A Systematic Review of Quality Improvement Initiatives in Public Health

A Systematic Review of Quality Improvement Initiatives in Public Health

Abstract Summary

This report presents a systematic review of the literature on smaller-scale Quality Improvement (QI) initiatives in governmental public health, with a focus on informing the Kent County Health Department’s (KCHD) Data Dashboard QI project. Decision-makers in public health often face challenges in increasing service efficiency with limited resources. QI interventions have shown promise in improving public health programs by identifying and addressing errors, inefficiencies, and redundancies. However, the existing peer-reviewed literature on smaller-scale QI initiatives in public health is limited. This review aims to bridge this gap by analyzing the available grey literature and providing recommendations based on successful smaller-scale QI projects.

Introduction

Local public health departments frequently encounter the need to improve the efficiency of their services while operating within restricted budgets. QI interventions are effective strategies to achieve these goals by eliminating errors, inefficiencies, and redundancies in public health programs. Despite the routine implementation of smaller-scale QI initiatives in governmental public health, the peer-reviewed literature on this topic remains scarce. Dilley et al. (2012) conducted a systematic review, revealing gaps in the evidence of linkages between QI interventions and their impact on public health outcomes. Additionally, it also highlighted the limited representation of smaller-scale public health QI efforts in peer-reviewed literature.

Methods

To address the research gap, a systematic review was conducted following established guidelines. The primary goal was to identify QI initiatives in public health that align with the objectives of the KCHD Data Dashboard project. A Python web scraper was built and used to collect QI project data from the Public Health Quality Improvement Exchange (PHQIX) database. Projects were categorized based on organization type, population size, and health department focus areas, and they were selected based on the following inclusion criteria:

(['Focus Areas: Communicable/infection diseases'] ==True)

OR (['Focus Areas: Foodborne illness'] == True)

OR (['Focus Areas: Reportable diseases'] == True)]

Results

A total of 206 QI initiatives were identified from the PHQIX database. Among them, 19 projects met the selection criteria and were considered relevant to the KCHD project. The QI tools most frequently utilized in these successful initiatives included brainstorming, fishbone diagrams, process maps/flow charts, and root cause analysis. Similarly, the predominant QI method employed was the Plan/Do/Check/Act (PDCA) cycle, which encompasses planning, testing, data analysis, and implementation in a continuous improvement cycle. A smaller subset of projects also utilized the rapid cycle improvement approach, which accelerates the QI cycle within a shorter timeframe.

Discussion

The findings from this review highlight the effectiveness of specific QI tools and methods in public health. Notably, successful initiatives used root cause analyses and found actionable solutions using QI tools. Interestingly, KCHD's Communicable Disease Division has already integrated some of these tools in the Data Dashboard project and aligned well with existing QI best practices. The measurable success of the Data Dashboard project provides tangible evidence of the benefits of QI interventions and may motivate further intensive QI projects in the future.

Recommendations

The following recommendations for the KCHD Data Dashboard project are recommended based on this review’s findings:

Continued use of QI tools and methods:

Given the success of the QI tools and methods utilized in the Data Dashboard project so far, KCHD should further leverage these approaches. Brainstorming sessions, process mapping, and the PDCA cycle can help identify root causes, develop actionable solutions, and drive continuous improvement in the surveillance process.

Knowledge transfer and collaboration:

KCHD should actively engage with other local public health departments to exchange information, learn from peers, and disseminate their own QI experiences. Collaborative efforts to share learning and prevent QI knowledge from being limited to specific practitioners may benefit public health as a whole.

Evaluation and dissemination:

KCHD should use evaluation measures to further describe the impact of QI interventions on communicable disease surveillance. Findings and best practices should be disseminated through peer-reviewed publications and conferences to contribute to the growing body of evidence on QI in governmental public health.

Conclusion

This systematic review provides valuable insights into the existing grey literature on QI initiatives in local public health, filling the gap in knowledge regarding smaller-scale projects. By leveraging successful QI tools and methods, KCHD may enhance the efficiency of their communicable disease surveillance efforts, improve public health outcomes, and optimize their use of limited resources. Moreover, KCHD must embrace a culture of continuous improvement to stay at the forefront of QI practices in public health.

References

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