Company: CPESN USA Company background: CPESN® USA is America’s first clinically integrated network of pharmacy providers. With more than 3,500 community-based pharmacies operating in 48 networks across 43 states and Washington D.C., CPESN USA is the country’s fourth largest pharmacy organization and reaches 83% of the population with hand delivery to patients’ doorsteps. Over 8,500 CPESN pharmacy providers deliver patient care services that have proven to improve the health of patients and lower total cost of their care. CPESN USA incorporates innovation and technology to empower its networks of pharmacy providers to succeed in an evolving health outcomes marketplace. Contact: Monali Bhosle Title: Assistant Director, Analytics and Reporting Country: United States Award Category: Innovative Problem Solver Tell us about the business problem you were trying to solve? At CPESN USA, we utilize SAS to analyze complex data from various sources, e.g., we receive real-time care plan data from independent community pharmacies. We receive care plan data as JSON messages; hence we needed a scalable solution to extract key information from JSON, analyze and compile it into readable reports, and disseminate the reports promptly. Documenting these data accurately is extremely important since the participating pharmacies are paid based on the clinical services. Our small Analytics and Reporting team includes three data analysts; hence standardization and automation are the key to our team’s success. We needed an analytics software that would integrate seamlessly with applications such as Mirth, Python and PostgresSQL to process the ingested care plan data. How did you use SAS to solve that business problem? What products did you use and how did you use them? We utilize SAS to analyze data stored in PostgresSQL database, provide insights, create reports, and visualization for payors, partners, and purchasers. These reports are used for multiple programs to pay the pharmacies for their valuable services. To date, we have processed 8M care plans for 1.5M unique patients. SAS enables us to create these 100+ comprehensive reports on a weekly basis. Through these value-based programs, CPESN pharmacies have significantly improved patient outcomes including controlled A1C, cholesterol, and improved medication adherence.   We also used SAS for advanced analytics to build predictive models that assign patient-level opportunity scores using healthcare claims data. These opportunity scores are used by the pharmacists in their daily workflow to identify patients with elevated healthcare needs. We process ~290M claims for ~20M patients monthly in SAS EG to create these opportunity scores using SAS EG’s Schedule functionality. The code is automated is SAS and requires only 10-15 mins of analyst time every month. We primarily use Base SAS and SAS-EG to create standardized reports and visualization. SAS can be easily integrated into our web-based and other open-source applications to display and share the data innovatively. We have standardized the code in SAS that can be used across multiple programs. This is extremely valuable for our small Analytics and Reporting team. We also integrated various quality control checks into this code for the internal team. Additionally, we use SAS-EG to create hundreds of pharmacy business intelligence reports monthly in PDF format. What were the results or outcomes? We have completed or currently engaged in 250 programs with various payers (e.g., insurance companies, employers, Medicaid Managed Care Organizations, Pharmacy Benefit Managers). These programs have proven improve the health of Americans who use CPESN pharmacies. In one recent analysis by Elevance Health, CPESN pharmacies who documented care in an electronic Care Plan were responsible for lowering the overall cost of hospitalizations by 30% and lowering the overall cost of Emergency Department visits by 18%. Other programs have similar positive results.   Here is CPESN success story: https://vimeo.com/878392289 Why is this approach innovative? Seamless integration of various applications including open-source applications such as Python is the need of the hour.  These applications offer different features that are unique and more apt for the business need or the problem at hand. I have personally been using SAS for the last 15 years and amazed by the advancements made by the SAS team in their analytics software for scalable solutions. Our approach is innovative because we integrated SAS with various applications such as Mirth, Python, and PostgresSQL to ingest and extract care plan data from different technology vendors. We also used SAS's inbuilt advanced analytics functions to optimize the reporting and quality control checks. This unique data processing model helped our small team to perform efficiently and successfully fulfil the business needs.    What advice would you give to new SAS users? In the healthcare industry, analyzing data with patient identifiers requires the utmost quality standards. SAS’s industry-leading advanced analytics software with 24/7 support by experts and SAS community dashboards are extremely helpful, and all new SAS users should use these services proactively. Our team also takes advantage of SAS training videos and local SAS meet-ups to keep up with the new advancements and offerings by SAS.  ... View more

Company: CPESN USA Company background: CPESN® USA is America’s first clinically integrated network of pharmacy providers. With more than 3,500 community-based pharmacies operating in 48 networks across 43 states and Washington D.C., CPESN USA is the country’s fourth largest pharmacy organization and reaches 83% of the population with hand delivery to patients’ doorsteps. Over 8,500 CPESN pharmacy providers deliver patient care services that have proven to improve the health of patients and lower total cost of their care. CPESN USA incorporates innovation and technology to empower its networks of pharmacy providers to succeed in an evolving health outcomes marketplace. Contact: Monali Bhosle Title: Assistant Director, Analytics and Reporting Country: United States Award Category: Community Uplift Award Tell how you've used SAS to have a positive impact on your community? For our team, the most crucial application of SAS analytics software was during COVID-19 pandemic. CPESN USA was selected by the Centers for Disease Control and Prevention (CDC) as one of the Federal Retail Pharmacy Partners to administer COVID vaccines via local pharmacies. The challenge for our team was to ingest vaccine administration data that we received from 2,000 individual businesses (our CPESN pharmacies), create reports in a specific template provided by the CDC, and upload those reports to the CDC portal on daily basis. We implemented a process in SAS-EG that not only performed all these tasks but also performed quality control checks to ascertain that we are sending accurate vaccine administration data to CDC. Our rigorous processes reflected in CDC’s data validation score card where we achieved 10/10 on all data quality metrics!   The impact on the communities these pharmacies served was tremendous! Since we were able to receive and report vaccine administration data, local independent pharmacies were able to participate in the CDC’s program. Without us, they wouldn’t be able to access the federal allocation of vaccine. The program closed at the end of 2023, and our 2,000 CPESN participating pharmacies received 7M doses of vaccine and administered nearly 6.8M vaccinations. Our combined efforts earned the pharmacies $270M in additional revenue ($180K per pharmacy) and helped make a healthier patient population within the local community.   Here is the CPESN Success Story: Success Stories Showcase 2023 on Vimeo   What SAS products are you using and how are you using them? We primarily use Base SAS and SAS-EG to create standardized reports and visualization. SAS can be easily integrated into our web-based and open-source applications to access and analyze complex data. We have standardized the code in SAS that can be used across multiple programs. This is extremely valuable for our small Analytics and Reporting team. During COVID-19 pandemic, the daily reports were created in SAS-EG and were exported into the template provided by CDC. We also integrated various quality control checks into this code for the internal team.   What was your most surprising discovery about your work? I have personally been using SAS for the last 15 years and amazed by the advancements made by the SAS team in their analytics software for scalable solutions. At CPESN USA, our most surprising discovery was the ease of using SAS-EG to analyze complex data with inbuilt functions and the ability to automate/schedule the reports. We built our state-of-the-art predictive models in SAS, which are ultimately being utilized by community pharmacies across the nation to better serve their patient population. We were also surprised to know that SAS can easily integrate APIs to fetch data from external sources. We are working on implementing the API-based extraction of US Census data, that will be integrated into the pharmacy workflow to gain valuable insights about the community they serve.   In the healthcare industry, analyzing the data with patient identifiers requires the utmost standards. SAS’s industry-leading advanced analytics software with 24/7 support by experts and SAS community dashboards not only enables us to meet those standards but also helps us in creating accurate and rigorous analytics solution for our customers, which ultimately translates into improved performance of CPESN pharmacies and improved health of the patients in the communities they serve. ... View more

I am trying to flag ID as 1 if they are present in different months. The following code seems to be flagging some records correctly and others incorrectly. I am not able to understand why some of them are not getting flagged (see the rows in RED). Please advise.    data test1;  set test;  by id month;     if first.month then do;      flag = "Y";    end; run;   ID month flag 1 6 Y 1 7 Y 2 5 Y 2 6 Y 3 7   3 7 Y 4 6 Y 4 7 Y 5 6 Y 5 7 Y 6 6 Y 7 7   8 7   8 7   8 7   8 7 Y 9 6   9 7 Y 10 6   10 7   10 7 Y 11 6 Y 11 7 Y 12 6   12 7 Y 13 6 Y 13 6   13 7   14 6 Y 14 7 Y 15 6 Y 15 7 Y 16 6 Y 16 7 Y 17 5 Y 17 6   17 7 Y ... View more