System hazards in managing laboratory test requests and results in primary care: medical protection database analysis and conceptual model

Objectives To analyse a medical protection organisation's database to identify hazards related to general practice systems for ordering laboratory tests, managing test results and communicating test result outcomes to patients. To integrate these data with other published evidence sources to inform design of a systems-based conceptual model of related hazards. Design A retrospective database analysis. Setting General practices in the UK and Ireland. Participants 778 UK and Ireland general practices participating in a medical protection organisation's clinical risk self-assessment (CRSA) programme from January 2008 to December 2014. Main outcome measures Proportion of practices with system risks; categorisation of identified hazards; most frequently occurring hazards; development of a conceptual model of hazards; and potential impacts on health, well-being and organisational performance. Results CRSA visits were undertaken to 778 UK and Ireland general practices of which a range of systems hazards were recorded across the laboratory test ordering and results management systems in 647 practices (83.2%). A total of 45 discrete hazard categories were identified with a mean of 3.6 per practice (SD=1.94). The most frequently occurring hazard was the inadequate process for matching test requests and results received (n=350, 54.1%). Of the 1604 instances where hazards were recorded, the most frequent was at the ‘postanalytical test stage’ (n=702, 43.8%), followed closely by ‘communication outcomes issues’ (n=628, 39.1%). Conclusions Based on arguably the largest data set currently available on the subject matter, our study findings shed new light on the scale and nature of hazards related to test results handling systems, which can inform future efforts to research and improve the design and reliability of these systems

Directional wave observations, Thimble Shoal light, October 19, 1993 to April 14, 1994

The Virginia Institute of Marine Science, in cooperation with the Virginia Department of Conservation and Recreation, Division of Soil and Water conservation, has identified as one of its major goals the systematic study of hydrodynamic processes that affect recreational, shoreline and benthic resources in the coastal zone of the Commonwealth. As one component of the Virginia Coastal Information Program, a wave climatology project was initiated in 1988 with support from the National Oceanographic and Atmospheric Agency\u27s Coastal Zone Management Program administered by the Virginia Council on the Environment. Directional wave observations were begun on a seasonal schedule (fall, winter, spring) at a single station location near the Thimble Shoal Light in lower Chesapeake Bay. In 1993, a one-year cooperative agreement between the United States of America and the Commonwealth of Virginia permitted a second wave station to be operated at the entrance to the Thimble Shoal Channel, a major navigational route in the lower bay (Figure 1). Simultaneous wave observations obtained at these two stations, Thimble Shoal Light (TSL) and Thimble Shoal Entrance (TSE), were presented in an earlier report (Boon and Hepworth, 1993). The present report contains a description of the observations and analyses performed at the TSL wave station, the sole station in operation during the 1993-1994 season

Cross-shoreface Suspended Sediment Transport : A Response to the Interaction of Nearshore and Shelf Processes, Fall 1994 Duck, NC Field Experiment

Deployment : The tripods were assembled, tested and secured onboard the RIV Sea Diver, which left the Little Creek Amphibious Base in Norfolk, Virginia early on 26 September. While underway to the deployment site, the continuous surface water conductivity and temperature survey was run and several CTD casts were made. The tripods were deployed on 26 September and secured to the sea floor with sand anchors by VIMS divers. The R/V Sea Diver then began the series of on/off shore transects at the tripod deployment site for approximately 12 hours. The vessel returned to port on 27 September . Recovery: The tripod recovery cruise began late on 21 October and repeated the underway data collection scheme of the September cruise. On October 22 divers removed the sand anchors and the tripods were recovered without incident. The on/off shore transects were repeated and transit to port occurred on 23 October

Chesapeake Bay Wave Climate : Wolf Trap Wave Station, Report and Summary of Wave Observations November 6, 1989 through August 2, 1990

The Virginia Institute of Marine Science, in cooperation with the Virginia Department of Conservation and Recreation, Division of Soil and Water Conservation, has identified as one of its major goals the systematic study of hydrodynamic processes that affect recreational, shoreline and benthic resources in the coastal zone of the Commonwealth. In pursuit of that goal, a long-term study of the wave climate in the Virginia portion of Chesapeake Bay was initiated in 1988 with support from the National Oceanographic and Atmospheric Administration through the Coastal Zone Management Program administered by the Virginia Council on the Environment (Grant No. NA89AA-D-CZ134)

Chesapeake Bay wave climate : Thimble Shoal light wave station, report and summary of wave observations, October 8, 1990 through August 22, 1991 and Chesapeake light tower - VIMS Star gage test measurements and evaluation, July, August, October 1991

This report also presents a description of a directional wave gaging system, known as a Star gage, that is designed for long-term, low-maintenance operation both within and immediately outside the Chesapeake Bay entrance area. This development was prompted by our dependence to date on the single-point, PUV-type directional wave gage described below. While ideally suited for short-term investigative studies at different sites, the PUV directional wave gage requires field service visits at monthly intervals to maintain adequate performance and uninterrupted operation. A prototype Star gage system was constructed and field tested to evaluate its potential use as a long-term and eventual real-time wave gage for the Virginia coastal environment. A test deployment of the VIMS Star gage, a 4-element pressure sensor array utilizing a star configuration (Goda, 1985) was conducted at the Chesapeake Light Tower (CLT, Fig. 1) located approximately 14 nautical miles east of the bay entrance. Results of these tests are reported in Section VII

Chesapeake Bay wave climate : Thimble Shoals wave station, report and summary of wave observations, September 27, 1988 through October 17, 1989

The Virginia Institute of Marine Science, in cooperation with the Virginia Department of Conservation and Recreation, Division of Soil and Water Conservation, has identified as one of its major goals the systematic study of hydrodynamic processes that affect recreational, shoreline and benthic resources in the coastal zone of the Commonwealth. In pursuit of that goal, a long-term study of the wave climate in the Virginia portion of Chesapeake Bay was initiated in 1988 with support from the National Oceanographic and Atmospheric Administration through the Coastal Zone Management Program administered by the Virginia Council on the Environment (Grant Ho. HA88AA-D-CZ092). Past knowledge of wave properties in the Chesapeake Bay region has been conspicuous in its lack of an observational basis. Although inner shelf and deep water wave measurements have been made outside the Chesapeake Bay entrance, none of these have produced reliable directional information (Seymour et al., 1985). Therefore, before addressing certain long-term wave monitoring objectives, it was deemed essential to develop a basis for them by obtaining a representative (year-long) series of wave observations at one or more selected locations. The first of these has recently been completed for a station designated as VIMS BAY! located near Thimble Shoals to the west of the Chesapeake Bay entrance (Fig. 1). This report contains a summary of data for the initial year of continuous directional wave measurements made at the Thimble Shoals station

The drivers of Higher Education leadership competence: a study of Moldovan HEI's

This paper examines the qualities and skills needed by leaders and managers in Higher Education; the extent to which leaders and managers in 15 Moldovan Institutions perceive themselves to hold those qualities and skills; and the main drivers for holding higher levels of them. Review of the literature suggests that the qualities and skills examined belong to nine domains. The leaders and managers perceive themselves to be strongest on the Personal Values domain and weakest on Managing Resources. Where respondents have moved to the action stage of learning, perceive their organisation to be supportive of development, and have access to a broader range of development activities they are more likely to report higher levels of competence on the qualities and skills. The paper concludes that where institutions want to develop leadership and management capacity they need to help leaders and managers to psychologically commit to acting on their development needs

Automating Fictional Ideation using ConceptNet

The invention of fictional ideas (ideation) is often a cen- tral process in producing artefacts such as poems, music and paint- ings in a creative way. Automated fictional ideation should, there- fore, be of much interest in the study of Computational Creativity, but only a few approaches have been explored. We describe here the preliminary results of a new method for automated generation and evaluation of fictional ideas which uses ConceptNet, a semantic net- work. We evaluate the results obtained through a small study that involves participants scoring ideas via an online survey. We believe this approach constitutes a firm basis on which a more sophisticated model for automated creative ideation can be built

Characterization of patients with idiopathic normal pressure hydrocephalus using natural language processing within an electronic healthcare record system

OBJECTIVE: Idiopathic normal pressure hydrocephalus (iNPH) is an underdiagnosed, progressive, and disabling condition. Early treatment is associated with better outcomes and improved quality of life. In this paper, the authors aimed to identify features associated with patients with iNPH using natural language processing (NLP) to characterize this cohort, with the intention to later target the development of artificial intelligence–driven tools for early detection. / METHODS: The electronic health records of patients with shunt-responsive iNPH were retrospectively reviewed using an NLP algorithm. Participants were selected from a prospectively maintained single-center database of patients undergoing CSF diversion for probable iNPH (March 2008–July 2020). Analysis was conducted on preoperative health records including clinic letters, referrals, and radiology reports accessed through CogStack. Clinical features were extracted from these records as SNOMED CT (Systematized Nomenclature of Medicine Clinical Terms) concepts using a named entity recognition machine learning model. In the first phase, a base model was generated using unsupervised training on 1 million electronic health records and supervised training with 500 double-annotated documents. The model was fine-tuned to improve accuracy using 300 records from patients with iNPH double annotated by two blinded assessors. Thematic analysis of the concepts identified by the machine learning algorithm was performed, and the frequency and timing of terms were analyzed to describe this patient group. / RESULTS: In total, 293 eligible patients responsive to CSF diversion were identified. The median age at CSF diversion was 75 years, with a male predominance (69% male). The algorithm performed with a high degree of precision and recall (F1 score 0.92). Thematic analysis revealed the most frequently documented symptoms related to mobility, cognitive impairment, and falls or balance. The most frequent comorbidities were related to cardiovascular and hematological problems. / CONCLUSIONS: This model demonstrates accurate, automated recognition of iNPH features from medical records. Opportunities for translation include detecting patients with undiagnosed iNPH from primary care records, with the aim to ultimately improve outcomes for these patients through artificial intelligence–driven early detection of iNPH and prompt treatment