Decision support and patient safety: the time has come

Hasley, Steve

doi:10.1016/j.ajog.2010.10.901

Cited by 7 publications

(5 citation statements)

References 24 publications

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“…The most recent study [5] shows only moderate agreement on CTG evaluation among obstetricians and is consistent with studies published before. In general, two possible solutions to overcome difficulties with CTG interpretation were suggested: more education and training [13] or cost‐effective solution in form of decision support system serving as an aid and providing additional information [14–17]. Majority of these solutions still waits to be adopted into daily clinical practice.…”

Section: Introductionmentioning

confidence: 99%

Agreement on intrapartum cardiotocogram recordings between expert obstetricians

Hruban

Spilka

Chudáček

et al. 2015

Evaluation Clinical Practice

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Rationale, aims and objectivesTo evaluate obstetricians' inter-and intra-observer agreement on intrapartum cardiotocogram (CTG) recordings and to examine obstetricians' evaluations with respect to umbilical artery pH and base deficit. Methods Nine experienced obstetricians annotated 634 intrapartum CTG recordings. The evaluation of each recording was divided into four steps: evaluation of two 30minute windows in the first stage of labour, evaluation of one window in the second stage of labour and labour outcome prediction. The complete set of evaluations used for this experiment is available online. The inter-and intra-observer agreement was evaluated using proportion of agreement and kappa coefficient. Clinicians' sensitivity and specificity was computed with respect to umbilical artery pH, base deficit and to Apgar score at the fifth minute. Results The overall proportion of agreement between clinicians reached 48% with 95% confidence intervals (CI) (CI: 47-50). Regarding the different classes, proportion of agreement ranged from 57% (CI: 54-60) for normal to 41% (CI: 36-46) for pathological class. The sensitivity of clinicians' majority vote to objective outcome was 39% (CI: 16-63) for the umbilical artery base deficit and 27% (CI: 16-42) for pH. The specificity was 89% (CI: 86-92) for both types of objective outcome. Conclusions The reported inter-/intra-observer variability is large and this holds irrespective of clinicians' experience or work place. The results support the need of modernized guidelines for CTG evaluation and/or objectivization and repeatability by introduction of a computerized approach that could standardize the process of CTG evaluation within the delivery ward. bs_bs_banner -96) N/A N/A BD ≥ 12 60 (29-85) 94 (91-97) 60 (29-85) 94 (90-96) 25 (1-75) 92 (87-95) N/A N/A Apgar < 7 0 (0-53) 92 (88-95) 0 (0-53) 92 (87-95) 33 (2-86) 92 (87-95) N/A N/A BD, base deficit; CTG; N/A, Not Available; SE, sensitivity; SP, specificity.Obstetrician agreement on CTG records L. Hruban et al.

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Section: Introductionmentioning

confidence: 99%

Agreement on intrapartum cardiotocogram recordings between expert obstetricians

Hruban

Spilka

Chudáček

et al. 2015

Evaluation Clinical Practice

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“…27 The use of data-mining techniques to determine whether a diagnosis is unusual or not can actually provide a useful reference for medical staff who lack clinical experience, thus reducing mistakes in diagnoses. 22 Using data mining to create an analytical model for medical resources consumed in the treatment of diabetes would provide a useful indicator for hospitals to control their costs. 10 Furthermore, text-mining techniques used to analyze special terms in nursing records have successfully increased consistency in the use of terms.…”

Section: Data Mining and Text Miningmentioning

confidence: 99%

“…10,21,22 Text mining is the extended application of data mining that focuses on mining unknown and hidden pieces of useful information from unstructured and semistructured text. 23 The process of text mining is basically the same as that of data mining.…”

Section: Data Mining and Text Miningmentioning

confidence: 99%

Evaluation of the Mining Techniques in Constructing a Traditional Chinese-Language Nursing Recording System

Liao

Chu

2014

CIN: Computers, Informatics, Nursing

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In 2009, the Department of Health, part of Taiwan's Executive Yuan, announced the advent of electronic medical records to reduce medical expenses and facilitate the international exchange of medical record information. An information technology platform for nursing records in medical institutions was then quickly established, which improved nursing information systems and electronic databases. The purpose of the present study was to explore the usability of the data mining techniques to enhance completeness and ensure consistency of nursing records in the database system.First, the study used a Chinese word-segmenting system on common and special terms often used by the nursing staff. We also used text-mining techniques to collect keywords and create a keyword lexicon. We then used an association rule and artificial neural network to measure the correlation and forecasting capability for keywords. Finally, nursing staff members were provided with an on-screen pop-up menu to use when establishing nursing records. Our study found that by using mining techniques we were able to create a powerful keyword lexicon and establish a forecasting model for nursing diagnoses, ensuring the consistency of nursing terminology and improving the nursing staff's work efficiency and productivity.

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“…Such computer-based dashboards and report-generating tools can be provider speciic or relect the data for an entire Institution [27][28][29]. Real-time access to quality and outcome data thereby allows to immediate identiication of potential adverse trends, or the hopefully positive response to interventions [30,31]. While no reporting system is perfect and often physicians might criticize that they are being inherently personally linked to adverse events, in a culture of shared accountability, any limitations in the data collection and the reporting process will clearly be acknowledged and used to improve our understanding of overall trends.…”

Section: Foundations Of Evidence-based Progressmentioning

confidence: 99%