Hospital Mortality

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Из курса от партнера Johns Hopkins University

Measuring the Success of a Patient Safety or Quality Improvement Project (Patient Safety VI)

16 оценки

Johns Hopkins University

Measuring the Success of a Patient Safety or Quality Improvement Project (Patient Safety VI)

16 оценки

Курс 6 из 7 — Specialization Patient Safety

How will you know if your patient safety and quality project is meeting its objectives? Peter Drucker once said “What gets measured, gets managed.” In this course, students will learn why measurement is critical to quality improvement work. Equally important, they will learn which data sources provide the most meaningful information and tools for how and where to locate them. Finally, students will learn how to interpret data from their patient safety and quality projects to guide and modify them during implementation to maximize their chances of making a difference for patients.

Из урока

Public Reporting of Performance Measures

In this module, learners will gain knowledge of the primary audiences for publicly reported performance measure sand some of the key measures that are currently reported. Learners will be exposed to some of the key websites that publicly report performance data and hear from a health system leader about some of the benefits and challenges of having a hospital’s quality and safety performance publicly available.

History, Objectives, & Key Examples6:38

Evidence of Impact & Maximizing the Benefits10:14

Hospital Readmissions4:11

Hospital Mortality3:38

Hospital Compare6:11

Interview with Renee Demski5:49

Exploring the Leapfrog Group4:27

Exploring My NHS3:33

Познакомьтесь с преподавателями

Matt Austin
Assistant Professor
Anesthesiology and Critical Care Medicine

Another example of a measure that is publicly reported is Hospital Mortality Rates.

Before we talk about measures of hospital mortality,

I did want to provide you with some data or statistics

about trends here in the United States with in-patient mortality.

In the year 2000,

2.5 per 100 persons hospitalized actually died in the hospital.

That rate was reduced to 2.2 in 2005,

and in 2010, we've actually reduce that rate to 2.0.

Represents a 20 percent reduction

between 2000 and 2010 and those results are statistically significant.

So, we've seen some good improvement in terms of patients surviving their hospital stay.

I've also provided some details around specific conditions and procedures or diagnoses.

As you'll see for almost every diagnoses,

these results show that mortality rates have actually decreased

significantly between 2000 and 2010 in U.S. hospitals.

So, why would it be interesting in measuring mortality rates?

Well, first of all,

it's a very objective measure,

either the patient survived their hospital stay,

or unfortunately, they may have died during their hospital stay.

But it's a very clear outcome,

their survival or death.

It's very easy to track.

This information is collected in administrative data records.

And death rates actually do provide us with information about important aspects of

hospital care that can affect

patients outcomes such as prevention and response to complications,

the hospital's emphasis on patient safety,

and the timeliness of care to the patient.

The Centers for Medicare and Medicaid Services, or CMS,

has developed a number of mortality measures

for medical conditions and surgical procedures,

and all of these are publicly reported on CMS's Hospital Compare.

These include things such as COPD 30-day mortality rates,

AMI 30-day mortality rates,

heart failure 30-day mortality rates, pneumonia, stroke,

and 30-day mortality rates after coronary artery bypass graft surgery.

These data are reported on Hospital Compare using a number of mechanisms.

One is to actually show the hospital's performance relative to the national mean or

average and whether that

hospital's value is within the confidence interval that one would expect.

If it is within the confidence interval,

it is shaded yellow.

If the hospital's performance is better than the confidence interval, it would be green.

And if it's worse, it would be in red.

This particular example, looking for mortality rates for COPD patients,

Johns Hopkins hospitals' performance is within the expected mortality range.

We actually have a number of challenges with mortality measures.

Similar to readmission measures,

we lack a single national standardized risk adjusted measure.

How much should we weigh the hospital effect?

Should we look at a 90-day mortality window, 30-day,

seven-day, or possibly even just in hospital?

So, we have continued conversations about,

what is the best way to measure mortality?

And what is the right group to include and exclude?

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