Care Transitions for People with Acquired Neurological Disability in the First 12 Months following Inpatient Rehabilitation: Health Service Use and Obstacles

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Introduction
Acquired neurological disability resulting from acquired brain injury (ABI) or spinal cord injury (SCI) has a substantial impact on individuals, their families, the health system, and broader society [1,2].Te often-protracted rehabilitation and recovery period for individuals with acquired neurological disability occurs within a complex mix of transitions between various services and providers [3].
Te focus of research is often on transitions during acute admissions and at discharge [3,4].However, the early postdischarge period is equally signifcant as people with acquired neurological disability will transition through many systems and providers due to their complex and fuctuating needs, infuencing recovery trajectories and access to health services [5,6].
Tere is no single, uniformly accepted defnition of care transitions.Te World Health Organization [7] defnes care transitions as "the various points where a patient moves to, or returns from, a particular physical location or makes contact with a health care professional for the purpose of receiving health care."Te Australian Commission on Safety and Quality in Health Care refers to care transitions as occurring within and between healthcare locations, settings, care delivery types, and levels of care, involving a range of care providers [8].Previous research has focused on single or certain types of transitions such as hospital to home [9][10][11][12], but there is less understanding of the multiple transition patterns involving access to services across diferent levels of health care following hospital discharge [13].A previous study, in an elderly cohort, investigated number and patterns of transitions between acute, postacute, and long-term care use, the frequency of emergency room visits, and other health care utilization patterns that could indicate transition problems [14].However, the larger knowledge gap hampers the development of both high-quality postdischarge service systems and integrated, person-centred pathways for people with complex needs [15][16][17][18].
People with acquired neurological disability leaving inpatient rehabilitation in Australia, as in many countries, frequently use various follow-up services across diferent healthcare settings [19].Australia's health system consists of publicly and privately funded services, with citizens primarily relying on Medicare, a universal public health insurance system, for accessing hospital and health professional services.Medicare entitles all citizens to free or low-cost access to public hospitals, medical services, and limited allied health services [20].Private health insurance is available to those who can aford it and helps cover the cost of private hospital services and community-based healthcare, including allied health services.Beyond the healthcare system, various lifetime care systems provide access to individualised care and supports for eligible people.Te National Disability Insurance Scheme (NDIS) provides individualised funded supports for personal care, aids, and equipment and housing needs for people with acquired neurological disability [21].Most Australian states also operate lifetime care and support schemes (e.g., National Injury Insurance Scheme in Queensland, NIISQ), for people who sustain serious injuries through motor vehicle or workrelated events [22].
Hospital readmissions and emergency department visits are not uncommon for people with neurological disability [23][24][25].Patterns of care transitions involving emergency care are especially noteworthy as they may highlight gaps in care transition processes [26,27].For example, inappropriate emergency care may indicate poorly coordinated transitions and limited access to primary health services [28][29][30].
Obstacles to service access for people with acquired neurological disability in the postdischarge period are relatively well understood [31][32][33][34] and are known contributors to complicated care transitions and access disparities [34][35][36][37].Of note, despite the criticality of ongoing therapies for people with acquired neurological disability, challenges in accessing allied health services have been repeatedly described [35,38].However, the impact of obstacles and service access difculties in the early postdischarge period on long-term care transitions in people with ABI and SCI remains unexplored.
To ensure seamless transitions and timely service access for people with ABI and SCI, a comprehensive system-wide picture of the postdischarge period must be established.Moreover, there is a need for greater research focus on the pattern of care transitions in the frst 12 months postdischarge due to periods' importance to the individuals' future rehabilitation and recovery trajectory.As such, this study aimed to (1) map and examine system-level care transitions including patterns of transitions and service use among people with ABI and SCI during the frst 12 months postdischarge from inpatient rehabilitation and (2) explore the relationship between early perceptions (3 months postdischarge) of obstacles and difculty with health service access to the pattern of care transitions.[39] investigating service access and wellbeing after ABI and SCI.Ethical approval was granted by the relevant Hospital (HREC/2019/QMS/50271) and University Human Research Ethics Committees (2019/ 456).All participants or their substitute decision makers provided written informed consent before study involvement.

Participants and Setting.
From July 2019 to March 2020, participants with a primary diagnosis of ABI or SCI were recruited from a tertiary health care centre in Queensland, Australia.Te centre hosts SCI and ABI specialist services, including inpatient, outpatient, transitional rehabilitation, and community outreach services.Participants were eligible if they (1) had a new diagnosis of SCI or ABI; (2) were aged ≥18 years; and (3) had the ability to provide informed consent or consent via a substitute decision maker.Exclusion criteria were (1) short-term visitors to Australia unavailable for follow-up and (2) health service use data unavailable from any of the required datasets.

System-Level Care
Transitions.In this study, care transitions were considered at a system level across three levels of care: primary health care (community-based), specialist health care (hospital or community-based specialist services), and emergency care (emergency services) (Figure 1).Transitions of care directly from one health service to another within the same level of care (i.e., between a primary care general practitioner (GP) and a primary care allied health professional) were not countered as separate care transitions.Tis transition categorisation of levels of care into primary, specialist, and emergency was chosen to enable distinct examination of aspects of the health care 2 Health & Social Care in the Community system most relevant to people with ABI and SCI.It also enabled emergency care to be considered independently from other planned admissions which were included in the specialist health care category (Figure 1).Tis categorisation was also facilitated by the composition of the Medicare Benefts Scheme (MBS) and Queensland Health datasets.

Data Linkage for Care Transitions and Health Service
Use. Te data linkage framework for the study was designed to cover specialist and mainstream health service use in the 12 months postdischarge from inpatient rehabilitation and included MBS data, Queensland Health datasets, and local electronic medical records (EMRs).Data linkage methods were used to capture care transition patterns and health services accessed during transitions.Te local EMRs were used to describe the cohort and identify characteristics of inpatient rehabilitation and discharge.Primary health care use was obtained through the MBS data collection [40], based on participants' unique IDs, which were provided to the data custodian.GP visits, and nursing and allied health services were fundamental, with other MBS items, such as diagnostic procedures, investigations, pathology, and therapeutic procedures, not included as they were reasons for service contacts or interventions rather than service use categories.Specialist health care use was recorded using the Queensland Hospital Admitted Patient Data Collection and Queensland Health Nonadmitted Patient Data Collection, accessed through the Statistic Services Branch (SSB), Queensland Health [41].Data linkage of Queensland Health data sets was performed by the SSB.Both deterministic and probabilistic methods of linking records are used, with clerical review used to manually inspect the "grey area" of uncertain matches in probabilistic linkage.Events were considered specialist care if they were (1) day admissions at public or private hospitals or day surgery units; (2) planned hospitalisations; or (3) nonadmitted, outpatient attendances for medical specialists or allied health services, care coordination, and other services, such as ftting of aids and appliances or wound management.Emergency care use was sourced from the Emergency Data Collection, also part of the SSB data collection and linkage process.Emergency care events included those resulting in physician consultation and discharge within 4 hours, short-stay events (4-24 hours), and unplanned hospitalizations (≥1 overnight stay) (Figure 1).employment status at time of injury.Injury-related variables included diagnosis (i.e., ABI and SCI), aetiology (i.e., nontraumatic and traumatic), and Functional Independence Measure (FIM) at discharge.Discharge variables were also recorded, including discharge destination, transportation independence at 3 months, and funding arrangement at discharge.As some participants were discharged following the start of the COVID-19 pandemic, discharge after the date of hospital-wide pandemic-related service closures (29 January 2020) was also recorded.Tis was considered as a potential confounding factor for the relationship between obstacles and difculty accessing health services and care transitions.

Survey
(1) Perception of Obstacles to Health Service Access.Participants' perceived obstacles to health service access in relation to transportation, fnance, and resource availability were assessed at 3 months postdischarge using the Service Obstacles Scale [42].Te scale comprises six items with three subscales: transportation as an obstacle (1 item), fnance as an obstacle (1 item), and satisfaction with treatment resources (4 items).Participants rated each item, from 1 (strongly disagree) to 7 (strongly agree).Transportation and fnance obstacles scores range from 1 to 7, while satisfaction with treatment resources ranges from 4 to 28.Higher scores indicate greater agreement that transportation and fnance are obstacles and lower satisfaction with treatment resource availability.In the current sample, internal consistency of treatment satisfaction was adequate (α � 0.71, 95% CI � 0.58 to 0.80).
(2) Perceived Difculty Accessing Health Services.Perceived difculty accessing health services and support was measured at 3 months postdischarge using the modifed Care Access Scale [43].Participants rated their access to healthcare and support when unwell on a scale of 1 (strongly disagree) to 5 (strongly agree).Te scale comprised six items measuring access frequency (i.e., "I don't always access healthcare and support when I should" and "Sometimes I feel unwell for a while before I access healthcare and support").A care access score was calculated by averaging the six scale items, ranging from 1 to 5, with higher scores indicating greater difculty accessing healthcare services and supports [43].Te Care Access Scale demonstrated good internal consistency in the current sample (α � 0.81; 95% CI � 0.73 to 0.87).

Data Analysis. Data were analyzed using R Statistical
Software version 4.2.0 [44].All measured variables were not normally distributed based on the Shapiro-Wilk test and visual inspection of histograms.Terefore, median (interquartile ranges) or frequency (%) was presented.Potential sample bias was explored by comparing the characteristics of participants with and without missing questionnaire data.Complete case data with no imputation of missing values were used for all analyses.
For the relationship between the number of care transitions (dependent variable) and care access, transportation obstacles, fnance obstacles, and satisfaction with treatment resources at 3 months postdischarge (independent variables), multivariate negative binomial regression was used due to overdispersion and lack of Poisson distribution in the data [45].Prescreening of independent variables and theoretically relevant covariates (age, sex, relationship status, education, diagnosis, traumatic nature of the injury, FIM scores at discharge, types of insurance funding at discharge, and discharge after COVID-19 related service closures) was performed using Spearman correlation matrix and univariate regression analysis.Variables with a p value <0.25 [46,47] in the univariate regression were selected for the fnal regression model.Two fnal models were built, one with and one without covariates.Key assumptions of the fnal models were checked, including the distribution of dependent variables, linearity of independent variables, independence of observations, and detection of outliers and infuential observations.Multicollinearity was assessed using a variance infation factor of <5.[48].
Care transition patterns were categorised based on the combination of diferent levels of care accessed at least once, that is, primary only, specialist only, primary-emergency, specialist-emergency, primary-specialist, and primary-specialist-emergency.No participants accessed emergency level care only.Hierarchical logistic regression was used to examine the relationship of the pattern of care transition involving emergency care (binary independent variable: yes/ no) to care access, transportation obstacles, fnance obstacles, and satisfaction with treatment resources at 3 months postdischarge (independent variables).Te prescreening process for independent variables and covariates, as well as the validation of logistic regression assumptions, followed the same approach as the negative binomial regression.Two models were built: frst with the selected covariates and the second included the selected covariates and independent variables.Regression analyses could not be conducted with the care transitions patterns that included primary or specialist care as dependent variables due to nearly universal involvement of primary or specialist care in participants' transitions.Odds ratios (ORs), coefcients, 95% confdence intervals (CIs), and p values were reported, with a statistically signifcant level set at 0.05.

Results
Ninety-three participants (56% SCI) with available health service data were included in this study, with 73 (78.5%) completing the survey (Figure 2).Characteristics of participants with and without missing survey data were largely comparable; however, those with missing survey data had less than half the number of care transitions (3.5 versus 9) compared to those with complete survey data Table 1.Sociodemographic, injury, and discharge related data for included participants are presented in Table 2.

Care Transitions and Health Service Use during
Transitions.Te median number of care transitions in the 12 months postdischarge was eight, with an interquartile range of 3-12 (Figure 3).Only three (3.2%)participants did not have any care transitions, while most participants (74.2%) experienced more than 3 transitions (Figure 3).A small number of participants (9.7%) had greater than 19 care transitions over the 12-month period with the maximum number being 47.Based on the level of care that participants accessed at least once in the frst 12 months, six major categories of care transition patterns were identifed (Figure 4).Te most frequent category of care transition (n � 51/93, 54.8%) was where care transitions occurred between all three levels: primary-specialist-emergency.Te second most frequent category (n � 35/93, 37.6%) was the primary-specialist pattern.Within each broad category of care transition, there was considerable variability amongst participants in terms of frequency, direction, and sequence of transitions (Figures 5(a Almost all participants had accessed various primary (96%) and specialist (97%) health services during the 12months postdischarge, with GPs and medical specialist's outpatient consultations being the most common in their respective categories (Table 3).Allied health services were the next most common in both categories.A planned hospital admission occurred for 13% of participants.Fiftynine percent of participants used the various types of emergency services with 26% requiring a hospital admission for greater than 24 hours (Table 3).

Relationship between Care Transitions and Service
Obstacles and Access.Te rating of difculty accessing health services at 3 months was low, with the median (interquartile range) being 1.6 (1.2-2.0).Te median (interquartile range) rating for transportation obstacles at 3 months was 3.0 (2.0-6.0), with 42.2% of participants agreeing that transportation was an obstacle to health service access.Similarly, the median (interquartile range) rating for fnance obstacles at 3 months was 3.0 (2.0-5.0), with 33.3% of participants agreeing that fnance was an obstacle to health service access.Te median (interquartile range) rating for satisfaction with treatment resources at 3 months was 12.0 (9.0-16.0).
Te spearman correlation matrix showed small to medium, positive, and signifcant correlations between fnance obstacles and transportation obstacles and satisfaction with treatment resources at 3 months (Table 4).Tere were no collinearity concerns for the continuous independent variables and potential covariates (Table 4).Based on the results of univariate regression analyses, transportation obstacles, fnance obstacles, and satisfaction with treatment resources at 3 months were selected as independent variables while age, discharge after COVID-19 related service closures, and NIISQ funding were selected as covariates for the negative binomial regression analyses with frequency of care transitions as the dependent variable.For the hierarchical logistic regression with care transition patterns that included emergency care as the dependent variable, transportation obstacles at 3 months were selected as the independent variable and injury type, FIM at discharge, and NDIS funding as covariates.
Univariate regression analyses indicated that both transportation and fnance obstacles and satisfaction with treatment resources at 3 months were signifcantly Health & Social Care in the Community associated with greater care transitions over 12 months (Table 5).However, in the multivariate analysis, only transportation obstacles at 3 months was found to be a marginally signifcant contributor (p � 0.051) to the number of care transitions over the 12 months after adjusting for age, discharge after COVID-19 related service closures, and NIISQ funding (Table 6).For the hierarchical logistic regression for care transitions that included emergency care, while there was a signifcant association with transportation as an obstacle in the univariate regression analysis (Table 5), after adjusting for injury type and FIM at discharge, no signifcant association was found (Table 7).

Discussion
Tis exploratory study is the frst to examine system-level care transitions for people living with acquired neurological disability resulting from ABI or SCI in the frst 12 months following acute inpatient rehabilitation.As a further novel aim, we examined relationships between early perception of  obstacles and difculty accessing health services and the pattern of care transitions.By elucidating the diversity of transitions and health service use, this study provides a valuable starting point to refect on the complexity of care transitions for people with ABI and SCI, but more importantly the potential treatment burden [49] that they experience due to interactions with multiple systems and services.
Te study fndings highlight that while there were six major categories of care transition patterns that people with SCI and ABI experience during the frst 12 months postdischarge, and within those broad categories, participants experienced considerable diversity and complexity in the frequency, direction, and sequence of transitions between the primary, specialist, and emergency care levels.Tis fnding aligns with previous research reporting highly varied care transition patterns among people with complex needs [15,50], including people with ABI during the frst 6 months after injury [51].Although multiple transitions may be indicative of the heterogeneity of needs associated with neurological disability [52,53], nonetheless, this picture warrants further consideration of the nature of transitions and how these might afect recovery and outcomes.For example, more transitions can increase the likelihood of   adverse events [54,55], contribute to suboptimal or fragmented care [56], and undermine person-centred pathways.Tese impacts may be exacerbated if systems themselves are segmented and convoluted as the Australian health care system arguably is.It operates on a complicated mix of public and private funding and discrete programs, with responsibilities for hospital, primary, and community care divided between diferent levels of government, all of which contribute to fragmented systems of care [57].Consequently, lack of coordination between various systems is commonplace for people with complex needs, particularly regarding referral and transitions, and can contribute to failures in access [58].In this context, the diversity and complexity of care transitions for people with ABI and SCI identifed in this study may indicate a need to design more seamless, personalised pathways that optimise rehabilitation and recovery trajectories.
Te study also found that early perceptions of transportation being an obstacle to accessing health services may be a factor contributing to more care transitions over the 12 months postdischarge.Transportation is a well-known determinant of access and transport obstacles are common in people with complex needs [59].Only 14% of participants in this study were able to drive independently 3 months after discharge from inpatient rehabilitation, which is consistent with previous research [35].Tese people may also vary in their level of caregiver support regarding transport [60].Transportation barriers are known to contribute to increased difculty with health service access [61] and may result in missed opportunities for early management of secondary conditions [62] or delayed progression of rehabilitation programs within the frst 3 months postdischarge, which in turn may result in more care transitions being required by the end of the frst 12 months postdischarge for people with ABI or SCI.However, it is important to note that transportation obstacles was measured by a single item and the association between early perception of transportation obstacles and increased care transitions was only marginally signifcant in the multivariate regression analysis.Hence, caution is needed in interpreting this fnding, particularly given the modest sample size.In addition, due to the diversity of the population studied and because transportation and other obstacles and their impacts are likely to be highly individual, further research is required to understand the nature of transportation obstacles and how they might infuence transitions.
Our fndings also provide insight into the possible systemic burden of treatment experienced by people with acquired neurological disability.Burden of treatment is the workload of healthcare and its efect on patient functioning and wellbeing.While the systemic burden of the disabling or chronic condition itself is often a focus of research, limited attention has been paid to the associated systemic treatment burden [63].Although treatment burden was not directly measured in this study, the number of care transitions experienced and health services used by participants in the frst      12 months after discharge reveal something of the early workload associated with the rehabilitation and recovery trajectory for people with ABI and SCI.Furthermore, previous research [64] supports the fnding that obstacles such as transport may contribute to greater care transitions, potentially increasing the systemic treatment burden for participants.As such, these fndings provide a springboard to better understand and measure the burden imposed by treatment regimens and systems on people with complex needs as a measure of quality of care [65].More could be learnt through future research combining qualitative accounts of personal experiences with more detailed mapping of transitions.Te fnding of many varied and complex care transitions may have implications when considering the development of future care transition interventions for people with acquired neurological disability.Future strategies could entail more comprehensive, personalised approaches to assist people navigating care transitions and overcoming obstacles to access.Furthermore, given the ongoing health and support needs of people with neurological disability, coordination between health and disability services could be strengthened, for example, by providing designated support coordination within the health system or through the NDIS for those who are eligible [66].
Person-centred care approaches, tailoring treatment to individual needs and providing personalized monitoring of developing issues and changing goals, are well established as central to efective rehabilitation and are already employed by many rehabilitation services.Approaches which support more comprehensive "personalised rehabilitation pathways" to enhance care transitions include utilisation of case management [67][68][69], care navigators [70,71], integrated care models [72,73], self-management approaches [74,75], improved resourcing [67,70], improved communication including (patient controlled) EMR [71,76], and person and family-engaged approaches [77,78].Further studies are needed to examine the best strategies or models for implementing more personalised rehabilitation pathways for people with SCI and ABI.
Tis study had several limitations.First, an a priori sample size calculation was not conducted as the primary objective of this study was to describe postdischarge care transition pathways.Te sample size is relatively modest for multivariate negative binomial or logistic regression analysis.Second, participants with fewer care transitions had more missing data particularly regarding completion of the care access and service obstacles components of the survey at 3 months postdischarge, suggesting lower engagement in the study and potentially limiting generalisability of the results.Tird, not all possible types and features of care transitions could be evaluated due to required data not being available as part of the data collection and linkage.Tis included care transitions to and from the community-based rehabilitation components of the specialist SCI and ABI services and the impact of readmissions to hospital on total number and pattern of care transitions.Fourth, although care transitions were characterised, it is unclear whether these care transitions were appropriate transitions or not.Assessment of the appropriateness of timing of care transitions may have important implications for future interventions and system improvement [51].Finally, fnancial and transportation obstacles were assessed only using a single item, which may not have fully captured all aspects of these barriers.

Conclusion
Tis study found that within six overarching categories, postdischarge system-level care transition patterns were diverse and complex for people with acquired neurological disability.Transport as an obstacle to service access may be contributed to increased transitions in the frst 12 months following discharge.While the heterogeneity of postdischarge needs may necessitate diverse care transitions and access to varied health services, the critical issue is to ensure these are personalised to individual need and that systems are performing optimally for the beneft of people with acquired neurological disability.Further research is needed to comprehensively document the characteristics and complications of care transitions for people with SCI and ABI, across the health and social service systems and how these relate to meaningful access and health outcomes.

Figure 1 :
Figure 1: Diagrammatic representation of the 3 levels of health care (rectangles), services accessed within each level of care (circles), and broad care transition pathways (arrows).

Figure 3 :
Figure 3: Proportions of participants by the frequency of care transitions in the frst 12 months postdischarge.

Figure 5 :
Figure 5: (a) Plots of care transitions, grouped by transition pattern category, in the frst 12 months postdischarge.(b) Plots of the primaryspecialist-emergency care transition pattern in the frst 12 months postdischarge.
Tis exploratory study involved survey and data linkage methods and was part of a broader research program: the Trajectories of Rehabilitation across Complex Environments (TRaCE) study 2.1.Research Design.

Table 1 :
Comparisons between participants with and without missing survey data in sociodemographic, injury, and discharge related variables, and number of health service use.

Table 3 :
Primary, specialist, and emergency health care use during the frst 12 months postdischarge.Note.A Data reported for people who used services and does not include those who did not use services.B Other includes aids and appliances, midwifery and maternity, wound management, postacute care, telehealth consultations, and respiratory.C Hospital presentations include public and private hospitals.

Table 4 :
Spearman correlation coefcients between potential continuous covariate variables (age, functional independence measure (FIM) at discharge) and independent variables (care access and service obstacles at 3 months).

Table 5 :
Univariate regressions between sociodemographic, injury, and discharge-related factors (potential covariates), care access, and service obstacles at 3 months (dependent variables) and the frequency and pattern of care transitions that included emergency care (use of emergency care) (dependent variables) in the frst 12 months postdischarge.

Table 6 :
Results of the negative binomial regression for the frequency of care transitions in the frst 12 months postdischarge (n �

Table 7 :
Summary of logistic regression models for the type of care transitions that included emergency care in the frst 12 months post-discharge (n � c Variable(s) entered on step 1: diagnosis type (spinal cord injury), FIM at discharge, having national disability insurance scheme funding, and transportation obstacles at