Overview
The average length of stay metrics in Marketscape for a hospice are calculated from all discharge claims submitted by the hospice during the standard one year reporting period. We count the number of days from the time of patient admission to discharge.
This metric can be found on the Explore page for facilities (shown above) or on the analyze page for a selected facility.
More detail
The index event would be a discharge claim submitted during the most recent one year reporting period. The counting period for counting the length of stay would be up to three years. This means that the longest length of stay would be from a patient who was discharged on the last day of the current data set but who was admitted on or before the first day three years back from the end of the current reporting period. This maximum is 1095 days (or 1096 if there is a leap year.) We do not count back past the three year reference period, so any patients who were in hospice care care prior to that time will receive a count of the maximum possible days within the reference period.
Example:
The skinny red rectangles represent the hospice stays. As long as the discharge (D/C) occurs during the one year reporting period, we count back up to three years to get a length of stay in days.
The yellow represents our standard reporting period, the period from which we gather our index events; in this case, hospice discharges. This one-year period aligns with the end of our current data set. That is, if the most recent data set end with 2019-Q3, this reporting period ends in the same quarter.
The blue is our counting period - we go back three years from the end of the reporting period to count the full length of stay for patients discharged during the reporting period. To be counted, start of care must be in this period. As you can see from the image, a stay can begin any time within the entire 3 year period, but must end in the one-year reporting period.
Length of stay calculations in the Marketscape include only patient stays where the patient has been discharged. As a result, length of stay metrics might be shorter in Marketscape than what you will find in other data references. For example: a patient who has been in post-acute care for over a year, but not discharged, would not appear in our length of stay metrics even though that could extend the length of stay average.
There are many different types of ALOS metrics. We calculate these metrics the same way, but the patient population used for each is different. For example, ALOS for a hospice would be based on ALL patients discharged from the hospice during the reporting period. ALOS for a facility; a SNF, or a hospital, would be calculated from the facility's population of patients. This is also true for physicians where we have two different ALOS metrics based on different patient populations for the selected physician. (See ALOS for Physicians, below.)
Trended ALOS
In Marketscape for Hospice, there are two tables of trended ALOS metrics:
For a selected facility
On the Analyze page for facilities there is a table named, Hospice Length of Stay Post-Discharge. These are length of stay metrics for hospice patients who were discharged from the selected facility and admitted to hospice within 30 days. This is a metric that limits length of stay metrics to the selected facility with relation to all hospices.
For a selected hospice
On the Analyze page for hospices, there is a table named, Trended LOS. This is a complementary view to the facility related metric. In this table we include length of stay metrics for the selected hospice for all patients discharges. This table includes mean averages and a median averages for four quarters along with county and State benchmarks.
These tables include four quarters of length of stay data that we calculate in the same way as the annual metric, with one exception. The reporting period from which we look for home health discharges is a quarter rather than from the entire year.
To get the trended quarters, we look at each quarter in our one year reporting period for discharges within the quarter. We then look back through a three year counting period that aligns with the end of the quarter. As you can see from the image below, we offset the beginning of the counting period to make the quarterly metrics comparable.
The above image only shows two quarters. The earlier two quarters will offset the three year period even further.
ALOS for Physicians
There are two ALOS metrics for Physicians. Please compare:
On the Explore page
In the Physicians table on the Explore page, the column ALOS contains the Average Length of Stay metrics for each physician
Please note that the ALOS for our selected Physician is 21 days.
Now let's click on the physician's name. This will take us to the Analyze page for our selected physician.
On the Analyze Page
Hmmmm... Now our Average Length of Stay for that physician is 28.82 days.
What is the difference?
The patient populations we use to calculate each metric are different. This produces metrics that tell a different story about patient care and provider performance.
In Sum
The reporting period and the way we calculate the metric are the same. The differences that separate the patient populations are the index event, and the calculation period.
Page/Parameter | Index Event | Calculation Period |
Explore Page ALOS | Patient discharge from hospice (during the reporting period) | 3 Months Prior - patient was seen by the selected physician within three months of admission to hospice stay |
Analyze Page ALOS | Death of the patient (during the reporting period) | 6 month period - physician saw the patient within six months of death |
Now, the details
On the Explore page, the metrics are designed to answer the question, For the selected provider, what is the potential for a post-acute referral? In sum, the Explore page is about referral potential. To do this, we limit the patient population to show close proximity between the provider and post-acute care. For a physician, we only count a patient as a hospice patient for a selected physician if the physician treated the patient within three months of post-acute admission. This increases the likelihood, for the patients counted, that the physician could have engaged the patient regarding post-acute care.
In contrast, if a physician treated a patient in January and the patient entered post-acute care in October, we would not count that patient on the Explore page because we can't infer a strong connection between the two events.
This is the limitation on the ALOS metric on the Explore page. We only include patients in the ALOS metric if they were discharged from hospice care during the reporting period, and they had been admitted to that hospice stay within three months of being treated by the selected physician.
The Analyze page has a slightly different focus, and the metrics are tailored to that purpose. The Analyze page, as the name suggests, is designed to provide a deeper and more thorough of your selected provider so that you can 1) compare the provider to other similar providers, and 2) so you can strategize how to engage with the provider. For this reason, some metrics are calculated differently to be more consistent for comparison.
For hospice metrics on the Analyze page, in general, and for the ALOS metric, in particular, we focus on mortalities rather than hospice discharge. It is possible that a patient discharged from hospice care might have not even been appropriate for hospice. If the patient died, we can make a relatively strong case that hospice care was appropriate.
That is why, on the Analyze page, the ALOS metric is calculated for patients who died within the reporting period who were seen by the physician within 6 months of death.
And that is why the two metrics are different on the two different pages.
In addition, expanding the time period for the Analyze page ALOS metric increases the size of the patient population. This will lead to fewer "<11" counts which provides a larger percentage of useful percentages of physicians on the Analyze page. This provides you with more available metrics when you compare providers. To be mathy, you always get a more accurate percentage when you increase the starting population for your calculations.
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