Hospital Outcomes Scores (HOS)

“Death is the most important hospital outcome to avoid.”

The Hospital Outcomes Scores (HOS) were developed to provide maximum transparency of hospital outcomes to healthcare consumers based on data compiled by the Centers for Medicare & Medicaid Services (CMS) because:

  • Deaths are the most important outcome to avoid during a hospital stay.
  • Death rates from serious treatable complications are much higher than all complications rates.
  • Existing hospital ratings are a blend of deaths, complications, procedures and other factors
  • Existing hospital ratings are not good predictors of death rates.
  • HOS’s scale of 0% to 100% better differentiates among top performing (low death rate) hospitals than a letter grade or numerical scale of 1 to 5.

See our article on Hospital Outcomes at LinkedIn 

What is HOS?

Those of you who prefer an Adobe Acrobat document to a video, can click on this link:
Hospital Outcomes Scoring (HOS) Intro for HC Professionals.

HOS is based on reported rates for 7 causes of death and 10 types of complications compiled by the Centers for Medicare & Medicaid Services (CMS) for over 4,000 U.S. hospitals. All death and complications rates are scaled from 0% (best) to 100% (worst) with a median of 50%. After scaling, all death rates are averaged together to provide a composite death rate, which is then re-scaled from 0% to 100%.  Hospital complications rates are calculated similarly.

To try out our Interactive HOS State & Score Selector demo click on the image below:

Screenshot of HOS Database Demo

A research paper for Health Care Professionals

This document, intended for healthcare professionals, provides a description of the Hospital Outcomes Scores (HOS) methodology, the underlying data on which it is based and some alternative methodologies that were considered before the final one was chosen.  It is a compendium of author’s notes and analyses rather than a polished document.

A research paper for Health Care Professional
Hospital Outcomes Scores: Purpose, Methodology & Data Analysis

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