International Journal of Health Planning and Management最新文献

The purpose of this paper is to study the evolution of LTLI in the UK between the pre- and post-Covid years of, respectively, 2019 and 2022 paying attention to differences in the propensity to LTLI between different subgroups of the population in each of the two years and then examining whether the propensity to LTLI changed between the years, both in respect of overall change and in respect of the separate population subgroups. This was achieved using UK Labour Force Survey data for 2019 and 2022. In terms of the social gradient to health, persons in the Managerial/Professional classes had a significantly higher PP (predicted probability) of N-LTI (i.e., of not having a long-term illness) than persons either in the Routine non-Manual or Routine Manual classes and also had a significantly lower PP of LTLI-lot (i.e., of having a long-term illness which limited activity by a lot) than persons either in the Intermediate or in the Routine Manual or Routine non-Manual classes. This was true in both 2019 and 2022. In other words, there was significant inequality in the PP of LTLI associated with the occupational classes. In terms of changes in the propensity to LTLI, the PP of having a long-term illness—regardless of whether it was limiting or not - was significantly higher in 2022 than it was in 2019 both for the overall population and for its subgroups.

In the quest for healthcare systems enhancement, the improvement of patient experience plays a central role. The challenge lies in converting patient-reported experience data into actionable knowledge for quality improvement. This study aims to investigate the use of patient-reported data as knowledge base for actions and to identify and map actions derived from the use of patient-experience data within two Italian regional healthcare systems. Patient Experience Data are systematically collected in both systems, providing real-time updates accessible by professionals and managers through web-based reporting systems and including a collaborative network among practitioners. A sequential exploratory mixed-method study was carried out in several qualitative and quantitative phases. In the first phase, a qualitative method was conducted to discuss the actionability of patient-reported data and to design a tool for collecting the improvement actions based on these data. In the second phase, a quali-quantitative survey was performed to explore the professionals' use of patient-reported information and the types of actions implemented. Finally, a workshop was held to discuss, interpret and validate the results. The initial workshop identified key dimensions for improvement initiatives. After design and distribution of survey, a total of 189 responses was collected, respectively 96 from Region A and 93 from Region B. Both regions ensured widespread use of patient-reported data (89%). The establishment of a collaborative network seemed to reduce the learning curve in using patient-reported data and fostered a culture of using patient feedback effectively. The results reveal a difference between the two regions, with a more extensive patient-reported data use in Region A, attributed to its systematic joining the PREMs Observatory, prior experiences with patient-feedback collection and use, and patient-experience indicators integrated into the performance evaluation system. Regarding practices of data use, four themes emerged, namely, internal actions addressed to hospital staff (35.9%), external actions addressed to users (18.6%), comfort and hospitality aspects (34.7%) and review of processes and procedures (10.8%). The study highlights the importance of effectively using patient-reported data to achieve organisational goals, by combining different managerial strategies. It demonstrates how professionals use such data for improvement actions and underscores the significance of various forms of knowledge dissemination and sharing. It advocates for fostering a culture of continuous learning and improvement within and across healthcare organisations.

Patients, families, and their representative groups must be key active participants (i.e. co-designers or co-producers) of healthcare and its improvement [1-6]. As one way to achieve this, healthcare systems and services need mechanisms to capture, process, and translate user feedback — including patient experience data — into healthcare improvement activities [3, 7-11]. User feedback — either quantitative or qualitative — can be gathered through routinely available data such as patient experience surveys, complaints, and online comments, or actively solicited by providers through bedside rounding, patient narratives, and photovoice initiatives, among others [5, 12-16]. Patient experience and user feedback can serve various purposes, from consultative roles (e.g., patient and family advisory councils), service evaluation purposes (e.g., experience surveys) and as part of collaborative co-design approaches - wherein patients, families or their representative become key partners for new service delivery approaches [11, 17, 18]. Therefore, effectively leveraging user feedback can drive quality improvement (QI) activities, transformative service redesigns, and the creation and evaluation of new healthcare services, programs, or policies. Additionally, user feedback and input may also be integrated into Learning Health Systems (LHS) to support user-centred practice improvement that also drives knowledge generation and sharing [19, 20].

To realise these outcomes, user feedback must be systematically collected, processed, analysed, and relayed in a timely manner to providers, enabling real time application at the point of care [12]. This often necessitates the development, study, and implementation of systems and processes that ensure user feedback is intentionally and meaningfully utilised to enhance healthcare and its person-centeredness.

In early 2024, we issued a ‘call for papers’ for a special issue on ‘Patient Experience Data and Feedback for Quality Improvement and Learning Health Systems’, for the International Journal of Health Planning and Management. During the first phase of the two-step submission process, we received 159 abstracts from authors across five continents, including from low- and middle-income countries (LMIC). Following an initial screening based on scope, methodological quality, and diversity, a little over 10% of the abstracts were invited for a full-text submission for peer review. From the pool of submitted papers, 13 were finally accepted for publication.

Among the articles included, one focuses on a low-income nation (Democratic Republic of Congo), three examine middle-income countries (Argentina, China, and Peru), and two analyse multi-country data that includes nations with varying income levels. Seven papers addressed high-income countries, with three from the USA and one each from Australia, Canada, Italy, and Swe