Policy Points: Scarce resources, especially in population health and public health practice, unde... more Policy Points: Scarce resources, especially in population health and public health practice, underlie the importance of strategic planning. Public health agencies' current planning and priority setting efforts are often narrow, at times opaque, and focused on single metrics such as cost-effectiveness. As demonstrated by SMART Vaccines, a decision support software system developed by the Institute of Medicine and the National Academy of Engineering, new approaches to strategic planning allow the formal incorporation of multiple stakeholder views and multicriteria decision making that surpass even those sophisticated cost-effectiveness analyses widely recommended and used for public health planning. Institutions of higher education can and should respond by building on modern strategic planning tools as they teach their students how to improve population health and public health practice. Strategic planning in population health and public health practice often uses single indicato...
As the mechanisms for discovery, development, and delivery of new vaccines become increasingly co... more As the mechanisms for discovery, development, and delivery of new vaccines become increasingly complex, strategic planning and priority setting have become ever more crucial. Traditional single value metrics such as disease burden or cost-effectiveness no longer suffice to rank vaccine candidates for development. The Institute of Medicine-in collaboration with the National Academy of Engineering-has developed a novel software system to support vaccine prioritization efforts. The Strategic Multi-Attribute Ranking Tool for Vaccines-SMART Vaccines-allows decision makers to specify their own value structure, selecting from among 28 pre-defined and up to 7 user-defined attributes relevant to the ranking of vaccine candidates. Widespread use of SMART Vaccines will require compilation of a comprehensive data repository for numerous relevant populations-including their demographics, disease burdens and associated treatment costs, as well as characterizing performance features of potential o...
Journal of Healthcare Management American College of Healthcare Executives, 2011
Discrete-event simulation can be used as an effective tool for healthcare administrators to &... more Discrete-event simulation can be used as an effective tool for healthcare administrators to "test" various operational decisions. The recent growth in hospital outpatient volumes and a constrained financial environment make discrete-event simulation a cost-effective way to diagnose inefficiency and create and test strategies for improvement. This study shows how discrete-event simulation was used in an adult medicine clinic within a large, tertiary care, academic medical center. Simulation creation steps are discussed, including information gathering, process mapping, data collection, model creation, and results. Results of the simulation indicated that system bottle-necks were present in the medication administration and check-out steps of the clinic process. The simulation predicted that matching resources to excessive demand at appropriate times for these bottleneck steps would reduce patients' mean time in the system (i.e., visit time) from 124.3 (s.d. +/- 65.7) minutes to 87.0 (s.d. +/- 36.4) minutes. Although other factors may affect real-world operations of a clinic, discrete-event simulation allows healthcare administrators and clinic operational decision makers to observe the effects of changing staffing and resource allocations on patient wait and throughput time. Discrete-event simulation is not a cure-all for clinic throughput problems, but can be a strong tool to provide evidentiary guidance for clinic operational redesign.
Healthcare organizations face challenges in efficiently accommodating increased patient demand wi... more Healthcare organizations face challenges in efficiently accommodating increased patient demand with limited resources and capacity. The modern reimbursement environment prioritizes the maximization of operational efficiency and the reduction of unnecessary costs (i.e., waste) while maintaining or improving quality. As healthcare organizations adapt, significant pressures are placed on leaders to make difficult operational and budgetary decisions. In lieu of hard data, decision makers often base these decisions on subjective information. Discrete event simulation (DES), a computerized method of imitating the operation of a real-world system (e.g., healthcare delivery facility) over time, can provide decision makers with an evidence-based tool to develop and objectively vet operational solutions prior to implementation. DES in healthcare commonly focuses on (1) improving patient flow, (2) managing bed capacity, (3) scheduling staff, (4) managing patient admission and scheduling procedures, and (5) using ancillary resources (e.g., labs, pharmacies). This article describes applicable scenarios, outlines DES concepts, and describes the steps required for development. An original DES model developed to examine crowding and patient flow for staffing decision making at an urban academic emergency department serves as a practical example.
European journal of emergency medicine : official journal of the European Society for Emergency Medicine, Jan 20, 2016
Emergency Department (ED) patient arrivals vary daily and change considerably during holidays, po... more Emergency Department (ED) patient arrivals vary daily and change considerably during holidays, posing challenges to resource allocation. Ramadan, during which observant Muslims follow a daily fasting period for ∼30 days, could represent a unique annual circumstance that predictably alters ED arrivals in predominantly Muslim populations. Our study examined an adult and pediatric ED in the United Arab Emirates to determine whether arrival patterns and patient characteristics differed during Ramadan. Hourly arrivals, census (number of patients in ED at any given time), and visit characteristics were retrospectively compared for Ramadan versus non-Ramadan periods over 4 years (2010-2013). Hourly arrivals and census were plotted using two-way repeated-measures analysis of variance. Differences in characteristics were examined using the χ-test and Wilcoxon rank sum tests. Ramadan adult and pediatric ED arrival patterns differed significantly (P<0.001) from non-Ramadan days, with sharp ...
Patient triage is necessary to manage excessive patient volumes and identify those with critical ... more Patient triage is necessary to manage excessive patient volumes and identify those with critical conditions. The most common triage system used today, Emergency Severity Index (ESI), focuses on resources utilized and critical outcomes. This study derives and validates a computer-based electronic triage system (ETS) to improve patient acuity distribution based on serious patient outcomes. This cross-sectional study of 25,198 (97 million weighted) adult emergency department visits from the 2009 National Hospital Ambulatory Medical Care Survey. The ETS distributes patients by using a composite outcome based on the estimated probability of mortality, intensive care unit admission, or transfer to operating room or catheterization suite. We compared the ETS with the ESI based on the differentiation of patients, outcomes, inpatient hospitalization, and resource utilization. Of the patients included, 3.3% had the composite outcome and 14% were admitted, and 2.52 resources/patient were used....
Journal of healthcare management / American College of Healthcare Executives
Discrete-event simulation can be used as an effective tool for healthcare administrators to "... more Discrete-event simulation can be used as an effective tool for healthcare administrators to "test" various operational decisions. The recent growth in hospital outpatient volumes and a constrained financial environment make discrete-event simulation a cost-effective way to diagnose inefficiency and create and test strategies for improvement. This study shows how discrete-event simulation was used in an adult medicine clinic within a large, tertiary care, academic medical center. Simulation creation steps are discussed, including information gathering, process mapping, data collection, model creation, and results. Results of the simulation indicated that system bottle-necks were present in the medication administration and check-out steps of the clinic process. The simulation predicted that matching resources to excessive demand at appropriate times for these bottleneck steps would reduce patients' mean time in the system (i.e., visit time) from 124.3 (s.d. +/- 65.7) mi...
Journal of healthcare management / American College of Healthcare Executives
Healthcare organizations face challenges in efficiently accommodating increased patient demand wi... more Healthcare organizations face challenges in efficiently accommodating increased patient demand with limited resources and capacity. The modern reimbursement environment prioritizes the maximization of operational efficiency and the reduction of unnecessary costs (i.e., waste) while maintaining or improving quality. As healthcare organizations adapt, significant pressures are placed on leaders to make difficult operational and budgetary decisions. In lieu of hard data, decision makers often base these decisions on subjective information. Discrete event simulation (DES), a computerized method of imitating the operation of a real-world system (e.g., healthcare delivery facility) over time, can provide decision makers with an evidence-based tool to develop and objectively vet operational solutions prior to implementation. DES in healthcare commonly focuses on (1) improving patient flow, (2) managing bed capacity, (3) scheduling staff, (4) managing patient admission and scheduling proced...
Background: Emergency Departments (ED) are challenged with excess demand for services and inadequ... more Background: Emergency Departments (ED) are challenged with excess demand for services and inadequate system capacity. Crowding at two independent EDs within a health system prompted an examination of the potential effects of improving patient throughput. The objective of this study was to determine the effects of reducing ED dwell time on temporal patterns of patient flow and demand for ED resources. Methods: Separate discrete event simulation (DES) models were developed for the EDs of a 1,000-bed urban medical center and a 560-bed community medical center using patient flow information. These models characterized the effects of reducing patient dwell time on ED care area census (i.e., staffing needs), waiting room census, total length of stay (LOS) and waiting time. Dwell time was defined as the time interval from when a patient entered the main ED care area to when the patient exited the ED by discharge or hospital admission. Total LOS is defined as the entire time interval from ED from arrival to exit (including waiting time). Results: DES results for each site demonstrate how natural patient arrivals and common hospital admission processes generate common temporal patterns of decreased crowding. Improving flow translates to most substantial reductions in waiting time and waiting room census during evening hours (17:00 to 22:00 hours). Significant effects on ED care area census and staffing demands are lagged, not occurring until overnight hours (2:00 to 8:00 hours). We reduced patient dwell time in 5% increments within the urban ED (16.2 min) and community ED (13.5 min) from 5% to 15%. For example, a 10% decrease in dwell time at the urban ED (32.4 min) and community ED (27.0 min) resulted in respective decreases in evening waiting room census by 49% (10.8 patients) and 26% (3.5 patients) during evening hours and ED care area census by 16% (3.6 patients) and 11% (2.0 patients) overnight. Conclusions: DES results suggest that increasing ED efficiency will most significantly decrease delays experienced by evening arrivals and provide opportunities to decrease care area census and reduce staff overnight.
Background: We developed a practical influenza forecast model based on real-time, geographically ... more Background: We developed a practical influenza forecast model based on real-time, geographically focused, and easy to access data, designed to provide individual medical centers with advanced warning of the expected number of influenza cases, thus allowing for sufficient time to implement interventions. Secondly, we evaluated the effects of incorporating a real-time influenza surveillance system, Google Flu Trends, and meteorological and temporal information on forecast accuracy.
Google Flu Trends (GFT) is a novel Internet-based influenza surveillance system that uses search... more Google Flu Trends (GFT) is a novel Internet-based influenza surveillance system that uses search engine query data to estimate influenza activity and is available in near real time. This study assesses the temporal correlation of city GFT data to cases of influenza and standard crowding indices from an inner-city emergency department (ED). This study was performed during a 21-month period (from January 2009 through October 2010) at an urban academic hospital with physically and administratively separate adult and pediatric EDs. We collected weekly data from GFT for Baltimore, Maryland; ED Centers for Disease Control and Prevention-reported standardized influenzalike illness (ILI) data; laboratory-confirmed influenza data; and ED crowding indices (patient volume, number of patients who left without being seen, waiting room time, and length of stay for admitted and discharged patients). Pediatric and adult data were analyzed separately using cross-correlation with GFT. GFT correlated with both number of positive influenza test results (adult ED, r = 0.876; pediatric ED, r = 0.718) and number of ED patients presenting with ILI (adult ED, r = 0.885; pediatric ED, r = 0.652). Pediatric but not adult crowding measures, such as total ED volume (r = 0.649) and leaving without being seen (r = 0.641), also had good correlation with GFT. Adult crowding measures for low-acuity patients, such as waiting room time (r = 0.421) and length of stay for discharged patients (r = 0.548), had moderate correlation with GFT. City-level GFT shows strong correlation with influenza cases and ED ILI visits, validating its use as an ED surveillance tool. GFT correlated with several pediatric ED crowding measures and those for low-acuity adult patients.
Objectives: System complexity is introduced as a new measure of system state for the emergency de... more Objectives: System complexity is introduced as a new measure of system state for the emergency department (ED). In its original form, the measure quantifies the uncertainty of demands on system resources. For application in the ED, the measure is being modified to quantify both workload and uncertainty to produce a single integrated measure of system state.
Journal of the American Medical Informatics Association : JAMIA, Jan 7, 2015
Hospitals are challenged to provide timely patient care while maintaining high resource utilizati... more Hospitals are challenged to provide timely patient care while maintaining high resource utilization. This has prompted hospital initiatives to increase patient flow and minimize nonvalue added care time. Real-time demand capacity management (RTDC) is one such initiative whereby clinicians convene each morning to predict patients able to leave the same day and prioritize their remaining tasks for early discharge. Our objective is to automate and improve these discharge predictions by applying supervised machine learning methods to readily available health information. The authors use supervised machine learning methods to predict patients' likelihood of discharge by 2 p.m. and by midnight each day for an inpatient medical unit. Using data collected over 8000 patient stays and 20 000 patient days, the predictive performance of the model is compared to clinicians using sensitivity, specificity, Youden's Index (i.e., sensitivity + specificity - 1), and aggregate accuracy measure...
Journal of the American Medical Informatics Association : JAMIA, Jan 5, 2015
To develop and prospectively evaluate a web-based tool that forecasts the daily bed need for admi... more To develop and prospectively evaluate a web-based tool that forecasts the daily bed need for admissions from the cardiac catheterization laboratory using routinely available clinical data within electronic medical records (EMRs). The forecast model was derived using a 13-month retrospective cohort of 6384 catheterization patients. Predictor variables such as demographics, scheduled procedures, and clinical indicators mined from free-text notes were input to a multivariable logistic regression model that predicted the probability of inpatient admission. The model was embedded into a web-based application connected to the local EMR system and used to support bed management decisions. After implementation, the tool was prospectively evaluated for accuracy on a 13-month test cohort of 7029 catheterization patients. The forecast model predicted admission with an area under the receiver operating characteristic curve of 0.722. Daily aggregate forecasts were accurate to within one bed for ...
Policy Points: Scarce resources, especially in population health and public health practice, unde... more Policy Points: Scarce resources, especially in population health and public health practice, underlie the importance of strategic planning. Public health agencies' current planning and priority setting efforts are often narrow, at times opaque, and focused on single metrics such as cost-effectiveness. As demonstrated by SMART Vaccines, a decision support software system developed by the Institute of Medicine and the National Academy of Engineering, new approaches to strategic planning allow the formal incorporation of multiple stakeholder views and multicriteria decision making that surpass even those sophisticated cost-effectiveness analyses widely recommended and used for public health planning. Institutions of higher education can and should respond by building on modern strategic planning tools as they teach their students how to improve population health and public health practice. Strategic planning in population health and public health practice often uses single indicato...
As the mechanisms for discovery, development, and delivery of new vaccines become increasingly co... more As the mechanisms for discovery, development, and delivery of new vaccines become increasingly complex, strategic planning and priority setting have become ever more crucial. Traditional single value metrics such as disease burden or cost-effectiveness no longer suffice to rank vaccine candidates for development. The Institute of Medicine-in collaboration with the National Academy of Engineering-has developed a novel software system to support vaccine prioritization efforts. The Strategic Multi-Attribute Ranking Tool for Vaccines-SMART Vaccines-allows decision makers to specify their own value structure, selecting from among 28 pre-defined and up to 7 user-defined attributes relevant to the ranking of vaccine candidates. Widespread use of SMART Vaccines will require compilation of a comprehensive data repository for numerous relevant populations-including their demographics, disease burdens and associated treatment costs, as well as characterizing performance features of potential o...
Journal of Healthcare Management American College of Healthcare Executives, 2011
Discrete-event simulation can be used as an effective tool for healthcare administrators to &... more Discrete-event simulation can be used as an effective tool for healthcare administrators to &amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;quot;test&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;quot; various operational decisions. The recent growth in hospital outpatient volumes and a constrained financial environment make discrete-event simulation a cost-effective way to diagnose inefficiency and create and test strategies for improvement. This study shows how discrete-event simulation was used in an adult medicine clinic within a large, tertiary care, academic medical center. Simulation creation steps are discussed, including information gathering, process mapping, data collection, model creation, and results. Results of the simulation indicated that system bottle-necks were present in the medication administration and check-out steps of the clinic process. The simulation predicted that matching resources to excessive demand at appropriate times for these bottleneck steps would reduce patients&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;#39; mean time in the system (i.e., visit time) from 124.3 (s.d. +/- 65.7) minutes to 87.0 (s.d. +/- 36.4) minutes. Although other factors may affect real-world operations of a clinic, discrete-event simulation allows healthcare administrators and clinic operational decision makers to observe the effects of changing staffing and resource allocations on patient wait and throughput time. Discrete-event simulation is not a cure-all for clinic throughput problems, but can be a strong tool to provide evidentiary guidance for clinic operational redesign.
Healthcare organizations face challenges in efficiently accommodating increased patient demand wi... more Healthcare organizations face challenges in efficiently accommodating increased patient demand with limited resources and capacity. The modern reimbursement environment prioritizes the maximization of operational efficiency and the reduction of unnecessary costs (i.e., waste) while maintaining or improving quality. As healthcare organizations adapt, significant pressures are placed on leaders to make difficult operational and budgetary decisions. In lieu of hard data, decision makers often base these decisions on subjective information. Discrete event simulation (DES), a computerized method of imitating the operation of a real-world system (e.g., healthcare delivery facility) over time, can provide decision makers with an evidence-based tool to develop and objectively vet operational solutions prior to implementation. DES in healthcare commonly focuses on (1) improving patient flow, (2) managing bed capacity, (3) scheduling staff, (4) managing patient admission and scheduling procedures, and (5) using ancillary resources (e.g., labs, pharmacies). This article describes applicable scenarios, outlines DES concepts, and describes the steps required for development. An original DES model developed to examine crowding and patient flow for staffing decision making at an urban academic emergency department serves as a practical example.
European journal of emergency medicine : official journal of the European Society for Emergency Medicine, Jan 20, 2016
Emergency Department (ED) patient arrivals vary daily and change considerably during holidays, po... more Emergency Department (ED) patient arrivals vary daily and change considerably during holidays, posing challenges to resource allocation. Ramadan, during which observant Muslims follow a daily fasting period for ∼30 days, could represent a unique annual circumstance that predictably alters ED arrivals in predominantly Muslim populations. Our study examined an adult and pediatric ED in the United Arab Emirates to determine whether arrival patterns and patient characteristics differed during Ramadan. Hourly arrivals, census (number of patients in ED at any given time), and visit characteristics were retrospectively compared for Ramadan versus non-Ramadan periods over 4 years (2010-2013). Hourly arrivals and census were plotted using two-way repeated-measures analysis of variance. Differences in characteristics were examined using the χ-test and Wilcoxon rank sum tests. Ramadan adult and pediatric ED arrival patterns differed significantly (P<0.001) from non-Ramadan days, with sharp ...
Patient triage is necessary to manage excessive patient volumes and identify those with critical ... more Patient triage is necessary to manage excessive patient volumes and identify those with critical conditions. The most common triage system used today, Emergency Severity Index (ESI), focuses on resources utilized and critical outcomes. This study derives and validates a computer-based electronic triage system (ETS) to improve patient acuity distribution based on serious patient outcomes. This cross-sectional study of 25,198 (97 million weighted) adult emergency department visits from the 2009 National Hospital Ambulatory Medical Care Survey. The ETS distributes patients by using a composite outcome based on the estimated probability of mortality, intensive care unit admission, or transfer to operating room or catheterization suite. We compared the ETS with the ESI based on the differentiation of patients, outcomes, inpatient hospitalization, and resource utilization. Of the patients included, 3.3% had the composite outcome and 14% were admitted, and 2.52 resources/patient were used....
Journal of healthcare management / American College of Healthcare Executives
Discrete-event simulation can be used as an effective tool for healthcare administrators to "... more Discrete-event simulation can be used as an effective tool for healthcare administrators to "test" various operational decisions. The recent growth in hospital outpatient volumes and a constrained financial environment make discrete-event simulation a cost-effective way to diagnose inefficiency and create and test strategies for improvement. This study shows how discrete-event simulation was used in an adult medicine clinic within a large, tertiary care, academic medical center. Simulation creation steps are discussed, including information gathering, process mapping, data collection, model creation, and results. Results of the simulation indicated that system bottle-necks were present in the medication administration and check-out steps of the clinic process. The simulation predicted that matching resources to excessive demand at appropriate times for these bottleneck steps would reduce patients' mean time in the system (i.e., visit time) from 124.3 (s.d. +/- 65.7) mi...
Journal of healthcare management / American College of Healthcare Executives
Healthcare organizations face challenges in efficiently accommodating increased patient demand wi... more Healthcare organizations face challenges in efficiently accommodating increased patient demand with limited resources and capacity. The modern reimbursement environment prioritizes the maximization of operational efficiency and the reduction of unnecessary costs (i.e., waste) while maintaining or improving quality. As healthcare organizations adapt, significant pressures are placed on leaders to make difficult operational and budgetary decisions. In lieu of hard data, decision makers often base these decisions on subjective information. Discrete event simulation (DES), a computerized method of imitating the operation of a real-world system (e.g., healthcare delivery facility) over time, can provide decision makers with an evidence-based tool to develop and objectively vet operational solutions prior to implementation. DES in healthcare commonly focuses on (1) improving patient flow, (2) managing bed capacity, (3) scheduling staff, (4) managing patient admission and scheduling proced...
Background: Emergency Departments (ED) are challenged with excess demand for services and inadequ... more Background: Emergency Departments (ED) are challenged with excess demand for services and inadequate system capacity. Crowding at two independent EDs within a health system prompted an examination of the potential effects of improving patient throughput. The objective of this study was to determine the effects of reducing ED dwell time on temporal patterns of patient flow and demand for ED resources. Methods: Separate discrete event simulation (DES) models were developed for the EDs of a 1,000-bed urban medical center and a 560-bed community medical center using patient flow information. These models characterized the effects of reducing patient dwell time on ED care area census (i.e., staffing needs), waiting room census, total length of stay (LOS) and waiting time. Dwell time was defined as the time interval from when a patient entered the main ED care area to when the patient exited the ED by discharge or hospital admission. Total LOS is defined as the entire time interval from ED from arrival to exit (including waiting time). Results: DES results for each site demonstrate how natural patient arrivals and common hospital admission processes generate common temporal patterns of decreased crowding. Improving flow translates to most substantial reductions in waiting time and waiting room census during evening hours (17:00 to 22:00 hours). Significant effects on ED care area census and staffing demands are lagged, not occurring until overnight hours (2:00 to 8:00 hours). We reduced patient dwell time in 5% increments within the urban ED (16.2 min) and community ED (13.5 min) from 5% to 15%. For example, a 10% decrease in dwell time at the urban ED (32.4 min) and community ED (27.0 min) resulted in respective decreases in evening waiting room census by 49% (10.8 patients) and 26% (3.5 patients) during evening hours and ED care area census by 16% (3.6 patients) and 11% (2.0 patients) overnight. Conclusions: DES results suggest that increasing ED efficiency will most significantly decrease delays experienced by evening arrivals and provide opportunities to decrease care area census and reduce staff overnight.
Background: We developed a practical influenza forecast model based on real-time, geographically ... more Background: We developed a practical influenza forecast model based on real-time, geographically focused, and easy to access data, designed to provide individual medical centers with advanced warning of the expected number of influenza cases, thus allowing for sufficient time to implement interventions. Secondly, we evaluated the effects of incorporating a real-time influenza surveillance system, Google Flu Trends, and meteorological and temporal information on forecast accuracy.
Google Flu Trends (GFT) is a novel Internet-based influenza surveillance system that uses search... more Google Flu Trends (GFT) is a novel Internet-based influenza surveillance system that uses search engine query data to estimate influenza activity and is available in near real time. This study assesses the temporal correlation of city GFT data to cases of influenza and standard crowding indices from an inner-city emergency department (ED). This study was performed during a 21-month period (from January 2009 through October 2010) at an urban academic hospital with physically and administratively separate adult and pediatric EDs. We collected weekly data from GFT for Baltimore, Maryland; ED Centers for Disease Control and Prevention-reported standardized influenzalike illness (ILI) data; laboratory-confirmed influenza data; and ED crowding indices (patient volume, number of patients who left without being seen, waiting room time, and length of stay for admitted and discharged patients). Pediatric and adult data were analyzed separately using cross-correlation with GFT. GFT correlated with both number of positive influenza test results (adult ED, r = 0.876; pediatric ED, r = 0.718) and number of ED patients presenting with ILI (adult ED, r = 0.885; pediatric ED, r = 0.652). Pediatric but not adult crowding measures, such as total ED volume (r = 0.649) and leaving without being seen (r = 0.641), also had good correlation with GFT. Adult crowding measures for low-acuity patients, such as waiting room time (r = 0.421) and length of stay for discharged patients (r = 0.548), had moderate correlation with GFT. City-level GFT shows strong correlation with influenza cases and ED ILI visits, validating its use as an ED surveillance tool. GFT correlated with several pediatric ED crowding measures and those for low-acuity adult patients.
Objectives: System complexity is introduced as a new measure of system state for the emergency de... more Objectives: System complexity is introduced as a new measure of system state for the emergency department (ED). In its original form, the measure quantifies the uncertainty of demands on system resources. For application in the ED, the measure is being modified to quantify both workload and uncertainty to produce a single integrated measure of system state.
Journal of the American Medical Informatics Association : JAMIA, Jan 7, 2015
Hospitals are challenged to provide timely patient care while maintaining high resource utilizati... more Hospitals are challenged to provide timely patient care while maintaining high resource utilization. This has prompted hospital initiatives to increase patient flow and minimize nonvalue added care time. Real-time demand capacity management (RTDC) is one such initiative whereby clinicians convene each morning to predict patients able to leave the same day and prioritize their remaining tasks for early discharge. Our objective is to automate and improve these discharge predictions by applying supervised machine learning methods to readily available health information. The authors use supervised machine learning methods to predict patients' likelihood of discharge by 2 p.m. and by midnight each day for an inpatient medical unit. Using data collected over 8000 patient stays and 20 000 patient days, the predictive performance of the model is compared to clinicians using sensitivity, specificity, Youden's Index (i.e., sensitivity + specificity - 1), and aggregate accuracy measure...
Journal of the American Medical Informatics Association : JAMIA, Jan 5, 2015
To develop and prospectively evaluate a web-based tool that forecasts the daily bed need for admi... more To develop and prospectively evaluate a web-based tool that forecasts the daily bed need for admissions from the cardiac catheterization laboratory using routinely available clinical data within electronic medical records (EMRs). The forecast model was derived using a 13-month retrospective cohort of 6384 catheterization patients. Predictor variables such as demographics, scheduled procedures, and clinical indicators mined from free-text notes were input to a multivariable logistic regression model that predicted the probability of inpatient admission. The model was embedded into a web-based application connected to the local EMR system and used to support bed management decisions. After implementation, the tool was prospectively evaluated for accuracy on a 13-month test cohort of 7029 catheterization patients. The forecast model predicted admission with an area under the receiver operating characteristic curve of 0.722. Daily aggregate forecasts were accurate to within one bed for ...
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