A retrospective cohort study on multidisciplinary collaboration in elective hip and knee arthroplasty to reduce duration of hospital admissions

Introduction

Total hip replacements (THR) and total knee replacements (TKR) are common procedures. 245,274 THRs and 232, 505 TKRs were performed between January 2020 and December 2022 according to the National Joint Registry (England, Wales, Northern Ireland, the Isle of Man and Guernsey) 2023 reports (1). X-rays are routinely performed for elective total hip and knee replacement patients at day 0 or day 1 post-operatively. These allow the surgeon to screen for unrecognised intraoperative complications (e.g., fracture), assess implant placement, and establish a radiographic baseline for follow-up. Additionally, they can guide training when a trainee has performed the operation. If a complication is identified on X-ray it can allow for an early intervention such as modification of weight bearing status or early revision. In our unit (The Royal Surrey County Hospital), elective arthroplasty patients must have a check X-ray performed post-operatively prior to discharge. This protocol is in keeping with the getting it right first time (GIRFT) elective hip or knee replacement pathway, which states that in the United Kingdom (UK) a post operative X-ray should be performed to assess position of implant prior to discharge (2). However, Husted et al., when looking at delays to discharge following arthroplasty surgery, noted that 20% of patients suffered a delay due to a logistical reason such as awaiting physiotherapy or post operative imaging (3). It was noted that in our unit some post operative elective total hip and knee patients had their discharge delayed awaiting their post-operative X-rays once being deemed medically fit for discharge. These delays in discharge also included additional overnight stays in hospital. Delayed discharges can have negative consequences at multiple levels. For patients, prolonged hospital stays increase the risk of hospital-acquired infections, reduced mobility, and overall decline in well-being. From a healthcare system perspective, delayed discharges lead to bed shortages, increasing patient congestion in emergency departments and limiting hospital capacity for new admissions. This, in turn, exacerbates waiting times for critical treatments and surgeries, ultimately impacting patient outcomes. Furthermore, the financial burden of unnecessary extended stays results in increased healthcare costs for both institutions and patients, placing strain on already stretched healthcare resources. Addressing this issue is crucial for enhancing hospital efficiency, optimizing resource utilization, and improving patient care. Singh Saggi et al. demonstrated that obtaining immediate post operative X-rays enroute from theatre recovery to the ward significantly reduced waiting time for post operative imaging and improved workflow efficiency and discharge of patients (4). However, in our unit, and commonly in the UK, district general hospital radiology departments are responsible for not only elective imaging but also emergent imaging from the emergency department and all other departments within the hospital. Therefore, consistent acquisition of post operative X-rays for elective hip and knee arthroplasty patients en route from theatre recovery to the ward was unable to be logistically feasible at our unit. The aim of this study was to quantify the magnitude of the issue related to post operative imaging for elective hip and knee arthroplasty patients and implement a practical interdepartmental collaborative solution between invested stakeholders within the care pathway of elective hip and knee arthroplasty patients within a district general hospital, thus optimising hospital length of stay and the associated patient safety and economic benefits. We present this article in accordance with the SQUIRE reporting checklist (available at https://jhmhp.amegroups.com/article/view/10.21037/jhmhp-25-4/rc).

Methods

Study design and data collection

This study was a two-cycle quality improvement project using a retrospective cohort. The study was conducted at an national health service (NHS) district general hospital (Royal Surrey County Hospital) in the orthopaedic department, which provides both acute trauma and elective services. The study included 399 elective arthroplasty cases (TKR, unicompartmental knee replacements and THR) performed between March 2023 and May 2024. Revision and emergency cases were excluded. The data set was derived from a review of all elective orthopaedic theatre lists within the date range. These lists and all patient documentation were on the hospital’s electronic patient record system (Cerner). For each arthroplasty case we noted the following patient demographics: age, gender, and American Society of Anaesthesiologist (ASA) grade (Table 1). We also noted the following time and date points: the operation, the postoperative X-ray, the physiotherapy discharge and the official time of discharge on the discharge letter. A delay was defined as the postoperative X-ray occurring after a physiotherapy discharge, in a patient deemed medically fit. Medically fit status was determined by an orthopaedic physician who assessed post operative observations, post operative blood test results, neurovascular status, pain control, and assessment of operative dressings to ensure integrity of surgical wound. If all post operative clinical factors were deemed to be within normal limits, then the patient was medically fit for discharge.

Delays were further divided into “same day” or “overnight” (if an additional overnight stay was incurred). Exclusion criteria included: unclear or insufficient documentation, if X-rays were not done due to industrial action, or the patient was transferred to another hospital.

The first data collection period (“Loop 1”) included 200 arthroplasty cases performed between 20th March 2023 and 1st August 2023. Three cases were excluded due to postoperative X-rays not happening due to industrial action and four cases were excluded for inadequate documentation. The final sample size for the first loop was n =193. The second data collection period (“Loop 2”) included 199 arthroplasty cases between 1^st December and 13^th May 2024. Five cases were excluded for inadequate documentation and two cases were excluded as the patients were transferred to another hospital. The final sample size for the second loop was n=192.

Root cause analysis and intervention

A root cause analysis was conducted to investigate the delay in obtaining post-operative X-ray. Factors considered included, patient fitness for transport to the radiology department, staffing issues, the portering procedure, and radiology request delays by the orthopaedic team and concerning if suitable nursing safety checks were performed to allow for intrahospital transfers. The portering procedure was examined to see if responsible for delay to X-ray slots. Physician radiology requesting for post operative X-rays was investigated as possible source for postponed imaging. The contemplated factors did not appear to be a barrier to post operative imaging. Subsequent discussion with the radiology department identified that there was no system in place to highlight clinical importance in the undifferentiated list on the electronic system of X-rays waiting to be performed across all departments in the hospital.

In response, a collaborative agreement between the radiology and orthopaedic departments was implemented. The process involved joint discussion between the physiotherapy and orthopaedic teams clinically prioritising patients that were likely to be medically fit and discharged by the physiotherapy team. Each morning, the orthopaedic team provided the radiology department with a prioritised list of elective hip and knee arthroplasty patients. Thus, the clinically prioritised list of the post-operative patients likely for discharge was created by multidisciplinary discussions between the orthopaedic team and the physiotherapy team. Factors used to prioritise patients included: ASA 1 or 2, age <75 years, no recorded intraoperative complication, adequate home support, and good preoperative independent mobility and independence in activities of daily living. The prioritised ‘golden patients’ were then allocated early morning post operative X-ray slots by the radiography team (Figure 1).

Figure 1 Pre and post intervention post-operative hip and knee arthroplasty X-ray acquisition procedure.

A period of four months was allowed before collection of the data for “loop 2”. Four months was collaboratively decided by the orthopaedic team to control for the confounding variable that the resident doctors rotate 4 monthly, thus hoping to capture the realistic picture that the intervention would withstand a new team change. The date range for this was 1st December 2023 to 13th May 2024 and population (after exclusions such as inadequate documentation, or patient transferred to a different hospital) was n=192.

Data analysis

The data set was compiled into an Excel spreadsheet for analysis. Using Excels IF function, we compared the physiotherapist discharge time to the X-ray time to identify delays. If the X-ray time was later than the physiotherapist discharge time, we recorded a delay. Once delays were identified, we calculated the duration of each delay and categorised them further into “same-day delays”, discharges that occurred within the same day as the X-ray, and “overnight delays” which were discharges that occurred after midnight of the X-ray taken. The remaining patients were categorised as “no delay”. Using Excel statistical functions, we calculated the mean, median, and interquartile ranges (IQRs) for patients categorised as having either a same-day delay or an overnight delay.

Statistical analysis

To account for potential confounding variables that could influence discharge timing, we compared baseline characteristics, including patient age, gender, and ASA score, between the pre- and post-intervention groups. A Chi-squared test was used for categorical variables (gender, ASA score), while a Mann-Whitney U test was used for age, as it was not normally distributed. The comparisons of the patient characteristics are presented in Table 1. After calculating the duration of delays for each patient, a chi-squared test of independence was performed to examine whether the distribution of discharge delays (no delay, same-day delay, overnight delay) differed significantly between the pre- and post-intervention groups. A statistically significant result would indicate an association between the intervention and the reduction in delays. To compare the duration of discharge delays between the two groups, we used a Mann-Whitney U test, a non-parametric test suitable for comparing two independent groups when the data is not normally distributed. This test assessed whether the intervention led to a significant reduction in the time patients remained delayed. To perform the chi-squared test and the Mann-Whitney U test we used python code inserted into Google Colab.

Results

Baseline characteristics of patients in the pre- and post-intervention groups are summarized in Table 1. The Mann-Whitney U test showed no significant difference in age distribution between Loop 1 and Loop 2 (U=5,184.000, P=0.65), suggesting that age was unlikely to impact delay outcomes. Similarly, chi-square analysis of gender distribution (χ²=0.000, P>0.99) and ASA grades (χ²=1.651, P=0.65) indicated no statistically significant differences between the groups.

Of the 193 patients in the first loop, 149 experienced no delay (77%), 26 experienced a same day delay (14%) and 18 experienced a delay resulting in them staying an extra night in hospital (9%). In the second loop of the 192 patients, 178 did not experience a delay (92%). 12 patients experienced a same day delay (6%), and 2 patients stayed an additional night in hospital (1%) shown in Table 2.

The mean length of discharge delay in loop 1 was 6.7 hours and in loop 2 was 4.3 hours. The median length of discharge delay in loops 1 and 2 were 1.92 and 1.2 hours, respectively. There were two outlying data points in loop 2 (both 19.8 hours 1.d.p). On further investigation, these two outlying data points highlight the only two cases in loop 2 that represented unnecessary overnight stays. For unknown reasons, the post operative X-rays did not occur day one postoperatively, indicating a breakdown in the post intervention acquisition procedure (Figure 1). The IQR in loop one was 17.4 hours and in loop two was 3.4 hours (Figure 2).

Figure 2 Duration of discharge delay.

A Chi-square test was conducted to compare the probability of a discharge delay pre and post the intervention. The proportion of delays significantly decreased from 44 (22.8%) patients pre intervention to 14 (7.3%) post intervention (χ²=16.90, P<0.001). More specifically, overnight delays reduced from 18 (9.3%) pre intervention, to 2 (1%) post intervention (χ²=15.1, P<0.001). Same day delays reduced from 26 (13.5%) pre intervention to 12 (6.3%) post intervention (χ²=8.04, P=0.004), confirming that the intervention led to a statistically significant reduction in delayed discharges (Figure 3).

Figure 3 Probability of delay to discharge pre- and post-intervention.

Post-intervention, the proportion of patients experiencing delays significantly decreased. However, a Mann-Whitney U test comparing discharge delay durations between the two loops did not show a statistically significant difference (U=282, P=0.64), indicating that while delays were reduced in frequency, their duration remained largely unchanged. Table 2 summarises the results pre and post intervention for the number and percentages of no delay, same day delay, overnight delay and length of discharge delay, in addition to showing the median and IQRs of the length of delays.

Discussion

Impact of postoperative X-ray delays on patient care and hospital costs

Unnecessary delays waiting for postoperative X-rays have deleterious effects; both economic and on patient welfare. The results showed 18 additional overnight stays were had in a four-month period. It was estimated in 2023 that the average cost of a standard hospital bed was £345 a day, removing any treatment or maintenance costs (2). Scaling this over the year, our unit alone had an estimated unnecessary spend of £19,000 on overnight stays for patients awaiting a post-operative arthroplasty X-ray. This is not considering the bed blocking effect or reducing the number of arthroplasty surgery cases which can be undertaken or other associated costs. Delayed discharge has been associated with significant impact on elective services with resultant cancellation of operations, thus having the knock-on effect on increasing elective waiting list times (3). The factors identified by a systematic review into the impact of delayed discharge identified 4 types of costs: (I) costs associated with patient stays after being deemed medically fit for discharge; (II) costs associated with delays in admission and prolonged waiting lists; (III) nursing staff costs while arranging delayed discharges; (IV) administration costs in conjunction with processes to solve delays (3). If these factors are considered, then the cost for prolonged length of stay due to delayed post-operative X-ray is much higher still. The issue of unnecessary overnight stays is ubiquitous across England. NHS England estimated from April 2022 to February 2023 there were a total of 4,372,011 overnight delays accosting the NHS nearly £1.7 billion (4).

Patient safety and quality of care implications

Patients suffer because of unnecessary hospital admissions. It can increase the incidence of hospital acquired infections and increase duration of rehabilitation time due to reduced mobility. Both factors are exacerbated by the common elderly demographic of patients requiring elective arthroplasty (5-7). Moreover, demand for arthroplasty is increasing and as such this will be an ever-increasing issue. It is predicted that by 2060 there will be almost a 40% increase in primary TKR and THR, estimating a total of 268,107 operations a year in the United Kingdom (7).

Effectiveness of the intervention in reducing delays

The data shows that whilst the intervention was simple, its impact was significant in improving the issue. A Chi-squared test of independence demonstrated a statistically significant difference in discharge delay categories between Loop 1 and Loop 2 (χ²=20.53, P<0.001). Post-intervention, the proportion of patients experiencing delays significantly decreased. However, a Mann-Whitney U test comparing discharge delay durations between the two loops did not show a statistically significant difference (U=282, P=0.64), indicating that while delays were reduced in frequency, their duration remained largely unchanged. A binomial test was conducted to compare the probability of a discharge delay before and after the intervention. The proportion of delays significantly decreased from 22.8% in Loop 1 to 7.3% in Loop 2 (P<0.001), confirming that the intervention led to a statistically significant reduction in delayed discharges.

These findings highlight the effectiveness of the intervention in reducing the overall frequency of discharge delays. However, the Mann-Whitney U test revealed that for those who did experience a delay, the length of delay did not significantly change (P=0.64). This suggests that while the intervention was effective in preventing delays, additional measures may be needed to reduce the duration of delays once they occur. Future studies could explore additional hospital workflow optimizations to address this aspect.

Improving patient flow is another strategy to resolve the issue of X-rays delaying discharge. This involves the patient going directly from the recovery suite to the radiology department before returning to the ward. However, our unit carries out both emergency and elective work on the same site, as do many others. As such, the radiology department runs a priority-based service and cannot guarantee the capacity to do this. Patient flow is better in elective “cold” sites and indeed such efficiency is an integral offering of these units. The UK GIRFT program has recognised this and targeted an increase in elective activity through elective surgical hubs of 30% in the year 2024/2025 (8,9).

Multidisciplinary collaboration as a key factor

The project was performed at a district general hospital in the UK, which has both elective and trauma services in the orthopaedic department. Therefore, the project was able to show that with coordination between orthopaedic, physiotherapy and radiology departments there was a reduction in delayed discharges and unnecessary inpatient overnight stays in medically fit for discharge elective hip and knee arthroplasty patients. It is common practice currently in the UK for district general hospitals to have both elective and trauma services on the same site. Therefore, this project highlights a simple solution that could be adopted by other district general hospitals with the aim of reducing costs through preventing prolonged length of stay for elective arthroplasty patients.

Alternative strategies to reduce discharge delays

GIRFT national guidance for elective hip and knee arthroplasty surgery in the UK leaning towards reducing length of stay through high quality care pathways and utilising Hub elective centres in the future there will be a significant impact on total costs with less economic burden on the district general hospital with regards to elective surgery. However, the uniform roll out of surgical Hubs for elective hip and knee arthroplasty surgery in the UK is yet to occur, and therefore it is imperative that efficiencies to produce the best possible care for patients but also reduce the economic burden on the struggling National Health Service are performed (10). Therefore, our study has shown a simple, inexpensive, low demand collaborative solution successful in reducing delayed discharges and unnecessary overnight inpatient stays for similar orthopaedic departments in district general hospitals with elective and trauma service commitments.

Conclusions

This quality improvement project demonstrates that a simple, multidisciplinary intervention can significantly reduce unnecessary discharge delays for elective arthroplasty patients awaiting postoperative X-rays. By streamlining communication and prioritization between orthopaedics, radiology, and physiotherapy teams, we achieved a 73% reduction in the likelihood of discharge delays. Additionally, our findings highlight the substantial economic burden of delayed discharges, with potential savings of approximately £19,000 per year for our unit alone resources that could be reallocated to improve patient care and elective capacity.While our intervention successfully reduced the frequency of discharge delays, the duration of delays for affected patients remained unchanged. This suggests that further workflow optimizations, such as improved radiology scheduling or dedicated arthroplasty imaging slots, may be necessary to eliminate delays entirely. Moreover, ensuring sustainability of this intervention is crucial, particularly in the face of resident doctor rotations. To address this, we have incorporated the protocol into the resident doctor induction handbook, reinforcing best practices for future teams.

Our findings also align with national healthcare priorities, such as the GIRFT initiative, which emphasizes efficiency and reduced inpatient stays. As the UK transitions towards dedicated elective surgical hubs, improvements like ours can serve as a scalable, cost-effective model for similar district general hospitals managing both elective and trauma workloads.

Ultimately, this study underscores the power of low-cost, high-impact interventions in reducing avoidable delays, improving patient flow, and alleviating financial strain on the NHS. Future research should explore complementary strategies to further enhance efficiency and ensure sustained improvements in elective surgical care.

Acknowledgments

None.

Footnote

Reporting Checklist: The authors have completed the SQUIRE reporting checklist. Available at https://jhmhp.amegroups.com/article/view/10.21037/jhmhp-25-4/rc

Data Sharing Statement: Available at https://jhmhp.amegroups.com/article/view/10.21037/jhmhp-25-4/dss

Peer Review File: Available at https://jhmhp.amegroups.com/article/view/10.21037/jhmhp-25-4/prf

Funding: None.

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://jhmhp.amegroups.com/article/view/10.21037/jhmhp-25-4/coif). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

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