Essay on Data On Predictors Of Discharge And Readmission For Hospital Inpatients

Essay on Data On Predictors Of Discharge And Readmission For Hospital Inpatients

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There is limited data on predictors of discharge and readmission for hospital inpatients. According to Rothman, Rothman, & (), “Unplanned hospital admissions are a major quality and cost issue in the US healthcare system”. About 20% of Medicare patients are readmitted to the hospital within 30 days, at an estimated cost of $17 billion per year (). Now that Medicare has begun to reduce payment to hospitals with high readmission rates, hospitals are looking for more effective ways of reducing readmissions. In order to develop new systems to address these concerns, there must be evidence in place to support to their use.
Evidence can come in a variety of forms. It can come from data, information, our own observations and vital signs, as well as patient/family member concerns. In order to be considered evidence however, the information must meet several criteria. It must be objective in that it does not house our personal opinions, it must be relevant towards the situation at hand, and timely in that the information is not out of date. It must also be transparent in that everyone has access to view the information as well as reproducible in that its results can be repeated and validated. Several hospitals are beginning to utilize a very convenient program for analyzing data and turning it into information, known as the Rothman Index.
The Rothman Index first got its start when an energetic 87-year-old woman underwent an aortic heart valve replacement in a Florida hospital. Staff members thought they were routinely observing an 87-year-old recovering after surgery. She seemed to be recovering nicely, but then became very sick very quickly. What they didn’t realize was that they were missing meaningful signs of deterioration that sadly ...

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...a dot on a vertical axis, posted hourly as new results are entered. Healthcare providers can then select multiple dots or points of data on the graph to compare the scores as well as see what contributed to that calculated score.
Many hospitals require their nurses to document a patient’s Rothman Index score at least once a shift. Not only does it give providers instance access as to how their patient is progressing, but it also highlights the areas that affect a patient’s score negatively in red so that it is known which areas to address and focus efforts on. The use of informatics systems such as this saves nurses a great deal of time by providing these early indicators and warning signs. From there we can then analyze the individual pieces of data, generate it into information and create an individualized plan of care for our patients to improve patient outcomes.

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