Entete 3

Publications on multimorbidity January-April 2018

By Martin Fortin
Our search for papers on multimorbidity that were published during the period January – April 2018 has been completed. As in previous searches, we have prepared a PDF file that can be accessed following this link.
Probably, there are some publications that were not detected by our search strategy using the terms “multimorbidity”, “multi-morbidity” and the expression “multiple chronic diseases” in PubMed (https://www.ncbi.nlm.nih.gov/pubmed), but we are sure that most publications on the subject are included in the list.
All references are also included in our library. Feel free to share with anyone interested in multimorbidity.

Redesigning primary care for the people who use it: unveiling the results of the 3D trial for patients with multimorbidity in general practice

By Chris Salisbury, Peter Bower, Stewart Mercer and Bruce Guthrie
There is good agreement about the sort of care that people with multimorbidity need. But can it be delivered in the busy setting of general practice, and does it improve outcomes? In this blog we discuss the results of the 3D trial, the largest study of an intervention for multimorbidity published to date.
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Managing multimorbidity is a litmus test for modern health care systems. Patients with many long-term conditions face major challenges in managing their conditions and need significant support, which means that these patients are often associated with high costs.
Despite the complexity of caring for these patients, there is also significant agreement about what sort of care they need. Many authors have highlighted that patient-centred care is crucial, with a significant focus on core skills such as understanding patient needs, sharing decision-making, and supporting self-management. These well-known patient-centred skills need augmenting when managing patients with multiple conditions, to help patients to prioritise conditions and goals and manage depression. It is also important to provide continuity of care and co-ordination to help patients and carers navigate the health care system.
Despite this consensus about what should be done, two core questions remain. First, can general practice be supported to provide this sort of care, given the pressures of limited time, high demand and competing clinical responsibilities? The barriers to implementation are significant.
Secondly, will these kinds of changes to general practice care lead to demonstrable benefits in patient health, quality of life and cost-effectiveness?
The 3D trial (published today in the Lancet) was an ambitious attempt to answer these questions. We took the current consensus about optimal care for multimorbidity, and translated that into a practical intervention (called 3D). In brief, this is a patient-centred model that seeks to improve continuity, co-ordination and efficiency of care by replacing disease-focused reviews of single conditions with more comprehensive and integrated six monthly reviews.
We then supported practices to deliver 3D in the busy world of everyday clinical care, to test whether it enhanced care and improved outcomes.
The trial is fully detailed in the paper, but in summary we tested 3D in over 33 practices in a randomised trial in Bristol, Greater Manchester and Ayrshire. We then measured the outcomes of over 1500 patients after 15 months in the study.
We posed two questions earlier. The first question was: can we implement current ‘best practice’ for multimorbidity in general practice? The answer to this was clearly ‘Yes’. Despite the well-known pressures on primary care, practices undertook training, introduced new systems, and worked with patients to introduce this new model of care (although some practices implemented it more successfully than others).
We know that practices changed the care they provided, because we have good data showing that the 3D model was introduced. More importantly, patients clearly reported that their experience of care was improved, with a whole host of measures of patient-centred care showing improvements over usual care. Patients reported better empathy, that their care felt more ‘joined up’, and that care was better aligned to their priorities.
Our second question was: does the introduction of current ‘best practice’ care for multimorbidity lead to demonstrable benefits in patient quality of life? The answer was an equally clear ‘No’. Despite strong evidence that 3D was implemented and that the changes were appreciated by patients, we found no evidence of changes in quality of life (our pre-defined primary outcome).
Although the 3D trial faced the usual challenges of research in general practice, we are confident that the design is rigorous. The questions we now face are about how we interpret the results.
There are many possible reasons why the changes in patient-centred care did not translate to better quality of life. The changes in patient centred care were significant, but they may not have been large enough to translate to other outcomes. The 3D model may need modification, and practices may need more time and support to truly embed changes. Patients may need more experience of the 3D model before changes in the process of care impact on their quality of life. Some of the comparison general practices were beginning to implement some similar ideas to those in 3D, making it harder to detect benefit from 3D. It is possible that current measures of quality of life are not sensitive to the care of patients with multimorbidity.
In fact, our findings are not so different to the wider literature, where previous trials of a range of different ideas to improve care for patients with long-term conditions have also failed to demonstrate improvements in quality of life. Indeed it has long been recognised that health is mainly determined by factors other than health care, so perhaps it is not surprising that improved care for multimorbidity does not necessarily lead to better overall health.
There is an important debate as to whether the benefits we have seen from introducing the 3D model are of sufficient value. Care for patients with long-term conditions is supposed to target the ‘Triple Aim’, which includes improving patient experience alongside better health outcomes and reduced costs. General practice prides itself on its ability to provide patient-centred care, but changes in the delivery of care and high demand have placed limits on the ability of practice teams to do this. Patients in the 3D trial reported gaps in their experience of care at the start of the trial, and 3D successfully overcome some of those gaps and improved quality of care for a group of patients whose experience of the health care system is often less than optimal.
In the absence of better ways of organising care, there may be an argument that the benefits reported by patients through adoption of 3D are worthwhile, because improving the quality of their care is itself a good thing, even if we cannot yet help patients improve the quality of their lives.
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• 3D was funded by the National Institute for Health Research Health Services and Delivery Research Programme (project number 12/130/15). The views and opinions expressed in this report are those of the authors and do not necessarily reflect those of the NIHR, the NHS or the Department of Health.

Frailty : Not just a problem for older people

By Peter Hanlon and Frances Mair
It is often said that many of the challenges faced in healthcare are due to ‘ageing populations’. It is clear, however, that health (and the need for health services) is not simply related to how old a person is. There are many other factors more closely linked to an individual’s need for care, many of which are related to age. These include multimorbidity – having two or more long-term health conditions – and frailty. Frailty is closely linked to multimorbidity, but the terms are not interchangeable.
Frailty describes a reduction in the body’s in-built reserves which is generally due to the cumulative effect of a range of individual deficits. People with frailty are therefore more at risk of developing significant illness, sometimes in response to relatively minor events or ‘stressors’. To provide high quality healthcare to people with frailty involves a holistic approach, considering the whole person and their wider context, rather than purely focusing on individual diseases in isolation. Managing frailty also takes considerable resource, as people may require additional support or services, and are more likely to require hospital admission.
Both frailty and multimorbidity are more common with increasing age, and therefore most research and interventions to improve care has focused on elderly people. It is also true, however, that the majority of people with multimorbidity are aged under 65 years. This is particularly true in areas of high socioeconomic deprivation. Despite this, the prevalence and effects of frailty at younger ages and in multimorbidity has not been investigated. Most studies, as well as most health services, that seek to target frailty have tended to exclude people aged less than 65 years, even though many people in this age group are affected by multimorbidity and may benefit from an approach to healthcare that reflects this.
Our recent study [1], published in The Lancet Public Health, seeks to address this research gap. It suggests that frailty affects ‘middle-aged’ as well as older people. We found that frailty, while strongly associated with multimorbidity, identifies middle aged people at increased risk of death, over-and-above known risk factors and number of long-term health conditions.
This study analyses frailty in a younger population than most previous research. We used data from the UK Biobank cohort – a large study of around 500,000 volunteers aged between 37 and 73 years. Participants in the study were considered ‘frail’ if they met three or more of the following criteria: weight loss, slow walking pace, low hand grip strength, low physical activity, and exhaustion. People with one or two of these features were considered ‘pre-frail’.
While frailty does get more common with increasing age, we found that people of all ages had the potential to be ‘frail’ using this definition. While only a small proportion of ‘middle-aged’ people were identified as frail by this definition – 3% overall – frailty was much more common in people with multimorbidity.  Of people with 2 or more long-term conditions, 7% were frail. This increased to 18% among people with 4 or more long-term conditions. Frailty was also closely linked with socioeconomic deprivation and obesity.
Frailty was associated with more than double the risk of death in men of all ages included (37 to 73 years) and in females above the age of 45 years. This was after accounting for deprivation, lifestyle factors such as smoking, obesity and alcohol, and the number of long-term conditions. Frailty, therefore, appears to carry additional risk of premature death in younger people, over-and-above the recognised risk factors such as smoking and multimorbidity. People with ‘pre-frailty’ also had an increased risk of death in all of these age groups.
These findings highlight the challenges faced by primary care teams caring for patients with complex problems and multimorbidity, many of whom may be too young to be eligible for existing services focusing on frailty in the elderly. This is particularly true in areas of high socioeconomic deprivation, where both multimorbidity and frailty among younger people is much more common.
This study shows that frailty may be identifiable at an earlier stage than is traditionally understood. This may, therefore, represent an opportunity to explore ways of intervening earlier. If this is to happen, researchers and healthcare professions will need to broaden their focus on frailty to include a wider age range. Importantly, it also highlights the need for a move away from disease focused to more person centred care that provides a more holistic approach to patient care that is tailored to meet an individual’s specific requirements.
Identifying frailty in those with multimorbidity may have positive implications for care, planning interventions and a patient’s prognosis.  We suggest integration of an assessment of frailty into the routine assessment of people with multimorbidity might help identification of those at greater risk and ensure more accurate targeting of the multidimensional, patient-centred reorganisation of care required to address complex multimorbidity.
There is a pressing need to understand frailty in younger people much more fully. When trying to provide services and care for people with frailty and multimorbidity it will be crucial to consider the needs of younger people (particularly those in areas of high socioeconomic deprivation). Our work demonstrates that frailty, like multimorbidity, is not just a problem that affects older people.
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[1] Peter Hanlon, Barbara I Nicholl, Bhautesh Dinesh Jani, Duncan Lee, Ross McQueenie, Frances S Mair. Frailty and pre-frailty in middle-aged and older adults and its association with multimorbidity and mortality: a prospective analysis of 493 737 UK Biobank participants. Lancet Public Health 2018. Published Online June 13, 2018. http://dx.doi.org/10.1016/S2468-2667(18)30091-4.

The Primary Care Outcomes Questionnaire: a new generic instrument for measuring outcomes in primary care

By Mairead Murphy and Chris Salisbury
The majority of primary care consultations are by patients with multiple long-term conditions [1]. With ninety percent of all patient interaction with health services in the UK going through primary care, it’s not surprising that primary care clinicians and researchers try to figure out ways to improve services for their patients. Interventions are many and varied, and result in important questions about their effectiveness. Do electronic consultations offer a good service to patients? If GPs introduce advice on healthy lifestyles into the consultation, does it make patients healthier? What about increasing the duration of GP appointments to ten minutes – does this improve outcomes for patients? Or ensuring that patients always see the same named doctor? Or painting the waiting room green?
Questions like these are normally answered by administration of a generic patient-reported questionnaire. By comparing the responses of groups of patients (say those with eight-minute consultations and those with ten-minute consultations), researchers can see which group has the highest scores, and therefore whether one method of delivering care is better than the other.
Although this might sound a simple process, in practice it is not so easy. The problem is that primary care delivers a range of outcomes, some of which are more directly health-related than others. The recent blog on this site by Susan Smith (Identifying key outcomes for multimorbidity research April 19th) found that 17 core outcomes were important to measure in people with long-term conditions. These included outcomes related to mortality, health-related quality of life, patient behaviours, shared decision making and quality of health services. When we explored this issue in 2015, we similarly found that primary care patients, both those with and without long term conditions want broad range of outcomes [2]. Some of these, such as reduction in pain or depression, are captured on most generic patient-reported questionnaires. But others, such as reduction in concern, a sense of confidence in health plan, or an understanding of illnesses/problems and an ability to manage symptoms, are less well-captured.
This is why we have designed a new questionnaire, called the Primary Care Outcomes Questionnaire, or the PCOQ. The PCOQ was designed in consultation with patients [3] specifically to measure outcomes which many primary care patients seek, and which GPs seek to deliver. It contains 24 questions in four areas: health and well-being; health knowledge and understanding; confidence in health plan; and confidence in health provision. We quantitatively tested the PCOQ in a sample of primary care patients and found that it was easy for patients to complete, had construct validity, and able to show change in each of the four areas. We published these findings in March in the BJGP [4]. We have made the PCOQ available free of charge for non-commercial use and hope that researchers will find it useful for assessing the effectiveness of interventions in primary care. In the future, we plan to test the PCOQ for use in routine clinical practice.
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1. Salisbury, C., et al., Epidemiology and impact of multimorbidity in primary care: a retrospective cohort study. British Journal of General Practice, 2011. 61(582): p. e12-21.
2. Murphy M, Hollinghurst S, Turner K, Salisbury C. Patient and practitioners’ views on the most important outcomes arising from primary care consultations: a qualitative study. BMC Fam Practice 2015;16:108. Doi: 10.1186/s12875-015-0323-9
3. Murphy M, Hollinghurst S, Salisbury C. Qualitative assessment of the primary care outcomes questionnaire: a cognitive interview study, BMC Health Services Research 2018 10.1186/s12913-018-2867-6
4. Murphy M, Hollinghurst S, Cowlishaw S, Salisbury C. Psychometric Testing of the Primary Care Outcomes Questionnaire, British Journal of General Practice, 26th March 2018,10.3399/bjgp18X695765

‘Multimorbidity Treatment Burden Questionnaire’ (MTBQ) – a new measure of treatment burden

By Polly Duncan and Chris Salisbury
A group of researchers from the University of Bristol, UK, have developed a new simply worded, concise questionnaire, named the ‘Multimorbidity Treatment Burden Questionnaire’ (MTBQ) to measure treatment burden (the perceived effort of looking after one’s health and the impact that this has on day to day life) in patients with multimorbidity (multiple long-term conditions).  The study has been published in the BMJ Open [1].
Treatment burden includes everything that the patient has to do to look after their health – from ordering, collecting and taking medicines; to co-ordinating, arranging transport for and attending health appointments with multiple different health professionals; to monitoring blood sugar or blood pressure levels; to learning about your health conditions; and taking on lifestyle advice.
To understand how new health care interventions impact on treatment burden, we need to be able to measure it, and a recent study published in the Annals of Family Medicine highlighted treatment burden as one of the core outcome measures for research studies involving patients with multimorbidity [2].
The MTBQ was developed as part of a large research study called the 3D Study [3].  The research team identified and reviewed three existing measures of treatment burden that were not specific to a medical condition.  A further measure has since been published.  We found that the existing measures had limitations (e.g. they did not cover all of the areas of treatment burden or they required good literacy levels and so were not suitable for our study population of mainly older people) and so we decided to develop and validate a new measure.
We discussed the concept of treatment burden and an existing framework of treatment burden that had been developed in the United States with members of a patient and public involvement group.  Using this framework as a guide, we developed a questionnaire to include all the important areas of treatment burden.  We interviewed patients with multimorbidity and asked them to comment on the layout and wording of questions, how easy the questions were to understand and to ‘think aloud’ as they answered the questionnaire – what did the questions mean to them and what answer would they give if they were completing the questionnaire?
The MTBQ was then completed by over 1500 mostly elderly patients (average age 71 years) with three or more long-term conditions who took part in the 3D Study.  The research team assessed the questionnaire against the ISOQOL international standards for developing and validating questionnaires and found that it performed well, demonstrating good face validity (e.g. it measured what it set out to measure), construct validity (e.g. patients with high disease burden and poor quality of life reported higher treatment burden), reliability and responsiveness to change  (e.g. as expected, patients who reported reduce quality of life over time also reported higher treatment burden over time) [1].
Strengths of the MTBQ include:
- simple wording
- a concise measure with ten questions
- all the important aspects of treatment burden are included
- it was tested in patients for whom it was intended – elderly patients (means age 71 years) with three or more long-term conditions
Further information about the MTBQ can be found here:
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References:
1. Duncan P, Murphy M, Man MS, et al. Development and validation of the Multimorbidity Treatment Burden Questionnaire (MTBQ). BMJ Open 2018;8(4):e019413. doi: 10.1136/bmjopen-2017-019413 [published Online First: 2018/04/12]
2. Smith SM, Wallace E, Salisbury C, et al. A Core Outcome Set for Multimorbidity Research (COSmm). Ann Fam Med 2018;16(2):132-38.
3. Man MS, Chaplin K, Mann C, et al. Improving the management of multimorbidity in general practice: protocol of a cluster randomised controlled trial (The 3D Study). BMJ Open 2016;6(4):e011261. doi: 10.1136/bmjopen-2016-011261

Identifying key outcomes for multimorbidity research

By Susan M Smith, Emma Wallace, Chris Salisbury, Maxime Sasseville, Elizabeth Bayliss, Martin Fortin
A new study has identified the most appropriate outcomes to assess in studies examining interventions for patients who suffer from multiple chronic medical conditions (multimorbidity). It has been conducted by researchers from RCSI (Royal College of Surgeons in Ireland). The study was carried out by the Health Research Board (HRB) Centre for Primary Care Research at RCSI’s Department of General Practice in collaboration with researchers from the University of Bristol, in the United Kingdom, the University of Sherbrooke in Canada and the University of Colorado din the USA . The study was published in the leading US primary care journal, the Annals of Family Medicine [1].
Multimorbidity is present in a patient when the individual has two or more chronic medical conditions. These patients are more likely to experience decreased quality of life, functional decline and increased need for healthcare. They often need to take several medications (polypharmacy) and can experience fragmented care due to involvement with multiple healthcare providers. There is growing interest in trying to identify effective interventions that can improve outcomes for patients with multimorbidity. We conducted a study to identify which outcomes should be prioritised in these studies. We used a Delphi consensus process involving 26 researchers, clinicians and patients from 13 countries.
This panel of international experts agreed that clinical trials of multimorbidity should measure and report, at minimum, quality of life, mortality, and mental health outcomes. The panel reached consensus on 17 core outcomes for multimorbidity research in total. The highest ranked outcomes were health-related quality of life, mental health outcomes and mortality. Other outcomes were grouped into overarching themes of patient-reported impacts and behaviors (treatment burden, self-rated health, self-management behavior, self-efficacy, adherence); physical activity and function (activities of daily living, physical function, physical activity); outcomes related to the medical visit (communication, shared decision-making, prioritization); and health systems outcomes (healthcare utilization, costs, quality of healthcare). The authors suggest that, when designing studies to capture important domains in multimorbidity, researchers consider the full range of outcomes based on study aims and interventions.
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1. Smith SM, Wallace E, Salisbury C, et al. A Core Outcome Set for Multimorbidity Research (COSmm). Ann Fam Med 2018;16(2):132-38.

A general practice street health service

By Tom Brett
This qualitative study [1] explores patient and allied health staff perspectives of a street-based, primary health service with the aim of identifying factors that influence patient access and management.
It is a useful companion paper to our recent 10-year retrospective cohort study [2] of multimorbidity among marginalised patients attending the Freo Street Doctor service.
Key themes emerging from the research included better doctor-patient empathy, better understanding of patient circumstances, fostering of social capital and facilitating referral pathways to health and social services.
The researchers noted that the provision of services for homeless and marginalised patients can be challenging for mainstream general practices.
Our findings show that patients attending the Freo Street Doctor service appreciate the open access nature of the clinic, the focus on psycho-social as well as medical needs and the empathy and understanding shown by the GPs, nurses and outreach services who deliver the service. The preparedness of the street health service providers to meet the altered needs of marginalised patients in their own backyard is a key factor in engagement.
Mainstream primary health care services would do well to recognise and adopt strategies that recognise the special needs and social circumstances of these patients.
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1.       Strange C,   Fisher C, Chan She Ping-Delfos W, Arnold-Reed D, Brett T.  A general practice street health service – patient and allied service provider perspectives. AJGP. 2018. 47 (1-2): 44-48.
2.       Arnold-Reed D, Troeung L, Brett T,  Chan She Ping-Delfos W, Geelhoed E, Fisher C, Preen D. Increasing multimorbidity in an Australian street health service – a 10-year retrospective cohort study,. AJGP. 2018; 47 (4): 181-189.

Multimorbidity in an Australian street health service

By Tom Brett
The Freo Street Doctor service is a free, primary care–based, mobile health clinic that has been operating in Fremantle, Western Australia since 2005. It operates from various locations in and around Fremantle, offering homeless and disadvantaged patients access to an accredited general practice service. It is serviced by a number of general practitioners, nurses, social workers and Aboriginal health workers as well as collaborating with numerous ancillary services to improve the health and circumstances of marginalised patients in this population group.
We report on a total of 4285 patients who attended the service over a 10 year period [1]. We found multimorbidity to be associated with increasing age, male sex and Aboriginality. An important finding from our study is the high Aboriginal attendance, comprising 31.5% of the total cohort (with 50.8% female). This attendance ratio is in sharp contrast with the <2% Aboriginal patients attending mainstream GP clinics Australia-wide.
Our research shows that multimorbidity is increasing over the past decade and presents as chronic physical and mental health problems in these marginalised, street health patients. These patients are at increased risk of ongoing neglect unless provided with a no-cost, multidisciplinary approach capable of delivering health and social services in a non-judgemental, comfortable and secure environment.
The progressive increase in attendance by young, especially Aboriginal, patients over the past decade, and the positive feedback from patients and allied services attending the Freo Street Doctor, make compelling arguments that this accredited, general practice–based service is addressing important health and social needs in an environment where they are clearly needed.
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1. Arnold-Reed D, Troeung L,  Brett T, Chan She Ping-Delfos W, Strange C, Geelhoed E, Fischer C,  Preen D. Increasing multimorbidity in an Australian street health service – a 10 year retrospective cohort study. AJGP. 2018; 47 (4): 181-189.

Publications on multimorbidity September- December 2017

By Martin Fortin
Our search for papers on multimorbidity that were published during the period September – December 2017 has been completed. As in previous searches, we have prepared a PDF file that can be accessed following this link.
Probably, there are some publications that were not detected by our search strategy using the terms “multimorbidity”, “multi-morbidity” and the expression “multiple chronic diseases” in PubMed (https://www.ncbi.nlm.nih.gov/pubmed), but we are sure that most publications on the subject are included in the list.
All references are also included in our library. Feel free to share with anyone interested in multimorbidity.

The EpiChron Cohort Study of Chronic Diseases and Multimorbidity

By Alexandra Prados Torres
I would like to share with you the profile of the EpiChron Cohort recently published in the International Journal of Epidemiology, a large-scale population-based study aimed at understanding how multimorbidity and the main chronic conditions appears and evolve in the population, and impact on health services and health outcomes. Created in 2010, it will gather information of the 1.3 M inhabitants of the Spanish region of Aragon until 2020. It has been developed by the EpiChron Research Group on Chronic Diseases from Aragon Health Sciences Institute (IACS) and IIS Aragón. This Cohort aims to study the problems associated to multimorbidity and chronicity (e.g., polypharmacy, low adherence to medical plan, increased risk of mortality, frailty, inappropriate health services use) and to identify risk factors (e.g., clinical, social, demographical) of negative health related outcomes. We also aim to study the evolution of trajectories of multimorbidity patterns over time and their impact on health outcomes with the final goal of developing predictive modeling tools. One key point of the project is to scaling up the knowledge in the area of chronicity and multimorbidity and to foster collaborations with other European and international research groups working in this area to conduct cross-national studies.
Besides the main characteristics of the EpiChron Cohort, this paper describes the data quality control process followed to ensure an adequate level of accuracy, reliability and appropriateness of data for research in multimorbidity.  Moreover, the main findings obtained to date are detailed in the paper.
The publication can be found in the following link: Prados-Torres et al 2018