Optimising the prostate cancer diagnostic pathway in a tertiary hospital in Karachi: a two-cycle quality improvement project

Abstract

Delays in the prostate cancer diagnostic pathway can prolong patient anxiety and delay treatment planning, particularly in high-volume resource-constrained settings. At Lifeline Hospital, Karachi, a care centre receiving approximately 60–70 suspected prostate cancer referrals per month, a baseline audit of the urology pathway (Cycle 1, November–December 2024) identified delays. Median referral-to-clinic, clinic-to-biopsy and biopsy-to-multidisciplinary team (MDT) intervals were 25.3, 28.0 and 18.3 days, respectively, and only 47% of patients completed diagnosis and treatment planning within the project’s primary 8-week benchmark from referral. This benchmark was informed by internationally recognised standards, including National Institute for Health and Care Excellence NG12 referral criteria and the National Health Service England Faster Diagnosis Standard and adapted to reflect local service constraints. This quality improvement project was registered locally as a service evaluation.

Following multidisciplinary stakeholder engagement and process mapping, three pragmatic interventions were introduced in early January 2025: (1) an additional weekly one-stop urology clinic, (2) expanded local anaesthetic transperineal biopsy capacity and (3) administrative prioritisation of urgent referrals, imaging coordination and MDT preparation. A reaudit of consecutive patients in Cycle 2 (January–February 2025) evaluated pathway performance after implementation.

Median clinic-to-biopsy time fell to 16.8 days (reduction 11.2 days; 40%), and biopsy-to-MDT time decreased to 7.6 days (reduction 10.7 days; >50%). Referral-to-clinic time improved modestly to 22.3 days. The proportion of patients completing diagnosis and treatment planning within 8 weeks increased from 47% to 58%.

This two-cycle quality improvement project shows that low-cost operational interventions targeting clinic capacity, biopsy access and administrative coordination can improve timeliness in prostate cancer diagnosis and treatment planning in a tertiary hospital setting. Further gains are likely to require better prediagnostic imaging pathways, faster reporting and sustained postproject monitoring. These findings offer a practical framework for tertiary hospitals in Pakistan aiming to optimise cancer diagnostic pathways within existing resource constraints.

WHAT IS ALREADY KNOWN ON THIS TOPIC

• Delays in prostate cancer diagnostic pathways are common in both high-resource and low-resource settings and are associated with patient anxiety and delayed treatment planning. While pathway redesign strategies such as rapid-access clinics, MRI-first models and improved coordination have reduced delays in high-income health systems, their applicability in resource-constrained tertiary hospitals remains limited and underexplored.

WHAT THIS STUDY ADDS

• This study demonstrates that low-cost, pragmatic operational changes, including increased clinic and biopsy capacity and improved administrative coordination, can significantly reduce diagnostic delays and improve timely completion of diagnosis and treatment planning in a high-volume tertiary hospital setting.

HOW THIS STUDY MIGHT AFFECT RESEARCH, PRACTICE OR POLICY

• These findings support the use of context-specific, cost-neutral quality improvement strategies to optimise cancer diagnostic pathways in resource-limited settings and highlight the importance of whole-pathway coordination, particularly integration with radiology services, for sustained improvement.

Problem

Prostate cancer is an increasingly diagnosed malignancy among men in Pakistan and is among the most common cancers in urban male populations. Timely diagnosis is important to reduce patient anxiety and support earlier treatment planning, yet delays remain common in settings with limited imaging capacity, restricted clinic availability and fragmented administrative processes. These pressures are particularly evident in high-volume tertiary hospitals, where demand frequently exceeds available diagnostic capacity.

At Lifeline Hospital, Karachi, a tertiary care private hospital serving a large metropolitan population, the urology service receives approximately 60–70 suspected prostate cancer referrals per month. A local review of the diagnostic pathway in late 2024 identified delay across several stages of care. In the baseline cycle, the median referral-to-first-urology-clinic interval was 25.3 days, the median clinic-to-biopsy interval was 28.0 days and the median biopsy-to-multidisciplinary team (MDT) interval was 18.3 days. Overall, only 47% of patients completed diagnosis and treatment planning within 8 weeks of referral, which was the project’s primary timeliness benchmark.

Root-cause analysis and process mapping suggested that delay was driven by a combination of operational and coordination problems rather than a single bottleneck. Key constraints included limited new-patient clinic capacity, delayed MRI scheduling and reporting, restricted local anaesthetic transperineal biopsy capacity and slow MDT turnaround. These were compounded by manual booking systems and the absence of a consistent prioritisation process for urgent referrals.

In response, a multidisciplinary improvement team was convened, including urologists, radiology and pathology representatives, nurse specialists, administrative staff and a clinical audit facilitator. The project focused on pragmatic, low-cost service redesign intended to improve pathway flow within existing institutional resources.

SMART aim

To reduce the median clinic-to-biopsy interval from 28.0 days by at least 30% and the median biopsy-to-MDT interval from 18.3 days by at least 40% within 3 months, while increasing the proportion of patients completing diagnosis and treatment planning within 8 weeks of referral from a baseline of 47% by at least 10 percentage points.

Background

Prostate cancer represents a growing public health challenge in Pakistan and globally and is among the most frequently diagnosed cancers in men. Its burden is increasing with ageing populations, greater awareness and wider use of prostate-specific antigen testing. Regional cancer registry and epidemiological data suggest a rising number of cases in major urban centres, including Karachi and Lahore, highlighting the need for timely diagnostic and treatment pathways.¹,³

Timely diagnosis is important both clinically and psychologically. Prolonged diagnostic intervals have been associated with heightened patient distress and uncertainty during the diagnostic phase.⁴ At the same time, evidence regarding optimal diagnostic pathway targets remains heterogeneous. Diagnostic pathway targets vary across health systems, and faster pathways must be balanced against diagnostic completeness, imaging availability, biopsy quality and local service constraints.⁵ For this reason, although shorter timed-pathway models such as 28-day cancer pathways provide useful system-level examples, the present project used completion of diagnosis and treatment planning within 8 weeks of referral as its primary benchmark.

While National Health Service England specifies a 28-day Faster Diagnosis Standard pathway for suspected prostate cancer, the European Association of Urology and the National Comprehensive Cancer Network prostate cancer diagnostic guidelines focus on evidence-based diagnostic evaluation and early detection without specifying an equivalent referral-to-diagnosis timed target.^{6 7} Evidence from higher-resource health systems suggests that pathway redesign can reduce delay.⁸,¹⁰ Reported approaches include direct-to-MRI pathways, faster radiology reporting, one-stop urology assessment models and closer coordination between imaging, biopsy, pathology and multidisciplinary review.¹¹ In parallel, major studies such as PROMIS (PROstate MR Imaging Study) and PRECISION (Prostate Evaluation for Clinically Important Disease: Sampling Using Image Guidance or Not?) have strengthened the case for multiparametric MRI and targeted biopsy as more efficient and diagnostically informative components of contemporary prostate cancer assessment.^{12 13} These developments have informed modern pathway design, but their implementation is often more difficult in low- and middle-income settings where access to imaging, reporting capacity, clinic slots and administrative support may be limited.

In many tertiary hospitals in South Asia, diagnostic pathways still depend on sequential, resource-limited processes that are vulnerable to delay at multiple stages. As a result, interventions that are effective in highly resourced systems may not be directly transferable without adaptation. This supports the need for pragmatic, context-sensitive quality improvement strategies that focus on coordination, workflow redesign and selective capacity expansion rather than major new infrastructure.¹⁴ Against this background, the present project was undertaken at Lifeline Hospital, Karachi, to test whether modest operational changes, including additional clinic and biopsy capacity and improved administrative prioritisation, could improve the timeliness of prostate cancer diagnosis and treatment planning within a busy tertiary-care environment.

Measurement

Context and study design

This was a retrospective, two-cycle audit and quality improvement project conducted in the urology department at Lifeline Hospital, Karachi, a tertiary care private hospital serving a large metropolitan population. The department receives approximately 60–70 suspected prostate cancer referrals per month through outpatient and internal specialist channels.

Patient cohorts

Cycle 1 (baseline) included all male patients referred with suspected prostate cancer between 1 November 2024 and 31 December 2024. Following review of baseline data and process mapping, pathway interventions were introduced early January 2025. Cycle 2 (reaudit) included equivalent consecutive referrals between 1 January 2025 and 28 February 2025, after implementation of the service changes. Patients with incomplete pathway data or atypical diagnostic pathways, such as incidental prostate cancer diagnosis, were excluded to improve comparability between cycles. As a service evaluation, no formal sample size calculation was performed; both cycles included all eligible consecutive referrals within the defined time periods. Although the two cycles were conducted in consecutive but distinct calendar periods, referral patterns and case mix were reviewed and appeared broadly comparable. Because the two cycles represented consecutive cohorts from the same service before and after implementation, comparison was considered appropriate for evaluating local pathway change within a quality improvement framework.

Data collection

Data were extracted retrospectively from the hospital Health Information Management System, Radiology Information System and departmental logs for biopsy scheduling, pathology reporting and MDT coordination. Recorded timestamps included referral receipt, first clinic appointment, MRI report date, biopsy date and MDT discussion date. Data completeness and consistency were checked independently by two reviewers against source records. During the implementation phase, pathway data were reviewed at weekly project meetings to support iterative service improvement. The use of standardised electronic timestamps and dual-review verification was intended to improve data reliability, although minor documentation delays could not be fully excluded.

Measures

Process measures were selected to reflect the main operational delays identified during baseline process mapping and because they represented stages that were directly modifiable through the planned interventions.

Primary process measures were:

• Referral to first urology clinic appointment (days).

• Clinic to biopsy interval (days).

• Biopsy to MDT discussion interval (days).

A supportive process measure was:

• MRI report turnaround time (days).

The primary outcome measure was the proportion of patients completing diagnosis and treatment planning within 8 weeks of referral, which was used as the project’s main timeliness benchmark throughout. A secondary outcome measure was overall pathway duration from referral to MDT discussion.

Baseline measurement in Cycle 1 showed median intervals of 25.3 days from referral to clinic, 28.0 days from clinic to biopsy and 18.3 days from biopsy to MDT. In the baseline cohort, 47% of patients completed diagnosis and treatment planning within 8 weeks of referral. MRI reporting time was reviewed as supportive process data because delayed imaging reporting had been identified during root-cause analysis as a contributor to downstream delay, but it was not treated as the principal determinant of project success.

A formal balancing-measure dataset was not collected prospectively. Measures such as non-attendance, cancellations, postbiopsy complications and unplanned reattendance were therefore not available consistently for both cycles and are identified as priorities for future audit cycles. This limitation is stated explicitly to improve transparency and reproducibility.

Analysis

The analysis was primarily descriptive, consistent with the purpose of a local quality improvement project evaluating service performance before and after pathway redesign. Medians and ranges were used to summarise pathway intervals because the data were not assumed to be normally distributed and sample sizes were modest. Changes between cycles were assessed using descriptive comparisons of pathway measures and run-chart interpretation. Outlying observations were reviewed individually and retained when clinically plausible. Data completeness exceeded 95% across both cycles.

Design

Following identification of delay across the prostate cancer diagnostic pathway, a multidisciplinary improvement team was established at Lifeline Hospital, Karachi. The team included consultant urologists, radiologists, pathology and oncology representatives, nurse specialists, administrative officers responsible for booking and MDT coordination and a clinical audit facilitator. This composition was intended to ensure that each major step in the pathway, from referral receipt to MDT discussion, was represented by staff directly involved in day-to-day delivery.

A detailed process-mapping exercise was undertaken using baseline-cycle data to visualise the pathway from referral receipt to MDT decision. Median waiting times and operational bottlenecks were annotated at each step. Stakeholder consultation confirmed four principal constraints: limited new-patient clinic capacity, delays in MRI scheduling and reporting, restricted local anaesthetic transperineal biopsy capacity and infrequent MDT scheduling with limited administrative oversight. These findings suggested that delay arose from multiple linked bottlenecks rather than a single isolated failure point.

The intervention was designed on the assumption that modest, targeted operational changes at the most delayed and modifiable stages of the pathway would yield the greatest reduction in overall time to diagnosis and treatment planning. In particular, the team identified the clinic-to-biopsy and biopsy-to-MDT stages as high-impact targets because these delays appeared to be driven primarily by scheduling and coordination rather than by the need for major new infrastructure. This rationale was consistent with published pathway-redesign literature and with the project’s baseline process data.

Three linked interventions were introduced. First, an additional weekly one-stop urology clinic was added to improve access to first specialist review and accelerate early decision-making. This increased new-patient clinic capacity from 12 to 16 slots per week. Second, local anaesthetic transperineal biopsy capacity was expanded through an additional weekly biopsy list, increasing available biopsy capacity from 6 to 10 slots per week and aiming to reduce clinic-to-biopsy delay. Third, administrative oversight of the pathway was formalised. This included proactive tracking of MRI reports, prepopulation of MDT discussion lists once pathology was available and prioritised coordination of patients judged clinically urgent.

In practice, urgent referrals were flagged at receipt by booking staff on the basis of referral information and consultant review, then escalated for earlier clinic, imaging or biopsy scheduling where capacity allowed. Pending imaging or pathology results were actively chased by administrative staff, and unresolved delays were escalated to the relevant clinical or radiology leads. Secretarial and booking staff maintained a live overview of patients awaiting the next pathway step, which allowed delays to be identified earlier and reduced the risk of cases being held up by administrative gaps alone.

Stakeholder engagement was central to intervention design and delivery. Regular meetings were held with radiology, nursing and administrative teams to refine workflow changes, test feasibility and review emerging barriers. Secretarial and booking staff were particularly important in implementing the prioritisation system and maintaining daily visibility of patients awaiting imaging, biopsy or MDT discussion. Radiology leadership was consulted regarding the feasibility of faster reporting for high-priority cases, although later project learning suggested that radiology capacity remained a downstream constraint despite improvement elsewhere in the pathway.

Several implementation risks were anticipated from the outset. These included limited staff availability for extra clinic and biopsy sessions, restricted radiology reporting capacity and the possibility that improvements in one part of the pathway would shift pressure to another. The team also anticipated that administrative redesign would only be effective if supported by consistent communication and routine review. To promote sustainability, the new processes were embedded within departmental workflow through recurring review meetings, real-time dashboard tracking, rotational staffing arrangements and ongoing collaboration between urology, radiology, pathology and administrative teams. The intention was not to create a temporary audit-only process, but to incorporate successful changes into standard service delivery. This is consistent with the manuscript’s later emphasis on weekly audit feedback, dashboards and continued cross-team engagement as the basis for sustained improvement.

Strategy

The improvement strategy was structured around two sequential Plan-Do-Study-Act (PDSA) cycles conducted over a 3-month period, with continuous data collection and weekly review meetings throughout implementation. Each cycle targeted a specific bottleneck within the prostate cancer diagnostic pathway, while allowing learning from the first cycle to inform changes in the second. Run charts were reviewed regularly to assess whether observed changes were sustained and whether variation across the pathway was narrowing over time.

PDSA cycle 1

Aim

To reduce the clinic-to-biopsy interval by at least 30% within 1 month.

Change hypothesis

Increasing biopsy capacity and improving list utilisation would absorb backlog and shorten waiting times for patients proceeding from specialist review to biopsy.

Plan and implementation

Cycle 1 focused on the clinic-to-biopsy stage, which baseline process mapping had identified as one of the most delayed and modifiable parts of the pathway. An additional weekly local anaesthetic transperineal biopsy list was introduced, increasing biopsy capacity from 6 to 10 slots per week. Newly referred eligible patients were preferentially allocated to the expanded list. To improve list utilisation, booking staff introduced reminder calls and appointment confirmation procedures, particularly after early experience showed that missed appointments reduced the effect of the added capacity.

Study

Cycle 1 data were reviewed weekly using run charts and service-tracking logs. The clinic-to-biopsy interval improved substantially, falling from a median of 28.0 days at baseline to approximately 19.0 days during the first cycle, with a later postintervention median of 16.8 days in the full reaudit period. This suggested that the intervention worked, but that its effect depended not only on added capacity but also on reliable patient attendance and tighter booking oversight.

Act and key learning

The principal learning from Cycle 1 was that added capacity alone was not sufficient. A small number of non-attendances initially reduced utilisation of the extra biopsy list, meaning that administrative refinements were needed to realise the full benefit of the intervention. Reminder calls and active list management therefore became part of routine workflow.

PDSA cycle 2

Aim

To reduce the biopsy-to-MDT interval and improve overall pathway coordination after gains had been achieved in clinic and biopsy access.

Change hypothesis

Strengthening administrative coordination, especially around MRI reporting, pathology completion and MDT preparation, would reduce downstream delay and improve the predictability of decision-making.

Plan and implementation

Cycle 2 focused on coordination after biopsy. Administrative officers were assigned to track pending MRI reports and liaise with radiology where results were delayed. The MDT coordinator began prepopulating discussion lists once pathology results became available, rather than waiting until the meeting week. In parallel, the added one-stop urology clinic increased new-patient capacity from 12 to 16 slots per week, helping reduce upstream referral-to-clinic delay. A small pilot of MRI-before-clinical assessment was tested in nine patients to explore whether earlier imaging might support faster downstream decisions, although this was not adopted as a formal pathway for all patients during the study period. The pilot was not scaled primarily because of radiology capacity constraints and the administrative complexity of pre-authorising MRI without prior specialist review, rather than clinical concerns about the approach itself, which showed promise in reducing downstream decision time.

Study

Weekly review showed that the biopsy-to-MDT interval fell from 18.3 days at baseline to 7.6 days, achieving the project target and reducing variation considerably. This was consistent with the run charts, which showed that in Cycle 2 most biopsy-to-MDT intervals clustered below 10 days, whereas Cycle 1 showed much broader spread. However, Cycle 2 also revealed an important unintended consequence: as clinic and biopsy stages became more efficient, radiology reporting delays became more visible and, in some cases, increased under workload pressure. MRI reporting therefore remained a downstream constraint rather than an area of clear improvement.

Act and key learning

The major learning from Cycle 2 was that improving one part of the pathway can shift pressure to another. Administrative coordination and earlier MDT preparation were effective, but sustainable improvement depended on stronger collaboration with radiology, including faster escalation of pending reports and consideration of protected rapid-reporting capacity for urgent cases. This reinforced the need for pathway-wide redesign rather than isolated service changes.

Continuous monitoring and iterative learning

Data were reviewed weekly by the project team and discussed at departmental meetings. Run charts were used to visualise change over time and to distinguish genuine process improvement from random variation. These data showed that Cycle 2 was associated not only with shorter median intervals but also with tighter clustering and fewer extreme delays, especially for clinic-to-biopsy and biopsy-to-MDT stages. Real-time monitoring fostered accountability, enabled rapid adjustment when bottlenecks re-emerged and helped embed quality improvement activity within routine team practice. Overall, the iterative PDSA approach achieved measurable gains while also strengthening the local culture of continuous measurement, shared ownership and cross-departmental problem solving.

Results

Cohort characteristics

A total of 42 patients were included in Cycle 1 (November–December 2024) and 38 patients in Cycle 2 (January–February 2025). Patients referred with suspected prostate cancer during the baseline and reaudit periods were screened for inclusion, as shown in figure 1 (for baseline characteristics of patients, see online supplemental table 1). Patients with incomplete pathway data or atypical diagnostic pathways were excluded as described in the Methods. No major differences were observed between the two cohorts in terms of age, PSA level or referral indication, supporting their comparability for local preintervention and postintervention assessment.

Figure 1. Cohort flow for baseline and reaudit cycles.

Process measure improvements

Median referral-to-first-urology-clinic time improved modestly from 25.3 days (range 12–45) in Cycle 1 to 22.3 days (range 10–52) in Cycle 2. Although this change was smaller than the downstream improvements, it was directionally consistent with the addition of one extra weekly one-stop clinic and suggests some benefit from increased access to first specialist review. However, referral-to-clinic remained the longest component of the pathway and continued to limit overall performance.

Median clinic-to-biopsy time decreased from 28.0 days (range 3–57) in Cycle 1 to 16.8 days (range 6–50) in Cycle 2, a 40% reduction. This was the largest observed improvement and was temporally associated with the additional weekly biopsy list and tighter booking oversight. In the earlier PDSA phase, the median had already fallen to approximately 19.0 days, with the later Cycle 2 median suggesting that the benefit strengthened once reminder calls and active list management became routine.

Median biopsy-to-MDT time improved from 18.3 days (range 7–55) to 7.6 days (range 1–12), representing a reduction of more than 50%. This improvement was associated with earlier MDT list preparation, closer administrative tracking and faster escalation of pending results. Variation also narrowed substantially, indicating a more stable and predictable downstream process.

MRI report turnaround was reviewed as a supportive process measure rather than a primary driver of project success. As shown in figure 2 (and online supplemental table 2), MRI reporting time remained largely unchanged and continued to represent a downstream bottleneck despite improvement in clinic access, biopsy capacity and MDT preparation. This finding is important because it shows that pathway gains in one area can expose capacity constraints elsewhere.

Figure 2. Comparison of key diagnostic pathway metrics before and after intervention. MDT, multidisciplinary team.

As shown in figure 2, the pathway duration from referral to MDT discussion decreased from 71.6 days in Cycle 1 to 46.7 days in Cycle 2, a reduction of approximately 35%. This improvement was driven primarily by shortening of the clinic-to-biopsy and biopsy-to-MDT intervals. These gains should be interpreted against the project's primary endpoint of completion of diagnosis and treatment planning within 8 weeks of referral.

Primary outcome measure

The proportion of patients completing diagnosis and treatment planning within 8 weeks of referral increased from 47% in Cycle 1 to 58% in Cycle 2. This represents an absolute improvement of 11 percentage points and indicates partial achievement of the project aim, although substantial scope for further improvement remained. To avoid mixed-target reporting, the authors treat the 8-week referral-to-diagnosis-and-treatment-planning endpoint as the sole primary benchmark in the Results section.

Variation over time and relationship to the intervention

The run charts support that the observed change was not limited to a shift in central tendency alone. In figure 3a, Cycle 1 clinic-to-biopsy intervals show broad scatter with several outliers exceeding 50 days, whereas Cycle 2 values are more tightly clustered, with most cases completed in less than 21 days. In figure 3b, biopsy-to-MDT intervals also show a marked narrowing of spread in Cycle 2, with nearly all patients discussed within 10 days. These visual patterns strengthen the interpretation that the intervention was associated not only with shorter median waiting times but also with greater process reliability.

Figure 3. Run-chart comparison of pathway variation before and after intervention. (a) Clinic-to-biopsy intervals (b) Biopsy-to-MDT intervals.

Although this was not a controlled study and causal claims should therefore remain cautious, the timing and direction of improvement were consistent with the implemented changes. The most marked reductions occurred in the pathway stages directly targeted by the intervention, while the MRI reporting step, which was not fully resolved operationally, remained comparatively resistant to improvement. This pattern supports the interpretation that the intervention contributed materially to the observed gains, while also highlighting the influence of contextual factors such as radiology workload and appointment non-attendance.

Figure 3 illustrates the reduction in process variation across the two most directly targeted stages of the pathway. In the clinic-to-biopsy stage, Cycle 1 showed marked scatter with several prolonged waits, whereas Cycle 2 values were more tightly grouped and generally fell below 21 days. A similar pattern was seen for biopsy-to-MDT time, where Cycle 2 showed substantially narrower spread and most patients were discussed within 10 days. These visual patterns support the interpretation that the intervention improved not only median performance but also predictability and operational consistency.

Data completeness, unintended consequences and cost implications

Data completeness exceeded 95% across both cycles, and timestamps were checked independently by two reviewers against source systems. Minor discrepancies in electronic documentation could not be excluded, but there was no evidence of systematic missingness likely to alter the overall direction of findings. No formal balancing-measure dataset was available for non-attendance, cancellations, postbiopsy complications or unscheduled reattendance, and this should be acknowledged explicitly in the Results and limitations sections.

The main unintended consequence observed during implementation was that radiology reporting delays became more visible once clinic and biopsy access improved. In other words, success in reducing upstream delays shifted operational pressure downstream. There were no major additional financial costs, as the intervention relied primarily on timetable reallocation, administrative coordination and use of existing staff and infrastructure rather than new capital investment.

Lessons and limitations

Lessons learned

This project showed that meaningful improvement in prostate cancer diagnostic timeliness can be achieved through relatively simple, low-cost operational changes rather than major new infrastructure. The most important gains came from improving coordination, increasing targeted capacity at key bottlenecks and involving the staff who manage the pathway on a day-to-day basis. In particular, engagement with administrative and secretarial staff proved highly valuable. Their familiarity with booking delays, MRI report chasing and MDT preparation helped identify practical bottlenecks that were less visible from a purely clinical perspective. Weekly data review and run charts also played an important role by providing rapid feedback, sustaining team engagement and helping the project evolve iteratively rather than remaining a fixed intervention throughout.

An important lesson was that added capacity alone was not enough. In the first PDSA cycle, the additional biopsy list reduced delay, but the full benefit was not realised immediately because non-attendance and list underutilisation reduced efficiency. Reminder calls and tighter booking oversight were therefore necessary refinements. A second key lesson was that improving one stage of the pathway can expose constraints elsewhere. As clinic access and biopsy throughout improved, radiology reporting delays became more visible and, in some cases, worsened under pressure. This highlighted the need for whole-pathway redesign rather than isolated changes in a single service component.

Several practical challenges arose during implementation. Staff availability for additional clinic and biopsy sessions was not always consistent, leading to occasional cancellations or reduced flexibility. Variations in patient readiness and appointment adherence also affected scheduling efficiency, although reminder calls and patient communication partially mitigated this. If the project were repeated, earlier formal engagement with radiology leadership, clearer escalation processes for delayed MRI reporting and prospective capture of balancing measures would be prioritised from the outset. Protected rapid-reporting capacity for urgent cases and predefined follow-up audit intervals would also strengthen sustainability.

This project had several limitations. It was a single-centre, short-duration quality improvement project with a modest sample size, particularly in Cycle 2, so the findings should be interpreted as evidence of local service improvement rather than broadly generalisable proof of effectiveness. Because the design was retrospective and pre–post rather than controlled, chance, temporal effects and contextual confounding cannot be excluded fully. For example, seasonal variation in referrals or staffing may have influenced pathway times, and awareness among staff that performance was being monitored may itself have changed behaviour during the audit period. Although these effects are difficult to separate from the intervention, the use of consecutive cohorts, standardised timestamps, dual-review data checking and run-chart assessment helped reduce some of these threats to validity.

Data quality was another limitation. Although data completeness exceeded 95%, the project depended on electronic timestamps recorded within routine hospital systems, and minor documentation delays or inconsistencies may have introduced imprecision. In addition, formal balancing measures such as non-attendance, cancellations, post-biopsy complications or unplanned reattendance were not collected consistently across both cycles. The project also did not include patient-reported outcome or experience measures, so it could not directly assess whether shorter pathway times reduced anxiety or improved perceived quality of care. Future cycles should include these measures alongside longer-term monitoring to determine whether the observed improvements are sustained under different workload conditions.

Overall, the project’s main strength was that it combined pragmatic service redesign with continuous measurement and iterative learning. Its main limitation was that it improved pathway performance within one local setting over a relatively short period. Further work should therefore focus on sustained post-project monitoring, stronger radiology integration and broader measurement of patient experience and balancing outcomes.

Conclusion

This quality improvement project showed that delays in the prostate cancer diagnostic pathway at Lifeline Hospital, Karachi, were reduced through targeted, low-cost operational change. The project achieved its primary aims: the clinic-to-biopsy interval fell by more than 30%, the biopsy-to-MDT interval fell by more than 40% and the proportion of patients completing diagnosis and treatment planning within 8 weeks of referral improved by 11 percentage points. These findings suggest that pragmatic service redesign focused on clinic access, biopsy capacity and administrative coordination can improve pathway timeliness in a resource-constrained tertiary-care setting.

The project adds to existing literature by showing that meaningful improvement is possible without major capital investment or external funding. In this setting, the most important gains came not from new infrastructure but from better scheduling, closer cross-team communication, clearer prioritisation and continuous measurement. The intervention was effectively cost-neutral, relying on reallocation of existing staff time, one additional weekly clinic, one additional weekly biopsy list and structured administrative oversight rather than new equipment or externally funded service expansion. This makes the model potentially attractive to decision-makers seeking practical quality improvement approaches within existing institutional resources.

The measures used in this project were appropriate for assessing operational performance, although balancing measures and patient-reported outcomes were not collected consistently and should be incorporated in future work. While the project did not change its core aims during implementation, iterative PDSA refinement strengthened delivery, particularly through reminder calls, active list management and closer MDT preparation. The findings therefore reflect not only the effect of increased capacity but also the value of adapting workflow in response to real-time learning.

Sustainability has been supported through integration of real-time pathway tracking, weekly review meetings and continued engagement between urology, radiology, pathology and administrative teams. To strengthen this further, postproject monitoring should continue through predefined repeat measurement, for example, quarterly pathway review and planned reaudit at regular intervals, so that gains can be tracked under changing workload conditions. These arrangements are intended to embed the intervention within routine service governance rather than treat it as a one-off audit exercise.

This model is likely to be transferable to similar tertiary hospitals facing diagnostic bottlenecks in prostate cancer care, although local adaptation will be necessary. Future work should focus on improving prediagnostic imaging pathways, reducing MRI reporting delays, adding formal balancing measures and incorporating patient-reported outcome and experience measures to assess the wider impact of faster diagnosis and treatment planning. Longer-term follow-up will also be needed to determine whether the observed improvements are sustained and whether further whole-pathway redesign can increase the proportion of patients completing diagnosis and treatment planning within 8 weeks of referral.

Data availability statement

Data sharing not applicable as no datasets generated and/or analysed for this study.