Background

The Organisation for Economic Co-operation and Development (OECD) Patient-Reported Indicator Surveys (PaRIS) initiative aims to support countries in improving care for people living with chronic conditions by collecting information on how people experience the quality and performance of primary and (generalist) ambulatory care services. This paper presents the development of the conceptual framework that underpins the rationale for and the instrumentation of the PaRIS survey.

Methods

The guidance of an international expert taskforce and the OECD Health Care Quality Indicators framework (2015) provided initial specifications for the framework. Relevant conceptual models and frameworks were then identified from searches in bibliographic databases (Medline, EMBASE and the Health Management Information Consortium). A draft framework was developed through narrative review. The final version was codeveloped following the participation of an international Patient advisory Panel, an international Technical Advisory Community and online international workshops with patient representatives.

Results

85 conceptual models and frameworks were identified through searches. The final framework maps relationships between the following domains (and subdomains): patient-reported outcomes (symptoms, functioning, self-reported health status, health-related quality of life); patient-reported experiences of care (access, comprehensiveness, continuity, coordination, patient safety, person centeredness, self-management support, trust, overall perceived quality of care); health and care capabilities; health behaviours (physical activity, diet, tobacco and alcohol consumption), sociodemographic characteristics and self-reported chronic conditions; delivery system characteristics (clinic, main healthcare professional); health system, policy and context.

Discussion

The PaRIS conceptual framework has been developed through a systematic, accountable and inclusive process. It serves as the basis for the development of the indicators and survey instruments as well as for the generation of specific hypotheses to guide the analysis and interpretation of the findings.

Introduction

Quality improvement (QI) is aimed at improving care. Equity is one of the six domains of healthcare quality, as defined by the Institute of Medicine. If this domain is ignored, QI projects have the potential to maintain or even worsen inequalities.

Aims and objectives

We aimed to understand why, how, for whom and in which contexts QI approaches increase, or do not change health inequalities in healthcare organisations.

Methods

We conducted a realist review by first developing an initial programme theory, then searching MEDLINE, Embase, CINAHL, PsychINFO, Web of Science and Scopus for QI projects that considered health inequalities. Included studies were analysed to generate context-mechanism-outcome configurations (CMOCs) and develop an overall programme theory.

Results

We screened 6259 records. Thirty-six records met our inclusion criteria, the majority of which were from the USA. We developed CMOCs covering four clusters: values and understanding, resources, data, and design. Five of these described circumstances in which QI may increase inequalities and 15 where it may reduce inequalities. We found that QI projects that are values-led and incorporate diverse, patient-led data into design are more likely to address health inequalities. However, when staff and patients cannot engage fully with equity-focused projects, due to practical or technological barriers, QI projects are more likely to worsen inequalities.

Conclusions

The potential for QI projects to positively impact inequalities depends on embedding equity-focused values across organisations, ensuring sufficient and appropriate resources are provided to staff delivering QI, and using diverse disaggregated data alongside considered user involvement to inform and assess the success of QI projects. Policymakers and practitioners should ensure that QI projects are used to address inequalities.

The continued use of low-value cancer screening practices not only represents healthcare waste but also a potential cascade of invasive diagnostic procedures and patient anxiety and distress. While prior research has shown it takes an average of 15 years to implement evidence-based practices in cancer control, little is known about how long it takes to de-implement low-value cancer screening practices. We reviewed evidence on six United States Preventive Services Task Force ‘Grade D’ cancer screening practices: (1) cervical cancer screening in women<21 years and >65 years, (2) prostate cancer screening in men≥70 years and (3) ovarian, (4) thyroid, (5) testicular and (6) pancreatic cancer screening in asymptomatic adults. We measured the time from a landmark publication supporting the guideline publication and subsequent de-implementation, defined as a 50% reduction in the use of the practice in routine care. The pace of de-implementation was assessed using nationally representative surveillance systems and peer-reviewed literature from the USA. We found the time to de-implementation of cervical cancer screening was 4 years for women<21 and 16 years for women>65. Prostate screening in men ≥70 has not reached a 50% reduction in use since the 2012 guideline release. We did not identify sufficient evidence to measure the time to de-implementation for ovarian, thyroid, testicular and pancreatic cancer screening in asymptomatic adults. Surveillance of low-value cancer screening is sparse, posing a clear barrier to tracking the de-implementation of these screening practices. Improving the systematic measurement of low-value cancer control practices is imperative for assessing the impact of de-implementation on patient outcomes, healthcare delivery and healthcare costs.

With public reporting and value-based payment, healthcare organisations have strong incentives to optimise quality of care, improve patient outcomes and lower costs.1 In response, organisations are implementing diverse and often novel quality improvement (QI) interventions (systematic efforts to improve the structure, process or outcome of care). Many organisations routinely assess the clinical effects and costs of QI interventions to support internal decisions about whether to discontinue, sustain or expand them.

These internal analyses create an opportunity for QI teams to publish their experiences and inform decision-making at peer organisations. Since QI interventions can be labour-intensive and thus costly, published economic evaluations are of great interest to leaders weighing decisions about whether to adopt them and how best to implement them. Published evaluations seek to answer a two-part question about the effectiveness and cost of a specific QI intervention at one healthcare organisation, with the goal of reporting...

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