Journal of Statistical Planning and Inference, Dec 1, 2021
Abstract Variability assessment of qualitative data has an important role in diverse areas such a... more Abstract Variability assessment of qualitative data has an important role in diverse areas such as sociology, quality engineering, healthcare, decision making, genetics, metrology in chemistry and many others. To test the homogeneity hypothesis, we use two main categorical factors. Using a cross-balanced design, we provide a decomposition theorem of the sample total-variation into ‘intra’ (within) component and ‘inter’ (between) component for any scale. Building on this, we provide a way for decomposing the ‘inter’ component itself into variation components contributed by the two factors and their interaction (when we consider more than one replicated test in the cross-design). Moreover, focusing on an ordinal scale, we offer segregation power indices for testing the significate effects of the two factors and their interaction. A two-way ORDANOVA calculator is provided to display the empirical distributions of the segregation power indices and to find critical points of the test statistics distributions at the given confidence level. Some examples are given to demonstrate the proposed method.
PURPOSE: Transfer of intensive care unit (ICU) patients to the operating room (OR) is a resource-... more PURPOSE: Transfer of intensive care unit (ICU) patients to the operating room (OR) is a resource-intensive, time-consuming process that often results in patient throughput inefficiencies, deficiencies in information transfer, and suboptimal nurse to patient ratios. This study evaluates the implementation of a coordinated patient transport system (CPTS) designed to address these issues. METHODS: Using data from 1,557 patient transfers covering the 2006-2010 period, interrupted time series and before and after designs were used to analyze the effect of implementing a CPTS at Mayo Clinic, Rochester. RESULTS: Using a segmented regression for the interrupted time series, on-time OR start time deviations were found to be significantly lower after the implementation of CPTS (p < .0001). The implementation resulted in a fourfold improvement in on-time OR starts (p < .01) while significantly reducing idle OR time (p…
Flexible Services and Manufacturing Journal, Dec 28, 2016
AbstractA critical step in patient care path is diagnosis. The demand for advanced imaging tests,... more AbstractA critical step in patient care path is diagnosis. The demand for advanced imaging tests, such as computerized axial tomography, magnetic resonance imaging and positron emission tomography (PET), increased dramatically in the past 15 years. Since imaging equipment remains relatively expensive, in order to fit the demand, the imaging resources must be managed effectively while ensuring required quality of service. In PET, a radiopharmaceutical (radioactive substance) is injected to patients prior to their scans. The time between substance injection and scan (standby or uptake time) is rigid. This constraint makes the patient appointment scheduling more challenging, because if at the end of the expected uptake time the scanner is not available, the quality of the scan is jeopardized (due to short half-life duration of the substance). The availability of the scanner is a consequence of prior scans’ appointments and durations. The aim of this work is to develop an approach for appointment scheduling in a system with one scanner, given a sequence of patients and rigid uptake time, in order to minimize the length of day while satisfying a minimal pre-determined quality of service. In order to solve this stochastic problem, we formulate its equivalent deterministic problem, based on simulated data, as a mixed-integer linear programming. To overcome the dimensionality limitations, we develop a simulation-based sequential algorithm that solves the problem in a reasonable time. We found that a fixed slot per scan policy, as a benchmark, is inferior to our method, especially in achieving stable and fair quality of service for patients.
Patient health is represented by a set of diagnoses, which determines personal health status. Eac... more Patient health is represented by a set of diagnoses, which determines personal health status. Each set corresponds to a certain health state and so, can be treated as an individual performance in this state and individual health can be considered as a corresponding multi-state system. Appropriate metrics for measuring patient’s state diagnosis changes during hospitalization are proposed. The first metric determines the dissimilarity between two single diagnoses, each of which is based on internationally recognized classification scheme. The second metric is aimed to compare between two sets of diagnoses with respect to the same patient and is based on the first metric, but uses additional, recently proposed, ideas of measuring heterogeneity/segregation between sets of categorical data. A numerical example and a real world illustration of the above measures are provided. The ultimate goal is the analysis of multistate health status data in order to improve the accuracy and quality of...
Abstract Prioritization is widely used in quality practice. Since the process is accompanied by u... more Abstract Prioritization is widely used in quality practice. Since the process is accompanied by unavoidable errors, in order to improve accuracy, prioritization is usually repeated by M independent experts, followed by aggregation of their decisions. The article studies the bias of such a procedure, under the assumption of a “gold standard” existence and Mallows’ model of errors creation, for different combinations of M, number of alternatives—n and probability of error-free prioritization P 0. Thereby it becomes possible to know how many experts are required and how accurate must they be in order to prevent the bias from exceeding some threshold.
Journal of Statistical Planning and Inference, Dec 1, 2021
Abstract Variability assessment of qualitative data has an important role in diverse areas such a... more Abstract Variability assessment of qualitative data has an important role in diverse areas such as sociology, quality engineering, healthcare, decision making, genetics, metrology in chemistry and many others. To test the homogeneity hypothesis, we use two main categorical factors. Using a cross-balanced design, we provide a decomposition theorem of the sample total-variation into ‘intra’ (within) component and ‘inter’ (between) component for any scale. Building on this, we provide a way for decomposing the ‘inter’ component itself into variation components contributed by the two factors and their interaction (when we consider more than one replicated test in the cross-design). Moreover, focusing on an ordinal scale, we offer segregation power indices for testing the significate effects of the two factors and their interaction. A two-way ORDANOVA calculator is provided to display the empirical distributions of the segregation power indices and to find critical points of the test statistics distributions at the given confidence level. Some examples are given to demonstrate the proposed method.
PURPOSE: Transfer of intensive care unit (ICU) patients to the operating room (OR) is a resource-... more PURPOSE: Transfer of intensive care unit (ICU) patients to the operating room (OR) is a resource-intensive, time-consuming process that often results in patient throughput inefficiencies, deficiencies in information transfer, and suboptimal nurse to patient ratios. This study evaluates the implementation of a coordinated patient transport system (CPTS) designed to address these issues. METHODS: Using data from 1,557 patient transfers covering the 2006-2010 period, interrupted time series and before and after designs were used to analyze the effect of implementing a CPTS at Mayo Clinic, Rochester. RESULTS: Using a segmented regression for the interrupted time series, on-time OR start time deviations were found to be significantly lower after the implementation of CPTS (p < .0001). The implementation resulted in a fourfold improvement in on-time OR starts (p < .01) while significantly reducing idle OR time (p…
Flexible Services and Manufacturing Journal, Dec 28, 2016
AbstractA critical step in patient care path is diagnosis. The demand for advanced imaging tests,... more AbstractA critical step in patient care path is diagnosis. The demand for advanced imaging tests, such as computerized axial tomography, magnetic resonance imaging and positron emission tomography (PET), increased dramatically in the past 15 years. Since imaging equipment remains relatively expensive, in order to fit the demand, the imaging resources must be managed effectively while ensuring required quality of service. In PET, a radiopharmaceutical (radioactive substance) is injected to patients prior to their scans. The time between substance injection and scan (standby or uptake time) is rigid. This constraint makes the patient appointment scheduling more challenging, because if at the end of the expected uptake time the scanner is not available, the quality of the scan is jeopardized (due to short half-life duration of the substance). The availability of the scanner is a consequence of prior scans’ appointments and durations. The aim of this work is to develop an approach for appointment scheduling in a system with one scanner, given a sequence of patients and rigid uptake time, in order to minimize the length of day while satisfying a minimal pre-determined quality of service. In order to solve this stochastic problem, we formulate its equivalent deterministic problem, based on simulated data, as a mixed-integer linear programming. To overcome the dimensionality limitations, we develop a simulation-based sequential algorithm that solves the problem in a reasonable time. We found that a fixed slot per scan policy, as a benchmark, is inferior to our method, especially in achieving stable and fair quality of service for patients.
Patient health is represented by a set of diagnoses, which determines personal health status. Eac... more Patient health is represented by a set of diagnoses, which determines personal health status. Each set corresponds to a certain health state and so, can be treated as an individual performance in this state and individual health can be considered as a corresponding multi-state system. Appropriate metrics for measuring patient’s state diagnosis changes during hospitalization are proposed. The first metric determines the dissimilarity between two single diagnoses, each of which is based on internationally recognized classification scheme. The second metric is aimed to compare between two sets of diagnoses with respect to the same patient and is based on the first metric, but uses additional, recently proposed, ideas of measuring heterogeneity/segregation between sets of categorical data. A numerical example and a real world illustration of the above measures are provided. The ultimate goal is the analysis of multistate health status data in order to improve the accuracy and quality of...
Abstract Prioritization is widely used in quality practice. Since the process is accompanied by u... more Abstract Prioritization is widely used in quality practice. Since the process is accompanied by unavoidable errors, in order to improve accuracy, prioritization is usually repeated by M independent experts, followed by aggregation of their decisions. The article studies the bias of such a procedure, under the assumption of a “gold standard” existence and Mallows’ model of errors creation, for different combinations of M, number of alternatives—n and probability of error-free prioritization P 0. Thereby it becomes possible to know how many experts are required and how accurate must they be in order to prevent the bias from exceeding some threshold.
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