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      Improving the Effectiveness of Electronic Health Record-Based Referral Processes

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          Abstract

          Electronic health records are increasingly being used to facilitate referral communication in the outpatient setting. However, despite support by technology, referral communication between primary care providers and specialists is often unsatisfactory and is unable to eliminate care delays. This may be in part due to lack of attention to how information and communication technology fits within the social environment of health care. Making electronic referral communication effective requires a multifaceted “socio-technical” approach. Using an 8-dimensional socio-technical model for health information technology as a framework, we describe ten recommendations that represent good clinical practices to design, develop, implement, improve, and monitor electronic referral communication in the outpatient setting. These recommendations were developed on the basis of our previous work, current literature, sound clinical practice, and a systems-based approach to understanding and implementing health information technology solutions. Recommendations are relevant to system designers, practicing clinicians, and other stakeholders considering use of electronic health records to support referral communication.

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          Most cited references77

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          Personal health records: definitions, benefits, and strategies for overcoming barriers to adoption.

          Recently there has been a remarkable upsurge in activity surrounding the adoption of personal health record (PHR) systems for patients and consumers. The biomedical literature does not yet adequately describe the potential capabilities and utility of PHR systems. In addition, the lack of a proven business case for widespread deployment hinders PHR adoption. In a 2005 working symposium, the American Medical Informatics Association's College of Medical Informatics discussed the issues surrounding personal health record systems and developed recommendations for PHR-promoting activities. Personal health record systems are more than just static repositories for patient data; they combine data, knowledge, and software tools, which help patients to become active participants in their own care. When PHRs are integrated with electronic health record systems, they provide greater benefits than would stand-alone systems for consumers. This paper summarizes the College Symposium discussions on PHR systems and provides definitions, system characteristics, technical architectures, benefits, barriers to adoption, and strategies for increasing adoption.
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            A new sociotechnical model for studying health information technology in complex adaptive healthcare systems.

            Conceptual models have been developed to address challenges inherent in studying health information technology (HIT). This manuscript introduces an eight-dimensional model specifically designed to address the sociotechnical challenges involved in design, development, implementation, use and evaluation of HIT within complex adaptive healthcare systems. The eight dimensions are not independent, sequential or hierarchical, but rather are interdependent and inter-related concepts similar to compositions of other complex adaptive systems. Hardware and software computing infrastructure refers to equipment and software used to power, support and operate clinical applications and devices. Clinical content refers to textual or numeric data and images that constitute the 'language' of clinical applications. The human--computer interface includes all aspects of the computer that users can see, touch or hear as they interact with it. People refers to everyone who interacts in some way with the system, from developer to end user, including potential patient-users. Workflow and communication are the processes or steps involved in ensuring that patient care tasks are carried out effectively. Two additional dimensions of the model are internal organisational features (eg, policies, procedures and culture) and external rules and regulations, both of which may facilitate or constrain many aspects of the preceding dimensions. The final dimension is measurement and monitoring, which refers to the process of measuring and evaluating both intended and unintended consequences of HIT implementation and use. We illustrate how our model has been successfully applied in real-world complex adaptive settings to understand and improve HIT applications at various stages of development and implementation.
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              Initial lessons from the first national demonstration project on practice transformation to a patient-centered medical home.

              The patient-centered medical home (PCMH) is emerging as a potential catalyst for multiple health care reform efforts. Demonstration projects are beginning in nearly every state, with a broad base of support from employers, insurers, state and federal agencies, and professional organizations. A sense of urgency to show the feasibility of the PCMH, along with a 3-tiered recognition process of the National Committee on Quality Assurance, are influencing the design and implementation of many demonstrations. In June 2006, the American Academy of Family Physicians launched the first National Demonstration Project (NDP) to test a model of the PCMH in a diverse national sample of 36 family practices. The authors make up an independent evaluation team for the NDP that used a multimethod evaluation strategy, including direct observation, in-depth interviews, chart audit, and patient and practice surveys. Early lessons from the real-time qualitative analysis of the NDP raise some serious concerns about the current direction of many of the proposed PCMH demonstration projects and point to some positive opportunities. We describe 6 early lessons from the NDP that address these concerns and then offer 4 recommendations for those assisting the transformation of primary care practices and 4 recommendations for individual practices attempting transformation.
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                Author and article information

                Journal
                BMC Med Inform Decis Mak
                BMC Med Inform Decis Mak
                BMC Medical Informatics and Decision Making
                BioMed Central
                1472-6947
                2012
                13 September 2012
                : 12
                : 107
                Affiliations
                [1 ]Department of Clinical Effectiveness and Performance Measurement, St. Luke’s Episcopal Health System, Houston, TX
                [2 ]University of Texas School of Biomedical Informatics and the UT-Memorial Hermann Center for Healthcare Quality & Safety, Houston, TX, USA
                [3 ]Houston VA HSR&D Center of Excellence and The Center of Inquiry to Improve Outpatient Safety Through Effective Electronic Communication, both at the Michael E. DeBakey Veterans Affairs Medical Center and the Section of Health Services Research, Department of Medicine, Baylor College of Medicine, VA Medical Center (152), 2002 Holcombe Blvd, Houston 77030, TX, USA
                Article
                1472-6947-12-107
                10.1186/1472-6947-12-107
                3492108
                22973874
                bf785d2d-3a00-496a-9576-fd48f6136ad5
                Copyright ©2012 Esquivel et al.; licensee BioMed Central Ltd.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 30 March 2012
                : 24 August 2012
                Categories
                Correspondence

                Bioinformatics & Computational biology
                Bioinformatics & Computational biology

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