Clinical audit of medical referral notes at Bangladesh Medical University Hospital
Authors
- Kazi Ali AftabDepartment of Internal Medicine, Bangladesh Medical University (former Bangabandhu Sheikh Mujib Medical University), Dhaka, Bangladesh
- Md. Abul Kalam AzadDepartment of Internal Medicine, Bangladesh Medical University (former Bangabandhu Sheikh Mujib Medical University), Dhaka, Bangladesh
- Khaled Mahbub MurshedDepartment of Internal Medicine, Bangladesh Medical University (former Bangabandhu Sheikh Mujib Medical University), Dhaka, Bangladesh
- Abdullah Al FaisalDepartment of Internal Medicine, Bangladesh Medical University (former Bangabandhu Sheikh Mujib Medical University), Dhaka, Bangladesh
- Md. Hashibul Hasan ShawonDepartment of Internal Medicine, Bangladesh Medical University (former Bangabandhu Sheikh Mujib Medical University), Dhaka, Bangladesh
- Mohd. Mujtaba Akib BhuiyanDepartment of Internal Medicine, Bangladesh Medical University (former Bangabandhu Sheikh Mujib Medical University), Dhaka, Bangladesh
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Published by Bangladesh Medical University (former Bangabandhu Sheikh Mujib Medical University).
Method: A cross-sectional study was carried out on 113 referral notes gathered from various departments in April 2025. Eight audit standards were adapted from BMU's existing referral notes. Trained auditers collected the completed referral notes and extracted data from the notes.
Result: About seven in ten (71.7%) of referral notes had date and time written properly. Most referrals (81.4%) were sent to faculty members, 65.5% having clear justification and 46.9% having full clinical information. About six in ten (58.4%) responded timely with proper explanations (61.1%), and a follow-up plan (65.5%). The study revealed considerable deficiencies. Overall, 46.9% of them met all required standards.
Conclusion: More than half of the referral notes did not meet the required standards. We recommend the introduction of an electronic referral system with a provision of periodic audits to maximise healthcare quality.
Clinical audits are systematic reviews of clinical practice aimed at assessing and enhancing the quality of patient care by comparing current practices against established standards [1]. Medical referral notes act as a vital communication tool among healthcare providers, ensuring continuity of care, accurate diagnosis, and prompt treatment [2]. Poorly written referral notes can cause delays in patient management, miscommunication, and suboptimal clinical outcomes [3]. Therefore, evaluating the quality of referral documentation by the service providers are crucial for improvements of healthcare. The success of medical referrals depends on the completeness, clarity, and relevance of the information provided [4]. Studies have indicated that incomplete or vague referral letters contribute to diagnostic mistakes, unnecessary tests, and increased healthcare costs [5,6].
A well-organised referral note should include patient demographics, clinical history, examination findings, provisional diagnosis, and clear referral objectives [7]. However, audits across different healthcare settings show significant variation in the quality of referral documentation, with key elements often missing [8]. In low- and middle-income countries, these challenges are intensified by limited resources, high patient volumes, and insufficient training in medical documentation [9,10]. Even in high-income settings, variability in referral quality continues, emphasising the need for standardised templates and ongoing professional training [11]. Clinical audits provide a systematic way to assess compliance with best practices, pinpoint deficiencies, and apply corrective measures. [12]. Previous studies have demonstrated that audit-driven quality improvement initiatives result in improved patient outcomes and more efficient healthcare systems [13].
Anecdotal reports from clinicians at Bangladesh Medical University (BMU) indicated frequent issues with referral quality, such as missing information and ambiguous instructions. This audit was initiated to objectively examine the completeness and accuracy of referral notes, identify common deficiencies, and suggest evidence-based improvements.
This clinical audit was conducted on referral notes written in April 2025. One hundred thirteen referral notes were collected from the Medicine and Allied departments and the Surgery and Allied departments located in the blocks C and D. The inclusion criteria were inter-departmental referrals. Duplicate referrals were excluded.
Referral notes
BMU’s existing referral note format was considered the audit standards, having following eight indicators:
Referral side
Referral date and time
The referral should specify the date and time it was composed. Proper documentation ensures accountability and facilitates tracking delays in response. An absence of a clearly written referral date and time makes it difficult to evaluate timelines.
Referral recipient
Specifies the recipient's designation (e.g., Faculty/Medical Officer/Student) and helps to determine whether the referral reached the appropriate level of expertise.
Type of referral
There are two options: urgent and routine. Urgent referral requires immediate attention within an hour (e.g., life-threatening conditions). Routine referral can be responded within 24 hours.
Clinical information
The referral format includes relevant history (symptoms, duration, medical history, etc.), physical findings (vitals, examination notes), and lab/imaging results (if available) to support the referral.
Reason for referral
There is a large space for writing a clear justification and expected action from the respondent. Explain why the patient is referred (e.g., specialist opinion, further tests), and what action is anticipated (e.g., surgical assessment, diagnostic confirmation).
Referral respondent
This indicates who acknowledged or acted upon the referral and helps evaluate whether the responder had sufficient expertise.
Response side
Response date and time
The responding clinician should record the date and time in the format.
Response duration
It was calculated by subtracting the response time for the referral time. Perfect timing indication if the response was within the expected timeframe (e.g., urgent < 1 hour, routine < 24 hours).
Response quality
A proper explanation includes assessment, treatment plan, and a clear instruction.
Data collection and analysis
Data were extracted by trained auditors using a standardised checklist. The auditors were physicians who had completed structured training to understand referral standards (e.g., required clinical elements, urgency criteria), apply audit tools consistently (e.g., checklists), and reduce bias (e.g., avoiding subjective interpretations of "adequate" documentation). Auditor training was conducted by the authors at the Department of Internal Medicine of BMU covering referral standard criteria defining a "complete" referral (e.g., history, examination, labs), checklist utilisation, and maintaining confidentiality and objectivity. Descriptive statistics (numbers and their corresponding percents) were used to analyse compliance.


In this clinical audit, we found that the 71.7% referral notes had properly written referral dates and times. The referrals were mostly (88.5%) sent to the faculty members. Routine referrals (within 24 hours) accounted for 73.5% of the instances. Fully documented clinical information was present in 46.9% of cases. The reason for referral with a clear justification was provided in 65.5% notes (Table 1).
Clinical audit standards | Number (%) |
Referral side | |
Referral date and time written | |
Date and time | 81 (71.7) |
Date only | 28 (24.8) |
No date and time | 4 (3.5) |
Type of referral notes | |
Routine | 83 (73.5) |
Urgent | 13 (12.4) |
Not specified | 5 (4.4) |
Clinical information written in referral notes | |
History | 108 (95.6) |
Physical examination | 53 (46.9) |
Lab investigation | 79 (69.9) |
Reason written in referral notes | |
Clearly | 74 (65.5) |
Unclearly | 39 (34.5) |
Type of respondent who responded to the referral notes | |
Faculty | 92 (81.4) |
Student | 6 (5.3) |
Not specified | 11 (9.8) |
Response side | |
Response date and time | |
Date and time | 50 (44.2) |
Date | 42 (37.2) |
No date and time | 21 (18.6) |
Response duration | |
Perfect time | 66 (58.4) |
Delayed response | 25 (22.1) |
Not responded | 5 (4.4) |
Response with proper explanation | |
Written | 69 (61.1) |
Not written | 44 (38.9) |
Variables | Number (%) |
Indication of colposcopy a |
|
VIA positive | 200 (66.7) |
Abnormal pap test | 13 (4.3) |
Human papilloma virus DNA positive | 4 (1.3) |
Suspicious looking cervix | 14 (4.7) |
Others b | 69 (23.0) |
Histopathological diagnosis | |
Cervical intraepithelial neoplasia 1 | 193 (64.3) |
Cervical intraepithelial neoplasia 2 | 26 (8.7) |
Cervical intraepithelial neoplasia 3 | 32 (10.7) |
Invasive cervical cancer | 27 (9.0) |
Chronic cervicitis | 17 (5.6) |
Squamous metaplasia | 5 (1.7) |
a All patients were referred to the Colposcopy Clinic of Bangabandhu Sheikh Mujib Medical University (currently, Bangladesh Medical University); VIA indicate, visual inspection of the cervix with acetic acid; b (per vaginal discharge, post-coital bleeding) |
Variables | Frequency (%) |
Indication of colposcopy |
|
Visual inspection of the cervix with acetic acid positive | 200 (66.7) |
Abnormal pap test | 13 (4.3) |
Human papilloma virus DNA positive | 4 (1.3) |
Suspicious looking cervix | 14 (4.7) |
Others (per vaginal discharge, post-coital bleeding) | 69 (23.0) |
Histopathological diagnosis | |
Cervical Intraepithelial Neoplasia 1 | 193 (64.3) |
Cervical Intraepithelial Neoplasia 2 | 26 (8.7) |
Cervical Intraepithelial Neoplasia 3 | 32 (10.7) |
Invasive cervical cancer | 27 (9.0) |
Chronic cervicitis | 17 (5.6) |
Squamous metaplasia | 5 (1.7) |
Groups based on pre-test marks | Pretest | Posttest Marks (%) | Difference in pre and post-test marks (mean improvement) | P |
Didactic lecture classes | ||||
<50% | 36.6 (4.8) | 63.2 (9.4) | 26.6 | <0.001 |
≥50% | 52.8 (4.5) | 72.4 (14.9) | 19.6 | <0.001 |
Flipped classes | ||||
<50% | 36.9 (4.7) | 82.2 (10.8) | 45.4 | <0.001 |
≥50% | 52.8 (4.6) | 84.2 (10.3) | 31.4 | <0.001 |
Data presented as mean (standard deviation) |
Background characteristics | Number (%) |
Age at presentation (weeks)a | 14.3 (9.2) |
Gestational age at birth (weeks)a | 37.5 (2.8) |
Birth weight (grams)a | 2,975.0 (825.0) |
Sex |
|
Male | 82 (41) |
Female | 118 (59) |
Affected side |
|
Right | 140 (70) |
Left | 54 (27) |
Bilateral | 6 (3) |
Delivery type |
|
Normal vaginal delivery | 152 (76) |
Instrumental delivery | 40 (20) |
Cesarean section | 8 (4) |
Place of delivery |
|
Home delivery by traditional birth attendant | 30 (15) |
Hospital delivery by midwife | 120 (60) |
Hospital delivery by doctor | 50 (25) |
Prolonged labor | 136 (68) |
Presentation |
|
Cephalic | 144 (72) |
Breech | 40 (20) |
Transverse | 16 (8) |
Shoulder dystocia | 136 (68) |
Maternal diabetes | 40 (20) |
Maternal age (years)a | 27.5 (6.8) |
Parity of mother |
|
Primipara | 156 (78) |
Multipara | 156 (78) |
aMean (standard deviation), all others are n (%) |
Background characteristics | Number (%) |
Age at presentation (weeks)a | 14.3 (9.2) |
Gestational age at birth (weeks)a | 37.5 (2.8) |
Birth weight (grams)a | 2,975.0 (825.0) |
Sex |
|
Male | 82 (41) |
Female | 118 (59) |
Affected side |
|
Right | 140 (70) |
Left | 54 (27) |
Bilateral | 6 (3) |
Delivery type |
|
Normal vaginal delivery | 152 (76) |
Instrumental delivery | 40 (20) |
Cesarean section | 8 (4) |
Place of delivery |
|
Home delivery by traditional birth attendant | 30 (15) |
Hospital delivery by midwife | 120 (60) |
Hospital delivery by doctor | 50 (25) |
Prolonged labor | 136 (68) |
Presentation |
|
Cephalic | 144 (72) |
Breech | 40 (20) |
Transverse | 16 (8) |
Shoulder dystocia | 136 (68) |
Maternal diabetes | 40 (20) |
Maternal age (years)a | 27.5 (6.8) |
Parity of mother |
|
Primipara | 156 (78) |
Multipara | 156 (78) |
aMean (standard deviation), all others are n (%) |
Mean escape latency of acquisition day | Groups | ||||
NC | SC | ColC | Pre-SwE Exp | Post-SwE Exp | |
Days |
|
|
|
|
|
1st | 26.2 (2.3) | 30.6 (2.4) | 60.0 (0.0)b | 43.2 (1.8)b | 43.8 (1.6)b |
2nd | 22.6 (1.0) | 25.4 (0.6) | 58.9 (0.5)b | 38.6 (2.0)b | 40.5 (1.2)b |
3rd | 14.5 (1.8) | 18.9 (0.4) | 56.5 (1.2)b | 34.2 (1.9)b | 33.8 (1.0)b |
4th | 13.1 (1.7) | 17.5 (0.8) | 53.9 (0.7)b | 35.0 (1.6)b | 34.9 (1.6)b |
5th | 13.0 (1.2) | 15.9 (0.7) | 51.7 (2.0)b | 25.9 (0.7)b | 27.7 (0.9)b |
6th | 12.2 (1.0) | 13.3 (0.4) | 49.5 (2.0)b | 16.8 (1.1)b | 16.8 (0.8)b |
Average of acquisition days | |||||
5th and 6th | 12.6 (0.2) | 14.6 (0.8) | 50.6 (0.7)b | 20.4 (2.1)a | 22.4 (3.2)a |
NC indicates normal control; SC, Sham control; ColC, colchicine control; SwE, swimming exercise exposure. aP <0.05; bP <0.01. |
Referrals were responded mostly by faculty members (81.4%), with a perfect response time (58.4%) and proper explanations (61.1%). There was no date or time in case of 28.3% of the notes. In 55.8% referral notes, response time and dates were not written. Only 46.9% met all required standards.
In addition, we explored whether there was any follow-up plan in the referral reply although it was not in the list of the standards. Such a plan was mentioned by 65.5% of the responding clinicians (Figure 1).
Categories | Number (%) |
Sex |
|
Male | 36 (60.0) |
Female | 24 (40.0) |
Age in yearsa | 8.8 (4.2) |
Education |
|
Pre-school | 20 (33.3) |
Elementary school | 24 (40.0) |
Junior high school | 16 (26.7) |
Cancer diagnoses |
|
Acute lymphoblastic leukemia | 33 (55) |
Retinoblastoma | 5 (8.3) |
Acute myeloid leukemia | 4 (6.7) |
Non-Hodgkins lymphoma | 4 (6.7) |
Osteosarcoma | 3 (5) |
Hepatoblastoma | 2 (3.3) |
Lymphoma | 2 (3.3) |
Neuroblastoma | 2 (3.3) |
Medulloblastoma | 1 (1.7) |
Neurofibroma | 1 (1.7) |
Ovarian tumour | 1 (1.7) |
Pancreatic cancer | 1 (1.7) |
Rhabdomyosarcoma | 1 (1.7) |
aMean (standard deviation) |





Test results | Disease | Sensitivity (%) | Specificity (%) | PPV (%) | NPV (%) | ||
Yes | No | ||||||
Reid’s score ≥ 5 | Positive | 10 | 15 | 37.0 | 94.5 | 40.1 | 93.8 |
Negative | 17 | 258 |
|
|
|
| |
Swede score ≥ 5 | Positive | 20 | 150 | 74.1 | 45.0 | 11.8 | 94.6 |
Negative | 7 | 123 |
|
|
|
| |
Swede score ≥ 8 | Positive | 3 | 21 | 11.1 | 92.3 | 12.5 | 91.3 |
Negative | 24 | 252 |
|
|
|
| |
a High-grade indicates a score of ≥5 in both tests; PPV indicates positive predictive value; NPV, negative predictive value |
Test | Sensitivity (%) | Specificity (%) | Positive predictive value (%) | Negative predictive value (%) |
Reid’s score ≥ 5 | 37.0 | 94.5 | 40.0 | 93.8 |
Swede score ≥ 5 | 74.1 | 45 | 11.8 | 94.6 |
Swede score ≥ 8 | 11.1 | 92.3 | 12.5 | 91.3 |
Test | Sensitivity (%) | Specificity (%) | Positive predictive value (%) | Negative predictive value (%) |
Reid’s score ≥ 5 | 37.0 | 94.5 | 40.0 | 93.8 |
Swede score ≥ 5 | 74.1 | 45 | 11.8 | 94.6 |
Swede score ≥ 8 | 11.1 | 92.3 | 12.5 | 91.3 |
Narakas classification | Total 200 (100%) | Grade 1 72 (36%) | Grade 2 64 (32%) | Grade 3 50 (25%) | Grade 4 14 (7%) |
Complete recoverya | 107 (54) | 60 (83) | 40 (63) | 7 (14) | - |
Near complete functional recovery but partial deformitya | 22 (11) | 5 (7) | 10 (16) | 6 (12) | 1 (7) |
Partial recovery with gross functional defect and deformity | 31 (16) | 7 (10) | 13 (20) | 10 (20) | 1 (7) |
No significant improvement | 40 (20) | - | 1 (1.5) | 27 (54) | 12 (86) |
aSatisfactory recovery bGrade 1, C5, 6, 7 improvement; Grade 2, C5, 6, 7 improvement; Grade 3, panpalsy C5, 6, 7, 8, 9, Grade 4, panpalsy with Hornon’s syndrome. |
Narakas classification | Total 200 (100%) | Grade-1 72 (36%) | Grade-2 64 (32%) | Grade-3 50 (25%) | Grade-4 14 (7%) |
Complete recoverya | 107 (54) | 60 (83) | 40 (63) | 7 (14) | - |
Near complete functional recovery but partial deformitya | 22 (11) | 5 (7) | 10 (16) | 6 (12) | 1 (7) |
Partial recovery with gross functional defect and deformity | 31 (16) | 7 (10) | 13 (20) | 10 (20) | 1 (7) |
No significant improvement | 40 (20) | - | 1 (1.5) | 27 (54) | 12 (86) |
aSatisfactory recovery bGrade 1, C5, 6, 7 improvement; Grade 2, C5, 6, 7 improvement; Grade 3, panpalsy C5, 6, 7,8,9, Grade 4, panpalsy with Hornon’s syndrome. |
Variables in probe trial day | Groups | ||||
NC | SC | ColC | Pre-SwE Exp | Post-SwE Exp | |
Target crossings | 8.0 (0.3) | 7.3 (0.3) | 1.7 (0.2)a | 6.0 (0.3)a | 5.8 (0.4)a |
Time spent in target | 18.0 (0.4) | 16.2 (0.7) | 5.8 (0.8)a | 15.3 (0.7)a | 15.2 (0.9)a |
NC indicates normal control; SC, Sham control; ColC, colchicine control; SwE, swimming exercise exposure. aP <0.01. |
Pain level | Number (%) | P | ||
Pre | Post 1 | Post 2 | ||
Mean (SD)a pain score | 4.7 (1.9) | 2.7 (1.6) | 0.8 (1.1) | <0.001 |
Pain categories | ||||
No pain (0) | - | 1 (1.7) | 31 (51.7) | <0.001 |
Mild pain (1-3) | 15 (25.0) | 43 (70.0) | 27 (45.0) | |
Moderete pain (4-6) | 37 (61.7) | 15 (25.0) | 2 (3.3) | |
Severe pain (7-10) | 8 (13.3) | 2 (3.3) | - | |
aPain scores according to the visual analogue scale ranging from 0 to 10; SD indicates standard deviation |
Surgeries | Number (%) | Satisfactory outcomes n (%) |
Primary surgery (n=24) |
|
|
Upper plexus | 6 (25) | 5 (83) |
Pan-palsy | 18 (75) | 6 (33) |
All | 24 (100) | 11 (46) |
Secondary Surgery (n=26) |
|
|
Shoulder deformity | 15 (58) | 13 (87) |
Wrist and forearm deformity | 11 (42) | 6 (54) |
All | 26 (100) | 19 (73) |
Primary and secondary surgery | 50 (100) | 30 (60) |
Mallet score 14 to 25 or Raimondi score 2-3 or Medical Research grading >3 to 5. |
Narakas classification | Total 200 (100%) | Grade-1 72 (36%) | Grade-2 64 (32%) | Grade-3 50 (25%) | Grade-4 14 (7%) |
Complete recoverya | 107 (54) | 60 (83) | 40 (63) | 7 (14) | - |
Near complete functional recovery but partial deformitya | 22 (11) | 5 (7) | 10 (16) | 6 (12) | 1 (7) |
Partial recovery with gross functional defect and deformity | 31 (16) | 7 (10) | 13 (20) | 10 (20) | 1 (7) |
No significant improvement | 40 (20) | - | 1 (1.5) | 27 (54) | 12 (86) |
aSatisfactory recovery bGrade 1, C5, 6, 7 improvement; Grade 2, C5, 6, 7 improvement; Grade 3, panpalsy C5, 6, 7,8,9, Grade 4, panpalsy with Hornon’s syndrome. |
Trials | Groups | ||||
NC | SC | ColC | Pre-SwE Exp | Post-SwE Exp | |
1 | 20.8 (0.6) | 22.1 (1.8) | 41.1 (1.3)b | 31.9 (1.9)b | 32.9 (1.8)a, b |
2 | 10.9 (0.6) | 14.9 (1.7) | 37.4 (1.1)b | 24.9 (2.0)b | 26.8 (2.5)b |
3 | 8.4 (0.5) | 9.9 (2.0) | 32.8 (1.2)b | 22.0 (1.4)b | 21.0 (1.4)b |
4 | 7.8 (0.5) | 10.4 (1.3) | 27.6(1.1)b | 12.8 (1.2)b | 13.0 (1.4)b |
Savings (%)c | 47.7 (3.0) | 33.0 (3.0) | 10.0 (0.9)b | 23.6 (2.7)b | 18.9 (5.3)b |
NC indicates normal control; SC, Sham control; ColC, colchicine control; SwE, swimming exercise exposure. aP <0.05; bP <0.01. cThe difference in latency scores between trials 1 and 2, expressed as the percentage of savings increased from trial 1 to trial 2 |


Lesion-size | Histopathology report | Total | |||||
CIN1 | CIN2 | CIN3 | ICC | CC | SM | ||
0–5 mm | 73 | 0 | 0 | 0 | 5 | 5 | 83 |
6–15 mm | 119 | 18 | 1 | 4 | 0 | 0 | 142 |
>15 mm | 1 | 8 | 31 | 23 | 12 | 0 | 75 |
Total | 193 | 26 | 32 | 27 | 17 | 5 | 300 |
CIN indicates cervical intraepithelial neoplasia; ICC, invasive cervical cancer; CC, chronic cervicitis; SM, squamous metaplasia |
| Histopathology report | Total | ||||||
CIN1 | CIN2 | CIN3 | ICC | CC | SM | |||
Lesion -Size | 0-5 mm | 73 | 0 | 0 | 0 | 5 | 5 | 83 |
6-15 mm | 119 | 18 | 1 | 4 | 0 | 0 | 142 | |
>15 mm | 1 | 8 | 31 | 23 | 12 | 0 | 75 | |
Total | 193 | 26 | 32 | 27 | 17 | 5 | 300 | |
CIN indicates Cervical intraepithelial neoplasia; ICC, Invasive cervical cancer; CC, Chronic cervicitis; SM, Squamous metaplasia |
Group | Didactic posttest marks (%) | Flipped posttest marks (%) | Difference in marks (mean improvement) | P |
<50% | 63.2 (9.4) | 82.2 (10.8) | 19.0 | <0.001 |
≥50% | 72.4 (14.9) | 84.2 ( 10.3) | 11.8 | <0.001 |
Data presented as mean (standard deviation) |





The audit revealed a large variability in referral quality, with critical omissions that could impact badly patient care. The absence of date and time, incomplete clinical information, delayed response time, lack of proper explanation, and lack of follow-up plans were particularly concerning, as they may lead to inappropriate and delayed management. Less than half of referral notes met all required standards.
The BMU currently uses a paper-based referral note. Transitioning to electronic systems for documentation and referrals may enhance the quality and legibility of medical notes, reduce errors and improve compliance with standards. Our compliance with proper date/time documentation, aligns closely with the finding of Johnston et al (68%) [1]. Similarly complete clinical information aligns almost exactly with the findings of Pronovost et al. (47%) on the adherence standards [14]. Our finding of 65.5% referrals with clear justification remains below the 82% standard reported by Wright and colleagues [13].
Perfect response time in our analysis (58.4%) was lower than that reported by others (61.1% - 78.0%) [15,16]. Follow-up plan documentation (65.5%) failed to reach the 80% standard demonstrated in Shojania and Grimshaw's optimal practice model [17].
Most concerning was our finding that less than half of referrals met all standards. This gap underscores the need for systemic interventions like those proposed by Dixon-Woods and Martin, whose framework achieved 89% sustained improvement through continuous quality monitoring [18].
Our results support WHO’s recommendation for standardized referral protocols in low-compliance settings [19]. Moreover, this study supports global efforts to strengthen healthcare systems through ongoing quality improvement and patient-centred care. Given the increasing focus on interdisciplinary collaboration in modern healthcare, optimising referral processes is essential for reducing errors and enhancing clinical efficiency [20].
This study has limited generalisability as it was done at Bangladesh's top academic hospital for a short period. However, we presume the situation is similar or even worse in other tertiary-level hospitals, such as medical college hospitals and specialised institutes.
Conclusion
The clinical audit identified large gaps in referral documentation and processing, including incomplete clinical information, delayed responses and lack of follow-up plans. We recommend introduction of an electronic system for referral notes with an alert system, periodic training, and audits for maximizing the benefits.