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Use of surveillance data in developing geographic dissemination strategies: A study of the diffusion of olanzapine to Michigan children insured by medicaid

Abstract Objective: The purpose of this study was to examinethe diffusion of olanzapine to urban and rural children insured by Medicaid in Michigan by identifying prescribing clusters through surveillance of claims records. Methods: Prescription claims records for all antipsychotic medications for 3...

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Published in:Clinical therapeutics 2007-02, Vol.29 (2), p.359-370
Main Authors: Penfold, Robert B., PhD, Kelleher, Kelly J., MD, MPH
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description Abstract Objective: The purpose of this study was to examinethe diffusion of olanzapine to urban and rural children insured by Medicaid in Michigan by identifying prescribing clusters through surveillance of claims records. Methods: Prescription claims records for all antipsychotic medications for 3,567 children insured by Medicaid in Michigan from 1996 through 1998 were examined through the state Medicaid database. There were 29,069 pediatric prescriptions for antipsychotic medications; 2949 were for olanzapine (576 children, 510 providers). These data were linked to the Area Resource File, Provider Enrollment File, and Rural-Urban Commuting Area codes. Patient and provider locations were geocoded by ZIP code. Mixed logistic regression analysis was performed to determine the probability of a child's being prescribed olanzapine given certain community, patient, and provider characteristics. Spatial clusters were identified through the local Moron's L statistic and empirical Bayes standardized incidence rates. Results: Rural children were more likely than urbanchildren to be prescribed olanzapine (odds ratio [OR], 1.29; P < 0.001). There were significant differences by age and sex, with older children and girls more likely than younger children and boys to be prescribed olanzapine (OR, 1.30 and 1.37, respectively; both, P < 0.001). At the county level, the number of pediatricians per primary care physician reduced the likelihood of a child's being prescribed olanzapine (OR, 0.88; P = 0.039). The effect of the number of available mental health professionals was not significant. The global Moran's L statistic was U indicating modcrate clustering of the use of olanzapine. Conclusion: Graphic surveillance data may be usefulfor studying the delivery and use of health cue services. Further research is needed to determine how this method can be used strategically to facilitate or impede the diffusion of new medications.
doi_str_mv 10.1016/j.clinthera.2007.02.017
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Methods: Prescription claims records for all antipsychotic medications for 3,567 children insured by Medicaid in Michigan from 1996 through 1998 were examined through the state Medicaid database. There were 29,069 pediatric prescriptions for antipsychotic medications; 2949 were for olanzapine (576 children, 510 providers). These data were linked to the Area Resource File, Provider Enrollment File, and Rural-Urban Commuting Area codes. Patient and provider locations were geocoded by ZIP code. Mixed logistic regression analysis was performed to determine the probability of a child's being prescribed olanzapine given certain community, patient, and provider characteristics. Spatial clusters were identified through the local Moron's L statistic and empirical Bayes standardized incidence rates. Results: Rural children were more likely than urbanchildren to be prescribed olanzapine (odds ratio [OR], 1.29; P &lt; 0.001). There were significant differences by age and sex, with older children and girls more likely than younger children and boys to be prescribed olanzapine (OR, 1.30 and 1.37, respectively; both, P &lt; 0.001). At the county level, the number of pediatricians per primary care physician reduced the likelihood of a child's being prescribed olanzapine (OR, 0.88; P = 0.039). The effect of the number of available mental health professionals was not significant. The global Moran's L statistic was U indicating modcrate clustering of the use of olanzapine. Conclusion: Graphic surveillance data may be usefulfor studying the delivery and use of health cue services. Further research is needed to determine how this method can be used strategically to facilitate or impede the diffusion of new medications.</description><identifier>ISSN: 0149-2918</identifier><identifier>EISSN: 1879-114X</identifier><identifier>DOI: 10.1016/j.clinthera.2007.02.017</identifier><identifier>PMID: 17472829</identifier><language>eng</language><publisher>Belle Mead, NJ: EM Inc USA</publisher><subject>Adolescent ; Age Factors ; Antipsychotic Agents - supply &amp; distribution ; Antipsychotic Agents - therapeutic use ; Benzodiazepines - supply &amp; distribution ; Benzodiazepines - therapeutic use ; Biological and medical sciences ; Child ; Child, Preschool ; diffusion ; Ethnic Groups ; Family physicians ; Female ; geographic dissemination ; Geographic Information Systems ; geographic surveillance ; Health care ; Health Services Accessibility ; Health surveillance ; heterogeneity ; Humans ; Infant ; Information Dissemination ; Innovations ; Insurance Claim Review ; Internal Medicine ; Logistic Models ; Male ; Medicaid ; Medicaid - statistics &amp; numerical data ; Medical Education ; Medical sciences ; Medical screening ; Medicare ; Mental disorders ; Mental health ; Michigan ; olanzapine ; Pediatrics ; Pharmacology. 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Methods: Prescription claims records for all antipsychotic medications for 3,567 children insured by Medicaid in Michigan from 1996 through 1998 were examined through the state Medicaid database. There were 29,069 pediatric prescriptions for antipsychotic medications; 2949 were for olanzapine (576 children, 510 providers). These data were linked to the Area Resource File, Provider Enrollment File, and Rural-Urban Commuting Area codes. Patient and provider locations were geocoded by ZIP code. Mixed logistic regression analysis was performed to determine the probability of a child's being prescribed olanzapine given certain community, patient, and provider characteristics. Spatial clusters were identified through the local Moron's L statistic and empirical Bayes standardized incidence rates. Results: Rural children were more likely than urbanchildren to be prescribed olanzapine (odds ratio [OR], 1.29; P &lt; 0.001). There were significant differences by age and sex, with older children and girls more likely than younger children and boys to be prescribed olanzapine (OR, 1.30 and 1.37, respectively; both, P &lt; 0.001). At the county level, the number of pediatricians per primary care physician reduced the likelihood of a child's being prescribed olanzapine (OR, 0.88; P = 0.039). The effect of the number of available mental health professionals was not significant. The global Moran's L statistic was U indicating modcrate clustering of the use of olanzapine. Conclusion: Graphic surveillance data may be usefulfor studying the delivery and use of health cue services. Further research is needed to determine how this method can be used strategically to facilitate or impede the diffusion of new medications.</description><subject>Adolescent</subject><subject>Age Factors</subject><subject>Antipsychotic Agents - supply &amp; distribution</subject><subject>Antipsychotic Agents - therapeutic use</subject><subject>Benzodiazepines - supply &amp; distribution</subject><subject>Benzodiazepines - therapeutic use</subject><subject>Biological and medical sciences</subject><subject>Child</subject><subject>Child, Preschool</subject><subject>diffusion</subject><subject>Ethnic Groups</subject><subject>Family physicians</subject><subject>Female</subject><subject>geographic dissemination</subject><subject>Geographic Information Systems</subject><subject>geographic surveillance</subject><subject>Health care</subject><subject>Health Services Accessibility</subject><subject>Health surveillance</subject><subject>heterogeneity</subject><subject>Humans</subject><subject>Infant</subject><subject>Information Dissemination</subject><subject>Innovations</subject><subject>Insurance Claim Review</subject><subject>Internal Medicine</subject><subject>Logistic Models</subject><subject>Male</subject><subject>Medicaid</subject><subject>Medicaid - statistics &amp; numerical data</subject><subject>Medical Education</subject><subject>Medical sciences</subject><subject>Medical screening</subject><subject>Medicare</subject><subject>Mental disorders</subject><subject>Mental health</subject><subject>Michigan</subject><subject>olanzapine</subject><subject>Pediatrics</subject><subject>Pharmacology. 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Drug treatments</topic><topic>Physicians</topic><topic>Population Surveillance</topic><topic>Practice Patterns, Physicians' - statistics &amp; numerical data</topic><topic>prescribing practices</topic><topic>Probability</topic><topic>Professions</topic><topic>Psychiatry</topic><topic>Rural Health Services</topic><topic>Rural Population</topic><topic>Sex Factors</topic><topic>Telemedicine</topic><topic>Urban Health Services</topic><topic>Urban Population</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Penfold, Robert B., PhD</creatorcontrib><creatorcontrib>Kelleher, Kelly J., MD, MPH</creatorcontrib><collection>Pascal-Francis</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Nursing &amp; Allied Health Database</collection><collection>Health &amp; Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Healthcare Administration Database (Alumni)</collection><collection>Medical Database (Alumni Edition)</collection><collection>ProQuest Pharma Collection</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>Research Library (Alumni Edition)</collection><collection>ProQuest Central (Alumni)</collection><collection>ProQuest Central</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>Research Library Prep</collection><collection>ProQuest Health &amp; Medical Complete (Alumni)</collection><collection>Nursing &amp; Allied Health Database (Alumni Edition)</collection><collection>Health &amp; Medical Collection (Alumni Edition)</collection><collection>Healthcare Administration Database</collection><collection>PML(ProQuest Medical Library)</collection><collection>Research Library</collection><collection>Algology Mycology and Protozoology Abstracts (Microbiology C)</collection><collection>Research Library (Corporate)</collection><collection>Nursing &amp; Allied Health Premium</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>ProQuest Central Basic</collection><collection>MEDLINE - Academic</collection><jtitle>Clinical therapeutics</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Penfold, Robert B., PhD</au><au>Kelleher, Kelly J., MD, MPH</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Use of surveillance data in developing geographic dissemination strategies: A study of the diffusion of olanzapine to Michigan children insured by medicaid</atitle><jtitle>Clinical therapeutics</jtitle><addtitle>Clin Ther</addtitle><date>2007-02-01</date><risdate>2007</risdate><volume>29</volume><issue>2</issue><spage>359</spage><epage>370</epage><pages>359-370</pages><issn>0149-2918</issn><eissn>1879-114X</eissn><abstract>Abstract Objective: The purpose of this study was to examinethe diffusion of olanzapine to urban and rural children insured by Medicaid in Michigan by identifying prescribing clusters through surveillance of claims records. Methods: Prescription claims records for all antipsychotic medications for 3,567 children insured by Medicaid in Michigan from 1996 through 1998 were examined through the state Medicaid database. There were 29,069 pediatric prescriptions for antipsychotic medications; 2949 were for olanzapine (576 children, 510 providers). These data were linked to the Area Resource File, Provider Enrollment File, and Rural-Urban Commuting Area codes. Patient and provider locations were geocoded by ZIP code. Mixed logistic regression analysis was performed to determine the probability of a child's being prescribed olanzapine given certain community, patient, and provider characteristics. Spatial clusters were identified through the local Moron's L statistic and empirical Bayes standardized incidence rates. Results: Rural children were more likely than urbanchildren to be prescribed olanzapine (odds ratio [OR], 1.29; P &lt; 0.001). There were significant differences by age and sex, with older children and girls more likely than younger children and boys to be prescribed olanzapine (OR, 1.30 and 1.37, respectively; both, P &lt; 0.001). At the county level, the number of pediatricians per primary care physician reduced the likelihood of a child's being prescribed olanzapine (OR, 0.88; P = 0.039). The effect of the number of available mental health professionals was not significant. The global Moran's L statistic was U indicating modcrate clustering of the use of olanzapine. Conclusion: Graphic surveillance data may be usefulfor studying the delivery and use of health cue services. Further research is needed to determine how this method can be used strategically to facilitate or impede the diffusion of new medications.</abstract><cop>Belle Mead, NJ</cop><pub>EM Inc USA</pub><pmid>17472829</pmid><doi>10.1016/j.clinthera.2007.02.017</doi><tpages>12</tpages></addata></record>
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subjects Adolescent
Age Factors
Antipsychotic Agents - supply & distribution
Antipsychotic Agents - therapeutic use
Benzodiazepines - supply & distribution
Benzodiazepines - therapeutic use
Biological and medical sciences
Child
Child, Preschool
diffusion
Ethnic Groups
Family physicians
Female
geographic dissemination
Geographic Information Systems
geographic surveillance
Health care
Health Services Accessibility
Health surveillance
heterogeneity
Humans
Infant
Information Dissemination
Innovations
Insurance Claim Review
Internal Medicine
Logistic Models
Male
Medicaid
Medicaid - statistics & numerical data
Medical Education
Medical sciences
Medical screening
Medicare
Mental disorders
Mental health
Michigan
olanzapine
Pediatrics
Pharmacology. Drug treatments
Physicians
Population Surveillance
Practice Patterns, Physicians' - statistics & numerical data
prescribing practices
Probability
Professions
Psychiatry
Rural Health Services
Rural Population
Sex Factors
Telemedicine
Urban Health Services
Urban Population
title Use of surveillance data in developing geographic dissemination strategies: A study of the diffusion of olanzapine to Michigan children insured by medicaid
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