Asset Details
Do you wish to reserve the book?
Validation of an algorithm to prioritize patients for comprehensive medication management in primary care settings
Hey, we have placed the reservation for you!
By the way, why not check out events that you can attend while you pick your title.
Oops! Something went wrong.
Looks like we were not able to place the reservation. Kindly try again later.
Are you sure you want to remove the book from the shelf?
Validation of an algorithm to prioritize patients for comprehensive medication management in primary care settings
Do you wish to request the book?
Validation of an algorithm to prioritize patients for comprehensive medication management in primary care settings
Please be aware that the book you have requested cannot be checked out. If you would like to checkout this book, you can reserve another copy
We have requested the book for you!
Your request is successful and it will be processed during the Library working hours. Please check the status of your request in My Requests.
Oops! Something went wrong.
Looks like we were not able to place your request. Kindly try again later.
Journal Article
Validation of an algorithm to prioritize patients for comprehensive medication management in primary care settings
2024
Overview
BackgroundComprehensive medication management (CMM) programs optimize the effectiveness and safety of patients’ medication regimens, but CMM may be underutilized. Whether healthcare claims data can identify patients appropriate for CMM is not well-studied.AimDetermine the face validity of a claims-based algorithm to prioritize patients who likely need CMM.MethodWe used claims data to construct patient-level markers of “regimen complexity” and “high-risk for adverse effects,” which were combined to define four categories of claims-based CMM-need (very likely, likely, unlikely, very unlikely) among 180 patient records. Three clinicians independently reviewed each record to assess CMM need. We assessed concordance between the claims-based and clinician-review CMM need by calculating percent agreement as well as kappa statistic.ResultsMost records identified as ‘very likely’ (90%) by claims-based markers were identified by clinician-reviewers as needing CMM. Few records within the ‘very unlikely’ group (5%) were identified by clinician-reviewers as needing CMM. Interrater agreement between CMM-based algorithm and clinician review was moderate in strength (kappa = 0.6, p < 0.001).ConclusionClaims-based pharmacy measures may offer a valid approach to prioritize patients into CMM-need groups. Further testing of this algorithm is needed prior to implementation in clinic settings.
Publisher
Springer Nature B.V
Subject
