medCMOS {medAdherence}R Documentation

Continuous Multiple interval measure of Over-Supply

Description

medCMOS function calculates the Continuous Multiple interval measure of Over-Supply

Usage

medCMOS(df=data, followUpDays=365)

Arguments

df a dataframe created by preData funtion
followUpDays days of follow up. 365 is the default, 12 month follow up

Details

Continuous Multiple interval measure of Over-Supply (CMOS) was calculated concurrently with CMG. The description of both calculations are as follows:

From the first prescription refill to the next prescription refill, a patient can accumulate a surplus or a deficit by either coming to pick up their medicaiton too early (which would show up as a surplus) or too late (which is considered to be a deficit). Future deficits and surpluses are accumulated based on existing deficits and surpluses.

If a person continuously has deficits or surpluses for each prescription refill period, the deficits or surpluses are always accumulated into accumulated deficits or surplus categories, respectively. An old surplus can cancel out a new deficit. If the accumulated surplus is more than the new deficit, the remaining surplus remains an accumulated surplus. If there is an accumulated surplus that precedes a new deficit , but less than the new deficit, the remaining deficit goes to the accumulated gap category.

At the end of the observation period, the accumulated gap is divided by the total days between the first and last prescription to get the CMG value for each patient. Similarly, the accumulated surplus is divided by the total days between the first and last presciption to get the measure of surplus for each patient.

Author(s)

Xiangyang Ye, Pharmacotherapy Outcomes Research Center, University of Utah

References

Morningstar, BA, Sketris IS, et al. Variation in Pharmacy Prescription Refill Adherence Measures by Type of Oral Antihyperglycaemic Drug Therapy in Seniors in Nova Scotia, Canada Journal of Clinical Pharmacy and Therapeutics 2002;27:213-220

Hess, LM, Raebel, MA, et al. Measurement of Adherence in Pharmacy Administrative Databases: A Proposal for Statndard Definitions and Preferred Measures The Annals of Pharmacotherapy 2006;40:1280-1288

Examples

data(cmos)
predt <- preRxData(df=cmos,id=ptid,rxDate=rxDay,daySupply=supplies)
postdt <- postRxData(predt)
medCMOS(postdt)

[Package medAdherence version 1.01 Index]