Emerging Business Intelligence Framework for a Clinical Laboratory Through Big Data Analytics

Mohammed, Emad A.; Naugler, Christopher; Far, Behrouz H.

doi:10.1016/b978-0-12-802508-6.00032-6

Cited by 49 publications

(35 citation statements)

References 22 publications

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“…To account for this background monthly variation, we used historic test volumes at each of the 3 testing laboratories and all sites combined to create interrupted time series 13 in IBM SPSS Statistics (version 22). Preliminary analyses showed that Winter's additive models gave the best model fit, therefore these were used for subsequent analyses.…”

Section: Discussionmentioning

confidence: 99%

Implementation of an intervention to reduce population-based screening for vitamin D deficiency: a cross-sectional study

et al. 2017

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Background:We describe the implementation of an intervention in Alberta in support of the Choosing Wisely Canada recommendation against population screening for vitamin D deficiency (as determined by serum total 25-hydroxyvitamin D testing). We hypothesized that the introduction of a specialized requisition for vitamin D testing would reduce the annual number of vitamin D tests performed. Methods:We performed a cross-sectional observational study that included all vitamin D tests ordered in Alberta between Apr. 1, 2015, and Mar. 31, 2016. There were no exclusion criteria. A special requisition for ordering vitamin D tests in Alberta was introduced on Apr. 1, 2015. Using an interrupted time series model, we compared predicted versus observed vitamin D test volumes for the 12-month period following the introduction of the new requisition. The sole outcome measure was the monthly change in volume of vitamin D testing. In addition, we calculated any cost savings as a result of reduced testing. Results:Over the first 12 months of the intervention, there was a reduction in the number of tests ordered from a predicted 342 477 tests to 29 525 tests (91.4% reduction). This decrease represented a direct spending decrease of Can$938 856-$1 564 760 per year in Alberta.Interpretation: A provincially led implementation of a Choosing Wisely Canada recommendation resulted in a large and sustained reduction in serum total 25-hydroxyvitamin D testing in Alberta. This study shows that provincially led interventions based on Choosing Wisely Canada recommendations can result in substantial reductions in laboratory tests.Vitamin D screening has been particularly problematic for the health system in Alberta because there has been a massive increase in test volumes over the past 10 years, 9 with evidence that testing has been preferentially directed toward low-risk patients. 10 We describe the implementation of an intervention in Alberta in support of the Choosing Wisely Canada recommendation against population screening for vitamin D deficiency. This initiative was accompanied by a province-wide communication strategy that included an update of the provincial clinical practice guidelines to align them with the new requisition, development of an information sheet that was provided to physicians to give to patients who requested vitamin D testing that was not clinically indicated, and the appending of a comment describing the intervention to all reported vitamin D results for the month before the intervention. Methods Intervention SettingThis work was performed in Alberta and includes all vitamin D tests ordered in the province from Apr. 1, 20151, , to Mar. 31, 2016. This is an observational study using publicly available secondary data on laboratory test volumes. The intervention exposure was equal for all physicians (a specialized requisition) and there were not treatment and control groups. There was no specific follow-up of either patients or physicians in this study. Test volumes for both inpatient and outpatient samples were us...

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Section: Discussionmentioning

confidence: 99%

Implementation of an intervention to reduce population-based screening for vitamin D deficiency: a cross-sectional study

et al. 2017

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“…Likewise, statistically speaking, the ACI results obtained in Section 3.2 (747.5103 for non-stationary and 753.3721 for stationary) demonstrated that the non-stationary condition is more adequate. The AIC test serves to evaluate how good a model is for predicting future values [30]. The lower the value of the AIC the better the model.…”

Section: Resultsmentioning

confidence: 99%

Effect of the Non-Stationarity of Rainfall Events on the Design of Hydraulic Structures for Runoff Management and Its Applications to a Case Study at Gordo Creek Watershed in Cartagena de Indias, Colombia

Gonzalez-Alvarez

Coronado-Hernández

Fuertes-Miquel

et al. 2018

Fluids

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Abstract:The 24-h maximum rainfall (P 24h-max ) observations recorded at the synoptic weather station of Rafael Núñez airport (Cartagena de Indias, Colombia) were analyzed, and a linear increasing trend over time was identified. It was also noticed that the occurrence of the rainfall value (over the years of record) for a return period of 10 years under stationary conditions (148.1 mm) increased, which evidences a change in rainfall patterns. In these cases, the typical stationary frequency analysis is unable to capture such a change. So, in order to further evaluate rainfall observations, frequency analyses of P 24h-max for stationary and non-stationary conditions were carried out (by using the generalized extreme value distribution). The goodness-of-fit test of Akaike Information Criterion (AIC), with values of 753.3721 and 747.5103 for stationary and non-stationary conditions respectively, showed that the latter best depicts the increasing rainfall pattern. Values of rainfall were later estimated for different return periods (2,5,10,25, 50, and 100 years) to quantify the increase (non-stationary versus stationary condition), which ranged 6% to 12% for return periods from 5 years to 100 years, and 44% for a 2-year return period. The effect of these findings were tested in the Gordo creek watershed by first calculating the resulting direct surface runoff (DSR) for various return periods, and then modeling the hydraulic behavior of the downstream area (composed of a 178.5-m creek's reach and an existing box-culvert located at the watershed outlet) that undergoes flooding events every year. The resulting DSR increase oscillated between 8% and 19% for return periods from 5 to 100 years, and 77% for a 2-year return period when the non-stationary and stationary scenarios were compared. The results of this study shed light upon to the precautions that designers should take when selecting a design, based upon rainfall observed, as it may result in an underestimation of both the direct surface runoff and the size of the hydraulic structures for runoff and flood management throughout the city.

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“…AIC is a statistical technique that used for selection of a good model. The best model is the model that has the minimum AIC among all models [13]. …”

Section: Methodsmentioning

confidence: 99%

The Prediction Incidence of the Three Most Common Cancers Among Iranian Military Community During 2007-2019: a Time Series Analysis.

Khoshdel

Alimohamadi

Ziaei³

et al. 2019

Journal of Preventive Medicine and Hygiene

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Emerging Business Intelligence Framework for a Clinical Laboratory Through Big Data Analytics

Cited by 49 publications

References 22 publications

Implementation of an intervention to reduce population-based screening for vitamin D deficiency: a cross-sectional study

Implementation of an intervention to reduce population-based screening for vitamin D deficiency: a cross-sectional study

Effect of the Non-Stationarity of Rainfall Events on the Design of Hydraulic Structures for Runoff Management and Its Applications to a Case Study at Gordo Creek Watershed in Cartagena de Indias, Colombia

The Prediction Incidence of the Three Most Common Cancers Among Iranian Military Community During 2007-2019: a Time Series Analysis.

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