KAREN SLIDE 1: Good afternoon everyone and welcome to the atom Alliance Quality Innovation Network Presentation on Interpreting CMS Hospital Readmission Reports.
Dawn FitzGerald, MS, MBA Chief Executive Officer, Qsource
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Dawn FitzGerald oversees all contracts and provides stewardship with the Qsource Board of Directors. She has more than 20 years experience in healthcare quality improvement and measurement. FitzGerald’s training and work history span diverse public health fields, including developmental psychology, gerontology, HEDIS compliance, Baldrige/ISO quality management systems, disparities and analytics.
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KAREN SLIDE 6: And now it is my pleasure to introduce the CEO of Qsource, Dawn FitzGerald. Dawn has more than 20 years of experience in healthcare quality and measurement. Her training and work history span diverse public health fields including developmental psychology, gerontology, HEDIS compliance, Baldrige and ISO quality management systems, disparities and analytics. DAWN SLIDE 6: Opening Remarks: Thank you for taking the time to join us. We appreciate all you do to improve quality and achieve better outcomes in health and healthcare and at lower costs for the patients and communities we serve.
Introduction to the atom Alliance
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Multi-state alliance for powerful change composed of three nonprofit, healthcare QI consulting companies.
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DAWN SLIDE 7: Introduce the atom Alliance: As you may know, atom Alliance is a five-year, five-state initiative to ignite powerful and sustainable change in healthcare quality. We welcome participants from AL, IN, KY, MS and TN. I will now introduce our speakers today, Lesley Hays and Melanie Fite:
Melanie Fite, BBA, MBA Programmer/Analyst
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Melanie Fite provides analytical support and organizes data for reporting while collaborating with the atom Alliance team members. Melanie has over 30 years of experience in medical practice operations, compliance and HIPAA privacy and security. She has expertise in radiology information systems, data analysis, report writing and presenting data results. Melanie holds a master’s degree in business administration.
How do I know that I have received a report?
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• If you are a registered QualityNet user, you should receive the following e-mail notification:
• If you are not a registered QualityNet user, please see your QIO Liaison
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First I’m going to go over a couple of things about the report delivery.
Downloading the Reports via QualityNet• Website: https://www.qualitynet.org/
• Click on “Login” to enter the QualityNet Portal. • Log in to your account.
• Click on “Secure File Transfer” at the top.
• Locate the “AutoRoute_inbox” and click on it.
• The hospital report file(s) should be in the inbox if your account was active at the time of the file upload.
• Highlight it and click “Download.”
• Select “Save” and it will want you to select a location on your computer (Desktop, etc.) where you want the file to be saved to.
• Select a location, then click “Save” and the file should then be downloaded to that location.
Objectives• During this webinar you will learn how to:
• Understand and interpret your CMS Readmissions Report• Gain a better understanding and evaluate the complex nature
of hospital readmissions• Review analysis of contributing factors from Medicare Part
A claims data
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In this presentation, I’ll be going through the report interpretation in detail. During this webinar you will learn how to: Understand and interpret your CMS Readmissions Report Gain a better understanding and evaluate the complex nature of hospital readmissions Review analysis of contributing factors from Medicare Part A claims data
Page A1Monthly Discharges and Readmissions
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Just a few things about the report before I go over this first chart. This consolidated report contained information obtained from Medicare Part A claims. Monthly discharges are from your hospital, the index hospital. Readmission rate is calculated by using the total number of readmissions from all facilities. Pages A -1 thru A-6 (the first 6 pages of the report) reflect the monthly number of discharges and associated readmissions data for the past 12 months of data. Page A-1 reflects monthly discharges from your facility, total readmission count is followed by readmissions to your facility in parenthesis. For example, in the red circle on the left, there are 353 all cause discharges, 81 total readmissions, with 44 readmissions from the same hospital. Discharges by diagnosis are calculated using the patient’s primary diagnosis code. We chose 6 primary diagnosis codes to analyze. They are AMI (Acute Myocardial Infarction), HTF (Heart Failure), PNE (Pneumonia) VTE (Venous thromboembolism) and COPD (Chronic Obstructive Pulmonary� Disease). The primary diagnosis code analysis follows the same structure, discharges, all readmissions/same hospital readmissions and the readmission rate. There may be some blanks in this table, as noted in the red circle on the right. This is not due to lack of data. This means that there were zero discharges for the primary diagnosis code, therefore zero readmissions and no readmission rate was able to be calculated.
Page A1 (cont.)
Readmission to Different/Same Hospital
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In the bar chart, readmissions to/from your facility are noted in blue. Readmissions to another facility associated with your discharges are noted in green.
Page A2Hospital Ranking
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Your hospital’s 30-Day all cause readmission rate for each month is ranked relative to all hospital providers in the state. The hospital’s rank is determined by ordering facilities from lowest to highest 30-day readmission rates, and rank is established relative to the total number of providers in the state. The lower the 30-day readmission rate, the better the state rank is. The means that if you have a state ranking of 1, you have the lowest 30-Day all cause readmission rate in the state.
Pages A3-A6Monthly Readmission Rates (for all-cause and select primary diagnoses)
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On pages A3-A6, all cause and each of the 6 primary diagnoses readmission rates are plotted by month to show rates over time and to compare them with the statewide averages for the same time periods. In the red circle, something I would like to point out, is that the data points can fluctuate tremendously when the hospital has very small denominators (discharges). For example, inside the red circle, we see that month 10 has 0% readmission rate. This could be 2 discharges and 0 readmissions.) In month 12, discharges could also be 2 and readmissions 1, which gives your hospital a 50% readmission rate for that month. 2015M10, 2 discharges/0 readmissions, 2015M12 could be 2 discharges and 1 readmission. (jumps to 50%)
Pages B1-B6
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Pages B-1 – B-6 are similar in all respects to pages A-1 thru A-6, except the data in Pages B-1 – B-6 reflects the quarterly number of discharges and associated readmissions (rather than monthly).
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Pages B1 – B6 contain the same analysis and are similar in all respects to the first 6 pages of the reports, however, B1-B6 reflects your hospital’s QUARTERLY , rather than monthly number of discharges and associated readmissions. The quarterly reports contains 3 years of data.
Page CReadmission Rates for the Most Recent Quarter (all-cause and select primary diagnoses compared to the state average)
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The chart and graphs on Page C shows discharges, readmissions and 30-Day readmission rates for all cause and the selected 6 primary diagnoses as compared to the state-wide average.
Page D
Discharges To and Readmissions From (by discharge destination)
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Page D represents your hospital’s discharges by discharge destination (using Part A claims indicated discharge destination) for the most recent quarter. % of Discharges – the percent of total discharges using the associated discharge code. Readmissions – the number of readmissions occurring among those discharged using the associated discharge code. % of Readmissions – the percent of total readmissions using the associated discharge code. Readmission rate – the percentage of readmissions in relation to the total number of discharges associated with the associated discharge code.
Page D (cont.)
Frequency of Beneficiaries with 30-Day Readmissions
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The frequency of beneficiaries with 30-day readmissions reflects your hospital’s count of readmissions categorized by beneficiary utilization. For example, in the red circle, we can see that one beneficiary was readmitted 7 times within 30 days. Bene% - percentage of beneficiaries as a total of beneficiary count Readm = Beneficiary count x readmission frequency Readm Cum = Beneficiary count x readmission total
Page EQuarterly Mortality Rates
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Page E represents a chart and corresponding graph depicting mortality rates over time compared to the statewide rates. Mortality rate is defined as deaths in the 30 days after admission date as the numerator and # of unique beneficiary discharges as the denominator This is Medicare only data and the death rate will be higher. Hospitals should have a lower rate. The quality innovation networks (QINs) have access to every Medicare beneficiary’s date of death through CMS, which gets the date from the death certificate. Hospitals usually don’t have access to every Medicare beneficiary’s date of death unless they follow them after discharge.
Page FAverage CMS Reimbursement (by diagnosis compared to the state average)
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This chart shows the average CMS reimbursement for all admissions and the select clinical conditions (primary diagnosis) over time and the state-wide average as well.
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How can this data be helpful to your hospital?• Are there patterns in the data that might suggest opportunities to improve
your hospital’s identification of appropriate readmissions reduction efforts. For example, is your state rank significantly higher than the rest of the hospitals statewide (Page A-2)?
• Are there patterns of higher readmissions within a particular clinical condition that might warrant targeting a particular hospital unit for enhanced discharge planning (Page A-1)?
• Are the results due primarily to larger than expected readmissions from nursing homes (Page D)?
• Are results due to a small number of beneficiaries that are frequent hospital utilizers (Page D)?
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How can this data be helpful to your hospital? Are there patterns in the data that might suggest opportunities to improve your hospital’s identification of appropriate readmissions reduction efforts. For example, is your state rank significantly higher than the rest of the hospitals statewide (Page A-2)? Are there patterns of higher readmissions within a particular clinical condition that might warrant targeting a particular hospital unit for enhanced discharge planning (Page A-1)? Are the results due primarily to larger than expected readmissions from nursing homes (Page D)? Are results due to a small number of beneficiaries that are frequent hospital utilizers (Page D)? After reviewing the data, you can conduct internal confirmatory analysis and develop appropriate interventions.
What data can atom provide that you don’t have access to now?• Readmissions to other hospitals• State ranking by readmission rates• Discharge to and readmissions from different discharge settings• Data that supports your efforts to better understand and
evaluate the complex nature of hospital readmissions.
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What data can atom provide that you don’t have access to now? Readmissions to other hospitals State ranking by readmission rates Discharge to and readmissions from different discharge settings Data that supports your efforts to better understand and evaluate the complex nature of hospital readmissions.
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Thank you for joining us!
• Please visit us at www.atomAlliance.org
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Thank you very much for joining us today and please remember that atom Alliance staff is here to help you.
On-Demand Learning (ODL)Our On-Demand Learning (ODL) area on www.atomAlliance.org allows you to participate in archived events when it is most convenient.
Live events are usually posted as an ODL opportunity 10 days after the live session.
Requirements to participate?
• Review the list of ODL opportunities
• Click “Go”
• Submit your name and other informationfor documentation
• Click “Submit” and you’ll have accessto the ODL of your choice.
• Share the opportunity with your peers!
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The recording and transcript will be posted to the atomAlliance.org website, in the on-demand learning section. Our On-Demand Learning area on www.atomalliance.org allows you to participate in archived events when it is most convenient.
This material was prepared by atom Alliance, the Quality Innovation Network-QualityImprovement Organization (QIN-QIO), coordinated by Qsource for Tennessee, Kentucky,Indiana, Mississippi and Alabama under a contract with the CENTERS FOR MEDICARE &MEDICAID SERVICES (CMS), a federal agency of the U.S. Department of Health andHuman Services. Content does not necessarily reflect CMS policy. 17.HIIN.04.003
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We look forward to seeing you in other virtual places as well—please connect with us on Facebook, Twitter, Linkedin or Pinterest! Thank you again and have a wonderful afternoon.
