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BJGP OPEN
Treatment burden in multiple long-term conditions: a
mixed-methods study protocol
Johnson, Rachel; Kovalenko, Anastasiia G; Blakeman, Thomas; Panagioti,
Maria; Lawton, Michael; Dawson, Shoba; Duncan, Polly; Fraser, Simon D;
Valderas, Jose; Chilcott, Simon; Goulding, Rebecca; Salisbury, Chris
DOI: https://doi.org/10.3399/BJGPO.2023.0097
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Received 02 June 2023
Accepted 05 June 2023
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Treatment burden in Multiple Long-Term Conditions: a mixed-methods study protocol
Authors:
Rachel Johnson, BM BCh PhD
https://orcid.org/0000-0266-3433
Bristol Medical School, University of Bristol, UK
Anastasiia G Kovalenko, BA, MSc, Doctoral Research Fellow*
https://orcid.org/0000-0002-4299-3587
Bristol Medical School, University of Bristol, UK
Tom Blakeman, PhD, MRCGP
https://orcid.org/0000-0003-3298-8423
Division of Population Health, Health Services Research and Primary Care, The University of
Manchester, UK
Maria Panagioti, BA, MSc, PhD
https://orcid.org/0000-0002-7153-5745
Division of Population Health, Health Services Research and Primary Care, The University of
Manchester, UK
Michael Lawton, PhD
https://orcid.org/0000-0002-3419-0354
Bristol Medical School, University of Bristol, UK
Shoba Dawson, BA, MSc, PhD
https://orcid.org/0000-0002-6700-6445
Bristol Medical School, University of Bristol, UK
Polly Duncan, MPH, MRCGP, NIHR Doctoral Research Fellow
https://orcid.org/0000-0002-2244-3254
Bristol Medical School, University of Bristol, UK
Simon DS Fraser, BM MSc DM FFPH MRCGP
http://orcid.org/0000-0002-4172-4406
School of Primary Care, Population Science and Medical Education, Faculty of Medicine, University of
Southampton, UK
Jose Valderas, MPH PhD
https://orcid.org/0000-0002-9299-1555
Centre for Research in Health Systems Performance (CRiHSP) and Division of Family Medicine,
Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore
Simon Chilcott, public contributor
Rebecca Goulding, PhD
https://orcid.org/0000-0003-0716-5126
Division of Population Health, Health Services Research and Primary Care; The University of
Manchester, UK
Chris Salisbury, MD, FRCGP
https://orcid.org/0000-0002-4378-3960
Bristol Medical School, University of Bristol, UK
* Corresponding author: Anastasiia G Kovalenko
Email: a.g.kovalenko@bristol.ac.uk
Funding: This study is funded by the NIHR School for Primary Care Research Grant Reference
Number 564
Ethical approval: This study has received favourable ethical opinion from Health Research Authority
and Health and Care Research Wales (IRAS 311163)
Competing interests: Prof Chris Salisbury and Dr Polly Duncan developed and validated the original
Multimorbidity Treatment Burden Questionnaire.
Dr Michael Lawton received fees for advising on a secondary analysis of an RCT sponsored by North
Bristol NHS trust.
Acknowledgements: We would like to acknowledge the PPI group for their input in designing the
study.
1
Abstract
Background: Treatment burden represents the work patients undertake because of their healthcare,
and the impact of that effort on the patient. Most research has focused on older adults (65+) with
multiple long-term conditions (MLTC-M) but there are more younger adults (18-65) living with
MLTC-M and they may experience treatment burden differently. Understanding experiences of
treatment burden, and identifying those most at risk of high treatment burden, are important for
designing primary care services to meet their needs.
Aim: To understand the treatment burden associated with MLTC-M, for people aged 18-65 years,
and how primary care services affect this burden.
Design & setting: Mixed-methods study in 20- 33 primary care practices in two UK regions.
Method: i. In-depth qualitative interviews with adults living with MLTC-M (approximately 40
participants) to understand their experiences of treatment burden and the impact of primary care;
with a think-aloud aspect to explore face validity of a novel short treatment burden questionnaire
for routine clinical use (STBQ) in the initial 15 interviews. ii. Cross-sectional patient survey
(approximately 1000 participants) with linked routine medical record data to examine the factors
associated with treatment burden for people living with MLTC-M, and to test the validity of STBQ.
Conclusion: This study will generate in-depth understanding of the treatment burden experienced by
people aged 18-65 years living with MLTC-M, and how primary care services affect this burden. This
will inform further development and testing of interventions to reduce treatment burden, and
potentially influence MLTC-M trajectories and improve health outcomes.
Introduction
Multiple long-term conditions (multimorbidity or MLTC-M, defined as the existence of two or more
long-term conditions) affects approximately 1 in 4 of the UK population, is associated with reduced
quality of life and increased hospital admissions [1, 2] and accounts for over half of the costs of
primary and secondary care [3]. MLTC-M is more prevalent, and occurs at a younger age, in more
deprived areas, contributing to health inequalities [3-5]. MLTC-M disproportionately affects those
living in areas of socio-economic deprivation and minority ethnic groups [6]. Most research on
MLTC-M has included patients aged over 65 years, however, almost a third of people with four or
more conditions are under this age [7].
Treatment burden represents the work that patients undertake because of their healthcare, and the
impact of that effort on patients [8, 9]. Younger populations may experience different challenges
that affect their treatment burden. Interventions focused on younger populations have the
potential, through addressing treatment burden at an earlier stage, to influence trajectories of
MLTC-M [10]
United Kingdom (UK) National Institute for Health and Care Excellence (NICE) MLTC-M guidance for
[11] recognises the need to reduce treatment burden [12]. However, no existing interventions have
shown convincing reduction of treatment burden for people living with MLTC-M [13-15].
Few qualitative studies have investigated the experience of treatment burden for people with MLTC-
M in primary care [16, 17]. A recent systematic review of the impact of interventions on patient-
2
reported burden of treatment included 11 studies, only one of which focussed on people living with
MLTC-M [14]. Available measures of treatment burden are too time consuming to be used in routine
clinical practice to identify patients at risk of being overburdened by the demands of their
healthcare. The multimorbidity treatment burden questionnaire (MTBQ) is a validated measure
developed to capture the effort required to manage MLTC-M [7]. It has been used to evaluate
treatment burden in two UK surveys, largely focused on people in older age groups, and more
affluent / minimally diverse populations [7, 18]. Each of these studies has evaluated the
performance of a different single-item measure alongside the MTBQ; these had limited sensitivity
and positive predictive value [18, 19]. Practical ways of measuring treatment burden in routine
primary care practice would be valuable, enabling identification of people who are more likely to be
over-burdened.
To our knowledge, no studies have explored the impact the organisation of primary care services has
on the treatment burden experienced by people with MLTC-M. This protocol describes a mixed-
methods study. The overarching aim is to understand the treatment burden associated with MLTC-M
for people aged 18-65 years, and how primary care services affect this burden, in order to inform
service design. We will:
1a) explore, in-depth, their experiences of treatment burden and its impact;
1b) explore the face validity of a short treatment burden screening questionnaire (STBQ).
2a) examine the factors associated with treatment burden for adults living with MLTC-M;
2b) test the validity of the STBQ for routine clinical use.
Method
Concurrent mixed-methods study including qualitative and quantitative components, and
stakeholder engagement (Figure 1).
[insert figure 1 here]
Theoretical Framework
The cumulative complexity model [20] is used as a theoretical framework for the study. It describes
the balance between the workload that an individual experiences because of their healthcare, and
the capacity they have to manage that workload.
Definition of multimorbidity
We will use the 20-condition Cambridge multimorbidity score to identify eligible participants [4, 21].
We will develop GP electronic record searches, based on the published code sets to identify people
with two or more of these 20 conditions.
Participants Adults (18-65 years) with two or more long-term conditions.
We will exclude people with dementia, those lacking capacity to consent, people receiving palliative
care, and nursing home or care home residents.
Inclusivity
People from ethnic minority groups are likely to report poorer health outcomes and experiences of
accessing health services than their white-British counterparts [6]. They are often under-represented
in research, limiting the relevance and generalisability of results.
3
We will seek to increase participation of people from ethnic minority groups and socio-economically
disadvantaged communities. All participant materials will be translated and back-translated into
commonly spoken languages in the study areas. Interpreters will be available for interviews.
Qualitative study
Design
Semi-structured qualitative interviews with adults living with MLTC-M exploring objectives 1a,b.
Sampling
We will recruit up to eight primary care practices across two geographical areas. Participants will be
purposively sampled to achieve maximal variation in practice-level deprivation and rurality; patient
age, gender, ethnicity, employment status, being a carer, and type of MLTC. Invitations will be sent
to eligible patients identified by electronic record searches in participating practices. Interested
people will contact the study team to arrange an interview in-person, by telephone or videocall.
Fully informed consent will be taken at the time of the interview (written or audio-recorded).
Data collection
Topic guides have been developed and piloted with input from the PPI (patient and public
involvement) group. In-depth interviews will focus on patients’ experiences of MLTC-M burden and
their capacity to manage the workload. We will explore how different health conditions interact how
the experience of burden changes with time and circumstances; how patients navigate primary care
services, and the impact of health services on MLTC-M burden and capacity. Interviews will be
audio-recorded, professionally transcribed, anonymised, and managed in NVivo 12.
Up to 15 initial interviews will explore participants’ thoughts about the STBQ. Participants will be
asked to think aloud [22] as they complete the measure, including commenting on the layout and
wording, and discussing the reasoning behind their questionnaire responses. These interviews will
be carried out in blocks of 3-5. At the end of each block, the data will be reviewed and the
questionnaire modified.
Participating patients will be offered a £25 shopping voucher.
Analysis
Analysis will involve two stages.
Objective 1a,b. Data analysis will be thematic [23], conducted by the interviewers, members of the
research team and up to two public contributors from the PPI group. Analysis will begin with line-by-
line coding, followed by discussion to agree the coding frame. Transcripts will be coded by one
researcher, and a randomly chosen sample will be reviewed independently by a second researcher.
The researchers will initially identify themes, which will then be discussed with other members of
the research team. Analysis will continue alongside data collection, allowing the topic guides to be
modified to respond to findings. Up to two members of the PPI group will be invited to contribute to
the analysis by (i) being involved in a facilitated discussion in which codes are developed and
researcher interpretations of the data checked; (ii) using selected extracts from transcripts to sense-
check, refine and expand themes.
4
Objective 1b. Framework analysis [24] will be conducted to analyse the think-aloud interviews. The
researchers will summarise the data within a framework matrix, based on the different aspects of
the questionnaire. The final version of the STBQ will be used in the survey.
Sample size and participant recruitment will be determined based on the concept of information
power [25]. Our analysis is informed by established theory, interviews will be focused on the
research questions, and we anticipate participants will have rich experiences relevant to the
research question. These factors will increase the information power of our sample. Sufficient
information power will be achieved when the sample is deemed to have addressed the study’s
research questions (we estimate 30-40 interviews).
Quantitative study
Design
Cross-sectional patient survey and analysis of linked routinely collected GP record data, addressing
objectives 2a, b.
Sampling
We will sample up to 25 primary care practices across two geographical areas in England, aiming to
recruit 50% of practices from Index of Multiple Deprivation (IMD) deciles 1-5 [with one being most
deprived and 10 least deprived] and at least 6 practices in deciles 1-3. Practices will run electronic
searches to identify eligible patients, and will invite a random sample of up to 500. Sample size
calculation is presented in Table 1.
[insert table 1 here]
Data collection
i. Survey
The measures included in the survey are described in Table 2.
[insert table 2 here]
ii. Medical records
Survey respondents will be asked to consent to access to their medical records. For consenting
participants, the following data will be collected and linked to the survey data for analysis: age, sex,
individual-level deprivation, number and type of long-term health conditions, number of prescribed
medications, and number and type of consultations in general practice. In addition, we will collect
anonymised data on the age, sex, deprivation level and number of long-term conditions of all
patients invited to complete the survey, facilitating comparison with the respondent sample.
Data management and analysis.
Data will be managed in a REDCap database and analysed using Stata 17. Unclear questionnaire data
will be treated as missing. Descriptive analyses will report MTBQ, PROMIS 10 and PCPCM by the
other variables of interest.
Regression analyses: We will investigate the association of MTBQ scores with the variables of
interest. We will explore three types of regression models: logistic regression where MTBQ scores
are dichotomised into those with and without high burden; ordinal logistic regression where the
MTBQ score is categorised into different levels of burden, and linear regression with the global
5
MTBQ scores as a continuous measure. Initially we will assess each of the variables of interest in
univariate models and will then build multivariable models using stepwise methods. Multicollinearity
will be assessed using variance inflation factors and we will consider non-linear associations for
numeric variables. Depending on missing data we will carry out complete case analyses and also
imputed analyses. The results from the linear regression will be presented as primary results with
the rest as a sensitivity analyses dependent on testing the assumptions in the regression models.
More details are available in Supplementary Material 1.
STBQ validation: Different versions of the STBQ will be explored through inter-item correlations,
internal consistency (Cronbach’s alpha), and comparison of the association between the STBQ with
high treatment burden as measured by the MTBQ using the receiver operator characteristic curve
and diagnostic parameters: sensitivity, specificity, positive and negative predictive values. We aim to
achieve the shortest possible questionnaire that has a high sensitivity.
Stakeholder engagement
We will hold three workshops in the two study sites. An early workshop will engage a diverse group
of people living with MLTC-M in discussions about the content of the interviews and survey. In two
late workshops we will engage with stakeholders representing patients, primary healthcare services,
commissioners and policy makers to identify the implications of our research findings.
Patient and Public Involvement
Our PPI group of eight members with lived experience of MLTC-M contributed to the development
of the research questions, the study protocol, study documentation, and the design of the survey
and qualitative topic guide. They will be involved in the analysis of the qualitative data,
interpretation and dissemination of the study findings.
Discussion
This study uses qualitative interviews with patients, and a cross-sectional patient survey linked to
routine data to understand treatment burden experienced by people 18-65 years living with MLTC-
M, and the ways in which the organisation of primary care services affects? this burden. Through the
qualitative research we will use the cumulative complexity model to understand how and why
treatment burden affects younger people and how workload and capacity interact [20]. Through the
cross-sectional survey with linked routine data we will identify the factors associated with treatment
burden, and associations between treatment burden and quality of life. Finally, we will seek to
validate a short treatment burden measure for use in routine clinical care. We will produce practical
recommendations for how primary care services can reduce treatment burden experienced by
people 18-65 years living with MLTC-M. This will lead to further development and testing of
interventions to reduce MLTC-M burden, with the potential to influence MLTC-M trajectories and
improve health outcomes.
6
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Table 1. Power for total sample size of 1000, baseline risk of high burden 20% and risk of high
burden 30% in group with characteristic of interest.
Prevalence of patient characteristic of interest a
0.2
0.25
0.3
0.35
0.4
0.45
0.5
POWER
84.4%
89.2%
92.1%
93.8%
94.9%
95.4%
95.6%
aFor example, patient living in a deprived area
Table 2. Survey measures
Concept
Measure
Description
Socio-
demographic
data
Age, gender, ethnicity
and employment
status
Participants are asked to describe:
age
gender
ethnicity (selecting from the list provided here:
https://www.ethnicity-facts-
figures.service.gov.uk/style-guide/ethnic-
groups)
employment status
Health status
a. PROMIS 10 [26, 27]
b. Self-reported long-
term conditions
a. A validated 10-item person-centered measure of
health and functioning for people with long-term
conditions. The questions are a better fit for our
purposes than those included in, for example, the SF-12.
b. One question asks the participant to list the
conditions they believe they have, that have or will last
longer than 6 months
Treatment
burden
a. The multimorbidity
Treatment Burden
Questionnaire
(MTBQ) [7]
b. Novel short
treatment burden
questionnaire
(STBQ)
a. The MTBQ is a concise, simply-worded set of
questions to measure treatment burden in people with
MLTC-M. In this study, we will use the 13-item
questionnaire.
b. Building on previous work to develop a single
question screening measure for treatment burden [18]
we have developed, with PPI input, the STBQ. It includes
two questions: one - to screen for high treatment
burden, and one – to understand what they find difficult
from a range of options. The STBQ has been developed
for use in clinical practice, rather than as a research tool.
It may be revised in response to feedback from initial
qualitative interviews.
Primary care
experience
PCPCM [28]
The PCPCM focuses on the patient’s access to care,
relationship with the doctor / practice, and ability to
reach health outcome goals. It comprises 11 items that
form an evaluation of access, continuity,
comprehensiveness, coordination, advocacy, family and
community context, and goal-oriented care.
Health
literacy
SILS [29]
A validated single-item screening instrument, designed
to identify patients with limited reading ability who need
help reading health-related materials.
Healthcare
use
Healthcare Use [30]
We will include five questions, adapted from Salisbury
and colleagues [30], asking whether participants have
recently stayed at an NHS hospital, visited A&E, and
taken time off work to attend hospital and GP
appointments.
Other
We may additionally include a small number of
questions from other validated questionnaires if it is
apparent from stakeholder work or initial qualitative
work that any issues create treatment burden for
patients which are not already included in the other
data sources proposed.
Figure 1. Study flowchart.
Qualitative patient interview study(months 1-25)
Cross-sectional patient survey (months 1-28)
Recruitment of primary care practices (n= up to 8)
Practices search electronic records to identify eligible participants, and
send invitations by post and SMS.
Practices search electronic records to identify eligible participants;
send invitations by post and SMS (first and reminder)
Survey completion (n = 1000)
Additional patient interviews (n = up to 25)
Data input and analysis
Mixed methods analysis
Recruitment of primary care practices (n = up to 25)
Workshop 1 (months 0-8)
Face-to-face or virtual workshops with patient stakeholders
To inform content of qualitative interviews / review survey materials
Extraction of routinely collected medical record data
Workshops 2 and 3 (months 22-24)
Face to face or virtual workshops with patient stakeholders to discuss the implications of the study findings
Writing up study reports
Data transcription and Interview analysis (n= approximately 40 interviews)
Initial patient interviews (n = up to 15) and rapid analysis to inform the
survey