Computerized provider order entry (CPOE) with clinical decision support (CDS) can help hospitals improve care. Little is known about what CDS is presently in use and how it is managed, however, especially in community hospitals. This study sought to address this knowledge gap by identifying standard practices related to CDS in US community hospitals with mature CPOE systems.
Materials and Methods
Representatives of 34 community hospitals, each of which had over 5 years experience with CPOE, were interviewed to identify standard practices related to CDS. Data were analyzed with a mix of descriptive statistics and qualitative approaches to the identification of patterns, themes and trends.
This broad sample of community hospitals had robust levels of CDS despite their small size and the independent nature of many of their physician staff members. The hospitals uniformly used medication alerts and order sets, had sophisticated governance procedures for CDS, and employed staff to customize CDS.
The level of customization needed for most CDS before implementation was greater than expected. Customization requires skilled individuals who represent an emerging manpower need at this type of hospital.
These results bode well for robust diffusion of CDS to similar hospitals in the process of adopting CDS and suggest that national policies to promote CDS use may be successful.
Clinical; decision support systems; medical order entry systems
To conduct a grounded needs assessment to elicit community-based physicians' current views on clinical decision support (CDS) and its desired capabilities that may assist future CDS design and development for community-based practices.
Materials and methods
To gain insight into community-based physicians' goals, environments, tasks, and desired support tools, we used a human–computer interaction model that was based in grounded theory. We conducted 30 recorded interviews with, and 25 observations of, primary care providers within 15 urban and rural community-based clinics across Oregon. Participants were members of three healthcare organizations with different commercial electronic health record systems. We used a grounded theory approach to analyze data and develop a user-centered definition of CDS and themes related to desired CDS functionalities.
Physicians viewed CDS as a set of software tools that provide alerts, prompts, and reference tools, but not tools to support patient management, clinical operations, or workflow, which they would like. They want CDS to enhance physician–patient relationships, redirect work among staff, and provide time-saving tools. Participants were generally dissatisfied with current CDS capabilities and overall electronic health record usability.
Physicians identified different aspects of decision-making in need of support: clinical decision-making such as medication administration and treatment, and cognitive decision-making that enhances relationships and interactions with patients and staff.
Physicians expressed a need for decision support that extended beyond their own current definitions. To meet this requirement, decision support tools must integrate functions that align time and resources in ways that assist providers in a broad range of decisions.
Qualitative/ethnographic field study; biomedical informatics; developing/using clinical decision support (other than diagnostic) and guideline systems; knowledge acquisition and knowledge management; human-computer interaction and human-centered computing; social/organizational study; developing/using computerized provider order entry; you have; improving the education and skills training of health professionals; system implementation and management issues
Clinical decision support (CDS), defined broadly as patient-specific information and knowledge provided at the point of care, depends on a foundation of high quality electronic patient data. Little is known about how clinicians perceive the quality and value of data used to support CDS within an electronic health record (EHR) environment.
During a three-year research study, we collected ethnographic data from ten diverse organizations, including community hospitals, academic medical centers and ambulatory clinics.
An in-depth analysis of the theme “data as a foundation for CDS” yielded a descriptive framework incorporating five subthemes related to data quality: completeness, accessibility, context specificity, accuracy, and reliability.
We identified several multi-dimensional models that might be used to conceptualize data quality characteristics for future research. These results could provide new insights to system designers and implementers on the importance clinicians place on specific data quality characteristics regarding electronic patient data for CDS.
Following the IOM report, “Health IT and Patient Safety: Building Safer Systems for Better Care,” the Office of the National Coordinator for Health Information Technology sponsored a project to address safety concerns in electronic health record-enabled (EHR) healthcare systems. To address the complexity of EHR-related errors and the difficulty in eliminating them, we designed the SAFER project (Safety Assurance Factors for EHR Resilience) to proactively identify potential safety issues and best practices for addressing them. We take into account the full sociotechnical context of EHR implementation and use. Our iterative work is grounded in several recently developed informatics-based scientific methods including:
Review of scientific clinical informatics literatureUse of Rapid Assessment Process mixed-methods approaches developed for evaluating EHR-enabled healthcare systems in contextA semantic wiki for asynchronous collaborationAn 8-dimension socio-technical model of safe and effective EHR use
We are developing and piloting self-assessment “checklist-type” tools using a unique mix of methods based on the science of biomedical informatics. As the country continues its rapid EHR deployment, we believe that these tools are essential to ensure that the safety of the “EHR-enabled healthcare system” continues to improve.
Using an eight-dimensional model for studying socio-technical systems, a multidisciplinary team of investigators identified barriers and facilitators to clinical decision support (CDS) implementation in a community setting, the Mid-Valley Independent Physicians Association in the Salem, Oregon area. The team used the Rapid Assessment Process, which included nine formal interviews with CDS stakeholders, and observation of 27 clinicians. The research team, which has studied 21 healthcare sites of various sizes over the past 12 years, believes this site is an excellent example of an organization which is using a commercially available electronic-health-record system with CDS well. The eight-dimensional model proved useful as an organizing structure for the evaluation.
Developing/using computerized provider order entry; improving the education and skills training of health professionals; developing/using clinical decision support (other than diagnostic) and guideline systems; social/organizational study; qualitative/ethnographic field study; knowledge representations; classical experimental and quasi-experimental study methods (lab and field); designing usable (responsive) resources and systems; statistical analysis of large datasets; discovery and text and data mining methods; automated learning; human–computer interaction and human-centered computing; qualitative/ethnographic field study; clincal decision support; machine learning; knowledge bases; clinical decision support; ambulatory care; ambulatory care
Clinical decision support (CDS) is a valuable tool for improving healthcare quality and lowering costs. However, there is no comprehensive taxonomy of types of CDS and there has been limited research on the availability of various CDS tools across current electronic health record (EHR) systems.
To develop and validate a taxonomy of front-end CDS tools and to assess support for these tools in major commercial and internally developed EHRs.
Study design and methods
We used a modified Delphi approach with a panel of 11 decision support experts to develop a taxonomy of 53 front-end CDS tools. Based on this taxonomy, a survey on CDS tools was sent to a purposive sample of commercial EHR vendors (n=9) and leading healthcare institutions with internally developed state-of-the-art EHRs (n=4).
Responses were received from all healthcare institutions and 7 of 9 EHR vendors (response rate: 85%). All 53 types of CDS tools identified in the taxonomy were found in at least one surveyed EHR system, but only 8 functions were present in all EHRs. Medication dosing support and order facilitators were the most commonly available classes of decision support, while expert systems (eg, diagnostic decision support, ventilator management suggestions) were the least common.
We developed and validated a comprehensive taxonomy of front-end CDS tools. A subsequent survey of commercial EHR vendors and leading healthcare institutions revealed a small core set of common CDS tools, but identified significant variability in the remainder of clinical decision support content.
Developing/using computerized provider order entry; knowledge representations; classical experimental and quasi-experimental study methods (lab and field); designing usable (responsive) resources and systems; statistical analysis of large datasets; discovery; text and data mining methods; automated learning; human-computer interaction and human-centered computing; qualitative/ethnographic field study; clinical decision support; manning maddux; decision support; biomedical informatics; developing and refining EHR data standards (including image standards); controlled terminologies and vocabularies; measuring/improving patient safety and reducing medical errors; machine learning; electronic health records; meaningful use
Clinical decision support (CDS) is a powerful tool for improving healthcare quality and ensuring patient safety; however, effective implementation of CDS requires effective clinical and technical governance structures. The authors sought to determine the range and variety of these governance structures and identify a set of recommended practices through observational study.
Three site visits were conducted at institutions across the USA to learn about CDS capabilities and processes from clinical, technical, and organizational perspectives. Based on the results of these visits, written questionnaires were sent to the three institutions visited and two additional sites. Together, these five organizations encompass a variety of academic and community hospitals as well as small and large ambulatory practices. These organizations use both commercially available and internally developed clinical information systems.
Characteristics of clinical information systems and CDS systems used at each site as well as governance structures and content management approaches were identified through extensive field interviews and follow-up surveys.
Six recommended practices were identified in the area of governance, and four were identified in the area of content management. Key similarities and differences between the organizations studied were also highlighted.
Each of the five sites studied contributed to the recommended practices presented in this paper for CDS governance. Since these strategies appear to be useful at a diverse range of institutions, they should be considered by any future implementers of decision support.
The purpose of this study was to identify recommended practices for computerized clinical decision support (CDS) development and implementation and for knowledge management (KM) processes in ambulatory clinics and community hospitals using commercial or locally developed systems in the U.S.
Guided by the Multiple Perspectives Framework, the authors conducted ethnographic field studies at two community hospitals and five ambulatory clinic organizations across the U.S. Using a Rapid Assessment Process, a multidisciplinary research team: gathered preliminary assessment data; conducted on-site interviews, observations, and field surveys; analyzed data using both template and grounded methods; and developed universal themes. A panel of experts produced recommended practices.
The team identified ten themes related to CDS and KM. These include: 1) workflow; 2) knowledge management; 3) data as a foundation for CDS; 4) user computer interaction; 5) measurement and metrics; 6) governance; 7) translation for collaboration; 8) the meaning of CDS; 9) roles of special, essential people; and 10) communication, training, and support. Experts developed recommendations about each theme. The original Multiple Perspectives framework was modified to make explicit a new theoretical construct, that of Translational Interaction.
These ten themes represent areas that need attention if a clinic or community hospital plans to implement and successfully utilize CDS. In addition, they have implications for workforce education, research, and national-level policy development. The Translational Interaction construct could guide future applied informatics research endeavors.
This case report describes a qualitative investigation into how a Hands-free Communication Device (HCD) system impacted communication among anesthesia staff in a pediatric surgical suite. The authors recruited a purposive sample that included anesthesiologists, certified registered nurse anesthetists, circulating nurses, a charge nurse, and a postanesthesia care unit nurse. Data were collected using semistructured interviews and observations, then analyzed using a constant comparison approach. The results corroborate and enrich themes that were discovered in a previous qualitative study of HCD systems: (1) communication access, (2) control, (3) training, (4) environment and infrastructure. The results also generated new subthemes and themes: (1) technical control, (2) choosing communication channels, and (3) reliability. The authors conclude that HCD systems profoundly impacted communication in a largely positive way, although reliability of the technology remained an issue. The authors' findings contribute a valuable insight into the growing body of knowledge about implementation and use of HCD systems.
Federal legislation (Health Information Technology for Economic and Clinical Health (HITECH) Act) has provided funds to support an unprecedented increase in health information technology (HIT) adoption for healthcare provider organizations and professionals throughout the U.S. While recognizing the promise that widespread HIT adoption and meaningful use can bring to efforts to improve the quality, safety, and efficiency of healthcare, the American Medical Informatics Association devoted its 2009 Annual Health Policy Meeting to consideration of unanticipated consequences that could result with the increased implementation of HIT. Conference participants focused on possible unintended and unanticipated, as well as undesirable, consequences of HIT implementation. They employed an input–output model to guide discussion on occurrence of these consequences in four domains: technical, human/cognitive, organizational, and fiscal/policy and regulation. The authors outline the conference's recommendations: (1) an enhanced research agenda to guide study into the causes, manifestations, and mitigation of unintended consequences resulting from HIT implementations; (2) creation of a framework to promote sharing of HIT implementation experiences and the development of best practices that minimize unintended consequences; and (3) recognition of the key role of the Federal Government in providing leadership and oversight in analyzing the effects of HIT-related implementations and policies.
We have carried out an extensive qualitative research program focused on the barriers and facilitators to successful adoption and use of various features of advanced, state-of-the-art electronic health records (EHRs) within large, academic, teaching facilities with long-standing EHR research and development programs. We have recently begun investigating smaller, community hospitals and out-patient clinics that rely on commercially-available EHRs. We sought to assess whether the current generation of commercially-available EHRs are capable of providing the clinical knowledge management features, functions, tools, and techniques required to deliver and maintain the clinical decision support (CDS) interventions required to support the recently defined "meaningful use" criteria.
We developed and fielded a 17-question survey to representatives from nine commercially available EHR vendors and four leading internally developed EHRs. The first part of the survey asked basic questions about the vendor's EHR. The second part asked specifically about the CDS-related system tools and capabilities that each vendor provides. The final section asked about clinical content.
All of the vendors and institutions have multiple modules capable of providing clinical decision support interventions to clinicians. The majority of the systems were capable of performing almost all of the key knowledge management functions we identified.
If these well-designed commercially-available systems are coupled with the other key socio-technical concepts required for safe and effective EHR implementation and use, and organizations have access to implementable clinical knowledge, we expect that the transformation of the healthcare enterprise that so many have predicted, is achievable using commercially-available, state-of-the-art EHRs.
To analyze the effects that hands-free communication device (HCD) systems have on healthcare organizations from multiple user perspectives.
This exploratory qualitative study recruited 26 subjects from multiple departments in two research sites located in Portland, Oregon: an academic medical center and a community hospital. Interview and observation data were gathered January through March, 2007.
Data were analyzed using a grounded theory approach. Because this study was exploratory, data were coded and patterns identified until overall themes ‘emerged’.
Five themes arose: (1) Communication access—the perception that HCD systems provide fast and efficient communication that supports workflow; (2) Control—social and technical considerations associated with use of an HCD system; (3) Training—processes that should be used to improve use of the HCD system; (4) Organizational change—changes to organizational design and behavior caused by HCD system implementation; and (5) Environment and infrastructure—HCD system use within the context of physical workspaces.
HCD systems improve communication access but users experience challenges integrating the system into workflow. Effective HCD use depends on how well organizations train users, adapt to changes brought about by HCD systems, and integrate HCD systems into physical surroundings.
To explore the need for, and use of, high-quality, collaborative, clinical knowledge management (CKM) tools and techniques to manage clinical decision support content.
In order to better understand the current state of the art in CKM, we developed a survey of potential CKM tools and techniques. We conducted an exploratory study by querying a convenience sample of respondents about their use of specific practices in CKM.
The following tools and techniques should be priorities in organizations interested in developing successful computer-based provider order entry (CPOE) and clinical decision support (CDS) implementations: 1) A multidisciplinary team responsible for creating and maintaining the clinical content; 2) An external organizational repository of clinical content with web-based viewer that allows anyone in the organization to review it; 3) An online, collaborative, interactive, internet-based tool to facilitate content development; 4) An enterprise-wide tool to maintain the controlled clinical terminology concepts. Even organizations that have been successfully using Computer-based Provider Order Entry with advanced Clinical Decision Support features for well over 15 years are not using all of the CKM tools or practices that we identified.
If we are to further stimulate progress in the area of clinical decision support, we must continue to develop and refine our understanding and use of advanced CKM capabilities.
In prior work, using a Rapid Assessment Process (RAP), we have investigated clinical decision support (CDS) in ambulatory clinics and hospitals. We realized that individuals in these settings provide only one perspective related to the CDS landscape, which also includes content vendors and electronic health record (EHR) vendors. To discover content vendors’ perspectives and their perceived challenges, we modified RAP for industrial settings. We describe how we employed RAP, and show its utility by describing two illustrative themes. We found that while the content vendors believe they provide unique much-needed services, the amount of labor involved in content development is underestimated by others. We also found that the content vendors believe their products are resources to be used by practitioners, so they are somewhat protected from liability issues. To promote adequate understanding about these issues, we recommend a “three way conversation” among content vendors, EHR vendors, and user organizations.
To describe the foci, activities, methods, and results of a four-year research project identifying the unintended consequences of computerized provider order entry (CPOE).
Using a mixed methods approach, we identified and categorized into nine types 380 examples of the unintended consequences of CPOE gleaned from fieldwork data and a conference of experts. We then conducted a national survey in the U.S.A. to discover how hospitals with varying levels of infusion, a measure of CPOE sophistication, recognize and deal with unintended consequences. The research team, with assistance from experts, identified strategies for managing the nine types of unintended adverse consequences and developed and disseminated tools for CPOE implementers to help in addressing these consequences.
Hospitals reported that levels of infusion are quite high and that these types of unintended consequences are common. Strategies for avoiding or managing the unintended consequences are similar to best practices for CPOE success published in the literature.
Development of a taxonomy of types of unintended adverse consequences of CPOE using qualitative methods allowed us to craft a national survey and discover how widespread these consequences are. Using mixed methods, we were able to structure an approach for addressing the skillful management of unintended consequences as well.
Attitude to computers; Hospital information systems; User-computer interface; Physician order entry
The most effective decision support systems are integrated with clinical information systems, such as inpatient and outpatient electronic health records (EHRs) and computerized provider order entry (CPOE) systems.
The goal of this project was to describe and quantify the results of a study of decision support capabilities in Certification Commission for Health Information Technology (CCHIT) certified electronic health record systems.
The authors conducted a series of interviews with representatives of nine commercially available clinical information systems, evaluating their capabilities against 42 different clinical decision support features.
Six of the nine reviewed systems offered all the applicable event-driven, action-oriented, real-time clinical decision support triggers required for initiating clinical decision support interventions. Five of the nine systems could access all the patient-specific data items identified as necessary. Six of the nine systems supported all the intervention types identified as necessary to allow clinical information systems to tailor their interventions based on the severity of the clinical situation and the user's workflow. Only one system supported all the offered choices identified as key to allowing physicians to take action directly from within the alert.
The principal finding relates to system-by-system variability. The best system in our analysis had only a single missing feature (from 42 total) while the worst had eighteen.This dramatic variability in CDS capability among commercially available systems was unexpected and is a cause for concern.
These findings have implications for four distinct constituencies: purchasers of clinical information systems, developers of clinical decision support, vendors of clinical information systems and certification bodies.
To identify and describe unintended adverse consequences related to clinical workflow when implementing or using computerized provider order entry (CPOE) systems.
We analyzed qualitative data from field observations and formal interviews gathered over a three-year period at five hospitals in three organizations. Five multidisciplinary researchers worked together to identify themes related to the impacts of CPOE systems on clinical workflow.
CPOE systems can affect clinical work by 1) introducing or exposing human/computer interaction problems, 2) altering the pace, sequencing, and dynamics of clinical activities, 3) providing only partial support for the work activities of all types of clinical personnel, 4) reducing clinical situation awareness, and 5) poorly reflecting organizational policy and procedure.
As CPOE systems evolve, those involved must take care to mitigate the many unintended adverse effects these systems have on clinical workflow. Workflow issues resulting from CPOE can be mitigated by iteratively altering both clinical workflow and the CPOE system until a satisfactory fit is achieved.
attitude to computers; hospital information systems; user–computer interface; physician order entry
Health Information Technology Systems (HITS) are becoming more widely integrated into patient care in the dental school setting. The purpose of this study was to evaluate the impact of a chairside HITS on users in the dental school setting. Qualitative techniques, including interviews, focus groups and observations, were used. Using grounded theory, we saw 9 themes emerge. One theme of particular interest was that “training and support needs of end-users were significant.” This paper explores this theme in detail and discusses the implications.
Clinical Decision Support (CDS) is viewed as a means to improve safety and efficiency in health care. Yet the lack of consensus about what is meant by CDS represents a barrier to effective design, implementation, and utilization of CDS tools. We conducted a multi-site qualitative inquiry to understand how different people define and describe CDS. Using subjects’ multiple perspectives we were able to gain new insights as to what stakeholders want CDS to achieve and how to achieve it even when those perspectives are competing and conflicting.
Clinical Decision Support (CDS) is viewed as a means to improve safety and efficiency in health care. Yet the lack of a consensus around what is meant by CDS represents a barrier to effective design, use, and utilization of CDS tools. We conducted a multi-site qualitative inquiry to understand how different people define and describe CDS. Using subjects’ multiple perspectives we were able to gain new insights as to what stakeholders want CDS to achieve and how to achieve it; even at times when those perspectives are competing and conflicting.
To determine what “average” clinicians in organizations that were about to implement Computer-based Provider Order Entry (CPOE) were expecting to occur, we conducted an open-ended, semi-structured survey at three community hospitals.
We created an open-ended, semi-structured, interview survey template that we customized for each organization. This interview-based survey was designed to be administered orally to clinicians and take approximately five minutes to complete, although clinicians were allowed to discuss as many advantages or disadvantages of the impending system roll-out as they wanted to.
Our survey findings did not reveal any overly negative, critical, problematic, or striking sets of concerns. However, from the standpoint of unintended consequences, we found that clinicians were anticipating only a few of the events, emotions, and process changes that are likely to result from CPOE.
The results of such an open-ended survey may prove useful in helping CPOE leaders to understand user perceptions and predictions about CPOE, because it can expose issues about which more communication, or discussion, is needed. Using the survey, implementation strategies and management techniques outlined in this paper, any chief information officer (CIO) or chief medical information officer (CMIO) should be able to adequately assess their organization's CPOE readiness, make the necessary mid-course corrections, and be prepared to deal with the currently identified unintended consequences of CPOE should they occur.
Medical Order Entry Systems; Ethnology; Hospitals, Community; Medical Informatics
There is a pressing need for high-quality, effective means of designing, developing, presenting, implementing, evaluating, and maintaining all types of clinical decision support capabilities for clinicians, patients and consumers. Using an iterative, consensus-building process we identified a rank-ordered list of the top 10 grand challenges in clinical decision support. This list was created to educate and inspire researchers, developers, funders, and policy-makers. The list of challenges in order of importance that they be solved if patients and organizations are to begin realizing the fullest benefits possible of these systems consists of: Improve the human-computer interface; Disseminate best practices in CDS design, development, and implementation; Summarize patient-level information; Prioritize and filter recommendations to the user; Create an architecture for sharing executable CDS modules and services; Combine recommendations for patients with co-morbidities; Prioritize CDS content development and implementation; Create internet-accessible clinical decision support repositories; Use freetext information to drive clinical decision support; Mine large clinical databases to create new CDS. Identification of solutions to these challenges is critical if clinical decision support is to achieve its potential and improve the quality, safety and efficiency of healthcare.
How does paper usage change following the introduction of Computerized Physician Order Entry and the Electronic Medical Record (EMR/CPOE)? To answer that question we analyzed data collected from fourteen sites across the U.S. We found paper in widespread use in all institutions we studied. Analysis revealed psychological, ergonomic, technological, and regulatory reasons for the persistence of paper in an electronic environment. Paper has unique attributes allowing it to fill gaps in information timeliness, availability, and reliability in pursuit of improved patient care. Creative uses have led to “better paper.”
We are investigating the development, implementation and evaluation of clinical decision support (CDS) projects to advance our understanding of how best to incorporate these interventions into the delivery of healthcare. Our overall goal is to explore how the translation of clinical knowledge into CDS and its incorporation into practice can be routinely achieved to improve the quality of healthcare delivered in the U.S.A. Toward this end, we have developed a 7-step model that provides a framework for clinical decision support-related standards that are necessary if we wish to achieve these goals. We believe that if all commercially available EHR systems had the features and functions described in these recommendations, many more healthcare organizations could begin to develop and implement the basic CDS features that are necessary to radically transform the quality, safety, and cost of the current healthcare system.