A COMPARATIVE LOOK AT THE STATE OF EMR ADOPTION IN EUROPE

Transcription

1 A COMPARATIVE LOOK AT THE STATE OF EMR ADOPTION IN EUROPE Status and outlook of EMR adoption in Europe based on a comparison of Germany, Netherlands, UK and Norway NB: data for UK and Norway are preliminary PRESENTED BY: UWE BUDDRUS, MANAGING DIRECTOR HIMSS ANALYTICS EUROPE EHELSE HIMSS 2013 Analytics - 24 APRIL Europe - OSLO Mastering the Challenges of Clinical Decision Support - 1 TECHNOLOGY AND CARE KEY HIT CONCEPTS FOR COMPLEX HEALTHCARE PROCESSES MANAGEMENT HIMSS Analytics Europe Mastering the Challenges of Clinical Decision Support - 2 1

2 CLOSED LOOP MEDICATION ADMINISTRATION key components and challenges CPOE and/or e-prescribing Medication orders pass CDS and flow to Pharmacy and/or Ward emar Update and availability for review, override management and future CDSS interactions POC Administration Secure identification of nurse, patient and medication at POC by bar code scanning or RFID POC registration in emar dual signature for critical meds Pharmacy / Nurse Validation of order and dispensing of Unit Doses (e.g. by ADM) with bar code or complete prescription information NB: compounded vs. packaged med. ADM optional HIMSS Analytics Europe Mastering the Challenges of Clinical Decision Support THE STATUS OF CLOSED LOOP MEDICATION ADMIN. installed base of key components in acute hospitals, % of institutions DE NL NO* UK Pharmacy 88.7% 100% 100% 100% Pharmacy-IS 65% 100% 100% 84.6% eprescribing 28.4% 85.2% 12.5% 39.1% emar, of which 32.8% 70.4% 12.5% 38.3% available at PoC 20% 80% n/a 100% ADM for Unit-Doses 4% 38.9% 25% 7.1% Bar code / RFID, 80% 94% 100% 54% for medication 36% 65% 13% 7% CLMA 3.2% 38.9% 0% 0% data: UK (n = 50) data: DE (n = 377), NL (n = 62), *NO (n = 8, Health Region South East). HIMSS Analytics Europe Mastering the Challenges of Clinical Decision Support - 4 2

3 CLINICAL DECISION SUPPORT 3 levels from error checking to pathway optimisation Level Level 1: conflict checking during order entry System: low electronic order entry User: low Requirements Level 2: rules engine firing during order entry System: medium - CPOE with rules engine User: medium user friendliness; alert fatigue Level 3: rules engine triggered by physician / clinical documentation proposes pathways System: high CPOE, structured documentation, controlled medical vocabulary (CMV) tools, Evidence-based medicine / knowledge management, medical device integration, rules and workflow engines support predictive alerts, order sets and clinical pathways User: high trust, involvement, process design HIMSS Analytics Europe Mastering the Challenges of Clinical Decision Support - 5 THE STATUS OF CLINICAL DECISION SUPPORT installed base of key components in acute hospitals, % of institutions data: UK (n = 50) data: DE (n = 377), NL (n = 62), *NO (n = 8, Health Region South East). HIMSS Analytics Europe Mastering the Challenges of Clinical Decision Support - 6 3

4 CHRONIC DISEASE MANAGEMENT... Healthcare IT in the operational process Electronic Patient / Health Record Determination of the parameters for screening & of good practices Data warehousing, BI, QM Population reporting - process - results Screen & enroll Intake - best practice - guidance Devices and Apps, Telemedicine Monitoring - self management - regular consultations Care Plan - targets - actions - multidisciplinary Electronic Medical Record with emar, CPOE, CDSS, etc. HIMSS Analytics Europe Mastering the Challenges of Clinical Decision Support - 7 THE STATUS OF CHRONIC DISEASE MANAGEMENT installed base of key components in acute hospitals, % of institutions HIMSS Analytics Europe Mastering the Challenges of Clinical Decision Support - 8 Norway: no data collected for CDMS data: UK (n = 50) data: DE (n = 377), NL (n = 62), NO (n = 8, Health Region South East). 4

5 THE EMR ADOPTION MODEL AND THE STATUS OF EMR ADOPTION HIMSS Analytics Europe Mastering the Challenges of Clinical Decision Support - 9 THE EUROPEAN EMR ADOPTION MODEL in 7 Stages to Highest Quality in Patient Care Paperless patient record environment for highest quality of care, data continuity & full HIE Full electronic clinical decision support, and highest medication safety Completely electronic diagnostic image management Electronic order entry with decision support and result reporting Clinical ordering and documentation especially nursing care A patient-centered electronic data repository Electronic diagnostic and pharmacy department information HIMSS Analytics Europe Mastering the Challenges of Clinical Decision Support

6 EMR ADOPTION IN EUROPE... based on HIMSS Analytics European EMR Adoption Model Ø 2.6 Ø 2 Ø 3.7 Ø 1.7 DE (n = 371), NL (n = 49), NO (n = 8, Health Region South East), UK (n = 26). HIMSS Analytics Europe Mastering the Challenges of Clinical Decision Support - 11 EMR ADOPTION IN EUROPE preliminary findings overall EMRAM Stage DE NL NO UK Stage 7 0.3% 0.0% 0.0% 0.0% Stage 6 0.0% 3.8% 0.0% 0.0% Stage 5 8.3% 34.6% 12.5% 16.0% Stage 4 1.9% 3.8% 0.0% 0.0% Stage 3 8.3% 1.9% 0.0% 0.0% Stage % 55.8% 87.5% 36.0% Stage 1 0.6% 0.0% 0.0% 24.0% Stage % 0.0% 0.0% 24.0% N (valid) Mean Median * Please note: Data basis very low. Only shown for indicative purpose. DE (n = 324), NL (n = 52), NO (n = 8, Health Region South East), UK (n = 25). HIMSS Analytics Europe Mastering the Challenges of Clinical Decision Support

7 DIMENSIONS OF EMR ADOPTION AN INTRODUCTION TO THE DDEAM HIMSS Analytics Europe Mastering the Challenges of Clinical Decision Support - 13 DDEAM Dimension Dependent EMR Adoption Model A robust scale for implementation of EMR adopted to European/Nordic conditions Eight dimensions each with four levels, arranged into seven global development levels Dependencies between dimensions determine the scale. You do not enter the next level until fulfilling all demands in the current level Every level must involve change in at least one of the dimensions, but the scale should still be as concise as possible The scale provides advice on next steps strategically. The ROI appear on higher levels, in which a higher proportion of processes are supported electronically in a contiouous fashion. Optimal sequence of actions will improve changes of positive results Ref: Hallvard Lærum, Oslo University Hospital HIMSS Analytics Europe Mastering the Challenges of Clinical Decision Support

8 DEPENDENT DIMENSIONS IN EMR ADOPTION a draft of the DDEAM HIMSS Analytics Europe Mastering the Challenges of Clinical Decision Support - 15 Uwe Buddrus Managing Director HIMSS Analytics Europe Schwägrichenstraße Leipzig, GERMANY ubuddrus@himssanalytics.eu phone: For further information visit: HIMSS Analytics Europe Mastering the Challenges of Clinical Decision Support