Matches in SemOpenAlex for { <https://semopenalex.org/work/W2287108254> ?p ?o ?g. }
- W2287108254 endingPage "1215" @default.
- W2287108254 startingPage "1208" @default.
- W2287108254 abstract "Research has demonstrated that variation in availability and utilization of health care resources exist on a range of scales, from regions of the United States, hospital referral regions, ZIP codes, and census tracts. Limited research using spatial analyses has found that variation in medication adherence exists across census tracts. Using spatial analysis, researchers may be able to effectively analyze geographically dispersed data to determine whether factors such as sociodemographics, local shared beliefs and attitudes, barriers to access such as availability of prescribers or pharmacies, or others are associated with variations in medication adherence in a defined geographic area. To (a) demonstrate that medication adherence may be mapped across an entire state using medication possession ratios and (b) determine whether a geographic pattern of adherence to statins could be identified at the ZIP code level for members of a statewide insurer.This study utilized pharmacy claims data from a statewide insurer. Insured statin users were aged greater than 30 years, had at least 1 statin prescription, and were continuously enrolled for the observation year. Patient medication possession ratios (MPR) were derived, which were then aggregated as a mean MPR for each ZIP code. ZIP codes were categorized as higher (MPR greater than 0.80) or lower (MPR less than 0.80) adherence and mapped using Arc GIS, a platform for designing and managing solutions through the application of geographic knowledge. Analysis included a determination of whether the MPRs of higher and lower adherence ZIP codes were significantly different. Hot spot analysis was conducted to identify clustering of higher, midrange, and lower adherent ZIP codes using the GetisORD Gi* Statistic. This test provides z-scores and P values to indicate where features with either high or low values cluster spatially. MPRs for these 3 categories were compared using one-way analysis of variance (ANOVA). Of 1,154 Michigan ZIP codes, 907 were represented by 212,783 insured statin users. The mean statin MPR by ZIP code was 0.79 ± 0.4. The mean MPR for higher adherent ZIP codes was 0.83 ± 0.03 and 0.76 ± 0.03 for lower adherent ZIP codes (P less than 0.001). Significant clustering of ZIP codes by adherence levels was evident from the hot spot analysis. The mean MPR was 0.84 ± 0.04 for high adherence areas, 0.79 ± 0.03 for midrange areas, and 0.74 ± 0.04 for lower adherent areas (overall P less than 0.001). Significant variations in adherence exist across ZIP codes at a state level. Future research is needed to determine locally relevant factors associated with this finding, which may be used to derive locally meaningful interventions." @default.
- W2287108254 created "2016-06-24" @default.
- W2287108254 creator A5025992740 @default.
- W2287108254 creator A5055502154 @default.
- W2287108254 date "2014-12-01" @default.
- W2287108254 modified "2023-10-01" @default.
- W2287108254 title "Geospatial Analysis of Statin Adherence Using Pharmacy Claims Data in the State of Michigan" @default.
- W2287108254 cites W1482971865 @default.
- W2287108254 cites W1533985811 @default.
- W2287108254 cites W1753613962 @default.
- W2287108254 cites W1968142559 @default.
- W2287108254 cites W1970706607 @default.
- W2287108254 cites W1973562947 @default.
- W2287108254 cites W1982497210 @default.
- W2287108254 cites W1984505003 @default.
- W2287108254 cites W1984841114 @default.
- W2287108254 cites W2002100903 @default.
- W2287108254 cites W2010273779 @default.
- W2287108254 cites W2012985419 @default.
- W2287108254 cites W2021042232 @default.
- W2287108254 cites W2034232242 @default.
- W2287108254 cites W2035637857 @default.
- W2287108254 cites W2044417549 @default.
- W2287108254 cites W2044849113 @default.
- W2287108254 cites W2046479315 @default.
- W2287108254 cites W2048834465 @default.
- W2287108254 cites W2064850677 @default.
- W2287108254 cites W2078685392 @default.
- W2287108254 cites W2085892135 @default.
- W2287108254 cites W2087627141 @default.
- W2287108254 cites W2101621119 @default.
- W2287108254 cites W2103653520 @default.
- W2287108254 cites W2107399972 @default.
- W2287108254 cites W2110066529 @default.
- W2287108254 cites W2110171695 @default.
- W2287108254 cites W2118310760 @default.
- W2287108254 cites W2118617630 @default.
- W2287108254 cites W2118745042 @default.
- W2287108254 cites W2124041619 @default.
- W2287108254 cites W2126872456 @default.
- W2287108254 cites W2142665554 @default.
- W2287108254 cites W2151644601 @default.
- W2287108254 cites W2153205212 @default.
- W2287108254 cites W2154245896 @default.
- W2287108254 cites W2157325805 @default.
- W2287108254 cites W2158612521 @default.
- W2287108254 cites W2158996987 @default.
- W2287108254 cites W2159933694 @default.
- W2287108254 cites W2160219101 @default.
- W2287108254 cites W2161982558 @default.
- W2287108254 cites W2166834128 @default.
- W2287108254 cites W2318884468 @default.
- W2287108254 doi "https://doi.org/10.18553/jmcp.2014.20.12.1208" @default.
- W2287108254 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/25443514" @default.
- W2287108254 hasPublicationYear "2014" @default.
- W2287108254 type Work @default.
- W2287108254 sameAs 2287108254 @default.
- W2287108254 citedByCount "7" @default.
- W2287108254 countsByYear W22871082542016 @default.
- W2287108254 countsByYear W22871082542017 @default.
- W2287108254 countsByYear W22871082542018 @default.
- W2287108254 countsByYear W22871082542019 @default.
- W2287108254 countsByYear W22871082542020 @default.
- W2287108254 crossrefType "journal-article" @default.
- W2287108254 hasAuthorship W2287108254A5025992740 @default.
- W2287108254 hasAuthorship W2287108254A5055502154 @default.
- W2287108254 hasConcept C104863432 @default.
- W2287108254 hasConcept C126322002 @default.
- W2287108254 hasConcept C159110408 @default.
- W2287108254 hasConcept C205649164 @default.
- W2287108254 hasConcept C2426938 @default.
- W2287108254 hasConcept C2776839432 @default.
- W2287108254 hasConcept C2908647359 @default.
- W2287108254 hasConcept C3018590553 @default.
- W2287108254 hasConcept C45827449 @default.
- W2287108254 hasConcept C512399662 @default.
- W2287108254 hasConcept C52130261 @default.
- W2287108254 hasConcept C545542383 @default.
- W2287108254 hasConcept C58640448 @default.
- W2287108254 hasConcept C71924100 @default.
- W2287108254 hasConcept C9770341 @default.
- W2287108254 hasConcept C99454951 @default.
- W2287108254 hasConceptScore W2287108254C104863432 @default.
- W2287108254 hasConceptScore W2287108254C126322002 @default.
- W2287108254 hasConceptScore W2287108254C159110408 @default.
- W2287108254 hasConceptScore W2287108254C205649164 @default.
- W2287108254 hasConceptScore W2287108254C2426938 @default.
- W2287108254 hasConceptScore W2287108254C2776839432 @default.
- W2287108254 hasConceptScore W2287108254C2908647359 @default.
- W2287108254 hasConceptScore W2287108254C3018590553 @default.
- W2287108254 hasConceptScore W2287108254C45827449 @default.
- W2287108254 hasConceptScore W2287108254C512399662 @default.
- W2287108254 hasConceptScore W2287108254C52130261 @default.
- W2287108254 hasConceptScore W2287108254C545542383 @default.
- W2287108254 hasConceptScore W2287108254C58640448 @default.
- W2287108254 hasConceptScore W2287108254C71924100 @default.
- W2287108254 hasConceptScore W2287108254C9770341 @default.
- W2287108254 hasConceptScore W2287108254C99454951 @default.