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The purpose of this study was to describe the extent of change in patient care orders primarily for six diagnoses, procedures, or conditions in a not-for-profit Midwestern rural referral hospital. A descriptive method was used to analyze changes in the order sets over time for chest pain with acute myocardial infarction, degenerative osteoarthritis with hip joint replacement and degenerative osteoarthritis with knee joint replacement procedures, coronary artery bypass graft procedures, congestive heart failure, and pneumonia. Ten items about service-specific order sets were abstracted during pre- and post-EHR implementation and a year later. We then examined use 5 years later. The findings illustrate how the order sets evolved with multiple nested order sets to facilitate computerized provider order entry with a rate greater than 70% by physicians. The total number of available patient care orders within the order sets increased primarily because of linked nested order sets related to medications and diagnostic tests. Five years later, 50% of the orders were medication orders. In conclusion, this was important to deploy the order sets within smaller critical-access hospital facilities to train providers in adopting order sets internally.

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A longitudinal study examined seven outcomes of chronically ill patients receiving community-based case management services. A repeated-measures analysis showed that these patients reported greater satisfaction with quality of life and personal well-being and controlled their symptoms better, but declined in self-care activities of daily living and in self-care instrumental activities of daily living.

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The implementation of electronic health records in rural settings generated new challenges beyond those seen in urban hospitals. The preparation, implementation, and sustaining of clinical decision support rules require extensive attention to standards, content design, support resources, expert knowledge, and more. A formative evaluation was used to present progress and evolution of clinical decision support rule implementation and use within clinician workflows for application in an electronic health record. The rural hospital was able to use clinical decision support rules from five urban hospitals within its system to promote safety, prevent errors, establish evidence-based practices, and support communication. This article describes tools to validate initial 54 clinical decision support rules used in a rural referral hospital and 17 used in clinics. Since 2005, the study hospital has added specific system clinical decision support rules for catheter-acquired urinary tract infection, deep venous thrombosis, heart failure, and more. The findings validate the use of clinical decision support rules across sites and ability to use existing indicators to measure outcomes. Rural hospitals can rapidly overcome the barriers to prepare and implement as well as sustain use of clinical decision support rules with a systemized approach and support structures. A model for design and validation of clinical decision support rules into workflow processes is presented. The replication and reuse of clinical decision support rule templates with data specifications that follow data models can support reapplication of the rule intervention in subsequent rural and critical access hospitals through system support resources.

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PURPOSE: The impact of implementing commercially available health care information technologies at hospitals in a large health system on the identification of potential adverse drug events (ADEs) at the medication ordering stage was studied. METHODS: All hospitals in the health system had implemented a clinical decision-support system (CDSS) consisting of a centralized clinical data repository, interfaces for reports, a results reviewer, and a package of ADE alert rules. Additional technology including computerized provider order entry (CPOE), an advanced CDSS, and evidence-based order sets was implemented in nine hospitals. ADE alerts at these hospitals were compared with alerts at nine hospitals without the advanced technology. A linear mixed-effects model was used in determining the mean response profile of six dependent variables over 28 total months for each experimental group. RESULTS: Overall, hospitals with CPOE and an advanced CDSS captured significantly more ADE alerts for pharmacist review; an average of 336 additional potential ADEs per month per hospital were reviewed. Pharmacists identified some 94% of the alerts as false positives. Alerts identified as potentially true positives were reviewed with physicians, and order changes were recommended. The number of true-positive alerts per 1000 admissions increased. CONCLUSION: The implementation of CPOE and advanced CDSS tools significantly increased the number of potential ADE alerts for pharmacist review and the number of true-positive ADE alerts identified per 1000 admissions.

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The complexity in adopting health information technology (IT) standards is not from lack of standards. Rather, there are a vast number of standards that overlap and some that are missing. The objective of this article is to provide nurses with an understanding of the importance of the National Health IT Agenda and be empowered to influence the processes to ensure nursing is represented. Several aspects include harmonization and adoption of standards necessary to achieve interoperability, and the strategies for nursing leaders to advocate for adoption of those standards.

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Electronic health records (EHRs) are a cost-saving and environmentally friendly means for documenting patient care and improving patient safety, quality, and evidence-based practice. Standardized clinical classification systems and terminologies are essential ingredients of the EHR. Their selection must be driven by a clear understanding of requirements for their use and application. This article describes the principle uses of clinical information and motives for consistency in practice, and provides a distinction between classification systems and reference terminologies for clinical settings.

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Electronic medical records and health records provide a variety of clinical decision support interventions to guide or support the clinical user. These interventions are design features to guide users in next steps, offer useful evidence-based knowledge, or provide patient information relevant to a decision.

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The structure and content of the dialog with a clinical end-user is a critical aspect of clinical information system use, data capture and retrieval, and efficient and effective health care. This dialog is driven ultimately by embedded structures and processes that: a) provide functional models of clinical expression in support of professional practice, and b) determine how structured terminologies ought to populate these models. Based on diverse practical experience, this study identifies challenges to implementing structured clinical terminologies, categorizing them by both stakeholder group and application area. Collaboration across all stakeholders and across a wide range of application areas is identified as a key ingredient to successful terminology implementation and use.

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Mercy Medical Center, North Iowa implemented electronic health records (EHR), computerised provider order entry (CPOE) and event tracking systems in the emergency department (ED) as part of hospital-wide implementation of clinical information systems. This case study examines the changes in outcomes and processes in the ED following implementation. Although the system was designed to enhance efficiency, there was a significant increase in the mean length of stay (about 17 minutes, or 15%) in the ED after implementation. This surprising finding was examined in relationship to the multiple process-of-care changes in the ED.

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BACKGROUND: Implementation of health information technology (HIT) has encountered many difficulties and produced mixed outcomes. Yet Trinity Health, a major integrated delivery system, successfully leveraged implementation of a systemwide electronic health record (EHR) to promote process redesign and continuous quality improvement. IMPLEMENTING A SYSTEMWIDE EHR: After several years of planning, two waves of EHR implementation were launched, in 2001 and 2003. One system HIT team collaborated with each hospital team for 18 months before its 24-hour transition to the EHR. During EHR planning, the system HIT team used five principles of redesign of care processes: (1) identify and address safety problems, (2) promote evidence-based practices, (3) reduce practice variations and standardize terminologies and care processes, (4) improve communication and relationships among clinician roles, and (5) augment multiple uses of data in HIT-supported care processes. Patient-centered work flows were developed to design improved patient care processes for different types of patients, such as medical inpatients and emergency outpatients. These admission-to-discharge work flows addressed gaps in quality, safety, and efficiency and helped ensure that the EHR and decision supports reflected crucial interactions among clinicians and with the patient. By the end of 2008, 13 of Trinity Health's 17 major health care organizations ("ministries") made the transformation to using EHRs. DISCUSSION: EHR-supported care redesign requires development of substantial system capacities in clinical informatics, customization and standardization of vendor's products, collaboration and coordination between system and hospital implementation teams, quality training for clinicians and change agents, and significant clinician participation in local preparations.

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Trinity Health is a large multihospital healthcare system that developed a system-wide information technology strategy and implementation model. This study looks at how that system-wide strategy and implementation model, called Project Genesis, was used at Mercy Medical Center-North Iowa, a Trinity Health rural referral hospital, and how the care delivery system was redesigned using an electronic health record. This study was funded in part by a grant (UC1 HS15196; Rural Iowa Redesign of Care Delivery with EHR Functions) from the Agency for Healthcare Research and Quality to implement an integrated EHR system in the hospital and two clinics and assess its impact on patient safety, quality of care and organizational culture. The study looks at redesigning care delivery using the Trinity Implementation Model that consists of local and system-wide planning components; physician and nurse ownership; order set development; clinical workflow redesign; and training and support. It then examines the initial experiences of the IT implementation at Mercy Medical Center-North Iowa, the impact on health information management, lessons learned and future steps to achieve a paperless medical record.

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A working framework is presented for interdisciplinary professionals for designing, building, and evaluating clinical decision support rules (expert rules) within the electronic health record. The working framework outlines the key workflow processes for eight health system organizations for selecting, designing, building, activating, and evaluating rules. In preparation, an interdisciplinary team selected expert rules for their organizations. A physician, a nurse, and/or pharmacy informatics specialists led the team for each organization. The team chose from a catalog of expert rules that were supported by regulatory or clinical evidence. The design process ensured that each expert rule followed evidence-based guidelines and was programmed to automate steps in planning and delivering patient care. Expert rules were prioritized when improving the safety and quality of care. Finally, clinical decision support rules were evaluated for abilities to improve the consistency and currency of assessments and follow-through on patient findings from these assessments. The informatics specialists from each of the health system organizations also participated in a health system oversight group to construct the key processes for this beginning framework. The group refined the processes for the selection, design, construction, activation, and evaluation of expert rules over the past 3 years. These steps offered direction to subsequent clinic and hospital organizations in a similar situation. This case study identified four key considerations when implementing and evaluating the clinical decision support expert rules within care delivery. In summary, the processes for decision support expert rules required rigorous development and change control processes to support operation.

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