Selected Case Studies
Selected Case Studies
Case studies across medical AI risk-warning prototypes, healthcare and public-health dashboards, enterprise healthcare technology delivery, and 0-to-1 product and workflow operations.
Case 01
Oncology High-Risk Prescribing Warning System Prototype
MSc independent research exploring how high-risk prescribing patterns in oncology — particularly psychotropic medicines and CNS depressant combinations — could be surfaced for pharmacist or clinician review. The aim is a review-support prototype, not a treatment recommendation engine.
Real-world prescribing data is dense and time-ordered: the same medication combination can be routine in one window and high-risk in another. The challenge was to design candidate trigger logic and explainable outputs that a reviewer can trust, while staying strictly within a non-clinical, proof-of-concept boundary.
- Conducted literature and data-feasibility research mapping candidate oncology cohorts, medication timelines, drug classes, observation windows, and proxy safety events (emergency visits, admissions, falls, delirium).
- Designed candidate trigger logic around drug-class overlap, medication burden, and age / prior-event explanation context.
- Built explainable yellow/red review-priority alerts that output triggered classes, time window, rationale fields, and a review prompt.
- Planned a review-interface structure: medication timeline, active alerts, trigger rationale, patient stratification, review queue, and candidate-logic notes.
Real-world data feasibility
Mapped cohort identification, inclusion/exclusion, observation windows, drug-class grouping, and proxy safety events using real-world healthcare data structures. Aggregate-level feasibility exploration only.
Candidate warning logic
Examples include opioid + sedating-medication overlap within one window, psychotropic/sedating medication burden, and age / prior falls-or-delirium explanation context — each paired with an explanation output.
Explainable alert output
A prototype alert card: review-priority level, triggered medication-class combination, time window, explanation fields, and a prompt to clinical or pharmacy review.
Boundary & data ethics
Non-clinical proof of concept. Yellow/red indicate prototype review priority only, not validated clinical risk stratification. Candidate logic requires supervisor, clinical, or pharmacy validation and does not replace clinical judgement. No patient-level or restricted data is shown.
Demonstrates how real-world healthcare data, candidate rules, and explainable outputs can be combined into a review-support prototype — connecting data science, healthcare context, and product thinking. It is a non-clinical proof of concept that supports, and does not replace, clinical review.
Case 02
Women's Health Access Pressure Dashboard
Designed for a UK women's-health startup-style regional research and strategy scenario: which regions in England should a small team investigate first for access pressure, and why? It uses public aggregate data only.
Different signals use different units and tell different stories — long waits, deprivation, and population scale don't move together. The challenge was to combine them transparently without implying a clinical or individual-level risk judgement.
- Combined three public aggregate signals: England gynaecology waiting-time statistics, the English deprivation index, and England female population estimates.
- Normalized waiting pressure, access friction, and affected-population scale to 0–100 indicators and combined them through an adjustable weighted priority index.
- Designed dashboard storytelling: regional ranking, driver decomposition, a map view, and a selected-region explanation card.
- Documented method and limitations — awareness, trust, transport/time-off, and care-quality barriers lack comparable public data and remain follow-up questions.
Three signals & sources
Waiting pressure (gynaecology waiting times, Mar 2026), deprivation & access friction (English deprivation index, 2025), and affected-population scale (female population estimates, mid-2024).
Weighted priority index
Each signal normalized to 0–100 and combined through adjustable weights (default 50 waiting / 30 deprivation / 20 population), so users can test scenarios rather than trust a single fixed score.
Dashboard storytelling
Regional ranking with a regional-mean line, driver decomposition by signal, an England map (warmer = higher pressure), and a selected-region 'why this region' card with a next-investigation hypothesis.
Boundary & data scope
Public aggregate data only — no patient-level, user-level, employer-level, or internal provider data. The priority index supports regional exploration and decision support; it is not a clinical risk score and does not replace clinical judgement.
Turns scattered public datasets into a transparent, adjustable decision-support tool that shows not just which regions rank highest but why — positioning the index as a discovery tool for strategy, explicitly not a clinical risk score.
Case 03
Johnson & Johnson Healthcare Technology Delivery Case
In a healthcare technology environment at Johnson & Johnson, China-region business modules needed cloud access while accounting for data isolation, security compliance, network access, and global deployment constraints. Business users needed a clear onboarding path; technical and global teams needed early visibility of China-specific risks and dependencies.
The global Azure environment and the China-region environment were not always aligned — services, permissions, and access patterns available globally were not always available in China. Selected components had to be validated before global teams could configure networking and access.
- Acted as a translator between business stakeholders and technical teams, converting network architecture, access-control logic, and security dependencies into business-actionable rollout steps.
- Coordinated business, security, network, Microsoft, and global stakeholders to support delivery.
- Ran development-environment proof-of-concept checks and produced risk lists and validation feedback to reduce rollout rework.
- Created SOPs and user-facing documentation for cloud resource requests, access control, network issues, and platform usage.
Localised cloud access architecture
Mapped China-region module onboarding into compliant Azure access architecture and validation documentation, accounting for data isolation, security, and network dependencies before global handover.
Dev-environment PoC & risk list
Conducted development-environment proof-of-concept checks and produced risk lists, validation feedback, architecture notes, and cross-team handover materials.
Cloud cost & optimisation reporting
Analysed Azure usage, cost, risks, and optimisation actions through monthly Excel/PPT reporting, contributing to a 16% reduction in average monthly cloud costs.
Reusable SOPs & handover
Created SOPs and user-facing documentation for cloud resource requests, access control, network issues, and platform usage to reduce repeated questions and rework.
Shows I understand the full journey of a technical solution inside a healthcare enterprise — from requirements clarification, access security, and risk identification through to business delivery. Healthcare data products depend on controlled data environments, clear permission boundaries, and security-compliant workflows, not only models or interfaces.
Case 04
0-to-1 Product & Customer Workflow Operations
A new customer-facing business (Tada Coffee & Bistro) needed a full product and operations loop from 0 to 1: positioning, customer journey, CRM, service workflow, and online/offline operations.
Community engagement -> WeChat mini-program -> ordering / booking / payment -> service workflow -> feedback & CRM follow-up -> product iteration
Directly relevant to digital health: the same building blocks — user journey design, feedback loops, CRM-style follow-up, and product iteration — underpin patient and user engagement and adherence in digital-health products.
- Owned product positioning, customer journey, CRM, service workflow, online/offline operations, and performance tracking.
- Launched and iterated a WeChat mini-program for ordering, booking, and payment.
- Analysed behaviour and feedback from 1,500+ WeChat community members and 1,000+ organic RedNote followers.
- Used customer feedback and A/B testing to improve the user journey and increase online conversion by 10%.
- Ran CRM-style follow-up and feedback loops to support retention and repeat visits.
- Translated community feedback into product iteration, content strategy, and campaign decisions.
Case 05
Operational KPI Dashboards & Reporting
At Only Education, multiple campuses needed clearer visibility into enrolment, renewals, refunds, attendance, revenue, and course consumption for weekly and monthly management reporting.
Turned fragmented campus data into structured reporting and recommendations — the data-to-decision foundation that the healthcare dashboards build on.
- Built SQL/Excel dashboards and KPI trackers covering enrolment, renewals, refunds, attendance, revenue, course consumption, and campus performance.
- Analysed student behaviour, retention, conversion, and operational trends across campuses.
- Prepared PowerPoint reporting for sales and management teams.
- Tracked weekly and monthly KPIs across multiple campuses.
- Translated fragmented operational data into management reporting, business insights, and follow-up recommendations.
Case 06
Hands-on Technical Lab (Edge Delivery)
A small supplementary lab, kept to show the hands-on technical ability behind the data products: I built a custom-domain edge-delivery demo to test DNS, HTTPS/TLS, redirects, cache behaviour, and response headers.
Supplementary technical proof that I can build, test, and explain web-delivery and infrastructure concepts — the practical skills behind deploying dashboards and data tools.
- Configured a custom-domain edge delivery demo.
- Tested DNS, HTTPS/TLS, redirects, cache behaviour, and response headers.
- Prepared a reproducible walkthrough for non-specialist readers.
- Validated DNS routing and HTTPS responses with command-line checks.
- Checked redirect status codes, security headers, cache-control, and edge cache behaviour.
- Summarised the setup in a walkthrough written for non-specialist readers.