Modeling factors influencing the demand for emergency department services in ontario: A comparison of methods

BMC Emergency Medicine

Volumn 11, Issue , 2011, Pages

  Moineddin, Rahim ^a,b,c   Meaney, Christopher ^a   Agha, Mohammad ^b,c,d,e   Zagorski, Brandon ^b   Glazier, Richard Henry ^a,b,c,d  

^a UNIVERSITY OF TORONTO   (Canada)

^b INSTITUTE FOR CLINICAL EVALUATIVE SCIENCES   (Canada)

^c UNIVERSITY OF TORONTO   (Canada)

^d ST MICHAEL'S HOSPITAL   (Canada)

^e PEDIATRIC ONCOLOGY GROUP OF ONTARIO   (Canada)

Author keywords

[No Author keywords available]

Indexed keywords

ADULT; AGED; AMBULATORY CARE; ARTICLE; BINOMIAL DISTRIBUTION; CANADA; COMORBIDITY; CROWDING; DISEASE SEVERITY; EDUCATIONAL STATUS; EMERGENCY HEALTH SERVICE; EMERGENCY TREATMENT; EMERGENCY WARD; FEMALE; HEALTH BEHAVIOR; HEALTH CARE ACCESS; HEALTH CARE DELIVERY; HEALTH CARE POLICY; HEALTH CARE UTILIZATION; HEALTH STATUS; HEALTH SURVEY; HIGH SCHOOL; HOUSEHOLD; HUMAN; INCOME; INTERMETHOD COMPARISON; MAJOR CLINICAL STUDY; MALE; MEDICAL RESEARCH; PATIENT CARE; PHYSICIAN; POISSON DISTRIBUTION; PRIMARY MEDICAL CARE; PROBABILITY; SCORING SYSTEM; SOCIAL STATUS; STATISTICAL ANALYSIS; STATISTICAL MODEL; URBAN AREA; EMERGENCY; HEALTH SERVICE; MIDDLE AGED; NONBIOLOGICAL MODEL; ORGANIZATION AND MANAGEMENT; REGRESSION ANALYSIS; SOCIOECONOMICS; STATISTICS; UTILIZATION REVIEW;

ADULT; AGED; AGED, 80 AND OVER; EMERGENCIES; EMERGENCY SERVICE, HOSPITAL; FEMALE; HEALTH SERVICES ACCESSIBILITY; HEALTH SERVICES NEEDS AND DEMAND; HUMANS; MALE; MIDDLE AGED; MODELS, ORGANIZATIONAL; ONTARIO; REGRESSION ANALYSIS; SOCIOECONOMIC FACTORS; YOUNG ADULT;

EID: 80052839950     PISSN: None     EISSN: 1471227X     Source Type: Journal    
DOI: 10.1186/1471-227X-11-13     Document Type: Article

References (24)

1. Chan B, Schull M, Schultz S. Emergency Department Services in Ontario: Atlas Report: Institute for Clinical Evaluative Sciences. 2001,
2. Paul P, Heng BH, Seow E, Molina J, Tay SY. Predictors of frequent attenders of emergency department at an acute general hospital in Singapore. Emergency Medicine Journal 27(11):843-48.
3. Sempere-Selva T, Peiro S, Sendra-Pina P, Martinez-Espin C, Lopez-Aguilera I. Inappropriate use of an accident and emergency department: Magnitude, associated factors, and reason - An approach with explicit criteria. Annals of Emergency Medicine 2001, 37(6):568-79. 10.1067/mem.2001.113464, 11385325.
4. Gavaler J, Van Thiel D. The non-emergency in the emergency room. Journal of the National Medical Association 1980, 72(1):33-36. 2537390, 7373663.
5. Lang T, Davido A, Diakite B, Agay E, Viet J. Using the hospital emergency department as a regular source of care. European Journal of Epidemiology 1997, 13:223-28. 10.1023/A:1007372800998, 9085009.
6. Brown E, Goel V. Factors related to emergency department use: results from the Ontario health survey 1990. Annals of Emergency Medicine 1994, 24(6):1083-91. 10.1016/S0196-0644(94)70237-3, 7978589.
7. Ovens H, Chan B. Heavy users of emergency services: a population-based review. CMAJ 2001, 165(8):1049-50. 81539, 11699700.
8. Jacoby L, Jones S. Factors associated with ED use by "repeater" and "non-repeater" patients. Journal of Emergency Nursing 1982, 8(5):243-47.
9. Olsson M, Hansagi H. Repeated use of the emergency department: qualitative study of the patient's perspective. Emergency Medicine Journal 2001, 18:430-34. 10.1136/emj.18.6.430, 1725740, 11696488.
10. Pope D, Fernandes C, Bouthillette F, Etherington J. Frequent users of the emergency department: a program to improve case and reduce visits. CMAJ 2000, 162(7):1017-20. 1232308, 10763402.
11. Andren K. A study of the relationship between social network, perceived ill health and utilization of emergency care. Scandinavian Journal of Social Medicine 1988, 16:87-93.
12. Ionescu-Ittu R, McCusker J, Ciampi A, Vadeboncoeur AM, Roberge D, Larouche D, et al. Continuity of primary care and emergency department utilization among elderly people. CMAJ 2007, 177(11):1362-8. 10.1503/cmaj.061615, 2072991, 18025427.
13. Carret M, Fassa A, Kawachi I. Demand for emergency department service: factors associated with inappropriate use. BMC Health Services Research 2007, 7(131):1-9. 1764870, 17199886.
14. Mullahy J. Specification and testing of some modified count data models. Journal of Econometrics 1986, 33:341-65.
15. Gurmu S, Trivedi PK. Excess Zeros in Count Models for Recreational Trips. Journal of Business and Economic Statistics 1996, 14(4):469-77.
16. Chin HC, Quddus MA. Modeling Count Data with Excess Zeroes. Sociological Methods & Research 2003, 32(1):90-116.
17. Cheung YB. Zero-inflated models for regression analysis of count data: a study of growth and development. Statistics in Medicine 2002, 21(10):1461-69. 10.1002/sim.1088, 12185896.
18. Gonzales-Barron U, Kerr M, Sheridan JJ, Butler F. Count data distributions and their zero-modified equivalents as a framework for modelling microbial data with a relatively high occurrence of zero counts. International Journal of Food Microbiology 136(3):268-77.
19. Rose C, Martin S, Wannemuehler K, Pilikaytis B. On the use of zero-inflated and hurdle models for modeling vaccine adverse event count data. Journal of Biopharmaceutical Statistics 2006, 16:463-81. 10.1080/10543400600719384, 16892908.
20. Beland Y. Canadian community health survey-methodological overview. Health Reports 2002, 13:9-14.
21. Long S. Regression models for categorical and limited dependent variables. Advanced Quantitative Techniques in the Social Sciences Series 1997, Thousand Oaks, CA: Sage Publication.
22. Lambert D. Zero-inflated Poisson regression, with an application to defects in manufacturing. Technometrics 1992, 34(1):1-14.
23. Greene WH. Accounting for excess zeroes and sample selection in the Poisson and negative binomial regression models: New York University, Leonard N. Stern School of Business, Department of Economics. 1994,
24. Vuong Q. Likelihood ratio tests for model selection and non-nest hypotheses. Econometrica 1989, 57(2):307-33.