Clinical Informatics VIReC CyberSeminar Series 2006 Clinical Informatics Attributes of An Ideal Informatics System with Highlights from a State of the Art Conference Denise M. Hynes, Ph.D., R.N. Director, VIReC Research Health Scientist, MCHSPR COE

HSR&D Resource Centers CiDER = Center for Information Dissemination & Education Resources HERC = Health Economics Resource Center metric = Measurement Excellence & Training Resources Information Center VIReC = VA Information Resource Center

Series/Course Objectives To learn about applications in clinical informatics in research and quality improvement efforts –VA and non-VA efforts To understand approaches for evaluating clinical informatics and IT interventions

Selected Course Topics Attributes of an Ideal Information System: Highlights from a State of the Art Conference Approaches for Evaluating Health Informatics Technology and CDSS Implementation of CDSS in Hypertension Management Implementation of a CDSS in Mental Health Using CDSS in Pain Management Informatics Applications for Promoting Collaborative Care

Session Objectives Understand the key aspects to consider in a clinical information system Understand the desired attributes of a clinical information system Become aware of the barriers and facilitators to use of IT in healthcare and research

IOM Quality Chasm Report, 2001 Predominance of chronic care Need for evidence-based practice Critical value of information technology

IOM Committee on Quality of Health Care in America Point-of-care access to health literature and evidence-based guidelines Computer-assisted decision support systems; Computerized patient clinical data Automation of decisions to reduce errors Electronic communication between providers Electronic communication between providers and patients

Informatics Support for Clinical Practice Guideline Implementation StepFacilitatorsInformatics Support Awareness Priming Activities such as profiling of baseline performance Profiling from prescription order and diagnosis database Acceptance Active education such as Academic Detailing; Clinical Opinion Leaders Present evidence relevant to patient; allow opinion leaders to browse knowledge base Adoption Enabling strategies such as incorporation into clinic workflow Integration with existing EMR/CPRS Adherence Reinforcing Strategies such as reminders Point-of-care patient-specific advisories & alerts Pathman, et al. Medical Care 1996; 34:

Diffusion of Innovation Theory: Key Dimensions Nature of the innovation itself How communication channels can be impacted Time Social system and organizational context

Challenge of Using Information Technology (IT) for QI Integrating new forms of decision support into legacy data systems and electronic record interfaces Sociotechnical aspects Goldstein, et al., JAMIA 11: , 2004.

Berg’s Sociotechnical Success Technical success – generates correct recommendations offline – extracts and uses patient data correctly – integrates with CPRS to display for the right Patient, Provider Clinical location Time window – tracks the data needed for research evaluation Sociological success – clinicians find it usable and useful Berg, M., Int J Med Inf, (2): p

Social Challenges of IT in Health Clinicians’ time constraints –Strike balance between ease of access to system and ease of ignoring it –Balance with interpersonal needs of patients Variability in comfort with computers –And virtually no training time available Lack of consensus/agreement about the guidelines

State of the Art Conference Summary Attributes of an Ideal Integrated Informatics System that Supports Implementation of Evidence

The ideal information management system supports managers, providers and patients to achieve practice and outcomes consistent with evidence

Supports knowledge-based decisions Evaluation/Reporting Capability Evolves with health care system Accurate/Correct Content Standardized/Compatible Attributes of the Ideal Information System

Defined Accountability: organization vs. provider Equitable: “No service/facility left behind” Sustainable Secure

Usable – Integrated – All electronic – flexible – transparent to users – non intrusive – easily up-datable

Current Information Systems do not fully utilized knowledge-based decision support Clinical reminders, order check system, notification and alerts Data capture limited to local system Difficult to prioritize Handling of adverse events Priority 1: Supports knowledge-based decisions

Strategies: Research on how to prioritize Require research to include data on added value in terms of mortality and morbidity Barrier: too much info/provider overload

Strategies: National patient data record Patient ownership of patient data, guidelines and reminders Common patient identifier Common provider identifier Integration across systems Research on what information users need Barrier: lack of integration

Strategies: Basic research in managing information complexity Alignment of research priorities with clinical management Performance measures focused on how much evidence informs practice Regular presentation of significant translation research findings to senior leadership Barrier: Operationalizing evidence

Strategies: Flexibility in decision support with required feedback about reasons for non-compliance and barriers to compliance Local review of compliance with local solutions (tailored training) Add autonomy in other areas: e.g., guideline input, self-review, link to reference materials Barrier: Threats to provider autonomy

rapid monitoring and feedback for evidence- based practice recommend appropriate treatment (reminders), track actual treatment and results, provide ongoing analysis of effectiveness Support analysis and review at different levels and contexts Priority 2: Reporting/Evaluation Functions

Strategies: More automation of data (e.g., link diagnosis to test) Review and monitoring of data quality Linkages to other information in EHR so provider doesn’t have to reenter (e.g., test results) Barrier: Data issues

Reporting complexity requires specialized knowledge Strategies: Use OLAP cubes to simplify user generation of reports Barrier: Reporting complexity

Reporting function on existing patient care system eats system resources, slows response time Strategies: Move reports off system – put analytical tools on a system separate from pt care system Barrier: System resources

Aspects of the information system are based on prior care models Current methods of data collection may not match business process or support evidence- based practice Priority 3: Information system needs to evolve with health care system

Strategies: Develop patient-centered data collection methods, core data elements, and system capacity for patient-based health data sets Encourage basic research on capturing home care data for all stakeholders Barrier: Emphasis on provider- level activities and provider- entered data

Focus on outcomes (maintaining/improving functional status of the patient), not workload encourage “just in time” rather than “just in case” visits, collect interim data remotely Barrier: Emphasis on workload rather than care received by patient

Some Summary Remarks Technology must be tailored to providers’ needs Fit into workflow in real time Minimize request for additional information Meet need for speed Elicit feedback and respond Tracking mechanisms needed to support research