Clinical decision support tools in pharmacy practice

Clinical decision support (CDS) tools are resources designed to support clinical decision-making by bringing together patient-specific information, clinical knowledge and evidence at the point of care^​1​. These tools are increasingly embedded within digital health systems across the NHS, supporting both clinicians and patients^​2​. NHS England highlights CDS tools as an important component of safer, more consistent care, with potential benefits for quality, safety and efficiency when implemented well^​2​. Alongside clinician-facing systems, these tools enable shared decision-making, helping clinicians and patients to explore treatment options together via structured, transparent information on benefits and harms^​3​.

As medicines regimens become more complex and pharmacy professionals take on expanded clinical and prescribing roles, the need for effective decision support has increased. National and international patient-safety initiatives continue to emphasise the role of digital systems in reducing preventable harm^​2,4​. This article explores the current use of CDS tools in pharmacy practice, considers its benefits and limitations, and discusses emerging opportunities for future development.

CDS tools as a way to improve safety

Medication errors are a common and significant cause of preventable harm across the healthcare system^​5​. In England, it is estimated that approximately 237 million medication errors occur each year, with around 66 million considered clinically significant and associated with avoidable patient harm^​5​. National regulatory reviews have consistently highlighted medicines safety as an area which requires sustained improvement, with errors that occur across prescribing, dispensing, administration and monitoring^​6–8​. Evidence from both adult and paediatric settings demonstrates that medication-related harm is rarely attributable to a single failure but instead reflects system-level vulnerabilities across the medicines pathway^​9–12​.

Alongside this, the roles of pharmacists and pharmacy technicians have continued to evolve. Both groups increasingly work in patient-facing clinical roles and contribute to medicines optimisation, with pharmacists also undertaking independent or supplementary prescribing in many settings^​13,14​. These expanded responsibilities increase opportunities to improve safety and quality but also emphasise the need for effective support tools to manage complexity consistently and safely^​1​.

There has also been a clear shift away from paper-based resources towards digital and integrated sources of clinical information. While formularies and guidelines remain essential, they are now commonly accessed through electronic systems or embedded within clinical workflows^​1,14​. Integrated CDS has the potential to provide guidance at the point of care, but it has challenges related to usability, over-reliance and implementation^​15​.

Current CDS tools

CDS tools can be broadly categorised into three types: 

• CDS systems; 
• Reference-based tools;
• Patient-facing tools. 

All three types of tools aim to guide clinical decisions and improve patient care by adhering to the ‘5 rights’ of CDS design^​16​: to provide the right information, to the right person, in the right format, through the right channel and at the right time.

CDS systems

CDS systems are integrated into digital health software, such as electronic prescribing and medicines administration (ePMA) systems, pharmacy dispensing systems and electronic patient records. They also offer a range of functionalities at the point of care, driven by clinical information in the patient’s chart: dosing support, interaction checking, guiding treatment recommendations and adherence to evidence-based guidelines^​1​. 

Table 1: Examples of integrated clinical decision support tools

Reference-based tools

Reference-based tools provide healthcare professionals with regularly updated, evidence-based information and guidelines to support informed clinical decision-making^​17,18​. The shift of these tools from printed text to digital platforms allows quick information retrieval and integration as reference links into ePMA systems and electronic patient records, such as the British National Formulary (BNF), British National Formulary for Children (BNFc), Medusa, the National Institute for Health and Care Excellence (NICE) and national/local guidelines. 

Reference tools such as the BNF provide general guidance on drug usage and their considerations but also provide additional CDS tools such as an interaction checker and links to clinical calculators^​19​. Clinical calculators such as CHA_₂DS_₂-VASc support personalised decision-making and reduce manual calculation errors^​2​. Comprehensive tools, such as BMJ Best Practice and UpToDate, provide pharmacists with access to in depth treatment algorithms with medicines management options and numerous calculators for risk assessment, drug dosing and co-morbidities management^​20,21​. Health Education England provides access to BMJ Best Practice to all NHS England staff, while some NHS organisations may also provide access to UpToDate (See Table 2).

Table 2: Examples of reference-based tools

Patient-facing tools

Personalised care means patients are actively involved in decisions about their treatment and receive information to empower them to manage their health^​22​. The NHS App and other third-party adherence apps and patient engagement platforms help patients manage their medications and stay on track with their medication routines^​23​. Patient decision aids provide evidence-based information about associated benefits and harms to support shared decision-making between people and their clinician^​3​. 

Special considerations in high-risk groups

CDS tools require careful application in patient groups where standardised recommendations may not reflect individual needs. In older adults, multimorbidity and polypharmacy increase the risk of adverse drug reactions and treatment burden^​24,25​. While CDS can identify interactions, contraindications and high-risk medicines, it may not fully account for frailty, limited life expectancy or cumulative harm. In these situations, guideline-driven prompts may be inappropriate and clinical judgement remains essential.

Similarly, in paediatric patients, reliance on CDS does not eliminate medication error, and the consequences of error may be more significant. CDS tools developed using adult data and prescribing models may not perform well when applied to children, reinforcing the need for paediatric-specific approaches to decision support^​26​. While targeted paediatric CDS tools — including integrated dose calculators — can improve prescribing safety in controlled settings, this does not remove the need for specialist judgement, particularly where off-label use and clinical nuance sit outside standard rule sets^​27,28​. The case study below sets out an example that illustrates this point.

There are additional limitations where administration and formulation are central to safe use. In frail adults, swallowing difficulties, covert administration and liquid formulations often require nuanced decisions that are not well supported by automated alerts.

Children, young people and adults with learning disabilities and autism also require tailored use of CDS. Behaviours perceived as ‘challenging’ are frequently managed with medication, despite often reflecting unmet needs, communication barriers or environmental factors^​29​. CDS tools that prioritise symptom-based prescribing may reinforce this unless used alongside person-centred assessment and reasonable adjustments. 

Transitions of care represent another high-risk context for CDS use. Medication changes are common at admission, transfer and discharge, increasing the likelihood of error^​30​. CDS can support medicines reconciliation and discharge planning, but its effectiveness depends on accurate, shared information and clear responsibility for reviewing alerts, implementing medication changes and ensuring appropriate follow-up.

Benefits and opportunities

When well designed and appropriately implemented, CDS tools can reduce prescribing errors by identifying interactions, contraindications and dose limits at the point of care^{​1,31,32​}. This supports safer, more consistent decision-making, particularly in high-risk or time-pressured environments.

CDS tools also promote the standardisation of practice by embedding national and local guidance directly into clinical workflows. This helps reduce unwarranted variation, supports adherence to evidence-based recommendations and provides a transparent rationale for treatment decisions that can be shared across the multidisciplinary team^​2​.

From an operational perspective, CDS can improve efficiency by reducing the need to manually search multiple reference sources and by automating routine safety checks. Structured data generated through CDS systems can also support audit, service evaluation, research and quality improvement, enabling organisations to identify trends in prescribing, monitor high-risk medicines and target improvement work^​1,33​.

Importantly, CDS tools can facilitate multidisciplinary and shared decision-making. Decision aids and patient-facing tools provide accessible information on treatment options, benefits and harms, helping patients and families to engage more meaningfully in discussions about care^​3​. Used in this way, CDS tools act as both safety mechanism and communication aid within medicines optimisation.

Limitations and risks

Alongside these benefits, CDS tools introduce risks. High volumes of non-specific or poorly contextualised alerts contribute to alert fatigue, increasing the likelihood that important warnings will be overridden or ignored^​34​. Alerts that interrupt workflow or require documentation outside the prescribing interface can also increase cognitive load and encourage workarounds^​1,35​. 

Automation bias is another concern. The absence of an alert may be incorrectly interpreted as confirmation that a prescription is safe, creating a false sense of security^​35​. This is particularly problematic in complex or specialist areas where CDS rules cannot capture the full clinical context.

Over-reliance on automated checks may also contribute to de-skilling if core knowledge of dosing, interactions and therapeutic decision-making is not maintained^​36​. CDS tools should therefore support, rather than replace, professional review.

As digital health technologies expand, unregulated apps and calculators present additional risk if algorithms are outdated or not aligned with current guidance. Pharmacy professionals risk using outdated data and incorrect algorithms, while patients could be shown inappropriate responses for their needs^​37​. 

CDS tools require constant maintenance to stay up to date as guidelines and formularies evolve. This demands significant financial and workforce investment across clinical, governance and technical teams. Without continuous updates, the tools become obsolete. Even advanced healthcare organisations report difficulty keeping them up to date^​35​. 

Emerging directions

Emerging developments in CDS are increasingly shaped by advances in AI and machine learning. AI-enabled systems can support predictive risk modelling, earlier identification of medication-related harm and more personalised dosing by analysing complex datasets, including laboratory results and treatment histories^​31​.

Work examining AI across the medication-use process also highlights the value of indication-based prescribing, shifting practice from drug-centred workflows towards diagnosis-led decision-making^​32​. As pharmacist prescribing expands, aligning workflows with these approaches may strengthen adherence to evidence-based standards and support medicines optimisation^​32​.

Advances in genomics further extend CDS capability through integration of pharmacogenomic data and predictive modelling to guide gene–drug decisions, with the results of early studies demonstrating improvements in risk prediction and dosing accuracy^​38​.

Digital patient-facing tools, including mobile applications and decision aids, create additional opportunities to support engagement, adherence and shared decision-making. As systems become more connected, robust interoperability and data standards remain essential to ensure CDS functions safely across care settings.

Across these developments, pharmacy professionals remain central. Professional guidance consistently highlights the role of pharmacists in leading the design, validation, governance and evaluation of AI-enabled CDS to ensure implementation is safe, ethical and clinically meaningful^​37​.

Implications for pharmacy practice

The evolution of CDS has practical implications for the pharmacy workforce. Pharmacy professionals are well placed to contribute to system design and governance owing to their oversight of the medicines pathway and expertise in risk management. This role extends beyond configuration to ongoing validation, monitoring of unintended consequences and the optimisation of alert strategies.

Digital literacy and structured training are increasingly important as AI-enabled tools become embedded in routine practice. Reviews of AI applications in pharmacy repeatedly highlight the need for pharmacists to develop competence in data interpretation, algorithmic limitations and ethical considerations surrounding automation^​31,38​.

Effective implementation also depends on close collaboration with prescribers, nurses, digital teams, regulators and patients to ensure CDS supports real clinical workflows rather than disrupting them. Balancing medicines safety priorities with multidisciplinary practice and patient expectations is essential for sustainable adoption.

Organisations need robust evaluation frameworks to assess the impact of CDS on patient outcomes, efficiency, equity and staff workload. Ongoing measurement allows systems to be refined and ensures that decision support genuinely enhances, rather than complicates, medicines optimisation^​32​.

Conclusion

CDS is now embedded across digital prescribing and medicines management systems, playing an important role in improving safety, consistency and quality of care. When well designed and appropriately implemented, CDS can reduce error, support evidence-based decision-making and enable more effective multidisciplinary and shared decision-making. However, these tools are not a substitute for professional judgement, particularly in complex or high-risk situations, where clinical context is essential. Pharmacy professionals have a key role in the design, governance and ongoing optimisation of CDS to ensure systems remain accurate, usable and patient-centred as digital and AI-enabled approaches continue to evolve.