Using prediction to facilitate patient flow in a health care delivery chain

Thesis (Ph. D.)--Massachusetts Institute of Technology, Engineering Systems Division, 2013.

[1]  Daniel M. Fox.  Chaos and Organization in Health Care , 2011 .

[2]  K D Stark,et al.  Predicting readmission to substance abuse treatment using state information systems. The impact of client and treatment characteristics. , 2000, Journal of substance abuse.

[3]  Joseph Brian Adams,et al.  Logistic and neural network models for predicting a hospital admission , 2005 .

[4]  G. Jensen,et al.  Predicting early nonelective hospital readmission in nutritionally compromised older adults. , 1997, The American journal of clinical nutrition.

[5]  Steven L Bernstein,et al.  Development and validation of a new index to measure emergency department crowding. , 2003, Academic emergency medicine : official journal of the Society for Academic Emergency Medicine.

[6]  Chuan Zhou,et al.  Forecasting emergency department crowding: a prospective, real-time evaluation. , 2009, Journal of the American Medical Informatics Association : JAMIA.

[7]  A Russell Localio,et al.  The impact of emergency department crowding measures on time to antibiotics for patients with community-acquired pneumonia. , 2007, Annals of emergency medicine.

[8]  S. Schneider,et al.  Emergency department crowding: a point in time. , 2003, Annals of emergency medicine.

[9]  E P Steinberg,et al.  Predicting hospital readmissions in the Medicare population. , 1985, Inquiry : a journal of medical care organization, provision and financing.

[10]  E. Hing,et al.  Wait time for treatment in hospital emergency departments: 2009. , 2012, NCHS data brief.

[11]  T. Rosenthal.  The Medical Home: Growing Evidence to Support a New Approach to Primary Care , 2008, The Journal of the American Board of Family Medicine.

[12]  James P. Womack,et al.  Lean Thinking: Banish Waste and Create Wealth in Your Corporation , 1996 .

[13]  P. Shekelle,et al.  Systematic Review: Impact of Health Information Technology on Quality, Efficiency, and Costs of Medical Care , 2006, Annals of Internal Medicine.

[14]  Robert G. Sargent,et al.  Validation and verification of simulation models , 1999, Proceedings of the 2004 Winter Simulation Conference, 2004..

[15]  S. Zeger,et al.  The challenge of predicting demand for emergency department services. , 2008, Academic emergency medicine : official journal of the Society for Academic Emergency Medicine.

[16]  Peter Bacchetti,et al.  Effect of emergency department crowding on time to antibiotics in patients admitted with community-acquired pneumonia. , 2007, Annals of emergency medicine.

[17]  Eric Howell,et al.  Active Bed Management by Hospitalists and Emergency Department Throughput , 2008, Annals of Internal Medicine.

[18]  David W. Hosmer,et al.  Applied Logistic Regression , 1991 .

[19]  L. Beril Toktay,et al.  The Value of Collaborative Forecasting in Supply Chains , 2011, Manuf. Serv. Oper. Manag..

[20]  E. Ionides,et al.  Forecasting models of emergency department crowding. , 2009, Academic emergency medicine : official journal of the Society for Academic Emergency Medicine.

[21]  S D Culler,et al.  Preventable hospitalizations in primary care shortage areas. An analysis of vulnerable Medicare beneficiaries. , 1999, Archives of family medicine.

[22]  Proctor P Reid,et al.  The Human Factor in Health Care Systems Design , 2005 .

[23]  Chad Boult,et al.  Screening Elders for Risk of Hospital Admission , 1993, Journal of the American Geriatrics Society.

[24]  L. Davis,et al.  Prediction of hospital length of stay. , 1966, Health services research.

[25]  Johann L. Hurink,et al.  Decision support system for the operating room rescheduling problem , 2012, Health care management science.

[26]  Gad Abraham,et al.  Short-Term Forecasting of Emergency Inpatient Flow , 2009, IEEE Transactions on Information Technology in Biomedicine.

[27]  Robert G. Sargent,et al.  Verification, validation, and accreditation: verification, validation, and accreditation of simulation models , 2000, WSC '00.

[28]  Scott L. Zeger,et al.  Predicting Emergency Department Length of Stay Using Quantile Regression , 2009, 2009 International Conference on Management and Service Science.

[29]  Peter J. Haug,et al.  A multivariate time series approach to modeling and forecasting demand in the emergency department , 2009, J. Biomed. Informatics.

[30]  Osman Balci.  Principles and techniques of simulation validation, verification, and testing , 1995, WSC '95.

[31]  G. Hejblum,et al.  A systematic review of models for forecasting the number of emergency department visits , 2009, Emergency Medicine Journal.

[32]  Dante Morra,et al.  Understanding hospital and emergency department congestion: an examination of inpatient admission trends and bed resources. , 2010, CJEM.

[33]  Jeffrey L. Schnipper,et al.  Inability of Providers to Predict Unplanned Readmissions , 2011, Journal of General Internal Medicine.

[34]  Bradley D Gordon,et al.  Using online analytical processing to manage emergency department operations. , 2004, Academic emergency medicine : official journal of the Society for Academic Emergency Medicine.

[35]  Pierce Story,et al.  Management Engineering for Effective Healthcare Delivery: Principles and Applications , 2011 .

[36]  A Schmoldt,et al.  Digitoxin metabolism by rat liver microsomes. , 1975, Biochemical pharmacology.

[37]  Shari J. Welch,et al.  An independent evaluation of four quantitative emergency department crowding scales. , 2006, Academic emergency medicine : official journal of the Society for Academic Emergency Medicine.

[38]  T. Falvo,et al.  The opportunity loss of boarding admitted patients in the emergency department. , 2007, Academic emergency medicine : official journal of the Society for Academic Emergency Medicine.

[39]  Dominik Aronsky,et al.  Forecasting emergency department crowding: a discrete event simulation. , 2008, Annals of emergency medicine.

[40]  Robert A Lowe,et al.  Emergency department crowding as a health policy issue: past development, future directions. , 2002, Annals of emergency medicine.

[41]  Wallace J. Hopp,et al.  Factory physics : foundations of manufacturing management , 1996 .

[42]  Stephen K Epstein,et al.  Development of an emergency department work score to predict ambulance diversion. , 2006, Academic emergency medicine : official journal of the Society for Academic Emergency Medicine.

[43]  D. Aronsky,et al.  Systematic review of emergency department crowding: causes, effects, and solutions. , 2008, Annals of emergency medicine.

[44]  D. Spaite,et al.  Measuring and improving quality in emergency medicine. , 2002, Academic emergency medicine : official journal of the Society for Academic Emergency Medicine.

[45]  A. Sher,et al.  Characterization of a programmed alteration in an 18S ribosomal gene that accompanies the experimental induction of drug resistance in Schistosoma mansoni. , 1991, Proceedings of the National Academy of Sciences of the United States of America.

[46]  F. Zwemer,et al.  Coping with a crowded ED: an expanded unique role for midlevel providers. , 2003, The American journal of emergency medicine.

[47]  Dominik Aronsky,et al.  The emergency department occupancy rate: a simple measure of emergency department crowding? , 2008, Annals of emergency medicine.

[48]  Karen Clark,et al.  Patient Flow in the Emergency Department: Is Timeliness to Events Related to Length of Hospital Stay? , 2007, Journal of nursing care quality.

[49]  Kedar Sambhoos,et al.  Models for solving emergency room crisis. , 2010 .

[50]  Steven Walczak,et al.  Predicting Hospital Length of Stay with Neural Networks , 1998, FLAIRS.

[51]  Jesse M Pines,et al.  The emergency department crowding paradox: the longer you stay, the less care you get. , 2007, Annals of emergency medicine.

[52]  Jiexun Li,et al.  Hospital Admission Prediction Using Pre-hospital Variables , 2009, 2009 IEEE International Conference on Bioinformatics and Biomedicine.

[53]  Anthony Kirtland,et al.  Simulating an emergency department “is as much fun as…” , 1995, WSC '95.

[54]  D. King,et al.  Redesigning emergency department patient flows: Application of Lean Thinking to health care , 2006, Emergency medicine Australasia : EMA.

[55]  Ranjit Bose,et al.  Knowledge management-enabled health care management systems: capabilities, infrastructure, and decision-support , 2003, Expert Syst. Appl..

[56]  Wojtek Michalowski,et al.  Using a Bayesian belief network model to categorize length of stay for radical prostatectomy patients , 2006, Health care management science.

[57]  Padraig Cunningham,et al.  An artificial neural network ensemble to predict disposition and length of stay in children presenting with bronchiolitis , 2004, European journal of emergency medicine : official journal of the European Society for Emergency Medicine.

[58]  R. Haynes,et al.  Effects of computer-based clinical decision support systems on physician performance and patient outcomes: a systematic review. , 1998, JAMA.

[59]  Khoa Nguyen,et al.  Bursting at the Seams: Improving Patient Flow to Help America's Emergency Departments , 2004 .

[60]  William M. Grove,et al.  Clinical versus mechanical prediction , 2000 .

[61]  R H Sarma,et al.  Delineation of the intimate details of the backbone conformation of pyridine nucleotide coenzymes in aqueous solution. , 1975, Biochemical and biophysical research communications.

[62]  M. Wargon,et al.  From model to forecasting: a multicenter study in emergency departments. , 2010, Academic emergency medicine : official journal of the Society for Academic Emergency Medicine.

[63]  Peter Szolovits,et al.  The coming of age of artificial intelligence in medicine , 2009, Artif. Intell. Medicine.

[64]  G Vassilacopoulos,et al.  Allocating Doctors to Shifts in an Accident and Emergency Department , 1985, The Journal of the Operational Research Society.

[65]  B. Asplin,et al.  Hospital-based emergency care: a future without boarding? , 2006, Annals of emergency medicine.

[66]  G. M. Koole,et al.  Modeling the emergency cardiac in-patient flow: an application of queuing theory , 2007, Health care management science.

[67]  Darrell W. Starks,et al.  The use of simulation to reduce the length of stay in an emergency department , 2003, Proceedings of the 2003 Winter Simulation Conference, 2003..

[68]  Jordan S Peck,et al.  Predicting emergency department inpatient admissions to improve same-day patient flow. , 2012, Academic emergency medicine : official journal of the Society for Academic Emergency Medicine.

[69]  Dominik Aronsky,et al.  Predicting Hospital Admission for Emergency Department Patients using a Bayesian Network , 2005, AMIA.

[70]  Richard P. Lewis,et al.  ACC/AHA guidelines for the management of patients with acute myocardial infarction. A report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines (Committee on Management of Acute Myocardial Infarction). , 1996, Journal of the American College of Cardiology.

[71]  อนิรุธ สืบสิงห์,et al.  Data Mining Practical Machine Learning Tools and Techniques , 2014 .

[72]  Mark Fackrell,et al.  Predicting overflow in an emergency department , 2007 .

[73]  Elizabeth H Bradley,et al.  US emergency department performance on wait time and length of visit. , 2010, Annals of emergency medicine.

[74]  Frank McGuire.  Using simulation to reduce length of stay in emergency departments , 1994, Proceedings of Winter Simulation Conference.

[75]  Carl J Pepine,et al.  ACC/AHA guideline update for the management of patients with unstable angina and non-ST-segment elevation myocardial infarction--2002: summary article: a report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines (Committee on the Management of Patients , 2002, Circulation.

[76]  Todd G Nick,et al.  Estimating the degree of emergency department overcrowding in academic medical centers: results of the National ED Overcrowding Study (NEDOCS). , 2004, Academic emergency medicine : official journal of the Society for Academic Emergency Medicine.

[77]  Steven J. Spear,et al.  Chasing the Rabbit: How Market Leaders Outdistance the Competition and How Great Companies Can Catch up and Win , 2008 .

[78]  P H Millard,et al.  Developing a Bayesian belief network for the management of geriatric hospital care , 2001, Health care management science.

[79]  E. Dickson,et al.  Use of lean in the emergency department: a case series of 4 hospitals. , 2009, Annals of emergency medicine.

[80]  Rajiv Kohli,et al.  HMSS: a management support system for concurrent hospital decision making , 1996, Decision Support Systems.

[81]  Peter Szolovits,et al.  Artificial intelligence in medical diagnosis. , 1988, Annals of internal medicine.

[82]  Melanie Jessup,et al.  Implementing an emergency department patient admission predictive tool: insights from practice. , 2010, Journal of health organization and management.

[83]  Sinead O'Doherty,et al.  A validated clinical model to predict the need for admission and length of stay in children with acute bronchiolitis , 2004, European journal of emergency medicine : official journal of the European Society for Emergency Medicine.

[84]  Victor R Fuchs,et al.  Health care reform: why? What? When? , 2005, Health affairs.

[85]  William J. Long.  Medical Diagnosis using a probabilistic causal network , 1989, Appl. Artif. Intell..

[86]  Steffen Bayer,et al.  Business dynamics: Systems thinking and modeling for a complex world , 2004 .

[87]  Bengt Klefsjö,et al.  The machine that changed the world , 2008 .

[88]  Steven Walczak,et al.  A decision support tool for allocating hospital bed resources and determining required acuity of care , 2003, Decis. Support Syst..

[89]  Yan Sun,et al.  Predicting hospital admissions at emergency department triage using routine administrative data. , 2011, Academic emergency medicine : official journal of the Society for Academic Emergency Medicine.

[90]  Karin V Rhodes,et al.  A conceptual model of emergency department crowding. , 2003, Annals of emergency medicine.

[91]  V M Trivedi,et al.  A stochastic model for predicting discharges: applications for achieving occupancy goals in hospitals. , 1980, Socio-economic planning sciences.

[92]  T. McBride,et al.  Predicting Nursing-Home Admission and Length of Stay: A Duration Analysis , 1991, Medical care.

[93]  Elizabeth Lee-Lewandrowski,et al.  Implementation of a point-of-care satellite laboratory in the emergency department of an academic medical center. Impact on test turnaround time and patient emergency department length of stay. , 2003, Archives of pathology & laboratory medicine.

[94]  Taesik Lee,et al.  Reducing Emergency Department overcrowding - five patient buffer concepts in comparison , 2008, 2008 Winter Simulation Conference.

[95]  Caleb J. Siefert,et al.  Factors Associated with Extended Length of Stay for Patients Presenting to an Urban Psychiatric Emergency Service: A Case-Control Study , 2009, The Journal of Behavioral Health Services & Research.

[96]  Dominik Aronsky,et al.  Forecasting emergency department crowding: an external, multicenter evaluation. , 2009, Annals of emergency medicine.

[97]  Shimin Zheng,et al.  The potency of team-based care interventions for hypertension: a meta-analysis. , 2009, Archives of internal medicine.

[98]  B. Starfield,et al.  The medical home, access to care, and insurance: a review of evidence. , 2004, Pediatrics.

[99]  Asa Viccellio,et al.  The association between transfer of emergency department boarders to inpatient hallways and mortality: a 4-year experience. , 2009, Annals of emergency medicine.

[100]  Louis Rubino,et al.  Innovative Approach to the Aims for Improvement: Emergency Department Patient Throughput in an Impacted Urban Setting , 2007, The Journal of ambulatory care management.

[101]  Kevin E McVaney,et al.  How well do paramedics predict admission to the hospital? A prospective study. , 2006, The Journal of emergency medicine.

[102]  Kathleen L. Mosier,et al.  Does automation bias decision-making? , 1999, Int. J. Hum. Comput. Stud..

[103]  Fangruo Chen,et al.  Market Segmentation, Advanced Demand Information, and Supply Chain Performance , 2000, Manuf. Serv. Oper. Manag..

[104]  C. Arslanian-Engoren,et al.  Do Emergency Nurses' Triage Decisions Predict Differences in Admission or Discharge Diagnoses for Acute Coronary Syndromes? , 2004, The Journal of cardiovascular nursing.

[105]  Ben Harris,et al.  Emergency department crowding and decreased quality of pain care. , 2008, Academic emergency medicine : official journal of the Society for Academic Emergency Medicine.

[106]  H. Rubin,et al.  Hospitalists and an innovative emergency department admission process , 2004, Journal of General Internal Medicine.

[107]  Irene M. Spinello.  Electronic health records in ambulatory care. , 2008, The New England journal of medicine.

[108]  Jingshan Li,et al.  Modeling and analysis of hospital emergency department: An analytical framework and problem formulation , 2010, 2010 IEEE International Conference on Automation Science and Engineering.

[109]  R. Dittus,et al.  Optimizing cardiology capacity to reduce emergency department boarding: a systems engineering approach. , 2008, American heart journal.

[110]  David P Sklar,et al.  Emergency department crowding, part 1--concept, causes, and moral consequences. , 2009, Annals of emergency medicine.

[111]  Manuel D. Rossetti,et al.  Emergency department simulation and determination of optimal attending physician staffing schedules , 1999, WSC '99.

[112]  Carlos A Camargo,et al.  Continued rise in the use of mid-level providers in US emergency departments, 1993–2009 , 2012, International Journal of Emergency Medicine.

[113]  Peter Szolovits.  Uncertainty and Decisions in Medical Informatics , 1995, Methods of Information in Medicine.

[114]  Robbert Huijsman,et al.  Supply chain management in health services: an overview , 2011 .

[115]  S. Trzeciak,et al.  Emergency department overcrowding in the United States: an emerging threat to patient safety and public health , 2003, Emergency medicine journal : EMJ.

[116]  Elliott Fisher,et al.  Health Care Spending , Quality , and Outcomes More Isn ’ t Always Better , 2009 .

[117]  Jorge Miguel dos Santos Fradinho.  Towards high performing hospital enterprise architectures : elevating hospitals to lean enterprise thinking , 2011 .

[118]  P J Haug,et al.  A comprehensive set of coded chief complaints for the emergency department. , 2001, Academic emergency medicine : official journal of the Society for Academic Emergency Medicine.