Integrated primary care for patients with mental and physical multimorbidity

Integrated primary care for patients with mental and physical multimorbidity: cluster randomised controlled trial of collaborative care for patients with depression comorbid with diabetes or cardiovascular disease

Methods

Study design and participants

The Collaborative Interventions for Circulation and Depression (COINCIDE) trial was conducted by a multidisciplinary team as part of the Greater Manchester Collaboration for Leadership in Applied Health Research and Care (CLAHRC). CLAHRCs are innovative research programmes funded by the UK National Institute for Health Research that support evaluations of interventions most likely to be rapidly adopted in routine clinical practice. COINCIDE was a pragmatic practice level cluster randomised controlled trial with two parallel groups. The trial protocol has been previously published14 and updated.15

This trial was conducted in the English NHS in non-academic primary care general practices. We used a cluster design to avoid contamination of participants in the control group. General practices that held electronic registers of patients with diabetes and/or coronary heart disease were recruited across the north west of England between January and November 2012. Eligible patients were those with a record of diabetes and/or coronary heart disease registered at one of the participating practices who also had depressive symptoms (score ≥10 on the nine item patient health questionnaire (PHQ-9))16 for at least two weeks. Before postal invitations were sent, general practitioners checked the disease registers to exclude ineligible patients (aged under 18, recently deceased, no diabetes or coronary heart disease, or on the palliative care register). We excluded patients with psychosis or type I or type II bipolar disorder; those who were actively suicidal; those in receipt of services for substance misuse; or those in receipt of psychological therapy for depression from a mental health service.

Staff from the National Institute for Health Mental Health Research Network searched electronic records from participating general practices for eligible patients. Patients who met the eligibility criteria received a postal invitation, followed by a reminder letter three weeks later; non-responders to the reminder postal invitation were telephoned. To enhance recruitment of patients of South Asian origin an information flyer about the trial was included in Urdu and Gujarati; the information sheets and consent forms were also translated into Urdu and Gujarati. After the first postal invitation a researcher fluent in Urdu, Hindi, and Punjabi telephoned eligible patients of South Asian origin who did not speak English to provide further information about the study.

After receiving consent forms research staff screened patients for depressive symptoms over the telephone using the PHQ-916 and confirmed eligibility. Patients who scored ≥10 on the PHQ-9 were then visited by a researcher two weeks later and asked to complete a second PHQ-9. If patients also scored ≥10 on the PHQ-9 at the face-to-face visit they were invited to complete baseline assessments.

Randomisation and masking

General practices were randomised as they were recruited by using a central randomisation service provided by the clinical trials unit at the Christie NHS Foundation Trust, Manchester. Allocation of practices (other than the first six, which were allocated 1:1 at random) was by minimisation. This technique ensures “treatment groups that are very closely similar for several variables” even in small samples.17 We used only two practice level variables (index of multiple deprivation18 and list size) and incorporated a random element into this process by which practices were allocated to the trial arm that minimised the imbalance between characteristics with a probability weighting of 0.8.19 The allocation sequence was concealed from general practice staff and from all research staff, except the trial manager, the principal investigator, and the senior investigator with clinical supervisory responsibilities. Patients remained unaware of treatment allocation throughout the telephone screening and the baseline assessment appointments with research staff. Researchers who collected outcome data remained blinded to treatment allocation throughout the course of the trial. Because this trial used face-to-face psychological treatments it was not possible to maintain the blinding of participants beyond baseline or to blind the health professionals delivering the intervention.

Intervention and comparators

Collaborative care

Over three months, participants in the collaborative care arm received up to eight face-to-face sessions of brief psychological therapy delivered by a case manager who were “psychological wellbeing practitioners” employed by Improving Access to Psychological Therapies services in the English NHS. These services offer evidence based psychological treatments for people aged over 16, with no upper age limit, in accordance with stepped care treatment models recommended by NICE.20 Eighteen psychological wellbeing practitioners were involved in delivery of the intervention. Twelve of them were women; their mean age was 35 (SD 9.3); and they had a mean of 3.9 (SD 1.7) years of service.

The first treatment session aimed to be completed within 45 minutes during which the psychological wellbeing practitioner used a structured patient centred interview21 to gather information about the nature of the patient’s key problems, including their experience of the autonomic, behavioural, and cognitive symptoms associated with low mood and anxiety (the ABC model),22any modifying factors, and the impact of these symptoms, including level of risk. The link between the patient’s mood and management of their diabetes and/or heart disease was explored, and they were introduced to the standardised treatment manual and workbook (see appendix 1 and 2) to help develop a main problem statement and personalised goals. Subsequent sessions lasted for 30-40 minutes. Working with their psychological wellbeing practitioner, participants in the collaborative care arm chose to engage in behavioural activation, graded exposure, cognitive restructuring, and/or lifestyle changes. Treatments took place at the participant’s general practice clinic or at Improving Access to Psychological Therapies business premises.

To better achieve integrated care, a 10 minute collaborative meeting (by telephone or in person) between the patient and the psychological wellbeing practitioner and a practice nurse from the patient’s general practice was scheduled to take place at the end of the second and eighth sessions. Psychological wellbeing practitioners were guided by a manual to run these joint sessions (see appendix 3). These collaborative meetings focused on ensuring that psychological treatments did not complicate management of physical health and patient safety, reviewing patients’ progress with their problem statement and goals, reviewing relevant physical and mental health outcomes (such as depression, anxiety, diet, exercise), and planning future care. Psychological wellbeing practitioners also worked collaboratively with the patient and practice nurse to check that patients adhered to antidepressants as prescribed, dealt with concerns about side effects, and helped to arrange drug reviews with the general practitioner if necessary. In keeping with routine management of patients within Improving Access to Psychological Therapies services, psychological wellbeing practitioners monitored patients’ progress at each session, and delivery of care was structured in accordance with established stepped care protocols.23

Psychological wellbeing practitioners were trained in the COINCIDE collaborative care model over five days by a multidisciplinary team of psychological therapists, an academic general practitioner with special interests in mental health, and a primary care psychiatrist. Cultural competency training was delivered by a psychiatrist with special interests in translation of guided self help materials for people of South Asian origin. The training programme was piloted as part of a separate roll out of collaborative care in another region of the NHS24 and included sessions about diabetes and heart disease along with live and video demonstrations of each treatment session using simulated patients. The final training session focused on strategies for maintaining health and relapse prevention, effective liaison, supervision, and monitoring.

Practice nurses attended a half day workshop, where they met the psychological wellbeing practitioners tasked to work in their general practice and were introduced to the COINCIDE care model with an emphasis on effective liaison and delivering integrated physical and mental health care.

Psychological wellbeing practitioners received one hour of weekly individual supervision by an experienced psychological therapist within their service. New patients, patients at risk of self harm or harming others, poorly responding patients, and patients who did not attend were discussed at weekly supervision, and every case was reviewed during monthly case management supervision.25Supervisors could consult the trial clinical team about drug management. The COINCIDE team psychiatrist also visited Improving Access to Psychological Therapies teams to discuss how psychological wellbeing practitioners could work flexibly to respond to problems raised by patients—for example, by using the collaborative care approach to manage symptoms of anxiety or to manage depressive symptoms that were not linked to their long term condition. The trial psychiatrist also offered supervisors the option of telephone support.

Usual care

All participants received care as usual from their general practitioner, which could include referral for psychological therapy (including therapy provided by Improving Access to Psychological Therapies) and/or prescription of antidepressants. Psychological wellbeing practitioners who had been trained in the COINCIDE care model were restricted from working with patients allocated to control general practices.

Outcomes

All outcomes were collected at the individual participant level. Participants were followed up initially at six months. After a change in the protocol (see statistical analysis) participants were subsequently followed up at four months. To maximise retention, follow-up assessments were conducted when possible in person, although those who declined a visit were asked to complete the primary outcome measure over the telephone.

The primary outcome was the difference in the mean score on the 13 depression items of the symptom check list-90 (SCL-D13) four months after randomisation.26 The SCL-D13 has 13 items rated from 0-4, and the patients’ overall score on each item is an average of these ratings; higher scores indicate more severe depression. Secondary mental health outcomes were depression and anxiety measured with assessments used routinely in Improving Access to Psychological Therapies (PHQ-9 and generalised anxiety disorder-7 (GAD-7)27), and social support (ENRICHD social support inventory28). Physical health outcomes were global quality of life (WHOQOL-BREF29), disease specific quality of life (diabetes quality of life30 and Seattle angina questionnaire31), and disability (Sheehan disability scale (SDS)32). To assess change in behaviours and perceptions about managing long term conditions we assessed self management (health education impact questionnaire (heiQ)33), self efficacy,34 and illness beliefs (multimorbidity illness perceptions scale35). Process measures collected only at follow-up were patient centredness and care experience (patient assessment of chronic illness care (PACIC)36), and satisfaction with care (client satisfaction questionnaire (CSQ)37). The PACIC questionnaire is widely seen as a valid patient reported assessment of the delivery of high quality care for long term conditions and higher scores confirm hypothesised associations between shared decision making and assessments of quality of care and patient satisfaction.38

All secondary outcomes reported here were prespecified in the trial protocol but not prospectively registered in the trial register because of an administrative error on the part of the trial team.

Sample size

We powered the trial to have 80% power (α=0.05; intraclass correlation coefficient 0.06) to detect a difference between groups on the primary outcome at follow-up equivalent to a standardised effect size of 0.4, for which we required 15 practices per arm and 15 patients per cluster (n=450), allowing for 20% attrition. Our forecast was principally based on the findings of a pilot study of collaborative care in UK primary care that reported an effect size of 0.63 (95% confidence interval 0.08 to 1.07)39 and a subgroup analysis of 10 collaborative care trials that recruited patients with long term conditions (effect size −0.30, 95% confidence interval −0.39 to −0.21).13 We anticipated that the achievable effect size in populations with multimorbidity would be 0.4, which is a little under the average of these two previously published effect sizes.

Average recruitment in the first 11 practices was less than 15 patients per practice. We therefore increased the total number of clusters from 30 to 36, with a target of 10 patients per practice, to give 79% power to detect an effect of 0.4 under the same assumptions. The revised target sample was therefore 360 patients. To ensure that we recruited patients from the additional practices within the lifetime of the trial we reduced follow-up from six to four months. Changes to the protocol were made in agreement with the trial steering committee and published.15

Statistical analysis

We undertook intention to treat analyses for all clinical outcomes, reported in accordance with the Consolidated Standards of Reporting Trials guidelines extension for cluster trials.40 All analyses were undertaken in Stata 13, after a predefined analysis plan was shared with the data monitoring and ethics committee. We analysed outcomes at the end of follow-up using multiple linear regression with robust standard errors to account for the clustering of patients within practices.41 We controlled for baseline values of each outcome, patient age, sex, area deprivation (based on residential postcode), level of limitation of daily activities because of comorbidities,42 and use of antidepressants or antianxiety drugs (currently, previously, never); and at the practice level for the design (minimisation) factors of list size and area deprivation. Multiple imputation was used to estimate missing scale scores and other data values at both baseline and follow-up. It was based on chained equations with all primary and secondary outcomes (at both baseline and follow-up), patient demographics (age, sex, education), diagnoses (diabetes and/or heart disease), activity limitation, practice size, and deprivation. We used 10 multiple imputation sets to provide stability of results.43

We used multiple imputation for the main analysis because this generally provides less biased estimates of effect compared with a complete cases analysis.44 We ran two types of sensitivity analyses. To assess sensitivity of the results to multiple imputation we conducted a second analysis on complete cases that included all the same covariates as the main analysis. A further sensitivity analysis was undertaken, adding in a variable for length of follow-up, to determine if differential follow-up affected inferences. In all analyses we controlled for baseline values and clustering. We also report a further post hoc sensitivity analysis for the primary outcome using a restricted covariate set comprising the baseline outcome values and design factors (list size and area deprivation).

For outcomes with skewness outside the range (−1.5 to 1.5) or kurtosis outside the range (1.5 to 4.5), we used standard errors based on 1000 bootstrapped samples to derive confidence intervals and P values. To ease interpretation and to allow comparison with published studies, we estimated standard effect sizes as the difference in follow-up means divided by the pooled baseline standard deviation for all participants.

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