Medical Device Interoperability: From Abstract Concepts to Clinical Improvement

1. Medical Device Interoperability: From Abstract Concepts to Clinical Improvement Collaborative Innovation at the Bedside: A Case Study May 31, 2008 Yadin DavidEd.D., P.E., C.C.E. Biomedical Engineering Consultants, LLC Asst. Professor, Pediatrics, Baylor College of Medicine

2. Project Overview Create an environment where technology is a workflow enabler not a driver through adoption of interoperability and standardization at the point of care. • Integration – require that vendors (e.g., nurse call, monitors, communication systems) speak “nursing” instead of nursing speaking each vendor’s dialect • Collaboration – multi-disciplinary participation of Nursing, Biomed, and IT to determine solutions • Objective data – direct improvements in patient safety, staff satisfaction, & clinical workflows based on historical patient event data collected from bedside technologies

3. Why? Decades of medical device technology evolution, without examination of the cumulative impact on patient care workflow, has made the workplace more difficult for nurses and potentially less safe for patients. • Many visual/auditory alerts • Communication barriers • Burden on caregiver to learn and adapt to each system • Duplicate data entry • Lack of audit trails

4. How? Focus on point of care • Build internal collaboration & multi-disciplinary team • Understand bedside workflow & processes Commit to integration • Develop short-, mid-, and long-term vision • Drive vendors towards standards & interoperability Incremental adoption • Bridge “concept” to “reality” of technology via small cycles • Fund low cost proof of concept projects with governance decision points prior to major capital expenditures

5. Nursing, the human interface Medical Device Interoperability: From Abstract Concepts to Clinical Improvement • Many proprietary solutions • Significant overlap in function • Burden on caregiver to learn & adapt to each system Vendor driven technology Ed.D., Professor, Pediatrics, Baylor College of Medicine

6. What? • Centralize • Caregiver to patient assignments • Alarms from disparate systems • Message patient’s caregivers • Manage clinical alarms • Rules based distribution of alarms • Closed loop communication of alarms • Historical patient data (“black box”) • Record of patient transactions (e.g., alarms, caregiver responses, medical device to patient association) • Objective black box data to support root cause analysis and development of best practice models

7. It’s not about technology, but . . . It’s not about technology, but . . .

8. Service Oriented Architecture PnP Service Oriented Architecture PnP

9. Centralized assignments

10. Whiteboard Spectralink phone directory

11. Event Recorder Overview Problem: High frequency of clinical alarms generated at point of care Action plan: Address operational & technological solutions • Involve unit staff in focus groups in work process & human factors discussions • Keep leadership actively engaged – focus on quality of care • Review number of clinical alarms on 36-bed unit • Assess if monitoring clinically necessary & parameters are patient/age specific • Assess need for and develop training program • Determine appropriate filters for non-critical alarms

12. Event occurs Match event rule? Message recipient? Select output device(s) Message delivery result(s)? Message acknowledged? Centralize event processing E v e n t M a n a g e m e n t Monitor alarm, room 11005 Yes, send all monitor alarms Send to RN assigned to room 11005 Select comm device assigned to RN Message successfully delivered to comm device RN acknowledges message

13. Level 1 – alarm not escalated to level 2 or 3 RN & patient name Spectralink phone Detailed transaction log Event history - patient “black box”

14. Root cause analysis and investigations • Objective history for individual patient or unit profile • Can produce a comprehensive report of: • - All alarms, alerts, messages, and staff/equipment location • - For a patient, room, unit, or other selected parameters

15. Quality improvement tools • Proactively • - Collect data • - Analyze and measure trends • - Anticipate and correct gaps • - Share information with all stakeholders • Knowledge gained can direct improvements in • - Patient safety • - Staff satisfaction • - Clinical workflows • Patient black box is the cornerstone

16. RCA historical transaction

17. Preliminary Findings • Alarm frequency & distribution graph generated for 36-bed surgical/orthopedic unit • Initial data quantified anecdotal reports that nurses are barraged by alarms and messages

18. Dashboards

19. Results First deployment (36-bed unit) • Created governance structure & project roadmap • Clinical workflow and process maps developed • Used surveys & observation to evaluate incremental deployment and drive improvements • Training program materials & training completed • Validated full system deployment in patient care area Long-term project • Continue deployment to acute-care units • Implemented a high-availability infrastructure • Drive integration at the point of care by forcing vendor conformance to standards

20. Detailed Findings • Reviewing trending data • 2 to 5 patients (in 36-bed unit) account for >80% of monitor alarms • On 5/18/07, 2 patients generated 435 alarms out of a 508 total • Conducted lab simulation of cardiac and pulse oximeter • monitor alarms • ~33% of monitor alarms reset within 10-seconds • Critical alarms required a manual reset

21. What Worked • Multidisciplinary team – nursing, biomedical engineering, information services and vendors partnerships (select vendors carefully) • Bedside nursing focus group – drove identification & rapid resolution of issues and adoption of changes • Incremental approach – facilitated new workflow model, process evolution/validation, and major funding for proven proof of concept models • Improve communication - centralized assignments and communication of alarms/messages • Historical data – black box transaction capture, reporting, quality analysis (trends and patterns)

22. Lessons Learned What worked? • Continuous review of impact of bedside technology • Leadership, focus group, and tech team participation • Multi-disciplinary (Nursing, Biomed, IT) tech team • Simultaneous operational and technical improvements What’s next? • Expansion of initiatives to “smart” bedside alarms • Expanded deployment to additional units

23. Technology Lessons Learned It’s not about technology … it’s about patients & people … it’s about the bedside … it’s about collaboration … it’s about integration … it’s about workflow & process

24. Contact Information Yadin David, Ed.D., P.E., C.C.E. Biomedical Engineering Consultants, LLC david@biomedeng.com (713) 522-6666 Melita Howell Texas Children’s Hospital Sr. Project Manager mjhowell@TexasChildrensHospital.org (832) 824-4434