At a glance
- Role
- Product Manager, part-time contract
- Period
- 2025 – 2026
- Setting
- Private multi-specialty hospital, inpatient and outpatient
- Scope
- Workflows, billing, inventory, reporting, automation and AI tooling
- Worked with
- Physicians, nurses, pharmacy, administration, procurement and finance
- Tools
- SQL, Excel, Power BI, Microsoft Copilot Studio, n8n, Zapier, Make
Context
I joined Duchess International Hospital on a fixed-term, part-time contract to improve clinical and administrative workflows, supporting systems and compliance.
The work crossed department boundaries. A change in discharge could affect pharmacy, billing and nursing, so the teams needed a shared view of the problem and the proposed change.
The problem
Patient flow and billing were breaking down, but the explanations varied by department. I was asked to identify the causes and recommend practical changes.
In discharge, billing and medication use, operational data challenged the initial explanation.
Discharge: the wait came after the decision
People blamed the doctor's sign-off. The wait was in pharmacy and billing clearance after the decision to discharge had been made.
Billing: the errors started on the ward
People blamed the billing desk. Charges were being entered late or incompletely at the point of care, so the invoice was wrong before billing saw it.
Medication: stock, not pharmacy
People blamed pharmacy. The causes were stock gaps and slow procurement, one step behind the dispensary.
Five groups, five sets of priorities
Clinical, pharmacy, administration, procurement and finance each had urgent needs, in a heavily regulated setting where safety and compliance come first.
Finding the cause
Workshops and journey mapping
I ran workshops and journey-mapping sessions with physicians, nurses, pharmacy, administration and procurement to find where workflows broke down.
Current-state maps
I mapped current-state patient flow and billing across clinical, pharmacy, administrative, procurement and finance teams, and reviewed workflows across inpatient and outpatient departments.
What people said, checked against the data
I combined what staff described with operational data, and used the data to find where delays really occurred, which was not where people assumed.
Product decisions
Redesign the process before automating it
I redesigned ward rounds, discharge, billing and medication-use workflows instead of automating the existing steps.
The evidence pointed to problems in the sequence of work. Automating that sequence would have preserved the delays.
Start discharge clearance early
Pharmacy, billing and admin clearance now start as soon as a discharge is planned, not after it is signed.
The wait sat after the decision, so the fix was to move that work earlier and run it alongside the clinical steps.
Fix billing errors at the source
Charges are captured at the point of service under agreed rules, and checked automatically before the invoice is raised.
The errors came from what was entered on the ward. Checking invoices at the end would not have removed them.
Build agreement with billing and finance
Billing and finance were wary of automation. I showed them the error data before proposing any change.
The data showed that errors began upstream of billing. Establishing that shared understanding helped the team support the change.
One backlog for every department
I turned competing departmental priorities into a single prioritised backlog, judged against patient and operational impact, and ran regular demos.
Department heads were protecting their own priorities. One visible list and regular demos showed each of them where their request stood and why.
Check AI outputs before staff rely on them
I wrote the system prompts and instructions for the agents and automations, and evaluated their outputs for accuracy before staff relied on them.
In a clinical setting a confident wrong answer is a safety risk. Compliance, clinical safety and usability had to be balanced in every release.
Discharge, before and after
Before
- Doctor decides to discharge
- Discharge is signed
- Pharmacy, billing and admin clearance begin
- Patient waits for clearance
- Patient leaves
Clearance began only after sign-off. This is where the wait was.
After
- Discharge is planned
- Pharmacy, billing and admin clearance begin
- Discharge is signed
- Patient leaves
Clearance starts when discharge is planned and runs alongside the clinical steps.
What shipped
Ward rounds
Decisions are recorded during the round, so pharmacy, billing and nursing can act straight away.
Discharge
Pharmacy, billing and admin clearance start when discharge is planned.
Billing
Charges are captured at the point of service under agreed rules and checked automatically before the invoice.
Medication use
Orders are checked for risk before dispensing, and stock levels are visible before a medicine runs out.
Dashboards and leadership reporting
KPI dashboards covering patient, medication and inventory measures, built in SQL, Excel and Power BI.
Guides for staff
FAQs, user documentation and training on the new tools.
To protect patient confidentiality, this case study uses aggregate results and simplified diagrams. It includes no patient records or identifiable clinical information.
Delivery
Staff tested each change and signed it off before go-live, with a follow-up review afterwards.
A champion network of department superusers drove adoption, gathered feedback and kept changes visible across teams.
Readiness assessments, stakeholder engagement plans and training came before each rollout.
I led the cross-department rollout, balancing compliance, clinical safety and usability.
Measuring success
Wait times were measured at four points: discharge decision to the patient leaving, outpatient registration to seeing a clinician, prescription to dispensing, and service delivery to a final invoice.
Billing errors were counted from invoices corrected or reissued, patient disputes, missed charges found on review, and sample audits of invoices.
Compliance meant every department meeting the hospital's medication-safety policy and its external regulatory standards.
Dashboards tracked patient, medication and inventory KPIs, and adoption was monitored after each deployment.
Outcomes
Process and patient wait times cut by 50%.
Billing errors reduced by 70%.
100% compliance with safety and regulatory standards across departments.
Lessons learned
Observe the work as it happens
Time with clinical, pharmacy, administration and procurement staff revealed handoffs the process documents did not capture. Those observations made the workflow maps useful.
The team that gets blamed is rarely the cause
Discharge, billing and medication delays were each pinned on the last team to touch them. In all three the cause sat one or two steps earlier.
Set the baseline before the change
Baselines against the legacy manual processes were what let me show the impact of each change, and what kept leadership behind the next one.
Go-live is the midpoint
Adoption problems show up after launch. Spotting them early and following up with staff after go-live mattered as much as the rollout itself.
Explore the product
Agents and automations
Built with Microsoft Copilot Studio, n8n, Zapier and Make to take repetitive work off staff.
Request routing+
Requests from departments are routed to the right owner automatically.
Stock alerts+
An alert fires when inventory falls below a set level.
Automatic reporting+
Reports and dashboards refresh without manual work.
Billing rule check+
Billing entries that break a rule are flagged before the invoice is raised.