An exploration of treatment burden and patient capacity in people with stroke

Background and aims: Advances in modern medicine have led to improved outcomes after stroke, yet an increased treatment burden has been placed on patients. Treatment burden is the workload of health care for people with chronic illness and the impact that this has on functioning and well-being. Those with comorbidities are likely to be particularly burdened. Excessive treatment burden can negatively affect outcomes. Individuals are likely to differ in their ability to manage health problems and follow treatments, defined as patient capacity. The aim of this thesis was to explore the experience of treatment burden for people who have had a stroke and the factors that influence patient capacity. Methods: There were four phases of research. 1) A systematic review of the qualitative literature that explored the experience of treatment burden for those with stroke. Data were analysed using framework synthesis, underpinned by Normalisation Process Theory (NPT). 2) A cross-sectional study of 1,424,378 participants >18 years, demographically representative of the Scottish population. Binary logistic regression was used to analyse the relationship between stroke and the presence of comorbidities and prescribed medications. 3) Interviews with twenty-nine individuals with stroke, fifteen analysed by framework analysis underpinned by NPT and fourteen by thematic analysis. The experience of treatment burden was explored in depth along with factors that influence patient capacity. 4) Integration of findings in order to create a conceptual model of treatment burden and patient capacity in stroke. Results: Phase 1) A taxonomy of treatment burden in stroke was created. The following broad areas of treatment burden were identified: making sense of stroke management and planning care; interacting with others including health professionals, family and other stroke patients; enacting management strategies; and reflecting on management. Phase 2) 35,690 people (2.5%) had a diagnosis of stroke and of the 39 co-morbidities examined, 35 were significantly more common in those with stroke. The proportion of those with stroke that had >1 additional morbidities present (94.2%) was almost twice that of controls (48%) (odds ratio (OR) adjusted for age, gender and socioeconomic deprivation; 95% confidence interval: 5.18; 4.95-5.43) and 34.5% had 4-6 comorbidities compared to 7.2% of controls (8.59; 8.17-9.04). In the stroke group, 12.6% of people had a record of >11 repeat prescriptions compared to only 1.5% of the control group (OR adjusted for age, gender, deprivation and morbidity count: 15.84; 14.86-16.88). Phase 3) The taxonomy of treatment burden from Phase 1 was verified and expanded. Additionally, treatment burdens were identified as arising from either: the workload of healthcare; or the endurance of care deficiencies. A taxonomy of patient capacity was created. Six factors were identified that influence patient capacity: personal attributes and skills; physical and cognitive abilities; support network; financial status; life workload, and environment. A conceptual model of treatment burden was created. Healthcare workload and the presence of care deficiencies can influence and be influenced by patient capacity. The quality and configuration of health and social care services influences healthcare workload, care deficiencies and patient capacity. Conclusions: This thesis provides important insights into the considerable treatment burden experienced by people who have had a stroke and the factors that affect their capacity to manage health. Multimorbidity and polypharmacy are common in those with stroke and levels of these are high. Findings have important implications for the design of clinical guidelines and healthcare delivery, for example co-ordination of care should be improved, shared decision-making enhanced, and patients better supported following discharge from hospital.

Cognitive impairment in heart failure

The clinical syndrome of heart failure is one of the leading causes of hospitalisation and mortality in older adults. Due to ageing of the general population and improved survival from cardiac disease the prevalence of heart failure is rising. Despite the fact that the majority of patients with heart failure are aged over 65 years old, many with multiple co-morbidities, the association between cognitive impairment and heart failure has received relatively little research interest compared to other aspects of cardiac disease. The presence of concomitant cognitive impairment has implications for the management of patients with heart failure in the community. There are many evidence based pharmacological therapies used in heart failure management which obviously rely on patient education regarding compliance. Also central to the treatment of heart failure is patient self-monitoring for signs indicative of clinical deterioration which may prompt them to seek medical assistance or initiate a therapeutic intervention e.g. taking additional diuretic. Adherence and self-management may be jeopardised by cognitive impairment. Formal diagnosis of cognitive impairment requires evidence of abnormalities on neuropsychological testing (typically a result ≥1.5 standard deviation below the age-standardised mean) in at least one cognitive domain. Cognitive impairment is associated with an increased risk of dementia and people with mild cognitive impairment develop dementia at a rate of 10-15% per year, compared with a rate of 1-2% per year in healthy controls.1 Cognitive impairment has been reported in a variety of cardiovascular disorders. It is well documented among patients with hypertension, atrial fibrillation and coronary artery disease, especially after coronary artery bypass grafting. This background is relevant to the study of patients with heart failure as many, if not most, have a history of one or more of these co-morbidities. A systematic review of the literature to date has shown a wide variation in the reported prevalence of cognitive impairment in heart failure. This range in variation probably reflects small study sample sizes, differences in the heart failure populations studied (inpatients versus outpatients), neuropsychological tests employed and threshold values used to define cognitive impairment. The main aim of this study was to identify the prevalence of cognitive impairment in a representative sample of heart failure patients and to examine whether this association was due to heart failure per se rather than the common cardiovascular co-morbidities that often accompany it such as atherosclerosis and atrial fibrillation. Of the 817 potential participants screened, 344 were included in this study. The study cohort included 196 patients with HF, 61 patients with ischaemic heart disease and no HF and 87 healthy control participants. The HF cohort consisted of 70 patients with HF and coronary artery disease in sinus rhythm, 51 patients with no coronary artery disease in sinus rhythm and 75 patients with HF and atrial fibrillation. All patients with HF had evidence of HF-REF with a LVEF <45% on transthoracic echocardiography. The majority of the cohort was male and elderly. HF patients with AF were more likely to have multiple co-morbidities. Patients recruited from cardiac rehabilitation clinics had proven coronary artery disease, no clinical HF and a LVEF >55%. The ischaemic heart disease group were relatively well matched to healthy controls who had no previous diagnosis of any chronic illness, prescribed no regular medication and also had a LVEF >55%. All participants underwent the same baseline investigations and there were no obvious differences in baseline demographics between each of the cohorts. All 344 participants attended for 2 study visits. Baseline investigations including physiological measurements, electrocardiography, echocardiography and laboratory testing were all completed at the initial screening visit. Participants were then invited to attend their second study visit within 10 days of the screening visit. 342 participants completed all neuropsychological assessments (2 participants failed to complete 1 questionnaire). A full comprehensive battery of neuropsychological assessment tools were administered in the 90 minute study visit. These included three global cognitive screening assessment tools (mini mental state examination, Montreal cognitive assessment tool and the repeatable battery for the assessment of neuropsychological status) and additional measures of executive function (an area we believe has been understudied to date). In total there were 9 cognitive tests performed. These were generally well tolerated. Data were also collected using quality of life questionnaires and health status measures. In addition to this, carers of the study participant were asked to complete a measure of caregiver strain and an informant questionnaire on cognitive decline. The prevalence of cognitive impairment varied significantly depending on the neuropsychological assessment tool used and cut-off value used to define cognitive impairment. Despite this, all assessment tools showed the same pattern of results with those patients with heart failure and atrial fibrillation having poorer cognitive performance than those with heart failure in sinus rhythm. Cognitive impairment was also more common in patients with cardiac disease (either coronary artery disease or heart failure) than age-, sex- and education-matched healthy controls, even after adjustment for common vascular risk factors.

Identifying health inequalities in individuals with major mental illness (MMI) using routine data

Abstract and Summary of Thesis: Background: Individuals with Major Mental Illness (such as schizophrenia and bipolar disorder) experience increased rates of physical health comorbidity compared to the general population. They also experience inequalities in access to certain aspects of healthcare. This ultimately leads to premature mortality. Studies detailing patterns of physical health comorbidity are limited by their definitions of comorbidity, single disease approach to comorbidity and by the study of heterogeneous groups. To date the investigation of possible sources of healthcare inequalities experienced by individuals with Major Mental Illness (MMI) is relatively limited. Moreover studies detailing the extent of premature mortality experienced by individuals with MMI vary both in terms of the measure of premature mortality reported and age of the cohort investigated, limiting their generalisability to the wider population. Therefore local and national data can be used to describe patterns of physical health comorbidity, investigate possible reasons for health inequalities and describe mortality rates. These findings will extend existing work in this area. Aims and Objectives: To review the relevant literature regarding: patterns of physical health comorbidity, evidence for inequalities in physical healthcare and evidence for premature mortality for individuals with MMI. To examine the rates of physical health comorbidity in a large primary care database and to assess for evidence for inequalities in access to healthcare using both routine primary care prescribing data and incentivised national Quality and Outcome Framework (QOF) data. Finally to examine the rates of premature mortality in a local context with a particular focus on cause of death across the lifespan and effect of International Classification of Disease Version 10 (ICD 10) diagnosis and socioeconomic status on rates and cause of death. Methods: A narrative review of the literature surrounding patterns of physical health comorbidity, the evidence for inequalities in physical healthcare and premature mortality in MMI was undertaken. Rates of physical health comorbidity and multimorbidity in schizophrenia and bipolar disorder were examined using a large primary care dataset (Scottish Programme for Improving Clinical Effectiveness in Primary Care (SPICE)). Possible inequalities in access to healthcare were investigated by comparing patterns of prescribing in individuals with MMI and comorbid physical health conditions with prescribing rates in individuals with physical health conditions without MMI using SPICE data. Potential inequalities in access to health promotion advice (in the form of smoking cessation) and prescribing of Nicotine Replacement Therapy (NRT) were also investigated using SPICE data. Possible inequalities in access to incentivised primary healthcare were investigated using National Quality and Outcome Framework (QOF) data. Finally a pre-existing case register (Glasgow Psychosis Clinical Information System (PsyCIS)) was linked to Scottish Mortality data (available from the Scottish Government Website) to investigate rates and primary cause of death in individuals with MMI. Rate and primary cause of death were compared to the local population and impact of age, socioeconomic status and ICD 10 diagnosis (schizophrenia vs. bipolar disorder) were investigated. Results: Analysis of the SPICE data found that sixteen out of the thirty two common physical comorbidities assessed, occurred significantly more frequently in individuals with schizophrenia. In individuals with bipolar disorder fourteen occurred more frequently. The most prevalent chronic physical health conditions in individuals with schizophrenia and bipolar disorder were: viral hepatitis (Odds Ratios (OR) 3.99 95% Confidence Interval (CI) 2.82-5.64 and OR 5.90 95% CI 3.16-11.03 respectively), constipation (OR 3.24 95% CI 3.01-3.49 and OR 2.84 95% CI 2.47-3.26 respectively) and Parkinson’s disease (OR 3.07 95% CI 2.43-3.89 and OR 2.52 95% CI 1.60-3.97 respectively). Both groups had significantly increased rates of multimorbidity compared to controls: in the schizophrenia group OR for two comorbidities was 1.37 95% CI 1.29-1.45 and in the bipolar disorder group OR was 1.34 95% CI 1.20-1.49. In the studies investigating inequalities in access to healthcare there was evidence of: under-recording of cardiovascular-related conditions for example in individuals with schizophrenia: OR for Atrial Fibrillation (AF) was 0.62 95% CI 0.52 - 0.73, for hypertension 0.71 95% CI 0.67 - 0.76, for Coronary Heart Disease (CHD) 0.76 95% CI 0.69 - 0.83 and for peripheral vascular disease (PVD) 0.83 95% CI 0.72 - 0.97. Similarly in individuals with bipolar disorder OR for AF was 0.56 95% CI 0.41-0.78, for hypertension 0.69 95% CI 0.62 - 0.77 and for CHD 0.77 95% CI 0.66 - 0.91. There was also evidence of less intensive prescribing for individuals with schizophrenia and bipolar disorder who had comorbid hypertension and CHD compared to individuals with hypertension and CHD who did not have schizophrenia or bipolar disorder. Rate of prescribing of statins for individuals with schizophrenia and CHD occurred significantly less frequently than in individuals with CHD without MMI (OR 0.67 95% CI 0.56-0.80). Rates of prescribing of 2 or more anti-hypertensives were lower in individuals with CHD and schizophrenia and CHD and bipolar disorder compared to individuals with CHD without MMI (OR 0.66 95% CI 0.56-0.78 and OR 0.55 95% CI 0.46-0.67, respectively). Smoking was more common in individuals with MMI compared to individuals without MMI (OR 2.53 95% CI 2.44-2.63) and was particularly increased in men (OR 2.83 95% CI 2.68-2.98). Rates of ex-smoking and non-smoking were lower in individuals with MMI (OR 0.79 95% CI 0.75-0.83 and OR 0.50 95% CI 0.48-0.52 respectively). However recorded rates of smoking cessation advice in smokers with MMI were significantly lower than the recorded rates of smoking cessation advice in smokers with diabetes (88.7% vs. 98.0%, p<0.001), smokers with CHD (88.9% vs. 98.7%, p<0.001) and smokers with hypertension (88.3% vs. 98.5%, p<0.001) without MMI. The odds ratio of NRT prescription was also significantly lower in smokers with MMI without diabetes compared to smokers with diabetes without MMI (OR 0.75 95% CI 0.69-0.81). Similar findings were found for smokers with MMI without CHD compared to smokers with CHD without MMI (OR 0.34 95% CI 0.31-0.38) and smokers with MMI without hypertension compared to smokers with hypertension without MMI (OR 0.71 95% CI 0.66-0.76). At a national level, payment and population achievement rates for the recording of body mass index (BMI) in MMI was significantly lower than the payment and population achievement rates for BMI recording in diabetes throughout the whole of the UK combined: payment rate 92.7% (Inter Quartile Range (IQR) 89.3-95.8 vs. 95.5% IQR 93.3-97.2, p<0.001 and population achievement rate 84.0% IQR 76.3-90.0 vs. 92.5% IQR 89.7-94.9, p<0.001 and for each country individually: for example in Scotland payment rate was 94.0% IQR 91.4-97.2 vs. 96.3% IQR 94.3-97.8, p<0.001. Exception rate was significantly higher for the recording of BMI in MMI than the exception rate for BMI recording in diabetes for the UK combined: 7.4% IQR 3.3-15.9 vs. 2.3% IQR 0.9-4.7, p<0.001 and for each country individually. For example in Scotland exception rate in MMI was 11.8% IQR 5.4-19.3 compared to 3.5% IQR 1.9-6.1 in diabetes. Similar findings were found for Blood Pressure (BP) recording: across the whole of the UK payment and population achievement rates for BP recording in MMI were also significantly reduced compared to payment and population achievement rates for the recording of BP in chronic kidney disease (CKD): payment rate: 94.1% IQR 90.9-97.1 vs.97.8% IQR 96.3-98.9 and p<0.001 and population achievement rate 87.0% IQR 81.3-91.7 vs. 97.1% IQR 95.5-98.4, p<0.001. Exception rates again were significantly higher for the recording of BP in MMI compared to CKD (6.4% IQR 3.0-13.1 vs. 0.3% IQR 0.0-1.0, p<0.001). There was also evidence of differences in rates of recording of BMI and BP in MMI across the UK. BMI and BP recording in MMI were significantly lower in Scotland compared to England (BMI:-1.5% 99% CI -2.7 to -0.3%, p<0.001 and BP: -1.8% 99% CI -2.7 to -0.9%, p<0.001). While rates of BMI and BP recording in diabetes and CKD were similar in Scotland compared to England (BMI: -0.5 99% CI -1.0 to 0.05, p=0.004 and BP: 0.02 99% CI -0.2 to 0.3, p=0.797). Data from the PsyCIS cohort showed an increase in Standardised Mortality Ratios (SMR) across the lifespan for individuals with MMI compared to the local Glasgow and wider Scottish populations (Glasgow SMR 1.8 95% CI 1.6-2.0 and Scotland SMR 2.7 95% CI 2.4-3.1). Increasing socioeconomic deprivation was associated with an increased overall rate of death in MMI (350.3 deaths/10,000 population/5 years in the least deprived quintile compared to 794.6 deaths/10,000 population/5 years in the most deprived quintile). No significant difference in rate of death for individuals with schizophrenia compared with bipolar disorder was reported (6.3% vs. 4.9%, p=0.086), but primary cause of death varied: with higher rates of suicide in individuals with bipolar disorder (22.4% vs. 11.7%, p=0.04). Discussion: Local and national datasets can be used for epidemiological study to inform local practice and complement existing national and international studies. While the strengths of this thesis include the large data sets used and therefore their likely representativeness to the wider population, some limitations largely associated with using secondary data sources are acknowledged. While this thesis has confirmed evidence of increased physical health comorbidity and multimorbidity in individuals with MMI, it is likely that these findings represent a significant under reporting and likely under recognition of physical health comorbidity in this population. This is likely due to a combination of patient, health professional and healthcare system factors and requires further investigation. Moreover, evidence of inequality in access to healthcare in terms of: physical health promotion (namely smoking cessation advice), recording of physical health indices (BMI and BP), prescribing of medications for the treatment of physical illness and prescribing of NRT has been found at a national level. While significant premature mortality in individuals with MMI within a Scottish setting has been confirmed, more work is required to further detail and investigate the impact of socioeconomic deprivation on cause and rate of death in this population. It is clear that further education and training is required for all healthcare staff to improve the recognition, diagnosis and treatment of physical health problems in this population with the aim of addressing the significant premature mortality that is seen. Conclusions: Future work lies in the challenge of designing strategies to reduce health inequalities and narrow the gap in premature mortality reported in individuals with MMI. Models of care that allow a much more integrated approach to diagnosing, monitoring and treating both the physical and mental health of individuals with MMI, particularly in areas of social and economic deprivation may be helpful. Strategies to engage this “hard to reach” population also need to be developed. While greater integration of psychiatric services with primary care and with specialist medical services is clearly vital the evidence on how best to achieve this is limited. While the National Health Service (NHS) is currently undergoing major reform, attention needs to be paid to designing better ways to improve the current disconnect between primary and secondary care. This should then help to improve physical, psychological and social outcomes for individuals with MMI.