Excel Data Analysis for Healthcare Training Course

Duration 5 days 10 modules · 33 contact hours
Level Intermediate Certificate on completion
Who attends Healthcare Data Analyst, Health Services Manager and others
Fee from USD 1,100 KSh 95,000 for Kenyan organisations
Where 52 cities + online See dates by city
Next start 16 Nov 2026 Course code SD-HSM-058

Before you join: This intermediate course assumes participants can create and save Excel workbooks, enter formulas, format worksheets and work with basic tables.

Dates & prices

Two start dates a month in every city, and live online on weekdays or weekends. Fees are per participant; classroom fees include tuition, materials, lunch and refreshments, and the certificate.

Suggest a date or city

Showing the next six months. Later dates, other cities and private deliveries for your team are available on request.

Course overview

Health systems managers and analysts need reliable evidence for decisions on access, quality, capacity, workforce and financial performance. Yet data often arrives as inconsistent extracts from electronic health records, appointment systems, finance systems and operational reports. Manual spreadsheets can obscure missing values, duplicate records, changing definitions and formula errors. This course helps participants turn recurring healthcare data into controlled analyses that support service planning, performance review and management action.

Participants learn to structure healthcare datasets, clean imported records, apply Excel formulas, build PivotTables and produce decision-ready charts and dashboards. They calculate operational measures such as bed occupancy, length of stay, waiting times, no-show rates and activity volumes; financial measures including budget variances and cost per case; and quality indicators using rates, ratios, denominators and stratification. The course also addresses data dictionaries, confidential-data handling, small-number disclosure checks, audit trails and quality assurance before report distribution.

Teaching combines short instructor briefings with healthcare cases, guided workbook builds, group exercises, reporting simulations and individual application planning. Cases reflect common management questions, such as identifying delayed discharge patterns, reconciling coded activity with tariffs, monitoring clinic attendance and explaining a variance to an executive team. Participants leave with a reusable healthcare reporting workbook structure, KPI definition sheet, data-quality checklist and refresh procedure that can be adapted to their own service area.

The course is suited to professionals who already use Excel and need stronger analytical methods for healthcare management reporting. It is particularly relevant where teams must produce recurring performance packs, respond to data requests or improve confidence in operational and financial information.

What you will be able to do

  • Structure healthcare datasets using Excel Tables, data dictionaries and controlled field definitions
  • Clean and validate imported healthcare records using Power Query and Excel quality checks
  • Build formula-driven measures for activity, access, quality, capacity and cost reporting
  • Analyse healthcare performance using PivotTables, stratification, rates and variance analysis
  • Calculate operational indicators including occupancy, waiting times, no-show rates and length of stay
  • Create management dashboards using PivotCharts, slicers, conditional formatting and clear visual design
  • Apply confidentiality, disclosure-control and workbook audit practices to healthcare reports
  • Produce a repeatable Excel reporting process with documented definitions, refresh steps and checks

Benefits of attending

For you

  • Faster production of accurate healthcare performance reports
  • Stronger evidence for service improvement discussions
  • Practical methods for detecting data-quality problems
  • Greater confidence explaining trends, rates and variances
  • Reusable workbook designs for recurring management information

For your organisation

  • More consistent definitions for operational and financial healthcare indicators
  • Reduced spreadsheet errors in recurring management reports
  • Earlier identification of access, capacity and quality exceptions
  • Clearer evidence for resource allocation and service planning
  • Improved auditability of reported healthcare performance data

Course modules

10 modules over 5 days

Participants can organise healthcare data in Excel workbooks with clear fields, definitions and controlled structures.

  • Workbook architecture for patient, service, finance and workforce datasets
  • Tables, structured references and named ranges for controlled analysis
  • Data types, units and date formats in clinical extracts
  • Column-level data dictionaries linking source fields to measures
  • De-identified records and minimum-necessary handling of sensitive information
  • Importing CSV files and relational extracts into Excel tables

Participants can identify, correct and document common data-quality issues in healthcare extracts.

  • Data-quality dimensions: completeness, validity, consistency, timeliness and uniqueness
  • TRIM, CLEAN and SUBSTITUTE functions standardising imported text fields
  • Duplicate detection using COUNTIFS, Remove Duplicates and composite identifiers
  • Data Validation rules controlling dates, categories and numeric ranges
  • Missing-data flags separating unknown, not applicable and not recorded
  • Power Query steps profiling, transforming and combining recurring extracts
  • Exception logs documenting corrections, owners and unresolved data issues

Participants can build auditable Excel formulas for common healthcare activity and performance measures.

  • SUMIFS and COUNTIFS calculations for admissions, visits and discharges
  • XLOOKUP joins between activity records, reference lists and tariffs
  • IFERROR logic distinguishing missing, zero and invalid values
  • Date functions calculating length of stay and reporting periods
  • Absolute references protecting formula logic during monthly refreshes
  • Formula auditing with precedents, dependents and error checking

Participants can summarise and filter healthcare activity data using PivotTables and PivotCharts.

  • PivotTables summarising activity by service line, month and provider
  • Calculated fields and measures for rates, costs and variances
  • PivotCharts communicating filtered results without exposing record-level data
  • Slicers and timelines supporting controlled self-service report filtering
  • Grouping dates, age bands and value ranges for analysis
  • Refresh routines preserving field definitions and report consistency

Participants can interpret healthcare measures using rates, stratification, distributions and time-based analysis.

  • Descriptive statistics for wait times, occupancy and length of stay
  • Rates, ratios and denominators for service performance measures
  • Stratification by specialty, age band, payer and care setting
  • Percentiles and control limits distinguishing variation from single observations
  • Run charts tracking monthly performance against target thresholds
  • Confidence intervals and small-number suppression for published rates

Participants can create readable Excel dashboards that focus management attention on material exceptions.

  • Chart selection matching comparisons, trends, distributions and part-to-whole patterns
  • Combo charts comparing activity, capacity and target performance
  • Sparklines and conditional formatting highlighting exceptions within scorecards
  • Dynamic charts driven by PivotTable filters and slicers
  • Dashboard layout using visual hierarchy, whitespace and consistent scales
  • Accessibility checks for colour contrast, labels and printable reports

Participants can analyse demand, capacity and patient-flow indicators for service management decisions.

  • Bed occupancy calculations using available bed days and occupied bed days
  • Length-of-stay analysis by admission type, specialty and discharge destination
  • Waiting-time cohorts measuring referral-to-treatment pathways and breach rates
  • Appointment no-show rates segmented by clinic, day and reminder status
  • Capacity-demand tables comparing appointments, staffing hours and patient arrivals
  • Pareto analysis prioritising delay causes and improvement actions

Participants can connect activity, cost and budget information to explain financial performance.

  • Cost-per-case calculations linking expenditure, activity volumes and case categories
  • Budget-versus-actual variance analysis by department, account and month
  • Case-mix comparisons using diagnosis-related groups and weighted activity
  • Tariff reconciliation matching coded activity, prices and submitted claims
  • Scenario models testing volume, staffing and unit-cost assumptions
  • Contribution analysis separating fixed, variable and step costs

Participants can apply practical controls that protect confidential data and strengthen report auditability.

  • Role-based access, file permissions and version-control conventions for workbooks
  • Minimum-necessary data selection under patient confidentiality requirements
  • Cell protection and locked formulas preventing unauthorised report changes
  • Audit trails recording sources, transformations, assumptions and approvals
  • Disclosure-control checks for small cells and potentially identifiable results
  • Quality-assurance checklist before distributing monthly management information reports

Participants can plan a repeatable Excel reporting process for a priority healthcare management need.

  • KPI definitions specifying numerator, denominator, target, owner and refresh frequency
  • Balanced scorecard structure connecting quality, access, finance and workforce
  • Variance commentary distinguishing facts, causes, risks and required decisions
  • Requirements brief defining audience, decisions, indicators and data sources
  • Refresh procedure documenting steps, dependencies, timing and responsible roles
  • Personal application plan targeting one priority healthcare reporting process

Exercises and examples are adapted to each cohort's sectors and roles.

What you take back to work

  1. Healthcare KPI definition sheet
  2. Excel healthcare reporting workbook template
  3. Data-quality validation checklist
  4. Operational performance dashboard model
  5. Monthly report refresh procedure
  6. Healthcare management reporting action plan

Who should attend

  • Healthcare Data Analyst — needs reliable methods for recurring operational and performance reporting
  • Health Services Manager — needs evidence for capacity, access, quality and service decisions
  • Hospital Performance Officer — needs controlled KPI reports for management review meetings
  • Clinical Audit Coordinator — needs practical analysis tools for quality and outcome indicators
  • Healthcare Finance Analyst — needs activity, tariff, cost and budget variance analysis
  • Workforce or Operations Planner — needs demand, capacity and utilisation evidence for planning

Skills and tools covered

Healthcare data cleaningExcel formula analysisPivotTable reportingOperational KPI analysisHealthcare dashboard designWorkbook quality assurance

Tools and standards

Microsoft Excel, Power Query, PivotTable, Power Pivot

How the course runs

Training methodology

The course uses short instructor briefings followed by healthcare-focused case work, guided workbook builds, group exercises and reporting simulations. Participants work with realistic extracts covering activity, appointments, bed use, finance and performance indicators. The instructor demonstrates each Excel method, then supports participants as they apply it to structured scenarios. Group discussion examines indicator definitions, data-quality risks and management interpretation. Individual application planning helps participants identify a reporting process, workbook or KPI pack to improve after the course.

Requirements and prerequisites

This intermediate course assumes participants can create and save Excel workbooks, enter formulas, format worksheets and work with basic tables. Experience handling healthcare operational, financial, workforce or quality data is useful, although participants do not need clinical qualifications. Participants should be comfortable reading measures such as counts, percentages and averages. Prior knowledge of PivotTables, Power Query, statistical software, database design, programming or advanced mathematics is not required. The course explains healthcare reporting methods without assuming knowledge of a particular national health system.

A typical training day

08:30 – 10:30First session
10:30 – 10:45Refreshment break
10:45 – 12:30Second session
12:30 – 13:30Lunch and networking
13:30 – 15:00Third session
15:00 – 15:15Refreshment break
15:15 – 16:30Workshop and daily review

Live online deliveries follow the same structure in East Africa Time, with shorter screen blocks and longer breaks.

What the fee includes

  • Instruction by a practitioner facilitator
  • Full course workbook and materials
  • Exercise files, templates and case studies
  • Refreshments and lunch on classroom deliveries
  • Certificate of completion
  • Post-course application plan

Frequently asked questions

Participants should be able to use basic formulas, format worksheets and work with simple tables. PivotTables, Power Query and advanced statistical knowledge are taught during the course and are not required beforehand.

Participants should bring a laptop with a current desktop version of Microsoft Excel, preferably Microsoft 365 or Excel 2021 or later. They may also bring a de-identified report, KPI pack or workbook structure they want to improve.

It suits analysts, managers, audit staff, finance analysts and planners who prepare or use healthcare performance information. It is appropriate for hospital, primary care, public health, social care and health insurance settings.

The course uses healthcare management questions, datasets and indicators rather than generic business examples. It covers healthcare-specific issues such as activity definitions, patient confidentiality, small-number disclosure, waiting times, occupancy and tariff reconciliation.

Participants can apply the methods to recurring management packs, operational dashboards, budget reports and service-improvement analysis. The workbook structures, definitions and checklists can be adapted to local data sources and reporting cycles.

Each training day runs from 08:30 to 16:30 and provides about 6.5 contact hours. Time is divided across ten modules covering data preparation, analysis, dashboards, operational and financial measures, governance and application planning.

Questions about this course?

Ask about dates, fees, group bookings or running it for your team. Our training team replies by email.

Ask on WhatsApp info@skillsetdevelopment.com

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