deviations

Reversing the normalization of performance deviations can be difficult

Many organizations suffer from performance deviation despite their best efforts.




deviations

Large deviations for perturbed Gaussian processes and logarithmic asymptotic estimates for some exit probabilities

Claudio Macci and Barbara Pacchiarotti
Theor. Probability and Math. Statist. 111 (), 21-43.
Abstract, references and article information




deviations

A Markovian Gauss inequality for asymmetric deviations from the mode of symmetric unimodal distributions

Chris A.J. Klaassen
Theor. Probability and Math. Statist. 111 (), 9-19.
Abstract, references and article information




deviations

Measuring monetary policy deviations from the Taylor rule [electronic journal].




deviations

Covered Interest Parity Deviations: Macrofinancial Determinants [electronic journal].

International Monetary Fund




deviations

Cytosine analogue, a method of preparation of a cytosine analogue, a DNA methyltransferase 1 inhibitor, a method for DNA methylation inhibition, the use of the analogue in the treatment of diseases associated with deviations from normal DNA methylation

A cytosine analog, a method of preparation of a cytosine analog, a DNA methyltransferase 1 inhibitor, and a method for DNA methylation inhibition, is provided for the treatment of diseases associated with deviations from normal DNA methylation. The analog of cytosine may be comprised of 1, N4, 5 and 6-substituted derivatives of cytosine or 5,6-dihydrocytosine, wherein the analog can be described by the chemical formula where R1 is H, R3, R4, 2'-deoxyribosyl, R4 is alkyl or aryl, X is N or C, wherein if X in the analog of formula I is N, then R5 is no substituent and if X in the analog of formula I and/or II is C or if X in the analog of formula II is N, then R5 and R6 are independently alkyl, aryl, hydroxyalkyl, aminoalkyl, hydroxyl, carboxyl, amino group, alkoxyl, aryloxyl, aminoalkyl, aminoaryl, thio group, sulfonyl, sulfinyl or halogen.




deviations

Device for compensating deviations from a coaxial arrangement of components of a regulating organ to control the gas pressure of a coke oven chamber

A device for compensating deviations from a coaxial arrangement of components of a regulating organ, said regulating arrangement being comprised of a regulating organ, a crown pipe, and an immersion cup which serve for controlling the gas pressure of a coke oven chamber, with the regulating arrangement being comprised of an immersion cup with a water immersion that seals the gas space of a coke oven chamber versus the gas collecting main and/or plant units downstream, and wherein the height of the water level of the water immersion represents a regulating means to control the gas pressure, and wherein said regulating arrangement is furthermore comprised of an immersion pipe that configures a specially shaped crown pipe at its end submerging into the water of the immersion cup, and that is comprised of a regulating organ to regulate the water level.




deviations

Large Deviations for Additive Functionals of Markov Chains

Alejandro D. de Acosta and Peter Ney - AMS, 2014, 108 pp., Softcover, ISBN-13: 978-0-8218-9089-9, List: US$76, All AMS Members: US$60.80, MEMO/228/1070

For a Markov chain ({X_j}) with general state space (S) and ({f:S ightarrowmathbf{R}^d}), the large deviation principle for...




deviations

Du traitement des deviations uterines par les pessaires intra-uterins ... / par le Dr Depaul.

Paris : W. Remquet, 1854.




deviations

Distances and large deviations in the spatial preferential attachment model

Christian Hirsch, Christian Mönch.

Source: Bernoulli, Volume 26, Number 2, 927--947.

Abstract:
This paper considers two asymptotic properties of a spatial preferential-attachment model introduced by E. Jacob and P. Mörters (In Algorithms and Models for the Web Graph (2013) 14–25 Springer). First, in a regime of strong linear reinforcement, we show that typical distances are at most of doubly-logarithmic order. Second, we derive a large deviation principle for the empirical neighbourhood structure and express the rate function as solution to an entropy minimisation problem in the space of stationary marked point processes.




deviations

Dynamic Evolution of Practice Guidelines: Analysis of Deviations From Assessment and Management Plans

Adherence to guidelines has generally been shown to improve patient care and reduce the cost of care. Current understanding of the varying reasons why clinicians deviate from guidelines is based on surveys and retrospective reviews.

We examined clinician deviations from guidelines in a prospective fashion and attempted to categorize those deviations. Better elucidation of clinician reasoning behind deviations may inform care improvement and help define strategies to eliminate unjustifiable deviations. (Read the full article)




deviations

Avoiding Protocol Deviations

Year in and year out, protocol deviations are the most common FDA Site Inspection finding. Why does this keep happening?

If you’ve seen FDA’s Inspectional Observation Summaries, you know that in 2015 the most frequently cited violation in clinical research by far was “failure to conduct research in accordance with the investigational plan.”  Do you know this finding also topped the list the year before that?  And the year before that?  In fact, deviating from the protocol has been the most common observation every year for the last decade.

Why does this keep happening?



The Nature of Protocols
This will come as a surprise to no one: not all protocols are well written.  Important procedures can be hidden in the most obscure places.  Charts depicting Time and Events Schedules are famous for carrying dozens of footnotes that appear nowhere else in the protocol, yet convey important study procedures.   For instance, a pre-dosing column may include a footnote that provides a timeframe for performing a physical exam; a post-dosing footnote might specify the interval at which vitals must be taken.   Failing to follow study procedures compromises subject safety and data integrity; FDA won’t care whether the procedures were in big bold italics or 7-point font.

This, too, may come as no surprise, but not all protocols are error-free.   Information in charts may not match the narrative.  Procedures in Section A may conflict with procedures in Section B.  When the FDA investigator spots an inconsistency, you’ll be asked which of the two conflicting procedures you followed and why.  If you performed procedure A only because you didn’t even notice there was a B, it will be clear you didn’t read the protocol as thoroughly as you needed to.  The FDA investigator may become concerned that your study execution differed from the sponsor’s intention.  This is not a concern you want to trigger.

For these reasons, it’s imperative that study staff read and understand the protocol.  Study team members need to ask questions about anything they’re unsure of, seek clarification on protocol inconsistencies, and get responses that satisfy before starting the study.   A PowerPoint overview is not sufficient training.

One more irksome attribute of protocols that can make them difficult to follow -- they change.  While most study sites allocate time and resources for initial protocol training, many lack a plan for training staff on protocol amendments.   A disproportionate number of protocol deviations occur in amended procedures, and it’s often because staff members have been insufficiently trained on them.  (And when you do train on protocol amendments, don’t forget to document it.)

Deviation Temptation
A protocol is not a suggestion; PIs cannot substitute their own judgment for prescribed procedures, no matter how well-intentioned the departure.  The protocol for a psoriasis study might call for the PI to perform a series of punch biopsies, very invasive procedures.  After the first biopsy, an empathetic PI might be tempted to skip a second if he observes the plaque is clearing up; the drug is working.  But this would be a protocol deviation.  The protocol for another study might preclude the use of a particular drug, even though the drug is routinely used throughout the practice to treat a symptom that a study participant is exhibiting.  But the study protocol trumps standard of care; prescribing the drug would be a protocol deviation.

A PI who feels she must deviate from the protocol for some reason must obtain prior approval, since failure to follow the protocol can jeopardize the reliability of the study data, if not subject rights and safety.



Deviations Happen
So you’ve thoroughly read the protocol, you’ve asked your questions and received the necessary clarifications, you’ve trained your staff on the protocol and its amendments, and you do your best to follow them.

Despite all your preparation and vigilance, protocol deviations happen.  They just do.  And when they do, here are two don'ts.

(1) Don’t panic.

(2) Don’t let an FDA investigator find them first.
Take the time to fully document any protocol deviations.  Be sure to record why they happened, how they were corrected, and what was submitted to the IRB.

[Note: IRBs have different requirements about what types of protocol deviations should be communicated.  Out-of-window visits are common and are frequently considered too minor to report.  But nothing’s black and white.  If the missed visit resulted in missed doses, that would probably change the calculus. The PI needs to determine whether to notify the IRB, and if no submission is thought necessary, it’s a good idea to document why not.]

_______________________________________________________________

A version of this article originally appeared in InSite, the Journal of the Society for Clinical Research Sites.




deviations

Beyond basis basics [electronic resource] : leverage demand and deviations from the law of one price / Todd M. Hazelkorn, Tobias J. Moskowitz, Kaushik Vasudevan

Cambridge, Mass. : National Bureau of Economic Research, 2020




deviations

Large deviations / S.R.S. Varadhan

Online Resource




deviations

Assessing the impact of deviations in optimized multistep flow synthesis on the scale-up

React. Chem. Eng., 2020, 5,838-848
DOI: 10.1039/D0RE00025F, Perspective
M. K. Sharma, J. Raval, Gwang-Noh Ahn, Dong-Pyo Kim, A. A. Kulkarni
This manuscript highlights the unavoidable connection between manual and self-optimized flow synthesis protocols for multistep flow synthesis and its scale-up.
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