---
title: "URSA-PHF | Summary Dashboard"
slug: "phf-reports-ursa-phf-summary-dashboard"
updated: 2025-07-08T18:05:19Z
published: 2025-07-08T18:05:19Z
canonical: "docs.ursahealth.com/phf-reports-ursa-phf-summary-dashboard"
stale: true
---

> ## Documentation Index
> Fetch the complete documentation index at: https://docs.ursahealth.com/llms.txt
> Use this file to discover all available pages before exploring further.

# URSA-PHF | Summary Dashboard

## Overview

This report is designed to monitor performance across markets, payors, and patient cohorts across top population health measures. Unlike other URSA-PHF reports which contain measures related to a single topic (e.g., Hospital Inpatient Readmissions) and are meant to introduce users to the key concepts related to that topic (e.g., which inpatient admissions qualify for the denominator of a readmission measure), this report includes a selection of measures across topic areas. This report contains pre-built dashboards to provide helpful views of measure results disaggregated by various patient, claim, or encounter groupers. These boards are meant to serve as a starting point and are meant to be localized based to your organization (e.g., your definition of a market).

[Video](https://cdn.document360.io/02092ce8-55b8-4ac5-9554-c0ccb3223feb/Images/Documentation/URSA-PHF%20Summary%20Dashboards.mp4)

## Use this report to

- Access pre-built boards that provide a profile of your patient population, their utilization, and variation across time, geography, plan membership, and patient condition cohorts.
- Create leadership dashboards for clinical and/or operational leads that monitor utilization across markets and payor contracts.
- Perform ad hoc analyses to answer questions raised by clinical and/or operational leaders across URSA-PHF topics areas.
- Upon receiving historical claims data for a new population (e.g., new risk based payor contract is going live) to understand the historical and current profile of the population and their utilization compared to existing populations.

## Potential takeaways

**Answering questions about the profile of your population:**

- How many patients have active plan membership broken out by their insurance financial class (Commercial/Medicare/Medicaid)?
- What percent of our patients have hypertension (or any of 50+ other specific chronic conditions)?
- What level of variation is there in the disease burden across plans and our clinics?
  - What percent of all patients have conditions impacting 2+ systems?
  - How does that vary by plan?
  - How does that vary by which of our clinics they are attributed to?
- What percent of hospital inpatient admissions result in a same day discharge?
  - What are the top reasons for those encounters?
  - How much is spent on those encounters?
- How does spending vary across types of encounters, services, and settings for patients living in geographies with differing levels of SDoH risk or barriers?