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Modeling factors influencing the demand for emergency department services in Ontario: a comparison of methods.
BMC Emerg Med. 2011 Aug 19; 11:13.BE

Abstract

BACKGROUND

Emergency departments are medical treatment facilities, designed to provide episodic care to patients suffering from acute injuries and illnesses as well as patients who are experiencing sporadic flare-ups of underlying chronic medical conditions which require immediate attention. Supply and demand for emergency department services varies across geographic regions and time. Some persons do not rely on the service at all whereas; others use the service on repeated occasions. Issues regarding increased wait times for services and crowding illustrate the need to investigate which factors are associated with increased frequency of emergency department utilization. The evidence from this study can help inform policy makers on the appropriate mix of supply and demand targeted health care policies necessary to ensure that patients receive appropriate health care delivery in an efficient and cost-effective manner. The purpose of this report is to assess those factors resulting in increased demand for emergency department services in Ontario. We assess how utilization rates vary according to the severity of patient presentation in the emergency department. We are specifically interested in the impact that access to primary care physicians has on the demand for emergency department services. Additionally, we wish to investigate these trends using a series of novel regression models for count outcomes which have yet to be employed in the domain of emergency medical research.

METHODS

Data regarding the frequency of emergency department visits for the respondents of Canadian Community Health Survey (CCHS) during our study interval (2003-2005) are obtained from the National Ambulatory Care Reporting System (NACRS). Patients' emergency department utilizations were linked with information from the Canadian Community Health Survey (CCHS) which provides individual level medical, socio-demographic, psychological and behavioral information for investigating predictors of increased emergency department utilization. Six different multiple regression models for count data were fitted to assess the influence of predictors on demand for emergency department services, including: Poisson, Negative Binomial, Zero-Inflated Poisson, Zero-Inflated Negative Binomial, Hurdle Poisson, and Hurdle Negative Binomial. Comparison of competing models was assessed by the Vuong test statistic.

RESULTS

The CCHS cycle 2.1 respondents were a roughly equal mix of males (50.4%) and females (49.6%). The majority (86.2%) were young-middle aged adults between the ages of 20-64, living in predominantly urban environments (85.9%), with mid-high household incomes (92.2%) and well-educated, receiving at least a high-school diploma (84.1%). Many participants reported no chronic disease (51.9%), fell into a small number (0-5) of ambulatory diagnostic groups (62.3%), and perceived their health status as good/excellent (88.1%); however, were projected to have high Resource Utilization Band levels of health resource utilization (68.2%). These factors were largely stable for CCHS cycle 3.1 respondents. Factors influencing demand for emergency department services varied according to the severity of triage scores at initial presentation. For example, although a non-significant predictor of the odds of emergency department utilization in high severity cases, access to a primary care physician was a statistically significant predictor of the likelihood of emergency department utilization (OR: 0.69; 95% CI OR: 0.63-0.75) and the rate of emergency department utilization (RR: 0.57; 95% CI RR: 0.50-0.66) in low severity cases.

CONCLUSION

Using a theoretically appropriate hurdle negative binomial regression model this unique study illustrates that access to a primary care physician is an important predictor of both the odds and rate of emergency department utilization in Ontario. Restructuring primary care services, with aims of increasing access to undersupplied populations may result in decreased emergency department utilization rates by approximately 43% for low severity triage level cases.

Authors+Show Affiliations

Department of Family and Community Medicine, University of Toronto, Ontario, Canada. rahim.moineddin@utoronto.caNo affiliation info availableNo affiliation info availableNo affiliation info availableNo affiliation info available

Pub Type(s)

Journal Article
Research Support, Non-U.S. Gov't

Language

eng

PubMed ID

21854606

Citation

Moineddin, Rahim, et al. "Modeling Factors Influencing the Demand for Emergency Department Services in Ontario: a Comparison of Methods." BMC Emergency Medicine, vol. 11, 2011, p. 13.
Moineddin R, Meaney C, Agha M, et al. Modeling factors influencing the demand for emergency department services in Ontario: a comparison of methods. BMC Emerg Med. 2011;11:13.
Moineddin, R., Meaney, C., Agha, M., Zagorski, B., & Glazier, R. H. (2011). Modeling factors influencing the demand for emergency department services in Ontario: a comparison of methods. BMC Emergency Medicine, 11, 13. https://doi.org/10.1186/1471-227X-11-13
Moineddin R, et al. Modeling Factors Influencing the Demand for Emergency Department Services in Ontario: a Comparison of Methods. BMC Emerg Med. 2011 Aug 19;11:13. PubMed PMID: 21854606.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Modeling factors influencing the demand for emergency department services in Ontario: a comparison of methods. AU - Moineddin,Rahim, AU - Meaney,Christopher, AU - Agha,Mohammad, AU - Zagorski,Brandon, AU - Glazier,Richard Henry, Y1 - 2011/08/19/ PY - 2011/02/14/received PY - 2011/08/19/accepted PY - 2011/8/23/entrez PY - 2011/8/23/pubmed PY - 2011/12/14/medline SP - 13 EP - 13 JF - BMC emergency medicine JO - BMC Emerg Med VL - 11 N2 - BACKGROUND: Emergency departments are medical treatment facilities, designed to provide episodic care to patients suffering from acute injuries and illnesses as well as patients who are experiencing sporadic flare-ups of underlying chronic medical conditions which require immediate attention. Supply and demand for emergency department services varies across geographic regions and time. Some persons do not rely on the service at all whereas; others use the service on repeated occasions. Issues regarding increased wait times for services and crowding illustrate the need to investigate which factors are associated with increased frequency of emergency department utilization. The evidence from this study can help inform policy makers on the appropriate mix of supply and demand targeted health care policies necessary to ensure that patients receive appropriate health care delivery in an efficient and cost-effective manner. The purpose of this report is to assess those factors resulting in increased demand for emergency department services in Ontario. We assess how utilization rates vary according to the severity of patient presentation in the emergency department. We are specifically interested in the impact that access to primary care physicians has on the demand for emergency department services. Additionally, we wish to investigate these trends using a series of novel regression models for count outcomes which have yet to be employed in the domain of emergency medical research. METHODS: Data regarding the frequency of emergency department visits for the respondents of Canadian Community Health Survey (CCHS) during our study interval (2003-2005) are obtained from the National Ambulatory Care Reporting System (NACRS). Patients' emergency department utilizations were linked with information from the Canadian Community Health Survey (CCHS) which provides individual level medical, socio-demographic, psychological and behavioral information for investigating predictors of increased emergency department utilization. Six different multiple regression models for count data were fitted to assess the influence of predictors on demand for emergency department services, including: Poisson, Negative Binomial, Zero-Inflated Poisson, Zero-Inflated Negative Binomial, Hurdle Poisson, and Hurdle Negative Binomial. Comparison of competing models was assessed by the Vuong test statistic. RESULTS: The CCHS cycle 2.1 respondents were a roughly equal mix of males (50.4%) and females (49.6%). The majority (86.2%) were young-middle aged adults between the ages of 20-64, living in predominantly urban environments (85.9%), with mid-high household incomes (92.2%) and well-educated, receiving at least a high-school diploma (84.1%). Many participants reported no chronic disease (51.9%), fell into a small number (0-5) of ambulatory diagnostic groups (62.3%), and perceived their health status as good/excellent (88.1%); however, were projected to have high Resource Utilization Band levels of health resource utilization (68.2%). These factors were largely stable for CCHS cycle 3.1 respondents. Factors influencing demand for emergency department services varied according to the severity of triage scores at initial presentation. For example, although a non-significant predictor of the odds of emergency department utilization in high severity cases, access to a primary care physician was a statistically significant predictor of the likelihood of emergency department utilization (OR: 0.69; 95% CI OR: 0.63-0.75) and the rate of emergency department utilization (RR: 0.57; 95% CI RR: 0.50-0.66) in low severity cases. CONCLUSION: Using a theoretically appropriate hurdle negative binomial regression model this unique study illustrates that access to a primary care physician is an important predictor of both the odds and rate of emergency department utilization in Ontario. Restructuring primary care services, with aims of increasing access to undersupplied populations may result in decreased emergency department utilization rates by approximately 43% for low severity triage level cases. SN - 1471-227X UR - https://www.unboundmedicine.com/medline/citation/21854606/Modeling_factors_influencing_the_demand_for_emergency_department_services_in_Ontario:_a_comparison_of_methods_ L2 - https://bmcemergmed.biomedcentral.com/articles/10.1186/1471-227X-11-13 DB - PRIME DP - Unbound Medicine ER -