Patient Pathway Tracking: Understanding and Optimising Patient Journeys

Why this topic matters

In the current NHS landscape, managing increasing demand with finite resources requires an acute understanding of operational flows. Patient pathway tracking moves beyond anecdotal evidence to provide concrete data on how patients move through services. This insight is essential for:

• Identifying delays and bottlenecks: Pinpointing specific points where patients wait unnecessarily, leading to prolonged hospital stays or delayed access to treatment.
• Optimising resource allocation: Understanding where staff, equipment, or facility capacity is overstretched or underutilised.
• Improving patient experience: Reducing uncertainty, anxiety, and the number of handovers for patients, leading to a smoother journey.
• Enhancing clinical outcomes: Timely access to diagnostics and treatment is often critical for better clinical results.
• Meeting national targets: Understanding current performance against targets such as those for cancer pathways, elective care, and emergency care.
• Informing service redesign and quality improvement (QI) initiatives: Providing a robust evidence base for change.

Without effective pathway tracking, opportunities for improvement may remain hidden, and attempts at redesign may address symptoms rather than root causes, potentially leading to unintended consequences.

Practical explanation

Patient pathway tracking involves collecting, analysing, and visualising data related to key stages in a patient's journey. It's not just about looking at individual appointments, but understanding the entire sequence of events and the time elapsed between them. Key aspects include:

Defining the ‘Pathway’

A pathway is a predefined series of steps or events that a patient typically undergoes for a specific condition or service. This could range from a simple diagnostic pathway to a complex multi-disciplinary cancer pathway. The first step in tracking is to clearly define the start and end points and the critical intermediate milestones (e.g., referral received, first outpatient appointment, diagnostic test, treatment decision, procedure, discharge).

Data Sources

Data for pathway tracking can come from various sources within an NHS organisation:

• Electronic Patient Records (EPRs): Often the richest source, containing dates and times of appointments, admissions, discharges, diagnostic results, and treatment decisions.
• Referral Management Systems: Tracking initial referrals and their processing.
• Booking and Scheduling Systems: Providing data on appointment dates, no-shows, and cancellations.
• Laboratory and Radiology Information Systems (LIMS/RIS): Documenting diagnostic test requests, performance, and reporting.
• Theatre Management Systems: Recording surgical procedures, start/end times, and delays.
• Manual data collection: For specific, localised projects or when digital systems are incomplete, though this should be used judiciously due to resource implications.

Key Metrics

Common metrics derived from pathway tracking include:

• Waiting times: Time from referral to first appointment, referral to diagnosis, diagnosis to treatment, etc.
• Length of stay (LoS): For inpatients.
• Throughput: The number of patients completing a specific stage of the pathway within a given timeframe.
• Conversion rates: E.g., proportion of referrals converted to appointments, or diagnostic tests leading to treatment.
• Variation: Differences in pathway lengths or processes for different patients or clinical teams, which can highlight unwarranted variation.
• Deflections/fall-offs: Patients who drop out of a pathway before completion.

Visualisation

Visualising pathways helps to make data understandable and actionable. Common methods include:

• Process maps/swimlane diagrams: Showing the sequence of steps and responsible departments (often part of a QI project).
• Gantt charts: Illustrating timelines and dependencies.
• Flowcharts: Simple representations of steps and decision points.
• Dashboards: Interactive displays summarising key metrics and trends over time.

Common pitfalls

Whilst powerful, pathway tracking is not without its challenges:

• Poor data quality or incompleteness: Missing dates, incorrect entries, or incompatible data across different systems can severely hamper analysis.
• Lack of standardised definitions: Different departments may define 'referral date' or 'treatment start' differently, leading to inconsistent data.
• Scope creep: Trying to track too many complex pathways at once, overwhelming resources.
• Resistance to change: Staff may feel that data collection adds to their burden or that data is being used punitively.
• Focusing on data collection over action: Generating reports without translating insights into tangible improvements.
• ** siloed thinking:** Pathway inefficiencies often span multiple departments, requiring cross-functional collaboration that may not always be readily available.
• Lack of continuous monitoring: Pathway performance can degrade over time if not regularly reviewed and adjusted.

Step-by-step approach to pathway tracking

Implementing or enhancing patient pathway tracking can be approached systematically:

Step 1: Define Your Scope and Objectives

• Identify a specific pathway: Start with a high-impact pathway, perhaps one with known long waits, high patient complaints, or national priority (e.g., suspected cancer, elective orthopaedic surgery, emergency department patient flow).
• Clearly state your objectives: What do you want to achieve? (e.g., 'reduce time from referral to first treatment for condition X by 20%,' 'understand drivers of prolonged LoS in Y ward,' 'identify variation in diagnostic turnaround times').
• Map the 'as-is' pathway: Engage clinical and operational staff to map out the current process, noting all steps, handovers, and typical times.

Step 2: Identify and Extract Data

• Determine key data points: Based on your objectives and pathway map, identify which dates and events are critical to track.
• Locate data sources: Work with IT and information governance teams to identify which systems hold the necessary data.
• Establish data extraction methods: This may involve automated reporting, database queries, or in some cases, manual chart review for initial validation.

Step 3: Analyse and Interpret Data

• Process raw data: Clean, transform, and link data from various sources. This may require data standardisation.
• Calculate key metrics: Generate the metrics identified in the 'Practical Explanation' section.
• Identify trends, outliers, and bottlenecks: Look for patterns over time, unusually long durations at specific stages, and variation between different care providers or sites.
• Root cause analysis: For identified problems, delve deeper to understand why they are occurring (e.g., using '5 Whys' or fishbone diagrams). This often requires qualitative input from staff.

Step 4: Visualise and Communicate Findings

• Create clear visualisations: Use dashboards, process maps, and charts to present data in an easily digestible format.
• Contextualise the data: Explain what the data means in practical terms for patient care and operational efficiency.
• Share with stakeholders: Present findings to the clinical teams, management, and other relevant groups to foster shared understanding and buy-in for change.

Step 5: Implement and Monitor Improvements

• Develop targeted interventions: Based on your analysis, design specific changes to address identified issues (e.g., redesigning processes, reallocating resources, implementing new technologies).
• Pilot changes: Test interventions on a small scale where possible to refine them before wider rollout.
• Monitor impact: Continue to track the pathway metrics to assess the effectiveness of your interventions. This is crucial for demonstrating improvement and ensuring sustainability.
• Review and iterate: Pathway tracking and improvement is a continuous cycle; regularly review performance and adapt processes as needed.

Example in clinical practice: Optimising the Urgent Suspected Cancer pathway

A gastroenterology department was struggling with long waits for endoscopy for patients on the Urgent Suspected Cancer (USC) pathway. Data from the EPR and endoscopy booking system revealed significant variation in the time from referral receipt to diagnostic endoscopy, with some patients waiting beyond the national standard.

Pathway tracking identified several issues:

1. Administrative bottleneck: A single administrative assistant was responsible for reviewing all USC referrals and booking appointments, leading to a backlog during periods of annual leave or sickness.
2. Scheduling inefficiencies: Endoscopy slots were not ring-fenced specifically for USC patients, leading to them being filled by routine cases or last-minute cancellations if not booked immediately.
3. Incomplete referrals: A high proportion of referrals lacked essential clinical information (e.g., baseline blood tests), requiring a delay for contacting the referrer and obtaining this data before booking.

Interventions implemented:

• Process redesign: Implemented a new triage process where two administrative staff (cross-trained) reviewed USC referrals daily.
• Dedicated slots: Ring-fenced several endoscopy slots each week exclusively for USC patients, released for others only 24 hours prior if unfilled.
• Referral proforma: Collaborated with primary care to introduce a standardised referral proforma, embedded in GP systems, mandating key information.

Outcome: Within six months, the department saw a 30% reduction in the median time from referral to diagnostic endoscopy for USC patients, significantly improving compliance with national targets and, most importantly, reducing anxiety and earlier diagnosis for patients.

How Lazomis can help

Lazomis offers tools to facilitate various stages of patient pathway tracking and improvement:

• Lazomis Dashboards: Can be configured to visualise key pathway metrics, enabling real-time monitoring of waiting times, throughput, and activity across different stages of a patient's journey. These can integrate data from various existing NHS systems to provide a unified view.
• Lazomis QI Project Setup: Provides a structured framework for defining your pathway improvement projects, including setting SMART objectives, designing interventions, and tracking progress against your baseline data.
• Lazomis Process Mapping Tool: Supports collaborative mapping of current ('as-is') and future ('to-be') patient pathways, helping teams identify critical steps, handovers, and areas for optimisation.
• Lazomis Data Collection & Audit: For specific, targeted audits or for gathering qualitative data to complement system-level data, our tools can streamline the collection and analysis of information pertinent to pathway bottlenecks.

This resource supports, but does not replace, clinical judgement. Local policy, formulary and specialist advice should be followed.

Key takeaways