Project Overview:
The "Patient Intake Needs Assessment" project was conducted for the Cobalt Department of Health (CDH) (a pseudonym) to address performance gaps in patient intake processes. The initiative aimed to identify and resolve issues affecting intake efficiency and accuracy within the organization.
Organization Background:
Cobalt Department of Health (CDH): CDH is a local health department dedicated to promoting health and wellness in the community. Its mission involves partnering with community members to deliver accessible healthcare services and programs aimed at improving public health outcomes. The organization is structured into several divisions, with approximately 150 employees providing a range of health services, particularly for underserved populations.
Strategic Goals: CDH focuses on three primary goals: growing programs and services, delivering excellent customer service, and building internal capacity. Key initiatives include increasing appointment completions, enhancing participation in health programs, and ensuring effective operational processes.
The project focused on addressing persistent patient intake errors, which averaged 7-10 reported errors weekly. These errors have remained consistent over six months, significantly impacting provider workload, patient care quality, and overall operational efficiency. The main objective was to reduce the error rate from 29% to the desired target of 10%, thereby improving the patient intake experience and aligning with CDH’s strategic priorities.
To understand and alleviate these errors, a variety of analytical tools and frameworks were employed:
5 Whys Analysis: This systematic approach was used to dig deep into the root causes of the patient intake errors by asking "why" repeatedly until the underlying issues were identified. It facilitated a thorough understanding of the problem beyond surface-level symptoms.
Fishbone Diagram: This visualization tool helped categorize and illustrate the various root causes of the patient intake errors, allowing the team to see connections between different variables and identify areas that needed intervention.
Human Performance Technology (HPT) Models: Various HPT models were applied to frame the analysis and intervention selection, including:
Gilbert's Behavior Engineering Model: This model was used to identify organizational factors that might hinder effective performance, such as insufficient training, lack of resources, and unclear expectations.
Rummler-Brache Performance Matrix: This helped map the relationships between the organizational goals, processes, and performer roles, ensuring the interventions aligned with the overall mission of the department.
Van Tiem’s HPT Model: This model provided a structured approach to analyze the performance issues within the organization, focusing on the interactions of worker, workplace, work, and world, which collectively influence performance outcomes. It emphasizes understanding the context in which performance occurs and ensures that interventions align effectively with organizational goals.
Multicriteria Analysis: This approach assigned weights to various selection criteria and provided a structured method for comparing interventions based on their potential impact and feasibility. It ensured that the selected interventions addressed the identified root causes effectively.
Pairwise Comparison: This method enabled direct comparisons between the proposed interventions, allowing the team to prioritize solutions based on multiple criteria quickly and collaboratively.
Environmental Scan: This analysis provided insights into the external factors affecting performance, such as market conditions and regulatory issues, helping to contextualize the internal challenges faced by CSRs.
Stakeholder Interviews: Conducted with key stakeholders, including Customer Service Representatives and leadership, to gain deeper insights into the challenges faced in the patient intake process, understand perceptions of current practices, and gather suggestions for improvement.
Surveys and Focus Groups: Data collection methods that gathered qualitative and quantitative input from CSRs, providers, and leadership to assess current performance and identify pain points in the patient intake process.
Causes
The analysis revealed seven key root causes:
Environmental factors impact the patient intake process.
Notable issues included inadequate organizational structure for monitoring and training deficiencies for Customer Service Representatives (CSRs).
Unclear expectations for error reporting and resolution.
Based on the data-driven analysis, the following interventions were proposed:
Design Job Aids: Develop user-friendly resources using adult learning principles to assist CSRs in their roles.
Cross-Training Initiatives: Implement hands-on training to improve clinical knowledge among CSRs.
Task Analysis: Create a straightforward, documented patient intake process to standardize operations.
Establish Key Performance Indicators (KPIs): Introduce metrics for identifying and reducing patient intake errors.
Improve Online Accessibility: Enhance the usability of online forms to facilitate pre-appointment data collection from patients.
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