Clinical quality registries: Establishing the socio‐technical infrastructure for learning health systems

Abstract

Background

Clinical quality registries (CQR) systematically monitor and provide feedback on the appropriateness and effectiveness of health care within specific clinical domains, collecting data about medical care processes and outcomes, and providing benchmarked performance reports to health care providers for the purpose of driving improvements in safety and quality.

Aims

The successful development of a learning infrastructure requires the alignment of people, technologies, policies, and processes, brought together by shared needs and a culture of continuous quality improvement. The creation and description of such infrastructure is likely to successfully support the delivery of services critical to continuous quality improvement initiatives.

Materials and Methods

We aimed to describe the construction and impacts of healthcare improvement infrastructure within CQRs.

Results

Socio‐technical infrastructure comprises participants that contribute to the design, evaluation, reporting and dissemination of quality improvement activities: employing effective and timely data acquisition, describing healthcare processes and outcomes; supported by directed policy process and supportive organisations. Review of CQR function identifies positive impacts on healthcare utilisation, improved clinical outcomes and significant improvement in survival supported by cost effective investment.

Discussion

Quality improvement frameworks and strategies have been developed to drive CQRs towards international best practice in learning health system structure for data collection and reporting; delivering efficiency and interoperability in data collection and exchange; promoting standardised approaches to CQR design.

Conclusion

Clinical quality registries have demonstrated significant national impacts in quality improvement in high burden disease domains. These registries rely on the construction and resourcing of socio‐technical infrastructures that support quality improvement.

1. LEARNING HEALTH SYSTEMS

Learning health systems (LHS) were defined by the Institute of Medicine in 2007, as a system where “science, informatics, incentives, and culture are aligned for continuous improvement and innovation, with best practices seamlessly embedded in the delivery process and new knowledge captured as an integral by‐product of the delivery experience.” ¹ Despite the functional attraction of this statement, multiple barriers to the establishment of LHS have been identified including: (1) poor organizational culture; (2) inadequate infrastructure and availability of effective data systems; (3) limited supply of skilled individuals; (4) funding; and (5) competing priorities and the lack of a cohesive mission. ² , ³ The development of a quality improvement infrastructure provides a potential mechanism to overcome these difficulties. We aim to describe a socio‐technical infrastructure to support quality improvement activities within LHS for healthcare improvement.

2. SOCIO‐TECHNICAL INFRASTRUCTURE

The successful development of a learning infrastructure requires the alignment of people, technologies, policies, and processes—brought together by shared recognized needs and a culture of continuous quality improvement. The creation of such infrastructure is likely to successfully support the delivery of services critical to continuous quality improvement initiatives. ⁴ This infrastructure includes: people within a trained workforce to conduct the work; technologies that support data collection, analysis, evaluation, reporting, and dissemination; policies that shape and frame targeted domains and improvement activities; and processes that support workplace routines, efficiency, and sustainability ⁴ (Table 1). A further element of this infrastructure is a shared culture of commitment to quality improvement by participants. ⁵

TABLE 1.

Sectoral components of Socio‐technical Infrastructure.

Sector	Components
People	Patient advocates and organizations Clinicians Project officers Data collectors Data analysts Health system governance Improvement governance bodies University and research Education Government
Technology	Data privacy and protection Data linkage Data quality and completeness Data storage Data analysis and risk adjustment Reporting strategies Feedback Data dashboards
Policy	Focus on safety and quality Engagement of community, patients, indigenous and culturally and linguistically diverse populations Governance structure with expert advisory panels Protection of patient privacy and adherence to jurisdictional/national legislation Organizational learning, innovation, and continuous quality improvement that leads to improved patient care Identifying, critically assessing, and translating knowledge and evidence into improved practices Building new knowledge and evidence around how to improve healthcare and health outcomes Analyzing clinical data to support learning, knowledge generation, and improved patient care Engagement of clinicians, patients, and other stakeholders in processes of learning, knowledge generation, and translation
Process	Maximize registry participation and stakeholder engagement Secure funding Choose performance indicators Define data elements Set performance target expectation Ensure data integrity and completeness Build trust in data Data analysis and risk adjustment Provide community education Provide data reports with feedback Negative outlier identification and management Research confirming registry effectiveness Education to extend registry reach

3. CLINICAL QUALITY REGISTRIES

Clinical quality registries (CQR) systematically monitor and provide feedback on the appropriateness and effectiveness of health care within specific clinical domains, collecting data about medical care processes, procedures, and outcomes, monitoring adherence to national/international guidelines, and providing benchmarked performance reports to health care providers driving improvements in safety and quality ⁶ , ⁷ , ⁸ , ⁹ (Figure 1). A national framework has been developed by the Australian Commission on Safety and Quality in Health Care, describing the governance, purpose, structure, and processes to facilitate registries in achieving their purpose ¹⁰ , ¹¹ (Figure 2). A CQR national strategy was released in 2020 by the Australian Government, which underpins the development of priority activities to advance the assessment of quality and safety of delivered care at national levels and provides robust infrastructural architecture for quality improvement. ¹²

FIGURE 1.

The clinical quality registry (CQR) continuous improvement cycle. ¹⁰

FIGURE 2.

Functional overview of Australian National Clinical Quality Registries. ¹¹

These frameworks and strategies have been developed to drive CQRs toward international best practice for data collection and reporting; delivering efficiency and interoperability in data collection and exchange; promoting standardized approaches to CQR design; reducing the time and cost of developing future CQRs through the provision of a generalizable and reusable design; and standardizing data elements and definitions to facilitate benchmarking, data comparisons, and data exchange. ¹¹

4. CLINICAL REGISTRY UNITS

The Swedish healthcare system has over 103 national CQRs, ⁷ and in Australia a similar number. ¹³ Key to their success is a widespread perception of meaningful innovation, confidence in data integrity, high potential for quality improvement, research and knowledge development, and strong patient involvement. Further success factors have been the securing of national funding for registry activities, and focus on the collection of PROMs and value‐based healthcare. ¹⁴

University faculties such as the School of Public Health and Preventive Medicine, Monash University (Melbourne, Australia), have extensive experience in the establishment and maintenance of clinical registries, currently supporting 37 CQR at state, national, and multi‐national levels. ¹⁵ These registries collect minimum data sets from patients treated in multiple hospitals at local, state, national, and multi‐national levels. The development of these institutional synergies reduces duplicative investment and creates economies of scale that foster and extend the reach of improvement infrastructure to encompass multiple healthcare improvement activities.

LHS strategies have been engaged in primary practice for specific healthcare problems, although both patients and providers identify knowledge translation and utilization across multiple improvement targets at local practice and practice networks. ¹⁶ Disease‐specific LHS are represented at multinational levels, exampled by the Improve Care Now network in pediatric inflammatory bowel disease, engaging 30 000 patients, 1 400 clinicians providing annual management guidelines, research proposals, quality improvement infrastructure, and annual educational conference updates. ¹⁷

5. EXAMPLES OF REGISTRY OUTPUTS

Recent CQR studies have assessed survival outcomes associated with achieving compliance with agreed quality indicators. ¹⁸ , ¹⁹ , ²⁰ , ²¹ , ²² Cohorts in a lung cancer registry achieving high indicator compliance versus those who did not experienced a significant reduction in mortality, with the most powerful impacts evident in the provision of anti‐cancer treatment (67% reduction), and resection in stage I–II non‐small cell lung cancer (NSCLC; 64% reduction). ¹⁸ There was also a marked reduction in mortality associated with improved clinical documentation and multidisciplinary meeting presentation (24% reduction), potentially resulting in better informed decision making.

A systematic review exploring the quality of patient care and clinical outcomes associated with registry participation revealed significant improvements in processes of care, positive impacts on healthcare utilization, improved clinical outcomes, and identified significant improvement in survival in colon cancer and lung cancer following the initiation of a CQR. ²³ A further systematic review exploring the cost effectiveness of CQR in five national registries identified an estimated overall return on the cost of investment by registries of 1.6–5.5 times. ²⁴

The success and sustainability of CQRs as LHSs requires specific infrastructural development and maintenance. These are discussed below.

5.1. People

Socio‐technical infrastructure comprises the full range of participants that contribute to the design, conduct, data evaluation, reporting, dissemination, and processes that contribute to quality improvement initiatives, Table 1. The design and creation of CQRs is led by care providers, patients, carers, and families as part of governance entities that wish to both document and improve measures of equity, access to care, disparity, and unwarranted clinical variation. Foundational to the design and direction of the process is the engagement of consumers, either independently or representing advocacy organizations providing patient‐centered and community interest in specific diseases.

Health informatics experts guide efficient approaches to data extraction from existing information technology infrastructure and must be involved from the concept and design phase, given the ongoing evolution of health informatics. Additional important contributors include stakeholder institution representatives including nurse specialists, governance, economists, educators, academics, researchers, implementation scientists, government leadership, policy makers, and quality improvement representatives. ²⁵ One of the unique strengths of CQRs is the engagement of all craft group providers eligible to participate in CQRs, resulting in a multidisciplinary model of junior and senior contributors from relevant disciplines that unite in support of the premise of driving improvements across the sector.

5.2. Technology

Key to the success of registry processes is the effective and timely acquisition of data describing healthcare processes and outcomes. Advanced flexible, responsive, and timely information, data linkage, and data transfer are vital. This process demands ethical conduct and respect for patient privacy, review of medical records, data linkage, data transfer, data storage, and analysis, using software and storage strategies that maximize completeness and timeliness of data capture. The cyclical linkage of providers of health care to registry‐generated knowledge is a further challenge given the increasingly overwhelming burden of modern communications.

Registry reporting varies depending on stakeholder needs but may include measures of quality indicator processes and outcomes, summary statistics, high‐risk population descriptors, economic outcomes, and institution‐specific patient cohorts. The use of data dashboards providing direct data visualization can be adapted to specific needs targeting disease communities, healthcare networks, hospitals, divisions, departments, teams, and down to the individual provider level. ²⁶ The evolution of technical systems that target the collection of patient and provider perspectives on healthcare delivery (patient reported outcomes and experiences; PROMs and PREMs) is essential to better guide the design and implementation of new healthcare improvement strategies. ²⁷ A number of CQR‐specific technology initiatives are underway via Australia's National CQR Program, including a project to map common data elements captured in national CQRs, with the aim of defining a CQR minimum dataset that would facilitate interaction with electronic medical records. ²⁵

5.3. Policy

The development of policy directions for quality improvement is diverse and initiated at local practice levels, departments, programs, hospitals, healthcare networks, provincial levels, states, and at national and multi‐national levels, with the overriding policy directions established by governments and public institutional bodies. Importantly, the Australian national registry strategy was approved by all state and territory governments and identifies responsibilities for all stakeholder levels. Nevertheless, competing priorities, including significant investment in state‐wide EMRs, are challenging this partnership. ¹³

Over the last few decades, a number of national and international healthcare safety and quality improvement bodies have been established, including national agencies such as the Agency for Healthcare Research and Quality (USA), the Australian Commission on Safety and Quality in Health Care (Australia), the Care Quality Commission (UK), the Swedish Healthcare Quality Registries, and global bodies such as the International Society for Quality in Health Care (Ireland) and the Institute for Healthcare Improvement (USA). A recent paper has attempted to develop a taxonomy of guiding policy principles for the shaping of LHS processes, identifying enabling conditions including: (1) Workforce skilled for LHS work, (2) Data systems, informatics technology, and resources are in place, (3) The organization invests resources in LHS work, and (4) Supportive organizational culture. ²⁸

5.4. Process

Four key organizational attributes have been identified as providing an enabling framework for an effective LHS: (1) Organizations which build knowledge or evidence; (2) Organizations where quality improvement practices are standard practice; (3) Organizations where patients and family members are actively engaged; and (4) Organizations where culture emphasizes and supports learning. ²⁸ The embrace of these attributes likely leads to the development of process activities that enhance compliance with quality indicators that reflect optimal care. These processes include the definition of specific quality improvement indicators, the creation of performance target expectations, building trust in data completeness, directing opportunities for quality improvement initiatives, and the generation of research evidence to support registry processes and outcomes ²⁹ (Figure 3).

FIGURE 3.

Benchmarked reporting enables institutions to identify quality indicator performance at the hospital and network level and identifies negative outlier performance (>2 Standard Deviations below population mean) facilitating the targeting of quality improvement.

The reporting of benchmarked data increases accountability and transparency, engages patients, families, and stakeholders, and fosters collaboration and innovation. ¹⁰ Transparent reporting of benchmarked outcomes to all stakeholders, including patients, communities, hospital governance bodies, and care providers, with reports identifying outliers, provides a powerful catalyst for all providers to assess current practices. ¹¹ Such reporting fosters solution innovation and ultimately improves patient care through quality improvement implementation. ¹²

6. FUTURE OPPORTUNITIES

Successful quality improvement requires an evidence‐based approach to set optimal standards, design implementation strategies, and to evaluate their effectiveness. Multiple recent literature reviews by researchers in the field have proposed frameworks identifying barriers and facilitators to successful LHS evolution. ¹ , ² , ³ , ⁴ , ⁵ , ⁶ , ⁷

Potential barriers to continuous quality improvement include inadequate project planning, defining objectives, inadequate resources, insufficient support for the collection of high quality data, inefficient capture of data from the medical record, poor information systems, and the lack of training and skills. ⁸ The effective utilization of readily available and accessible electronic medical record data, routine data linkage strategies, and finally a critical number of data scientists and artificial intelligence opportunities may provide enough technological advantage to progress effective knowledge translation, dissemination, and communication.

Several modeling frameworks have been proposed to enhance project success and sustainability over time, with success factors focused on expertise, culture, data systems, investment, and supportive culture. ² , ⁶ , ⁹ Recognized success factors include strengthened leadership, quality improvement mentoring, monitoring, supportive supervision and coaching participation, empowerment, engaging all stakeholders in decision‐making, and appropriate staff compensation. ⁸

7. CONCLUSION

CQRs have demonstrated significant national impacts in quality improvement in high burden disease domains. These registries rely on the construction and resourcing of socio‐technical infrastructures that support quality improvement. Registry clusters support multi‐sectoral quality improvement synergies that build quality improvement capability across multiple disease domains, and support the development, sustainability, and dissemination of LHS improvement opportunities.

CONFLICT OF INTEREST STATEMENT

The authors declare no conflicts of interest.

Stirling RG, Ahern S, Millar J, Evans S, Dawkins P, Zalcberg J. Clinical quality registries: Establishing the socio‐technical infrastructure for learning health systems. Learn Health Sys. 2025;9(4):e70036. doi: 10.1002/lrh2.70036