Analyze Patient Records in Excel
Budget: ₹600 – ₹1,500 INR
I have a raw database export of patient records that first needs to be shaped into a clean, well-structured Excel workbook and then explored.
The work falls into two clear parts:
1. Statistical summary
• Descriptive statistics (mean, median, standard deviation, counts) for key clinical variables.
• Pivot-table overviews of demographics, diagnoses, procedures, length of stay, and any other obvious fields you spot once the data are visible.
• Clear charts where they help tell the story.
2. Comparative study
• Side-by-side comparison of at least two cohorts that I will specify once you have the data laid out (for example, treatment A vs. treatment B, or age brackets).
• Appropriate tests (t-test, chi-square, or non-parametric equivalents as the data dictate) with p-values noted.
• A short, plain-English interpretation of what the numbers show.
I am fine with you using the tools you know best—Power Query for the import, formulas, pivot tables, or even a bit of VBA if it simplifies repetitive steps—but the deliverable must remain an editable .xlsx file plus a concise summary sheet that walks me through your findings. Clean, readable formulas and comments are a must so that I can re-trace your steps later.
If anything in the export looks off (missing headers, obvious outliers, or coding quirks), flag it early so we fix issues before analysis begins.
The work falls into two clear parts:
1. Statistical summary
• Descriptive statistics (mean, median, standard deviation, counts) for key clinical variables.
• Pivot-table overviews of demographics, diagnoses, procedures, length of stay, and any other obvious fields you spot once the data are visible.
• Clear charts where they help tell the story.
2. Comparative study
• Side-by-side comparison of at least two cohorts that I will specify once you have the data laid out (for example, treatment A vs. treatment B, or age brackets).
• Appropriate tests (t-test, chi-square, or non-parametric equivalents as the data dictate) with p-values noted.
• A short, plain-English interpretation of what the numbers show.
I am fine with you using the tools you know best—Power Query for the import, formulas, pivot tables, or even a bit of VBA if it simplifies repetitive steps—but the deliverable must remain an editable .xlsx file plus a concise summary sheet that walks me through your findings. Clean, readable formulas and comments are a must so that I can re-trace your steps later.
If anything in the export looks off (missing headers, obvious outliers, or coding quirks), flag it early so we fix issues before analysis begins.