BackgroundGlobally, health‐care systems and organizations are looking to improve health system performance through the implementation of a person‐centred care (PCC) model. While numerous conceptual frameworks for PCC exist, a gap remains in practical guidance on PCC implementation.MethodsBased on a narrative review of the PCC literature, a generic conceptual framework was developed in collaboration with a patient partner, which synthesizes evidence, recommendations and best practice from existing frameworks and implementation case studies. The Donabedian model for health‐care improvement was used to classify PCC domains into the categories of “Structure,” “Process” and “Outcome” for health‐care quality improvement.DiscussionThe framework emphasizes the structural domain, which relates to the health‐care system or context in which care is delivered, providing the foundation for PCC, and influencing the processes and outcomes of care. Structural domains identified include: the creation of a PCC culture across the continuum of care; co‐designing educational programs, as well as health promotion and prevention programs with patients; providing a supportive and accommodating environment; and developing and integrating structures to support health information technology and to measure and monitor PCC performance. Process domains describe the importance of cultivating communication and respectful and compassionate care; engaging patients in managing their care; and integration of care. Outcome domains identified include: access to care and Patient‐Reported Outcomes.ConclusionThis conceptual framework provides a step‐wise roadmap to guide health‐care systems and organizations in the provision PCC across various health‐care sectors.
ObjectivesExplore the experience of patients undergoing colorectal surgery within an Enhanced Recovery After Surgery (ERAS) programme. Use these experiential data to inform the development of a framework to support ongoing, meaningful patient engagement in ERAS.DesignQualitative patient-led study using focus groups and narrative interviews. Data were analysed iteratively using a Participatory Grounded Theory approach.SettingFive tertiary care centres in Alberta, Canada, following the ERAS programme.ParticipantsTwenty-seven patients who had undergone colorectal surgery in the last 12 months were recruited through purposive sampling. Seven patients participated in a codesign focus group to set and prioritise the research direction. Narrative interviews were conducted with 20 patients.ResultsPatients perceived that an ERAS programme should not be limited to the perioperative period, but should encompass the journey from diagnosis to recovery. Practical recommendations to improve the patient experience across the surgical continuum, and enhance patient engagement within ERAS included: (1) fully explain every protocol, and the purpose of the protocol, both before surgery and while in-hospital, so that patients can become knowledgeable partners in their recovery; (2) extend ERAS guidelines to the presurgery phase, so that patients can be ready emotionally, psychologically and physically for surgery; (3) extend ERAS guidelines to the recovery period at home to avoid stressful situations for patients and families; (4) consider activating a programme where experienced patients can provide peer support; (5) one size does not fit all; personalised adaptations within the standardised pathway are required.Drawing upon these data, and through consultation with ERAS Alberta stakeholders, the ERAS team developed a matrix to guide sustained patient involvement and action throughout the surgical care continuum at three levels: individual, unit and ERAS system.ConclusionThis patient-led study generated new insights into the needs of ERAS patients and informed the development of a framework to improve patient experiences and outcomes.
ObjectivesThe shift to the patient-centred care (PCC) model as a healthcare delivery paradigm calls for systematic measurement and evaluation. In an attempt to develop patient-centred quality indicators (PC-QIs), this study aimed to identify quality indicators that can be used to measure PCC.MethodsDesign: scoping review. Data Sources: studies were identified through searching seven electronic databases and the grey literature. Search terms included quality improvement, quality indicators, healthcare quality and PCC. Eligibility Criteria: articles were included if they mentioned development and/or implementation of PC-QIs. Data Extraction and Synthesis: extracted data included study characteristics (country, year of publication and type of study/article), patients’ inclusion in the development of indicators and type of patient populations and point of care if applicable (eg, in-patient, out-patient and primary care).ResultsA total 184 full-text peer-reviewed articles were assessed for eligibility for inclusion; of these, 9 articles were included in this review. From the non–peer-reviewed literature, eight documents met the criteria for inclusion in this study. This review revealed the heterogeneity describing and defining the nature of PC-QIs. Most PC-QIs were presented as PCC measures and identified as guidelines, surveys or recommendations, and therefore cannot be classified as actual PC-QIs. Out of 502 ways to measure PCC, only 25 were considered to be actual PC-QIs. None of the identified articles implemented the quality indicators in care settings.ConclusionThe identification of PC-QIs is a key first step in laying the groundwork to develop evidence-based PC-QIs. Research is needed to continue the development and implementation of PC-QIs for healthcare quality improvement.
Background Large‐scale transformation depends on effective engagement of diverse stakeholders. With the evolution of the role of the ‘patient partner’ in health‐care decision making, understanding the motivations of these individuals is essential to the success of engagement initiatives. This study reports on motivational factors associated with patient engagement in health care. Methods Patient co‐investigators and a researcher co‐designed and conducted this study. A survey was administered to patients and family members. Key informant interviews and previous research informed the development of the survey tool. The survey data were analysed using exploratory factor analysis to identify the underlying dimensions in the data. Cronbach's alpha was used to determine reliability. Results A total of 1449 individuals participated in the survey. Of these, 543 completed and 427 partially completed the survey (67% complete rate). The mean age of the respondents was 54 years. The majority of participants were female, well‐educated, retired, married and lived in an urban centre. Seven motivational factors explained 65% of the total variance. Analysis of internal consistency revealed acceptable reliability for all items. The seven motivations were as follows: Self‐fulfillment, Improving Healthcare, Compensation, Influence, Learning New Things, Conditional and Perks. Conclusion The results of this research describe a sample of patient and family members currently engaged with health systems. We identified seven motivational factors underlying their engagement. A deeper knowledge of volunteer motivations will not only create meaningful engagement opportunities for patients, but also enable health organizations to gain from the experience of these individuals, thereby enhancing quality and sustainability of patient engagement programmes.
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