Health service use by patients with heart failure living in a community setting: a cross-sectional analysis in North West London

Dani Kim; Benedict Hayhoe; Paul Aylin; Martin R Cowie; Alex Bottle

doi:10.3399/bjgp20X711749

Abstract

Background The complex nature of heart failure (HF) management, often involving multidimensional care, is widely recognised, but overall health service utilisation by patients with HF has not previously been described.

Aim To describe overall health service use by adults with HF living in a community setting.

Design and setting Cross-sectional analysis of prevalent HF cases from January 2015 to December 2018 using an administrative dataset covering primary and secondary care, and ‘other’ (community, mental health, social care) services in North West London.

Method Healthcare use of each service was described overall and by individual components of secondary care (such as, outpatient appointments), and ‘other’ services (such as, nursing contacts). Usage patterns were identified using k-means cluster analysis, using all distinct contacts for the whole study period, and visualised with a heatmap.

Results A total of 39 301 patients with a prevalent diagnosis of HF between 1 January 2015 and 31 December 2018 were found. Of those, approximately 90% used health services during the study period, most commonly outpatient services, GP consultations, unplanned accident and emergency visits, and community services. Use of cardiology-specific services ranged from around 3% (cardiology-related community care) to around 20% (outpatient cardiology visits). GP consultations decreased by 11% over the study period. Five clusters of patients were identified, each with statistically significantly different care usage patterns and patient characteristics.

Conclusion Patients with HF make heavy but heterogeneous use of services. Relatively low and falling use of GP consultations, and the apparently low uptake of community rehabilitation services by patients with HF, is concerning and suggests challenges in primary care access and integration of care.

INTRODUCTION

Heart failure (HF) affects >900 000 people in the UK¹ and results in significant morbidity and mortality, frequent hospitalisations, and reduced quality of life. Patients with HF are usually older with comorbidities, and may have complex and highly heterogeneous medical and social needs.¹ A multidisciplinary team (MDT) approach is considered the gold standard model for HF management² and is recommended for high-risk patients in the Health and Social Care Act of 2012,³ and other national⁴^–⁶ and international guidelines.⁷^,⁸ Despite this, there is currently little understanding of the nature of HF care beyond the hospital setting in the UK. Therefore, this study aimed to describe overall health and social service use and care usage patterns by patients with HF in North West London (NWL).

METHOD

Data

Whole Systems Integrated Care (WSIC) data were used: a linked de-identified dataset of individual-level patient records of events from primary, secondary, community, mental health, and social care services in NWL, covering >2 million patients across 400 GP practices.⁹^,¹⁰ It has some similarities with primary care-based research databases like Clinical Practice Research Datalink (CPRD) and The Health Improvement Network (THIN),¹¹^,¹² but with the addition of community, mental health, and social care service records.

Definitions

Patient characteristics

Sex, age, ethnicity, deprivation level, comorbidities, care status, blood pressure, body mass index (BMI), and smoking and alcohol drinking statuses were defined using primary care data at the start of each 1-year period, looking back 5 years to retrieve data. Socioeconomic status was based on the 2015 Index of Multiple Deprivation (IMD)¹³ and divided into quintiles (1 = most deprived; 5 = least deprived). Comorbidities were defined as per the Charlson Index in Khan et al,¹⁴ with some extra ones defined by the authors (see Supplementary Table S1 for details).

Health service use

Health service use was described for each cohort using data for that 1-year period. Primary care use was defined as having a consultation with a GP. Secondary care use included emergency admissions, elective admissions, unplanned accident and emergency (A&E) visits, and outpatient visits. Use of ‘other’ health services (community, mental health, and social care services) were described overall and by individual components. Variables in these ‘other’ health service tables were often not in coded form, so contacts were first indexed with keywords (Box 1) arrived at iteratively by manually searching for the most common terms in each table.

Service and component	Index terms
Community
Nursing	nursing
Rehabilitation	rehab^a
Urgent	rapid, acute, urgent, emergency, A&E, unplanned, admit^a, hospital adm^a, inpatient, ambulance
Intermediate	intermediate, CIS
Cardiology	heart, cardi^a, stroke
Diabetes	diabet^a, endocri^a
Physio- or occupational therapy	occupation^a, physio^a
Podiatry	foot, pod^a
Respiratory	pulmon^a, respir^a, COPD, TB, tubercul^a, thorac^a
Neurology	musculo^a, MSK, neuro^a, parkinson^a
Urinary	genito^a, bladder, bowel, continenc^a, urinary
Speech language therapy	SLT, speech, language
Falls	falls
Diet and nutrition	diet, nutrition^a
Memory and cognition	memory, cognition
Home	home
Phone	phone
Unknown	(none of the above key terms)

Mental health
Outpatient	outpatient, day case
Community	community
Urgent	rapid, acute, urgent, emergency, A&E, unplanned
Specialist	special^a, nurs^a,^aist
Dementia	dementi^a, memory, cogni^a
Learning disability	learning
Eating disorder	eating, anorexi^a
Psychiatric	psy^a
Review	review^a
Consultation	consult^a
Treatment	treat^a
Assessment	assess^a
Unknown	(none of the above key terms)

Social care
Nursing	nursing
Rehabilitation	rehab^a
Urgent	rapid, acute, urgent, emergency, A&E, unplanned
Personal care	personal care, home care, day care, bathing, extra care, reable^a, care service
Food	food, meal
Domestic	domiciliary, domestic, housework, laundry, shopping, cleaning, washing
Transport	transfer, transport, migration, trip, mobil^a
Disability	dis’y, disabilit^a, disable^a
Occupational therapy	occupational therapy
Memory and cognition	dementia, memory, cognition
Assisted equipment technology	assistive tech^a, assisted equipment, equipment, technology
Nursing home	nursing home, residential home, residential care, care home
Mental health	mental, CMHT
Community	community
Social	social
Carer	carer
Housing and living	housing, living
Unknown	(none of the above key terms)^a

↵a Superscript used as a wildcard character during key term search. When used, search returns results containing text preceding ^‘a’. A&E = accident and emergency. CIS = community independence service. CMHT = community mental health team. COPD = chronic obstructive pulmonary disease. HF = heart failure. MSK = musculoskeletal. SLT = speech language therapy. TB = tuberculosis.

Box 1.

Key terms used to index individual components in ‘other’ services to describe the types of services used by patients with HF in respective settings

Heart failure (HF) prevalence is increasing and requires multidisciplinary management, including within primary care. Using a linked database for North West London’s 2.2 million population, this study found that in 39 301 patients with HF, only 60% had seen their GP and 20% had been referred for cardiac rehabilitation during the study period, while overall use of unscheduled care by patients with HF was high, with >40% using accident and emergency services. Findings from cluster analysis, highlighting groups of patients with HF that are particularly high and low users of elements of care, may facilitate active case finding and provision of more supportive and preventative care to improve outcomes for these patients.

How this fits in

Cluster analysis

The authors sought to discover patterns of healthcare utilisation via k-means cluster analysis.¹⁵ Nine healthcare utilisation count variables, reflecting total usage from 2014 to 2018, were used to define clusters: emergency admissions; elective admissions; unplanned A&E visits not ending in admission; outpatient visits (cardiology); outpatient visits (other); GP consultations; and community, mental health, and social care contacts. Only distinct contacts and attended outpatient visits were included, and extreme high users (in the top 0.1% for any of these variables) were excluded.

Data were log-transformed and normalised (min–max method) before analysis to give higher weighting to lower values and equal weighting to all variables, respectively. K-means required the number of clusters (k = 5) to be pre-specified (see Supplementary Box S1 for details).

Statistical analysis

Patient characteristics and prevalence of health service use were summarised for the four yearly cohorts and clusters separately. Usage patterns for each cluster were visualised using a heatmap by comparing the cluster mean usage with the average population usage, taking the percentage difference between these two means.

Differences in healthcare utilisation variables and key patient characteristics across clusters were analysed using Kruskal–Wallis tests for continuous variables and Pearson χ² tests for categorical variables, with two-tailed testing and a significance level of 0.05. All analyses were conducted using R (version 3.4.0).

RESULTS

Patient characteristics

A total of 39 301 patients from 359 GP practices between 1 January 2015 and 31 December 2018 had an HF diagnosis recorded and met the inclusion criteria (see Supplementary Figure S1 for flowchart of study population), that is, approximately 10 new patients with HF per practice per year. The vast majority of patients were in each of the four yearly cohorts.

In 2018, most patients were female (56.2%, n = 19 463), aged ≥65 years (58.1%, n = 20 129), and were of white (31.1%, n = 10 793), Asian (25.7%, n = 8905), or unknown (27.3%, n = 9454) ethnicity (Table 1). Almost two-thirds (63.8%, n = 22 092) had multimorbidity, that is, had a comorbidity in addition to existing HF, and of these more than half had at least two additional comorbidities, most commonly diabetes (26.1%, n = 9053) or hypertension (36.1%, n = 12 507).

View this table:

Table 1.

Patient characteristics for each cohort

A total of 6999 (17.8%) people died and 110 (0.3%) opted out of the WSIC dataset.

Most patient characteristics remained constant during the study period except for an increase in proportion of the underweight (60% increase) and the oldest age group (40% increase), and a nearly 20% reduction in the prevalence of hypertension (Table 1).

Health service use

Approximately 90% of patients used health services during the study period (data not shown). In 2018, the most commonly used healthcare services were outpatients (70.1%, n = 24 283), GP consultations (59.9%, n = 20 741), unplanned A&E (40.8%, n = 14 145), community (39.7%, n = 13 762), emergency admissions (26.7%, n = 9257) and outpatient cardiology (23.8%, n = 8231) services (Table 2). Community care was the most common ‘other’ service used, of which the most frequent components were nursing (23.2%, n = 8052), podiatry (15.6%, n = 5397), and rehabilitation-related services (8.3%, n = 2861). Few (2.9%, n = 1005) used community care related to cardiology even though >1 in 5 had a GP record of referral to cardiac rehabilitation. In total, 6.3% (n = 2178) had a referral for echocardiogram, of which over half had abnormal results (51.1%, n = 1113). Both social care and mental health service use were less common (3.9% and 4.5%, respectively). When used, mental health contacts were commonly community-related (4.3%, n = 1489), suggesting a community integrated approach; social care contacts were personal care (3.1%, n = 1057), community (0.7%, n = 232), domestic (0.7%, n = 253), and disability-related (0.7%, n = 248) (Table 2).

View this table:

Table 2.

Health service ever used by patients with HF in NWL between 2015 and 2018

In 2018, only 3067 (8.9%) patients did not use any services, while around one-quarter used >3 different types (24.8%, n = 8607). Services were most commonly used in combination with secondary care and least commonly with ‘other’ health services (Table 2 and Figure 1). Few patients used only primary care and ‘other’ services (2.3%, n = 781) or ‘other’ services alone (2.0%, n = 682).

Figure 1.

Venn diagram of service use in 2018, showing an approximation of group sizes. An intersection is missing between primary care and ‘other’ services (2.3%) – documentation of R eulerr package states ‘with three or more sets intersecting, exact Euler diagrams are often impossible. For such cases eulerr attempts to provide a good approximation.’¹⁶

Over the study period, health service use increased for all elements of secondary care analysed, particularly elective admissions (37% increase) and outpatient visits (24% increase), but decreased for primary care (11% decrease). Though many components of the community contacts remained constant, there were more than double contacts related to diet and nutrition (Table 2).

Cluster analysis

Altogether 318 patients were excluded from the k-means cluster analysis due to extremely high usage. Of the four and five-cluster solutions identified via preliminary analysis (see Supplementary Box S1), the five-cluster solution was chosen as the extra cluster had distinct usage patterns (Figure 2). Additionally, all patient characteristics differed significantly across clusters (see Supplementary Table S2 and Supplementary Figure S2). Patients who were younger, female, with less comorbidity, and not living in care homes were generally low users of health care (clusters 1 and 2). Perhaps unsurprisingly, those with higher blood pressure and more comorbidities had relatively more GP consultations (cluster 2). Patients who were older, male, and had more comorbidities were generally higher users of health care (clusters 3, 4 and 5). The lowest users of GP appointments were very high users of all other services (cluster 3, Figure 2). Those with the most cardiovascular comorbidity (cluster 4) had the highest usage of cardiology-related outpatient services and referrals to echocardiography (42.0%) (Figure 2). The oldest patients with the highest mortality (cluster 5) were the highest users of emergency inpatient, A&E, and ‘other’ services (Figure 2).

Figure 2.

Heatmap of service utilisation by cluster. Numbers represent percentage difference between cluster mean and population mean values of each health utilisation variable. A&E = accident and emergency.

DISCUSSION

Summary

Overall health service utilisation was high. Almost everyone in the present study population used some kind of health service during the study period: outpatients (7 in 10), primary care (6 in 10 saw a GP), community services, especially nursing (2 in 10), and unplanned A&E visits (4 in 10). Community care use related to cardiology was low. Few patients used only primary care and ‘other’ services, which may reflect modest needs or a lack of community and primary care provision suitable for complex needs.

Patterns of health service utilisation depended on age and comorbidity but were highly heterogeneous. Younger patients with fewer comorbidities (clusters 1 and 2) had the lowest usage, which may partly indicate underutilisation and/or lack of access. For instance, those with infrequent GP consultations (clusters 1 and 3) were also more likely to be of mixed ethnicity and living in areas of higher deprivation and demographics known to be associated with poorer primary care access.¹⁷^,¹⁸ These patients also showed the highest levels of unknown values for patient variables (derived from GP data) and lower than average GP consultation rates, which could reflect both poor health management and low engagement of patients in their own health (they were also more likely to be smokers). The oldest and most likely to live in care homes (cluster 5) had the highest usage of emergency inpatient, A&E, and ‘other’ services, and had high levels of comorbidity, especially renal disease, and the highest mortality. Higher usage of care is expected in older patients with comorbidities,¹⁹^–²¹ but some use might be excessive and avoidable.¹⁹^,²⁰ Health service use was high in the present population of adults with HF living in a community setting. However, overall, relatively low GP service use, which decreased over the study period, and high use of emergency and other unscheduled care in these vulnerable patients is of significant concern and may suggest challenges in access to primary care services. These findings warrant further investigation to ensure equity of access and appropriate integrated care provision for patients with HF.

Strengths and limitations

The authors used a linked dataset with near-complete population coverage for the region and employed both descriptive analysis and clustering algorithms to describe health service use by this highly heterogeneous population. The dataset is large and reflective of current medical practice, but the study has several limitations.

Electronic health records are not specifically intended for research, and coding is highly variable.²² Coding in some of the WSIC tables required additional cleaning and processing, which could introduce bias; however, a transparent coding methodology to mitigate this was provided. Moreover, coded data rely on recorded information, meaning that certain diseases or service components may have been underestimated, for example, cardiac rehabilitation, or that certain primary care data coding may have been affected by pay-for-performance schemes. The authors were unable to ascertain the reasons for the community care or mental health consultations as diagnosis coding was irregular. It is also likely that the fall in GP consultations during the study period was offset by more practice nurse contacts, which were not included in the dataset.

Lastly, though the dataset was based on adults living in a community setting from a large and ethnically diverse area in England, the findings may not be generalisable to the wider population of people with HF.

Comparison with existing literature

Few studies have attempted to quantify individual patterns of care in real-world settings beyond the hospital. Robertson et al described the burden of HF on the Australian healthcare system, but were only able to assess hospitalisation data,²³ as was the case for the present authors’ previous work.²⁴^,²⁵ Similarly, other studies have described a single dimensional aspect of health service use by the population of people with HF.²⁶^,²⁷ The present findings are consistent with these, showing that secondary care use is high,²³ participation in cardiac rehabilitation in the community is low,²⁶^,²⁸ and that requirement for personal care, such as nursing and homecare services, is relatively common.²⁷

An increase over time in most healthcare services use was observed in the present study, especially outpatient visits, but a surprising decrease of 11% in GP consultations. Furthermore, only 60% of patients had GP appointments during the study period, which contrasts with the national GP Patient Survey of 2019,²⁹ where 85% of patients reported having had a GP appointment in the past year. Potential explanations include the increasing workload and workforce pressures on primary care, changes in primary care practice with more frequent contacts with practice nurses and allied health professionals, a significant problem of access to care, and/or differences in case mix.

Another surprising finding is the apparently limited uptake of community cardiac rehabilitation. The National Audit of Cardiac Rehabilitation 2018 report²⁸ suggests that around half of eligible patients take up cardiac rehabilitation. The report did indicate significant regional variation. However, it seems likely that differences in coding of data are responsible for the very low uptake in this analysis; ‘rehabilitation’ events may be recorded elsewhere and currently unavailable in WSIC, and ‘community cardiology’ may also include HF nurse domiciliary care.

The authors further report low use of mental health and social care services by patients with HF, but whether this observed level is appropriate is unclear without further assessment.

Implications for research and practice

The present finding of increased secondary and urgent care service use, low GP appointment use, and apparently limited cardiac rehabilitation is of concern and suggests a lack of multidisciplinary HF care. National Institute for Health and Care Excellence guidelines recommend an MDT approach, but there is no standard definition besides who should be involved and what should be achieved.¹ Each local area has unique challenges and requires tailored solutions; research is needed to establish the nature, location, timing, and intensity of the support needed by patients with HF. In an ethnically diverse area with a relatively young population like NWL, where deprivation level and ethnicity may affect a person’s access to health care, creating a strong MDT embedded in primary care may be very pertinent. For example, practice nurses may target recently diagnosed patients in primary care, that is, younger patients with fewer comorbidities, on early education and management, which may include additional telephone and/or specialist community support for those with lower socioeconomic status. This, in conjunction with hospital-based solutions, like early supported discharge plans for older patients, who are the highest users of secondary care, may provide significant and long-term benefits for the NWL area. Local solutions like these have been shown not only to reduce utilisation of health services but also to improve patient wellbeing and result in large cost savings for the NHS.³⁰

Though the present data could not establish whether an MDT approach was implemented in the NWL area, it may well be that MDTs exist but their solutions are not translating into reduced secondary care use. Successful MDTs will require cooperation, coordination, and communication across health services. Reasons for ineffective multidisciplinary care could be posited through the following questions: is there an overarching coordinating unit for multidisciplinary care? Are the IT systems compatible for such care? Is information exchange readily available and safe? Is communication across settings both smooth and frequent? Is the approach sustainable? These questions illustrate how successful solutions will require sustained financial investments and the solid backing of all relevant stakeholders, and the sheer challenge of this may explain why many MDTs have had only neutral effects.²

Acknowledgments

The Department of Primary Care and Public Health at Imperial College London is grateful for support from the NWL NIHR Applied Research Collaboration and the Imperial NIHR Biomedical Research Centre.

Notes

Funding

The Dr Foster Unit at Imperial College London is partially funded by a grant from Dr Foster, a private healthcare information company. It is also partly funded by research grants from the National Institute for Health Research (NIHR) Health Services and Delivery Research (HS&DR) (ref: 17/99/72). Martin R Cowie’s salary is supported by the NIHR Cardiovascular Biomedical Research Unit at the Royal Brompton Hospital, London. None of the funders had any role in the conception, design, analysis, or reporting of this study

Ethical approval

Whole Systems Integrated Care (WSIC) is a dataset of North West London (NWL) residents who have consented to the anonymous data in their online health records for research purposes. Additionally, this specific study was approved by the Discover Research Advisory Group (DRAG), which is a nominated body that provides a governance mechanism for evaluating project applications requesting the WSIC de-identified dataset.

Provenance

Freely submitted; externally peer reviewed.

Competing interests

Alex Bottle, Dani Kim, and Paul Aylin had financial support through a research grant from Dr Foster for the submitted work. There were no financial relationships with any organisations that might have an interest in the submitted work in the previous 3 years and no other relationships or activities that could appear to have influenced the submitted work. Benedict Hayhoe is a GP working in the NHS.

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Received September 29, 2019.
Revision requested November 18, 2019.
Accepted January 16, 2020.

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[1] 1.↵
National Institute for Health and Care Excellence
Chronic heart failure in adults: diagnosis and management NG1062018https://www.nice.org.uk/guidance/ng106 (accessed 19 May 2020).

[2] National Institute for Health and Care Excellence

[3] 2.↵
Morton G,
Masters J,
Cowburn PJ
Multidisciplinary team approach to heart failure managementHeart20181041613761382
OpenUrl FREE Full Text

[4] Morton G,

[5] Masters J,

[6] Cowburn PJ

[7] 3.↵
Legislation.gov.uk
Health and Social Care Act 2012http://www.legislation.gov.uk/ukpga/2012/7/contents/enacted (accessed 19 May 2020).

[8] Legislation.gov.uk

[9] 4.↵
National Collaboration for Integrated Care and SupportIntegrated care and support: our shared commitment2013assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/198748/DEFINITIVE_FINAL_VERSION_Integrated_Care_and_Support_-_Our_Shared_Commitment_2013-0513.pdf (accessed 19 May 2020).

[10] 5.
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[13] NHS England

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Ponikowski P,
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Ankerk SD,
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[15] Ponikowski P,

[16] Voors AA,

[17] Ankerk SD,

[18] et al.

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Health service use by patients with heart failure living in a community setting: a cross-sectional analysis in North West London

Abstract

INTRODUCTION

METHOD

Data

Definitions

Patient characteristics

Health service use

Cluster analysis

Statistical analysis

RESULTS

Patient characteristics

Health service use

Cluster analysis

DISCUSSION

Summary

Strengths and limitations

Comparison with existing literature

Implications for research and practice

Acknowledgments

Notes

Funding

Ethical approval

Provenance

Competing interests

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