AUTOMATED MEDICATION ORDERING USING MEDICINES DISPENSING DATA AND A SOFTWARE ROBOT
European Statement
Selection, Procurement and Distribution
Author(s)
Linda Jeffery
Hospital Pharmacy Central Denmark Region
linjef@rm.dk
Why was it done?
Ordering medications manually takes time and is prone to human error. Since the electronic patient journal, MidtEPJ, holds detailed records of patients’ medication administration, the idea was to use that data to automate the ordering process. The vision was a system where medication use would automatically trigger a restocking order. As there is no direct interface between MidtEPJ and the pharmacy’s ordering system, Apovision, the project aimed to see if it was possible to transfer data between the two systems. As three (of the five) regions in Denmark use the same EPJ system, and all rely on Apovision, a successful pilot in Central Denmark Region could potentially be scaled nationwide.
What was done?
This project investigated whether it would be possible to automate medication ordering for a hospital ward’s standard stock by using dispensing data from MidtEPJ. A software robot (RPA) was developed to pull data from MidtEPJ and create a draft requisition in Apovision. The goal was to simulate an automated process that could ease manual workload, improve accuracy, and support better stock management.
How was it done?
The regional IT team worked closely with the pharmacy to design a workaround. Dispensing data were extracted from MidtEPJ, processed by the RPA, and used to generate a draft order in Apovision. A neurological ward was chosen for testing due to its single medication room and relatively consistent data. Fifteen medications were selected based on their high flow, dosage complexity, and formulation. The system triggered a draft order once a set usage threshold was reached. The process remained semi-automated to meet GDP standards and allow pharmacy technician oversight.
What has been achieved?
The robot successfully generated daily reports and draft orders based on documented usage. However, some discrepancies were found due to documentation habits, timing of data extraction, and product variations. The project showed, for the first time, that automated ordering is technically possible and that a link between MidtEPJ and Apovision can be created.
What next?
The concept is scalable, but further work is needed to improve data accuracy and system integration. With the right technical support, the model could be expanded to cover full inventories and be rolled out across other regions.
THE CLINICAL PHARMACEUTICAL SERVICE IT TEAM: ENHANCING MEDICATION WORKFLOWS AND PATIENT SAFETY IN EPIC
European Statement
Patient Safety and Quality Assurance
Author(s)
Christina Theil Schnor and Saranya Loganathan.
Why was it done?
In 2018, hospitals in Region Zealand (RZ), Denmark, transitioned to the electronic health record (EHR) system, EPIC. Following this, hospital pharmacists faced repeated medication order challenges causing adverse events such as inappropriate medication orders, dispensing and administration errors, and insufficient workflow coordination. These issues resulted in complex, time-consuming workflows impacting quality and patient safety. Additionally, collaboration between corporate IT and clinical staff was challenged by a lack of understanding of practical issues. To address this, pharmacists of RZ established the Clinical Pharmaceutical Service IT Team (CPS IT Team) to build specialized knowledge of the EHR medication module, aiming to assure quality, optimize workflows, strengthen interdisciplinary coordination, and support safer and more efficient clinical use.
What was done?
CPS IT Team standardized workflows, enhanced coordination of medication order tasks, and created a forum to effectively utilize professional knowledge and networks across areas.
How was it done?
To address diverse Clinical Pharmacy challenges, CPS IT Team became the bridge between internal organization (RZ Hospital Pharmacy and corporate IT) and external partners (EPIC and The Capital Region of Denmark (CRD)). For this reason, CPS IT Team was established with one team manager and two units: Internal and External unit. CPS IT Team continuously adapts to evolving Clinical Pharmacy needs.
What has been achieved?
The establishment of CPS IT Team has driven significant internal optimization and standardized workflows. Acting as a coordinating unit, it optimizes medication processes from ordering to dispensing and administration. Dialogue with IT has been strengthened, enabling more efficient, targeted communication across professional groups.
Collaboration with EPIC and CRD has enhanced quality assurance and optimized workflows. CPS IT Team efforts have helped prevent medication-related adverse events, improve workflows, and optimize medication processes. Interdisciplinary collaboration and professional consultation networks between regional clinics, hospital pharmacies, IT, and EPIC have been notably strengthened. These efforts have increased patient safety and fostered a safer, more coherent workflow in EPIC.
What next?
Fusion of RZ and CRD into Region Eastern Denmark will change CPS IT Team’s working conditions, opening new opportunities such as an expanded collegial network and broader range of tasks and needs. Systematic data use will support Hospital Pharmacy’s work, improving efficiency and quality in daily operations.
FROM PAPER TO PLATFORM: STRENGTHENING ADVERSE DRUG REACTION REPORTING IN TUBERCULOSIS CARE VIA A PHARMACIST-LED DIGITAL SYSTEM IN AN OVERCROWDED HOSPITAL SETTING
European Statement
Clinical Pharmacy Services
Author(s)
Netchanok Kanjana, Ratnaton Khangkhasuwan, Thumwadee Thongkamchum, Pitchaporn Tepsuone, Nawiga Plong-on, Siriwan Wongvarodom, Rungnapa Songsiriphan
Why was it done?
Assessment of adverse drug reactions (ADRs) in tuberculosis (TB) patients is complex due to the concurrent administration of multiple anti-TB agents and the 9–12 day process often required for rechallenge. At our tertiary referral center, frequent transitions of TB patients between inpatient wards and the outpatient clinic, exacerbated by persistent overcrowding and a bed occupancy rate of 138%, resulted in paper-based ADR documentation being vulnerable to loss or fragmentation. This compromised patient safety and increased the risk of repeated hypersensitivity reactions.
What was done?
A digital platform was developed and implemented to systematically document and monitor ADRs in TB patients, aiming to enhance patient safety, prevent recurrent hypersensitivity events, and significantly improve the continuity, completeness, and quality of ADR reporting across all care transitions.
How was it done?
Key data elements were identified through structured pharmacist interviews and literature review. An AppSheet-based application was designed to enable real-time documentation and centralized monitoring of ADR data. The system was deployed across relevant inpatient wards and the outpatient TB clinic during the 3-month pilot period (March 1 to May 31, 2025). Pharmacists were trained to record ADR reports directly into the application, ensuring seamless information access.
What has been achieved?
Complete ADR reporting increased substantially: 56 ADR entries for 21 TB patients were documented during the pilot. This includes 8 complete ADR assessments (e.g., 3 Augmented, 5 Bizarre), compared to only 3 and 4 complete reports recorded on paper in 2023 and 2024, respectively. Crucially, no recurrent hypersensitivity reactions were observed during the intervention period. The application significantly improved continuity of care and facilitated timely, comprehensive ADR reporting.
What next?
Future plans focus on strengthening data security and system stability by migrating the application to the hospital’s internal server and integrating login with the national health provider authentication system. Expansion will involve scaling the system to include ADR monitoring across network hospitals, ensuring complete information transfer when patients are referred back to their primary facilities.
DESIGN AND IMPLEMENTATION OF AN INTEGRATED PHARMACEUTICAL CARE MODEL IN PATIENTS UNDERGOING ASSISTED REPRODUCTIVE TREATMENTS
European Statement
Clinical Pharmacy Services
Author(s)
A.M. AGUI CALLEJAS1, C. REDONDO GALÁN1, S. MANRIQUE RODRIGUEZ1, C. MARTINEZ FERNANDEZ-LLAMAZARES1, Y. RIOJA DIEZ1, L. MORENO OCHOA2, F. PEREZ MILAN, A. HERRANZ ALONSO1, M. SANJURJO SAEZ1.
1 GREGORIO MARAÑON UNIVERSITY GENERAL HOSPITAL, PHARMACY, MADRID, SPAIN.
2 HOSPITAL GREGORIO MARAÑON, OBSTETRICS AND GYNAECOLOGY, MADRID, SPAIN.
Why was it done?
Patients undergoing AR treatments face a substantial information burden and complex drug regimens, including injectable self-administration, which complicate understanding and adherence while increasing the risk of errors. A single-visit care programme was developed, integrating medical consultation, nursing-led administration training, pharmaceutical care, and treatment dispensing. This coordinated model aims to enhance follow-up, reduce patient burden, and improve healthcare quality, resulting in safer, more effective, and efficient outcomes.
What was done?
A pharmaceutical care programme was developed and implemented to monitor treatment and dispense medication to patients undergoing assisted reproduction (AR) procedures.
How was it done?
A multidisciplinary team was established, including gynaecologists, clinical pharmacists, and advanced practice nurses. Patients were selected according to local healthcare criteria. The programme addressed logistical coordination, pharmacotherapeutic monitoring, and patient support. A mobile application (including medication management, adverse events and bidirectional messaging) was developed from March to August 2025 and launched in the final month. Medication was dispensed in exact patient-specific amounts, following quality and traceability protocols, to reduce costs and minimise home waste. Main limitations were the short implementation period and small sample size, related to the app’s recent launch.
What has been achieved?
93 patients were included (mean age: 40 years, SD=3.9). 102 treatment initiation consultations and 194 follow-up visits were recorded (7 patients with > 1 cycle). Medication dispensing was based on Madrid Health Service criteria: In Vitro Fertilisation (IVF) in women over 40 years (45%) or with previous children (30%), fourth IVF cycle (7%), artificial insemination (AI) in patients with previous children (13%), and oocyte preservation (OP) in patients with previous offspring (5%). Eight patients were enrolled in the app: 12.5% sought supplement compatibility advice, 37.5% reported adverse effects, and 50% recorded medication intake. Median treatment duration was 8 days [interquartile ranges: 4–10 (IVF and AI); 8-10 (OP)]. The estimated savings, derived from the difference between the units supplied in full medication packs and those actually consumed by patients, amounted to €15,441.
What next?
This initiative exemplifies good practice by integrating medical consultation, nursing-led training, pharmaceutical care, and dispensing in one visit, reducing burden while improving safety and efficiency. A digital tool enhanced monitoring and communication, making the model transferable to other outpatient settings.
WHEN CRISIS BECOMES COLLABORATION: A NATIONAL RESPONSE TO COMPOUNDED MEDICINES SHORTAGES
European Statement
Introductory Statements and Governance
Author(s)
F.H. Nielsen
A.G Pedersen
L. Jensen
M. Kristoffersen
P. Stoffersen
T. P Dahl
Why was it done?
The shutdown significantly increased the risk of shortages for 271 compounded medicines, many vital for specialised treatments. To secure patient safety and equal access, a coordinated national approach was required to mobilise production capacity and set priorities. Due to the short shelf life of compounded medicines, it was crucial to establish a rapid national response to prevent critical shortages.
What was done?
Following the sudden shutdown of a compounding pharmacy, a national response was initiated. A joint online platform was established between the National Group for Compounded Medicines and the National Task Force for Medicine Shortages, both composed of representatives from hospital pharmacies. This platform consolidated data and decisions, ensuring planning through a national perspective. Based on the merged data, production was coordinated between remaining compounding pharmacies, both public and private, to ensure supply.
How was it done?
An online platform was established to track stock levels across hospital pharmacies, and clinical criticality was assessed on a 1–3 scale visualised with a colour code showing national coverage in days or weeks. Oral solutions with short shelf life were identified as top priority due to imminent stock depletion. Each product was reviewed for possible substitution, therapeutic alternatives, or justification for compounding. Short-term measures included extemporaneous preparation, while long-term strategies involved outsourcing, substitution, and redistribution of stock. Regular national meetings ensured the remaining two compounding pharmacies developed joint production plans, distributing workload and adjusting capacity.
What has been achieved?
This initiative demonstrates how hospital pharmacies, through national collaboration, can ensure resilience in crises. Within two months, nearly all medicines were reintroduced, substituted, or outsourced, and supply maintained without major safety incidents. The national approach included both public and private pharmacies, and their collaboration was strengthened.
What next?
The model provides a transferable framework for future shortages, proving that collaboration, shared data, and prioritisation tools can ensure patient safety and equity of access. The same model has since been applied to other critical shortages, confirming its broader value.
CYBER RISK ANTICIPATION: HOW TO GET YOUR HOSPITAL PHARMACY PREPARED IN (ALMOST) 2 HOURS?
European Statement
Introductory Statements and Governance
Author(s)
C. Delage1, P. Troude2, U. Gouot3, V. Bloch1, B. Isabey4, A. Desmons5.
1 Pharmacy Department, Lariboisière-Fernand Widal Hospital, GHU APHP.Nord, Assistance Publique – Hôpitaux de Paris, 2 rue Ambroise Paré, 75010 PARIS
2 Public Health Department, Lariboisière-Fernand Widal Hospital, GHU APHP.Nord, Assistance Publique – Hôpitaux de Paris, 200 rue du faubourg Saint-Denis, 75010 PARIS
3 Information Systems Department, Lariboisière-Fernand Widal Hospital, GHU APHP.Nord, Assistance Publique – Hôpitaux de Paris, 2 rue Ambroise Paré, 75010 PARIS
4 Hospital Executive Management, Lariboisière-Fernand Widal Hospital, GHU APHP.Nord, Assistance Publique – Hôpitaux de Paris, 2 rue Ambroise Paré, 75010 PARIS
5 General Affairs Department, Lariboisière-Fernand Widal Hospital, GHU APHP.Nord, Assistance Publique – Hôpitaux de Paris, 2 rue Ambroise Paré, 75010 PARIS
Why was it done?
With the 2024 Olympic Games approaching, French healthcare institutions faced an elevated cyberattack risk. Preparing healthcare services for such events is essential but often time-consuming, leading sometime to postpone or abandon this work. A rapid, pragmatic methodology was therefore needed to efficiently assess vulnerabilities and define concrete preparedness measures without overburdening teams.
What was done?
A fast-track business continuity plan (BCP) approach was developed by the management department of our university hospital and implemented in the pharmacy department to rapidly assess preparedness for cyber risks and IT disruptions. The structured process mapping allowed each sector to produce an operational continuity plan in only a few hours, evaluating process vulnerability, defining measures to maintain operations during a cyberattack, and identifying needs (new IT equipment, human resources, backup materials).
How was it done?
Dedicated meeting (1-4 hours) were held for each pharmacy sector (medicines, medical devices, sterilisation, radiopharmacy), involving the cyber risk pharmacist referent and sector head. The plan took the form of a table describing all sector processes (eg., procurement, storage, dispensing), their normal functioning and IT requirements (applications, devices, networked medical equipment…). Subsequent columns described degraded functioning and required resources (staff, equipment, premises) at three time horizons: 3 hours, 3 days, and 3 weeks after the start of a cyberattack.
What has been achieved?
Nine BCPs identified 64 processes. In just a few hours, the method provided a clear picture of which sectors/processes were resilient and which were unprepared. It revealed vulnerabilities such as reliance on IT systems and automation, lack of printed procedures, and absence of backup equipment. Simple measures were identified to improve preparedness: printing key documents (eg. hospital formulary), identifying critical data for regular backup, training staff, etc. This rapid diagnostic approach raised awareness among hospital management of resources needed to sustain pharmacy operations during cyber disruption.
What next?
Based on their BCP, each sector took measures to get prepared to IT shutdown. Using professionals’ deep process knowledge to design practical solution to ensure continuity of clinical activity makes preparedness for IT disruption more accessible. Given its simplicity, the methodology was generalised by hospital management to all departments.
IMPLEMENTATION OF AMS STANDARDS IN THE ELECTRONIC PRESCRIBING SYSTEM/HOSPITAL INFORMATION SYSTEM (HIS) OF THE UNIVERSITY HOSPITAL COLOGNE GERMANY
European Statement
Patient Safety and Quality Assurance
Author(s)
Dr. Tobias Leinweber1, Dr. Lukas Tometten2, Tobias Wingen1, Dr. Andrea Liekweg1, Prof. Dr. Norma Jung2
1 Hospital Pharmacy, University Hospital Cologne, Germany
2 Department I of Internal Medicine, Division of Infectious Diseases, University Hospital Cologne, Germany
Why was it done?
Standardized dosing tables for anti-infective agents, specifically vancomycin and piperacillin/tazobactam, were developed and integrated into the electronic prescribing system (hospital information system – HIS) of the University Hospital Cologne. The tables provide evidence-based, renal function–adjusted dosing recommendations within the clinical workflow, supporting clinicians in accurate and safe prescribing.
What was done?
Existing treatment standards for infectious diseases were often underutilized in daily practice due to limited accessibility and lack of integration into the electronic prescribing system/HIS. This led to dosing errors—particularly with vancomycin, where underdosing may cause therapeutic failure and overdosing toxicity. Additionally, EUCAST updates to piperacillin/tazobactam dosing required hospital-wide adaptation of practices. The initiative aimed to improve dosing accuracy, enhance antimicrobial therapy safety, and standardize prescribing practices through direct system integration.
How was it done?
The project was developed by an interdisciplinary team consisting of the Antimicrobial Stewardship (AMS) team, the Department of Infectious Diseases, and the hospital pharmacy. To ensure effective adoption and continuous improvement, a stepwise implementation approach was chosen, enabling feedback collection and iterative refinement. The rollout was supported by ward pharmacists who provided on-site guidance and assistance during initial implementation. Targeted training sessions and regular email communications informed and engaged prescribers. All relevant information was integrated into the hospital’s antibiotic guideline to ensure easy access and long-term consistency in clinical practice. Challenges such as differing user familiarity and workflow adjustments were addressed through ongoing training and direct support.
What has been achieved?
The implementation of the vancomycin dosing standard led to more consistent therapeutic drug monitoring (TDM), faster achievement of therapeutic levels, lower rates of toxicity, and reduced linezolid use, indicating improved prescribing behavior. The piperacillin/tazobactam dosing table was widely adopted, though further training remains necessary for full-scale use. Overall, the integration demonstrated improved medication safety, greater standardization, and enhanced clinical acceptance of the HIS-based prescribing system.
What next?
Training sessions, interdisciplinary experience exchange and interviews with clinicians are planned to ensure ongoing optimization.
This initiative illustrates how interprofessionally developed standards can be effectively embedded into clinical workflows. The approach can be easily transferred to other hospitals using similar prescribing software, offering a scalable model to strengthen antimicrobial stewardship, improve prescribing competence, and enhance patient safety.
CHATGPT-5 AS A POTENTIAL ALLY IN IDENTIFYING DRUG–DRUG INTERACTIONS?
European Statement
Patient Safety and Quality Assurance
Author(s)
Presenting author : H Decouvelaere
Co-author : C Lambert de Cursay
Why was it done?
Drug–drug interactions (DDIs) represent a major issue in clinical pharmacology, as they can lead to serious, sometimes fatal, adverse effects. The emergence of artificial intelligence models such as ChatGPT raises questions about their reliability in identifying DDIs. The literature reports that ChatGPT may generate nonexistent information (“hallucinations”) or provide inaccurate or incomplete data. However, evidence regarding its use in detecting DDIs remains limited.
What was done?
To evaluate the reliability of ChatGPT in detecting DDIs, particularly for recently marketed drugs or those under compassionate use authorization (CUA), for which conventional databases are sometimes incomplete.
How was it done?
Thirteen older drugs (marketed before 2010) and seven drugs marketed since June 2025 or under CUA were identified. All pairwise drug combinations were tested. A standardized script was used to query ChatGPT consistently, minimizing bias related to question phrasing. Results were checked using reliable sources (product characteristics summaries, scientific literature, DDI-Predictor, etc.). Searches were conducted between July and September 2025 using ChatGPT-5.
What has been achieved?
A total of 210 drug pairs were analyzed. ChatGPT’s responses were consistent with the literature for 72% of pairs (n=152). For 9% (n=18), the information was incomplete. Partial discrepancies were observed for 1% (n=2) and total discrepancies for 18% (n=38). Among these, 68% (n=26) corresponded to ChatGPT hallucinations and 32% (n=12) to undetected DDIs. Agreement with the literature was 65% (n=59) for older drug pairs, 95% (n=20) for pairs of two recent or CUA drugs, and 74% (n=73) for mixed pairs (old and recent drugs).
What next?
ChatGPT-5 can serve as a helpful tool for identifying DDIs, providing correct analysis in nearly 75% of cases. However, its performance remains limited due to the significant risk of hallucination or omission. ChatGPT’s responses were less reliable for older drugs, likely because of the vast and sometimes outdated documentation available. Conversely, newer or CUA drugs—although less documented—benefited from more recent and homogeneous sources, improving response quality. Therefore, ChatGPT-5 cannot replace human expertise or official databases. It should always be used as a complementary tool, with its outputs verified against trusted sources.
ARTIFICIAL INTELLIGENCE AND AUTOMATION: TRANSFORMING HOW WE MANAGE DRUG RECALLS AND MEDICINE SUPPLY NOTIFICATIONS
European Statement
Patient Safety and Quality Assurance
Author(s)
Anna Lydon & Jonathan Day
Why was it done?
National drug recalls and Government issued Medicines Supply Notifications (MSNs) must be responded to promptly to minimise risk to patients and ensure stock safety. Within our Trust, comprising four hospital sites at different locations, an incident occurred where a recall email received over a bank holiday weekend which went unnoticed. The existing system relied solely on staff checking their emails, which posed a risk of delayed action—particularly during weekends, leave periods, and across multiple sites. This highlighted the need for a more robust and transparent process to ensure that all recalls and MSNs are received, actioned, and tracked in real time.
What was done?
A digital process was developed using Microsoft Power Automate and Artificial Intelligence (AI) to automate the handling of drug recalls and MSN emails. The flow triggers when a drug recall or MSN email is received. It extracts key information using AI, and automatically distributes the information across the relevant pharmacy and clinical teams across all Trust sites.
How was it done?
When a drug recall or MSN email is received, the attached PDF is analysed with an AI model trained with specific prompts to extract key fields including the drug name, MSN number, date, impact level and required actions. The extracted data automatically populates the MSN or drug recall Excel log – replacing what was a manual data entry process. Power Automate then initiates an approval process and posts a summarised Teams notification into a Teams channel for all relevant members. Each member receives the alert and one person from each site must acknowledge receipt. Following acknowledgement from a member of each site, Power Automate posts a confirmation in the Teams channel, enhancing transparency and providing assurance that the recall has been actioned. AI determines the appropriate clinical speciality for the drug and automatically directs a summary email to the corresponding pharmacists and clinicians working in that area.
What has been achieved?
The process ensures consistent and timely handling of recalls and MSNs, reducing reliance on individual inbox monitoring. It has improved visibility across all sites, eliminated missed notifications, and significantly reduced manual data entry time. Staff feedback has been positive, with greater confidence that all recalls and MSNs are captured and actioned promptly.
What next?
Future plans include integrating automatic escalation plans for unacknowledged alerts. The same model could also be expanded to other time-critical communications, such as National Patient Safety Alerts to further strengthen medicines governance across the organisation.
ARTIFICIAL INTELLIGENCE POWERED DOCUMENT MANAGEMENT FOR HOMECARE PRESCRIPTIONS
European Statement
Patient Safety and Quality Assurance
Author(s)
Anna Lydon & Jonathan Day
Why was it done?
Homecare prescriptions are physically sent to external homecare companies for dispensing, so the hospital must retain a copy for governance, audit and continuity of care. Previously, prescriptions were scanned in and manually moved to local folders with variable filenames, introducing risk of error, no audit trail and duplicated effort (pharmacy and clinical teams both scanning). This was a slow, manual process, with a typical delay of around 2-3 weeks before prescriptions were uploaded due to the high volume. We therefore needed a safer, faster and auditable process to retain copies of homecare prescriptions in the official patient record.
What was done?
We developed a Robotic Process Automation (RPA) which involved ustilising an Artificial Intelligence (AI) enabled workflow to capture homecare prescriptions, extract key fields, automatically file using standardised filenames, validate patient identifiers, and automatically upload documents into the patient record for all healthcare professionals (HCP) to view in real time.
How was it done?
We used Microsoft Power Automate and Azure AI to build an AI-driven RPA process to read scanned homecare prescriptions, extract key fields, standardise filenames, validate patient identifiers, and automatically upload documents into the official patient record. Within the automatic process, there are built-in validation checks to verify AI-extracted fields. If the AI confidence score is low or a check fails, the workflow prompts for human confirmation of the patient’s hospital number and then resumes processing.
What has been achieved?
To date, the solution has processed over 5,000 homecare prescriptions with 98% field-extraction accuracy. Average handling time has reduced from 3 minutes per prescription to 10 seconds per 50 prescriptions, equating to around 5 hours saved per 100 prescriptions. This novel process has released 7.5 hours of pharmacy staff time per week. Prescriptions are now available in the patient record in real time, improving information availability at the point of care and enabling staff to focus on higher value tasks. This has strengthened data quality and governance, and provides an audit trail whilst reducing duplication of work between pharmacy and multiple clinical teams.
What next?
We plan to extend the workflow so that all AI-extracted fields are written back to the Homecare Patient SQL database, creating a single, queryable source of truth and enabling automated checks, dashboards and reporting. We also plan to roll the solution out for other prescription types (outpatient and discharge), replacing off-site paper storage with searchable patient records, reducing storage costs, improving retrieval times, and strengthening governance.