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PubMed1998

Implementation of a clinical information system in nurse-managed care.

The Penn Nursing Network Information System Project is a collaborative effort of practitioners, academic researchers, and a health-care software developer. The Penn Nursing Network, a group of nurse-managed practices owned and operated by the University of Pennsylvania School of Nursing, has taken a leadership role in the project. PNN is developing an information system specific to the needs of nurse-managed care and creating a data warehouse for nursing centres in the Philadelphia region. Important components of this project include the identification of key data elements to represent the problems treated, interventions performed, and outcomes sensitive to the nursing care provided. The Omaha System provided a useful framework for capturing the necessary data elements. However, additional data were needed. In addition, attention was paid to the development of a software program that would complement the workflow of the practitioner while capturing data efficiently. The main goal of the project is development of a longitudinal database reflective of clinical practice, to be used for both research and evaluation.

Clinical Nursing Research↗

PubMed2024

optiPRM: A Targeted Immunopeptidomics LC-MS Workflow With Ultra-High Sensitivity for the Detection of Mutation-Derived Tumor Neoepitopes From Limited Input Material.

Personalized cancer immunotherapies such as therapeutic vaccines and adoptive transfer of T cell receptor-transgenic T cells rely on the presentation of tumor-specific peptides by human leukocyte antigen class I molecules to cytotoxic T cells. Such neoepitopes can for example arise from somatic mutations and their identification is crucial for the rational design of new therapeutic interventions. Liquid chromatography mass spectrometry (LC-MS)-based immunopeptidomics is the only method to directly prove actual peptide presentation and we have developed a parameter optimization workflow to tune targeted assays for maximum detection sensitivity on a per peptide basis, termed optiPRM. Optimization of collision energy using optiPRM allows for the improved detection of low abundant peptides that are very hard to detect using standard parameters. Applying this to immunopeptidomics, we detected a neoepitope in a patient-derived xenograft from as little as 2.5 × 106 cells input. Application of the workflow on small patient tumor samples allowed for the detection of five mutation-derived neoepitopes in three patients. One neoepitope was confirmed to be recognized by patient T cells. In conclusion, optiPRM, a targeted MS workflow reaching ultra-high sensitivity by per peptide parameter optimization, makes the identification of actionable neoepitopes possible from sample sizes usually available in the clinic.

Humans↗

PubMed2026

Surgical management of jugular foramen meningiomas: a function-prioritized perioperative workflow.

OBJECTIVE: Jugular foramen meningiomas are challenging because of their deep, neurovascularly crowded location and multicompartment extension; hyperostosis and rigid dural attachment further narrow the corridor and increase the risk of lower cranial nerve morbidity, causing dysphagia and airway complications that may rarely require tracheostomy. This study aimed to describe a contemporary function-first workflow integrating compartment-based anatomy, venous sinus status, preoperative embolization, and continuous vagus nerve monitoring and its relation to clinically actionable recovery endpoints. METHODS: The authors retrospectively reviewed 26 consecutive patients who underwent primary surgery for jugular foramen meningiomas (2014-2025). Tumors were classified as intradural + intrajugular (IJ) or intradural + intrajugular + extracranial extension (IJE). Retrosigmoid, suprajugular, or transjugular approaches were selected by tumor extension and sigmoid-jugular venous status. Selective embolization and continuous vagus nerve monitoring were used when feasible. Outcomes included extubation timing, time to oral intake, 1-year swallowing/voice severity, extent of resection, and salvage stereotactic radiosurgery (SRS) for progression/regrowth. RESULTS: Twenty tumors were IJ and 6 were IJE. Selective embolization was performed in 16 patients (62%) without complications. Continuous vagus nerve monitoring was implemented in 16 patients (62%); lower preservation rates showed an exploratory association with worse 1-year swallowing. All patients were extubated immediately after surgery. Oral intake began by postoperative day ≤ 7 in 20 patients (77%); only 1 required > 14 days before resuming oral intake. At 1 year, swallowing and hoarseness remained worse in 54% and 46% of patients, respectively, but almost all cases were mild; the same patient had moderate dysphagia/hoarseness, and none required tracheostomy, gastrostomy, long-term tube feeding, or phonosurgery. Simpson grade IV comprised 69% of cases but predominantly reflected intrajugular/extracranial residual rather than persistent intradural disease. No patient without preoperative facial nerve palsy developed new palsy; serviceable hearing was preserved in 70%, and 38% with preoperative nonserviceable hearing improved to serviceable hearing. During a median 55.6-month follow-up, 3 patients (12%) underwent salvage SRS for regrowth; none required reoperation. CONCLUSIONS: A function-first workflow guided by anatomical compartment extension and intraoperative monitoring can support rapid recovery and durable functional independence in jugular foramen meningiomas. The IJE phenotype identifies a higher-risk subgroup for delayed oral intake and postoperative subjective dysphagia/hoarseness, while continuous vagus nerve monitoring may provide actionable insights to calibrate surgical aggressiveness and support function-prioritized acceptance of intrajugular/extracranial residual with close surveillance and salvage SRS when needed.

Humans↗

PubMed2006

Developing a lean culture in the laboratory.

The Director of Pathology at Jackson Memorial Hospital was interested in improving the operational efficiencies of the department in order to enhance the department's level of service in conjunction with the expansion of the overall health system. The decision was made to implement proven Lean practices in the laboratory under the direction of a major consulting firm. This article details the scope of the initial project as well as the operating principles of Lean manufacturing practices as applied to the clinical laboratory. The goals of the project were to improve turnaround times of laboratory results, reduce inventory and supply costs, improve staff productivity, maximize workflow, and eliminate waste. Extensive data gathering and analysis guided the work process by highlighting the areas of highest opportunity. This systematic approach resulted in recommendations for the workflow and physical layout of the laboratory. It also included the introduction of "standard workflow" and "visual controls" as critical items that streamlined operational efficiencies. The authors provide actual photographs and schematics of the reorganization and improvements to the physical layout of the laboratory. In conclusion, this project resulted in decreased turnaround times and increased productivity, as well as significant savings in the overall laboratory operations.

Clinical Laboratory Techniques↗

PubMed2005

An optimized workflow for the integration of biological information into radiotherapy planning: experiences with T1w DCE-MRI.

Planning of radiotherapy is often difficult due to restrictions on morphological images. New imaging techniques enable the integration of biological information into treatment planning and help to improve the detection of vital and aggressive tumour areas. This might improve clinical outcome. However, nowadays morphological data sets are still the gold standard in the planning of radiotherapy. In this paper, we introduce an in-house software platform enabling us to combine images from different imaging modalities yielding biological and morphological information in a workflow driven approach. This is demonstrated for the combination of morphological CT, MRI, functional DCE-MRI and PET data. Data of patients with a tumour of the prostate and with a meningioma were examined with DCE-MRI by applying pharmacokinetic two-compartment models for post-processing. The results were compared with the clinical plans for radiation therapy. Generated parameter maps give additional information about tumour spread, which can be incorporated in the definition of safety margins.

Algorithms↗

PubMed1995

ASOP: a new method and tools for capturing a clinical encounter.

ASOP is a proposed method for future medical record notation. This permutation of the original POMR-SOAP method is necessary to provide the standardized workflow and medical nomenclature which will be essential for automated medical record systems and forms-based encounter recording. The development of an ASOP system is dependent on tools to map assessment to appropriate terminology within a universal medical dictionary and generate intelligent queries across the World-Wide-Web. In this study we intend to demonstrate the need for change in the POMR system and highlight some of the current tools in development to make the ASOP method the medical record notation system of choice.

Computer Communication Networks↗

PubMed2006

Validation of QF-PCR for prenatal aneuploidy screening in the United States.

OBJECTIVE: QF-PCR is an inexpensive and reliable method for aneuploidy screening; however, despite its obvious advantages, it is not in routine use in the United States. Our objective in the present study was to validate QF-PCR as a means for prenatal aneuploidy screening in our institution. METHODS: A QF-PCR assay using 15 primer pairs located on chromosomes 13, 18, 21 X and Y was established for aneuploidy screening. Amniotic fluid (AF) and chorionic villus sampling (CVS) samples consisting only of the cells recovered from the plasticware discarded by our institutional cytogenetics laboratory were collected and DNA was prepared by a simple and inexpensive microwave procedure. QF-PCR was then performed and interpreted using established criteria. RESULTS: 687 consecutive prenatal samples were screened in a blinded prospective manner, and results were compared to those obtained by conventional cytogenetics. 100% of autosomal trisomies were detected, and there were zero false positives. A single case each of XXY and 45X were missed. CONCLUSIONS: QF-PCR for prenatal aneuploidy screening was validated in our laboratory and has now been approved by the New York State Clinical Laboratory Evaluation Program. We propose a simple protocol for integrating QF-PCR into the normal cytogenetics laboratory workflow.

Amniotic Fluid↗

PubMed1998

Filmless cardiac imaging: motion or commotion?

At present times the medical cardiology imaging is still arguing about the usefulness of X-Ray Cine film in comparison with digital and filmless imaging. It is clear that both techniques have their advantages. X-Ray Cine film is a well established technique of which the possibilities are well known. At a first glance filmless imaging offers nothing but advantages. However the whole picture becomes clear when trying to implement these systems in a clinical environment, because at that time aspects of investments, technological continuity and risks, needed skills and effects on the workflow appear. This article has the purpose to clarify some of these aspects and give guidance in the difficult process of making the right decision.

Cineangiography↗

PubMed2026

Deep learning techniques in predicting BRAF mutation status in cutaneous melanoma from histopathologic images.

AIMS: To develop and validate a deep learning framework for discriminating BRAF mutation status in cutaneous melanoma from routine H&E whole-slide images (WSIs) as a proof-of-concept complementary approach alongside molecular testing. METHODS: We built a two-stage pipeline comprising U-Net-based tumour segmentation followed by an Inception v3 classifier. In total, 272 institutional melanoma cases with confirmed BRAF status were used for model development (training and internal validation). Generalisability was assessed in an external test set of 76 cutaneous melanoma cases from the Cancer Genome Atlas (TCGA). Dermatopathologist-defined tumour-rich regions of interest were used to train and evaluate segmentation. WSIs were processed at 20×magnification using 512×512 tiles; slide-level mutation probabilities were obtained by averaging the predicted probabilities across all tumour-enriched tiles. RESULTS: Inception v3 achieved area under the receiver operating characteristic curve values of 0.973 (training), 0.954 (validation) and 0.915 (TCGA testing) and outperformed a ResNet50 baseline, showing stable external generalisation. Performance remained robust in advanced pathological T-category primary tumours (pT3-T4). Tumour probability heatmaps supported spatial interpretability by localising regions contributing most strongly to predicted mutation status. CONCLUSIONS: Deep learning applied to routine H&E WSIs can infer BRAF mutation status in cutaneous melanoma with consistent performance across institutional and external cohorts. Given the observed external sensitivity and negative predictive value, the model is not suitable for rule-out use or for deferring/omitting molecular testing. Any workflow integration is future work and would require prospective validation and calibration of probability outputs in real-world clinical series.

Artificial Intelligence↗

PubMed2006

Clinical computing in general dentistry.

OBJECTIVE: Measure the adoption and utilization of, opinions about, and attitudes toward clinical computing among general dentists in the United States. DESIGN: Telephone survey of a random sample of 256 general dentists in active practice in the United States. MEASUREMENTS: A 39-item telephone interview measuring practice characteristics and information technology infrastructure; clinical information storage; data entry and access; attitudes toward and opinions about clinical computing (features of practice management systems, barriers, advantages, disadvantages, and potential improvements); clinical Internet use; and attitudes toward the National Health Information Infrastructure. RESULTS: The authors successfully screened 1,039 of 1,159 randomly sampled U.S. general dentists in active practice (89.6% response rate). Two hundred fifty-six (24.6%) respondents had computers at chairside and thus were eligible for this study. The authors successfully interviewed 102 respondents (39.8%). Clinical information associated with administration and billing, such as appointments and treatment plans, was stored predominantly on the computer; other information, such as the medical history and progress notes, primarily resided on paper. Nineteen respondents, or 1.8% of all general dentists, were completely paperless. Auxiliary personnel, such as dental assistants and hygienists, entered most data. Respondents adopted clinical computing to improve office efficiency and operations, support diagnosis and treatment, and enhance patient communication and perception. Barriers included insufficient operational reliability, program limitations, a steep learning curve, cost, and infection control issues. CONCLUSION: Clinical computing is being increasingly adopted in general dentistry. However, future research must address usefulness and ease of use, workflow support, infection control, integration, and implementation issues.

Attitude to Computers↗

PubMed2026

Automated Classification of Lymphoma Subtypes From Histopathological Images Using a U-Net Deep Learning Model: Comparative Evaluation Study.

BACKGROUND: Accurate classification and grading of lymphoma subtypes are essential for treatment planning. Traditional diagnostic methods face challenges of subjectivity and inefficiency, highlighting the need for automated solutions based on deep learning techniques. OBJECTIVE: This study aimed to investigate the application of deep learning technology, specifically the U-Net model, in classifying and grading lymphoma subtypes to enhance diagnostic precision and efficiency. METHODS: In this study, the U-Net model was used as the primary tool for image segmentation integrated with attention mechanisms and residual networks for feature extraction and classification. A total of 620 high-quality histopathological images representing 3 major lymphoma subtypes were collected from The Cancer Genome Atlas and the Cancer Imaging Archive. All images underwent standardized preprocessing, including Gaussian filtering for noise reduction, histogram equalization, and normalization. Data augmentation techniques such as rotation, flipping, and scaling were applied to improve the model's generalization capability. The dataset was divided into training (70%), validation (15%), and test (15%) subsets. Five-fold cross-validation was used to assess model robustness. Performance was benchmarked against mainstream convolutional neural network architectures, including fully convolutional network, SegNet, and DeepLabv3+. RESULTS: The U-Net model achieved high segmentation accuracy, effectively delineating lesion regions and improving the quality of input for classification and grading. The incorporation of attention mechanisms further improved the model's ability to extract key features, whereas the residual structure of the residual network enhanced classification accuracy for complex images. In the test set (N=1250), the proposed fusion model achieved an accuracy of 92% (1150/1250), a sensitivity of 91.04% (1138/1250), a specificity of 89.04% (1113/1250), and an F1-score of 90% (1125/1250) for the classification of the 3 lymphoma subtypes, with an area under the receiver operating characteristic curve of 0.95 (95% CI 0.93-0.97). The high sensitivity and specificity of the model indicate strong clinical applicability, particularly as an assistive diagnostic tool. CONCLUSIONS: Deep learning techniques based on the U-Net architecture offer considerable advantages in the automated classification and grading of lymphoma subtypes. The proposed model significantly improved diagnostic accuracy and accelerated pathological evaluation, providing efficient and precise support for clinical decision-making. Future work may focus on enhancing model robustness through integration with advanced algorithms and validating performance across multicenter clinical datasets. The model also holds promise for deployment in digital pathology platforms and artificial intelligence-assisted diagnostic workflows, improving screening efficiency and promoting consistency in pathological classification.

Humans↗

PubMed2005

Strengthening the links in the supply chain--some preventive medicine.

There are many links in the supply chain that can lead to a "break" in an organization's supply process. These breaks can waste professional and clinical time and take staff away from patient care activities. By paying attention to some key areas, designing efficient workflows, and monitoring supply usage, an organization can avoid the headaches of a supply process that doesn't optimize scarce labor resources. It also can lead to significant savings that go directly to the organization's bottom line. As with all hospital processes, some consistent and focused preventive medicine makes sense for its supply chain.

Cost Control↗

PubMed2005

[Research and development of a clinical laboratory information system].

A clinical laboratory information system consists of two parts--the information system and the management system. Its development is based on scientific and rational lab-workflow, consulting the international standard HL7 Protocol, and combined with barcode technique and instrument communication. The information system mainly manages the data which come from the whole lab testing process while the management system is dominating the lab office work and management decisions.

Clinical Laboratory Information Systems↗

PubMedDate not supplied

Kaiser Permanente Colorado Region Pharmacy Department: innovative leader in pharmacy practice.

OBJECTIVE: To describe innovative programs within the Kaiser Permanente Pharmacy Department in the Colorado Region. SETTING: One of eight regions of the nation's largest nonprofit health maintenance organization. PRACTICE DESCRIPTION: The pharmacy department comprises two services, Clinical Pharmacy Services and Pharmacy Operations/Support Services, which are integrated to provide comprehensive care. PRACTICE INNOVATION: Within Clinical Pharmacy Services, the Primary Care Clinical Pharmacy Services team works alongside physicians to provide integrated patient care. The Centralized Clinical Pharmacy Service teams manage large groups of patients effectively and efficiently. The Clinical Pharmacy Specialty staff and the Disease State Management clinical pharmacy specialists provide focused drug therapy expertise. MAIN OUTCOME MEASURES: Clinical and economic outcomes; recognition by national organizations. RESULTS: Technological innovations are used within Pharmacy Operations/Support Services to increase pharmacists' time for patient care activities. The use of technology by the Pharmacy Automated Refill Center and the implementation of ScriptPro in the medical office pharmacies decrease dispensing demands by processing large volumes of prescriptions. Workflow in the medical office pharmacies has also been reengineered to increase efficiency. Various programs have been developed by the Pharmacy Information Technology Service to support patient care initiatives. Benchmark clinical and economic outcomes have been demonstrated. Positive outcomes have also resulted in quality and safety awards and captured the attention of national pharmacy and medical organizations. CONCLUSION: The Colorado Region Pharmacy Department has been recognized as a leader in pharmacy practice through the development of innovative services that provide exceptional patient care.

Anticoagulants↗

PubMedDate not supplied

The diffusion of decision support systems in healthcare: are we there yet?

Clinical decision support (CDS) systems, with the potential to minimize practice variation and improve patient care, have begun to surface throughout the healthcare industry. This study reviews historic patterns of information technology (IT) in healthcare, analyzes barriers and enabling factors, and draws three lessons. First, the widespread adoption of clinical IT, including CDS systems, depends on having the right organizational and individual financial incentives in place. Second, although CDS systems and clinical IT in general are powerful tools that can be used to support the practice of medicine, they alone cannot redefine the workflow or processes within the profession. Healthcare managers counting on technology to restructure or monitor clinicians' work patterns are likely to encounter substantial resistance to CDS systems, even those that generate valuable information. Third, while the pace of implementing IT systems in healthcare has lagged behind that of other industries, many of the obstacles are gradually diminishing. However, several factors continue to inhibit their widespread diffusion, including the organizational turmoil created by large numbers of mergers and acquisitions, and the lack of uniform data standards.

Attitude to Computers↗

PubMed2005

Radiology interpretation process modeling.

Information and communication technology in healthcare promises optimized patient care while ensuring efficiency and cost-effectiveness. However, the promised results are not yet achieved; the healthcare process requires analysis and radical redesign to achieve improvements in care quality and productivity. Healthcare process reengineering is thus necessary and involves modeling its workflow. Even though the healthcare process is very large and not very well modeled yet, its sub-processes can be modeled individually, providing fundamental pieces of the whole model. In this paper, we are interested in modeling the radiology interpretation process that results in generating a diagnostic radiology report. This radiology report is an important clinical element of the patient healthcare record and assists in healthcare decisions. We present the radiology interpretation process by identifying its boundaries and by positioning it on the large healthcare process map. Moreover, we discuss an information data model and identify roles, tasks and several information flows. Furthermore, we describe standard frameworks to enable radiology interpretation workflow implementations between heterogeneous systems.

Canada↗

PubMed2005

Comparative evaluation of the Cobas Amplicor HIV-1 Monitor Ultrasensitive Test, the new Cobas AmpliPrep/Cobas Amplicor HIV-1 Monitor Ultrasensitive Test and the Versant HIV RNA 3.0 assays for quantitation of HIV-1 RNA in plasma samples.

BACKGROUND: There are several commercially available assays for the quantitation of HIV RNA. A new automated specimen preparation system, the Cobas AmpliPrep, was developed to automate this last part of the PCR. OBJECTIVES AND STUDY DESIGN: We compared the results obtained by the Roche Cobas Amplicor HIV-1 Monitor Ultrasensitive Test (MCA, manual sample preparation) with those by the Versant HIV-1 RNA 3.0 assay (bDNA). Secondly we compared the MCA with the new Cobas AmpliPrep/Cobas Amplicor HIV Monitor Ultrasensitive Test (CAP/CA, automated specimen preparation) by investigating clinical patient samples and a panel of HIV-1 non-B subtypes. Furthermore, we assessed the assay throughput and workflow (especially hands-on time) for all three assays. RESULTS: Seventy-two percent of the 140 investigated patient samples gave concordant results in the bDNA and MCA assays. The MCA values were regularly higher than the bDNA values. One sample was detected only by the MCA within the linear range of quantification. In contrast, 38 samples with results <50 copies/ml in the MCA showed in the bDNA results between 51 and 1644 copies/ml (mean value 74 copies/ml); 21 of these specimens were shown to have detectable HIV RNA < 50 copies/ml in the MCA assay. The overall agreement between the MCA and the CAP/CA was 94.3% (551/584). The quantification results showed significant correlation, although the CAP/CA generated values slightly lower than those generated by the manual procedure. We found that the CAP/CA produced comparable results with the MCA test in a panel of HIV-1 non-B subtypes. CONCLUSIONS: All three assays showed comparable results. The bDNA provides a high sample throughput without the need of full automation. The new CAP/CA provides reliable test results with no HIV-subtype specific influence and releases time for other works in the laboratory; thus it is suitable for routine diagnostic PCR.

Automation↗

PubMed2026

An introductory practical guide to secondary data analysis in pediatric urology.

INTRODUCTION: Secondary data analysis (SDA) has become an increasingly important approach in pediatric urology, enabling the study of long-term outcomes, care variation, and disparities in populations with chronic or congenital urologic conditions. With the growing availability of large datasets, a structured approach to designing and conducting SDA studies is increasingly relevant. OBJECTIVES: To provide an introductory, practical guide to SDA in pediatric urology by (1) summarizing commonly used data sources with representative studies, (2) outlining a stepwise approach to designing and executing SDA studies, and (3) highlighting key methodological considerations, limitations, and opportunities for future work. STUDY DESIGN: Narrative review of existing literature and commonly used datasets relevant to pediatric urology, including administrative claims, hospital encounter databases, clinical registries, electronic health record networks, and population-based surveys. RESULTS: Data sources differ in scope, clinical granularity, longitudinal follow-up, and representativeness, and each is suited to specific research questions. We present a practical workflow for SDA, including dataset selection, cohort definition, and analytic planning. Linkage across datasets can provide a more comprehensive view of care patterns and outcomes, although feasibility is influenced by legal, technical, and data-quality constraints. DISCUSSION: SDA enables population-level analyses and the study of rare conditions that are challenging to evaluate through single-center or prospective designs. However, careful cohort definition, feasibility assessment, and awareness of data limitations are essential to ensure validity and interpretability. CONCLUSION: SDA provides a scalable, cost-efficient framework for generating meaningful evidence in pediatric urology. Continued efforts to harmonize data elements, improve linkage infrastructure, and support cross-institution collaboration will enhance the quality and impact of future research. This article provides a practical framework and examples to support the design and execution of SDA studies.

Humans↗