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Improve Your Patient Journey

A 6-step guide to optimizing your Epic EHR workflows.
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Improve Your Patient Journey
Challenges (10) Goals (10) 6 Steps Preview Outcomes Data FAQs (4)

Optimize Patient Journey Workflows in Epic EHR for Better Care

Our platform provides deep visibility into your daily workflows by uncovering hidden bottlenecks and deviations that slow down progress. By analyzing event data, you can pinpoint exactly where delays occur and determine the root causes of operational friction. This insight allows you to streamline clinical paths and ensure a more efficient experience for everyone involved.

Download our pre-configured data template and address common challenges to reach your efficiency goals. Follow our six-step improvement plan and consult the Data Template Guide to transform your operations.

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The Strategic Value of Optimizing Patient Journeys

In the modern healthcare landscape, the patient journey is more than a series of clinical encounters, it is a complex web of interactions that determines the quality of care and the financial health of the organization. When you manage a patient journey within Epic EHR, you are dealing with a vast ecosystem where every registration, triage note, and medication order leaves a digital footprint. However, the sheer volume of data often obscures the actual flow of patients through your facilities. Optimizing this journey is essential because inefficiencies do not just represent lost revenue, they can lead to poorer clinical outcomes, increased clinician burnout, and decreased patient satisfaction. By focusing on process optimization, healthcare leaders can move away from anecdotal evidence and toward a data driven strategy that ensures patients receive the right care at the right time.

Turning Epic EHR Data into Process Intelligence

Process mining acts as a bridge between the raw data stored in Epic modules, such as EpicCare and Cadence, and the actionable insights needed for operational excellence. While Epic provides excellent reporting tools for individual snapshots, process mining looks at the longitudinal record of the patient episode. It connects the dots between a patient being registered in the emergency department and their eventual discharge from a specialized ward. By visualizing the actual path taken by thousands of patients, you can see the deviations from your standard of care protocols. This transparency allows you to identify where the process stalls, whether it is a delay in diagnostic testing or a bottleneck in specialist consultations, without needing to manually audit individual charts.

Targeting Hidden Bottlenecks and Friction Points

One of the most significant challenges in healthcare is the presence of invisible bottlenecks that delay care delivery. For example, a patient might spend hours in a holding pattern because a specific diagnostic result has not been reviewed, or because the discharge planning process did not begin early enough in the stay. Using process mining on your Epic EHR data allows you to isolate these friction points. You might discover that certain departments have a significantly higher cycle time for triage than others, or that specific treatment pathways frequently lead to unexpected readmissions. By pinpointing these areas, you can implement targeted interventions, such as adjusting staffing levels during peak admission times or automating certain notifications within the EHR to prompt faster clinical actions.

Measuring Success through Clinical and Operational KPIs

Improving the patient journey leads to measurable benefits across several key performance indicators. First and foremost is the reduction in total cycle time, which directly impacts bed turnover rates and hospital capacity. When you streamline the flow from admission to discharge, you increase your ability to serve more patients without necessarily adding more physical infrastructure. Furthermore, process mining helps ensure compliance with clinical pathways, which is critical for both patient safety and insurance reimbursement. By reducing the variance in how care is delivered, you create a more predictable and reliable environment. This not only improves the bottom line by reducing wasted resources but also enhances the patient experience by providing a smoother, more transparent path to recovery.

Advancing Your Healthcare Operations

Starting the journey toward a fully optimized clinical process does not require a complete overhaul of your existing systems. Instead, it begins with a shift in perspective, moving from managing individual tasks to managing the end to end flow. By leveraging specialized templates designed for Epic EHR, you can quickly gain visibility into your current state and begin identifying the low hanging fruit for improvement. Whether your goal is to reduce wait times in the emergency department, improve the efficiency of your surgical suites, or ensure timely follow up after discharge, the data already exists within your system. The key is to use process mining to unlock that data, allowing you to make informed decisions that benefit both your staff and the patients who rely on your care.

Patient Journey care coordination discharge planning clinical workflow patient flow healthcare operations admissions management

Common Problems & Challenges

Identify which challenges are impacting you

Patients often experience significant delays between registration and their initial assessment, which compromises patient safety and lowers satisfaction scores. These bottlenecks in the early stages of the journey create a ripple effect that slows down the entire clinical workflow and increases emergency department crowding.

ProcessMind analyzes event logs within Epic EHR to pinpoint exactly where triage delays occur and which patient cohorts are most affected. By visualizing the time gaps between registration and assessment, healthcare leaders can reallocate staff during peak periods to ensure faster initial care.

When discharge planning begins only hours before a patient leaves, it leads to administrative gridlock and occupied beds that should be available for new admissions. This inefficiency increases the average length of stay and strains hospital capacity, which directly impacts revenue and patient flow.

Our solution tracks the timing of discharge initiation relative to the total patient episode in Epic EHR. By identifying cases where discharge planning starts too late, we help administrators implement protocols that trigger early planning, ensuring smoother transitions and better bed management.

Delays between ordering a diagnostic test and its performance frequently stall the clinical decision making process. When clinicians are forced to wait for lab results or imaging, the entire treatment plan is put on hold, extending the patient stay and delaying critical interventions.

By mapping the diagnostic lifecycle within Epic EHR, ProcessMind highlights specific departments or test types that consistently cause delays. This visibility allows managers to address resource constraints or process inefficiencies in the lab or imaging departments to accelerate the patient journey.

Moving patients from the emergency department to specialized wards or between units often involves long wait times that disrupt care continuity. These transfer bottlenecks tie up staff resources and leave patients in suboptimal environments, which can negatively affect clinical outcomes.

We provide a clear view of transfer patterns and wait times recorded in Epic EHR modules like Cadence and EpicCare. ProcessMind identifies the specific handoffs that take longer than expected, enabling teams to streamline communication and logistics between departments.

High variability in how treatment plans are executed for similar diagnoses leads to unpredictable patient outcomes and increased operational costs. When clinicians deviate from established protocols without clear justification, it becomes difficult to maintain a high standard of care across the organization.

ProcessMind compares actual patient paths against standard clinical protocols by analyzing activity logs in Epic EHR. This analysis reveals where deviations occur, allowing clinical leaders to standardize workflows and ensure that every patient receives the most effective evidence based care.

The time spent waiting for a specialist to perform a consultation can significantly extend a patient's stay, especially in complex cases. These delays often result from poor communication or scheduling conflicts, which keep patients in hospital beds longer than clinically necessary.

Our platform tracks the duration between a consultation request and the actual specialist visit within Epic EHR. By identifying the specific specialties or shifts where delays are most prevalent, healthcare organizations can optimize specialist availability and reduce overall length of stay.

Delays in administering medication after an order is placed can jeopardize patient recovery and lead to clinical complications. In a high pressure environment, these gaps are often invisible to management but have a direct impact on the quality of care and patient safety.

ProcessMind monitors the delta between medication orders and administration events captured in Epic EHR. This allows nursing leadership to identify systemic delays and provide targeted support or process adjustments to ensure timely medication delivery for all patients.

Patients returning to the hospital shortly after discharge often point to gaps in the initial care journey or inadequate discharge instructions. Frequent readmissions increase costs, reduce bed availability, and can lead to financial penalties from payers who monitor quality metrics.

By analyzing the full patient episode and subsequent readmission events in Epic EHR, ProcessMind identifies common factors or process failures that precede a return visit. This insight enables providers to strengthen discharge planning and follow-up care for high risk patient groups.

When follow-up appointments are not scheduled before a patient leaves the facility, the risk of non-compliance and health regression increases. Manual scheduling processes often lead to missed opportunities, as staff may overlook this step during a busy discharge window.

ProcessMind checks the event logs in Epic EHR to see if a follow-up appointment was scheduled as part of the discharge activity. We highlight episodes where this step was missed, helping clinics automate reminders or refine workflows to ensure every patient has a clear path for continuing care.

A slow progression from initial assessment to a confirmed diagnosis delays the start of specialized treatment and extends the period of uncertainty for the patient. This bottleneck often occurs due to fragmented communication between diagnostic services and the primary care team.

Our tool visualizes the end-to-end diagnostic phase within the Epic EHR journey, measuring the time from triage to diagnosis confirmation. By identifying the stages where the process stalls, healthcare teams can improve coordination and speed up the delivery of targeted care.

Typical Goals

Define what success looks like

Prompt initial assessment is critical for patient safety and clinical outcomes. Reducing the time between registration and triage ensures that high-risk patients receive immediate attention, which minimizes the risk of condition deterioration and improves the overall patient experience in the emergency or outpatient setting. This immediate response is the first step in a successful care journey.

ProcessMind visualizes the flow from registration to assessment within Epic EHR to pinpoint specific times of day or departments where bottlenecks occur. By analyzing these patterns, healthcare administrators can adjust staffing levels or modify intake procedures to ensure a 20 percent faster transition to clinical care, directly improving triage throughput.

Efficient discharge planning is essential for maintaining hospital capacity and preventing boarding in the emergency department. By streamlining the steps required to transition a patient out of the facility, hospitals can increase bed turnover rates and ensure that incoming patients are admitted without unnecessary delays, which improves patient flow across the entire organization.

Using process mining on Epic EHR data allows teams to identify the specific milestones that delay discharge, such as pending lab results or pharmacy orders. ProcessMind highlights these friction points, enabling providers to implement proactive discharge planning that can reduce the average length of stay by 15 percent or more while maintaining care quality.

Rapid diagnostic results are the foundation of timely treatment decisions. Reducing the interval between ordering a test and confirming a diagnosis prevents treatment delays and helps clinicians move forward with appropriate care plans, which ultimately shortens the entire patient episode and reduces the total cost of care per patient journey.

ProcessMind tracks the lifecycle of diagnostic orders in Epic EHR to reveal where delays occur, whether in the lab, imaging, or during the physician review phase. By monitoring these cycle times, organizations can optimize order sets and communication workflows to achieve a significant reduction in time to diagnosis, ensuring clinical decisions are based on the latest data.

Internal transfers are often fraught with communication gaps and logistical hurdles that leave patients in limbo. Speeding up the movement of patients from the emergency department to inpatient wards or between specialized units ensures continuity of care and better utilization of clinical resources, preventing bottlenecks that impact the entire hospital ecosystem.

By mapping the journey across different hospital departments in Epic EHR, ProcessMind identifies the exact handoff points where delays occur most frequently. This visibility allows managers to address specific departmental bottlenecks and improve transfer efficiency by up to 25 percent, ensuring patients reach the appropriate level of care without waiting.

Standardizing care through evidence-based protocols is vital for ensuring high-quality outcomes and patient safety. High adherence rates reduce clinical variability, which helps in predicting recovery times and ensuring that every patient receives the best possible treatment regardless of the attending clinician, which is essential for consistent care delivery.

ProcessMind analyzes actual treatment paths against desired protocols within Epic EHR to identify non-compliant deviations. This allows clinical leads to provide targeted training or update clinical decision support tools, ensuring that over 90 percent of patient episodes follow the prescribed care pathway, which leads to more predictable outcomes and reduced complications.

Specialist input is often a prerequisite for complex treatment decisions. Slow consultation responses can stall the entire patient journey, leading to longer hospital stays and increased costs. Improving the speed of these consultations ensures that specialized expertise is integrated into the care plan as early as possible, accelerating the path to recovery.

With ProcessMind, organizations can measure the duration between a consultation request and the specialist's note entry in Epic EHR. Identifying departments or specialties with the longest response times enables the implementation of better notification systems and service level agreements to drive faster clinical collaboration and shorten the overall treatment timeline.

Precise medication delivery is fundamental to patient recovery and the prevention of adverse events. Ensuring that medications are administered according to the prescribed schedule improves the effectiveness of the treatment plan and enhances patient safety throughout their hospital stay, reducing the risk of medication-related errors or setbacks.

ProcessMind extracts timestamp data from Epic EHR to monitor the interval between medication orders and administration. This provides a clear view of pharmacy and nursing workflow performance, allowing for targeted adjustments that eliminate late doses and ensure a 98 percent on-time administration rate, which directly supports faster patient recovery.

Readmission within 30 days is a key metric for care quality and hospital reimbursement. By improving the quality of the initial journey and ensuring patients are stable and well-informed upon discharge, healthcare providers can significantly reduce the likelihood of complications that require a return to the hospital, benefiting both the patient and the provider.

ProcessMind correlates patient journey patterns with readmission flags in Epic EHR to identify care paths that frequently lead to poor outcomes. These insights allow providers to refine discharge criteria and post-acute care coordination, aiming for a 10 to 20 percent reduction in readmission rates by identifying high-risk journeys before they conclude.

The patient journey does not end at the hospital exit. Ensuring that follow-up appointments are scheduled before discharge is essential for monitoring recovery and preventing complications. Seamlessly bridging the gap between inpatient and outpatient care maintains the continuum of treatment and supports long-term health success.

ProcessMind identifies gaps in the discharge process where follow-up scheduling is missed or delayed within Epic EHR modules like Cadence. By visualizing these failures, organizations can implement automated prompts and workflows that ensure every patient has a scheduled follow-up, improving long-term health outcomes and reducing the administrative burden on nursing staff.

The time it takes to reach a confirmed diagnosis directly impacts the start of definitive treatment. Accelerating this phase of the patient journey reduces patient anxiety and prevents the progression of illness, leading to more successful clinical interventions and shorter overall hospital stays for complex cases.

By analyzing the sequences of activities in Epic EHR from initial assessment to diagnosis confirmation, ProcessMind uncovers the specific diagnostic steps that cause the most delay. Streamlining these workflows allows clinical teams to reach a diagnosis 30 percent faster, enabling quicker initiation of the primary treatment plan and improving clinical throughput.

The 6-Step Improvement Path for Patient Journey

1

Download the Template
2

Export Your Data
3

Upload Your Dataset
4

Analyze Your Process
5

Implement Improvements
6

Monitor Your Process
1

Download the Template

What to do

Obtain the specialized Excel template designed for Epic EHR data structures, ensuring all clinical and administrative fields are mapped correctly.

View Data Template Guide Download Template
Why it matters

Starting with a pre-configured structure reduces mapping errors and aligns your patient episode data with process mining requirements.

Expected outcome

A ready-to-use data structure for your patient journey analysis.

YOUR CLINICAL INSIGHTS

Gain Complete Clarity on Your Epic EHR Workflows

ProcessMind provides a clear lens into your clinical operations by mapping every step of the patient journey. You will uncover hidden inefficiencies and gain the data needed to streamline discharge planning and triage.
  • Visualize actual patient paths in real time
  • Identify root causes of discharge delays
  • Analyze triage performance across departments
  • Track the impact of operational changes
Discover your actual process flow
Discover your actual process flow
Identify bottlenecks and delays
Identify bottlenecks and delays
Analyze process variants
Analyze process variants
Design your optimized process
Design your optimized process

PROVEN OUTCOMES

Optimizing Clinical and Operational Excellence

Healthcare organizations leverage process mining to visualize the complete Patient Episode within Epic EHR, allowing teams to eliminate care delays and improve resource utilization. These metrics demonstrate the impact of data-driven process optimization on the patient experience.

0 %
Faster Care Delivery

Reduction in triage completion time

Optimizing the flow from registration to initial assessment allows patients to receive clinical care much earlier in their journey.
0 %
Reduced Readmission Rates

Decrease in unplanned readmissions

Identifying gaps in discharge and follow up planning helps prevent patients from returning for unplanned care within 30 days of release.
0 %
Improved Care Compliance

Increase in protocol conformance

Aligning patient episodes with evidence based standards ensures that all clinical steps are performed in the correct sequence for better health outcomes.
0 days
Enhanced Bed Capacity

Reduction in total length of stay

Initiating discharge planning earlier in the patient episode frees up critical bed space and reduces logistical bottlenecks during ward transfers.
0 hours
Faster Specialist Access

Reduction in consultation lead time

Reducing the time between a consultation request and the actual assessment accelerates treatment decisions and improves the patient experience.

Results vary based on process complexity and data quality. These figures represent typical improvements observed across healthcare implementations.

FAQs

Frequently asked questions

Process mining uses your Epic EHR log data to visualize exactly how patients move through your facility. It identifies hidden bottlenecks such as triage delays or ward transfer lags that traditional reporting might miss. This data-driven approach helps you transition from guessing where problems exist to seeing evidence based patterns.

You typically extract data from the Clarity or Caboodle reporting databases, focusing on event logs tied to the Patient Episode. The extraction needs to include a unique identifier, activity descriptions like triage start or discharge complete, and a timestamp for each event. Most teams use standard SQL queries or existing ETL pipelines to pull this information securely.

Yes, the tool can pinpoint exactly where the discharge process stalls, whether it is waiting for transport, pharmacy clearance, or physician sign-off. By visualizing these friction points, clinical managers can implement targeted changes to shorten the discharge cycle and increase bed availability. You can also monitor the impact of these changes in real time to ensure sustained improvement.

No, process mining is non-intrusive and works by analyzing the digital footprints already created by your staff in Epic. It captures the process as it currently exists without requiring clinicians to change how they document patient care. The insights gathered will actually help you simplify workflows by removing unnecessary steps and manual workarounds.

Most healthcare organizations see their first process maps within four to six weeks of initial data extraction. This timeline includes the initial data cleaning, mapping events to the patient journey, and validating the findings with clinical stakeholders. Once the foundation is set, ongoing monitoring provides immediate visibility into daily operations.

Privacy is a top priority, and the process mining setup usually involves de-identifying Patient Episode IDs before the data leaves your secure environment. You can filter out protected health information while still retaining the sequence of events necessary for process optimization. This ensures compliance with HIPAA and other healthcare data regulations while still providing actionable insights.

By analyzing the full patient journey, the tool can find correlations between specific treatment paths and unplanned readmissions. For instance, you might discover that patients who skip specific follow-up scheduling steps or experience rushed discharge planning are more likely to return. These insights allow you to standardize care protocols to improve patient outcomes and reduce return visits.

You generally need a data analyst familiar with Epic reporting structures and a clinical lead to interpret the process maps. The technical maintenance involves managing the data pipeline from Clarity or Caboodle to ensure the analysis reflects the most recent patient episodes. Many organizations start with a small pilot project before scaling to more complex departments.

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