Factors associated with delayed order-to-administration time in the emergency department: a retrospective analysis

Abstract

Background

Timely medication administration in the emergency department (ED) is critical for improving patient outcomes. This study aimed to identify predictors of delayed order-to-administration (OTA) time, defined as exceeding 30 min for stat medications.

Methods

A retrospective analysis was conducted in the ED of a 1,000-bed tertiary hospital. Patients aged 20 years or older who received stat medications between June 1 and August 31, 2020, were included. Only the first stat medication order per patient was analyzed. Data on patient demographics, triage characteristics, environmental factors, prescription details, and OTA times were extracted from the hospital’s electronic medical record and nursing information system. Multivariable logistic regression with backward elimination was used to identify predictors of OTA delays.

Results

Among the 11,429 patient visits included, 9.9% experienced OTA delays exceeding 30 min. Predictors of higher odds of delay included older age (adjusted odds ratio [aOR]: 1.01, 95% CI: 1.00–1.01), female sex (aOR: 1.49, 95% CI: 1.31–1.69), limited mobility (aOR: 1.38, 95% CI: 1.17–1.63 for ambulatory with assistance; aOR: 1.24, 95% CI: 1.03–1.48 for non-ambulatory patients), trauma (aOR: 1.35, 95% CI:1.09–1.66), hourly patient visits (aOR: 1.07, 95% CI: 1.05–1.10), concurrent intravenous fluid use (aOR:1.42, 95% CI:1.04–1.93), blood tests (aOR: 1.73, 95% CI: 1.30–2.30), radiography (aOR: 2.22, 95% CI: 1.87–2.64), and computed tomography (aOR: 1.57, 95% CI: 1.37–1.80). Reduced odds of delay were observed among patients with triage level 1 compared to level 3 (aOR 0.25, 95% CI:0.16–0.39), those arriving during night shifts compared to day shifts (aOR: 0.33, 95% CI: 0.18–0.63), and those receiving intramuscular medications compared to intravenous administration (aOR 0.71; 95% CI, 0.55–0.93).

Conclusions

Several patient, environmental, and diagnostic-related factors were associated with OTA delays in stat medication administration. Understanding these predictors may help inform strategies to optimize ED workflows. Further research is warranted to validate these findings in other ED settings.

Clinical trial number

Not applicable.

Background

Emergency department (ED) crowding is a persistent barrier to timely healthcare delivery, significantly impacting time-sensitive processes within emergency medicine. Numerous studies have explored the effects of crowding on medication administration times, consistently finding that increased ED congestion correlates with delays in delivering essential treatments, such as analgesics [1, 2] and antibiotics [3,4,5]. These delays have been shown to adversely affect patient outcomes, highlighting the urgent need for efficient operational processes in the ED [4, 6, 7].

The relationship between ED crowding and treatment delays is multifaceted. While research often highlights overcrowding as a cause of delays [7, 8], there is also the possibility that these delays contribute to crowding by extending patient stay and throughput times [9]. This bidirectional relationship underscores the importance of understanding specific factors that influence treatment delays, as optimizing these processes could potentially reduce patient throughput times and, consequently, alleviate some aspects of ED crowding.

In emergency medicine, the prompt delivery of care is paramount. The term “stat,” derived from the Latin “statim,” meaning immediately, underscores the urgency of prioritizing orders that require expedited attention. In practice, many institutions and clinical protocols consider a 30-minute window as the expected timeframe for administering stat medication orders [10,11,12]. This threshold is also supported by evidence from time-sensitive scenarios such as ST-elevation myocardial infarction, sepsis, and acute pain, where delays in administering treatments like dual antiplatelet agents, antibiotics, or analgesics have been associated with worse patient outcomes [11,12,13,14,15,16]. Therefore, a 30-minute cut-off may serve as a pragmatic and clinically relevant benchmark for defining timely medication administration in emergency settings.

Despite extensive research on the consequences of ED crowding, significant gaps remain in understanding the specific factors influencing medication order-to-administration (OTA) time, which can be considered a measurable index of treatment delays. A systematic review has emphasized the need to investigate these factors to inform policy-making and improve care efficiency [8]. However, studies examining OTA times in the ED remain scarce, highlighting the need for further research in this area. Ensuring timely medication administration is essential, as delays can impact patient outcomes and overall ED efficiency.

This study aims to identify predictors of OTA time delays exceeding 30 min for stat medications in the ED. By analyzing a range of measurable factors—including patient, triage, environmental, and prescription-related characteristics—we seek to identify the underlying contributors to prolonged OTA times. To our knowledge, this is the first study to address ED overcrowding and treatment delays by identifying predictors of OTA delays using quantifiable factors. These insights are expected to inform the development of strategies to optimize medication administration processes, potentially guiding interventions designed to enhance operational efficiency and improve patient outcomes in the ED.

Methods

Study design and setting

This retrospective study was conducted in the ED of Ditmanson Medical Foundation Chia-Yi Christian Hospital, a 1,000-bed private tertiary referral teaching hospital located in an urban area in Taiwan. The hospital receives over 70,000 patient visits annually. Data for this study were collected from June 1 to August 31, 2020, through the hospital’s Electronic Medical Record (EMR) and Nursing Information System (NIS).

Selection of participants

The study included all patients aged 20 years or older who received on-site treatment with stat medications in the ED. Exclusion criteria included individuals with incomplete data, duplicate entries, or those who did not require or receive stat medications. This included patients undergoing examinations without needing prescriptions, those prescribed take-home medications without stat medication use, and those on routine medication schedules only. Obstetric patients in imminent labor requiring urgent induction were excluded, as they were managed by specialists and bypassed the ED. In addition, patients triaged for specialist consultation in gynecology and otorhinolaryngology rather than direct ED physician management were excluded, as specialized examination rooms are located far from the ED, and their medication and examination processes differ from standard ED protocols in our institution.

Prescriptions with missed administration time were defined as orders that were placed but not administered due to reasons such as patient refusals, escapes, discharge against medical advice, or circumstances where medications were deemed unsuitable for administration, such as medications dropped on the ground or broken injectable vials. These cases were excluded since they lacked administration times and could not be analyzed for OTA time. Each patient visit was treated a unique unit of analysis. To maintain the independence of observations and avoid bias from repeated patient-level variables, only the first stat prescription order per visit was included. Patients with multiple ED visits during the study period were analyzed as separate encounters (Fig. 1).

Fig. 1

Study flowchart and outcome measurement. Flowchart illustrating the selection process of emergency department (ED) patient visits aged ≥ 20 years from June 1 to August 31, 2020. Of 14,877 visits, 3,448 were excluded due to no medication use, non-stat prescriptions, obstetric cases bypassing the ED, specialist consultations, or missed administration times. The final 11,429 visits were included for analysis. Patients were categorized based on order-to-administration (OTA) time, with 10,304 visits having OTA time ≤ 30 min and 1,125 visits experiencing OTA time > 30 min. The distribution of analgesic and antibiotic prescriptions within each group is shown. The study aimed to identify predictors associated with OTA time delays (> 30 min). ED, emergency department; ENT, otorhinolaryngology; GYN, Gynecology

Study setting and measurements

This study collected quantifiable data across four domains. Patient characteristics included age, gender, method of arrival, activity status, and referral status. Triage characteristics encompassed the type of illness and Emergency Severity Index triage level. Environmental characteristics covered factors such as ED shifts, weekend visits, number of nurses on duty, and hourly patient visit counts. Prescription characteristics included the route of medication administration, use of intravenous fluids, and any laboratory tests or imaging studies ordered concurrently with the stat medication.

OTA time is a critical outcome measure in this study, defined as the interval between the physician’s prescription order and the actual administration of medication. When an ED physician issues a stat medication prescription through the ED system, the order is recorded in the EMR, and the ED nurse is notified via a printout.

The process of medication retrieval and administration depends on the patient’s condition and triage level. For triage Level 1 patients managed in the resuscitation area, such as those with respiratory failure, shock, acute myocardial infarction, or major trauma, stat medications are administered in the resuscitation area. In these cases, ED staff retrieve medications directly from the ED pharmacy or medication dispensing machine, bypassing the patient and family to minimize delay. For patients with lower acuity (triage Level 2–5), there are currently no formalized triage protocols for stat medication administration. In these cases, prescriptions are typically conveyed to the ED pharmacy by family members, hospital couriers (for non-ambulatory patients), ED staff (for urgent prescriptions), or by ambulatory patients themselves. The ED is equipped with a medication dispensing machine that stores approximately 70 commonly used medications and is maintained by the ED pharmacy. However, retrieval from the machine requires an authorized order and must be carried out by ED staff. Once the medication is prepared, it is returned to the ED treatment rooms for administration by the nurse.

The institution’s protocol includes the “three checks” and the “five rights of medication use” to ensure accuracy and safety. The three checks involve confirming the medication upon order retrieval, verifying the drug during preparation and withdrawal, and conducting a final check when disposing of empty containers or bags. The five rights ensure verification of the right patient, drug, dose, route, and time [17, 18]. Together, these safeguards minimize medication errors, enhance patient safety, and ensure reliable OTA timing.

At the bedside, the medication is transported on a nursing cart equipped with the NIS. Immediately before administration, the nurse performs a barcode scan, which is recorded in the NIS to confirm the exact time of administration. This comprehensive approach not only ensures safety but also provides accurate and verifiable records, crucial for investigating OTA times.

Outcomes

The primary outcome of interest was identifying predictors of delays in OTA time, with a specific focus on instances where administration occurred more than 30 min after the prescription order. Secondary outcomes included delays in OTA time for the administration of analgesics and antibiotics.

Data analysis

All included patient visits were categorized into two groups based on OTA time: those with OTA times of ≤ 30 min and those with > 30 min, for comparison. Descriptive statistics were applied to characterize the study population. Categorical variables were reported as counts and percentages and analyzed using the Chi-square test. Continuous variables were presented as medians with interquartile ranges (IQR) and evaluated using the Mann-Whitney U test.

To identify predictors of delayed OTA time (> 30 min), multivariable logistic regression with backward selection was used. Variables with a p value < 0.05 from the univariable analysis were included in the model, estimating odds ratio (OR) with 95% confidence interval (CI). Subgroup analyses focused specifically on analgesics and antibiotics to assess the impact of predictors on these medications.

All statistical analyses were executed using JASP (Version 0.18.2). Statistical significance was set at p < 0.05. This study was approved by the Institutional Review Board of Ditmanson Medical Foundation Chia-Yi Christian Hospital (CYCH-IRB2023031).

Results

Enrollment

Data for this study were collected over a three-month period, from June 1, 2020, to August 31, 2020. Initially, 14,877 patient visits were identified as potential subjects. After excluding patients who did not receive medication in the ED (n = 411), prescriptions without a stat order (n = 2,715), obstetric patients in imminent labor requiring urgent induction and bypassing the ED (n = 40), patients triaged for gynecology and otorhinolaryngology specialist care rather than direct ED physician management (n = 204), and prescriptions with missed administration time (n = 78), a total of 11,429 patient visits were included in the final analysis (Fig. 1).

Main results

Of the included patient visits, 10,304 visits (90.1%) had an OTA time of 30 min or less, while 1,125 individuals (9.9%) experienced an OTA time exceeding 30 min. Significant differences in characteristics between those with and without delayed OTA time (> 30 min) were observed across patient, triage, environmental, and prescription-related factors (Table 1). Table 2 presents the results of univariable and multivariable logistic regression analyses.

Table 1 Baseline characteristics between emergency patient visits with and without delayed order-to-administration time (> 30 min)

Table 2 Predictors of delay in order-to-administration time (> 30 min) in emergency department patients

Patient characteristics

Within patient characteristics, age and sex were significant predictors of delays in OTA time (> 30 min). Each additional year of age slightly increased the odds of experiencing a delay (adjusted OR [aOR] 1.01; 95% CI, 1.00–1.01; p < 0.001). Female patients were more likely to experience delays compared to male patients (aOR 1.49; 95% CI, 1.31–1.69). Compared to fully ambulatory patients, those requiring assistance and non-ambulatory patients had higher odds of delay, with aORs of 1.38 (95% CI, 1.17–1.63) and 1.24 (95% CI, 1.03–1.48), respectively (Table 2).

Triage characteristics

Regarding triage characteristics, patients presenting with trauma had significantly higher odds of experiencing OTA delays compared to those with medical conditions (aOR 1.35; 95% CI, 1.09–1.66). Analysis by triage level showed that patients triaged at Level 1 were significantly less likely to experience delays than those at Level 3 (aOR 0.25; 95% CI, 0.16–0.39). However, delays for Level 2 patients were not statistically significant compared to Level 3 (aOR 0.97; 95% CI, 0.81–1.15).

Environmental characteristics

Environmental factors also influenced OTA times. Patient arrival time affects the odds of delays, with those presenting during night shifts having lower odds of delays compared to day shifts (aOR 0.33; 95% CI, 0.18–0.63). Additionally, the hourly patient visit rate was a significant factor; each additional patient visit per hour increased the odds of experiencing a delay (aOR 1.07; 95% CI, 1.05–1.10).

Prescription characteristics

Several prescription-related factors were associated with delayed OTA times. The route of administration had varying impacts. Intramuscular (IM) medications were associated with lower odds of delay compared to intravenous (IV) medications (aOR 0.71; 95% CI, 0.55–0.93), while topical administrations were linked to higher odds of delay (aOR 1.96; 95% CI, 1.47–2.62). Concurrent orders for imaging studies and diagnostic tests also influenced OTA delays. Radiography (aOR 2.22; 95% CI, 1.87–2.64), computed tomography (CT) scans (aOR 1.57; 95% CI, 1.37–1.80), intravenous fluid use (aOR 1.42; 95% CI:1.04–1.93), and blood test (aOR 1.73; 95% CI, 1.30–2.30) were associated with higher odds of delay. In contrast, electrocardiogram (ECG) exams were linked to lower odds of delay (aOR 0.78; 95% CI, 0.66–0.92).

Subgroup analyses

Subgroup analyses for analgesic and antibiotic prescriptions are presented in Tables 3 and 4, respectively. For analgesic prescriptions (n = 3,962), factors associated with significantly higher odds of delay included each additional year of age (aOR 1.01; 95% CI: 1.00–1.01), female sex (aOR 1.88; 95% CI: 1.51–2.33), and triage level 2 vs. level 3 (aOR 1.36; 95% CI: 1.04–1.79). Additional predictors included each additional patient visit per hour (aOR 1.06; 95% CI: 1.02–1.10), IV fluid use (aOR 2.29; 95% CI: 1.24–4.22), and concurrent orders for blood tests (aOR 2.15; 95% CI: 1.23–3.76), radiography (aOR 2.38; 95% CI: 1.75–3.25), and CT scans (aOR 1.35; 95% CI: 1.08–1.68). Conversely, patients triaged at level 1 (aOR 0.15; 95% CI: 0.05–0.47) and those presenting during night shifts (aOR 0.44; 95% CI: 0.30–0.65) had reduced odds of delay (Table 3).

Table 3 Predictors of delay in order-to-administration time (> 30 min) for prescription of analgesia (n = 3962) in emergency department patients

Table 4 Predictors of delay in order-to-administration time (> 30 min) for prescription of antibiotics (n = 1022) in emergency department patients

For antibiotic prescriptions (n = 1,022), factors associated with higher odds of delay included each additional patient visit per hour (aOR 1.16; 95% CI: 1.09–1.24), and concurrent orders for blood tests (aOR 3.03; 95% CI: 1.07–8.55) and CT scans (aOR 1.92; 95% CI: 1.29–2.85). Patient mobility status showed a trend toward affecting OTA delays but did not reach statistical significance.

Discussion

This study aimed to identify predictors of delays in OTA times exceeding 30 min for stat medications in a high-volume ED setting. Our findings indicate that a substantial proportion (9.9%) of patient visits experienced delays in medication administration, exceeding the 30-minute threshold. Significant predictors of delayed OTA times included patient, triage, environmental, and prescription-related factors.

Among patient characteristics, increased age, female sex, and reduced mobility were associated with higher odds of OTA delays. Older patients frequently experience longer ED wait times and extended lengths of stay, likely due to more complex care needs and multiple comorbidities [19,20,21,22]. This aligns with findings that age is a significant factor in ED dynamics, particularly among non-admitted patients [23] and in specific conditions like trauma [24]. Addressing the unique needs of older patients through targeted interventions may help improve timeliness in patient disposition.

Female patients also showed higher odds of OTA delays, consistent with some studies indicating longer throughput times for females [19, 22]. Several factors may contribute to this disparity. Physiological differences, such as a higher likelihood of difficult venous access– reported to be up to three times more common in women– may prolong IV-line placement and delay medication administration [25]. Furthermore, additional diagnostic requirements, such as pelvic exams for female patients with abdominal pain, may extend the time before medication administration. Staffing dynamics can also play a role, as female patients may request same-gender providers, leading to delays if female staff are unavailable. These factors highlight the multifaceted nature of OTA delays in female patients, warranting further research to quantify their impact and explore targeted interventions.

Regarding methods of arrival, patients transported by ambulance initially appeared more likely to experience OTA delays, as indicated by a crude OR of 1.95 (95% CI, 1.55–2.46) in univariable analysis. This finding aligns with studies on ED crowding that identify ambulance arrivals as contributing to treatment delays [26, 27]. However, after adjusting for confounding variables, the association with ambulance arrivals diminished. In contrast, patients with reduced mobility, especially those requiring assistance or who were non-ambulatory, consistently had higher odds of delay, suggesting that mobility status may play a more critical role than arrival mode in influencing OTA times. Therefore, current protocols, which utilize hospital couriers or ED staff to support medication retrieval, could be enhanced with additional resources or technology supports focused on assisting less mobile patients [28].

Triage characteristics, including illness severity and type, significantly influenced OTA times. Trauma patients had higher odds of delays (aOR 1.35; 95% CI, 1.09–1.66), likely due to the complexity and resource demands of trauma care, including non-ambulatory status, frequent imaging needs, and intensive resource allocation [29, 30]. This suggests that trauma patients may require additional process checks to ensure timely medication administration. Future research should explore strategies to reduce OTA times in this group.

Patients triaged at level 1 had significantly reduced odds of delay (aOR 0.25; 95% CI, 0.16–0.39), indicating effective prioritization for critical cases. However, level 2 patients showed no significant difference from level 3 in delay rates, suggesting potential inefficiencies in managing moderately severe cases. This highlights the need for process improvements to ensure timely care for these patients.

Environmental factors significantly influenced OTA times. Delays were less common during night shifts (00:00–07:59) compared to day shifts (08:00–15:59), likely due to lower patient volumes and less crowded conditions at night. Additionally, a higher nurse-to-patient ratio may have contributed to greater efficiency. As shown in Table 1, the total number of patients during night shifts is approximately half that of day or evening shifts. In our ED, the average nursing workforce consists of 10–11 nurses during night shifts, compared to 14–15 nurses during day shifts (Supplementary Table 1). This relatively higher nurse-to-patient ratio at night may allow for more efficient care and faster medication administration. Moreover, pharmacy wait times may be shorter during night shifts, as daytime pharmacy services are often shared with non-ED patients, potentially increasing workload and wait times during the day. Night shifts also typically involve fewer ancillary distractions, such as routine procedures and interdepartmental consultations, which are more common during the busier daytime hours.

Another intriguing factor is the “weekend effect,” which has been linked to increased hospital mortality [31]. This effect had an initial crude OR of 0.86 (95% CI, 0.75–0.99). However, this association was not significant after adjusting for other factors, such as hourly patient visits. We found that each additional patient per hour increased the odds of delay (aOR 1.07; 95% CI, 1.05–1.10), underscoring the impact of ED crowding on timely medication administration.

Prescription characteristics, particularly the route and type of administration, significantly influenced delays. Patients receiving IM medications had lower odds of delays compared to those receiving IV medications, likely due to simpler and quicker administration processes. In contrast, topical medications, often ordered stat for trauma patients for wound cleaning and dressing, are generally applied after initial evaluations. Therefore, delayed OTA times for topical medication may be reasonable, given their role in the treatment sequence.

Ancillary procedures, such as IV fluid administration, blood tests, radiography, and CT scans were significantly associated with increased odds of delayed medication administration. In contrast, ECG orders were associated with reduced delays. This may be attributed to the fact that, in our institution, ECGs are performed at triage for patients presenting with chest pain or suspected myocardial infarction and are immediately interpreted by emergency physicians. In confirmed cases of myocardial infarction, patients are rapidly transferred to the resuscitation area, where medications such as aspirin are administered without delay. Additionally, ECGs are typically performed within the ED by trained staff, eliminating the need for patient transport and facilitating a faster workflow. Conversely, medications administration may be postponed until after completing more complex procedures like imaging or blood tests. These findings underscore the need for streamlined diagnostic protocols, enhanced interdepartmental coordination, and adjusted medication administration protocols for patients undergoing ancillary procedures to minimize treatment delays.

Subgroup analyses of analgesics and antibiotics highlighted key factors influencing OTA times and potential strategies for reducing delays. These medications were prioritized due to their critical role in timely ED care.

For analgesics, timely pain management is essential for improving patient experience and potentially shortening ED lengths of stay [32, 33]. Factors associated with lower odds of delay included triage level 1 and night shifts. This suggests that the most critically ill patients and those seen during less crowded night shifts are more likely to receive analgesics promptly in our setting. In contrast, older age, female sex, triaged level 2 (compared to level 3), higher hourly patient volumes, concurrent IV fluid use, and concurrent blood tests, radiography, and CT scans were linked to increased delays (Table 3). Notably, in this subgroup analysis, female sex was associated with higher odds of delay compared to the main analysis, with an aOR of 1.88 vs. 1.49 (Tables 2 and 3). This finding underscores the need for heightened awareness in ensuring timely analgesic administration for female patients. Additionally, IV fluid use and concurrent diagnostic tests followed a similar trend (Tables 2 and 3).

Delays in analgesic administration can have significant clinical implications, exacerbating patient suffering and negatively impacting the overall ED experience. Prolonged pain may lead to increased stress, anxiety, and other adverse physiological effects [34], which can prolong recovery and delay discharge. These findings suggest that prioritizing pain management alongside or before adjunct tests may help mitigate delays. When faced with high patient volumes, ED staff may need to carefully balance the timing of analgesic administration and diagnostic tests to ensure timely pain relief. Future research should also explore specific causes of delays, such as patient-specific issues (e.g., waiting for renal function) and ED workflow challenges, to further refine strategies for improving pain management timeliness in the ED.

Similarly, for antibiotics, numerous studies have confirmed the importance of early administration for sepsis patients, with delays linked to poorer outcomes when 3-hour or 1-hour bundle targets are missed [13, 35,36,37]. In our study, higher hourly patient volume and concurrent diagnostic orders, such as blood tests and CT scans, were identified as key predictors of delayed antibiotics administration. Limited patient mobility also showed a trend toward contributing to delays. These findings highlight the need for streamlined diagnostic workflows and enhanced mobility support to ensure timely antibiotics delivery. It is important to note, however, that the clinical decision to initiate antibiotic therapy in sepsis is often based on clinical suspicion, requiring prompt recognition and judgment by the treating physician. This element of clinical acumen is difficult to quantify and was not directly captured in our dataset. Future research should consider approaches that integrate both clinical decision-making and system-level factors to better understand and reduce delays in antibiotic administration. Prompt antibiotic therapy remains essential to mitigating risks of clinical deterioration, organ dysfunction, and mortality in patients with sepsis or other serious infections [13, 37].

Limitations

This study has several limitations. First, its retrospective design, single-site setting and use of data collected approximately four years ago may limit generalizability and relevance to current practice. Changes in ED workflows, protocols, or staffing over time may have introduced systematic bias. For example, the proportion of OTA time ≤ 30 min in this study was approximately 90%, higher than that reported in a previous study from another country [11]. Given the limited literature on OTA time, multi-site, prospective studies using more recent data are needed to validate these findings. Second, certain unmeasured factors that could influence OTA times were not included in this analysis. For instance, nurse workload, staff experience levels, and familiarity with ED protocols may impact medication delivery. Additionally, information regarding the individuals responsible for delivering prescriptions to the ED pharmacy (e.g., family members, staff, or patients themselves), as well as data on ED bed occupancy rate, were not available in the dataset, limiting our ability to assess their potential influence on medication delays. Third, the study collected data over a three-month period, which may not account for seasonal variations in ED activity, such as increased patient volumes during the flu season. Fourth, external factors such as pharmacy staffing and medication availability were not considered but may also impact delays. Fifth, this study did not account for variations in IV medication preparation. Some medications are pre-formulated, while others require admixture, which can vary in complexity and preparation time. These differences may have contributed to variability in OTA times within the IV medication group. Sixth, subgroup analyses were limited. While we examined analgesics and antibiotics due to their clinical relevance and adequate sample sizes, other time-sensitive medication groups (e.g., antiepileptics, thrombolytics, sedation, anaphylaxis treatments) could not be analyzed due to insufficient data. Similarly, although timely antibiotic administration in sepsis is critical, we were unable to reliably identify sepsis cases in our dataset. As a result, antibiotic use was used as a proxy for suspected infection. Future studies with larger sample sizes and more detailed clinical data are needed to explore these important subgroups. Finally, the lack of data on the physiological status of patients is another limitation. This information could provide critical insights into whether OTA time is associated with patient outcomes. Future research should explore how OTA time influences clinical outcomes and patient safety, rather than focusing solely on system-level efficiency. Expanding future studies to include clinical indicators such as vital signs, disease severity, and treatment responses would enhance our understanding of the true impact of OTA time on patient care. Future studies should examine these elements to provide a more comprehensive view of factors affecting OTA times in the ED.

Conclusions

ED crowding contributes to treatment delays, further worsening congestion and negatively impacting patient care. Identifying predictors of OTA delays is essential for developing strategies to optimize medication administration efficiency. Through the analysis of 11,429 ED patients, this study identified patient characteristics, triage processes, environmental conditions, and prescription details as key factors influencing medication administration times. To address these delays, practical interventions should focus on improving care for high-risk groups, including older adults, female patients, individuals with limited mobility, and trauma patients. Optimizing medication protocols for patients undergoing ancillary procedures, such as imaging or blood tests, may help streamline workflows and reduce unnecessary waiting times. Mobility assistance programs could further support timely medication retrieval and administration for patients with physical limitations. Additionally, enhancing staff training to improve coordination between medication administration and diagnostic procedures may help ensure that critical treatments are not delayed. Adjustments in pharmacy operations, particularly during peak hours, could also contribute to more efficient medication turnaround times. Future research should focus on implementing these interventions across diverse clinical settings to validate their effectiveness and explore innovative approaches for improving the timeliness of emergency care.