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At least 199 records · Page 11Linked to original sources
PubMed2003

Linking guidelines to Electronic Health Record design for improved chronic disease management.

The promise of electronic decision support to promote evidence based practice remains elusive in the context of chronic disease management. We examine the problem of achieving a close relationship of Electronic Health Record (EHR) content to other components of a clinical information system (guidelines, decision support and workflow), particularly linking the decisions made by providers back to the guidelines. We use the openEHR architecture, which allows extension of a core Reference Model via Archetypes to refine the detailed information recording options for specific classes of encounter. We illustrate the use of openEHR for tracking the relationship of a series of clinical encounters to a guideline via a case study of guideline-compliant treatment of hypertension in diabetes. This case study shows the contribution guideline content can have on problem-specific EHR structure and demonstrates the potential for a constructive interaction of electronic decision support and the EHR.

Chronic Disease↗
PubMed2005

A clinical problem-oriented decision support model based on extended temporal database functionalities.

Several diagnostic decision support systems have been proposed. Yet, such systems are not commonly used partly due to insufficient temporal reasoning. We have developed a clinical problem-oriented diagnostic decision support model that employs temporal reasoning by using extended temporal database functionalities developed at our lab. In addition, our model supports the workflow of the diagnostic process and employs detailed clinical data. We developed a prototype system that implements the concepts of the model.

Databases as Topic↗
PubMed2006

A taxonomic description of computer-based clinical decision support systems.

OBJECTIVE: Computer-based clinical decision support systems (CDSSs) vary greatly in design and function. Using a taxonomy that we had previously developed, we describe the characteristics of CDSSs reported in the literature. METHODS: We searched PubMed and the Cochrane Library for randomized controlled trials (RCTs) published in English between 1998 and 2003 that evaluated CDSSs. We coded each CDSS using our taxonomy. RESULTS: 58 studies met our inclusion criteria. The 74 reported CDSSs varied greatly in context of use, knowledge and data sources, nature of decision support offered, information delivery, and workflow impact. Two distinct subsets of CDSSs were seen: patient-directed systems that provided decision support for preventive care or health-related behaviors via mail or phone (38% of systems), and inpatient systems targeting clinicians with online decision support and direct online execution of the recommendations (18%). 84% of the CDSSs required extra staffing for handling CDSS-related input or output. CONCLUSION: Reported CDSSs are heterogeneous along many dimensions. Caution should be taken in generalizing the results of CDSS RCTs to different clinical or workflow settings.

Databases, Bibliographic↗
PubMed2003

The nurse, M.D. and IT. Executive dialogue series.

Clinical information systems are proven to enhance workflow and outcomes, and yet hospitals often face staff resistance when systems are installed. This roundtable discussion explores how nurses and physicians can collaborate on developing IT systems.

Attitude to Computers↗
PubMed2006

A survey of factors affecting clinician acceptance of clinical decision support.

BACKGROUND: 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. METHODS: 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). RESULTS: 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". CONCLUSION: 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.

Adult↗
PubMed2026

Accelerating Lung Cancer Management Through Previsit Liquid Biopsy: Results From the LUNG-FAST Pilot Study.

BACKGROUND: Timely molecular profiling is essential for treatment selection in non-small cell lung cancer (NSCLC), yet delays in biomarker testing remain common. We evaluated the feasibility and early clinical impact of a nurse navigator-driven workflow to initiate liquid biopsy before the initial oncology visit. METHODS: LUNG-FAST (Liquid Biopsy for Urgent Neoplastic Genomic Profiling Focused Accelerated Stratification and Testing) was a 4-month prospective pilot at a tertiary cancer center. Intake nurse navigators identified eligible patients with suspected or newly diagnosed lung cancer and facilitated previsit liquid biopsy ordering. Feasibility, turnaround times, genomic findings, and early clinical outcomes were assessed. RESULTS: Among 64 patients, intake nurse navigators identified 94% (60/64) of eligible cases. Liquid biopsy was ordered in 58 patients, with 62% (36/58) placed before the initial oncology visit. Median turnaround time from blood draw to results was 8.5 days for commercial testing and 12.5 days for institutional testing. FDA-actionable genomic alterations were identified in 34% (22/64) of patients, while an additional 11% (7/64) harbored clinically relevant, non-FDA-actionable alterations. Overall, FDA-actionable or clinically relevant alterations were identified in 45% (29/64), with 22% detected by liquid biopsy and an additional 23% by tissue-only profiling. Median time from new patient visit to systemic therapy was 26 days. CONCLUSIONS: A nurse navigator-driven workflow enabling previsit liquid biopsy is feasible and identifies actionable genomic alterations in a substantial proportion of patients with lung cancer. Plasma and tissue profiling are complementary, and earlier plasma-based testing may expedite treatment decision-making while highlighting opportunities to optimize biomarker testing workflows.

Humans↗
PubMed1999

[Wish and reality in installation of a clinic-wide system for image and documentation access].

PROBLEM: This report describes the problems that can occur in the representation of the radiological workplace in a digital environment. On one hand the radiologist can sometimes access good equipment in "stand-alone" surroundings (CT, laser printer, workstations,...); on the other hand, the existing insufficient communication between different components is only rarely qualified to support the radiological workflow. This unsatisfactory framework handicaps the required clinic-wide distribution of radiological information. METHODS: From the beginning we defined user groups requiring different radiological data closely associated with specific hard- and software: The radiological workstation in the department for reporting and image processing. The demonstration workstation in wards/outpatient departments for clinicians involved in treatment. Standard PCs with access to the digital medical document for clinicians involved in treatment. At all workstations the medical as well as the legal unity of digital radiological images and the corresponding report is ensured. RESULTS: Only the first two user groups have unrestricted access to the RIS database and to the PACS archive. We have decided that the RIS should be the master of the RIS/PACS-System. For an effective master/slave relationship between RIS and PACS archive and PACS workstations we suggest to mark images and/or series of images. CONCLUSION: The third user group depends on the information exported by the radiologist from PACS. After the report is written and signed by the radiologist, the digital report is transferred from the RIS to the HIS. The report is automatically attached to these images. Authorized personnel at the wards and outpatient are able to read the combination of validated report and exported radiological images as part of the digital medical record with an intranet browser on standard PCs.

Computer Systems↗
PubMed2001

Towards integration of clinical decision support in commercial hospital information systems using distributed, reusable software and knowledge components.

PROBLEM: Clinicians' acceptance of clinical decision support depends on its workflow-oriented, context-sensitive accessibility and availability at the point of care, integrated into the Electronic Patient Record (EPR). Commercially available Hospital Information Systems (HIS) often focus on administrative tasks and mostly do not provide additional knowledge based functionality. Their traditionally monolithic and closed software architecture encumbers integration of and interaction with external software modules. Our aim was to develop methods and interfaces to integrate knowledge sources into two different commercial hospital information systems to provide the best decision support possible within the context of available patient data. METHODS: An existing, proven standalone scoring system for acute abdominal pain was supplemented by a communication interface. In both HIS we defined data entry forms and developed individual and reusable mechanisms for data exchange with external software modules. We designed an additional knowledge support frontend which controls data exchange between HIS and the knowledge modules. Finally, we added guidelines and algorithms to the knowledge library. RESULTS: Despite some major drawbacks which resulted mainly from the HIS' closed software architectures we showed exemplary, how external knowledge support can be integrated almost seamlessly into different commercial HIS. This paper describes the prototypical design and current implementation and discusses our experiences.

Abdominal Pain↗
PubMed2026

Moving Beyond Morphology to Multiplexed Molecular Imaging as the Next Frontier in Diagnostic Pathology.

Diagnostic pathology has long relied on the morphologic interpretation of hematoxylin and eosin-stained tissues to guide diagnosis and assess prognostic features. Although pathologists intuitively recognize spatial patterns and architectural organization, these assessments remain largely qualitative and difficult to quantify systematically. Immunohistochemistry and immunofluorescence have introduced molecular specificity but are limited in multiplexing capacity, whereas bulk genomic and transcriptomic assays provide high molecular depth but lose spatial context by averaging signals across heterogeneous cell populations. Recent advances in spatial proteomics-including mass spectrometry-based imaging and cyclic immunofluorescence-now enable multiplexed, single-cell protein analysis within intact tissue architecture. These technologies have revealed complex immune and stromal microenvironments, spatially organized biomarkers predictive of therapeutic response, and molecular gradients underlying disease progression. By integrating histologic and molecular information, spatial proteomics bridges traditional microscopy with high-dimensional omics, allowing quantitative, spatially resolved insights into tissue organization and disease mechanisms. This review summarizes recent developments in multiplexed spatial proteomics from both scientific and pathologic perspectives, highlighting how these technologies extend beyond morphology to quantify histologic patterns, refine biomarker discovery, and facilitate clinical translation. The review also examines translational challenges and barriers to clinical implementation, including costs, standardization requirements, and workflow integration.

Humans↗
PubMed2006

Lectin capture strategies combined with mass spectrometry for the discovery of serum glycoprotein biomarkers.

The application of mass spectrometry to identify disease biomarkers in clinical fluids like serum using high throughput protein expression profiling continues to evolve as technology development, clinical study design, and bioinformatics improve. Previous protein expression profiling studies have offered needed insight into issues of technical reproducibility, instrument calibration, sample preparation, study design, and supervised bioinformatic data analysis. In this overview, new strategies to increase the utility of protein expression profiling for clinical biomarker assay development are discussed with an emphasis on utilizing differential lectin-based glycoprotein capture and targeted immunoassays. The carbohydrate binding specificities of different lectins offer a biological affinity approach that complements existing mass spectrometer capabilities and retains automated throughput options. Specific examples using serum samples from prostate cancer and hepatocellular carcinoma subjects are provided along with suggested experimental strategies for integration of lectin-based methods into clinical fluid expression profiling strategies. Our example workflow incorporates the necessity of early validation in biomarker discovery using an immunoaffinity-based targeted analytical approach that integrates well with upstream discovery technologies.

Amino Acid Sequence↗
PubMed2006

Maintaining excellence in physician nurse communication with CPOE: A nursing informatics team approach.

Designing and implementing CPOE systems is difficult, presenting many challenges to overcome related to workflow redesign. As part of the Mayo Clinic Arizona CPOE design and implementation, it was recognized that physicians would be placing inpatient orders from multiple locations; therefore nurses no longer would have the usual visual clues to identify new physician orders. This could easily lead to a delay in implementing orders that require immediate action. To address this, a multidisciplinary team evaluated various communication options and designed two in-house Web-based applications to solve the communication gap. One application will provide staff nurses with visual alerts for stat and routine orders as they are processed in real time. A second application is a Web-based link to the nursing assignment sheets, which will give physicians and support staff access to staff nurse assignments and phone numbers, specific to each nursing unit.

Arizona↗
PubMed2006

The perfect storm for electronic health records.

EHRs and data sharing improve quality, reduce costs, and enhance workflow. They create a c ommunity of clinical collaboration, fostering the adoption of new knowledge and best practices. With government, provider, and payer support for the nationwide rollout of electronic records, 2006 will be the year in which the United States makes significant progress on the journey to deliver electronic systems to all clinicians.

Attitude of Health Personnel↗
PubMed2006

[Clinical laboratory system in a complete electronic hospital].

The use of a Laboratory Information System (LIS) and Laboratory Automation System (LAS) are clearly superior to manual results in terms of completeness and legibility. As the current clinical information system (CIS) in Gifu University Hospital consists of a complete electronic medical record system, the clinical laboratory was re-engineered to simplify workflow, pay attention to quality assurance, and decrease various costs by an intelligent laboratory management system. We named the new system Gifu Premiotic Intelligent Laboratory System (GPILS). Further advances will concentrate on the cost-effective use of LIS, and the potential use of GPILS in our laboratories will be discussed. In addition, because one of our clinical laboratories currently provides various useful clinical laboratory-oriented information to physicians and patients, we have developed new tools named the "Reference Data Base (RefDB)". In the near future, several different types of computer technology for various clinical laboratory information will lead to the development of highly specific platforms for LIS corresponding to a complete electronic medical record system.

Clinical Laboratory Information Systems↗
PubMed2026

AI echo INSIGHT study: A prospective blinded randomized trial of artificial intelligence echocardiogram interpretation.

BACKGROUND: Transthoracic echocardiography (TTE) is the most commonly performed cardiac imaging modality with over 30 million studies annually. Demand for timely expert interpretation continues to outpace capacity, creating diagnostic delays and inter-observer variability that impact patient care. Recent research has suggested computer vision artificial intelligence (AI) models can generate accurate preliminary comprehensive TTE reports, however, prospective evaluation is needed to determine whether AI-assisted TTE interpretation can improve clinician efficiency while preserving diagnostic accuracy. METHODS: AI ECHO INSIGHT is a prospective randomized blinded clinical trial conducted at Kaiser Permanente Northern California that will evaluate 1200 historical TTE studies (1000 consecutive unselected studies plus 200 with moderate or greater valvular disease) interpreted using three workflows: (1) AI-generated preliminary report finalized by a blinded cardiologist (AI-assisted); (2) cardiologist-generated preliminary report finalized by a blinded cardiologist (cardiologist-assisted); and (3) sonographer-generated preliminary report finalized by a blinded cardiologist (sonographer-assisted). The primary outcome is the rate of substantial change between preliminary and final reports, comparing the AI-assisted workflow to the pooled cardiologist-assisted and sonographer-assisted workflows. Secondary outcomes include cardiologist interpretation time for report finalization, superiority testing for diagnostic accuracy, and reporting consistency. CONCLUSION: AI ECHO INSIGHT is a prospective randomized blinded clinical trial evaluating the clinical impact of AI-assisted TTE interpretation on diagnostic accuracy, cardiologist efficiency, and reporting consistency in real-world echocardiography workflows. TRIAL REGISTRATION: ClinicalTrials.gov registration number NCT07229300.

Humans↗
PubMed2026

Beyond antibiotics: artificial intelligence-enabled anti-infective ecosystems for next-generation precision therapeutics against antimicrobial resistance.

The rapid global expansion of antimicrobial resistance (AMR) threatens to undermine decades of progress in infectious disease management and highlights the limitations of conventional antibiotic-centered therapeutic strategies. Although emerging technologies-including antimicrobial peptides, bacteriophage therapy, CRISPR-based antimicrobials, microbiome therapeutics, anti-virulence approaches, nanotechnology-enabled drug delivery, and artificial intelligence (AI)-have individually demonstrated considerable promise, they are predominantly being developed as independent interventions rather than as coordinated components of an integrated therapeutic strategy. This Perspective proposes the Intelligent Anti-Infective Ecosystem (IAIE) as a conceptual systems-level framework that computationally integrates multimodal diagnostics, pathogen genomics, microbiome profiling, AI-assisted decision support, programmable precision therapeutics, ecological monitoring, and longitudinal clinical feedback within a continuously learning dynamically optimized workflow. Unlike existing paradigms that primarily optimize individual technologies or therapeutic decisions, IAIE emphasizes closed-loop coordination among complementary antimicrobial approaches to support precision-guided infection management while preserving microbiome integrity and mitigating resistance selection pressure. We further outline the core components, operational principles, translational challenges, and technology readiness of the major therapeutic platforms that could contribute to such an ecosystem, while distinguishing clinically established interventions from emerging experimental strategies. Importantly, IAIE should be interpreted as a prospective conceptual architecture rather than an existing clinical platform. Its proposed clinical value remains to be established through sequential computational, preclinical, and prospective clinical investigations using standardized microbiological, ecological, and patient-centered outcome measures. By framing antimicrobial innovation within an responsive systems perspective, IAIE provides a roadmap for future multidisciplinary research aimed at integrating artificial intelligence and systems microbiology to enable sustainable management of antimicrobial resistance.

Humans↗
PubMed1999

[Aspects of electronic patient records in radiology].

PURPOSE: The computerized patient record must provide patient- and problem-oriented access to all relevant patient data for health care professionals. The aspects of such systems will be analyzed in the light of the radiologist's needs. METHODS: Integration of the computerized patient record in a hospital communication network allows automated data exchange with the ancillary systems. Accessibility of electronic textbooks supports case-based learning during routine work. RESULTS: The computerized patient record not only supports routine clinical tasks but also training, education and research. The workflow in a hospital can be supported by the computerized patient record. Studying the tasks of a radiology department shows that both clinicians and radiologists will benefit from such a system. DISCUSSION: Current implementations of clinical computerized workstations offer only a fraction of these features. Advances in technology and increasing demands at the point of care will promote the development of new information systems of this kind.

Computer Systems↗
PubMed1999

Workflow analysis and evidence-based medicine: towards integration of knowledge-based functions in hospital information systems.

The large extent and complexity of scientific evidence described in the concept of evidence-based medicine often overwhelms clinicians who want to apply best external evidence. Hospital Information Systems usually do not provide knowledge-based functions to support context-sensitive linking to external information sources. Knowledge-based components need specific data, which must be entered manually and should be well adapted to clinical environment to be accepted by clinicians. This paper describes a workflow-based approach to understand and visualize clinical reality as a preliminary to designing software applications, and possible starting points for further software development.

Artificial Intelligence↗