Healthcare IT Decoded - Data Visualization using Tableau

Understand the admissions and financial counseling steps in the patient journey, including registration vs admission, clinical data collection, and front desk revenue cycle management.

Explore the outpatient department workflow from front office to diagnosis, lab and radiology tests, and pharmacy prescription, highlighting the patient journey in the OPD setting.

Explore medical transcription and coding, including how ICD diagnosis and procedure codes standardize billing, drive revenue cycle management, and determine hospital costs through diagnosis-related group weights.

Identify source systems across emr platforms such as Meditech, Epic, Cerner, Sunquest, and GE Healthcare to understand data origins; incorporate lab, radiology, vitals, and external data for meaningful healthcare visualizations.

Identify source systems and extract data using formats like CSV, XML, and JSON, while applying HL7, FHIR, CCD, and DICOM standards for health care data visualization.

Explore how to define a logical data model by identifying KPIs, distinguishing master and transactional data, and aligning business analyst and technical teams before creating the database.

Load healthcare data after extraction and transformation, with the data model built in parallel with cleaning, using tools like Informatica Express, Mirth, Cloverleaf, and Rhapsody to support healthcare data standards.

Recap the patient journey from identifying source systems to extracting, transforming, and loading data, building logical and physical models, and deriving insights with Tableau or Power BI.

Explore the logic of building a Sankey chart in Tableau by connecting left-side age groups to right-side races with ranks and a sigmoid curve.

Create a Sankey chart in Tableau by connecting to a customized Excel file, duplicating data, padding fields, and building a curve with nested table calculations on age group and race.

Create the Sankey base in Tableau by turning marks to line, adding a path, and coloring by age group and race; size lines with a table calculation.

Learn to build a Sankey chart by creating the left and right sides, configuring age and race bar charts, applying shared filters, and refining labels, colors, and percentage breakdowns.

Create a Tableau Sankey dashboard by arranging the base, age, and race on opposite sides, removing labels and tooltips, and adding a bold 'Sankey Chart' header to emphasize deaths.

Create a unit chart in Tableau that uses symbols to proportionally represent hospital admissions. Use CMS readmissions data to visualize conditions like heart failure and COPD.

Access the My Tableau Repository and its Shapes folder to add and reload custom icons for the marks tab, using them in hex maps or unit charts.

Create a unit chart in Tableau to visualize hospital readmission reduction data by state, using calculated fields for calls and discharges, with icon shapes, colors, and labels.

Create a heatmap in Tableau from the measles dataset in Excel, arranging state by rows and year by columns, applying color by cases to reveal patterns and improve readability.

Create heatmaps in tableau using the covid 19 global data csv, exploring weekly deaths by country or region with color-coded bars to compare trends.

Explore heat map creation using BRFSS data on alcohol consumption from the CDC, including the data dictionary, prevalence and trends data, and visualization of crude prevalence by region.

Analyze BRFSS alcohol consumption data to build a heatmap in Tableau, filtering for 18–24 year olds who drank in the past 30 days, across 2001–2010, and removing duplicates.

Create an interactive heat map in Tableau to visualize alcohol consumption by location and year, using filters for topic, response, and age group, and customize colors for clear interpretation.

Explore how to create and interpret a donut chart in Tableau, using national health expenditures data, with filters for payer, service, age group, and gender to avoid double counting.

Create a donut chart in Tableau from age and gender health expenditure data, using dual axes and average values, and filter out total to show payer breakdown with labels.

Demonstrates building a donut chart in Tableau, applies filters on age group, gender, and services to exclude total values, ensuring accurate payer data like Medicaid.

Explore bullet charts that compare two values with a reference line and target line, using AHRQ inpatient discharge data by age groups, visualized in Tableau.

Create a bullet chart in Tableau by building calculated fields for 2019 and 2020 discharges, then use dual axis, gantt, and bar options to compare values.

Explore how bump charts rank penalties by state over time, turning dense line charts into readable rankings using CMS nursing home data for five to six states.

Create a bump chart in Tableau to visualize nursing home penalties by state, focusing on fine amounts, using table calculations to rank states and reverse the y-axis.

Learn to convert a bump chart into a heatmap in Tableau, using square marks and color cues to visualize nursing home penalties by state and quarter.