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A Risk Assessment Model of Interoperable Electronic Health Records Solutions Panel: The Challenges of Interoperability in e-Health Claude Sicotte Département.

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Presentation on theme: "A Risk Assessment Model of Interoperable Electronic Health Records Solutions Panel: The Challenges of Interoperability in e-Health Claude Sicotte Département."— Presentation transcript:

1 A Risk Assessment Model of Interoperable Electronic Health Records Solutions Panel: The Challenges of Interoperability in e-Health Claude Sicotte Département d’administration de la santé Faculté de médecine Université de Montréal

2 Feuille de route  Presentation of the Risk Assessment Model  Brief survey of the two cases under study  Analysis of the major risks involved in both EHR interoperable implementations  The Lessons  Questions & Comments

3 Risk Management Framework IT Implementation Stages Project Management Objectives & Expectations Risk Exposure Management Strategies Fit Project Success © Claude Sicotte, Université de Montréal

4 Risk Assessment Model Technologic O rganizational M anagerial H uman S trategic © Claude Sicotte, Université de Montréal

5 Five types of risk Technological Risk: Hardware & Software Complexity & Network interoperability complexity Human Risk: Resistance to change & Users’ unrealistic expectations Usability Risk: Potential of use in real workplace context Managerial Risk: Quality of Project Team, Resources availibility & Unrealistic project schedule Strategic/Political Risk: Misalignment of groups of professionals and organizations’ objectives and stakes © Claude Sicotte, Université de Montréal

6 Brief survey of the two EHR implementations cases The vision: A clinical data sharing network system The goal: To enhance access, quality and coordination of healthcare The objectives: To increase the speed of transmission and the exchange of clinical data & To reduce intervention delays The technology: A Network Electronic Health Record (EHR) - Data Warehouse © Claude Sicotte, Université de Montréal

7 The Technology: An interoperable EHR Shared Electronic Health Record (EHR) Common Patient Index - Unique network identifier Shared Medical Thesaurus Common Patient Inscription Module Common Patient Consent Management Module Clinical Data: Labs Results, Medical Imaging Reports No physicians’ electronic ordering; only data display Network Infrastructure: Proprietary High-band secure intranet - Previously deployed Technical Interfaces: Legacy Systems - EHR Data Warehouse © Claude Sicotte, Université de Montréal

8 Brief survey of the first case, the less successful one Users: 39 Pediatricians - 1 Pediatric Teaching Hospital, 2 Regional Community Hospitals, 4 Medical Clinics Data Providers: 3 Public Hospitals Project Length: Three years and 4 months (2000 - 2004) Length of IT use assessment: First 7 months (2004) Total Project Budget: 11 million $ (Cdn) The partners: Pediatric Teaching Hospital (Maître d’oeuvre) - 2 Regional Community Hospitals - 4 Pediatric Clinics - IBM - Several firms of Legacy systems - Technocentres Régional & National, GTQ - Sogique & IBM - Bell Canada, Vidéotron. © Claude Sicotte, Université de Montréal

9 Brief survey of the second case, the more successful one Users: 105 General Practitioners - 10 Medical Clinics Data Providers: Public Hospital & Private Labs Setting Project Length: Two years and 2 months (2001 - 2003) Length of IT use assessment: First 10 months (2003) Total Project Budget: 14.8 million $ (Cdn) The partners: Laval Planning Regional Agency (Maître d’oeuvre) - Omni-Med - AMOL - 10 Medical Clinics - Hôpital Cité de la santé & Labo MDS - MédiSolution, Nexxlink, Artefact, Lanier - Technocentres Régional & National, GTQ - Sogique & IBM - Bell Canada, Vidéotron. © Claude Sicotte, Université de Montréal

10 Level of implementation success (Source: Electronic Log History Journals) Case # 2 (2003) FebAprilJuneSeptNov % MDs-Users /week 28%55%53%64%69% Mean Nb of access/week 63,22,75,24,7 Mean session length (mnt) 134116124116139 © Claude Sicotte, Université de Montréal Case # 1 Teaching HospHosp AHosp BClinics Use Boycott, Anemic use 1 MDNone Administr. Personal

11 Differences between the initial and the final levels of Risk Technolo- gical HumanUsabilityManagerial Strategic & political Very High High Case #1 Moderate Case #2 Weak Very Weak © Claude Sicotte, Université de Montréal Risk Level Dimensions Initial risk Level

12 Technological Risk Assessment Risk Factors Newness of network software and infrastructure Interoperability - Infrastructure: Use of incompatible hardware Interoperability - Infostructure: Lack of common data standard for the transfer of clinical data (HL7) Risk Management Enlistment of outside IT experts (EHR firm) Data Warehouse solution Development of home-made technical interfaces/ Several Vendors Management of Users’ expectations © Claude Sicotte, Université de Montréal

13 Technological Risk Assessment Outcomes Case 1: Underestimation of the time needed to develop the technical interfaces 12-month delay Missed deadline Decline of users’ confidence Case 2: More realistic schedule - Better management of users’ expectations Users’ commitment to the project remained unaffected © Claude Sicotte, Université de Montréal

14 Human Risk Assessment Risk Factors Physicians’ voluntary participation: less risk Initial expectations and attitudes were positive No resistance to change Physicians were realistic about the large efforts needed to learn to use the EHR Risk Management Case 1: Weak efforts to build relations with users Case 2: Impressive and continuous implementation efforts to build strong relations with the physicians; Project champions; Experimental use of the system interface; … True users’ influence on the implementation process © Claude Sicotte, Université de Montréal

15 Human Risk Assessment Outcomes Case 1: An increase of the human risk because of: (a) weak efforts in users’ relation building before the go live (b) the delays to develop the technical interfaces Case 2: A decrease of the human risk despite serious technological problems (System response time) The physicians became increasingly confident in the success of the new system © Claude Sicotte, Université de Montréal

16 Usability Risk Assessment Risk Factors Low awareness in this matter Taken for granted Physicians’ perceived uselfulness Only system’s user friendliness = a significant risk Information usability = EHR Information Content Work usability = alignment between EHR use and work routines Risk Management Data Warehouse: Volume and data quality Case 1: Weak recruitment of patients (- -) Case 2: High responsiveness the Users’ needs (++) & Better recruitment of patients © Claude Sicotte, Université de Montréal

17 Usability Risk Assessment Outcomes Case 1: An increase of the usability risk because of (a) late efforts in patient recruitment (Information Usability) (a) no effort to align the EHR use with work routines (Work Usability) Case 2: A decrease of the usability risk due to a high perceived EHR usefulness (High Information Usability) - Despite an initial poor EHR system response time, physicians continued to participate because they saw that no efforts were being spared to find solutions to their problems - Despite a lower than expected work usability © Claude Sicotte, Université de Montréal

18 Managerial Risk Assessment Risk Factors Quality of the project management team (Skills & Knowledge Team size, variety and time constraints Availibility of resources Risk Management Case 1: Smaller team, possessed less expertise both in IT and project management; far less time to devote to the management of the project Case 2: More intensive managerial efforts & more responsive to Users’ needs and Project Risk © Claude Sicotte, Université de Montréal

19 Managerial Risk Assessment Outcomes Case 1: Because of its smaller size, team’s efforts were overload by technological problems at the expense of other important risks, namely the human and usability risks Case 2: Larger scope of problems’ awareness and capabilities to intervene

20 Strategic Risk Assessment Risk Factors Network’s diverse composition rather than network size Larger misalignment of partners’ objectives and stakes in Case #1 (Teaching academic center/Medical Clinics; Children/adult patients) Risk Management Rather small number of organizations One type of users = Physicians Case #2: Higher Network Homogeneity (composed solely of GPs + One Health Region) and early network building efforts © Claude Sicotte, Université de Montréal

21 Strategic Risk Assessment Outcomes Case 1: Interorganizational conflicts were not really a problem Gradual disinterestedness was more of a problem Case 2: Continuous increase of confidence between the diverse partners including the regional association of physicians, the EHR firm and the team project team

22 The main lessons Six key factors of success: 1. The vision 2. The Network strategy 3. Flexible Execution 4. Design of a hybrid electronic - paper system 5. Clinical processes engineering both at network and individual levels 6. Quality of the project management team © Claude Sicotte, Université de Montréal

23 Key success Factors Lesson # 1: The vision There is a need to widen the project vision to give more space to the Clinical dimension to offset the unavoidable weigth given to the technologic dimension A Two-way vision is necessary to create a synergy between the technology and the clinic Key elements: Responses to users’ needs & Management of users’ expectations © Claude Sicotte, Université de Montréal

24 Key success Factors Lesson # 2: The Network strategy There is a need to conceive what is the meaning of “Interorganizational Partnership“ beyond a Telecommunication network There is a need to simultaneously further a Collective/Network logic and Local logics at diverse levels: clienteles, programs, groups of healthcare professionals and organizations What are the incentives? © Claude Sicotte, Université de Montréal

25 Key success Factors Lesson # 3: Flexible Execution There is a need to continuously change the initial plan to solve emerging problems and capture opportunities It seems to be an especially difficult thing to accomplish especially after the go live Flexible execution is necessary both at the operational and strategic levels © Claude Sicotte, Université de Montréal

26 Key success Factors Lesson # 4: Hybrid System A frequent mistake: To conceive the project on the sole functionalities offered by the electronic solution It is rarely possible to completely eliminate the old paper system. It is thus important to build a hybrid system corresponding to the true users’ needs © Claude Sicotte, Université de Montréal

27 Key success Factors Lesson # 5: Clinical Engineering A reconfiguration of clinical work processes remains unavoidable. It needs to be done in such a way to offer benefits to the users It is the Achilles’ heel in many projects © Claude Sicotte, Université de Montréal

28 Key success Factors Lesson # 6: Quality of the Team There is a need to widen the composition, the size and the action scope of the project management team Three key human resources:  The IT Specialist  The Clinical Champion  The Change Manager © Claude Sicotte, Université de Montréal

29 Comments & Questions Claude.Sicotte@umontreal.ca


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