these studies, 26 used proportion of days covered, 23 used medication possession ratio, and 72 used self-reported questionnaires (e.g., the Morisky Scale) to assess MMA. About 50% of the studies included more than one method for measuring MMA, and different variations of medication possession ratio and proportion of days covered were used for measuring MMA. Conclusions: There appears to be no standardized method to measure MMA. With an increasing prevalence of polypharmacy, more efforts should be directed toward constructing robust measures suitable to evaluate adherence to complex regimens. Future research to understand the validity and reliability of MMA measures and their effects on objective clinical outcomes is also needed.

This emerging technology of cyclodextrin-based nanosponges is expected to provide technical solutions to the formulation arena and to come up with some successful products in the pharmaceutical market. It also has an exciting future in the field of therapeutics wherein it can cater site-directed drug delivery and hence it possesses vibrant opportunities.

ObjectivesLimited studies have investigated geographic accessibility to a nearby community pharmacy for elderly which is an essential determinant of the access to medications and pharmacy services. This research identified pharmacy deserts and investigated availability of different types of community pharmacies and their services for elderly enrolled in a State Pharmaceutical Assistance Program (SPAP).MethodsThe state of Pennsylvania in the US was used as a case to demonstrate the geographic accessibility to community pharmacy and services for elderly enrolled in SPAP. The locations of community pharmacies and households of elderly enrolled in SPAP were derived from Pharmaceutical Assistance Contract for the Elderly programs’ database. The street addresses were geocoded and the distance to a nearby community pharmacy was calculated for study sample using the haversine formula. The demographic and geographic data were aggregated to Census Tracts and pharmacy deserts were identified using the predefined criteria. Descriptive statistical analysis was used to determine whether there are statistical differences in the socio-demographic profiles and distribution of different types of community pharmacies and their services in pharmacy deserts and non-deserts. This research used hot spot analyses at county level to identify clusters of pharmacy deserts, areas with high concentration of different racial/ethnic groups and clusters of high densities of chain and independent pharmacies.ResultsThe Spatial analysis revealed that 39% and 61% Census Tracts in Pennsylvania were pharmacy deserts and non-deserts respectively (p < 0.001). Pharmacy deserts were found to have significantly more females, married and white elderly and fewer blacks and Hispanics compared to pharmacy non-deserts. Pharmacy deserts had significantly fewer chain and independent pharmacies and less delivery and 24-hour services in pharmacies than pharmacy non-deserts. Hot spot analyses showed that clusters of pharmacy deserts were more concentrated in southcentral, northwest and northeast regions of the state which represent rural areas and overlapped with clusters of high concentration of white individuals.ConclusionsThe findings suggest that urban-rural inequality, racial/ethnic disparity and differences in availability of pharmacies and their services exist between pharmacy deserts and non-deserts. The methodological approach and analyses used in this study can also be applied to other public health programs to evaluate the coverage and breadth of public health services.