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      Validation of the person-centred coordinated care experience questionnaire (P3CEQ)

      1 , 2 , 1 , 3 , 3
      International Journal for Quality in Health Care
      Oxford University Press (OUP)

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          Abstract

          Abstract Background Measuring patient experiences of healthcare is increasingly emphasized as a mechanism to measure, benchmark and drive quality improvement, clinical effectiveness and patient safety at both national and local NHS level. Person-centred coordinated care (P3C) is the conjunction of two constructs; person-centred care and care coordination. It is a complex intervention requiring support for changes to organizational structure and the behaviour of professionals and patients. P3C can be defined as: ‘care and support that is guided by and organized effectively around the needs and preferences of individuals’. Despite the vast array of PRMS available, remarkably few tools have been designed that efficiently probe the core domains of P3C. This paper presents the psychometric properties of a newly developed PREM to evaluate P3C from a patient perspective. Methods A customized EMIS search was conducted at 72 GP practices across the South West (Somerset, Devon and Cornwall) to identify 100 patients with 1 or more LTCs, and are frequent users of primary healthcare services. Partial Credit Rasch Modelling was conducted to identify dimensionality and internal consistency. Ecological validity and sensitivity to change were assessed as part of intervention designed to improve P3C in adults with multiple long-term conditions; comparisons were drawn between the P3CEQ and qualitative data. Results Response rate for the P3CEQ was 32.82%. A two-factor model was identified. Rasch analysis confirmed unidimensionality of each factor (using infit MSQ values between 0.5 and 1.5). High internal consistency was established for both factors; For the Person-centred scale Cronbach’s Alpha = 0.829, Person separation = 0.756 and for the coordination scale Cronbach’s alpha = 0.783, person separation = 0.672. Conclusions The P3CEQ is a valid and reliable measure of P3C. The P3C is considered to have strong face, construct and ecological validity, with demonstrable sensitivity to change in a primary healthcare intervention.

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          Most cited references13

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          Patient-centredness: a conceptual framework and review of the empirical literature.

          A 'patient-centred' approach is increasingly regarded as crucial for the delivery of high quality care by doctors. However, there is considerable ambiguity concerning the exact meaning of the term and the optimum method of measuring the process and outcomes of patient-centred care. This paper reviews the conceptual and empirical literature in order to develop a model of the various aspects of the doctor-patient relationship encompassed by the concept of 'patient-centredness' and to assess the advantages and disadvantages of alternative methods of measurement. Five conceptual dimensions are identified: biopsychosocial perspective; 'patient-as-person'; sharing power and responsibility; therapeutic alliance; and 'doctor-as-person'. Two main approaches to measurement are evaluated: self-report instruments and external observation methods. A number of recommendations concerning the measurement of patient-centredness are made.
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            Measuring patient-centered communication in patient-physician consultations: theoretical and practical issues.

            The goal of patient-centered communication (PCC) is to help practitioners provide care that is concordant with the patient's values, needs and preferences, and that allows patients to provide input and participate actively in decisions regarding their health and health care. PCC is widely endorsed as a central component of high-quality health care, but it is unclear what it is and how to measure it. PCC includes four communication domains: the patient's perspective, the psychosocial context, shared understanding, and sharing power and responsibility. Problems in measuring PCC include lack of theoretical and conceptual clarity, unexamined assumptions, lack of adequate control for patient characteristics and social contexts, modest correlations between survey and observational measures, and overlap of PCC with other constructs. We outline problems in operationalizing PCC, choosing tools for assessing PCC, choosing data sources, identifying mediators of PCC, and clarifying outcomes of PCC. We propose nine areas for improvement: (1) developing theory-based operational definitions of PCC; (2) clarifying what is being measured; (3) accounting for the communication behaviors of each individual in the encounter as well as interactions among them; (4) accounting for context; (5) validating of instruments; (6) interpreting patient ratings of their physicians; (7) doing longitudinal studies; (8) examining pathways and mediators of links between PCC and outcomes; and (9) dealing with the complexity of the construct of PCC. We discuss the use of observational and survey measures, multi-method and mixed-method research, and standardized patients. The increasing influence of the PCC literature to guide medical education, licensure of clinicians, and assessments of quality provides a strong rationale for further clarification of these measurement issues.
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              Estimating ordinal reliability for Likert-type and ordinal item response data: A conceptual, empirical, and practical guide

              This paper provides a conceptual, empirical, and practical guide for estimating ordinal reliability coefficients for ordinal item response data (also referred to as Likert, Likert-type, ordered categorical, or rating scale item responses). Conventionally, reliability coefficients, such as Cronbach’s alpha, are calculated using a Pearson correlation matrix. Ordinal reliability coefficients, such as ordinal alpha, use the polychoric correlation matrix (Zumbo, Gadermann, & Zeisser, 2007). This paper presents (i) the theoretical-psychometric rationale for using an ordinal version of coefficient alpha for ordinal data; (ii) a summary of findings from a simulation study indicating that ordinal alpha more accurately estimates reliability than Cronbach's alpha when data come from items with few response options and/or show skewness; (iii) an empirical example from real data; and (iv) the procedure for calculating polychoric correlation matrices and ordinal alpha in the freely available software program R. We use ordinal alpha as a case study, but also provide the syntax for alternative reliability coefficients (such as beta or omega). Accessed 35,197 times on https://pareonline.net from January 17, 2012 to December 31, 2019. For downloads from January 1, 2020 forward, please click on the PlumX Metrics link to the right.
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                Author and article information

                Journal
                International Journal for Quality in Health Care
                Oxford University Press (OUP)
                1353-4505
                1464-3677
                December 01 2018
                December 01 2018
                Affiliations
                [1 ]School of Psychology/Cognition institute, University of Plymouth, UK
                [2 ]University of Plymouth Faculty of Medicine and Dentistry, John Bull Building, Plymouth Science Park, Research Way, Plymouth, UK
                [3 ]Plymouth University, Peninsula Schools of Medicine and Dentistry, NIHR CLAHRC, South West Peninsula (PenCLAHRC), 1 Davy Road, Plymouth Science Park, Plymouth, UK
                Article
                10.1093/intqhc/mzy212
                734b329a-bfcb-4a7e-8299-26967bd70e0d
                © 2018

                http://creativecommons.org/licenses/by/4.0/

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