Understanding Pathways into Care-homes using Data (UnPiCD study): a two-part model to estimate inpatient and care-home costs using national linked health and social care data

BACKGROUND

Pathways into care-homes have been under-researched. Individuals who move-in to a care-home from hospital are clinically distinct from those moving-in from the community. However, it remains unclear whether the source of care-home admission has any implications in term of costs. Our aim was to quantify hospital and care-home costs for individuals newly moving-in to care homes to compare those moving-in from hospital to those moving-in from the community.

METHODS

Using routinely-collected national social care and health data we constructed a cohort including people moving into care-homes from hospital and community settings between 01/04/2013-31/03/2015 based on records from the Scottish Care-Home Census (SCHC). Individual-level data were obtained from Scottish Morbidity Records (SMR01/04/50) and death records from National Records of Scotland (NRS). Unit costs were identified from NHS Scotland costs data and care-home costs from the SCHC. We used a two-part model to estimate costs conditional on having incurred positive costs. Additional analyses estimated differences in costs for the one-year period preceding and following care-home admission.

RESULTS

We included 14,877 individuals moving-in to a care-home, 8,472 (57%) from hospital, and 6,405 (43%) from the community. Individuals moving-in to care-homes from the community incurred higher costs at £27,117 (95% CI £ 26,641 to £ 27,594) than those moving-in from hospital with £24,426 (95% CI £ 24,037 to £ 24,814). Hospital costs incurred during the year preceding care-home admission were substantially higher (£8,323 (95% CI£8,168 to £8,477) compared to those incurred after moving-in to care-home (£1,670 (95% CI£1,591 to £1,750).

CONCLUSION

Individuals moving-in from hospital and community have different needs, and this is reflected in the difference in costs incurred. The reduction in hospital costs in the year after moving-in to a care-home indicates the positive contribution of care-home residency in supporting those with complex needs. These data provide an important contribution to inform capacity planning on care provision for adults with complex needs and the costs of care provision.

1344 UNDERSTANDING PATHWAYS INTO CARE HOMES USING DATA (THE UNPICD STUDY)

Introduction

Moving into a care home is a significant, life-changing experience which occurs to address care needs which cannot be supported elsewhere. UK health policy recommends against moving into a care home from the acute hospital. However, this occurs in practice. Better understanding pathways into care homes could improve support for individuals and families, service planning and policymaking. Our aim was to characterise individuals who move-in to a care home from hospital and those moving-in from the community, identifying factors associated with moving-in from hospital.

Method

A retrospective observational cohort study was conducted involving adults moving into care homes in Scotland between 1/3/13-31/3/16 using the Scottish Care Home Census (SCHC), a national individual-level social care dataset. SCHC data were linked to routine data sources including hospital admissions, community prescribing and mortality. The data were split into those moving-in from hospital and those moving-in from the community. Descriptive statistics characterising the two groups were generated and multivariate regression undertaken to identify factors associated with moving-in from hospital.

Results

A total of 23,892 individuals were included in the analysis, of whom 13,564 (56.8%) moved-in from hospital. A third came directly from an acute hospital, with 57.7% from rehabilitation or community hospitals and 7.1% from inpatient psychiatry. Being male, receiving nursing care, high frailty risk, increasing numbers of hospital admissions and diagnoses of any fracture or stroke in the six months before moving-into the care home were all significant predictors of moving-in from hospital.

Conclusions

The population moving-in to care homes from hospital are clinical distinct from those moving-in from the community. National cross-sectoral data linkage of health and social care data is feasible, but the available data are dominated by health characteristics. There is an urgent need to operationalise other meaningful variables which shape care pathways to enhance understanding and evidence.

Atrial fibrillation and stroke outcomes in Scotland: real-world evidence from a contemporary, national dataset

Introduction

Atrial Fibrillation (AF) is an important cause of mortality and morbidity. The major risk of AF is stroke, which can be reduced through anticoagulation. The burden of stroke, and AF-related stroke, is particularly high in Scotland. It is often reported that AF-related stroke is associated with poorer outcomes than other stroke types, it is also thought to lead to an increased institutionalisation. Data supporting these observations are historic, but major advances in AF assessment and treatment could have changed outcome patterns. Real world evidence on outcomes, collected at scale, can give a useful measure of contemporary AF stroke outcomes.

Purpose

To assess whether stroke patients, with and without AF on admission, differ in terms of al-cause mortality, recurrence of stroke, and care home admission using contemporary large-scale observational data.

Methods

A retrospective cohort study linking national hospital, prescribing, care home and stroke audit data was conducted. The cohort, comprising patients ≥18 years of age with incident ischemic stroke between 2009 and 2017, was divided into three groups: AF-related stroke prescribed oral anticoagulant (OAC) pre-stroke event (AF-OAC Group); AF-related stroke not prescribed anticoagulant pre-stroke event (AF-noOAC Group); stroke with no prevalent or incident AF and no anticoagulation (comparator) (noAF-noOAC Group). Time-to-event analyses (adjusted for demographic and clinical characteristics) were conducted to estimate hazard ratios for recurrent stroke, all-cause mortality, and care-home admission with a follow-up time of two years.

Results

From a cohort of 64,159 incident ischemic strokes, 4,418 and 15,124 patients with AF were identified for groups AF-OAC and AF-noOAC, respectively. The remaining 44,617 patients belonged to group noAF-noOAC. An increasing number of incident strokes was observed with increasing age in each group up to 80–84 years. The risk of recurrent stroke was significantly greater in groups AF-OAC (HR 1.12 [95% CI 1.08,1.17]) and AF-noOAC (HR 1.05 [95% CI 1.03,1.08]) compared to noAF-noOAC group. An increased risk of all-cause mortality was observed in groups AF-OAC (HR 1.52 [95% CI 1.39,1.66]) and AF-noOAC (HR 1.59 [95% CI 1.51,1.68]) compared to the noAF-noOAC group. Patients in group AF-noOAC were more likely to be discharged to a care home following stroke (HR 1.37 [95% CI 1.23,1.52]) compared to patients in the other groups.

Conclusion

AF-related stroke is associated with poor outcomes, with significantly higher risks of recurrent stroke and all-cause mortality for patients with AF compared to non-AF stroke. Despite advances in AF care, our data suggest there is still potential to prevent a substantial proportion of disabling strokes through better identification and treatment of AF. These results must be interpreted with caution, as data take no account of treatment adherence, dosing or rationale for individual patient level prescribing decisions.

Funding Acknowledgement

Type of funding source: Private company. Main funding source(s): Bristol-Myers Squibb Research and Development