Premium
Assessment of clinical productivity tracking via reporting of quality patient indicators
Author(s) -
Stover Kayla R.,
Ballou Jordan M.,
Liles Anne M.,
Fleming Laurie W.,
Fleming Joshua W.,
Riche Daniel M.,
Pitcock James J.,
King S. Travis,
Capino Amanda C.
Publication year - 2019
Publication title -
journal of the american college of clinical pharmacy
Language(s) - English
Resource type - Journals
ISSN - 2574-9870
DOI - 10.1002/jac5.1032
Subject(s) - productivity , quality (philosophy) , variety (cybernetics) , pharmacy , tracking (education) , data collection , medicine , family medicine , psychology , computer science , statistics , pedagogy , philosophy , epistemology , economics , mathematics , artificial intelligence , macroeconomics
As the role of pharmacists in providing direct patient care continues to expand, the need for and interest in a method for assessing and measuring clinical productivity is becoming more paramount. Unfortunately, there is no consensus on how, when, and which quality indicators or clinical productivity measures should be collected. The primary objective of this study was to assess the landscape of clinical productivity tracking across practice sites. Methods A 13‐item Qualtrics questionnaire was administered through email lists from several national pharmacy organizations in the Spring of 2018. There were eight items related to quality indicators or clinical productivity measures. The information gathered included the type of indicator/measure collected, how it was collected, and perceived benefits and barriers. The remaining five items were basic demographic questions. Results A total of 349 participants responded, with 231 reporting that they currently track some type of patient quality indicator. Of these, 166 reported collecting a total of 903 indicators or measures using a variety of tracking systems. The most frequently reported measures collected were the number of patients seen and the type of recommendation or intervention made. The most cited reason for collecting these data was to demonstrate the impact to a practice site. The time required to collect data and the limitations of data collection systems were the two most frequently cited perceived barriers to collecting information. Conclusions A majority of respondents are collecting some form of quality indicator or clinical productivity measure. However, there is extensive variety in the exact indicators or measures being collected and the tracking systems being utilized for their collection. Although implementation would be difficult, a more standardized approach to tracking clinical productivity may be beneficial.