The Optimizing Care Model: A novel community pharmacy approach to enhance patient care delivery by leveraging the technician workforce through technician product verification.

Clicks: 375
ID: 52722
2019
Article Quality & Performance Metrics
Overall Quality Improving Quality
0.0 /100
Combines engagement data with AI-assessed academic quality
AI Quality Assessment
Not analyzed
Abstract
To explore initial outcomes of the Optimizing Care Model's impact on patient care through technician product verification after the first 3 months of implementation, including the model's impact on pharmacist workday composition, rates of patient care services delivered, and rates of product selection errors not identified during final product verification.Fourteen chain and independent community pharmacies licensed and located in Tennessee.The Optimizing Care Model is an innovative approach to community pharmacy practice aiming to foster a new patient-centered care delivery model that expands clinical service delivery through task delegation to pharmacist extenders.A quasiexperimental 1-group pretest-posttest design was used. Study sites self-reported data from 3 months before and 3 months after implementation of the intervention.Overall pharmacist time spent delivering patient care services increased significantly on implementation of the Optimizing Care Model (25% vs. 43%; P < 0.001), and time spent performing dispensing-related activities decreased significantly (63% vs. 37%; P = 0.02). There was a total increase in quantity of clinical services delivered to patients from baseline, but data from initial study outcomes did not reach statistical significance. At least 1 new clinical service provided under a collaborative practice agreement had been implemented by all 14 sites (100%) as of Spring 2018. Total undetected error rates were significantly less in the Optimizing Care Model phase compared to the traditional model (0.063% vs. 0.085%; P < 0.001).Initial results of the Optimizing Care Model demonstrate improved patient care through increased clinical service delivery versus the traditional model. Undetected error detection rates were low in both models, but lower in the Optimizing Care Model. The Optimizing Care Model may represent a novel approach to improving care for patients while creating efficiencies through a staff delegation model, providing pharmacists the opportunity to further evolve their practice and advance clinical care for patients.
Reference Key
hohmeier2019thejournal Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Hohmeier, Kenneth C;Garst, Aaron;Adkins, Lucy;Yu, Xinhua;Desselle, Shane P;Cost, Micah;
Journal journal of the american pharmacists association : japha
Year 2019
DOI S1544-3191(19)30347-4
URL
Keywords
pharmacokinetics poloxamer sustained release in vitro release sd, standard deviation im, intramuscular atp, adenosine 5′ triphosphate auc80h, area under the analyte concentration versus time curve from time zero to 80 h auclast, area under the analyte concentration versus time curve from time zero to the time of the last measurable (non-below quantification level) concentration auc∞, area under the analyte concentration vs time curve from time zero to infinite time c0, analyte plasma concentration at time zero can, acetonitrile cmc, critical micellar concentration cmt, critical micellar temperature cmax, maximum observed analyte plasma concentration dn, dose normalized doe, design of experiments eo, ethylene oxide gpt, gel point temperature gel erosion h&e, hematoxylin and eosin iv, intravenous in situ forming gels k2.edta, potassium ethylenediaminetetraacetic acid lc–ms/ms, liquid chromatography-tandem mass spectrometry mdr-tb, multi-drug resistant tuberculosis mrm, multiple reaction monitoring nmp, n-methyl-2-pyrrolidone p338, poloxamer 338 p407, poloxamer 407 plga, poly-(dl-lactic-co-glycolic acid) po, propylene oxide tfa, trifluoroacetic acid uhplc, ultra-high performance liquid chromatography uv, ultraviolet n, sample size t1/2, apparent terminal elimination half-life tlast, sampling time until the last measurable (non-below quantification level) analyte plasma concentration tmax, sampling time to reach the maximum observed analyte plasma concentration

Citations

No citations found. To add a citation, contact the admin at info@scimatic.org

Comments

No comments yet. Be the first to comment on this article.