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1 EHR Documentation and CDI: What to Expect and How to Successfully Handle the Transition Sam Antonios, MD, FACP, FHM, CCDS CDI and ICD 10 Physician Advisor Hospital CMIO Via Christi Health Wichita, Kansas 2 Learning Objectives At the completion of this educational activity, the learner will be able to: Relate some results from a full conversion to electronic documentation Articulate short and long term benefits and challenges to CDI following an EHR conversion Describe 14 tips for managing a transition to EHR 3
2 The World of Medicine Has Changed 4 Healthcare Analytics 1922 Surgical infection rate 0.9% Surgical mortality 3.1% Medical mortality 8.1% 5 Yesterday: Observe, record, tabulate, communicate. Sir William Osler ( ) Today: Observe, record, tabulate, communicate, copy, paste, code, bill, don t get paid. 6
3 Hospital Adoption of EHR Systems Has Increased More Than Fivefold Since 2008 Charles, D., Gabriel, M., & Furukawa, M. F. (2014). Adoption of electronic health record systems among U.S. nonfederal acute care hospitals: ONC Data Brief, 16. Washington, DC: Office of the National Coordinator for Health Information Technology. 7 Trends in EHR Adoption Show Increasing Use of Advanced Functionality 8 Via Christi Health 9
4 We Are No Different Than Many Healthcare Providers 10 Realizing a Vision Go live June 1, hospitals (3 acute, 1 rehab, 1 psych) 25 ambulatory/outpatient clinics Around 8,117 providers/clinicians/end users 28 solutions Single day go live 11 CDI Role as Superusers 12
5 Number of Reviews Dropped During Go Live (Anticipated) % 90.00% 80.00% 70.00% 60.00% 50.00% 40.00% 30.00% 20.00% 10.00% 0.00% CDMP Reviews (% of Eligible Population) 13 Physician Response Rate % 99.00% 98.00% 97.00% 96.00% 95.00% 94.00% 93.00% Response Rate 14 Average Use of Pages 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% Preconversion Pages to providers * Post conversion *Survey data with CDIS 15
6 Physician Agreement Rate 90.00% 80.00% 70.00% 60.00% 50.00% 40.00% 30.00% 20.00% 10.00% 0.00% Physician Agreement 16 CC and MCC Queries (% of Total) 40.00% 35.00% 30.00% 25.00% 20.00% 15.00% 10.00% 5.00% 0.00% CC MCC 17 Physician Clarification Impact and CDI Coder Match 20.00% 15.00% 10.00% 5.00% 0.00% Physician Clarification Impact 86.00% 85.00% 84.00% 83.00% 82.00% 81.00% 80.00% 79.00% 78.00% 77.00% CDS Coder DRG Match 18
7 Compared to Benchmarks 19 What Happened to the CMI? Medical CMI Surgical CMI 20 Overall CMI Dec2013 Jan2014 Feb2014 Mar2014 Apr2014 May2014 Jun2014 Jul2014 Aug2014 Sep2014 Oct2014 Nov2014 CMI Benchmark 21
8 Electronic Inbox 22 Was It Perfect Before? 23 New Concept: A Diagnosis Box 24
9 Electronic Selection 25 Adoption of Was Much Quicker Than Expected 26 Transcription Volume Dramatically Dropped Lines Jan 14 Feb 14 Mar 14 Apr 14 May 14 Jun 14 Jul 14 Aug 14 Sep 14 Oct 14 Nov 14 Dec 14 LINES 27
10 Transcription Turn Around Time (TAT) in Hours Dropped Then Had to Be Readjusted FTE Reduction 1 0 Jan 14 Feb 14 Mar 14 Apr 14 May 14 Jun 14 Jul 14 Aug 14 Sep 14 Oct 14 Nov 14 Dec 14 H&P Goal H&P TAT 28 Discharge Summary FTE Reduction 0 Jan 14 Feb 14 Mar 14 Apr 14 May 14 Jun 14 Jul 14 Aug 14 Sep 14 Oct 14 Nov 14 Dec 14 DS Goal DS TAT 29 No, Not A Fib or V Fib J J J J J J J F F F F F MMMMMMM AAAAAAMMMMMM J J J J J J J J J J J J A A AAAASSS SSSOOOOOONNN Series1 30
11 Front End Dictation Active Users J J J J J J J FFFFFMMMMMMM A AAAAAMMMMMM J J J J J J J J J J J J A A AAAASSSSSSOOOOOONNN 31 What Were the Wins and Challenges With the Transition? 32 Exposure to Codified Data 33
12 Exposure to DRG Concepts 34 Cloned Notes Are a Problem. But Were We Perfect? 35 Biggest Wins With Legibility Timeliness Clinical integration data from multiple sources (outpatient clinic other hospitals HIE) Access to the physical chart Continuity of data until discharge Quicker turnaround time for dictations CDI work remotely * Exposure to codes DRGs Auto population of labs and vital signs Shift of work to hospitalists/residents * 36
13 Biggest Challenges With Electronic Documentation Overwhelming inbox Citrix sessions Query not available to multiple individuals CDI work remotely Providers work remotely Cloned notes Auto population of labs and vital signs 37 MU 2 Standards Also Require Attention Standard SNOMED CT ISO/OMB RxNorm HL LOINC 2.40 Direct Protocol C CDA NCPDP 10.6 Objective(s) Problem list, smoking status, family history Demographics Medication list, medication allergy list, erx Incorporate lab results, all public health objectives, provide ambulatory lab results Incorporate lab results, lab registries, provide ambulatory lab results Summary of care and view, download & transmit MU common data set erx 38 Meaningful Use Objectives Supported by SNOMED CT 1. Maintain an up to date problem list of current and active diagnoses 2. Record patient family health history as structured data 3. Identify and report cancer cases to a state cancer registry 4. Record and chart changes in vital signs 5. Record smoking status 6. Provide a summary care record for each transition of care 39
14 What Is SNOMED CT? SNOMED CT is an extensive clinical terminology that was formed by the merger, expansion, and restructuring of SNOMED RT (Reference Terminology) and the United Kingdom National Health Service (NHS) Clinical Terms (also known as the Read Codes) SNOMED CT was acquired in April 2007 by the International Health Terminology Standards Organization (IHTSDO) 40 Example of the Multiple Hierarchy Concept Use in SNOMED CT Left kidney stone can be represented by adding the laterality attribute (left) to (kidney stone) 41 What Is Third Party Vocabulary (e.g., IMO)? IMO s interface terminology provides a tool to create problem lists and capture clinical intent that is similar to providers existing medical terms IMO s terminology service contains around 460,000 terms that are mapped to reference coding systems including SNOMED CT, ICD 9 CM, ICD 10 CM, CPT and LOINC 42
15 What Does The Future of Documentation Look Like? 43 Mobile Mobile Mobile 44 What About Natural Language Processing? May be in future of documentation Needs to fit the physician workflow It s about smart algorithms, not summation of data Incorporate quality data Currently turned off until further refined 45
16 How Long Should the NLP Take to Avoid Doctors Breaking the Screen? 46 NLP Has to Be About Smart Algorithms 47 48
17 49 My Dream Dashboard 50 51
18 Recommended Reading 52 ACP Policy Recommendations for Clinical Documentation Paper Defensive medicine documentation Problem oriented documentation E&M codes Structured data Open notes Patient generated health data 53 Top 14 Tips to Manage the Transition to 14. Create standards and guidelines addressing cloned notes 54
19 Top 14 Tips to Manage the Transition to 13. Limit structured notes when not needed 55 Top 14 Tips to Manage the Transition to 12. Make inbox first thing providers log into 56 Top 14 Tips to Manage the Transition to 11. Use a vocabulary other than ICD 9 or SNOMED for searches 57
20 Top 14 Tips to Manage the Transition to 10. Make sure the vocabulary displayed is not coded 58 Top 14 Tips to Manage the Transition to 9. Limit the auto population yield 59 Top 14 Tips to Manage the Transition to 8. Clarify copied diagnoses 60
21 Top 14 Tips to Manage the Transition to 7. Fight urge to work remotely 61 Top 14 Tips to Manage the Transition to 6. Show providers a copied error 62 Top 14 Tips to Manage the Transition to 5. Show the patient portal to providers 63
22 Top 14 Tips to Manage the Transition to 4. Promote front end dictation and make it available everywhere 64 Top 14 Tips to Manage the Transition to 3. Do not discourage or eliminate traditional dictation 65 Top 14 Tips to Manage the Transition to 2. Include CDI as superusers at go live(s) 66
23 Top 14 Tips to Manage the Transition to 1. Budget for a drop in CMI 67 Thank you. Questions? samer.antonios@viachristi.org In order to receive your continuing education certificate(s) for this program, you must complete the online evaluation. The link can be found in the continuing education section at the front of the program guide. 68
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