Abstract
Background
Effective record-keeping is crucial for safe surgical care worldwide. While structured tools for auditing records exist, evidence from low- and middle-income countries (LMICs) remains limited. This study was conducted to uphold the standard of surgical record-keeping in a tertiary care center in Sri Lanka using the Surgical Tool for Auditing Records (STAR).
Methods
This prospective, descriptive closed-loop audit included 92 patient records, 44 from Cycle 1 (April 1-14, 2024) and 48 from Cycle 2 (April 15-28, 2024). The evaluation was conducted using the STAR, which assesses documentation based on 50 criteria distributed across six key domains. Structured templates and educational sessions were utilized as interventions. Both audit cycle scores were compared to draw conclusions.
Results
The overall quality of surgical documentation improved significantly, with the mean STAR score rising from 67.34 ± 8.32 to 77.11 ± 7.17 (p < 0.001). Statistically significant improvements were noted across most domains except Consent and Anesthetic Records. Enhancements were observed across all evaluated domains, with the Subsequent Entries category showing the most notable progress (34.8%), while the Anesthetic Records demonstrated the smallest improvement (3.31%). The Discharge Summary section performed exceptionally well, attaining an average score of 94.44 ± 5.61; however, the diagnosis was recorded in only 50% of the reviewed records (n = 24/48). Although the Consent domain improved by 25.89%, it continued to be the lowest-scoring area overall.
Conclusion
Simple, low-cost interventions, such as templates and structured feedback, significantly improved record-keeping quality. Although the STAR has been widely applied globally, this study adds valuable evidence from a Sri Lankan tertiary hospital, offering practical insights for enhancing surgical documentation in LMICs and other resource-limited healthcare systems.
Keywords: clinical audit, low- and middle-income countries, medical records, quality improvement, surgical documentation
Introduction
Clinical records, supported by evidence-based medicine, skilled professionals, and emerging digital systems, form the backbone of modern healthcare, serving as both a clinical and administrative tool [1]. They serve as comprehensive documentation of a patient's medical history, current health status, treatment plans, and outcomes [2]. Sound documentation is essential in cases where multiple providers or disciplines are involved, as it ensures that everyone has access to the same information and can coordinate the management seamlessly [2]. Additionally, it also fulfils the legal and regulatory requirements that can be critical in legal situations where proof of care is needed [3]. Comprehensive medical records serve as evidence that a healthcare provider has adhered to the accepted standards of care [3]. The secondary functions of maintaining clinical records are that they serve as sources for research, epidemiology, service planning, resource allocation, and performance monitoring [4].
Therefore, the accuracy and legibility of these documents are paramount to making informed decisions, avoiding medical errors, and maintaining high-quality care [5]. Good clinical record-keeping should reflect complete and timely data gathering, as well as the recording and analysis of clinical information in a way that effectively supports its intended purpose [6].
Despite its importance, clinical record-keeping is often overlooked, leading to poorly maintained notes, illegible or inconsistent entries, offensive comments, and missing information [7]. Poor record-keeping is a common factor cited in malpractice litigation against medical practitioners [7]. There is an urgent need for evidence-based interventions to improve record-keeping standards and ensure that patient information is accurately and comprehensively documented.
A clinical audit enhances the quality of healthcare by assessing clinical practices against established standards to pinpoint areas needing improvement and implement positive changes [8]. Various tools for reviewing clinical records exist, such as the Crawford-Beresford-Lafferty (CRABEL) system, designed for inpatient specialties [9].
The Surgical Tool for Auditing Records (STAR) is a validated system derived from the CRABEL tool. It includes 50 items across six domains assessing surgical documentation quality. STAR has been shown to improve standards of record-keeping [10-12]. Initial Clerking (10 items; 20%), Subsequent Entries (8 items; 16%), Consent (7 items; 14%), Anesthetic Record (7 items; 14%), Operative Record (9 items; 18%), and Discharge Summary (9 items; 18%) were included as domains. The STAR system, known for its high internal consistency (Cronbach’s α = 0.959), provides a structured and reliable alternative to the CRABEL scoring system for assessing record-keeping quality [11]. The total score for individual records is calculated using the following formula: (50 - deducted points) × 2 [11].
Several clinical audits on record-keeping standards have been published across various institutions in Sri Lanka. However, it is unfortunate that no such audits have been published by the National Hospital of Sri Lanka (NHSL) despite it being the leading state hospital in the country. There is a need to raise awareness about the clinical value and research potential of auditing current record-keeping and documentation practices. This study aimed to evaluate and enhance surgical record documentation in a major tertiary care hospital in Sri Lanka using the STAR scoring system within a closed-loop audit cycle. Beyond its local context, this study provides lessons on practical, low-cost strategies for improving documentation that are relevant to other low- and middle-income countries (LMICs), while being potentially adaptable across global healthcare systems.
This study was presented as an abstract at the annual conference of the College of Surgeons of Sri Lanka in 2024.
Materials and methods
Study design and setting
This investigation was conducted as a prospective, quantitative audit. It focused on surgical documentation from patients admitted to the University Surgical Unit of the NHSL. Ethical approval was obtained from the Ethics Review Committee of the NHSL. All patient identifiers were removed before analysis to maintain confidentiality, and the Committee granted a waiver of individual patient consent. Cycle 1 was performed to establish baseline documentation quality. After interventions, Cycle 2 was completed using the same methodology to assess post-intervention improvement in surgical documentation.
Sample size
Due to logistical constraints and the high patient turnover in the surgical unit, a representative sample of 92 records (44 pre-intervention, 48 post-intervention) was reviewed using systematic random sampling. This approach ensured feasibility while maintaining proportional representation of the full ward record pool (approximately 200 records/month). These records were evaluated to determine the standard and completeness of surgical documentation. And the minimum requirement of STAR was 20 records, which was exceeded.
Study period
Data collection for each audit cycle was carried out over two weeks. The first cycle was conducted from April 1 to April 14, 2024, and the second cycle from April 15 to April 28, 2024. Both cycles included weekend and emergency admissions in accordance with the hospital duty roster to ensure representative sampling.
Data collection
Inpatient case notes from the surgical unit were reviewed manually and scored individually using the STAR. A minimum of 20 patient files is required for valid use of the STAR system. Data collection was performed twice daily at fixed time intervals to minimize temporal bias and ensure consistency in assessing documentation completeness. The project was jointly developed and implemented through collaboration between the NHSL University Surgical Unit and the Faculty of Medicine, University of Colombo.
Interventions
Between the two audit cycles, several strategies were implemented to enhance the quality of surgical documentation. Standardized templates were introduced for operative notes, anesthesia records, postoperative progress, and daily review entries. These templates, designed in alignment with institutional protocols, were distributed among medical officers in the University Surgical Unit. Feedback sessions were organized to present the findings from the first audit cycle. Junior doctors and registrars received targeted training through small-group discussions, emphasizing accurate and comprehensive documentation. They were encouraged to routinely use the standardized templates for operative and postoperative records and to ensure consistent completion and filing within patient case notes.
Statistical analysis
Data were analyzed using IBM SPSS Statistics for Windows, Version 23.0 (Released 2015; IBM Corp., Armonk, NY, USA), the licensed version available at the institution during the study. Descriptive statistics were used to summarize domain-specific and total STAR scores as means ± standard deviations. The distribution of paired differences between Cycle 1 and Cycle 2 was assessed using the Shapiro-Wilk test. When the differences followed a normal distribution, comparisons were made using the paired t-test; otherwise, the Wilcoxon signed-rank test was applied. Statistical significance was set at p < 0.05. Categorical variables were compared using chi-squared or Fisher’s exact tests where appropriate. All analyses followed the ethical principles of the Declaration of Helsinki (1996). The methodology was adapted from previously published STAR-based audits of surgical documentation [13,14].
Results
From April 1 to 28, 2024, we evaluated 92 patient records using the STAR. The results were encouraging, with an overall improvement in the score from an average of 67.34 in Cycle 1 to 77.11 in Cycle 2, as depicted in Figure 1.
Figure 1. Boxplot comparison of documentation (STAR) scores between Cycle 1 (A) and Cycle 2 (B).
(A) Median = 66.2%, IQR = 12.7 (60.8-73.5); minimum = 53.8%; maximum = 84.5%. (B) Median = 78.1%, IQR = 11.9 (71.3-83.2), minimum = 62.4%; maximum = 92.0%.
The box represents the interquartile range (IQR), extending from the 25th percentile (Q1) to the 75th percentile (Q3). The horizontal line inside the box indicates the median; the whiskers denote the minimum and maximum values within 1.5 × IQR.
STAR: Surgical Tool for Auditing Records.
Notably, all domains of STAR showed varying levels of improvement from the first cycle to the second, except the Consent and Anesthetic Record domains. The Subsequent Entries domain demonstrated the most significant enhancement (34.8%), followed by Consent (25.89%), while the Anesthetic Record domain showed the smallest improvement (3.31%) (Table 1, Figure 2, Figure 3).
Table 1. Domain-wise comparison of STAR scores between audit cycles.
Mean ± SD STAR scores for each documentation domain during Cycle 1 (N = 44) and Cycle 2 (N = 48) are presented with the percentage increase after intervention. Improvements reflect the effect of structured templates and feedback implemented between cycles.
STAR: Surgical Tool for Auditing Records.
| Domain | Cycle 1 (mean ± SD) | Cycle 2 (mean ± SD) | Test used | p-value | Statistical significance |
| Initial Clerking | 61.82 ± 13.17 | 71.14 ± 17.15 | Paired t-test | 0.0060 | Yes |
| Subsequent Entries | 52.34 ± 8.82 | 71.02 ± 10.64 | Paired t-test | <0.0001 | Yes |
| Consent | 51.30 ± 25.84 | 61.69 ± 24.99 | Paired t-test | 0.0779 | No |
| Anesthetic Record | 81.49 ± 9.54 | 84.09 ± 11.20 | Wilcoxon signed-rank | 0.0970 | No |
| Operative Record | 70.96 ± 16.81 | 80.81 ± 15.22 | Wilcoxon signed-rank | 0.0013 | Yes |
| Discharge Summary | 86.11 ± 13.15 | 93.94 ± 5.60 | Wilcoxon signed-rank | 0.0075 | Yes |
| Total STAR score | 67.34 ± 8.32 | 77.11 ± 7.17 | Paired t-test | 3.56 × 10⁻⁶ | Yes |
Figure 2. Domain-specific STAR scores for Cycles 1 and 2.
STAR- Surgical Tool for Auditing Records.
Figure 3. Percentage increase in STAR scores from Cycles 1 and 2.
STAR- Surgical Tool for Auditing Records.
While none of the domains reached a perfect score of 100 in the second cycle, the Discharge Summary came close with a near-perfect score of 93.94. This is a testament to the overall quality of the records. At the subscale level, significant improvements were observed in several items, including documentation of consultant identity, postoperative signatures, and consent-related risks/complications (exact Fisher's/chi-square p-values reported in Table 2). Other subscales showed numerical but non-significant changes.
Table 2. Comparison of STAR subscale compliance between the audit cycles.
Differences were analyzed using Fisher’s exact or Chi-square tests as appropriate. Exact two-sided p-values are reported; p < 0.05 was considered statistically significant.
| Domain | Subscale | Cycle 1, n/N (%) | Cycle 2, n/N (%) | Test | p-value | Statistical significance |
| Initial Clerking | Patient name | 43/44 (97.73%) | 48/48 (100.00%) | Fisher's | 0.4783 | No |
| Hospital number | 42/44 (95.45%) | 48/48 (100.00%) | Fisher's | 0.226 | No | |
| Referral source | 22/44 (50.00%) | 33/48 (68.75%) | Chi-square | 0.1054 | No | |
| Consultant | 7/44 (15.91%) | 22/48 (45.83%) | Chi-square | 0.0042 | Yes | |
| Date/time | 1/44 (2.27%) | 12/48 (25.00%) | Fisher's | 0.0019 | Yes | |
| Working diagnosis | 15/44 (34.09%) | 13/48 (27.08%) | Chi-square | 0.615 | No | |
| Investigations/results | 37/44 (84.09%) | 47/48 (97.92%) | Fisher's | 0.0257 | Yes | |
| Management plan | 26/44 (59.09%) | 31/48 (64.58%) | Chi-square | 0.7436 | No | |
| Allergies | 44/44 (100.00%) | 46/48 (95.83%) | Fisher's | 0.4955 | No | |
| Name/post | 35/44 (79.55%) | 44/48 (91.67%) | Fisher's | 0.1352 | No | |
| Subsequent Entries | Preop patient name/number | 43/44 (97.73%) | 48/48 (100.00%) | Fisher's | 0.4783 | No |
| Preop date/time | 19/44 (43.18%) | 22/48 (45.83%) | Chi-square | 0.9636 | No | |
| Preop heading | 37/44 (84.09%) | 42/48 (87.50%) | Chi-square | 0.8655 | No | |
| Preop Pt state/examination | 19/44 (43.18%) | 28/48 (58.33%) | Chi-square | 0.2137 | No | |
| Preop pertinent results | 27/44 (61.36%) | 47/48 (97.92%) | Fisher's | 0.056 | No | |
| Preop plan | 39/44 (88.64%) | 47/48 (97.92%) | Fisher's | 0.1002 | No | |
| Preop signature/name/post | 3/44 (6.82%) | 9/48 (18.75%) | Fisher's | 0.1238 | No | |
| Preop legibility | 43/44 (97.73%) | 48/48 (100.00%) | Fisher's | 0.4783 | No | |
| Postop Pt name/number | 39/44 (88.64%) | 48/48 (100.00%) | Fisher's | 0.0221 | No | |
| Postop date/time | 13/44 (29.55%) | 33/48 (68.75%) | Chi-square | 0.0004 | Yes | |
| Postop heading | 36/44 (81.82%) | 45/48 (93.75%) | Fisher's | 0.1096 | No | |
| Postop Pt state/examination | 29/44 (65.91%) | 44/48 (91.67%) | Fisher's | 0.0038 | Yes | |
| Postop pertinent results | 39/44 (88.64%) | 47/48 (97.92%) | Fisher's | 0.1002 | No | |
| Postop plan | 38/44 (86.36%) | 47/48 (97.92%) | Fisher's | 0.0515 | No | |
| Postop signature/name/post | 0/44 (0.00%) | 12/48 (25.00%) | Fisher's | 0.0003 | Yes | |
| Postop legibility | 43/44 (97.73%) | 48/48 (100.00%) | Fisher's | 0.4783 | No | |
| Consent | Patient name/number/date | 39/44 (88.64%) | 47/48 (97.92%) | Fisher's | 0.1002 | No |
| Operation | 19/44 (43.18%) | 32/48 (66.67%) | Chi-square | 0.04 | Yes | |
| Side and site | 20/44 (45.45%) | 22/48 (45.83%) | Chi-square | 1.0 | No | |
| Benefits | 12/44 (27.27%) | 18/48 (37.50%) | Chi-square | 0.4107 | No | |
| Risks/complications | 12/44 (27.27%) | 27/48 (56.25%) | Chi-square | 0.0094 | Yes | |
| Signatures | 33/44 (75.00%) | 45/48 (93.75%) | Fisher's | 0.0186 | Yes | |
| Name/post | 23/44 (52.27%) | 26/48 (54.17%) | Chi-square | 1.0 | No | |
| Anesthetic Record | Name of anesthetist | 41/44 (93.18%) | 48/48 (100.00%) | Fisher's | 0.1055 | No |
| Preop assessment | 44/44 (100.00%) | 47/48 (97.92%) | Fisher's | 1.0 | No | |
| Drugs and doses | 36/44 (81.82%) | 46/48 (95.83%) | Fisher's | 0.0439 | Yes | |
| Monitoring | 44/44 (100.00%) | 47/48 (97.92%) | Fisher's | 1.0 | No | |
| IVF given | 43/44 (97.73%) | 47/48 (97.92%) | Fisher's | 1.0 | No | |
| Postanesthetic information | 40/44 (90.91%) | 47/48 (97.92%) | Fisher's | 0.1894 | No | |
| Name/signature | 3/44 (6.82%) | 1/48 (2.08%) | Fisher's | 0.3457 | No | |
| Operative Record | Name/number/date | 41/44 (93.18%) | 47/48 (97.92%) | Fisher's | 0.3457 | No |
| Operating surgeon | 39/44 (88.64%) | 48/48 (100.00%) | Fisher's | 0.0221 | Yes | |
| Diagnosis post procedure | 8/44 (18.18%) | 27/48 (56.25%) | Chi-square | 0.0004 | Yes | |
| Description of findings | 22/44 (50.00%) | 43/48 (89.58%) | Chi-square | 0.0001 | Yes | |
| Details of tissues removed | 43/44 (97.73%) | 48/48 (100.00%) | Fisher's | 0.4783 | No | |
| Details of sutures used | 30/44 (68.18%) | 35/48 (72.92%) | Chi-square | 0.7879 | No | |
| Prosthetics with numbers | 40/44 (90.91%) | 43/48 (89.58%) | Fisher's | 1.0 | No | |
| Post-op instructions | 44/44 (100.00%) | 48/48 (100.00%) | Fisher's | 1.0 | No | |
| Surgeon/signature | 14/44 (31.82%) | 11/48 (22.92%) | Chi-square | 0.469 | No | |
| Discharge Summary | Name/number/address | 44/44 (100.00%) | 48/48 (100.00%) | Fisher's | 1.0 | No |
| Admission and discharge dates | 44/44 (100.00%) | 48/48 (100.00%) | Fisher's | 1.0 | No | |
| Discharging consultants | 41/44 (93.18%) | 48/48 (100.00%) | Fisher's | 0.1055 | No | |
| Diagnosis | 13/44 (29.55%) | 24/48 (50.00%) | Chi-square | 0.0741 | No | |
| Pertinent investigations | 40/44 (90.91%) | 48/48 (100.00%) | Fisher's | 0.0486 | Yes | |
| Operations/procedures | 43/44 (97.73%) | 48/48 (100.00%) | Fisher's | 0.4783 | No | |
| Complications | 36/44 (81.82%) | 48/48 (100.00%) | Fisher's | 0.0019 | Yes | |
| Medication on discharge | 39/44 (88.64%) | 48/48 (100.00%) | Fisher's | 0.0221 | Yes | |
| Follow-up | 41/44 (93.18%) | 48/48 (100.00%) | Fisher's | 0.1055 | No |
Of the subscales of the Discharge Summary, none showed any defects in the second cycle except for stating the diagnosis, which was only available in 50% of the records (n = 24). We believe that the junior doctors are reluctant to make any mistakes when providing a diagnosis. This may be due to a lack of support, experience, and the unavailability of an electronic coding system in the country. We believe this may be the same in most LMICs. But adequate interventions, as shown in our study, will bridge this gap over a long-term period if these audits are repeated at timely intervals.
Despite the Consent domain having the lowest score in both cycles, it showed a significant improvement of 25.89% from the first cycle to the second. This improvement is a promising sign for further enhancement. The benefits of the Procedure subscale were the least scored in the second cycle, found in only 18 (37.50%) of the records. Other subscales with notable deficiencies include the side and site of the procedure and the name and post of the doctor, appearing in only 22 (45.83%) and 26 (54.17%) of the records, respectively (Table 2).
The Subsequent Entries domain, which showed the most significant improvement of 34.8%, is a key area of progress. Its subscale, the postoperative name/signature of the doctor, scored the lowest overall in the first cycle, with zero entries. However, there was a notable improvement in the second cycle, with 12 records (25.0%) including this subscale.
The Anesthetic Record showed the slightest increase in mean score from the first cycle to the second, primarily due to the pre-audit mean score of 81.49. The name of the anesthetist was seen in 100% (n = 48) of the records in the second cycle. However, the name/signature subscale was only shown to be present in one (2.08%) record in the second cycle as opposed to three (6.82%) records in the first, indicating the need for further improvement in this area.
The total STAR score increased significantly from 67.34 ± 8.32 in Cycle 1 to 77.11 ± 7.17 in Cycle 2 (paired t-test, t = -5.317, p = 3.56 × 10⁻⁶). Significant improvements were also observed in Initial Clerking (61.82 ± 13.17 → 71.14 ± 17.15; t = -2.889, p = 0.0060), Subsequent Entries (52.34 ± 8.82 → 71.02 ± 10.64; t = −7.509, p < 0.0001), Operative Record (70.96 ± 16.81 → 80.81 ± 15.22; Wilcoxon W = 172.5, p = 0.0013), and Discharge Summary (86.11 ±13.15 → 93.94±5.60; Wilcoxon W = 87.5, p = 0.0075). Improvements in Consent (51.30 ± 25.84 → 61.69 ± 24.99; t = -1.806, p = 0.0779) and Anesthetic Record (81.49 ± 9.54 → 84.09 ± 11.20; Wilcoxon W = 26.5, p = 0.0970) did not reach statistical significance.
Discussion
This study was conducted to uphold the standard of surgical record-keeping and aimed to improve adherence to the STAR checklist in the professorial surgical unit services in the NHSL.
Our results indicate a significant overall improvement in the total STAR score from an average of 67.34 in Cycle 1 to 77.11 in Cycle 2. There were also improvements in documentation quality across all domains following the implementation of several targeted interventions between the two audit cycles. The improvement is a positive indicator of the efficacy of the interventions employed.
The increase in the total STAR score of our study is consistent with the existing literature. Tuffaha et al. reported an increase in the total STAR score from 83.4 to 97.6 [11]. Basu et al. documented an increment in the STAR score from 87 in the first cycle to 93 in the next cycle [15]. Chalikonda et al. also noted a rise from 76.7 to 81 for 10 years [10]. Another descriptive study rather than a full cycle audit by Kakada et al. revealed 98% compliance of their surgical records with STAR [16]. The relative improvement in documentation in our study was more significant compared to the above audits, which is likely due to the lower baseline STAR score of 67.34 ± 8.32. However, the mean score in the second cycle (77.11 ± 7.17) was comparatively lower than those reported in the literature. This discrepancy could be attributed to the shorter study period and limited sample size.
The most notable improvement was observed in the Subsequent Entries domain, which saw a substantial increase of 34.8%. This significant enhancement underscores the importance of regular updates and follow-ups in patient records. The improvement can be attributed to the implementation of structured templates and increased awareness among junior doctors and registrars about the importance of thorough documentation.
The Consent domain remained the lowest-scoring domain in both cycles despite showing an improvement of 25.89%. This indicates that while progress has been made, there are still considerable challenges in ensuring the comprehensive documentation of informed consent. The subscale for "benefits of the procedure" was the least documented, found in only 37.50% (n = 18) of records in the second cycle. Other deficiencies included the documentation of the side and site of the procedure (n = 22, 45.83%) and the name and post of the doctor (n=26, 54.17%). Obtaining informed consent is a fundamental ethical principle in contemporary medical practice and involves an educational process [17]. These findings highlight the need for continuous education and the redesign of consent forms to ensure that all critical information is consistently documented.
During the first cycle, one of the most significant defects was the lack of mentioning the name and post when documenting subsequent entries postoperatively (n = 0). This was also seen in subsequent entries preoperatively (n = 3, 6.82%) and relating to the name of the consultant during the initial clerking (n = 7, 15.91%). This is important since identifying the individuals involved in a patient's care ensures accountability and continuity of care. Another significant issue identified in the first cycle was the omission of the date and time during the initial clerking, which compromises the accuracy and traceability of medical records. Following the interventions, improvements were seen across all subscales mentioned above.
Despite the improvements, the Anesthetic Record domain showed the slightest increase in mean score, with only a 3.31% improvement. The pre-audit mean score for this domain was already high at 81.49, indicating that the baseline quality of anesthetic documentation was relatively good. However, there was the persistence of issues such as the documentation of the name/signature of the anesthetist, which was only present in 2.08% (n = 1) of records in the second cycle, compared to the 6.82% (n = 3) in the first cycle. This suggests the need for targeted interventions in this area to confirm the accuracy and completeness of the information and ensure accountability.
The Operative Record and Discharge Summary domains also showed significant improvements (p = 0.0013 and p = 0.0075, respectively). The use of standardized templates for operative and discharge summaries likely contributed to these enhancements. The near-perfect score of 93.94 ± 5.6 in the Discharge Summary domain in the second cycle is particularly encouraging, suggesting that the interventions were highly influential in ensuring comprehensive discharge documentation.
Our findings resonate with international audits that used the STAR tool in high-income settings, demonstrating that structured interventions can yield meaningful improvements. Importantly, the challenges observed, such as incomplete consent documentation and inconsistent subsequent entries, are not unique to Sri Lanka but are shared across many LMICs. By showing that low-resource, practical measures such as templates and focused education can drive measurable improvements, this study contributes globally relevant evidence that can inform quality improvement initiatives in diverse healthcare systems.
Interventions may continue to focus on areas showing the least improvement, such as the Consent domain. The introduction of a standardized checklist could help ensure that essential information, including the name and post of medical personnel, as well as the date and time, is consistently documented. Regular feedback and recognition of good documentation practices may further motivate ward staff and reinforce adherence to high standards of record-keeping.
Templates, including structured forms and checklists, may support more organized patient management and facilitate high-quality care delivery [18]. They can improve record-keeping by providing a consistent framework for documentation and by reducing the risk of missing critical information. Moreover, they can help systematically aggregate data to evaluate institutional performance and identify areas needing enhancement. The adoption of electronic medical record systems could represent a valuable next step, as previous studies have demonstrated their benefits in improving documentation quality, efficiency, and cost-effectiveness [19].
Expanding the sample size and extending the study period in future audits may provide more comprehensive data and allow stronger comparisons with the existing literature. The findings from this audit may inform similar initiatives across Sri Lanka and other LMICs, contributing to broader efforts to improve the quality and safety of surgical documentation.
Limitations
This study was conducted in a single surgical unit with a relatively small sample size and short study period, which may limit the generalizability of the findings. However, the closed-loop design demonstrates a replicable model for record-keeping audits. The interventions, testing templates, structured education, and feedback are low-cost, scalable strategies that could be readily applied in similar units worldwide. Future multicenter and longer-term studies will help validate and expand these findings. The audit cycles were conducted within a single month, which was split in half, and temporal variation may have influenced results. Future audits should extend data collection over multiple months to minimize time-related bias.
Conclusions
This closed-loop audit has demonstrated that targeted interventions, including structured templates, feedback, and educational initiatives, significantly improved surgical record-keeping quality in a tertiary hospital in Sri Lanka. While limited to a single unit, the study highlights challenges in documentation that are widely encountered across surgical services, particularly in LMICs. The use of the STAR tool provides a simple yet effective framework for identifying deficiencies and tracking progress. These findings suggest that low-cost, scalable interventions can strengthen documentation practices and patient safety in diverse healthcare contexts, offering lessons that extend well beyond the local setting.
Acknowledgments
The authors thank Dr Siddiqa Omar Mohamed Ozaal, Senior Registrar in Chemical Pathology, National Hospital Sri Lanka, for the assistance with the statistical analysis.
Appendices
Key messages
What Is Already Known
Surgical documentation is often incomplete, and while tools like the STAR scoring system exist, most published audits come from high-income countries.
What This Study Adds
A closed-loop audit in Sri Lanka shows that simple, low-cost interventions (templates, structured feedback, education) can significantly improve surgical record-keeping.
Why It Matters Internationally
The findings offer a scalable, practical model for improving documentation and patient safety in LMICs, with lessons relevant to healthcare systems worldwide.
Disclosures
Human subjects: Informed consent for treatment and open access publication was obtained or waived by all participants in this study. Ethics Review Committee of the National Hospital of Sri Lanka (NHSL) issued approval AAJ/ETH/COM/2024/APRIL.
Animal subjects: All authors have confirmed that this study did not involve animal subjects or tissue.
Conflicts of interest: In compliance with the ICMJE uniform disclosure form, all authors declare the following:
Payment/services info: All authors have declared that no financial support was received from any organization for the submitted work.
Financial relationships: All authors have declared that they have no financial relationships at present or within the previous three years with any organizations that might have an interest in the submitted work.
Other relationships: All authors have declared that there are no other relationships or activities that could appear to have influenced the submitted work.
Author Contributions
Concept and design: Omar Mohamed Ozaal Abdul Mubarack, Dakshitha P. Wickramasinghe
Acquisition, analysis, or interpretation of data: Omar Mohamed Ozaal Abdul Mubarack, Dileesha Wickramasinghe
Drafting of the manuscript: Omar Mohamed Ozaal Abdul Mubarack, Dileesha Wickramasinghe
Critical review of the manuscript for important intellectual content: Omar Mohamed Ozaal Abdul Mubarack, Dakshitha P. Wickramasinghe
Supervision: Omar Mohamed Ozaal Abdul Mubarack, Dakshitha P. Wickramasinghe
References
- 1.Improving standards in clinical record-keeping. Pullen I, Loudon J. https://www.cambridge.org/core/journals/advances-in-psychiatric-treatment/article/improving-standards-in-clinical-recordkeeping/71A305470FB06716F5205532CC09D2B9 Advances in Psychiatric Treatment. 2006;12:280–286. [Google Scholar]
- 2.Setting the records straight - a prospective audit of the quality of case notes in a surgical department: general surgery. Chamisa I, Zulu BMW. https://journals.co.za/doi/abs/10.10520/EJC66722. S Afr J Surg. 2007;45:92, 94-5. [PubMed] [Google Scholar]
- 3.Retrospective audit in documentation practice in surgical inpatients records, a two cycles audit. Gasoma EB. Ir J Med Sci. 2023;192:2345–2349. doi: 10.1007/s11845-022-03224-2. [DOI] [PubMed] [Google Scholar]
- 4.Standards in medical record keeping. Mann R, Williams J. Clin Med (Lond) 2003;3:329–332. doi: 10.7861/clinmedicine.3-4-329. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.An audit of anaesthesia record-keeping at the Lagos University Teaching Hospital. Desalu I, Olanipekun O, Agbamu P. https://www.ajol.info/index.php/ajaic/article/view/60591 Aluta Dig Mag. 2010;10:1–5. [Google Scholar]
- 6.Bodek H, Chairperson B. Standards for Clinical Documentation and Recordkeeping: Clinical Documentation and Recordkeeping. New York, NY: New York State Society for Clinical Social Work, Inc; 1992. Clinical Documentation and Recordkeeping. [Google Scholar]
- 7.Medical record keeping: clarity, accuracy, and timeliness are essential. Abdelrahman W, Abdelmageed A. https://www.bmj.com/content/348/bmj.f7716 BMJ. 2014;348:0. [Google Scholar]
- 8.Clinical audit, a valuable tool to improve quality of care: general methodology and applications in nephrology. Esposito P, Dal Canton A. http://dx.doi.org/10.5527/wjn.v3.i4.249. World J Nephrol. 2014;3:249–255. doi: 10.5527/wjn.v3.i4.249. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Use of the CRABEL score for improving surgical case-note quality. Ho MY, Anderson AR, Nijjar A, Thomas C, Goenka A, Hossain J, Curley PJ. http://dx.doi.org/10.1308/003588405X60687. Ann R Coll Surg Engl. 2005;87:454–457. doi: 10.1308/003588405X60687. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.An assessment of the quality of clinical records in elective orthopaedics using the STAR score. Chalikonda L, Phelan N, O'Byrne J. Ir J Med Sci. 2019;188:849–853. doi: 10.1007/s11845-018-1918-7. [DOI] [PubMed] [Google Scholar]
- 11.The STAR score: a method for auditing clinical records. Tuffaha H, Amer T, Jayia P, Bicknell C, Rajaretnam N, Ziprin P. http://dx.doi.org/10.1308/003588412x13171221499865. Ann R Coll Surg Engl. 2012;94:235–239. doi: 10.1308/003588412X13171221499865. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Improving the quality of medical documentation in orthopedic surgical notes using the surgical tool for auditing records (STAR) Score. Mafrachi B, Al-Ani A, Al Debei A, et al. http://dx.doi.org/10.7759/cureus.19193. Cureus. 2021;13:0. doi: 10.7759/cureus.19193. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.The value of auditing surgical records in a tertiary hospital setting. Alqudah M, Aloqaily M, Rabadi A, et al. Cureus. 2022;14:0. doi: 10.7759/cureus.21066. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.A closed-loop clinical audit of surgical documentation of inpatient records at a tertiary level hospital in Egypt. Hassan AG, Elqaffas EO, Elbouridy AM, Shawky MM, El-Fayoumi TA. Cureus. 2023;15:0. doi: 10.7759/cureus.49862. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.The surgical tool for auditing records (STAR) for oral & maxillofacial record keeping: trauma vs elective. Basu I, Shah N, Perry M. https://www.bjoms.com/article/S0266-4356(18)30352-8/abstract Br J Oral Maxillofac Surg. 2018;56:0. [Google Scholar]
- 16.Assessment of the quality of oral squamous cell carcinoma clinical records in oral surgery with Surgical Tool for Auditing Records (STAR) scoring. Kakada P, Ramalingam K, Ramani P, Krishnan M. BMC Oral Health. 2024;24:1060. doi: 10.1186/s12903-024-04811-8. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.How informed is the informed consent? Vikas H, Kini A, Sharma N, Gowda NR, Gupta A. http://dx.doi.org/10.4103/jfmpc.jfmpc_2393_20. J Family Med Prim Care. 2021;10:2299–2303. doi: 10.4103/jfmpc.jfmpc_2393_20. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Effectiveness and perceptions of using templates in long-term condition reviews: a systematic synthesis of quantitative and qualitative studies. Morrissey M, Shepherd E, Kinley E, McClatchey K, Pinnock H. Br J Gen Pract. 2021;71:0–9. doi: 10.3399/BJGP.2020.0963. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Value of the electronic medical record for hospital care: update from the literature. Uslu A, Stausberg J. http://dx.doi.org/10.2196/26323. J Med Internet Res. 2021;23:0. doi: 10.2196/26323. [DOI] [PMC free article] [PubMed] [Google Scholar]