Power BI Dashboard Reports

Dashboard 1.1: Executive Overview

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The Executive Overview dashboard provides a concise view of population scale, healthcare utilisation, claims cost, payer contribution, patient responsibility, and 30-day returns. It is designed for high-level operational monitoring before users drill into patient, clinical, claims, or readmission pages.

All figures use the synthetic Synthea export and are demonstrations of analytical engineering. They are not real-world clinical findings.

Dashboard 1.2: Key Performance Indicators

The return metric is based on 1,838 completed inpatient encounters, of which 620 had a later inpatient or emergency encounter within 30 days.

Dashboard 1.3: Visuals

Key findings from the exported data

Encounter utilisation mix

Wellness and ambulatory encounters account for 38,042 encounters, or 71.32% of all recorded utilisation. Inpatient encounters are a much smaller portion of volume but form the denominator for the 30-day return metric.

Highest-volume organisations

VA Boston Healthcare System Jamaica Plain Campus is the highest-volume organisation with 3,217 encounters, representing approximately 6.03% of all encounters.

Claims and coverage pattern

NO_INSURANCE has the largest total claim cost and no payer contribution, so the complete $1.31M is attributed to patient responsibility. Medicare has the second-highest claim cost and covers 63.82% of its associated claims.

Data and refresh note

Figures were calculated from the curated CSV marts in data/csv_output/. The current export manifest records a refresh timestamp of 2026-07-20 18:33 UTC. A successful Airflow run refreshes the CSVs and manifest; refreshing Power BI then updates the dashboard metrics and visualisations.

Dashboard 2.1: Patient Population

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The Patient Population dashboard describes the demographic composition, geographic distribution, aggregate patient expense and coverage fields, and active-condition burden of the synthetic population.

Patient expense and coverage fields are synthetic source-generated values. They are used to demonstrate aggregation and comparison techniques, not actual annual healthcare costs.

Dashboard 2.2: Visuals

Dashboard 2.3: Key Findings

Demographic composition

The population includes 609 female patients (52.01%) and 562 male patients (47.99%). White patients account for 965 records (82.41%), followed by Black patients with 101 records (8.63%) and Asian patients with 90 records (7.69%).

The ethnicity visual shows 1,058 non-Hispanic patients (90.35%) and 113 Hispanic patients (9.65%).

Geographic distribution

All patients are located in Massachusetts. Middlesex County has the largest population with 255 patients (21.78% of the total), followed by Worcester County with 150 patients.

Active condition burden

Obesity is the most common active condition, associated with 449 patients (38.34% of the population). Prediabetes and hypertension are also prominent, affecting 317 and 302 patients respectively. These are synthetic patterns intended only to demonstrate the active-condition visual and patient-count measure.

Dashboard 3.1: Clinical Utilisation

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The Clinical Utilisation dashboard combines encounter volume, service type, organisation activity, active-condition burden, procedure volume, and immunization volume. It supports an operational view of how the synthetic population uses healthcare services.

The dashboard also contains 15,478 immunization events. Provider specialty is not used as a slicer because the exported provider data contains only one specialty value: GENERAL PRACTICE.

Dashboard 3.2: Visuals

Recommended filters are calendar year, month, state, and encounter class. Use an encounter-class button slicer because it has only six easily comparable values.

Dashboard 3.3: Key Findings

Utilisation mix and time trend

Wellness encounters are the largest category with 19,106 events (35.82%), closely followed by ambulatory encounters with 18,936 (35.50%). Together they account for 71.32% of all encounters. Outpatient encounters add 9,003 events (16.88%), while inpatient and emergency encounters account for 1,838 and 2,090 events respectively.

The largest annual encounter volume is 3,178 in 2014, followed by 3,153 in 2017 and 3,148 in 2016. The lower 2020 value should be interpreted cautiously because the source extract ends during 2020 and does not represent a full-year comparison.

Organisation and provider coverage

The encounter fact covers 1,104 providers and 1,103 organisations. VA Boston Healthcare System Jamaica Plain Campus is the highest-volume organisation with 3,217 encounters, followed by Worcester Outpatient Clinic with 1,972 and HALLMARK HEALTH SYSTEM with 1,658.

Clinical activity and procedures

The dashboard combines these procedure volumes with the active-condition visual. Obesity, prediabetes, and hypertension are the three most common active conditions, associated with 449, 317, and 302 unique patients respectively.

These utilisation patterns are derived from synthetic data. They demonstrate the dashboard's filtering and aggregation logic, not real clinical service demand.

Dashboard 4.1: Claims and Costs

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The Claims and Costs dashboard presents encounter-level claims, payer coverage, patient responsibility, and separate native-grain procedure and medication costs. Keeping these facts separate avoids double counting procedure or medication costs inside encounter claims.

Dashboard 4.2: Visuals

Dashboard 4.3: Key Findings

Encounter claim funding

Total encounter claim cost is $6,868,312.95. Payers cover $3,307,391.57, or 48.15%, while $3,560,921.38, or 51.85%, is assigned to patient responsibility. The largest annual claim cost is $409,282.07 in 2014; the next highest years are 2017 ($406,208.08) and 2016 ($405,613.95).

Payer coverage pattern

NO_INSURANCE has the highest claim cost and no payer contribution, making it the largest patient-responsibility category. Anthem has the highest coverage rate among named payers at 76.70%, although its total claim cost is smaller than Medicare, Medicaid, and Blue Cross Blue Shield.

Medication and procedure cost concentration

Medication facts total $100,106,420.41. Only $6,306,231.73 is payer coverage, leaving $93,800,188.68 as medication patient responsibility. These medication values should not be added to encounter claims because they are stored at a different event grain.

Financial figures are synthetic and demonstrate how the dashboard separates encounter, procedure, and medication cost grain for trustworthy analysis.

Dashboard 5.1: Readmissions / 30-Day Returns

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This dashboard uses the project’s synthetic-data operational return metric. A completed inpatient encounter is flagged when a later inpatient or emergency encounter occurs within 30 days. It is not a clinical readmission measure and should not be interpreted as one.

Figures below match the published page with no slicer selections applied (calendar year full range; month, gender, ethnicity, and county all set to All).

Dashboard 5.2: Visuals

Optional slicers are available for calendar year, month, gender, ethnicity, and county. The findings in this report do not apply any of those filters. Payer, provider, organisation, and encounter-class slicers are not used on this page because the readmission fact connects directly only to patient and date dimensions.

Dashboard 5.3: Key Findings — No Filter

Overall return metric

Of 1,838 eligible inpatient encounters, 620 have a later inpatient or emergency encounter within 30 days. That produces a 33.73% synthetic 30-day return rate. The average time between the index discharge and the return encounter is 17.93 days.

Those 620 return events are associated with only 33 distinct patients. The dashboard therefore reports both encounter-level and patient-level counts: the synthetic source contains repeated inpatient-return patterns for a small number of patients, so the encounter numerator is much larger than the patient count.

Demographic breakdown

Male encounters show a higher synthetic return rate than female encounters. Ethnicity differences should be read carefully: Hispanic patients contribute a much smaller denominator (107 eligible encounters) than non-Hispanic patients.

County comparison

Hampshire and Suffolk counties lead the synthetic return-rate ranking among larger denominators. Lower-rate counties such as Barnstable and Bristol still have meaningful eligible volumes, so county ranking supports exploration rather than clinical ranking.

Trend interpretation

With no month or year filter applied, the calendar-year line chart uses the full synthetic timeline. The trend is volatile because annual eligible volumes are uneven. Peaks above 60% and sharp drops toward 0% reflect small yearly denominators more than a stable operational pattern, and should not be treated as clinical signal.

These are synthetic-data patterns used to demonstrate a time-window metric, demographic comparison, denominator-aware rate analysis, and record-level drill-down. Power BI may display eligible and non-return counts as rounded thousands (for example 2K and 1K); the exact mart values are 1,838 eligible and 1,218 with no 30-day return.