1. CRITICAL ACCESS HOSPITAL CLINICAL INFORMATION SYSTEMS AND HIT STRATEGIES Marcia M. Ward PhD James Bahensky MS AHRQ Annual Meeting - 2009 College of Public Health

2. Introduction Hospital size has been shown to have a systematic relationship to implementation of health information technology (HIT) 1,2 For small hospitals that convert to Critical Access Hospital (CAH) status, their Medicare payment methodology changes from a prospective payment system (PPS) to retrospective cost-based 3 CAHs’ positive finances have permitted many to refurbish aging facilities, enhance patient quality, 4 and invest in HIT 5

3. Research Objectives The goal of this study was to review the rural landscape in the use of HIT by examining CAHs in Iowa, a predominantly rural state with a large sample of CAHs To help understand the variability in HIT use by CAHs, business strategies for supporting HIT implementation are examined and the relationship between common approaches and HIT use is explored

4. 2005 HIT Survey of Iowa Hospitals - Approach  As part of the AHRQ grant, in Fall 2005 we developed a new survey of Iowa hospital clinical information systems. This survey consisted of:  general information on hospital IT services, network influence, connectivity  approaches to IT staffing, outside services  an inventory of clinical information systems to determine the level of systems in each hospital

5. Our Survey of HIT Capacity Part 1Part 2 Focus – profile of the hospital in terms of technology resources and capacity Focus – actual technology applications used for business and clinical operations Information Collected : the number of IT staff extent of use of consultants, vendors, ASP if the hospital was part of a network Information Collected: 46 HIT applications, both business and clinical whether each application was operational, being installed, or in the planning stages Response Options – 5 point Likert-type scales (ranging from “not at all” to “a great deal”) for extent items Response Options – for applications currently operational, being installed, or budgeted, information on the chosen vendor was collected

6. Hospital Distribution in Iowa The survey was mailed to all hospitals in Iowa (N=116) 82 Iowa hospitals are designated as CAHs – the focus of these analyses 6

7. Who Responded? Overall, 85% of hospitals and 85% of CAHs (N = 70) returned completed surveys For the CAHs, half of the responses were from the CEO, COO or CFO, and almost half were from the CIO or IT Manager

8. Basic IT Use in CAHs have a website presence (90%) use local area networks (85%) use intranets within their organizations (79%) Almost All CAHs use technology for remote interpretation of digital images (65%) use technology for consultative support through telemedicine (62%) Two-thirds of CAHs have client server applications (66%) have laptops and/or tablet PCs (66%) have nursing call systems (59%) Majority of CAHs

9. Business and Clinical Applications Financial systems (96%) Patient registration (97%) Patient billing IT systems (97%) Billing coding IT systems (86%) Inventory control (79% ) Business applications Inpatient laboratory (86%) Pharmacy (70%) Radiology (56%) Clinical Information Systems

10. EHR/EMR Systems in CAHs Status of EHR/EMR Availability 29% of CAHs have implemented systems 14% are currently installing 13% have it budgeted and 32% are planning 13% have no plans Top 3 Vendors of EMR among CAHs CPSI (26%) Dairyland (25%) Meditech (12%)

11. CPOE and CDSS Use in CAHs 12% have CPOE operational 13% are currently installing 26% have it budgeted 36% have no plans CPOE – computerized provider order entry 14% have CDSS operational 5% are currently installing 4% have it budgeted 74% have no plans CDSS – clinical decision support systems

12. EMR Stages – Garets and Davis Model StagesDefinition Stage 0 All Three Ancillaries (Lab, Rad, Pharmacy) Not Installed 19.25% Stage 1 Ancillary systems installed in all three (Lab, Rad, Pharmacy) 20.53% Stage 2 Clinical data repository (CDR), computerized medical vocabulary (CMV), Clinical Decision Support System (CDSS) inference engine, may have Document Imaging 49.66% Stage 3 Clinical documentation (flow sheets), CDSS (error checking), PACS available outside Radiology 8.12% Stage 4 Computerized Provider Order Entry (CPOE), CDSS (clinical protocols) 1.86% Stage 5 Closed loop medication administration 0.46% Stage 6 Physician documentation (structured templates), full CDSS (variance & compliance), full PACS 0.13% Stage 7 Medical record fully electronic; CDO able to contribute to EHR as byproduct of EMR 0.00% Total 100%

13. HIMSS Analytics Stages of EMR in CAHs Based on HIMSS Analytics 8-stage model for the measurement and understanding of EMR capabilities in hospitals 7, the current survey indicates that: 53% are in Stage 0 25% are in Stage 1 11% are in Stage 2 11% are in Stage 3 or higher

14. CAH Business Strategies for HIT  This survey of 70 CAHs in Iowa indicates use levels of IT applications that are quite similar to those found in a 2006 national survey of CAHs 8, suggesting that the current survey findings are generalizable  This survey and follow-up interviews in 16 CAHs with EMR indicate:  The most common strategy was the “best of breed” where the best available system is purchased for each specific purpose  A second common purchasing strategy was to incrementally add systems from a single vendor

15. CAH IT Staff Resources – Number of FTEs  A third of the CAHs do not employ any IT staff  Half only employ 1 to 2 IT staff  Fewer than 5% of CAHs employ more than 5 IT staff

16. CAH Use of External Staff Resources External IT Consultants Outsourcing IT Services Application System Providers (ASP) 91% use external IT consultants 85% of CAHs use outsourcing to meet their IT needs <40% of CAHs use ASP to support their clinical applications CAHs use external IT consultants: 38% to a great extent 12% to a large extent More than 40% of CAHs outsource: website system installation technical support network operations applications development services Of CAHs that use an ASP vendor, only 9% use this approach to a great extent

17. Approaches for CAHs with Few IT Staff  CAHs with fewer IT staff use outsourcing more (r = 0.72)  CAHs with no IT staff used outsourcing more to meet their needs for:  system installation (p<.05)  technical support (p<.01)  PC support (p<.0001)  network operations (p<.02)  help desk (p<.01)  user training (p<.001)  outsourced their full IT department (p<.01)

18. Staffing for HIT: Chicken or Egg CAHs rely on outsourcing more than larger hospitals to meet their IT needs CAHs that have not yet installed an EMR commonly operate without any IT staff whereas CAHs with an operational EMR tend to have at least a handful of in-house IT personnel - which comes first – staff or EMR? Follow-up interviews indicate that some CAHs purchased EMR systems and then hired IT staff Other CAHs hired IT staff to help with EMR decision/installation process

19. HIT Business Strategies for CAHs CAHs still lag behind larger hospitals in IT, especially clinical information systems However, CAHs are more financially able to purchase or upgrade HIT now because of increased revenue related to Medicare billing policy change CAHs are dividing into two groups in terms of HIT:  CAHs that are part of healthcare systems benefit in terms of having access to system technology and IT staff  Independent, rural CAHs have considerable difficulty finding IT staff and when they purchase EMRs, those EMRs have fewer functionalities (e.g., no CPOE or CDSS)

20. EMR Follow-up Interview Methods Using data from the 2005 HIT Survey, we identified 15 Iowa CAHs that had or were implementing EMR We developed interview guides and conducted follow-up on-site interviews with: CEO CIO/HIT Manager Chief of Nursing and/or Quality Director Tapes of the interviews were transcribed and two analysts reviewed transcriptions multiple times to identify themes in responses to questions

21. Decision to Implement EMR  Theme 1: Decision to implement EMR was driven by the beliefs that EMR will become the wave of the future and will be mandated in the near future.  Theme 2: Decision to implement EMR was driven by the hospital’s culture that emphasizes staying ahead of the curve (early adopters), pertaining to new technology and innovation.  Theme 3: Decision to implement EMR was based on a desire to be comparable to and compete with larger hospitals—a goal and vision that administration and staff took ownership of.

22. Decision to Implement EMR  Theme 5: Decision to implement EMR was influenced by system affiliation.  Theme 6: Decision to implement EMR was driven by the desire to improve efficiency, timely access, and quality, which would facilitate more patient- centered care.  Theme 7: Decision to implement EMR was driven by the initial need to improve their financial process (e.g. accurate and timely billing process).  Theme 8: Decision to implement EMR was driven by inadequacy of the stand-alone systems that were not integrated.

23. EMR Follow-up Interview Analyses Key themes to initial “why and how” questions were:  Purchases of EMR systems were largely made because of legacy systems, network influence, or wanting to stay current with larger hospitals  Process of choosing EMR system and vendor varied across hospitals  Hospitals had made little effort to track benefits and thus had little knowledge of benefits

24. References 1. American Hospital Association. Continued Progress - Hospital Use of Information Technology. http://www.aha.org/aha/content/2007/pdf/070227-continuedprogress.pdf http://www.aha.org/aha/content/2007/pdf/070227-continuedprogress.pdf 2. Li P, Bahensky JA, Jaana M, Ward MM. Role of multihospital system membership in electronic medical record adoption. Health Care Management Review, 33(2): 1-9, 2008 3. American Hospital Association. Forward Momentum: Hospital Use of Information Technology. Chicago, IL: American Hospital Association. 2005 4. Li P, Schneider JS, Ward MM. The effect of critical access hospital conversion on patient safety. Health Services Research, 42: 2089-2108, 2007 5. Bahensky JA, Frieden R, Moreau B, Ward MM. Critical Access Hospital informatics. How two rural Iowa hospitals overcame challenges to achieve IT excellence. J of Healthcare Information Management, 22(2): 16-22, 2008 6. Iowa Hospital Association. Profiles; Section VI: Hospital and Health System Specific Data. 2005, http://www.ihaonline.org/publications/profileserv/profileserv.shtml. Accessed October 25, 2008 http://www.ihaonline.org/publications/profileserv/profileserv.shtml 7. Garets D and Davis M. Electronic medical records vs. electronic health records: Yes, there is a difference. HIMSS Analytics. January 26, 200. http://www.himssanalytics.org/docs/WP_EMR_EHR.pdf http://www.himssanalytics.org/docs/WP_EMR_EHR.pdf 8.Flex Monitoring Team. The current status of health information technology use in CAHs. Flex Monitoring Team Briefing Paper No. 11; May 2006. http://www.flexmonitoring.org/documents/BriefingPaper11_HIT.pdf. Accessed October 25, 2008 http://www.flexmonitoring.org/documents/BriefingPaper11_HIT.pdf

25. Acknowledgements University of Iowa - College of Public Health Department of Health Management and Policy Center for Health Policy and Research Funded in part by: The Agency for Healthcare Research and Quality through grant # HS015009 – “HIT Value in Rural Hospitals”