Care plans and care planning in the management of long-term conditions in the UK: a controlled prospective cohort study

Reeves, David; Hann, Mark; Rick, Jo; Rowe, Kelly; Small, Nicola; Burt, Jenni; Roland, Martin; Protheroe, Joanne; Blakeman, Tom; Richardson, Gerry; Kennedy, Anne; Bower, Peter

doi:10.3399/bjgp14x681385

Cited by 24 publications

(28 citation statements)

References 35 publications

(19 reference statements)

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“…This is in line with previous work in a broader population of patients 37. Similarly, despite a very significant policy focus on care plans,38 many practices did not have a policy to provide them and most patients did not report receiving them.…”

Section: Discussionsupporting

confidence: 88%

Understanding usual care for patients with multimorbidity: baseline data from a cluster-randomised trial of the 3D intervention in primary care

et al. 2018

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ObjectivesRecent evidence has highlighted the high prevalence and impact of multimorbidity, but the evidence base for improving management is limited. We have tested a new complex intervention for multimorbidity (the 3D model). The paper describes the baseline characteristics of practices and patients in order to establish the external validity of trial participants. It also explores current ‘usual primary care’ for multimorbidity, against which the 3D intervention was tested.DesignAnalysis of baseline data from patients in a cluster-randomised controlled trial and additional data from practice staff.SettingPrimary care in the UK.ParticipantsPatients with multimorbidity (n=5253) and 154 practice staff.Primary and secondary outcome measuresUsing surveys and routinely available data, we compared the characteristics of participating and non-participating practices and participating and non-participating eligible patients.Baseline questionnaire data from patient participants was used to examine participant illness burden, treatment burden and perceptions of receiving patient-centred care. We obtained data about usual care preintervention from practice staff using questionnaires and a structured pro forma.ResultsParticipating practices were slightly larger, in less deprived areas, and with slightly higher scores for patient satisfaction compared with non-participating practices. Patients with dementia or learning difficulties were likely to be excluded by their general practitioners, but comparison of participants with non-participants identified only minor differences in characteristics, suggesting that the sample was otherwise representative. Patients reported substantial illness burden, and an important minority reported high treatment burden. Although patients reported relatively high levels of satisfaction with care, many reported not having received potentially important components of care.ConclusionThis trial achieved good levels of external validity. Although patients were generally satisfied with primary care services, there was significant room for improvement in important aspects of care for multimorbidity that are targeted by the 3D intervention.Trial registration numberISRCTN06180958; Post-results.

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Section: Discussionsupporting

confidence: 88%

Understanding usual care for patients with multimorbidity: baseline data from a cluster-randomised trial of the 3D intervention in primary care

et al. 2018

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“…Data for the analyses described here were originally collected as part of a wider cohort study designed to assess the impact of care planning on patient outcomes [7]. The current analyses use the baseline data from the cohort study.…”

Section: Methodsmentioning

confidence: 99%

“…The PACIC has been widely used in both validation studies and as an endpoint in outcomes research [4–7]. A short version for cardiovascular disease patients has been developed using factor analysis [8, 9] but despite the scale’s popularity, no analysis has been performed using modern test theories, including either parametric and non-parametric item response theory [10].…”

Section: Introductionmentioning

confidence: 99%

The Patient Assessment of Chronic Illness Care produces measurements along a single dimension: results from a Mokken analysis

Gibbons

Small

Rick

et al. 2017

Health Qual Life Outcomes

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BackgroundAs the worldwide prevalence of chronic illness increases so too does the demand for novel treatments to improve chronic illness care. Quantifying improvement in chronic illness care from the patient perspective relies on the use of validated patient-reported outcome measures. In this analysis we examine the psychometric and scaling properties of the Patient Assessment of Chronic Illness Care (PACIC) questionnaire for use in the United Kingdom by applying scale data to the non-parametric Mokken double monotonicity model.MethodsData from 1849 patients with long-term conditions in the UK who completed the 20-item PACIC were analysed using Mokken analysis. A three-stage analysis examined the questionnaire’s scalability, monotonicity and item ordering. An automated item selection procedure was used to assess the factor structure of the scale. Analysis was conducted in an ‘evaluation’ dataset (n = 956) and results were confirmed using an independent ‘validation’ (n = 890) dataset.ResultsAutomated item selection procedures suggested that the 20 items represented a single underlying trait representing “patient assessment of chronic illness care”: this contrasts with the multiple domains originally proposed. Six items violated invariant item ordering and were removed. The final 13-item scale had no further issues in either the evaluation or validation samples, including excellent scalability (Ho = .50) and reliability (Rho = .88).ConclusionsFollowing some modification, the 13-items of the PACIC were successfully fitted to the non-parametric Mokken model. These items have psychometrically robust and produce a single ordinal summary score. This score will be useful for clinicians or researchers to assess the quality of chronic illness care from the patient's perspective.

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“…As jointly developed strategies which outline the patient's preferences, needs and values for care, care plans are widely advocated as a means of individualising chronic disease care (159,(274)(275)(276). As such they have a valuable role in assisting clinicians and patients to deliberate and reach an agreement on care decisions.…”

Section: Care Plansmentioning

confidence: 99%

“…Empirical evidence indicates care plans can: enhance self-management practices (386); increase adherence to guideline recommendations (4); improve processes and clinical outcomes (387); and reduce or delay hospitalisation (388). However, the effectiveness of care plans relies on the care planning processes used and the clinician's and patient's desire and ability to participate in these processes (210,276,321).…”

Section: Introductionmentioning

confidence: 99%

Is Australian primary care practice equipped to provide multimorbidity care?

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Care plans and care planning in the management of long-term conditions in the UK: a controlled prospective cohort study

Cited by 24 publications

References 35 publications

Understanding usual care for patients with multimorbidity: baseline data from a cluster-randomised trial of the 3D intervention in primary care

Understanding usual care for patients with multimorbidity: baseline data from a cluster-randomised trial of the 3D intervention in primary care

The Patient Assessment of Chronic Illness Care produces measurements along a single dimension: results from a Mokken analysis

Is Australian primary care practice equipped to provide multimorbidity care?

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