Statin Therapy Case Study – AssignmentResearch Prompt:Electronic Clinical Quality Measures (eCQMs) are standards of practice used by the Centers for Medicare & Medicaid Services (CMS) to measure the...

1 answer below »



Statin Therapy Case Study – Assignment




Research Prompt:




Electronic Clinical Quality Measures (eCQMs) are standards of practice used by the Centers for Medicare & Medicaid Services (CMS) to measure the quality of healthcare provided by an institution. Criteria for meeting these standards are based upon electronically extracted data from the electronic health records (eHR) or other health information technology. Having the ability to quickly extract this data from your institution's eHR affords the ability to determine opportunities for quality improvement. As of 2022, there are 48 EC eCQMs covering a broad number of areas of practice.







You are interested in examining the 2022 eCQMs concerning use of statin therapy for the prevention and treatment of cardiovascular disease (CMS347v5). Your particular interest is in determining the prevalence of use of statins for the cardiovascular patients in your hospital. This standard has been determined based upon The American College of Cardiology (ACC)/American Heart Association (AHA)/Multi-society (MS) Guideline recommendations (2019) and are intended to provide a strong evidence-based foundation for the treatment of blood cholesterol for the primary and secondary prevention and treatment of patients with atherosclerotic cardiovascular disease (ASCVD) in patients of all ages.

















https://ecqi.healthit.gov/ecqm/ec/2022/cms347v5







Referring to the specifications for CMS347v5, you know that you will need to find information for the following types of patients.








Percentage of the following patients - all considered at high risk of cardiovascular events - who were prescribed or were on statin therapy during the measurement period:








*All patients who were previously diagnosed with or currently have an active diagnosis of clinical atherosclerotic cardiovascular disease (ASCVD), including an ASCVD procedure; OR








*Patients aged >= 20 years who have ever had a low-density lipoprotein cholesterol (LDL-C) level >= 190 mg/dL or were previously diagnosed with or currently have an active diagnosis of familial hypercholesterolemia; OR








*Patients aged 40-75 years with a diagnosis of diabetes





Research approach:







·





For right now, however, we are only seeking out the proportion of previously diagnosed or currently active ASCVD patients in the NeLL database, who were prescribed statin therapy during a two-year period, 2017-2019. This is Population 1 in the measure description.







·





Your approach will be to take a sample of 1000 ASCVD patient encounters to see about their statin therapy prevalence.







References:







·





Statin Therapy for the Prevention and Treatment of Cardiovascular Disease. Specifications. CMS347v5.html. ECQI ResourceCenter 2022.

https://ecqi.healthit.gov/ecqm/ec/2022/cms347v5







·











2019 ACC/AHA Guideline on the Primary Prevention of Cardiovascular Disease: A Report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines. J Am Coll Cardiol 2019;March 17: [Epub ahead of print: https://www.acc.org/latest-in-cardiology/ten-points-to-remember/2019/03/07/16/00/2019-acc-aha-guideline-on-primary-prevention-gl-prevention].




















Process Steps:







To create the NeLL datasets required to calculate the measure, please follow the instructions below. Please be aware that NeLL is a dynamic database and it is subject to change periodically. The data you download might not match the data that’s in the sample dataset provided to you.




























A.








To run Query:

















·








Go to Project NeLL site ->


https://projectnell.emory.edu/NELL_Student and log in using your email that you used to register for the site and your password.











·








Click "Try it Now"











·








In the Query Setup pop-up window choose all years of data (2017 – 2019)











·








Select Diagnosis button to search by ICD10 code for ASCVD (Atherosclerotic Cardiovascular Disease)











·








Select the option for “Simple” diagnosis and specify that you do not know the code to search for.











·








Enter ICD10 Code (i.e. "Atherosclerotic heart disease without angina pectoris" or "i25.10")











·








For Diagnosis Type, select “All Diagnosis Types” from the dropdown menu.











·








Choose Start Query




















B.








To create dataset:

















1.








You should receive Preliminary Results of thousands of matching patients and encounters, but for the purposes of this case study, you’ll only be able to download data for ~1,000 encounters.














a.














How many patients did you find? How many encounters?




















2.








In Preliminary Results window, select the Orders table in the drop down list (which will automatically include Diagnosis table based on the query)











3.








Choose Confirm











4.








Three boxes will appear in bottom right confirming the query is running











5.








Results window pops up with a limited sample of results











6.








Take a look at the Graphical Summary, Frequency Summary and Table View to get familiar with the query variables.














a.














Make a screen shot of the graphical summary




















7.








Double check query details (consider copying this for the data evaluation!)











8.








In the downloads tab, select Orders in the tables list.











9.








Under the “choose fields to download” section, select the “Select All” button











10.








Move the slider bar for number of encounters all the way to the end














a.














How many encounters was this?




















11.








Click on the download data button and the csv file downloads to your computer. Save the file in .xls or .xlsx format.




















C.








Data Analysis Steps:

















1.








Using the Excel app, open the Orders.csv file that was downloaded to your computer.











2.








An initial scan should show you that the file has one sheet with thousands of rows of data and a header row.











a.














How many rows of data do you have?











3.








Take a look at the data file and try to explore and understand the

columns


of data downloaded.









Formatting Encounter ID:








4.








Select the encounter_id column (Column B), right click and select “Format Cells”








5.








Select “Number” under “Category”, “0” for “Decimal Places” and select OK.








Adding Filters to Columns:








6.








Select any value in row 1 (column headers), go to Home > Sort & Filter, and select Filter to see the little drop arrows appear next to each column header.








Creating a Statin Orders sub-table (Sheet 2)








7.








Go to the Order column (column J), click on the filter drop down and select “Text Filters” > “Contains..”








8.








In the first box, enter the word “statin” and click ok.








9.








The sheet is now filtered and displays only the rows of data where order contains the word “statin”.











a.














How many rows of data do you have?











10.








Select these rows, copy and paste “values” in a new sheet








11.








Sheet 2 (Orders – Statin) has been created








Creating a pivot table to get results








12.








In sheet 2, Go to the “Insert” menu and select “Pivot Table”








13.








For range, select columns B through Q and select the option for the table to be placed in a “New Worksheet”.








14.








A new sheet opens up with the pivot table menu








15.








In the pivot table menu, select “order” and it’ll automatically show up in the rows box at the bottom. All the “statin” names will show up in the excel sheet (1 per row).








16.








Click on the list and uncheck the rows with “nystatin” because it is not a medication that falls under statin therapy.








17.








Next select encounter_id and it shows up in the “Values” box.








18.








Click on the arrow next to “sum of encounter id”, select “Value Field Settings” and choose “Count” to summarize the value field by.








19.








Click ok.








20.








Back in the pivot table menu, select “order status” and move it to the “Filters” box








21.








In the main excel sheet, select only “completed” under order status to exclude orders that were discontinued or not even fulfilled.








22.








Your table is now ready with a count of encounters for statin medications.











a.














Submit your pivot table.





























D.








For the eCQM analysis, the result is as follows:

















For the sample dataset provided, out of a total of 1.

How Many


encounters, statin medication orders were completed for 2.

How Many

encounters (3.

What Percent


of encounters).


















Additional Opportunities for Analysis:








Research indicates that certain populations are far less likely to receive guideline-recommended statin therapy than others. A retrospective study of the National Health and Nutrition Examination Survey found that Black and Hispanic race or ethnicity, low income, lack of health insurance coverage, poor health care access, young age, and female gender are predictors of lower statin utilization (Gu et al., 2018). In particular, there is extensive evidence that women are far less likely than men to be prescribed guideline-recommended statin therapy (Zhang et al., 2016; Nanna et al., 2019b), despite research showing that female patients with cardiovascular disease derive the same or greater benefit from statin therapy as male patients with cardiovascular disease (Puri et al., 2014).








·








Demographic analysis could be performed to explore the trends of statin therapy adherence in the sample NeLL population.











SUBMIT to Canvas from the instructions above:











B.1.a.





How many patients did you find? How many encounters?














B.6.a. Make a screen shot of the graphical summary














B.10.a. How many encounters was this?














C.2.a.










How many rows of data do you have?














C.9.a. How many rows of data do you have?














C.22.a. Submit your pivot table.











D. The final (for Population 1) eCQM answers: For the sample dataset provided, out of a total of

1.


How Many encounters, statin medication orders were completed for

2.


How Many encounters


(3.


What Percent


of encounters).

































































































































Statin Therapy Case Study – Assignment Research Prompt: Electronic Clinical Quality Measures (eCQMs) are standards of practice used by the Centers for Medicare & Medicaid Services (CMS) to measure the quality of healthcare provided by an institution. Criteria for meeting these standards are based upon electronically extracted data from the electronic health records (eHR) or other health information technology. Having the ability to quickly extract this data from your institution's eHR affords the ability to determine opportunities for quality improvement. As of 2022, there are 48 EC eCQMs covering a broad number of areas of practice. You are interested in examining the 2022 eCQMs concerning use of statin therapy for the prevention and treatment of cardiovascular disease (CMS347v5). Your particular interest is in determining the prevalence of use of statins for the cardiovascular patients in your hospital. This standard has been determined based upon The American College of Cardiology (ACC)/American Heart Association (AHA)/Multi-society (MS) Guideline recommendations (2019) and are intended to provide a strong evidence-based foundation for the treatment of blood cholesterol for the primary and secondary prevention and treatment of patients with atherosclerotic cardiovascular disease (ASCVD) in patients of all ages. https://ecqi.healthit.gov/ecqm/ec/2022/cms347v5 Referring to the specifications for CMS347v5, you know that you will need to find information for the following types of patients. Percentage of the following patients - all considered at high risk of cardiovascular events - who were prescribed or were on statin therapy during the measurement period: *All patients who were previously diagnosed with or currently have an active diagnosis of clinical atherosclerotic cardiovascular disease (ASCVD), including an ASCVD procedure; OR *Patients aged >= 20 years who have ever had a low-density lipoprotein cholesterol (LDL-C) level >= 190 mg/dL or were previously diagnosed with or currently have an active diagnosis of familial hypercholesterolemia; OR *Patients aged 40-75 years with a diagnosis of diabetes Research approach: · For right now, however, we are only seeking out the proportion of previously diagnosed or currently active ASCVD patients in the NeLL database, who were prescribed statin therapy during a two-year period, 2017-2019. This is Population 1 in the measure description. · Your approach will be to take a sample of 1000 ASCVD patient encounters to see about their statin therapy prevalence. References: · Statin Therapy for the Prevention and Treatment of Cardiovascular Disease. Specifications. CMS347v5.html. ECQI ResourceCenter 2022. https://ecqi.healthit.gov/ecqm/ec/2022/cms347v5 · 2019 ACC/AHA Guideline on the Primary Prevention of Cardiovascular Disease: A Report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines. J Am Coll Cardiol 2019;March 17: [Epub ahead of print: https://www.acc.org/latest-in-cardiology/ten-points-to-remember/2019/03/07/16/00/2019-acc-aha-guideline-on-primary-prevention-gl-prevention]. Process Steps: To create the NeLL datasets required to calculate the measure, please follow the instructions below. Please be aware that NeLL is a dynamic database and it is subject to change periodically. The data you download might not match the data that’s in the sample dataset provided to you. A. To run Query: · Go to Project NeLL site ->  https://projectnell.emory.edu/NELL_Student and log in using your email that you used to register for the site and your password. · Click "Try it Now" · In the Query Setup pop-up window choose all years of data (2017 – 2019) · Select Diagnosis button to search by ICD10 code for ASCVD (Atherosclerotic Cardiovascular Disease) · Select the option for “Simple” diagnosis and specify that you do not know the code to search for. · Enter ICD10 Code (i.e. "Atherosclerotic heart disease without angina pectoris" or "i25.10") · For Diagnosis Type, select “All Diagnosis Types” from the dropdown menu. · Choose Start Query B. To create dataset: 1. You should receive Preliminary Results of thousands of matching patients and encounters, but for the purposes of this case study, you’ll only be able to download data for ~1,000 encounters. a. How many patients did you find? How many encounters? 2. In Preliminary Results window, select the Orders table in the drop down list (which will automatically include Diagnosis table based on the query) 3. Choose Confirm 4. Three boxes will appear in bottom right confirming the query is running 5. Results window pops up with a limited sample of results 6. Take a look at the Graphical Summary, Frequency Summary and Table View to get familiar with the query variables. a. Make a screen shot of the graphical summary 7. Double check query details (consider copying this for the data evaluation!) 8. In the downloads tab, select Orders in the tables list. 9. Under the “choose fields to download” section, select the “Select All” button 10. Move the slider bar for number of encounters all the way to the end a. How many encounters was this? 11. Click on the download data button and the csv file downloads to your computer. Save the file in .xls or .xlsx format. C. Data Analysis Steps: 1. Using the Excel app, open the Orders.csv file that was downloaded to your computer. 2. An initial scan should show you that the file has one sheet with thousands of rows of data and a header row. a. How many rows of data do you have? 3. Take a look at the data file and try to explore and understand the columns of data downloaded. Formatting Encounter ID: 4. Select the encounter_id column (Column B), right click and select “Format Cells” 5. Select “Number” under “Category”, “0” for “Decimal Places” and select OK. Adding Filters to Columns: 6. Select any value in row 1 (column headers), go to Home > Sort & Filter, and select Filter to see the little drop arrows appear next to each column header. Creating a Statin Orders sub-table (Sheet 2) 7. Go to the Order column (column J), click on the filter drop down and select “Text Filters” > “Contains..” 8. In the first box, enter the word “statin” and click ok. 9. The sheet is now filtered and displays only the rows of data where order contains the word “statin”. a. How many rows of data do you have? 10. Select these rows, copy and paste “values” in a new sheet 11. Sheet 2 (Orders – Statin) has been created Creating a pivot table to get results 12. In sheet 2, Go to the “Insert” menu and select “Pivot Table” 13. For range, select columns B through Q and select the option for the table to be placed in a “New Worksheet”. 14. A new sheet opens up with the pivot table menu 15. In the pivot table menu, select “order” and it’ll automatically show up in the rows box at the bottom. All the “statin” names will show up in the excel sheet (1 per row). 16. Click on the list and uncheck the rows with “nystatin” because it is not a medication that falls under statin therapy. 17. Next select encounter_id and it shows up in the “Values” box. 18. Click on the arrow next to “sum of encounter id”, select “Value Field Settings” and choose “Count” to summarize the value field by. 19. Click ok. 20. Back in the pivot table menu, select “order status” and move it to the “Filters” box 21. In the main excel sheet, select only “completed” under order status to exclude orders that were discontinued or not even fulfilled. 22. Your table is now ready with a count of encounters for statin medications. a. Submit your pivot table. D. For the eCQM analysis, the result is as follows: For the sample dataset provided, out of a total of 1. How Many encounters, statin medication orders were completed for 2. How Many encounters (3. What Percent of encounters). Additional Opportunities for Analysis: Research indicates that certain populations are far less likely to receive guideline-recommended statin therapy than others. A retrospective study of the National Health and Nutrition Examination Survey found that Black and Hispanic race or ethnicity, low income, lack of health insurance coverage, poor health care access, young age, and female gender are predictors of lower statin utilization (Gu et al., 2018). In particular, there is extensive evidence that women are far less likely than men to be prescribed guideline-recommended statin therapy (Zhang et al., 2016; Nanna et al., 2019b), despite research showing that female patients with cardiovascular disease derive the same or greater benefit from statin therapy as male patients with cardiovascular disease (Puri et al., 2014). · Demographic analysis could be performed to explore the trends of statin therapy adherence in the sample NeLL population. SUBMIT B.1.a. How many patients did you find? How many encounters? B.6.a. Make a screen shot of the graphical summary B.10.a. How many encounters was this? C.2.a. How many rows of data do you have? C.9.a. How many rows of data do you have? C.22.a. Submit your pivot table. D. The final (for Population 1) eCQM answers: For the sample dataset provided, out of a total of 1. How Many encounters, statin medication orders were completed for 2. How Many encounters (3. What Percent of encounters). 1
Answered 1 days AfterOct 13, 2023

Answer To: Statin Therapy Case Study – AssignmentResearch Prompt:Electronic Clinical Quality Measures (eCQMs)...

Baljit answered on Oct 15 2023
29 Votes
C.2.a. How many rows of data do you have?
Answer:- There are 41614 rows in the data.
C.9.a. How
many rows of data do you have?
Answer:- There are 419 rows in the data after applying the filter.
C.22.a. Submit your pivot table.
Or
    order_status
    Completed
    
    
    Row Labels
    Count of...
SOLUTION.PDF

Answer To This Question Is Available To Download

Related Questions & Answers

More Questions »

Submit New Assignment

Copy and Paste Your Assignment Here