Surviving The Data Jungle

1. Surviving The Data Jungle A Team Approach for Beginners Using the Data Repository Patricia Korolog Mulberger, BSN, RN Suzanne Catalfomo, RPh Kalispell Regional Medical Center

2. Survival of the Fittest Using Data for Good Business Decisions Access to data real time Combine clinical and financial data Ability to slice and dice Ease of manipulating data Ability to fill in the gaps Meditech Medhost Kronos ANSOS eClinical Works Access previous data (no purging) NOW, NOW, NOW

3. Buried by NPR Difficult tool to learn, at best Reports are very specific May have to write several reports to sort differently or to summarize or see detail Report writers tend not to be the data users Where to find the data the user thinks you are pulling Initial validation � would IT know if it was completely wrong? Report writing only one small piece of IT workload Purging out of modules leaves data holes Combining information outside of Meditech cumbersome Scheduling reports often caused scheduler to crash TIME, TIME, TIME

4. Our Mission Getting the correct data to the user in a way that would allow the user to aggregate the data as needed, as well as to drill down into the data and allow a true business decision support process to occur Do all that without burying IT or our data users

5. Choosing Our Tools Relook at Data Repository Contains data purged from Meditech applications Relational database that can be combined with other databases Tables a bit more �friendly� than NPR data hierarchy Visual tools out there to help users find data easily

6. Choosing Our Tools We Need More Help! Looked at additional business decision support tools Ease of use Cost Bringing all our data together Usefulness � bang for the buck! Chose DIVER � Dimensional Insight

7. A New Model Jungle �Head�s Up� Danger alert passed from one animal group to the next Ensures no one gets eaten Team Approach Goals � Our Jungle �Head�s Up� Reporting challenges/successes passed from one dept to the next Solidarity between departments for fiscal health � ensures all survive Let go of silos of information Those who know the data become expert on how data is stored in DR Individual ownership of reporting needs Better validation of data (and of the DR) Dynamic solution that once built needs little tweaking for changes in sorting, summarizing and drilling down into a variety of detail fields IT becomes mentor in getting data, not primary data gatherer IT works on big picture � bringing it all together

8. First Steps Reporting Needs Who needs this information? How do they need it delivered? Casual Users View final results with no manipulation of data? Top management Intermediate Users Do some mild manipulation of the data but generally don�t have to dig much farther Advanced Users Slice and dice data, dig down into the detail, lots of manipulation AKA Data Junkies

9. Picking The Team Advanced Users Desire to be on the team Commitment to learn and to help others on the team learn Ability to learn on own No spoon feeding Variety of disciplines and departments

10. The Team IT Financial analyst and clinical analyst Minimal SQL and Crystal experience Intermediate to Advanced NPR experience Minimal DR experience Revenue Cycle Manager No experience in report writing tools Pharmacy Informatics Specialist NPR experience, No DR or SQL experience Laboratory Informatics Specialist NPR experience, No DR or SQL experience Operating Room Manager NPR experience, No DR or SQL experience HIM Manager No experience Quality Management No experience Cost Accounting No experience

11. Our Keys To Success Measurable, focused goals Start small and add tables Think of one model that would make your day How can we make that happen? Clarify roles and expectations Who takes the lead? Responsibilities of all team members How can we get help when needed? Keep team involved � seek out victories Learning as a priority � team rules Practice open communication and transfer of knowledge

12. The Approach Project Managed by IT Train together Weekly meetings for data validation and becoming experts in using the tool Weekly meetings for building �models� Each meeting show something new IT assist if unable to find data or has problem with data DR tasks with Meditech

13. The Approach Set up users with ODBC connection to DR Give users DR tools DRDiagram powerpoint MUSE or Meditech l list Link to http://www.meditech.com/prdr/Tables/55HTMLsCS/system.htm Meditech table schema in DIVER

16. Displays Table Name and Primary Keys

17. Click Into Table for More�

21. Timeline DIVER training end of January Began weekly meetings in February By March access to Data Repository for all users completed Since March Pharmacy, Laboratory, Nursing (Clinical Informatics) and Revenue Cycle Manager have robust reporting models built

22. 1st Win � Comparing Manual Excel Spreadsheet with Admissions Data Need Identify patients seen in provider based clinic not registered in Meditech Bill for services on same claim to decrease denials Old Way Printed office schedule and manually compared to alpha list of all hospital patients registered in Meditech for same time frame Missed patients Resource intensive New Way A model structure that allows the spreadsheet to be updated and then run against new admissions data Time savings approximately two hours/ week Increased accuracy (finds all patients) Decreased denials

26. Next Step eClinicalWorks and Meditech Instead of using manual spreadsheet, compare eClinicalWorks with Meditech Just beginning to learn the eClinicalWorks tables Use for all eClinicalWorks facilities

27. Laboratory Initial Approach Pull BBK, Lab, MIC specimen information and combine in one model Initial statistical and workload information

31. Combining all three tables into one Built a model for each area and combined Lab BBK Micro Especially easy since tables contain same columns

33. Lab Business Decision Impacts Staffing Issues Variations in workload to determine optimal staffing By Location Hour of Day Day of Week # of Blood Draws � Should I keep draw station open? By Phlebotomist By Ordering Location

34. Laboratory Specimen Results Pull specimen information and result detail into one table and then determine model Use for best practices

35. Creating 1st table

36. Creating 2nd table

37. Joining the Tables

38. Creating the Output File

39. Lab Results Combine two tables using visual tool LabSpecimens Parent table LabSpecimenTests Detail table Join tables using same tool Creating output file

40. Bring in output file to build model

41. Initial Basic Build

43. Adding a Column � Very Simple

45. Lab Best Practices Looked at hemolyzed specimens By Collector By Location Determined % of hemolyzed samples in which users might need retraining

47. Pharmacy Data � It�s a jungle out there! Pharmacy Data is dense First lesson about Pharmacy Data and DR Visit ID links to Patient Data Prescription ID links to Rx Data The DR map on Meditech.com indispensable Once you have your guidepoints you can see the forest for the trees!

48. NPR Orders entered per hour Pretty proud of myself for getting this to work! Had a �script� from a different site Had to personalize Only captures data from past 7 days

51. Pretty straightforward No macros Not difficult VAL statements Just a lot of fields and lines on picture Lot of formatting Line Checks �.But that�s all this can do. This tiger can�t change its stripes�

55. New Horizons Infection Control Needs Historically very manual Combining excel spreadsheets, text files and application information Combine registration / demographic information with diagnosis, laboratory results and pharmacy rx�s A must have ability in today�s world

56. The Flood Gates Open Desire for more SQL knowledge Common SQL terms to the team Team wants more advanced DIVER tool skills Looking at more on site training More DR table knowledge Other application table knowledge Midas, ANSOS, KRONOS, Medhost, eClinicalWorks

57. Survival Lessons Learned Team members must be self-motivated, self-learners and enthusiastic Lost Members Enthusiastic at first but only wanted end result Couldn�t get them into their databases quickly enough Midas, Kronos Get clinical data out there quickly A zillion financial NPR reports already built Combining clinical data with financial data imperative for healthcare survival Keep adding to the wins Dangle the carrot The users know what they need. If you give them a visual tool to pull together a report �model� that will allow them to dynamically pull a myriad of reports they will put in the effort Effort in the beginning really pays off so show the wins quickly Pretty counts

58. An Elephant Never Forgets Security in DR SQL Roles No access to P/P tables SQL Views Develop views for different entities Kalispell Regional Medical Center HealthCenter Northwest Both KRMC and HCNW Now adding other facilities

59. Jungle Noises from the Team �I was a little frustrated at first because it was all so foreign. But I got my first model report done quickly and once I saw that I knew I had the tool I needed to be able to make some sound business decisions� �Just give me more training� �We should have done this years ago!�

60. Questions?