OBJECTIVE: Understand the perceived role of electronic health records (EHR) and workflow fragmentation on clinician documentation burden in the emergency department (ED). METHODS: From February to June 2022, we conducted semistructured interviews among a national sample of US prescribing providers and registered nurses who actively practice in the adult ED setting and use Epic Systems' EHR. We recruited participants through professional listservs, social media, and email invitations sent to healthcare professionals. We analyzed interview transcripts using inductive thematic analysis and interviewed participants until we achieved thematic saturation. We finalized themes through a consensus-building process. RESULTS: We conducted interviews with 12 prescribing providers and 12 registered nurses. Six themes were identified related to EHR factors perceived to contribute to documentation burden including lack of advanced EHR capabilities, absence of EHR optimization for clinicians, poor user interface design, hindered communication, increased manual work, and added workflow blockages, and five themes associated with cognitive load. Two themes emerged in the relationship between workflow fragmentation and EHR documentation burden: underlying sources and adverse consequences. DISCUSSION: Obtaining further stakeholder input and consensus is essential to determine whether these perceived burdensome EHR factors could be extended to broader contexts and addressed through optimizing existing EHR systems alone or through a broad overhaul of the EHR's architecture and primary purpose. CONCLUSION: While most clinicians perceived that the EHR added value to patient care and care quality, our findings underscore the importance of designing EHRs that are in harmony with ED clinical workflows to alleviate the clinician documentation burden.

OBJECTIVE: To describe real-world practices and variation in implementation of the Information Blocking provisions amongst healthcare organizations caring for pediatric patients. MATERIALS AND METHODS: An online survey regarding implementation practices was distributed to representatives from 10 participating US healthcare organizations located in 6 different states. The survey was followed by structured interviews conducted through video conference. Information was gathered about implementation practices at each organization, with a focus on patient and proxy portal access to, and segmentation capabilities of, certain data classes listed in the United States Core Data for Interoperability Version 1. RESULTS: All organizations had implemented the information blocking provisions at their institution. All organizations utilized different portal account types for proxies and users. All organizations reported the capability of sharing labs, medications, problem lists, imaging, and notes with the parent/guardian of the non-adolescent minor user with differences in how sensitive elements within the data classes were protected. Variability existed in how data was shared with the remaining user types. DISCUSSION: Significant variability exists in how organizations have implemented the information blocking rules. Variation in data sharing and data access between institutions can result in privacy breaches and create confusion about completeness of data for patients and families. CONCLUSION: Healthcare organizations have utilized varying strategies to comply with the information blocking provisions of the 21st Century Cures Act. Increased clarity from the Office of the National Coordinator for Health Information Technology on minor, adolescent, and caregiver privacy and improved segmentation capabilities from Electronic Health Record vendors is needed.

The lesbian, gay, bisexual, transgender, queer, or questioning (LGBTQ+) community is vulnerable to health-care disparities. Many health-care organizations are working to collect sexual orientation and gender identity in their electronic health records (EHRs), with the goal of providing more inclusive care to their LGBTQ+ patients. There are significant human and technical barriers to making these efforts successful. Based on our 5-year experience at Geisinger (an integrated health system located in a rural, generally conservative area), this case report provides insights to overcome challenges in 4 critical areas: (1) enabling the EHR to collect and use information to support the health-care needs of LGBTQ+ patients, (2) building a culture of awareness and caring, empowering members of the health-care team to break down barriers of misunderstanding and mistrust, (3) developing services to support the needs of LGBTQ+ patients, and (4) partnering with local communities to become a trusted health-care provider.

Digital medical records have enabled us to employ clinical data in many new and innovative ways. However, these advances have brought with them a complex set of demands for healthcare institutions regarding data sharing with topics such as data ownership, the loss of privacy, and the protection of the intellectual property. The lack of clear guidance from government entities often creates conflicting messages about data policy, leaving institutions to develop guidelines themselves. Through discussions with multiple stakeholders at various institutions, we have generated a set of guidelines with 10 key principles to guide the responsible and appropriate use and sharing of clinical data for the purposes of care and discovery. Industry, universities, and healthcare institutions can build upon these guidelines toward creating a responsible, ethical, and practical response to data sharing.

Objective: To determine the effects of an inpatient portal intervention on patient activation, patient satisfaction, patient engagement with health information, and 30-day hospital readmissions. Methods and Materials: From March 2014 to May 2017, we enrolled 426 English- or Spanish-speaking patients from 2 cardiac medical-surgical units at an urban academic medical center. Patients were randomized to 1 of 3 groups: 1) usual care, 2) tablet with general Internet access (tablet-only), and 3) tablet with an inpatient portal. The primary study outcome was patient activation (Patient Activation Measure-13). Secondary outcomes included all-cause readmission within 30 days, patient satisfaction, and patient engagement with health information. Results: There was no evidence of a difference in patient activation among patients assigned to the inpatient portal intervention compared to usual care or the tablet-only group. Patients in the inpatient portal group had lower 30-day hospital readmissions (5.5% vs. 12.9% tablet-only and 13.5% usual care; P = 0.044). There was evidence of a difference in patient engagement with health information between the inpatient portal and tablet-only group, including looking up health information online (89.6% vs. 51.8%; P < 0.001). Healthcare providers reported that patients found the portal useful and that the portal did not negatively impact healthcare delivery. Conclusions: Access to an inpatient portal did not significantly improve patient activation, but it was associated with looking up health information online and with a lower 30-day hospital readmission rate. These results illustrate benefit of providing hospitalized patients with real-time access to their electronic health record data while in the hospital. Trial Registration: ClinicalTrials.gov Identifier: NCT01970852.

BACKGROUND: More than 100 studies document disparities in patient portal use among vulnerable populations. Developing and testing strategies to reduce disparities in use is essential to ensure portals benefit all populations. OBJECTIVE: To systematically review the impact of interventions designed to: (1) increase portal use or predictors of use in vulnerable patient populations, or (2) reduce disparities in use. MATERIALS AND METHODS: A librarian searched Ovid MEDLINE, EMBASE, CINAHL, and Cochrane Reviews for studies published before September 1, 2018. Two reviewers independently selected English-language research articles that evaluated any interventions designed to impact an eligible outcome. One reviewer extracted data and categorized interventions, then another assessed accuracy. Two reviewers independently assessed risk of bias. RESULTS: Out of 18 included studies, 15 (83%) assessed an intervention's impact on portal use, 7 (39%) on predictors of use, and 1 (6%) on disparities in use. Most interventions studied focused on the individual (13 out of 26, 50%), as opposed to facilitating conditions, such as the tool, task, environment, or organization (SEIPS model). Twelve studies (67%) reported a statistically significant increase in portal use or predictors of use, or reduced disparities. Five studies (28%) had high or unclear risk of bias. CONCLUSION: Individually focused interventions have the most evidence for increasing portal use in vulnerable populations. Interventions affecting other system elements (tool, task, environment, organization) have not been sufficiently studied to draw conclusions. Given the well-established evidence for disparities in use and the limited research on effective interventions, research should move beyond identifying disparities to systematically addressing them at multiple levels.

OBJECTIVE: We sought to assess the quality of race and ethnicity information in observational health databases, including electronic health records (EHRs), and to propose patient self-recording as an improvement strategy. MATERIALS AND METHODS: We assessed completeness of race and ethnicity information in large observational health databases in the United States (Healthcare Cost and Utilization Project and Optum Labs), and at a single healthcare system in New York City serving a racially and ethnically diverse population. We compared race and ethnicity data collected via administrative processes with data recorded directly by respondents via paper surveys (National Health and Nutrition Examination Survey and Hospital Consumer Assessment of Healthcare Providers and Systems). Respondent-recorded data were considered the gold standard for the collection of race and ethnicity information. RESULTS: Among the 160 million patients from the Healthcare Cost and Utilization Project and Optum Labs datasets, race or ethnicity was unknown for 25%. Among the 2.4 million patients in the single New York City healthcare system's EHR, race or ethnicity was unknown for 57%. However, when patients directly recorded their race and ethnicity, 86% provided clinically meaningful information, and 66% of patients reported information that was discrepant with the EHR. DISCUSSION: Race and ethnicity data are critical to support precision medicine initiatives and to determine healthcare disparities; however, the quality of this information in observational databases is concerning. Patient self-recording through the use of patient-facing tools can substantially increase the quality of the information while engaging patients in their health. CONCLUSIONS: Patient self-recording may improve the completeness of race and ethnicity information.

Objective: To provide recommendations on how to most effectively implement advanced features of acute care patient portals, including: (1) patient-provider communication, (2) care plan information, (3) clinical data viewing, (4) patient education, (5) patient safety, (6) caregiver access, and (7) hospital amenities. Recommendations: We summarize the experiences of 6 organizations that have implemented acute care portals, representing a variety of settings and technologies. We discuss the considerations for and challenges of incorporating various features into an acute care patient portal, and extract the lessons learned from each institution's experience. We recommend that stakeholders in acute care patient portals should: (1) consider the benefits and challenges of generic and structured electronic care team messaging; (2) examine strategies to provide rich care plan information, such as daily schedule, problem list, care goals, discharge criteria, and post-hospitalization care plan; (3) offer increasingly comprehensive access to clinical data and medical record information; (4) develop alternative strategies for patient education that go beyond infobuttons; (5) focus on improving patient safety through explicit safety-oriented features; (6) consider strategies to engage patient caregivers through portals while remaining cognizant of potential Health Insurance Portability and Accountability Act (HIPAA) violations; (7) consider offering amenities to patients through acute care portals, such as information about navigating the hospital or electronic food ordering.

Objective: Unintentional medication discrepancies contribute to preventable adverse drug events in patients. Patient engagement in medication safety beyond verbal participation in medication reconciliation is limited. We conducted a pilot study to determine whether patients' use of an electronic home medication review tool could improve medication safety during hospitalization. Materials and Methods: Patients were randomized to use a tool before or after hospital admission medication reconciliation to review and modify their home medication list. We assessed the quantity, potential severity, and potential harm of patients' and clinicians' medication changes. We also surveyed clinicians to assess the tool's usefulness. Results: Of 76 patients approached, 65 (86%) participated. Forty-eight (74%) made changes to their home medication list [before: 29 (81%), after: 19 (66%), p = .170]. Before group participants identified 57 changes that clinicians subsequently missed on admission medication reconciliation. Thirty-nine (74%) had a significant or greater potential severity, and 19 (36%) had a greater than 50-50 chance of harm. After group patients identified 68 additional changes to their reconciled medication lists. Fifty-one (75%) had a significant or greater potential severity, and 33 (49%) had a greater than 50-50 chance of harm. Clinicians reported believing that the tool would save time, and patients would supply useful information. Discussion: The results demonstrate a high willingness of patients to engage in medication reconciliation, and show that patients were able to identify important medication discrepancies and often changes that clinicians missed. Conclusion: Engaging patients in admission medication reconciliation using an electronic home medication review tool may improve medication safety during hospitalization.

Development and maintenance of order sets is a knowledge-intensive task for off-the-shelf machine-learning algorithms alone. We hypothesize that integrating clinical knowledge with machine learning can facilitate effective development and maintenance of order sets while promoting best practices in ordering. To this end, we simulated the revision of an "AM Lab Order Set" under 6 revision approaches. Revisions included changes in the order set content or default settings through 1) population statistics, 2) individualized prediction using machine learning, and 3) clinical knowledge. Revision criteria were determined using electronic health record (EHR) data from 2014 to 2015. Each revision's clinical appropriateness, workload from using the order set, and generalizability across time were evaluated using EHR data from 2016 and 2017. Our results suggest a potential order set revision approach that jointly leverages clinical knowledge and machine learning to improve usability while updating contents based on latest clinical knowledge and best practices.

To reduce the risk of wrong-patient errors, safety experts recommend limiting the number of patient records providers can open at once in electronic health records (EHRs). However, it is unknown whether health care organizations follow this recommendation or what rationales drive their decisions. To address this gap, we conducted an electronic survey via 2 national listservs. Among 167 inpatient and outpatient study facilities using EHR systems designed to open multiple records at once, 44.3% were configured to allow ≥3 records open at once (unrestricted), 38.3% allowed only 1 record open (restricted), and 17.4% allowed 2 records open (hedged). Decision-making centered on efforts to balance safety and efficiency, but there was disagreement among organizations about how to achieve that balance. Results demonstrate no consensus on the number of records to be allowed open at once in EHRs. Rigorous studies are needed to determine the optimal number of records that balances safety and efficiency.

OBJECTIVE: To systematically review the literature pertaining to asynchronous automated electronic notifications of laboratory results to clinicians. METHODS: PubMed, Web of Science, and the Cochrane Collaboration were queried for studies pertaining to automated electronic notifications of laboratory results. A title review was performed on the primary results, with a further abstract review and full review to produce the final set of included articles. RESULTS: The full review included 34 articles, representing 19 institutions. Of these, 19 reported implementation and design of systems, 11 reported quasi-experimental studies, 3 reported a randomized controlled trial, and 1 was a meta-analysis. Twenty-seven articles included alerts of critical results, while 5 focused on urgent notifications and 2 on elective notifications. There was considerable variability in clinical setting, system implementation, and results presented. CONCLUSION: Several asynchronous automated electronic notification systems for laboratory results have been evaluated, most from >10 years ago. Further research on the effect of notifications on clinicians as well as the use of modern electronic health records and new methods of notification is warranted to determine their effects on workflow and clinical outcomes.

OBJECTIVE: Prior studies of computing applications that support patients' medication knowledge and self-management offer valuable insights into effective application design, but do not address inpatient settings. This study is the first to explore the design and usefulness of patient-facing tools supporting inpatient medication management and tracking. MATERIALS AND METHODS: We designed myNYP Inpatient, a custom personal health record application, through an iterative, user-centered approach. Medication-tracking tools in myNYP Inpatient include interactive views of home and hospital medication data and features for commenting on these data. In a two-phase pilot study, patients used the tools during cardiothoracic postoperative care at Columbia University Medical Center. In Phase One, we provided 20 patients with the application for 24-48 h and conducted a closing interview after this period. In Phase Two, we conducted semi-structured interviews with 12 patients and 5 clinical pharmacists who evaluated refinements to the tools based on the feedback received during Phase One. RESULTS: Patients reported that the medication-tracking tools were useful. During Phase One, 14 of the 20 participants used the tools actively, to review medication lists and log comments and questions about their medications. Patients' interview responses and audit logs revealed that they made frequent use of the hospital medications feature and found electronic reporting of questions and comments useful. We also uncovered important considerations for subsequent design of such tools. In Phase Two, the patients and pharmacists participating in the study confirmed the usability and usefulness of the refined tools. CONCLUSIONS: Inpatient medication-tracking tools, when designed to meet patients' needs, can play an important role in fostering patient participation in their own care and patient-provider communication during a hospital stay.

OBJECTIVE: To describe HARVEST, a novel point-of-care patient summarization and visualization tool, and to conduct a formative evaluation study to assess its effectiveness and gather feedback for iterative improvements. MATERIALS AND METHODS: HARVEST is a problem-based, interactive, temporal visualization of longitudinal patient records. Using scalable, distributed natural language processing and problem salience computation, the system extracts content from the patient notes and aggregates and presents information from multiple care settings. Clinical usability was assessed with physician participants using a timed, task-based chart review and questionnaire, with performance differences recorded between conditions (standard data review system and HARVEST). RESULTS: HARVEST displays patient information longitudinally using a timeline, a problem cloud as extracted from notes, and focused access to clinical documentation. Despite lack of familiarity with HARVEST, when using a task-based evaluation, performance and time-to-task completion was maintained in patient review scenarios using HARVEST alone or the standard clinical information system at our institution. Subjects reported very high satisfaction with HARVEST and interest in using the system in their daily practice. DISCUSSION: HARVEST is available for wide deployment at our institution. Evaluation provided informative feedback and directions for future improvements. CONCLUSIONS: HARVEST was designed to address the unmet need for clinicians at the point of care, facilitating review of essential patient information. The deployment of HARVEST in our institution allows us to study patient record summarization as an informatics intervention in a real-world setting. It also provides an opportunity to learn how clinicians use the summarizer, enabling informed interface and content iteration and optimization to improve patient care.

OBJECTIVE: To systematically review existing literature regarding patient engagement technologies used in the inpatient setting. METHODS: PubMed, Association for Computing Machinery (ACM) Digital Library, Institute of Electrical and Electronics Engineers (IEEE) Xplore, and Cochrane databases were searched for studies that discussed patient engagement ('self-efficacy', 'patient empowerment', 'patient activation', or 'patient engagement'), (2) involved health information technology ('technology', 'games', 'electronic health record', 'electronic medical record', or 'personal health record'), and (3) took place in the inpatient setting ('inpatient' or 'hospital'). Only English language studies were reviewed. RESULTS: 17 articles were identified describing the topic of inpatient patient engagement. A few articles identified design requirements for inpatient engagement technology. The remainder described interventions, which we grouped into five categories: entertainment, generic health information delivery, patient-specific information delivery, advanced communication tools, and personalized decision support. CONCLUSIONS: Examination of the current literature shows there are considerable gaps in knowledge regarding patient engagement in the hospital setting and inconsistent use of terminology regarding patient engagement overall. Research on inpatient engagement technologies has been limited, especially concerning the impact on health outcomes and cost-effectiveness.

Much of what is currently documented in the electronic health record is in response toincreasingly complex and prescriptive medicolegal, reimbursement, and regulatory requirements. These requirements often result in redundant data capture and cumbersome documentation processes. AMIA's 2011 Health Policy Meeting examined key issues in this arena and envisioned changes to help move toward an ideal future state of clinical data capture and documentation. The consensus of the meeting was that, in the move to a technology-enabled healthcare environment, the main purpose of documentation should be to support patient care and improved outcomes for individuals and populations and that documentation for other purposes should be generated as a byproduct of care delivery. This paper summarizes meeting deliberations, and highlights policy recommendations and research priorities. The authors recommend development of a national strategy to review and amend public policies to better support technology-enabled data capture and documentation practices.

OBJECTIVE: To understand the nature of emerging electronic documentation practices, disconnects between documentation workflows and computing systems designed to support them, and ways to improve the design of electronic documentation systems. MATERIALS AND METHODS: Time-and-motion study of resident physicians' note-writing practices using a commercial electronic health record system that includes an electronic documentation module. The study was conducted in the general medicine unit of a large academic hospital. RESULTS: During the study, 96 note-writing sessions by 11 resident physicians, resulting in close to 100 h of observations were seen. Seven of the 10 most common transitions between activities during note composition were between documenting, and gathering and reviewing patient data, and updating the plan of care. DISCUSSION: The high frequency of transitions seen in the study suggested that clinical documentation is fundamentally a synthesis activity, in which clinicians review available patient data and summarize their impressions and judgments. At the same time, most electronic health record systems are optimized to support documentation as uninterrupted composition. This mismatch leads to fragmentation in clinical work, and results in inefficiencies and workarounds. In contrast, we propose that documentation can be best supported with tools that facilitate data exploration and search for relevant information, selective reading and annotation, and composition of a note as a temporal structure. CONCLUSIONS: Time-and-motion study of clinicians' electronic documentation practices revealed a high level of fragmentation of documentation activities and frequent task transitions. Treating documentation as synthesis rather than composition suggests new possibilities for supporting it more effectively with electronic systems.

OBJECTIVE: Meaningful use of electronic health records (EHRs) is dependent on accurate clinical documentation. Documenting common goals in the intensive care unit (ICU), such as sedation and ventilator management plans, may increase collaboration and decrease patient length of stay. This study analyzed the degree to which goals stated were present in the EHR. DESIGN: Descriptive correlational study of common goals verbally stated during daily ICU interdisciplinary rounds compared with the presence of those goals, and actions related to those goals, documented in the EHR over the subsequent 24 h for 28 patients over 15 days. The study setting was a neurovascular ICU with a fully implemented electronic nursing and physician documentation system. MEASUREMENTS: Descriptive statistics and χ(2) analyses were used to assess differences in EHR documentation of stated goals and goal-related actions. Inter-coder reliability was performed on 16 (13%) of the 127 stated goals. RESULTS: One-quarter of the stated goals were not documented in the EHR. If a goal was not documented, actions related to that goal were 60% less likely to be documented. The attending physician note contained 81% of the stated ventilator weaning goals, but only 49% of the sedation weaning goals; additionally, sedation goals were not part of the structured nursing documentation. Inter-coder reliability (κ) was greater than 0.82. LIMITATIONS: Observations in a single ICU setting at a large academic medical center using a commercial EHR. CONCLUSION: The current documentation tools available in EHRs may not be sufficient to capture common goals of ICU patient care.

OBJECTIVE: Healthcare delivery organizations are increasingly using online personal health records (PHRs) to provide patients with direct access to their clinical information; however, there may be a lack of consistency in the data made available. We aimed to understand the general use and functionality of PHRs and the organizational policies and decision-making structures for making data available to patients. MATERIALS AND METHODS: A cross-sectional survey was administered by telephone structured interview to 21 organizations to determine the types of data made available to patients through PHRs and the presence of explicit governance for PHR data release. Organizations were identified based on a review of the literature, PHR experts, and snowball sampling. Organizations that did not provide patients with electronic access to their data via a PHR were excluded. RESULTS: Interviews were conducted with 17 organizations for a response rate of 81%. Half of the organizations had explicit governance in the form of a written policy that outlined the data types made available to patients. Overall, 88% of the organizations used a committee structure for the decision-making process and included senior management and information services. All organizations sought input from clinicians. Discussion There was considerable variability in the types of clinical data and the time frame for releasing these data to patients. Variability in data release policies may have implications for PHR use and adoption. CONCLUSIONS: Future policy activities, such as requirement specification for the latter stages of Meaningful Use, should be leveraged as an opportunity to encourage standardization of functionality and broad deployment of PHRs.

OBJECTIVE: To measure the time spent authoring and viewing documentation and to study patterns of usage in healthcare practice. DESIGN: Audit logs for an electronic health record were used to calculate rates, and social network analysis was applied to ascertain usage patterns. Subjects comprised all care providers at an urban academic medical center who authored or viewed electronic documentation. MEASUREMENT: Rate and time of authoring and viewing clinical documentation, and associations among users were measured. RESULTS: Users spent 20-103 min per day authoring notes and 7-56 min per day viewing notes, with physicians spending less than 90 min per day total. About 16% of attendings' notes, 8% of residents' notes, and 38% of nurses' notes went unread by other users, and, overall, 16% of notes were never read by anyone. Viewing of notes dropped quickly with the age of the note, but notes were read at a low but measurable rate, even after 2 years. Most healthcare teams (77%) included a nurse, an attending, and a resident, and those three users' groups were the first to write notes during an admission. Limitations The limitations were restriction to a single academic medical center and use of log files without direct observation. CONCLUSIONS: Care providers spend a significant amount of time viewing and authoring notes. Many notes are never read, and rates of usage vary significantly by author and viewer. While the rate of viewing a note drops quickly with its age, even after 2 years inpatient notes are still viewed.

OBJECTIVE: To ascertain if outpatients with moderate chronic kidney disease (CKD) had their condition documented in their notes in the electronic health record (EHR). DESIGN: Outpatients with CKD were selected based on a reduced estimated glomerular filtration rate and their notes extracted from the Columbia University data warehouse. Two lexical-based classification tools (classifier and word-counter) were developed to identify documentation of CKD in electronic notes. MEASUREMENTS: The tools categorized patients' individual notes on the basis of the presence of CKD-related terms. Patients were categorized as appropriately documented if their notes contained reference to CKD when CKD was present. RESULTS: The sensitivities of the classifier and word-count methods were 95.4% and 99.8%, respectively. The specificity of both was 99.8%. Categorization of individual patients as appropriately documented was 96.9% accurate. Of 107 patients with manually verified moderate CKD, 32 (22%) lacked appropriate documentation. Patients whose CKD had not been appropriately documented were significantly less likely to be on renin-angiotensin system inhibitors or have urine protein quantified, and had the illness for half as long (15.1 vs 30.7 months; p<0.01) compared to patients with documentation. CONCLUSION: Our studies show that lexical-based classification tools can accurately ascertain if appropriate documentation of CKD is present in a EHR. Using this method, we demonstrated under-documentation of patients with moderate CKD. Under-documented patients were less likely to receive CKD guideline recommended care. A tool that prompts providers to document CKD might shorten the time to implementing guideline-based recommendations.

OBJECTIVE: To evaluate the data quality of ventilator settings recorded by respiratory therapists using a computer charting application and assess the impact of incorrect data on computerized ventilator management protocols. DESIGN An analysis of 29,054 charting events gathered over 12 months from 678 ventilated patients (1,736 ventilator days) in four intensive care units at a tertiary care hospital. MEASUREMENTS: Ten ventilator settings were examined, including fraction of inspired oxygen (Fio (2)), positive end-expiratory pressure (PEEP), tidal volume, respiratory rate, peak inspiratory flow, and pressure support. Respiratory therapists entered values for each setting approximately every two hours using a computer charting application. Manually entered values were compared with data acquired automatically from ventilators using an implementation of the ISO/IEEE 11073 Medical Information Bus (MIB). Data quality was assessed by measuring the percentage of time that the two sources matched. Charting delay, defined as the interval between data observation and data entry, also was measured. RESULTS: The percentage of time that settings matched ranged from 99.0% (PEEP) to 75.9% (low tidal volume alarm setting). The average charting delay for each charting event was 6.1 minutes, including an average of 1.8 minutes spent entering data in the charting application. In 559 (3.9%) of 14,263 suggestions generated by computerized ventilator management protocols, one or more manually charted setting values did not match the MIB data. CONCLUSION: Even at institutions where manual charting of ventilator settings is performed well, automatic data collection can eliminate delays, improve charting efficiency, and reduce errors caused by incorrect data.

Mechanical ventilators are designed to generate alarms when patients become disconnected or experience other critical ventilator events. However, these alarms can blend in with other accustomed sounds of the intensive care unit. Ventilator alarms that go unnoticed for extended periods of time often result in permanent patient harm or death. We developed a system to monitor critical ventilator events through our existing hospital network. Whenever an event is identified, the new system takes control of every computer in the patient's intensive care unit and generates an enhanced audio and visual alert indicating that there is a critical ventilator event and identifies the room number. Once the alert is acknowledged or the event is corrected, all the computers are restored back to the pre-alert status and/or application. This paper describes the development and implementation of this system and reports the initial results, user acceptance, and the increase in valuable information and patient safety.

In resource-limited mobile computing devices, Bluetooth wireless technology imposes a weighty burden due to inefficient power utilization and a sluggish device discovery process. Buttressing Bluetooth with radiofrequency identification (RFID) technology by performing an operation we call "Rendez-Blue" alleviates these limitations. In the Rendez-Blue process, an RFID signal is used as a cue to "wake-up" a sleeping Bluetooth radio. This ensures that the Bluetooth radio is active only when needed, significantly reducing power consumption. In addition, RFID is used to communicate Bluetooth device information, allowing the user to bypass the traditional 10.24-second discovery process.