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Service Evaluation Project An evaluation of patient pathway and attrition inthe BTHFT Living with Pain Service
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An evaluation of patient pathway andattrition in the BTHFT Living with Pain
Service
Sarah Morrow
Commissioned by:
Dr Romy Sherlock (Clinical Psychologist)
and
Dr Fiona Purdie (Clinical Psychologist)
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Contents
1. Introduction..........................................................................................................................4
1.1 Definition and Prevalence of Chronic Pain .....................................................................4
1.2 Management of CP ..........................................................................................................4
1.2.1 Multidisciplinary pain services .................................................................................5
1.3 Predicting CP Treatment Outcome ..................................................................................6
1.3.1 Depression and self-efficacy as predictors of outcome ............................................7
1.4 The BTHFT Living with Pain Service.............................................................................8
1.5 Rationale for Service Evaluation Project .........................................................................8
1.6 Research Aims .................................................................................................................9
2. Methodology .........................................................................................................................9
2.1 Procedure .........................................................................................................................9
2.2 Ethics..............................................................................................................................10
2.3 Measures ........................................................................................................................10
2.4 Data Analysis .................................................................................................................10
3. Results .................................................................................................................................11
3.2 Descriptive Data.............................................................................................................11
3.2.1 Referral, introductory group and assessment stage.................................................11
3.2.2 Psychology..............................................................................................................12
3.2.3 Occupational Therapy (OT)....................................................................................12
3.2.4 Physiotherapy..........................................................................................................12
3.2.5 LwPG ......................................................................................................................12
3.3 Logistic Regression Analyses ........................................................................................13
3.3.1 Physiotherapy..........................................................................................................14
3.3.2 LwPG ......................................................................................................................14
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4. Conclusion and Discussion ................................................................................................15
4.1 Key Findings..................................................................................................................15
4.2 Patient Pathway and Attrition ........................................................................................16
4.3 Predicting Treatment Entry / Completion......................................................................18
4.4 Matched Care for CP .....................................................................................................19
4.5 Strengths and Limitations ..............................................................................................21
4.6 Key Recommendations ..................................................................................................22
4.7 Dissemination of Results ...............................................................................................22
5. References ...........................................................................................................................23
6. Appendices..........................................................................................................................31
6.1 Appendix One: Email Confirming Ethical Approval ....................................................31
6.2 Appendix Two: Description of Measures ......................................................................32
6.3 Appendix Three: Insignificant Findings ........................................................................33
6.4 Appendix Four: Self and Commissioner’s Appraisals...................................................34
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1. Introduction
1.1 Definition and Prevalence of Chronic Pain
Chronic pain (CP) is delineated by the International Association for the Study of Pain
(IASP) as pain which has persisted for longer than three months; which is considered average
tissue healing time (Wilson, 2017). The duration of the pain transforms it from a symptom of
an injury or illness to a medical problem in its own right. CP is a disabling condition with a
multidimensional impact on patients, their families and daily living (Preis et al., 2018).
In the UK, CP affects approximately 28 million people, generating substantial
healthcare and socioeconomic costs (Anderson & Wallace, 2018). For example, in 2016 over
£537 million was spent on providing medications for CP sufferers. Additional societal costs
include recurrent visits to primary care and referrals to secondary care, absenteeism or people
leaving the work force and benefit claims. (NICE, 2018). The problem is also set to increase
in-line with the ageing population, with prevalence and severity found to be greater in the
elderly demographic (Mansfield, Sim, Jordan, & Jordan, 2016). This in mind, having systems
in place that support effective and efficient management of the condition is growing ever more
paramount.
1.2 Management of CP
By definition, CP cannot be treated and cured in the traditional biomedical sense.
Instead, the patient must be equipped with skills to manage their long-term pain at an acceptable
level (Hylands-White, Duarte, & Raphael, 2017). Severely affected individuals can be referred
to specialist pain clinics delivered by secondary care providers. Individuals requiring this level
of care will typically present with complex and co-occurring difficulties such as anxiety,
depression and fatigue alongside impairments in physical, social and cognitive functioning
(Kailainathan et al., 2017). Notably, severe presentations are ever more present with a growing
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trend towards increasingly complex pain disorders (Schofield, 2014), making the need for a
multidisciplinary team (MDT) approach to treatment more crucial than ever.
Accordingly, national standards outline a ‘biopsychosocial’ framework for use in
specialist pain clinics which highlights the imperative for MDT working in the management of
CP (British Pain Society, 2013; Faculty of Pain Medicine, 2015; NHS England, 2013).
Explicitly, this is an integrative approach to patient care that necessitates input from a range of
disciplines (i.e. medical, psychology, occupational therapy, physiotherapy etc.) to meet these
needs and to optimise treatment efficacy.
1.2.1 Multidisciplinary pain services. Specialist multidisciplinary pain clinics
commonly incorporate Pain Management Programmes (PMPs). These are evidence-based
multidisciplinary packages of treatment grounded in the biopsychosocial model (Wilson,
2017). PMPs serve to reinforce non-pharmacological techniques and self-management
strategies and are underpinned by therapeutic models such as Cognitive Behaviour Therapy
(CBT) and Acceptance and Commitment Therapy (ACT). Typically, PMPs are delivered on a
weekly basis in group format over a course of 8-12 half-day sessions (British Pain Society,
2013). These sessions are facilitated by professionals from different disciplines and consist of
physical, psychological, medical and occupational themes (Hylands-White et al., 2017).
Robust research has concluded that the comprehensive multidisciplinary management
of CP, incorporating various strategies and specialist treatments, is a clinically effective and
cost-efficient alternative to single-discipline treatment or usual care (Flor, Fydrich, & Turk,
1992; Guzmán et al., 2001; Scascighini, Toma, Dober-Spielmann, & Sprott, 2008). Kamper et
al. (2015) reproduced these findings in a more recent systematic meta-analysis which included
41 randomised controlled trials (RCTs), consequently strengthening the research. However,
despite the breadth of literature documenting the efficacy of MDT working and PMPs,
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suboptimal care and treatment continues to be reported (Akashi, Yano, & Aruga, 2012; Kress
et al., 2015; McCarberg, Nicholson, Todd, Palmer, & Penles, 2008) and the burgeoning pain
epidemic remains evident. Moreover, patients can spend many years seeking help, often getting
stuck in a ‘revolving door’ seeing countless specialists. Ultimately, this engenders feelings of
hopelessness in patients and reinforces the considerable burden of CP on individuals and
society (Clare, Andiappan, MacNeil, Bunton, & Jarrett, 2013).
Several factors have been identified as problematic in CP care which may contribute
towards patients returning to services such as: lengthy delays in identification, diagnosis and
referral; extensive waiting times for appointments; lack of knowledge about CP and of the pain
clinic role by both patients and healthcare professionals alike (Kress et al., 2015; Price, 2012);
pain management being regarded a low priority within healthcare systems (Johnson, Collett, &
Castro-Lopes, 2013); PMPs not being widely offered and lacking in evidence for longevity of
favourable effects beyond 12 months (Kress et al., 2015; Takai, Yamamoto-Mitani, Abe, &
Suzuki, 2015; Wilson, 2017) and a high degree of variability in the provision and quality of
MDT approaches in pain clinics (Kailainathan et al., 2017). Another important factor that may
influence the ‘revolving door’ crisis is patients being referred for treatment who do not enter
or complete it.
1.3 Predicting CP Treatment Outcome
It is reasonable to deduce that patients who choose to not enter, drop out of or derive
the least benefit from treatment may continue to have unmet needs regarding pain management.
Therefore, these patients may be more likely to demonstrate increased healthcare utilisation in
attempts to find relief from suffering. In efforts to mitigate this, several researchers have
investigated variables in CP patients which may predict treatment outcome. (De Pauw et al.,
2015; Hopwood, Creech, Clark, Meagher, & Morey, 2008; Kerns & Rosenberg, 2000;
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McCracken & Turk, 2002; Pagé, Romero Escobar, Ware, & Choinière, 2017; Richmond &
Carmody, 1999; Van der Hulst, Vollenbroek-Hutten, & Ijzerman, 2005). Within these studies,
the term ‘outcome’ has been defined and measured across several domains including: treatment
completion; physical, psychological and social functioning; quality of life; healthcare
utilisation and others. Examined predictive factors have generally included individual
characteristics, personality traits and psychological features. Notably however, depression and
pain self-efficacy (i.e. confidence in one’s ability to perform specific tasks despite the pain) are
two of the more widely-researched predictive factors across the CP literature.
1.3.1 Depression and self-efficacy as predictors of outcome. Depression and CP are
each prevalent and often co-occur (Rayner et al., 2016). Evidence has shown their coexistence
to predict or relate to adverse effects on treatment outcomes and increased healthcare use (De
Pauw et al., 2015; Keeley et al., 2008; Kerns & Haythornthwaite, 1988; Newman, Kapoor, &
Thorn, 2018; Pagé et al., 2017; Rayner et al., 2016). Similarly, several studies have found that
patients with low pain self-efficacy experience poorer outcomes (Denison, Åsenlöf, &
Lindberg, 2004; Mannion, Helbling, Pulkovski, & Sprott, 2009; Nicholas et al., 2011; Turk &
Okifuji, 2002; Turner, Ersek, & Kemp, 2005). Notably, a recent systematic review found that
self-efficacy was the most commonly researched pain-related belief as a predictor of MDT
treatment adherence and concluded that it had credible value as a predictive factor (Thompson,
Broadbent, Bertino, & Staiger, 2016).
That said, several limitations to research in this area have been documented, such as:
the heterogeneity among studies in patient characteristics, treatment and outcomes; small
sample sizes and inconsistency in results (De Pauw et al., 2015; Thompson et al., 2016; Van
der Hulst et al., 2005). Furthermore, while depression and pain self-efficacy have been
extensively researched as predictors of treatment completion and other outcomes, their
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influence on a patient’s decision to enter or reject recommended treatment remains relatively
unexplored. This is surprising considering that earlier research highlighted a significant
percentage of people with CP decline treatment when offered (Turk & Rudy, 1990). Therefore,
this information could be valuable to CP services in helping to inform suitable referrals.
1.4 The BTHFT Living with Pain Service
The Bradford Teaching Hospital Foundation Trust (BTHFT) Living with Pain Service
(LwPS) is provided by St. Luke’s Hospital in Bradford and has been established for 20 years.
The service is central to CP management and offers a MDT approach to care and treatment.
The current pathway into the service involves referring patients to an initial introductory group,
where service information and education about CP is provided.
Following this, if the patient feels the service will be useful for them, they opt into the
service and are invited to attend an initial assessment at a later date. At this point, assessment
data is collected which includes the use of standardised measurement tools, namely the Patient
Health Questionnaire-9 (PHQ-9) (Kroenke, Spitzer, & Williams, 2001) and the Pain Self-
Efficacy Questionnaire (PSEQ) (Nicholas, 2007) to assess mood and self-efficacy
retrospectively. This information helps inform appropriate referrals to different aspects of the
service (i.e. psychology, occupational therapy, physiotherapy, speciality doctor and the PMP).
The PMP at the service is an 8-week programme facilitated by various professionals from
different disciplines and is underpinned by several therapeutic models.
1.5 Rationale for Service Evaluation Project
No previous evaluation of patient pathway within the LwPS has been undertaken.
Therefore, there is a lack of clarity around rates of attrition at each stage of the referral process
and limited understanding as to the number of patients that enter recommended treatment.
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Identifying which parts of the service experience the highest rates of attrition will be helpful
for service delivery because once this information is obtained, steps can be taken to better
streamline the referral process in these areas. Tackling this could help to significantly reduce
waiting lists for different parts of the service.
Secondly, exploring whether patient scores on measures of mood and self-efficacy can
predict subsequent treatment entry may also help shape service delivery. Identifying predictor
variables for those who are most likely to enter or successfully complete treatment is important
as it is information that can be used to inform screening procedures and inclusion / exclusion
criteria. Essentially, this may also contribute to helping reduce the ‘revolving door’ problem
also experienced in this service.
1.6 Research Aims
To examine patient pathway and attrition through the LwPS using existing data.
To examine whether patient assessment scores on measures of mood and self-efficacy
predict subsequent treatment entry within the LwPS.
2. Methodology
2.1 Procedure
A quantitative approach was employed as it was deemed the most suitable for meeting
the aims of the service evaluation project (SEP) and allowed for a large dataset to be studied.
Referrals into the LwPS during the financial year 2016 – 2017 were analysed to gain an
appropriate snapshot of patient pathway and attrition. Although this initially equated to
approximately 1000 referrals, the analysis included much less than this once those who had
opted out of the service were discounted. Pathways of those patients who opted in to an initial
assessment during this period but did not attend an introductory group were also examined.
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Gathering this information involved auditing case notes and registers for introductory groups.
Data from the two outcome measures administered during initial assessments (PHQ-9 and
PSEQ) was also gathered.
Once data for initial stages of the service had been collected, patient pathway was
tracked using the service’s clinical manager system to identify numbers referred and rates of
attrition for further services within the LwPS. Pathway for those referred to the speciality
doctor could not be tracked due to this information being stored on a separate inaccessible
system.
2.2 Ethics
Prior to data collection, ethical approval was sought from the University of Leeds
Service Evaluation Project (SEP) ethics committee. Approval was granted on 18th December
2017 and a copy of the confirmation email can be found in Appendix one.
2.3 Measures
The PHQ-9 (Kroenke et al., 2001) is a brief 9-item questionnaire that is commonly used
to measure depressive symptomology. The PSEQ (Nicholas, 2007) is a 10-item questionnaire
that measures a person’s belief in their ability to perform daily activities despite the pain. Both
measures have evidenced good psychometric properties (Kroenke et al., 2001; Nicholas, 2007).
Detailed descriptions of these and administration instructions are provided in Appendix two.
2.4 Data Analysis
Data was collated within a customised database which was developed using Microsoft
Excel. Descriptive statistics were undertaken to gain an overview of referrals, opt-ins,
attendance and attrition rates at different points of the service. Data was then analysed using
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Statistic Package for Social Sciences (SPSS) version 22. Binary logistic regression analyses
were used to establish whether patient scores on the PHQ-9 and the PSEQ significantly
predicted subsequent treatment entry for three parts of the service (physiotherapy, psychology
and OT). For the LwPG, more detailed information was available which included whether the
patient part of or fully completed the group in contrast to the other three services where only
attendance to the first appointment was analysed. This was therefore incorporated into the
analysis to generate more robust findings and multinomial logistic regression analysis was
employed for the LwPG.
3. Results
3.2 Descriptive Data
3.2.1 Referral, introductory group and assessment stage. In total, 1073 referrals
were made to the LwPS between 1st April 2016 and 31st March 2017. 368 patients (34.3%)
opted in to an introductory group during this period, indicating that 705 patients (65.7%) opted
out of this part of the service. Of the 368 who opted in, 363 patients (98.6%) attended an
introductory group during this financial year. Subsequently, 222 of these patients (61.1%)
attended an initial assessment.
Additionally, 209 patients opted in to an initial assessment during this period but had
not attended an introductory group. These patients were also included in the analysis. It is
important to note that these patients may have attended an introductory group in a previous
year, which could apply in cases where re-referrals had occurred. Some of these patients may
have also just opted out of an introductory group. However, information to clarify which of the
two events had happened was unavailable at the time of data collection. In total, 420 initial
assessments were included in the analysis. 345 (82.1%) of these patients were referred on to
one or more services within the LwPS.
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3.2.2 Psychology. 101 referrals were made to psychology. This included referrals made
for individual therapy and to a much lesser degree, a mindfulness group. At the time of data
collection, 35 patients (34.7%) had opted in to receive individual therapy and were still on the
waiting list for this input. 39 patients (38.6%) had attended at least an initial psychological
assessment or a first group session. However, 27 patients (26.7%) had either not opted in to be
placed on the waiting list for individual therapy or had opted in to psychological intervention
but then did not attend their appointment.
3.2.3 Occupational Therapy (OT). 81 referrals were made to OT, 14 (17.3%) of these
were made to social services OT for equipment-related matters or to out of area occupational
therapists, therefore this data was either inapplicable or inaccessible. 61 patients (75.3%) were
seen for at least an initial OT assessment and 6 patients (7.4%) did not opt in or attend
assessment at this stage.
3.2.4 Physiotherapy. 139 referrals were made to physiotherapy, 6 patients (4.3%) were
referred to out of area physiotherapists, therefore this data was inaccessible. 105 (75.5%) were
seen for at least an initial physiotherapy assessment and 28 (20.2%) patients did not opt in or
attend assessment at this stage.
3.2.5 LwPG. 144 referrals were made to the LwPG. 82 patients (56.9%) fully
completed the group, 9 patients (6.3%) part-completed the group and 53 (36.8%) did not opt
in or attend. Figure 1 provides an overview of patient pathway and attrition at various stages
within the LwPS.
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Figure 1. Consort diagram of patient pathway and attrition
3.3 Logistic Regression Analyses
Of the 345 patients that were referred to further services, 10 patients had missing PHQ-
9 scores and 14 patients had missing PSEQ scores. Those on the waiting list for psychology
and those referred to out of area services or social services OT were excluded from this part
of the analysis. No significant results were found for the PSEQ and all insignificant outputs
can be found in Appendix three. However, patient scores on the PHQ-9 were found to
Referrals(n = 1073)
Introductory groupOpted in: (n = 368)Attended: (n = 363)
DNA: (n = 5)
Assessment – Attended 16 – 17 introgroup
Opted in: (n = 247)Attended: (n = 222)
DNA: (n = 25)
Referrals to further servicesTotal assessments: (n = 420)
Referred to further services: (n = 345)Not referred to further services: (n = 75)
PsychologyReferrals: (n = 101)Waiting list: (34.7%)
Attended: (38.6%)Opted out / DNA:
(26.7%)
OTReferrals: (n = 81)Out of area: (17.3%)Attended: (75.3%)Opted out / DNA:
(7.4%)
PhysiotherapyReferrals: (n = 139)Out of area: (4.3%)Attended: (75.5%)Opted out / DNA:
(20.2%)
LwPGReferrals: (n = 144)Completed: (56.9%)
Part-completed: (6.3%)Opted out / DNA:
(36.8%)
Assessment – DNA 16 – 17 introgroup
Opted in: (n = 209)Attended: (n = 198)
DNA: (n = 11)
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significantly predict treatment entry for physiotherapy and to some degree, treatment
completion for the LwPG.
3.3.1 Physiotherapy. Patient scores on the PHQ-9 at initial assessments significantly
predicted treatment entry for physiotherapy, ܾ= 0.08, Wald ଶ(1)ݔ = 5.57, = 0.02. The odds
ratio tells us that as this variable increased, i.e. as PHQ-9 scores increased, the change in the
odds of treatment entry was 1.08. Essentially, patients with higher scores on the PHQ-9
(indicating increased severity in low mood) were more likely to attend their first physiotherapy
appointment than those with lower PHQ-9 scores. Table 1 summarises these findings.
Table 1. Summary of significant findings for physiotherapy
95% CI for Odds Ratio
B (SE) Lower Odds Ratio Upper
Included
Constant -2.58** (0.61)
PHQ-9 .08* (0.03) 1.01 1.08 1.15
Note: ܴଶ = .41 (Hosmer & Lemeshow), .05 (Cox & Snell), .07 (Nagelkerke). Model ଶݔ (1) = 6.21, > .05.* > .05, ** > .001
3.3.2 LwPG. There were contrasting outputs for the LwPG. The full model (i.e. PHQ-
9 & PSEQ as predicting variables) did not significantly predict ) = .3) better than the null
model (i.e. a model with no predicting variables). Additionally, Psuedo ܴଶ values (i.e. results
of the Cox & Snell and Nagelkerke tests highlighted in Table 2) indicate that this model only
accounts for between 3-4% of the variance in the dependent variable, therefore implying that
the full model is likely to be a low predictor. However, this contrasts with the Goodness of Fit
test which is non-significant =) .33), therefore suggesting the model is indeed a good fit.
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Findings for the PHQ-9 were significant but only predicted a small amount, ܾ = -.07,
Wald ଶ(1)ݔ = 4.40, = 0.04. The odds ratio tells us that as this variable increased, i.e. as PHQ-
9 scores increased, the change in the odds of completing the program (rather than not attending
at all) was .93. This indicated that patients with higher scores on the PHQ-9 were less likely to
complete the program than not attend. Table 2 summarises these findings.
Table 2. Summary of findings for the LwPG
95% CI for Odds Ratio
B (SE) Lower Odds Ratio Upper
Full Completion vs. Non-attendance
Intercept 1.72 (.72)*
PHQ-9 -07 (.03)* .88 .93 1
PSEQ -.01 (.02) .96 .99 1.03
Part-attendance vs. Non-attendance
Intercept - .83 (1.35)
PHQ-9 - .06 (.06) .83 .94 1.07
PSEQ .00 (.03) .94 1 1.07
Note: ܴଶ = .03 (Cox & Snell), .04 (Nagelkerke). Model ଶݔ (4) = 4.91, < .05. *p < .05.
4. Conclusion and Discussion
4.1 Key Findings
This SEP was undertaken to gain a snapshot of referral pathways and rates of attrition
at different points throughout the LwPS. There was an additional focus on whether patient
scores on measures of mood and pain self-efficacy could predict subsequent treatment entry.
With these aims in mind, the following findings are of importance:
There was a large attrition rate between point of referral and introductory group.
However, some may have attended an introductory group in a previous year. Therefore,
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interpretations of attrition rates between referral and opt in to introductory group should
be tentative considering this.
The LwPG had the most referrals but the largest opt-out / DNA rate across treatment
groups with approximately 1/3 patient attrition.
1/3 patients were still on the waiting list for individual psychology at the time of data
collection, indicating an average waiting list period of 15 - 18 months.
Higher PHQ-9 scores at initial assessment significantly predicted more likelihood of
attending first physiotherapy appointments. In contrast, high PHQ-9 scores were found
to somewhat contribute to a decrease in likelihood of completing the LwPG. However,
the latter result should be interpreted with caution due to the results of this particular
regression analysis’
4.2 Patient Pathway and Attrition
Although conclusions must be tentative regarding the attrition rate between referral and
introductory group, the magnitude of this figure still allows some inferences to be drawn. This
attrition rate may imply some reluctance in patients opting in to the service and may indicate a
need to liaise more closely with stakeholders / referrers to explore reasons for this, e.g.
inappropriate referrals or patients not fully consenting.
In-part, these issues may stem from a lack of knowledge about speciality CP service
provision by all those involved at the point of referral, which research has found is a common
problem (Chronic Pain Policy Coalition, 2015; Kress et al., 2015). Providing further education
to healthcare professionals about the pain clinic role may consequently allow patients to feel
more empowered and make more informed decisions regarding treatment opt-in. Furthermore,
there is a gap for an overarching national clinical guideline for all types of CP, including cases
where no underlying condition can be found. Importantly, the National Institute for Health and
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Care Excellence (NICE) have announced that a guideline of this nature will soon be
disseminated (NICE, 2018), which may also assist clinicians when making decisions about
referrals.
Noticeably, it seems that most patients who opted in at introductory group and
assessment stage subsequently attended these parts of the service, indicating a lower need for
intervention at these steps. The LwPG received the most referrals but had the largest opt-out /
DNA rate across treatment groups (36.8% or approx. 1/3 patients). This was closely followed
by the attrition rate for psychology (26.7% or approx. 1/4 patients) and physiotherapy (20.2%
or approx. 1/5 patients). Interestingly, the attrition rate for OT was much lower (7.4%). While
there may be several reasons for this, one possibility is the higher incidence of home-based
visits that may be facilitated by the OT team given the nature of this treatment option. In
contrast, the LwPG, psychology and physiotherapy are more likely to offer a clinic-based
appointment system. This is an important distinction as many patients may have transportation
difficulties, perhaps due to CP, which may inhibit them from attending appointments. Where
possible, employing resources that promote more flexibility to facilitate appointments outside
of the clinic setting may help accommodate this need and consequently reduce rates of attrition
across the three services.
Another factor that may influence attrition and consequently the ongoing
undertreatment of CP is lengthy waiting lists. A systematic review found that wait-times for
CP treatment of 6 months or longer were associated with a significant decrease in patient
quality of life and psychological well-being (Lynch et al., 2008). In turn, this could conceivably
affect patient ability and motivation to engage in treatment. This is concerning considering
around 1/3 patients (34.7%) were still on the waiting list for individual psychological therapy,
indicating an average wait-time of 15 – 18 months from point of referral.
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A waiting list this lengthy is a patent example of demand outstripping resource, which
generally speaking is a common cause for concern across publicly funded psychological
therapy services within the UK (Beck, Burdett, & Lewis, 2015). One obvious solution for this
would be allocating more resources to those services in higher demand, such as psychological
therapy, which could create a more streamlined referral process. Moreover, investing additional
resources in this area could arguably be vital in helping to improve the ‘revolving door’
situation considering the extent of robust research demonstrating wide-ranging positive effects
of psychological interventions in CP services (Hoffman, Papas, Chatkoff, & Kerns, 2007;
Williams, Eccleston, & Morley, 2012).
4.3 Predicting Treatment Entry / Completion
The results for physiotherapy demonstrated significant findings for both the final model
and the PHQ-9, signifying a good level of confidence in these results. Fundamentally, patient
scores on the PHQ-9 significantly predicted treatment entry for physiotherapy. However, there
were inconsistent findings between the final model and PHQ-9 outputs for the LwPG. For this
part of the service, results highlighted that the final model (including both the PSEQ and PHQ-
9) did not significantly predict outcome (group completion) any better than the null model.
Furthermore, pseudo ܴଶ values suggested that the full model is likely to be a low predictor.
However, this contrasted with the model’s Goodness to Fit value and findings for the PHQ-9
scores, which were found to contribute a small amount to the likelihood of completing the
LwPG. Although findings for physiotherapy suggest there are probably other variables that
also influence treatment entry, the conflict across outputs for the LwPG likely indicates that
many other variables are at play, alongside the PHQ-9, which may also be contributing towards
the outcome. Consequently, conclusions and recommendations regarding this finding must
remain tentative.
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Although no significant results were found for the PSEQ, findings for the PHQ-9 were
interesting. For physiotherapy, findings suggest that those with higher scores on this measure
were more likely to attend their first appointment. In contrast, findings for the LwPG make
some indication that those with higher PHQ-9 scores were more likely to not attend than
complete the group. However, it is important to highlight the odds ratios for both significant
results, as both are only marginally under and over 1. This therefore implies less strength
regarding the directionality of these findings. Nonetheless, it is equally important to give
credence to these results given that significant predictive relationships were established for
both, albeit a weaker one for the LwPG. Whilst there may be several reasons for the opposing
directionality, one possibility may be related to the differences in treatment modalities.
The LwPG promotes self-management strategies and is underpinned by psychological
principles. Conversely, physiotherapy is focussed on restoring physical function and is a more
medically-aligned treatment. Research has found that patients with comorbid pain and
depression are associated with more intensive use of general medical services but lower rates
of use of mental health services (Bao, Sturm, & Croghan, 2003). These findings, therefore,
may support this research. However, considering no significant predictive relationship was
found between PHQ-9 scores and attendance to psychology, this limits the reliability of this
hypothesis. One approach that could be useful for service development, whilst acknowledging
the tentative nature of findings for the LwPG, could be adapting the model of care that is used
in the LwPS.
4.4 Matched Care for CP
A matched or stratified model is an approach to care and treatment which involves
‘matching’ a patient to the most appropriate treatment to meet their needs (Joice, Freeman,
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Toplis, & Bienkowski, 2010). The use of screening tools are central to informing decisions
about appropriate referrals and treatment pathways within a matched care system.
Matched care approaches implemented in pain services have been found to be both
clinically and cost effective when compared to non-matched control groups (Foster, Hill,
Doyle, & Young, 2014; Hill et al., 2011). In both studies, a prognostic screening tool was used
to allocate patients into one of three risk-defined groups (low, medium or high). Treatment
pathways were then developed and matched to these three groups. There are similarities
between this system and the current approach in the LwPS in terms of using the measures to
help inform referrals. However, considering the findings in this evaluation for the PHQ-9,
perhaps scores on this measure can play a more pivotal role when making treatment decisions.
On the PHQ-9, a score of 10 or above would place a patient in the clinical range and
would be suggestive of someone who meets the criteria for moderate to severe depression
(Clark & Oates, 2014). In many matched care models, this clinical cut score would be used as
grounds for service inclusion / exclusion. However, this cut score should not be strictly used in
this way for the LwPG given the likely interplay of several variables that were found to
influence treatment completion. Instead, the measure could be used more flexibly, alongside
clinical judgement, to identify those who may benefit from additional support prior to being
referred to the LwPG. For instance, patients scoring in the clinical range could be first offered
more intensive support in the form of support worker provision or it may be useful to explore
a referral to primary care with the patient to address their low mood before offering the LwPG.
Similarly, adaptations could be made for those referred to physiotherapy who score in the non-
clinical range on the PHQ-9, or who are deemed less-distressed. This could involve having
more detailed discussions with these patients about the service to help them make more
informed decisions before opting in.
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Overall, this system could enable a more streamlined referral process for these parts of
the service. A matched care approach helps identify those who are unlikely to enter or engage
with treatment and it is argued that doing this is more ethical to the patient, less frustrating for
the treatment staff and more cost efficient for services and organisations than offering treatment
to all patients (Turk & Rudy, 1990).
4.5 Strengths and Limitations
A key strength of this SEP is that it is the first comprehensive overview of patient
pathway and attrition within the BTHFT LwPS. The results have highlighted a need for a
review of current referral protocols and procedures that should involve all stakeholders.
Nevertheless, the study is not without its limitations.
Firstly, for those who attended an assessment during this period but not an introductory
group, the inability to clarify whether they had attended one in a previous year limited
generalisations that could be made about attrition between referral and opt in to the introductory
group. Secondly, the analysis of treatment completion for one group in combination with the
analysis of treatment entry for the other three parts of the service is important to bear in mind
when using the information to inform service delivery. If possible, it may be useful for any
further analysis to evaluate either treatment entry or treatment completion to better balance the
focus of the evaluation. Thirdly, the contrasting outputs for the LwPG means that firm
conclusions cannot be drawn and only light recommendations can be made. Fourthly,
approximately 1/3 patients were still on the waiting list for psychology and it is plausible that
predictive results may have been different if many had not still been waiting for treatment.
Finally, due to the quantitative nature of this evaluation, conclusions cannot be drawn about
the reasons for patient attrition at different parts of the service. Further qualitative investigation
would be required to explore this.
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4.6 Key Recommendations
Considering the results of this SEP, the following recommendations have been made:
To liaise more closely with referrers and primary care clinicians to explore reasons for
large attrition rates between referral and opt in to introductory group. This could involve
providing more education about the LwPS to professionals and developing materials /
resources that could be given to patients about the service.
To consider investing more resources to those services in higher demand to help
decrease wait-list times. Also, providing more flexibility where possible to facilitate
appointments outside of the clinic setting may alleviate patient attrition.
To consider implementing a flexible ‘matched care’ approach to treatment which uses
the PHQ-9 in collaboration with clinical judgement and patient input to inform referral
decisions.
4.7 Dissemination of Results
This SEP was presented to the Leeds Clinical Psychology Doctorate Course and to
local clinical psychologists at a University of Leeds poster conference. It will also be
presented at the BTHFT LwPS team meeting in due course.
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6. Appendices
6.1 Appendix One: Email Confirming Ethical Approval
Received on: 18th December 2017 at 17.26 by Debby Williams (Programme Co-ordinator)
“Dear Sarah
I have now received approval from the reviewers for your ethics, so you are now cleared tostart collecting data for your project.
Kind regards
Debby”
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6.2 Appendix Two: Description of Measures
The Patient Health Questionnaire–9 (PHQ-9). The PHQ-9 (Kroenke et al., 2001) is
a brief 9-item questionnaire that is commonly used to measure depressive symptomology.
Items are rated on a scale from 0 ‘not at all’ to 3 ‘nearly every day’ in relation to their
experiences over the past two weeks. The measure has demonstrated excellent internal
reliability (Cronbach a = .89), good test-retest reliability (.84), good construct validity, good
external validity and good sensitivity to change (88%) (Kroenke et al., 2001).
The Pain Self-Efficacy Questionnaire (PSEQ). The PSEQ (Nicholas, 2007) is a 10-
item questionnaire that measures a person’s belief in their ability to perform daily activities
despite the discomfort caused by the pain. Participants are asked to rate their self-confidence
in different life domains on a 7-point likert-type scale. Total scores range from 0 to 60, with
lower scores reflecting reduced pain self-efficacy. The PSEQ has been shown to have excellent
internal reliability (Cronbach a = .92) (Nicholas, 2007).
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6.3 Appendix Three: Insignificant Findings
Psychology.
Table 3. Results of binary logistic regression for psychology
Score df. Sig.
Step 0 Variables PHQ-9 .00 1 .99
PSEQ .03 1 .86
Overall Statistics .04 2 .98
OT.
Table 4. Results of binary logistic regression for OT
Score df. Sig.
Step 0 Variables PHQ-9 .64 1 .43
PSEQ .40 1 .53
Overall Statistics .86 2 .65
Physiotherapy.
Table 4. Results of binary logistic regression for physiotherapy which includes the
significant finding for the PHQ-9
Score df. Sig.
Step 0 Variables PHQ-9 5.85 1 .02
PSEQ .35 1 .56
Overall Statistics 5.86 2 .05
LwPG. The insignificant findings for the PSEQ for this part of the service has been
included in the main body of the report.
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6.4 Appendix Four: Self and Commissioner’s Appraisals