LICQual Level 3 Diploma in Pharmacy Data Analytics (Dip Pharmacy Data Analytics) 

The LICQual Level 3 Diploma in Pharmacy Data Analytics (Dip Pharmacy Data Analytics) is a specialized qualification designed for learners who wish to strengthen their expertise in data-driven decision-making within the pharmacy and healthcare sectors. This programme equips learners with the essential knowledge and analytical skills needed to interpret complex data, enhance pharmaceutical services, and contribute to improved patient outcomes.

By combining pharmacy knowledge with modern data analytics tools, this diploma enables learners to bridge the gap between clinical practice and digital innovation. Key areas include data interpretation, predictive modelling, pharmaceutical informatics, and quality improvement strategies, all of which are critical in today’s evolving healthcare environment.

This qualification is ideal for professionals aiming to enhance their career prospects, expand their knowledge base, and demonstrate their commitment to Continuing Professional Development (CPD). It not only prepares learners for advanced roles in pharmacy management, research, and healthcare technology but also supports organisations in achieving greater efficiency, compliance, and evidence-based practice.

Centres offering this qualification must ensure that delivery is supported by competent and qualified staff, with access to appropriate study materials, digital resources, and analytical tools. Maintaining high-quality training and learner support is essential to ensure successful outcomes. With the right guidance and facilities, learners will gain both the confidence and the capability to apply data analytics to real-world pharmacy challenges.

The LICQual Level 3 Diploma in Pharmacy Data Analytics is therefore a valuable pathway for learners seeking to advance within the pharmaceutical sector while contributing to innovation and excellence in healthcare.

Course Overview


Qualification Title

LICQual Level 3 Diploma in Pharmacy Data Analytics (Dip Pharmacy Data Analytics) 

Total Units

6

Total Credits

60

GLH

240

Qualification #

LICQ2201188


Qualification Specification

Download Qualification Specification

To enroll in the LICQual Level 3 Diploma in Pharmacy Data Analytics (Dip Pharmacy Data Analytics) , applicants must meet the following criteria:

  • Age Requirement: Applicants must be at least 18 years old.
  • Educational Requirements: A Level 2 qualification or equivalent in pharmacy, healthcare, science, or a related field is preferred. Learners with relevant professional experience may also be considered.
  • Experience: While prior experience in pharmacy, healthcare, or data handling is beneficial, it is not mandatory. A strong interest in pharmacy data analytics and healthcare innovation is essential.
  • English Language Proficiency: Applicants must have a good command of the English language. Non-native English speakers should demonstrate English proficiency equivalent to IELTS 5.0 or CEFR Level B1 to ensure effective participation and comprehension.
  • Commitment to CPD: Applicants should be committed to Continuing Professional Development (CPD) and willing to enhance their knowledge and skills to meet industry standards.
  • Access to Required Resources: Learners should have access to a computer or digital device with internet connectivity, as well as the ability to use software and tools relevant to pharmacy data analytics.

Qualification#

Unit Title

Credits

GLH

LICQ2201188-1

Fundamentals of Pharmacy Data Analytics

10

40

LICQ2201188-2

Data Collection, Management, and Integrity in Pharmacy

10

40

LICQ2201188-3

Statistical Methods and Data Interpretation

10

40

LICQ2201188-4

Pharmaceutical Informatics and Digital Health Systems

10

40

LICQ2201188-5

Data-Driven Decision-Making in Pharmacy Practice

10

40

LICQ2201188-6

Research, Reporting, and Professional Development in Data Analytics

10

40

By the end of this course, learners will be able to:

Unit 1: Fundamentals of Pharmacy Data Analytics

By the end of this unit, learners will be able to:

  • Explain the principles and importance of data analytics in pharmacy and healthcare.
  • Describe key data types and sources used in pharmacy practice.
  • Analyse the role of data in improving patient safety, compliance, and clinical outcomes.
  • Apply foundational knowledge of analytics to pharmacy-related case studies.

Unit 2: Data Collection, Management, and Integrity in Pharmacy

By the end of this unit, learners will be able to:

  • Demonstrate knowledge of data collection methods in pharmacy and healthcare settings.
  • Evaluate techniques for ensuring data accuracy, confidentiality, and security.
  • Apply principles of ethical data management and governance.
  • Assess challenges in maintaining data integrity and propose practical solutions.

Unit 3: Statistical Methods and Data Interpretation

By the end of this unit, learners will be able to:

  • Explain key statistical concepts relevant to pharmacy data analytics.
  • Apply statistical tools and techniques to analyse pharmaceutical datasets.
  • Interpret data results to support evidence-based pharmacy practice.
  • Present statistical findings in a clear and professional format.

Unit 4: Pharmaceutical Informatics and Digital Health Systems

By the end of this unit, learners will be able to:

  • Describe the role of pharmacy informatics in digital health transformation.
  • Evaluate the use of electronic health records and clinical information systems.
  • Demonstrate knowledge of digital tools and technologies used in pharmacy.
  • Assess the benefits and challenges of digital integration in healthcare delivery.

Unit 5: Data-Driven Decision-Making in Pharmacy Practice

By the end of this unit, learners will be able to:

  • Apply data analytics to improve pharmacy operations and patient care.
  • Evaluate pharmacy data for trends, risks, and opportunities.
  • Use data insights to support compliance, cost-effectiveness, and efficiency.
  • Demonstrate decision-making skills using real-world pharmacy data scenarios.

Unit 6: Research, Reporting, and Professional Development in Data Analytics

By the end of this unit, learners will be able to:

  • Plan and conduct small-scale pharmacy data research projects.
  • Critically evaluate data sources and apply evidence-based methods.
  • Produce professional reports with accurate analysis and recommendations.
  • Reflect on personal development needs and plan for Continuing Professional Development (CPD).

The LICQual Level 3 Diploma in Pharmacy Data Analytics is designed for learners who want to build specialized knowledge in using data to improve pharmacy practice, healthcare decision-making, and patient outcomes. This course is ideal for:

  • Aspiring pharmacy professionals who want to develop skills in pharmacy data analytics and digital healthcare.
  • Pharmacy technicians and assistants looking to enhance their expertise in data management, reporting, and analysis.
  • Healthcare professionals aiming to apply data-driven strategies in improving patient care and pharmacy services.
  • Quality assurance and compliance officers who wish to use data insights to maintain standards and regulatory compliance.
  • Graduates in pharmacy, life sciences, or healthcare seeking to specialize in pharmaceutical data analysis.
  • Research and development staff interested in applying analytical methods to healthcare innovation and pharmaceutical studies.
  • Data enthusiasts within healthcare who want to explore how analytics transforms pharmacy operations.
  • Professionals committed to Continuing Professional Development (CPD) and career advancement in the pharmaceutical and healthcare sectors.

Centres delivering the LICQual Level 3 Diploma in Pharmacy Data Analytics must meet specific standards to ensure high-quality training and learner success. These requirements guarantee that learners receive the knowledge, resources, and support needed to apply data analytics effectively within pharmacy and healthcare practice.

  • Qualified and competent staff – Centres must employ trainers and assessors with appropriate academic qualifications and relevant professional experience in pharmacy, healthcare, or data analytics.
  • Access to learning resources – Centres should provide up-to-date study materials, journals, case studies, and access to digital platforms and analytical tools.
  • Technology and facilities – Adequate IT facilities, software, and secure data systems must be available to support practical learning in pharmacy data analytics.
  • Robust quality assurance systems – Internal quality assurance policies must be in place to ensure fair assessments, accurate feedback, and consistent learner outcomes.
  • Compliance with international standards – Centres must deliver the qualification in line with global education and training benchmarks, ensuring relevance to the pharmaceutical and healthcare sectors.
  • Learner support and guidance – Academic support, mentoring, and career advice should be provided to help learners progress and achieve their professional goals.
  • Commitment to CPD – Centres must encourage both learners and staff to engage in Continuing Professional Development (CPD) to stay updated with industry developments.
  • Inclusive learning environment – A safe, supportive, and inclusive environment must be maintained, promoting equality, diversity, and active learner engagement.

Assessment and Verification

All units within this qualification are subject to internal assessment by the approved centre and external verification by LICQual. The qualification follows a criterion-referenced assessment approach, ensuring that learners meet all specified learning outcomes.

To achieve a ‘Pass’ in any unit, learners must provide valid, sufficient, and authentic evidence demonstrating their attainment of all learning outcomes and compliance with the prescribed assessment criteria. The Assessor is responsible for evaluating the evidence and determining whether the learner has successfully met the required standards.

Assessors must maintain a clear and comprehensive audit trail, documenting the basis for their assessment decisions to ensure transparency, consistency, and compliance with quality assurance requirements.

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