The purpose of this study is to examine the system performance in delivering oral health services in a public health district based on the Conceptual Framework to Measure Performance of the Public Health System (PHS). Using modeling and simulation, a predictive model based on the conceptual framework dimensions: mission, structural capacity, processes, and outcomes was developed to predict the performance of public health district in delivering oral health services.
This is a retrospective longitudinal study. The main objective of this study is to use a modeling and simulation approach to predict the performance of public health district dental clinic in delivering oral health services. Specifically, the following performance metrics were examined: average number of patients' visits per day at a public health district dental clinic; average number of diagnostic and preventive dental services delivered by the dentist or the dental hygienist per day at a public health district dental clinic; average number of corrective services provided by the dentist per day at a public health district dental clinic; and average total dental services. The scenarios, based on the existing structural capacities and the number of personnel, were modeled and simulated using Rockwell Automation Software, Arena® version 13.5.
Purposeful sampling consisted of five public health district dental clinics of Hampton Roads for the fiscal years, 2005–2010. For the purpose of this study the following five public health district dental clinics were chosen: Norfolk, Virginia Beach, Hampton, Peninsula, and Western Tidewater. Norfolk Health District operates two sites: Little Creek and Park Place. Virginia Beach District operates two sites: Birdneck and Pembroke. Western Tidewater Health District operates two sites: Isle of Wight and Southampton.
Data analysis revealed that adding a new healthcare provider (a dental hygienist) to the system has a statistically significant influence in delivering oral health services at all public health districts' dental clinics in the following performance metrics: number of patients' visits per day, diagnosis and preventive services, corrective services, and total number of dental services (p < 0.05).
","abstract_html":"<p>The purpose of this study is to examine the system performance in delivering oral health services in a public health district based on the Conceptual Framework to Measure Performance of the Public Health System (PHS). Using modeling and simulation, a predictive model based on the conceptual framework dimensions: mission, structural capacity, processes, and outcomes was developed to predict the performance of public health district in delivering oral health services.</p> <p>This is a retrospective longitudinal study. The main objective of this study is to use a modeling and simulation approach to predict the performance of public health district dental clinic in delivering oral health services. Specifically, the following performance metrics were examined: average number of patients' visits per day at a public health district dental clinic; average number of diagnostic and preventive dental services delivered by the dentist or the dental hygienist per day at a public health district dental clinic; average number of corrective services provided by the dentist per day at a public health district dental clinic; and average total dental services. The scenarios, based on the existing structural capacities and the number of personnel, were modeled and simulated using Rockwell Automation Software, Arena® version 13.5.</p> <p>Purposeful sampling consisted of five public health district dental clinics of Hampton Roads for the fiscal years, 2005–2010. For the purpose of this study the following five public health district dental clinics were chosen: Norfolk, Virginia Beach, Hampton, Peninsula, and Western Tidewater. Norfolk Health District operates two sites: Little Creek and Park Place. Virginia Beach District operates two sites: Birdneck and Pembroke. Western Tidewater Health District operates two sites: Isle of Wight and Southampton.</p> <p>Data analysis revealed that adding a new healthcare provider (a dental hygienist) to the system has a statistically significant influence in delivering oral health services at all public health districts' dental clinics in the following performance metrics: number of patients' visits per day, diagnosis and preventive services, corrective services, and total number of dental services (p < 0.05).</p>","abstract_has_math":false,"creators":["Alzahrani, Mohammad J."],"institution":null,"degree_name":"Doctor of Philosophy (PhD)","degree_level":"Dissertation","degree_discipline":"Health Services Research","degree_department":null,"school":null,"contributors":["Holly Gaff","Deanne Shuman","Rani A. Kady"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2011,"date_issued":"2011-07-01T07:00:00Z","date_published":"2011-07-01T07:00:00Z","updated_at":"2026-07-24T03:34:39Z","subjects":["Oral health delivery","Oral health services","Public health performance","Public oral health","Biomedical Engineering and Bioengineering","Dental Hygiene","Dental Public Health and Education","Dentistry","Public Health"],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[{"key":"dc:identifier","label":"Identifier","values":["9781124635521"],"render_values":[{"text":"9781124635521","href":null,"code":true}]}]},"links":{"outbound_url":"https://digitalcommons.odu.edu/healthservices_etds/22","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Holly Gaff","Deanne Shuman","Rani A. Kady"]},{"key":"dc:creator","label":"Author","values":["Alzahrani, Mohammad J."]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.available","label":"Dc Date Available","values":["2019-04-22T07:00:00Z"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Health Services Research"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Dissertation"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Doctor of Philosophy (PhD)"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Oral health delivery","Oral health services","Public health performance","Public oral health","Biomedical Engineering and Bioengineering","Dental Hygiene","Dental Public Health and Education","Dentistry","Public Health"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["9781124635521","https://digitalcommons.odu.edu/healthservices_etds/22"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["The purpose of this study is to examine the system performance in delivering oral health services in a public health district based on the Conceptual Framework to Measure Performance of the Public Health System (PHS). Using modeling and simulation, a predictive model based on the conceptual framework dimensions: mission, structural capacity, processes, and outcomes was developed to predict the performance of public health district in delivering oral health services.
This is a retrospective longitudinal study. The main objective of this study is to use a modeling and simulation approach to predict the performance of public health district dental clinic in delivering oral health services. Specifically, the following performance metrics were examined: average number of patients' visits per day at a public health district dental clinic; average number of diagnostic and preventive dental services delivered by the dentist or the dental hygienist per day at a public health district dental clinic; average number of corrective services provided by the dentist per day at a public health district dental clinic; and average total dental services. The scenarios, based on the existing structural capacities and the number of personnel, were modeled and simulated using Rockwell Automation Software, Arena® version 13.5.
Purposeful sampling consisted of five public health district dental clinics of Hampton Roads for the fiscal years, 2005–2010. For the purpose of this study the following five public health district dental clinics were chosen: Norfolk, Virginia Beach, Hampton, Peninsula, and Western Tidewater. Norfolk Health District operates two sites: Little Creek and Park Place. Virginia Beach District operates two sites: Birdneck and Pembroke. Western Tidewater Health District operates two sites: Isle of Wight and Southampton.
Data analysis revealed that adding a new healthcare provider (a dental hygienist) to the system has a statistically significant influence in delivering oral health services at all public health districts' dental clinics in the following performance metrics: number of patients' visits per day, diagnosis and preventive services, corrective services, and total number of dental services (p < 0.05).
"]},{"key":"dc:title","label":"Title","values":["Using Modeling and Simulation to Improve Oral Health Services Delivery in Hampton Roads, Virginia"]}]}],"canonical_facts":{"dc:contributor":["Holly Gaff","Deanne Shuman","Rani A. Kady"],"dc:creator":["Alzahrani, Mohammad J."],"dc:date.available":["2019-04-22T07:00:00Z"],"dc:description.abstract":["The purpose of this study is to examine the system performance in delivering oral health services in a public health district based on the Conceptual Framework to Measure Performance of the Public Health System (PHS). Using modeling and simulation, a predictive model based on the conceptual framework dimensions: mission, structural capacity, processes, and outcomes was developed to predict the performance of public health district in delivering oral health services.
This is a retrospective longitudinal study. The main objective of this study is to use a modeling and simulation approach to predict the performance of public health district dental clinic in delivering oral health services. Specifically, the following performance metrics were examined: average number of patients' visits per day at a public health district dental clinic; average number of diagnostic and preventive dental services delivered by the dentist or the dental hygienist per day at a public health district dental clinic; average number of corrective services provided by the dentist per day at a public health district dental clinic; and average total dental services. The scenarios, based on the existing structural capacities and the number of personnel, were modeled and simulated using Rockwell Automation Software, Arena® version 13.5.
Purposeful sampling consisted of five public health district dental clinics of Hampton Roads for the fiscal years, 2005–2010. For the purpose of this study the following five public health district dental clinics were chosen: Norfolk, Virginia Beach, Hampton, Peninsula, and Western Tidewater. Norfolk Health District operates two sites: Little Creek and Park Place. Virginia Beach District operates two sites: Birdneck and Pembroke. Western Tidewater Health District operates two sites: Isle of Wight and Southampton.
Data analysis revealed that adding a new healthcare provider (a dental hygienist) to the system has a statistically significant influence in delivering oral health services at all public health districts' dental clinics in the following performance metrics: number of patients' visits per day, diagnosis and preventive services, corrective services, and total number of dental services (p < 0.05).
"],"dc:identifier":["9781124635521","https://digitalcommons.odu.edu/healthservices_etds/22"],"dc:subject":["Oral health delivery","Oral health services","Public health performance","Public oral health","Biomedical Engineering and Bioengineering","Dental Hygiene","Dental Public Health and Education","Dentistry","Public Health"],"dc:title":["Using Modeling and Simulation to Improve Oral Health Services Delivery in Hampton Roads, Virginia"],"thesis:degree_discipline":["Health Services Research"],"thesis:degree_level":["Dissertation"],"thesis:degree_name":["Doctor of Philosophy (PhD)"]},"updated_at":"2026-07-24T03:34:39Z"}