-sensitive (mHSPC), castration-resistant (CRPC), and metastatic castration-resistant (mCRPC). Index plots were used to represent pathways clusters.

Results

The repartition of macro-variables values-surveillance, local treatment, androgenic deprivation, and advanced treatment-appeared to be consistent with prostate cancer status. Two to five clusters of healthcare pathways were observed in each of the different cohorts, corresponding for most of them to relevant clinical patterns, although some heterogeneity remained. For instance, clustering allowed to distinguish patients undergoing active surveillance, or treated according to cancer progression risk in HSPC, and patients receiving treatment for potentially curative or palliative purposes in mHSPC and mCRPC.

Conclusion

Visualization methods combined with a clustering approach enabled the identification of clinically relevant patterns of prostate cancer management. Characterization of these care pathways is an essential element for the comprehension and the robust assessment of healthcare technology effectiveness.

Identifying common patterns of health services use: a longitudinal study of older Swiss adults' care trajectories

BACKGROUND

Population ageing puts pressure on health systems initially designed to handle acute and episodic illnesses. Segmenting an ageing population based on its healthcare utilization may enable policymakers to undertake evidence-based resource planning. We aimed to derive a typology of healthcare utilization trajectories in Swiss older adults.

METHODS

Our work used data from the Lc65 + study, a population-based cohort of individuals aged 65 to 70 years at enrolment. The dimensions of healthcare utilization considered were ambulatory care, emergency care, hospitalizations, professional home care and nursing home stay. We applied the Sequence Analysis framework, within which we quantified the variation between each multidimensional pair of sequences, implemented a clustering procedure that grouped together older persons with similar profiles of health services use, and characterized clusters of individuals using selected baseline covariates.

RESULTS

Healthcare utilization trajectories were analysed for 2271 community-dwelling older adults over a period of 11 years. Six homogeneous subgroups were identified: constant low utilization (83.3% of participants), increased utilization (4.9%), late health deterioration (4.4%), ambulatory care to nursing home (1.5%), early fatal event (3.8%) and high ambulatory care (2.1%). Associations were found between cluster membership and age, sex, household composition, self-perceived health, grip strength measurement, comorbidities, and functional dependency.

CONCLUSIONS

The heterogeneous healthcare utilization profiles can be clustered into six common patterns. Different manifestations of functional decline were apparent in two distinct trajectory groups featuring regular home care use. Furthermore, a small proportion of individuals with a unique set of characteristics was related to the highest levels of ambulatory and emergency care use. New research avenues are outlined to investigate time-varying effects of health factors inside the clusters containing most unfavourable outcomes.

Multidimensional analysis of adult patients’ care trajectories before a first diagnosis of schizophrenia

For patients at high-risk for developing schizophrenia, a delayed diagnosis could be affected, among many reasons, by their patterns of healthcare use. This study aims to describe and generate a typology of patients’ care trajectories (CTs) in the 2 years preceding a first diagnosis of schizophrenia, over a medico-administrative database of 3712 adults with a first diagnosis between April 2014 and March 2015 in Quebec, Canada. This study applied a multidimensional approach of State Sequence Analysis, considering together sequences of patients’ diagnoses, care settings and care providers. Five types of distinct CTs have emerged from this data-driven analysis: The type 1, shared by 77.6% of patients, predominantly younger men, shows that this group sought little healthcare, among which 17.5% had no healthcare contact for mental disorders. These individuals might benefit from improved promotion and prevention of mental healthcare at the community level. The types 2, 3 and 4, with higher occurrence of mental disorder diagnoses, represent together 19.5% of the study cohort, mostly middle-aged and women. These CTs, although displaying roughly similar profiles of mental disorders, revealed very dissimilar sequences and levels of care providers encounters, primary and specialized care use, and hospitalizations. Surprisingly, patients of these CTs had few consultations with general practitioners. An increased attentiveness for middle-aged patients and women with high healthcare use for mental disorders could help to reduce delayed diagnosis of schizophrenia. This calls for further consideration of healthcare services for severe mental illness beyond those offered to young adults.

Distinct care trajectories among persons living with arthritic conditions: A two-year state sequence analysis

OBJECTIVES

Developing solutions to optimize care trajectories (CareTs) requires examining patient journeys through the health care system. This study aimed to describe CareTs among people living with arthritis and evaluate their association with self-reported health outcomes.

METHODS

Analyses were conducted using the TorSaDE Cohort (n = 102,148), which connects the 2007 to 2016 Canadian Community Health Surveys (CCHS) with Quebec administrative databases (longitudinal claims). CareTs of participants living with arthritis according to CCHS (n = 16,631), over the two years before CCHS completion, were clustered using state sequence analysis (months as a time unit). CareT group membership was then put in association with self-reported outcomes (pain intensity and interference, self-perceived general and mental health).

RESULTS

The analysis revealed five CareT groups characterized predominantly by: (1) arthritis-related visits to a specialist (n = 2,756; 16.6%), (2) arthritis-related emergency department visits (n = 2,928; 17.6%), (3) very high all-cause health care utilization and arthritis-related hospitalizations (n = 1,570; 9.4%), (4) arthritis-related medical visits to general practitioners and specialists (n = 2,708; 16.3%), (5) low all-cause health care utilization (n = 6,669; 40.1%). Multivariable results revealed that CareT group membership was associated with higher levels of pain interference (CareT group #3 vs. #5: OR: 1.4, 95%CI: 1.1-1.8) and fair/poor self-perceived general health (CareT group #1 vs. #5: OR: 1.551, 95%CI: 1.319-1.824; #2 vs. #5: OR: 1.244, 95%CI: 1.062-1.457; #3 vs. #5: OR: 1.771, 95%CI: 1.451-2.162; #4 vs. #5: OR: 1.481, 95%CI: 1.265-1.735).

DISCUSSION

Sate sequence analysis is an innovative method of studying CareTs and valuable for making evidence-based decisions taking into account inter- and intra-individual variability.

Antipsychotic utilization trajectories three years after initiating or reinitiating treatment of schizophrenia: A state sequence analysis approach

OBJECTIVE

This study aims to describe the utilization patterns of antipsychotic (AP) medication in patients with schizophrenia (SCZ), three years after initiating or reinitiating a given AP.

METHODS

Based on medico-administrative information on patients living in Quebec (Canada), this retrospective cohort study included 6444 patients with a previous diagnosis of SCZ initiating or reinitiating AP medication between January 1, 2012, and December 31, 2014, with continuous coverage by public drug insurance. For each day of follow-up (1092 days), patient was either exposed to one of the chosen categories of APs, or to none. This patient's sequence of AP exposure overtime has been referred to as the "antipsychotic utilization trajectory". These trajectories were analyzed using a State Sequence Analysis, an innovative approach which provides useful visual information on the continuation and discontinuation patterns of use over time.

RESULTS

Clozapine and long-acting injectable second-generation APs had the best continuation and discontinuation patterns over 3 years among all other groups, including less switching of APs, while oral first-generation APs had the poorest patterns. These findings were comparable among incident and non-incident cohorts. Oral second-generation antipsychotics, excluding clozapine, had a poorer continuation and discontinuation pattern than long-acting injectable antipsychotics.

CONCLUSION

State Sequence Analysis provides a clear representation of treatment adherence in comparison with dichotomous indicators of adherence or discontinuation. Consequently, this innovative method has shed light on the impact of the AP chosen to initiate or reinitiate treatment in SCZ, which has been identified as a key factor for long-term treatment continuation and discontinuation.

Exploring social inequalities in healthcare trajectories following diagnosis of diabetes: a state sequence analysis of linked survey and administrative data

Background

Social inequalities in complications associated with diabetes mellitus persist. As a primary care sensitive condition (PCSC), this association could be related to differential access to primary care. Our objectives are to establish a typology of care trajectories following a new diagnosis, and to explore social determinants of trajectories.

Methods

We used the TorSaDe (The Care Trajectories-Enriched Data) cohort, which links Canadian Community Health Survey respondents to health administrative data. Care trajectories were mapped over a two-year period following a new diagnosis and analysed using state sequence and clustering methods. Associations between individual and geographic characteristics with trajectory types were assessed with multinomial logistic regression.

Results

Three trajectories were identified: Regular Family Physician (FP) Predominant, Specialist Physician Predominant, and Few Services. With Regular FP as the reference, males had higher odds of experiencing the Few Services trajectory, higher education was associated with higher odds of both the Few Services and the Specialist trajectories, and immigrants had higher odds of the Specialist trajectory. Diagnoses in a physician’s office, as opposed to in hospital, were associated with higher odds of the Regular FP trajectory.

Conclusions

The Regular FP trajectory most closely aligns with the management principles of the PCSC approach. We did not find strong evidence of social status privileging access to this trajectory. However, the association with location of diagnosis suggests that efforts to ensure patients diagnosed in hospital are well linked to a regular family physician for follow up may help to reduce unnecessary specialist use and meet PCSC goals.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12913-021-07450-9.

Association between previous and future antipsychotic adherence in patients initiating clozapine: real-world observational study

BACKGROUND

Although recognised as the most effective antipsychotic for treatment-resistant schizophrenia, clozapine remains underused. One reason is the widespread concern about non-adherence to clozapine because of poor adherence before initiating clozapine.

AIMS

To determine if prior poor out-patient adherence to treatmentbefore initiating clozapine predisposes to poor out-patient adherence to clozapine or to any antipsychotics (including clozapine) after its initiation.

METHOD

This cohort study included 3228 patients with schizophrenia living in Quebec (Canada) initiating (with a 2-year clearance period) oral clozapine (index date) between 2009 and 2016. Using pharmacy data, out-patient adherence to treatment was measured by the medication possession ratio (MPR), over a 1-year period preceding and following the index date. Five groups of patients were formed based on their prior MPR level (independent variable). Two dependent variables were defined after clozapine initiation (good out-patient adherence to any antipsychotics and to clozapine only). Along with multiple logistic regressions, state sequence analysis was used as a visual representation of antipsychotic-use trajectories over time, before and after clozapine initiation.

RESULTS

Although prior poor adherence to antipsychotics was associated with poor adherence after clozapine initiation, the absolute risk of subsequent poor adherence remained low, regardless of previous adherence level. Most patients adhered to their treatment after initiating clozapine (>68% to clozapine and >84% to any antipsychotics).

CONCLUSIONS

Despite the fact that poor adherence prior to initiating clozapine is widely recognised by clinicians as a barrier for the prescription of clozapine, the current study supports the initiation of clozapine in all eligible patients.

Use of State Sequence Analysis in Pharmacoepidemiology: A Tutorial

While state sequence analysis (SSA) has been long used in social sciences, its use in pharmacoepidemiology is still in its infancy. Indeed, this technique is relatively easy to use, and its intrinsic visual nature may help investigators to untangle the latent information within prescription data, facilitating the individuation of specific patterns and possible inappropriate use of medications. In this paper, we provide an educational primer of the most important learning concepts and methods of SSA, including measurement of dissimilarities between sequences, the application of clustering methods to identify sequence patterns, the use of complexity measures for sequence patterns, the graphical visualization of sequences, and the use of SSA in predictive models. As a worked example, we present an application of SSA to opioid prescription patterns in patients with non-cancer pain, using real-world data from Italy. We show how SSA allows the identification of patterns in prescriptions in these data that might not be evident using standard statistical approaches and how these patterns are associated with future discontinuation of opioid therapy.

Use of primary and hospital care health services by chronic patients according to risk level by adjusted morbidity groups

Background

Patients with chronic diseases have increased needs for assistance and care. The objective of this study was to describe the characteristics and use of primary care (PC) and hospital care (HC) health services by chronic patients according to risk level based on adjusted morbidity groups (AMG) and to analyze the associated factors.

Methods

Cross-sectional descriptive observational study. Patients from a basic health area classified as chronically ill by the AMG classification system of the Madrid PC electronic medical record were included. Sociodemographic, clinical-care characteristics (classified as predisposing factors or need factors) and service utilization variables were collected. Univariate, bivariate and simple linear regression analyses were performed.

Results

The sample consisted of 9866 chronic patients and 8332 (84.4%) used health services. Of these service users, 63% were women, mean age was 55.7 (SD = 20.8), 439 (5.3%) were high risk, 1746 (21.2%) were medium risk, and 6041(73.4%) were low risk. A total of 8226 (98.7%) were PC users, and 4284 (51.4%) were HC users. The average number of annual contacts with PC was 13.9 (SD = 15); the average number of contacts with HC was 4.8 (SD = 6.2). Predisposing factors associated with services utilization at both care levels were: age (B coefficient [BC] = 0.03 and 0.018, 95% CI = 0.017–0.052 and 0.008–0.028, respectively, for PC and HC) and Spanish origin (BC = 0.962 and 3.396, 95% CI = 0.198–1.726 and 2.722–4.070); need factors included: palliative care (BC = 10,492 and 5047; 95% CI = 6457–14,526 and 3098-6995), high risk (BC = 4631 and 2730, 95% CI = 3022–6241 and 1.949–3.512), number of chronic diseases (BC = 1.291 and 0.222, 95% CI = 1.068–1.51 and 0.103–0.341) and neoplasms (BC = 2.989 and 4.309, 95% CI = 1.659–4.319 and 3.629–4.989).

Conclusions

The characteristics and PC and HC service utilization of chronic patients were different and varied according to their AMG risk level. There was greater use of PC services than HC services, although utilization of both levels of care was high. Service use was related to predisposing factors such as age and country of origin and, above all, to need factors such as immobility, high risk, and number and type of chronic diseases that require follow-up and palliative care.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12913-021-07020-z.

Care consumption of people with multiple sclerosis: A multichannel sequence analysis in a population-based setting in British Columbia, Canada

BACKGROUND

Persons with multiple sclerosis (PwMS) typically require complex multidisciplinary care, which is rarely formally assessed.

OBJECTIVES

We applied multichannel sequence analysis (MCSA) to identify care consumption patterns by PwMS in British Columbia, Canada.

METHODS

We created two cohorts, comprising incident and prevalent MS cases, using linked clinical and administrative data. We applied MCSA to quantify and compare the care pathways of PwMS, based on all-cause hospitalizations and physician visits (divided into five specialities). Care consumption clusters were characterized using demographic and clinical features.

RESULTS

From 1048 incident and 3180 prevalent PwMS, the MCSA identified 12 and 6 distinct care consumption clusters over a median follow-up of 9.6 and 13.0 years, respectively. Large disparities between clusters were observed; the median number of annual consultations ranged from 5.6 to 21.3 for general practitioners, 1.2 to 4.6 for neurologists and 0 to 5.3 for psychiatrists in the incident cohort. Characteristics at MS symptom onset associated with the highest care consumption included high comorbidity burden and older age. There were similar disparities and associations for prevalent PwMS.

CONCLUSION

The distinct patterns of care consumption, which were reminiscent of the heterogeneity of MS itself, may facilitate health service planning and evaluation, and provide a novel outcome measure in health research.

Examining longitudinal patterns of individual neighborhood deprivation trajectories in the province of Quebec: A sequence analysis application

Exposure to neighborhood deprivation has been associated with a number of health, behavioral and sociological outcomes. However, many negative outcomes associated with deprivation have a long latency and may be influenced by varying exposure to neighborhoods throughout time. Capturing the longitudinal exposure to neighborhood deprivation is methodologically complex when one wishes to include life course notions of order, duration and timing. In a sample of 60,555 participants, aged 12 years and older (representative of the population of the Province of Quebec in Canada) our objectives were to: 1) Create an indicator for neighborhood deprivation trajectories; 2) compare trajectories with cross-sectional and cumulative neighborhood deprivation; 3) identify individual socioeconomic determinants of membership to a trajectory cluster. Using sequence analysis based on optimal matching and clustering around theoretical types, we grouped sequences in nine neighborhood deprivation trajectory clusters. We found that half (50%) of the participants were in a stable trajectory and did not transition significantly from one deprivation tertile to another during their sequence. A comparison between a cross-sectional indicator of neighborhood deprivation and the trajectories showed that only 42.2% of the participants had a cross-sectional deprivation at the index date representative of their whole trajectory. We also found, using logistic regression (adjusted for age, sex, number of residential moves) that having no high school diploma, living in a rural area and being an immigrant was strongly associated with a deprived stable trajectory. Sequence analysis is an effective tool to describe neighborhood deprivation trajectories in a sample representative of the Quebec population. Trajectories are a useful addition to a better understanding of the distribution of health outcomes because they provide information about the order and accumulation of longitudinal exposures to neighborhood and seem to be associated with specific individual socioeconomic characteristics such as education, urbanity, and immigration status.

A new mixed-ligand coordination polymer: protective activity on influenza a virus-induced COPD via regulating tlr3 gene expression on alveolar epithelial cells

A new Cu(II) coordination polymer (CP) of [Cu₅(µ₃-OH)₂(bcpt)₄(bib)₂] (1, bib = 1,4-bis(1-imidazoly)benzene and H₂bcpt = 3,5-bis(3'-carboxyphenyl)-1,2,4-triazole) was synthesized by reaction of Cu(NO₃)₂·3H₂O reacting with 3,5-bis(3'-carboxyphenyl)-1,2,4-triazole in the existence of 1,4-bis(1-imidazoly)benzene as the second ligand. The treatment activity of the compound on influenza A virus induced chronic obstructive pulmonary disease (COPD) was evaluated. First, the biological function of the lung was assessed by measuring the partial pressure for the carbon dioxide (PaCO₂) and oxygen (PaO₂) via the analysis of blood gas. Next, the inflammatory cytokines released by alveolar epithelial cells were determined via the ELISA test kit. In addition to this, the real-time RT-PCR was carried out to determine the inflammatory response relative expression in the alveolar epithelial cells. Finally, the relative expression of the TLR3 on the alveolar epithelial cells was revealed by western blot. Possible binding patterns were acquired from the post scoring software and molecular docking, which exhibited two possible functional side chain binding sites of TLR3 to compounds binding, possibly offering distinct regulatory mechanisms.

Trajectory Modelling Techniques Useful to Epidemiological Research: A Comparative Narrative Review of Approaches

Trajectory modelling techniques have been developed to determine subgroups within a given population and are increasingly used to better understand intra- and inter-individual variability in health outcome patterns over time. The objectives of this narrative review are to explore various trajectory modelling approaches useful to epidemiological research and give an overview of their applications and differences. Guidance for reporting on the results of trajectory modelling is also covered. Trajectory modelling techniques reviewed include latent class modelling approaches, ie, growth mixture modelling (GMM), group-based trajectory modelling (GBTM), latent class analysis (LCA), and latent transition analysis (LTA). A parallel is drawn to other individual-centered statistical approaches such as cluster analysis (CA) and sequence analysis (SA). Depending on the research question and type of data, a number of approaches can be used for trajectory modelling of health outcomes measured in longitudinal studies. However, the various terms to designate latent class modelling approaches (GMM, GBTM, LTA, LCA) are used inconsistently and often interchangeably in the available scientific literature. Improved consistency in the terminology and reporting guidelines have the potential to increase researchers' efficiency when it comes to choosing the most appropriate technique that best suits their research questions.