33 Quality improvement

In the ever-evolving landscape of healthcare, the pursuit of quality is a paramount concern. Quality improvement (QI) initiatives aim to enhance patient care, optimise outcomes, and elevate the overall performance of healthcare organisations. To achieve these goals, healthcare systems and institutions deploy various quality improvement frameworks that provide structured approaches to identifying, addressing, and resolving issues that impact patient safety, efficiency, and effectiveness.

Understanding quality improvement frameworks

Quality improvement frameworks are systematic methods that guide healthcare organisations in identifying, analysing, and improving aspects of care delivery. These frameworks offer a structured approach to assessing current practices, identifying gaps, implementing changes, and evaluating the impact of those changes. They provide a framework for continuous improvement, emphasising data-driven decision-making and collaboration among multidisciplinary teams.

Quality improvement principles

Quality improvement frameworks share common principles and components that form the foundation for effective implementation:

Measurement and data collection

Robust data collection and measurement are central to quality improvement efforts. Frameworks emphasise the use of evidence-based metrics to quantify the quality of care, patient outcomes, and process performance. These measurements serve as a baseline and guide for evaluating the impact of interventions.

Engagement and collaboration

Quality improvement requires the engagement and collaboration of various stakeholders, including healthcare professionals, administrators, patients, families, and community partners. Effective communication and shared accountability are vital for successful implementation.

Goal setting and prioritisation

Frameworks help organisations set clear goals and priorities for improvement. By defining specific objectives and target outcomes, healthcare systems can focus their efforts on areas with the greatest potential for impact.

Continuous monitoring and evaluation

Quality improvement is an ongoing process. Frameworks emphasise the importance of continuous monitoring and evaluation to assess the effectiveness of interventions. Regular assessment ensures that improvements are sustained and adapted as needed.

Standardisation and best practices

Frameworks often involve the identification and dissemination of best practices, standardised protocols, and evidence-based guidelines. This ensures consistent and reliable care across different units and departments.

Prominent quality improvement frameworks

Several widely recognised quality improvement frameworks are applied in healthcare settings:

Plan-Do-Study-Act (PDSA) framework

The Plan-Do-Study-Act (PDSA) framework, also known as the Deming Cycle or Shewhart Cycle, is a powerful tool for continuous quality improvement in various fields, including healthcare. Developed by quality management pioneers W. Edwards Deming and Walter A. Shewhart, the PDSA framework provides a structured approach to making incremental changes, testing hypotheses, and achieving improvements over time.

The PDSA framework finds its roots in the work of Walter A. Shewhart, a statistician, engineer, and physicist who is often referred to as the father of statistical quality control. Shewhart’s ideas on iterative improvement and data-driven decision-making laid the foundation for the PDSA cycle. Later, W. Edwards Deming, a prominent quality management expert, expanded on Shewhart’s concepts and integrated them into his broader philosophy of total quality management.

The PDSA framework is comprised of four phases that seek to identify a core issues and how to progress forward to address a problem.

Plan phase

In the planning phase, the groundwork for improvement is laid. This involves identifying a problem, setting clear objectives, and devising a strategy for change. Key elements include:

• defining the problem or opportunity for improvement.
• setting specific, measurable, achievable, relevant, and time-bound (SMART) goals.
• identifying potential solutions and interventions.
• developing a plan for implementation, including defining roles and responsibilities.

“Do” phase

During the “do” phase, the planned changes are executed on a small scale. This phase provides an opportunity to test the changes in a controlled environment before full-scale implementation. Key elements include:

• implementing the planned changes according to the defined strategy.
• collecting data related to the changes being tested.
• monitoring the process closely and addressing any unexpected challenges that arise.

Study phase

In the study phase, the data collected during the “do” phase is analysed and evaluated to assess the impact of the changes. This analysis helps determine whether the changes resulted in the desired outcomes. Key elements include:

• analysing data to assess the extent to which the goals were achieved.
• comparing the results with the expected outcomes and goals set during the planning phase.
• identifying trends, patterns, and any discrepancies between expected and observed results.

“Act” phase

Based on the insights gained from the “study” phase, the “act” phase involves making informed decisions about the next steps. Depending on the results, organizations can choose to standardize, adjust, or abandon the changes. Key elements include:

• drawing conclusions from the data analysis.
• deciding whether to continue, modify, or abandon the changes.
• developing a plan for full-scale implementation if the changes were successful.
• identifying lessons learned and best practices for future improvements.

Examples of how PDSA can be applied to improve the quality in healthcare service

Hospital-acquired infections (HAIs) are a significant concern in healthcare, contributing to patient morbidity, prolonged hospital stays, and increased healthcare costs. Implementing quality improvement initiatives to address HAIs is critical for patient safety. The Plan-Do-Study-Act (PDSA) framework has been instrumental in achieving substantial improvements in this area.

A notable example of using the PDSA framework to reduce HAIs comes from a study conducted by Pronovost et al. (2006). In this study, a comprehensive approach to reducing central line-associated bloodstream infections (CLABSIs) in intensive care units (ICUs) was implemented. CLABSIs are a prevalent and potentially fatal type of HAI. The study took place in a large hospital system in Michigan, USA.

The study involved multiple PDSA cycles to implement evidence-based interventions. In the “Plan” phase, the team identified the problem, set specific goals, and devised strategies. They planned to implement a bundle of interventions, including proper hand hygiene, maximal barrier precautions during line insertion, chlorhexidine skin antisepsis, optimal site selection, and daily review of line necessity.

In the “Do” phase, the bundle of interventions was tested in a single ICU. This small-scale pilot allowed the team to refine the interventions, assess feasibility, and identify any unanticipated challenges. The team collected data on CLABSI rates before and after the interventions were implemented.

In the “Study” phase, the data were analysed to evaluate the impact of the interventions. The study found a significant reduction in CLABSIs after the implementation of the bundle. The rate of CLABSIs decreased from 7.7 infections per 1,000 catheter-days to zero infections over 18 months.

In the “Act” phase, the success of the interventions led to the decision to spread the bundle to other ICUs within the hospital system. The bundle’s impact was monitored continuously, and refinements were made as needed.

The implementation of the bundle using the PDSA framework resulted in a remarkable reduction in CLABSIs. This success garnered national attention and led to the “Michigan Keystone: ICU Project,” a collaborative initiative across the state to reduce CLABSIs in ICUs. The approach emphasised the PDSA cycle’s iterative nature, as data-driven refinements were continuously made to enhance the effectiveness of the interventions.

Additional frameworks

You may encounter these frameworks:

Lean Six Sigma

Integrating Lean principles (reducing waste and improving flow) with Six Sigma (reducing defects and variability), this framework focuses on process optimization and minimizing errors. It employs data-driven methodologies to identify root causes of problems and implement solutions. Watch Six Sigma at Hospital – DMAIC example, Healthcare DMAIC example (YouTube, 4m52s) to learn more.

Institute for Healthcare Improvement (IHI) Model for Improvement

This model emphasises setting specific aims, developing measures to track progress, and testing changes on a small scale before implementing them more broadly. The IHI’s “Plan-Do-Study-Act” approach aligns with the iterative nature of quality improvement.

Donabedian Model

Donabedian’s framework evaluates healthcare quality through three dimensions: structure (resources and facilities), process (how care is provided), and outcomes (effectiveness, safety, patient satisfaction). This model offers a comprehensive view of quality, highlighting the interconnectedness of these dimensions.

Baldrige Excellence Framework

Originating from the Baldrige Performance Excellence Program, this framework assesses organisational excellence across seven categories: leadership, strategy, customers, measurement, workforce, operations, and results. It emphasises a systems perspective and continuous improvement.

References

Pronovost, P., Needham, D., Berenholtz, S., Sinopoli, D., Chu, H., Cosgrove, S., … & Goeschel, C. (2006). An intervention to decrease catheter-related bloodstream infections in the ICU. New England Journal of Medicine, 355(26), 2725-2732.