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.
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.
The US FDA has been collecting information on medical devices involved in significant adverse advents since 1984. These reports have been used by researchers to advise clinicians on potential risks and complications of using these devices.
Research adverse events related to the use of Clinical Information Systems (CIS) as reported in FDA databases.
Three large, national, adverse event medical device databases were examined for reports pertaining to CIS.
One hundred and twenty unique reports (from over 1.4 million reports) were found, representing 32 manufacturers. The manifestations of these adverse events included: missing or incorrect data, data displayed for the wrong patient, chaos during system downtime and system unavailable for use. Analysis of these reports illustrated events associated with system design, implementation, use, and support.
The identified causes can be used by manufacturers to improve their products and by clinical facilities and providers to adjust their workflow and implementation processes appropriately. The small number of reports found indicates a need to raise awareness regarding publicly available tools for documenting problems with CIS and for additional reporting and dialog between manufacturers, organizations, and users.
Electronic Health Records; Information Systems; Mandatory Reporting; Medical Errors; United States Food and Drug Administration
Successful subspecialty referrals require considerable coordination and interactive communication among the primary care provider (PCP), the subspecialist, and the patient, which may be challenging in the outpatient setting. Even when referrals are facilitated by electronic health records (EHRs) (i.e., e-referrals), lapses in patient follow-up might occur. Although compelling reasons exist why referral coordination should be improved, little is known about which elements of the complex referral coordination process should be targeted for improvement. Using Okhuysen & Bechky's coordination framework, this paper aims to understand the barriers, facilitators, and suggestions for improving communication and coordination of EHR-based referrals in an integrated healthcare system.
We conducted a qualitative study to understand coordination breakdowns related to e-referrals in an integrated healthcare system and examined work-system factors that affect the timely receipt of subspecialty care. We conducted interviews with seven subject matter experts and six focus groups with a total of 30 PCPs and subspecialists at two tertiary care Department of Veterans Affairs (VA) medical centers. Using techniques from grounded theory and content analysis, we identified organizational themes that affected the referral process.
Four themes emerged: lack of an institutional referral policy, lack of standardization in certain referral procedures, ambiguity in roles and responsibilities, and inadequate resources to adapt and respond to referral requests effectively. Marked differences in PCPs' and subspecialists' communication styles and individual mental models of the referral processes likely precluded the development of a shared mental model to facilitate coordination and successful referral completion. Notably, very few barriers related to the EHR were reported.
Despite facilitating information transfer between PCPs and subspecialists, e-referrals remain prone to coordination breakdowns. Clear referral policies, well-defined roles and responsibilities for key personnel, standardized procedures and communication protocols, and adequate human resources must be in place before implementing an EHR to facilitate referrals.
Notifying clinicians about abnormal test results through electronic health record (EHR) -based "alert" notifications may not always lead to timely follow-up of patients. We sought to understand barriers, facilitators, and potential interventions for safe and effective management of abnormal test result delivery via electronic alerts.
We conducted a qualitative study consisting of six 6-8 member focus groups (N = 44) at two large, geographically dispersed Veterans Affairs facilities. Participants included full-time primary care providers, and personnel representing diagnostic services (radiology, laboratory) and information technology. We asked participants to discuss barriers, facilitators, and suggestions for improving timely management and follow-up of abnormal test result notifications and encouraged them to consider technological issues, as well as broader, human-factor-related aspects of EHR use such as organizational, personnel, and workflow.
Providers reported receiving a large number of alerts containing information unrelated to abnormal test results, many of which were believed to be unnecessary. Some providers also reported lacking proficiency in use of certain EHR features that would enable them to manage alerts more efficiently. Suggestions for improvement included improving display and tracking processes for critical alerts in the EHR, redesigning clinical workflow, and streamlining policies and procedures related to test result notification.
Providers perceive several challenges for fail-safe electronic communication and tracking of abnormal test results. A multi-dimensional approach that addresses technology as well as the many non-technological factors we elicited is essential to design interventions to reduce missed test results in EHRs.
Decision Support Systems; Clinical; Automated notification; diagnostic errors; abnormal diagnostic test results; Medical Records Systems; Computerized; patient follow-up; patient safety; health information technology; communication; primary care
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.
The United States (US) Health Information Technology for Economic and Clinical Health Act of 2009 has spurred adoption of electronic health records. The corresponding meaningful use criteria proposed by the Centers for Medicare and Medicaid Services mandates use of computerized provider order entry (CPOE) systems. Yet, adoption in the US and other Western countries is low and descriptions of successful implementations are primarily from the inpatient setting; less frequently the ambulatory setting. We describe prescriber and staff perceptions of implementation of a CPOE system for medications (electronic- or e-prescribing system) in the ambulatory setting.
Using a cross-sectional study design, we conducted eight focus groups at three primary care sites in an independent medical group. Each site represented a unique stage of e-prescribing implementation - pre/transition/post. We used a theoretically based, semi-structured questionnaire to elicit physician (n = 17) and staff (n = 53) perceptions of implementation of the e-prescribing system. We conducted a thematic analysis of focus group discussions using formal qualitative analytic techniques (i.e. deductive framework and grounded theory). Two coders independently coded to theoretical saturation and resolved discrepancies through discussions.
Ten themes emerged that describe perceptions of e-prescribing implementation: 1) improved availability of clinical information resulted in prescribing efficiencies and more coordinated care; 2) improved documentation resulted in safer care; 3) efficiencies were gained by using fewer paper charts; 4) organizational support facilitated adoption; 5) transition required time; resulted in workload shift to staff; 6) hardware configurations and network stability were important in facilitating workflow; 7) e-prescribing was time-neutral or time-saving; 8) changes in patient interactions enhanced patient care but required education; 9) pharmacy communications were enhanced but required education; 10) positive attitudes facilitated adoption.
Prescribers and staff worked through the transition to successfully adopt e-prescribing, and noted the benefits. Overall impressions were favorable. No one wished to return to paper-based prescribing.
Bar coded medication administration (BCMA), the automated electronic verification of medications by nurses at the patient bedside, provides an additional layer of safety to the process of medication administration in the hospital setting. We performed a retrospective, descriptive study of BCMA alerts for elevated potassium (>5.5 mg/dL) in place within a multihospital healthcare system. Overall, 642 BCMA alerts were analyzed with a 21.3% acceptance rate. In subgroup analysis, we found that the BCMA acceptance rate was 6.9% for patients aged less than one year, and 85.6% for patients aged greater than one year. The major contributing factor to the low overall acceptance rate was the high frequency of alerts in patients less than 1 year of age. Modifications to rules logic may be necessary for this specific population. While BCMA alerts can beneficial, they should be carefully implemented with periodic post-implementation analysis and refinement.
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
Health information technology and electronic medical records (EMRs) are potentially powerful systems-based interventions to facilitate diagnosis and treatment because they ensure the delivery of key new findings and other health related information to the practitioner. However, effective communication involves more than just information transfer; despite a state of the art EMR system, communication breakdowns can still occur. [1-3] In this project, we will adapt a model developed by the Systems Engineering Initiative for Patient Safety (SEIPS) to understand and improve the relationship between work systems and processes of care involved with electronic communication in EMRs. We plan to study three communication activities in the Veterans Health Administration's (VA) EMR: electronic communication of abnormal imaging and laboratory test results via automated notifications (i.e., alerts); electronic referral requests; and provider-to-pharmacy communication via computerized provider order entry (CPOE).
Our specific aim is to propose a protocol to evaluate the systems and processes affecting outcomes of electronic communication in the computerized patient record system (related to diagnostic test results, electronic referral requests, and CPOE prescriptions) using a human factors engineering approach, and hence guide the development of interventions for work system redesign.
This research will consist of multiple qualitative methods of task analysis to identify potential sources of error related to diagnostic test result alerts, electronic referral requests, and CPOE; this will be followed by a series of focus groups to identify barriers, facilitators, and suggestions for improving the electronic communication system. Transcripts from all task analyses and focus groups will be analyzed using methods adapted from grounded theory and content analysis.
Objectives: Computer-based provider order entry (CPOE) systems are implemented to increase both efficiency and accuracy in health care, but these systems often cause a myriad of emotions to arise. This qualitative research investigates the emotions surrounding CPOE implementation and use.
Methods: We performed a secondary analysis of several previously collected qualitative data sets from interviews and observations of over 50 individuals. Three researchers worked in parallel to identify themes that expressed emotional responses to CPOE. We then reviewed and classified these quotes using a validated hierarchical taxonomy of semantically homogeneous terms associated with specific emotions.
Results: The implementation and use of CPOE systems provoked examples of positive, negative, and neutral emotions. Negative emotional responses were the most prevalent, by far, in all the observations.
Conclusion: Designing and implementing CPOE systems is difficult. These systems and the implementation process itself often inspire intense emotions. If designers and implementers fail to recognize that various CPOE features and implementation strategies can increase clinicians' negative emotions, then the systems may fail to become a routine part of the clinical care delivery process. We might alleviate some of these problems by designing positive feedback mechanisms for both the systems and the organizations.
Real-time clinical decision support (CDS) integrated into clinicians' workflow has the potential to profoundly affect the cost, quality, and safety of health care delivery. Recent reports have identified a surprisingly low acceptance rate for different types of CDS. We hypothesized that factors affecting CDS system acceptance could be categorized as relating to differences in patients, physicians, CDS-type, or environmental characteristics.
We conducted a survey of all adult primary care physicians (PCPs, n = 225) within our group model Health Maintenance Organization (HMO) to identify factors that affect their acceptance of CDS. We defined clinical decision support broadly as "clinical information" that is either provided to you or accessible by you, from the clinical workstation (e.g., enhanced flow sheet displays, health maintenance reminders, alternative medication suggestions, order sets, alerts, and access to any internet-based information resources).
110 surveys were returned (49%). There were no differences in the age, gender, or years of service between those who returned the survey and the entire adult PCP population. Overall, clinicians stated that the CDS provided "helps them take better care of their patients" (3.6 on scale of 1:Never – 5:Always), "is worth the time it takes" (3.5), and "reminds them of something they've forgotten" (3.2). There was no difference in the perceived acceptance rate of alerts based on their type (i.e., cost, safety, health maintenance). When asked about specific patient characteristics that would make the clinicians "more", "equally" or "less" likely to accept alerts: 41% stated that they were more (8% stated "less") likely to accept alerts on elderly patients (> 65 yrs); 38% were more (14% stated less) likely to accept alerts on patients with more than 5 current medications; and 38% were more (20% stated less) likely to accept alerts on patients with more than 5 chronic clinical conditions. Interestingly, 80% said they were less likely to accept alerts when they were behind schedule and 84% of clinicians admitted to being at least 20 minutes behind schedule "some", "most", or "all of the time".
Even though a majority of our clinical decision support suggestions are not explicitly followed, clinicians feel they are of benefit and would be even more beneficial if they had more time available to address them.
American public policy makers recently established the goal of providing the majority of Americans with electronic health records by 2014. This will require a National Health Information Infrastructure (NHII) that is far more complete than the one that is currently in its formative stage of development. We describe a conceptual framework to help measure progress toward that goal.
The NHII comprises a set of clusters, such as Regional Health Information Organizations (RHIOs), which, in turn, are composed of smaller clusters and nodes such as private physician practices, individual hospitals, and large academic medical centers. We assess progress in terms of the availability and use of information and communications technology and the resulting effectiveness of these implementations. These three attributes can be studied in a phased approach because the system must be available before it can be used, and it must be used to have an effect. As the NHII expands, it can become a tool for evaluating itself.
The NHII has the potential to transform health care in America – improving health care quality, reducing health care costs, preventing medical errors, improving administrative efficiencies, reducing paperwork, and increasing access to affordable health care. While the President has set an ambitious goal of assuring that most Americans have electronic health records within the next 10 years, a significant question remains "How will we know if we are making progress toward that goal?" Using the definitions for "nodes" and "clusters" developed in this article along with the resulting measurement framework, we believe that we can begin a discussion that will enable us to define and then begin making the kinds of measurements necessary to answer this important question.
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
Email is the most important mechanism introduced since the telephone for developing interpersonal relationships. This study was designed to provide insight into how patients are using email to request information or services from their healthcare providers.
Following IRB approval, we reviewed all electronic mail (e-mail) messages sent between five study clinicians and their patients over a one-month period. We used a previously described taxonomy of patient requests to categorize all patient requests contained in the messages. We measured message volume, frequency, length and response time for all messages sent to and received by these clinicians.
On average the 5 physicians involved in this study received 40 messages per month, each containing approximately 139 words. Replies sent by the physicians contained 39 words on average and 59.4% of them were sent within 24 hours. Patients averaged 1 request per message. Requests for information on medications or treatments, specific symptoms or diseases, and requests for actions regarding medications or treatments accounted for 75% of all requests. Physicians fulfilled 80.2% of all these requests. Upon comparison of these data to that obtained from traditional office visits, it appears that the potential exists for email encounters to substitute for some percentage of office visits.
Electronic messaging is an important method for physicians and patients to communicate and further develop their relationship. While many physicians worry that either the number or length of messages from their patients will overwhelm them, there is no evidence to support this. In fact, the evidence suggests that many patient requests, formerly made over the telephone or during office visits, can be addressed via email thus potentially saving both patients and physicians time.
Electronic health records (EHRs) facilitate several innovations capable of reforming health care. Despite their promise, many currently unanswered legal, ethical, and financial questions threaten the widespread adoption and use of EHRs. Key legal dilemmas that must be addressed in the near-term pertain to the extent of clinicians' responsibilities for reviewing the entire computer-accessible clinical synopsis from multiple clinicians and institutions, the liabilities posed by overriding clinical decision support warnings and alerts, and mechanisms for clinicians to publically report potential EHR safety issues. Ethical dilemmas that need additional discussion relate to opt-out provisions that exclude patients from electronic record storage, sale of deidentified patient data by EHR vendors, adolescent control of access to their data, and use of electronic data repositories to redesign the nation's health care delivery and payment mechanisms on the basis of statistical analyses. Finally, one overwhelming financial question is who should pay for EHR implementation because most users and current owners of these systems will not receive the majority of benefits. The authors recommend that key stakeholders begin discussing these issues in a national forum. These actions can help identify and prioritize solutions to the key legal, ethical, and financial dilemmas discussed, so that widespread, safe, effective, interoperable EHRs can help transform health care.
electronic health records; ethics; medical; confidentiality
Effective clinical decision support (CDS) is essential for addressing healthcare performance improvement imperatives, but care delivery organizations (CDO) typically struggle with CDS deployment. Ensuring safe and effective medication delivery to patients is a central focus of CDO performance improvement efforts, and this article provides an overview of best-practice strategies for applying CDS to these goals. The strategies discussed are drawn from a new guidebook, co-published and co-sponsored by more than a dozen leading organizations. Developed by scores of CDS implementers and experts, the guidebook outlines key steps and success factors for applying CDS to medication management. A central thesis is that improving outcomes with CDS interventions requires that the CDS five rights be addressed successfully. That is, the interventions must deliver the right information, to the right person, in the right format, through the right channel, at the right point in workflow. This paper provides further details about these CDS five rights, and highlights other important strategies for successful CDS programs.
Clinical decision support; medication management; performance improvement
Clinical summarization, the process by which relevant patient information is electronically summarized and presented at the point of care, is of increasing importance given the increasing volume of clinical data in electronic health record systems (EHRs). There is a paucity of research on electronic clinical summarization, including the capabilities of currently available EHR systems.
We compared different aspects of general clinical summary screens used in twelve different EHR systems using a previously described conceptual model: AORTIS (Aggregation, Organization, Reduction, Interpretation and Synthesis).
We found a wide variation in the EHRs’ summarization capabilities: all systems were capable of simple aggregation and organization of limited clinical content, but only one demonstrated an ability to synthesize information from the data.
Improvement of the clinical summary screen functionality for currently available EHRs is necessary. Further research should identify strategies and methods for creating easy to use, well-designed clinical summary screens that aggregate, organize and reduce all pertinent patient information as well as provide clinical interpretations and synthesis as required.
Electronic Health Records; Clinical Summarization; User Interface
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.
Electronic health records (EHR) enable transmission and tracking of referrals between primary-care practitioners (PCPs) and subspecialists. We used an EHR to examine follow-up actions on electronic referral communication in a large multispecialty VA facility.
We retrieved outpatient referrals to five subspecialties between October 2006 and December 2007, and queried the EHR to determine their status: completed, discontinued (returned to PCP), or unresolved (no action taken by subspecialist). All unresolved referrals, and random samples of discontinued and completed referrals were reviewed to determine whether subspecialists took follow-up actions (i.e., schedule appointments anytime in the future) within 30 days of referral-receipt. For referrals without timely follow-up, we determined whether inaction was supported by any predetermined justifiable reasons or associated with certain referral characteristics. We also reviewed if PCPs took the required action on returned information.
Of 61,931 referrals, 22,535 were discontinued (36.4%), and 474 were unresolved (0.8%). We selected 412 discontinued referrals randomly for review. Of these, 52% lacked follow-up actions within 30 days. Appropriate justifications for inaction were documented in 69.8% (150/215) of those without action and included lack of prerequisite testing by the PCP and subspecialist opinion that no intervention was required despite referral. We estimated that at 30 days, 6.3% of all referrals were associated with an unexplained lack of follow-up actions by subspecialists. Conversely, 7.4% of discontinued referrals returned to PCPs were associated with an unexplained lack of follow-up.
Although the EHR facilitates transmission of valuable information at the PCP-subspecialist interface, unexplained communication breakdowns in the referral process persist in a subset of cases.
referrals; primary care; sub-specialty care; electronic health records; patient safety; health information technology; communication; diagnostic errors; patient follow-up
Conceptual models have been developed to address challenges inherent in studying health information technology (HIT). This manuscript introduces an 8-dimensional model specifically designed to address the socio-technical challenges involved in design, development, implementation, use, and evaluation of HIT within complex adaptive healthcare systems. The 8 dimensions are not independent, sequential, or hierarchical, but rather are interdependent and interrelated 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 assuring that patient care tasks are carried out effectively. Two additional dimensions of the model are internal organizational features (e.g., 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.
Decision Support Systems; Clinical; Automated notification; diagnostic errors; abnormal diagnostic test results; Medical Records Systems; Computerized; patient follow-up; patient safety; health information technology; communication; primary care