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Streamlining Data Requests with UCMC Analytics Core

Learn how UCMC Analytics Core improves data request processes, ensuring efficiency and transparency for all stakeholders. Request data easily through ACReS for quality improvement, operational, billing, and research purposes within UCM. Follow a structured process to submit, review, and receive data with the best-suited analytics team.

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Streamlining Data Requests with UCMC Analytics Core

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  1. Disclaimer and Permissions • This educational activity is being presented without the provision of commercial support and without bias or conflict of interest from the planners and presenters. • The purpose of these materials is to provide insight into the variety of data sources, as well as the recommended process for obtaining data from the Analytics Core within UCMC • These materials are not meant to provide an exhaustive analysis of all data sources and means for requesting data within the institution • It is not permissible to share these materials outside UCMC UCMC DATA |

  2. How do I request data? UCMC DATA

  3. Recap Historically: Data pulls for quality improvement, operational, billing and research purposes were traditionally requested to individuals across the institution without standardization or tracking This approach led to imbalanced work, nonstandard approaches to fulfilling data requests, and inefficiencies for both analysts and data requesters UCMC DATA

  4. Request Request Request Request Request analyst Request analyst analyst analyst analyst analyst UCMC DATA

  5. Recap Historically: Data pulls for quality improvement, operational, billing and research purposes were traditionally requested to individuals across the institution without standardization or tracking This approach led to imbalanced work, nonstandard approaches to fulfilling data requests, and inefficiencies for both analysts and data requesters Solution: Analytics Core was developed to streamline the data request process and allow for appropriate allocation of institutional resources to process these requests, ultimately improving the experience of both data teams and data requesters. UCMC DATA

  6. Request Request Request Request Request Request Unified intake and review analyst UCMC DATA

  7. Analytics Core • Analytics Core is comprised of analytics leads from both technical and business teams spanning UCM and BSD • Analytics Core meets weekly to review all data requests submitted via ACReS (Analytics Core Request System) to reduce duplication of resources, improve data quality, and provide a platform for communication and transparency UCMC DATA

  8. Membership Legend: Quality CBIS Operations Business Finance Research UCMC DATA

  9. How Do I Request Data? ACReS Analytics Core Request System https://cri-app02.bsd.uchicago.edu/ACReS UCMC DATA

  10. Analytics Core Requester Experience AC Team Analyst Requester AC Team Analyst AC Team Analyst Requester Requester Analyst communication with requester as needed Receive submission confirmation email Contact with analyst within 1-2 business days Request Delivered Log in to ACReS Submit Request & Agree to Requester Obligations Data Request UCMC DATA

  11. Step 1: Log into ACReS Website • https://cri-app02.bsd.uchicago.edu/ACReS UCMC DATA

  12. Step 2: Begin a New Request You must use this data responsibly and as you indicate based on intention Make sure all stakeholders are included to ensure communication gets to everyone Requests generally take 4-6 weeks, urgent is 2 weeks Intention/Purpose Methods (if applicable) Variables/Metrics/ Elements needed (Include date ranges, inclusions, exclusions) If yes, then this must go to CRI If yes, this may need to go through the QI Determination Process UCMC DATA

  13. There may be legal implications for data leaving the organization (ex. DUA) Step 3: Complete the Form Only 1-2 teams have access to historical data CBIS teams can handle daily, real-time requests, while Clarity, AADS, CEA can handle one-time or monthly Different teams are specialized within certain data types. Different teams are specialized in creating different types of outputs UCMC DATA

  14. Step 4: Submit the Form Optional, can help teams prioritize your request Gives me a place to start if I have questions You must select “Submit” otherwise, we will not receive your request!!! Save draft will keep in a “draft” location that only you can see UCMC DATA

  15. Step 5: Post Request Submission • You will receive a confirmation email summary • Check back to see status updates (you will receive updates via email, and through the ACReS tool) • Your request will be assigned to the most qualified analytics team by the end of the next business day • The analytics team assigned to your request will now be your primary contact for this request UCMC DATA

  16. ACReS Request Triage Process AC Team Analyst AC Team Lead AC Team Analyst AC Team Analyst Requester AC Program Manager Communicates with requester as needed until request delivery Accepts or Rejects Request within 1 business day Contacts requester within 1-2 business day & begins work Close Request Requester submits Data Request Routes request to best suited team lead within 1 business day Accept Reject Data Request UCMC DATA

  17. The Good, The Bad & The Ugly A Good request includes the following components: • Purpose • Intention • Scope • Methods • Specifications such as inclusions and exclusions • Lists of codes, physicians, medications, data sources • Date Range • Sometimes requests can be too long or too vague • A requester may request bits and pieces of a request from different analysts/teams • The intention of the request is not evident UCMC DATA

  18. The Good, The Bad & The Ugly An example of a good request: As part of a research study, IRB13-0885, we will need to have data from REDCap merged with Epic/lab/ADT data. This study has informed consent for identified data. We will collect survey data in REDCap and upload .csv files with minute-by-minute heart rate, respiratory rate, and movement data for each patient. This needs to be merged with all of our research group's typical data/variables used to calculate eCART scores, i.e., • location stamped and time-stamped physiologic parameters (heart rate, blood pressure, respiratory rate, body temperature, oxygen saturation and mental status) as documented by the patient’s nurse • co-morbidities • laboratory results • radiological orders • interventional orders • medication ordered and administered (narcotics, sedatives, sleeping medications) • nursing assessments • sex • age • primary and secondary diagnoses • date of admission • date of discharge • discharge disposition • adverse events during hospitalization, defined as Rapid Response Team activations, emergent ICU transfer, cardiac arrest, or mortality • Sometimes requests can be too long or too vague • A requester may request bits and pieces of a request from different analysts/teams • The intention of the request is not evident UCMC DATA

  19. The Good, The Bad & The Ugly An example of a good request: Break out of PCGD survey responses overall rating of care score by clinic type (primary care has several which includes urgent care). The specifics would be: 1- clinic within PCGD 2- physician 3- ORC rating from PG survey 4- total N size for PCG practice clinic Date range for last 6 months.July 1 - November 1, 2016 Purpose: to assist in prioritizing discharge care call expansion into PCG visits and to determine which visits. UCMC DATA

  20. The Good, The Bad & The Ugly Requests that are not well written (whether long or short) may result in delays in an effort to understand all the elements and ensure routing to the right team. The requester may not follow the process and reach out to more than one analyst separately (we will find out!) The intention is not clear until after the fact, which may have consequences. An example of a not so good request: “looking to do a study on bronchoscopies performed over the past 8 years.” UCMC DATA

  21. Benefits & outcomes of our processes Assign multiple teams to collaborate on a signal request Sophisticated tracking Faster turn around times Share data sources, data sets Leverage existing reports Identify & address organizational reporting needs

  22. “The Power Is Yours!” Be involved and reach out! Check back to see the status of your request Contact us if your concerned about your request, or haven’t heard from us! Set realistic expectations: • We receive 100’s of requests per month- our analysts are busy, sometimes less than 2 week turnaround time is not feasible! However, investing time in understanding your own request/ topic will help ! • Improves the quality and processing times of your request Handle the data responsibly! • Remember, we are using our patients data. • Safeguards and considerations are made within the ACReS processes to protect the patients data, teams and requester. UCMC DATA

  23. Center for Quality Structure and Request Triage UCMC DATA

  24. Center for Quality Structure UCMC DATA

  25. Center for Quality Quality Performance Assessment Quality Performance Improvement Responding to the onslaught of reporting needs Making change so that we get better Clinical Effectiveness Analytics Understanding our performance Advanced Analytics & Data Science Making complex problems manageable UCMC DATA

  26. Advanced Analytics and Data Science 90% hold at least 1 advanced Degree or in process of pursing • Ph.D. Biophysics • Bioengineering • Computer Science • Biochemical Engineering How would you describe us UCMC DATA

  27. Health Information Life Cycle Analyst is an active participant of team and understands the WHYs Analyst finalizes report design and determines what’s possible Driven by a few different scenarios Analyst finds, organizes, validates data in a reproducible manner Analyst shares information as an active participant of the team Analyst assembles, visualizes, models data as information UCMC DATA

  28. Data preparation scenarios 1. The report already exists Programming Chart Review Programming Chart Review 2. Data are in the computer Data are cleansed, transformed, calculations made, validated, and data are positioned 3. Data will require hand-abstraction Data are ready for analysis 4. Data require special cleansing / transformation Many steps / costs likely 5. Data are not in our hands yet Contracts UCMC DATA

  29. Interrater reliability testing Exec review Leadership review Secondary validation Data are cleansed, transformed, calculations made, validated, and data are positioned Team reviews draft ± sets goals CFQ team review Goal vetting with leads *full review process shown UCMC DATA

  30. Data are ready 1. The report already exists Programming Chart Review Programming Chart Review 2. Data are in the computer Driven by a few different scenarios Data are cleansed, transformed, calculations made, validated, and are positioned 3. Data will require hand-abstraction Data are ready for analysis 4. Data require special cleansing / transformation Many steps / costs likely 5. Data are not in our hands yet Contracts UCMC DATA

  31. Health Information Life Cycle Analyst is an active participant of team and understands the WHYs Analyst finalizes report design and determines what’s possible Analyst finds, organizes, validates data in a reproducible manner Analyst shares information as an active participant of the team Analyst assembles, visualizes, models data as information UCMC DATA

  32. Census Forecasting: Model Development – Process (Ensuring Quality)

  33. CRDW Request Triage UCMC DATA

  34. Requestor submits data request (online) Face-to-face meeting of requestor and point person (30-60 minutes) IRB check - Project manager and Office of Clinical Research (1 hour) Project manager, point person, and report writers meet weekly to review and assign requests (1 hr) Internal review - Point person and report writer (1-2 hours) Specifications document and cost estimate (1-3 hours) Report writer develops SQL code for data extraction (1-20 hours) Report writer pulls sample data set (30-60 minutes) Requestor validates sample data set (1-2 hours) Internal verification that data set matches specifications document. Recheck that queries are written correctly (1-5 hours) Report writer pulls final data set (30-60 minutes)

  35. CRDW Spec Document UCMC DATA

  36. Data Request Challenges: Most Common Hold-ups Regulatory • Distinction between data points used for screening vs. those needed for the actual data set, particularly related to PHI Lack of response • Unwillingness to meet during office hours • Timeliness responding to data clarification emails Cohort identification • Data is not available in a format that is conducive to data extraction Request expectations • Asking us to making the binary decisions • One patient per row Funding • No budget to facilitate the research UCMC DATA

  37. CRI Resources Office Hours • Tuesdays, Room N161, by appointment 10-4 • Fridays, Room N161, by appointment 10-12 IRB guidance • CRDW specific IRB language ITM grant application guidance • http://itm.uchicago.edu/itm-funding-opportunities/ Semi-self service tools • I2b2 • SEE Cohorts Data Storage Solutions • REDCap • Bulkstorage UCMC DATA

  38. CRI Resources UCMC DATA

  39. UCMC DATA

  40. Semi Self-Service Tools i2b2 UCMC DATA

  41. Semi Self-Service Tools SEE-Cohorts: https://seecohorts.cri.uchicago.edu/ UCMC DATA

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