OPSCB/574 Competency 3 Assessment and Rubric

Title: Competency 1 - Assessment

Course: OPSCB/574: Creating Value Through Operations

University of Phoenix

Date: November 29, 2025

This analysis evaluates the patient check in process at an outpatient clinic, with a focus on check in delay time, measured from the scheduled appointment time until the completion of registration. Check in delays are a meaningful metric because it directly impacts patient satisfaction, clinic flow, throughput and staff workload.

The check in workflow includes patient arrival, demographic confirmation, insurance verification, documentation review and entry into the electronic health record (EHR). Delays commonly occur when insurance verification is incomplete, patients lack required documents, or staffing is inconsistent during peak appointment times. These factors introduce variation into the process and affect predictability.

The DMAIC framework was used to evaluate the process.

Define: Critical to quality (CTQ) requirements include complete pre registration, accurate insurance verification and check in delays below the five minute performance target. Defects include delays of longer than five minutes and missing documentation at arrival.

Measure: Ninety check in delay observations were collected, revealing variation linked to appointment type and staff workflow differences.

Analyze: SIPOC mapping and a fishbone analysis identified root causes such as inconsistent pre arrival communication, manual data entry, EHR navigation challenges and incomplete documentation.

Improve: Improvement opportunities include standardized scripting, automated document collection and streamlined verification steps. Control: Standard operating procedures, dashboards and scheduled performance audits can sustain gains.

Strengths and Opportunities for Improvement

Strengths:

• The check in process follows a consistent sequence with clearly defined responsibilities. • Staff performance is predictable when documentation is complete. • The overall process is stable, which allows for capability improvement.

Opportunities: • Reduce manual data entry through digitized forms and electronic document upload. • Strengthen pre-arrival communication to decrease missing insurance and demographic information. • Improve staffing alignment during peak hours. • Standardize scripts to reduce variation in how check in procedures are completed.

Step 2: Evaluation of Control Chart and Process Metrics

An Individuals (X) Control Chart was constructed using the 90 observations of check in delay time. Statistical calculations were as follows:

· Mean (X̄): 7.21 minutes

· Upper Control Limit (UCL): 2.87 minutes

· Lower Control Limit (LCL): 15.83 minutes

Control Chart Interpretation

Analysis of the chart shows:

· No points fall above the UCL or below the LCL.

· No patterns of seven or more consecutive points on one side of the mean.

· No seven point increase or decrease trends.

· No alternating or cyclical patterns indicating systematic variation.

These results indicate that the process exhibits common cause variation and is statistically stable.

Process Capability

Capability indices were computed:

· Cp = 0.87

· Cpk = 0.84

Both values fall below the industry benchmark of 1.0, indicating that the process is not capable of consistently meeting desired performance targets. While the process is stable, its natural variation is too wide relative to expectations and the average check in time is not centered within the acceptable range.

This analysis evaluated the patient check in process using Statistical Process Control (SPC) and Six Sigma methodologies. Check in delay time was used as the primary metric because it directly influences patient experience and operational efficiency.

The SPC analysis shows that the process is statistically stable, with no violations of standard control chart rules. However, capability indices indicate that the process is not capable, meaning performance does not consistently meet expectations for timely registration.

Lean methods are well suited to address workflow redesign and reduction of non–value-added tasks, while Six Sigma tools can be applied after stabilization to reduce remaining variation. Overall, the results show the need for process redesign to reduce delays, improve predictability and align performance with clinic goals.

Summary of Control Chart and Process Metrics Using SPC Methods

The Individuals (X) Control Chart demonstrates predictable behavior within established control limits. All measured points fall within the calculated UCL and LCL and no Western Electric rule violations are present. This indicates a stable process with variation caused by the inherent nature of the workflow rather than special external causes.

Although stable, the low Cp and Cpk values highlight that the process variation exceeds acceptable ranges for performance. Therefore, targeted improvements are necessary to narrow process variation and center the mean check in time within the desired performance window.

Six Sigma, Lean and Other Tools Evaluation Summary

Lean and Six Sigma tools offer complementary strengths for improving this process.

Lean tools such as 5S, standard work, error-proofing (poka-yoke) and workflow mapping can reduce waste, eliminate redundant steps and streamline the check in process. These tools are particularly effective for improving flow and reducing non–value-added activities.

Six Sigma tools including DMAIC, Pareto analysis, hypothesis testing and root cause analysis are well suited for reducing variation once waste has been removed. These tools can help refine the process and increase capability.

Additional tools such as automated pre registration reminders, predictive analytics for identifying high delay appointment types and visual performance dashboards can further enhance the process.

Description of the Statistical Process Control Project

The SPC project aimed to assess the stability and capability of the patient check in delay process.

Project Steps

1. Data Collection: Ninety consecutive check in delay observations were recorded to capture real operational conditions.

2. Chart Construction: An Individuals (X) Control Chart was developed using calculated mean and control limits.

3. Rule Analysis: Standard SPC rules were applied to identify any signals of special-cause variation.

4. Capability Evaluation: Cp and Cpk indices were calculated and compared to organizational performance expectations.

5. Root Cause Identification : Variation sources were categorized using process mapping, SIPOC analysis and cause and effect tools.

Project Findings

The process is stable but not capable. Improvements must focus on workflow simplification, documentation completeness, staffing patterns and automation to reduce variation and enhance performance.

Recommendations For Improvement:

Based on the SPC analysis, the following improvement actions are recommended:

1. Strengthen Pre-Registration Completion

· Provide automated reminders for required documents.

· Implement mandatory insurance verification prior to arrival.

2. Reduce Manual Data Entry

· Allow patients to upload documents electronically.

· Use EHR hard stops to prevent incomplete entries.

3. Adjust Staffing During Peak Times

· Use arrival forecasts to align staffing levels with demand.

· Assign a float staff member during high-volume hours.

4. Implement Lean Workflow Redesign

· Remove duplicate verification steps.

· Provide standardized scripting for all check in staff.

· Use visual cues to signal incomplete documentation.

5. Apply Six Sigma Variation Reduction

· Use Pareto analysis to pinpoint the largest delay contributors.

· Reduce variation by standardizing the most variable steps.

Expected Benefits

· Lower average check in delays

· Narrower process variation

· Improved patient satisfaction

· Enhanced operational efficiency

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