Literature DB >> 32482500

Development of a screening tool to identify patients likely to benefit from clinical pharmacist review in a home-based primary care population.

Amy E Stewart, James F Lovato, Rachel Zimmer, Alyssa P Stewart, Molly T Hinely, Mia Yang.   

Abstract

OBJECTIVE: To create a novel screening tool that identified patients who were most likely to benefit from pharmacist in-home medication reviews.
DESIGN: Single-center, retrospective study. SETTING AND PARTICIPANTS: A total of 25 homebound patients in Forsyth County, NC, aged 60 years or older with physical or cognitive impairments and enrolled in home-based primary care or transitional and supportive care programs participated in the study. Pharmacy resident-provider pairs conducted home visits for all patients in the study. Pharmacy residents assessed the subjective risk (high, medium, low) of medication nonadherence using information obtained from home visits (health literacy, support network, medications, and detection of something unexpected related to medications). An electronic medical record-based risk score was simultaneously calculated using screening tool components (i.e., electronic frailty index score, LACE+ index [length of stay in the hospital, acuity of admission, comorbidity, emergency department utilization in the 6 months before admission], and 2015 American Geriatric Society Beers Criteria). OUTCOME MEASURES: The electronic medical record-based screening tool numerical risk scores were compared with pharmacy resident subjective risk assessments using tree-based classification models to determine screening tool components that best predicted pharmacy residents' subjective assessment of patients' likelihood of benefit from in-home pharmacist medication review. Following the study, satisfaction surveys were given to providers and pharmacy residents.
RESULTS: The best predictor of high-risk patients was an electronic frailty index score greater than 0.32 (indicating very frail) or LACE+ index greater than or equal to 59 (at high risk for hospital readmission). Pharmacy residents and providers agreed that homebound patients at high-risk for medication noncompliance benefited from pharmacist time and attention in home visits.
CONCLUSION: In homebound older persons, this screening tool allowed for the identification of patients at high-risk for medication nonadherence through targeted in-home pharmacist medication reviews. Further studies are needed to validate the accuracy of this tool internally and externally.
Copyright © 2020. Published by Elsevier Inc.

Entities:  

Mesh:

Year:  2020        PMID: 32482500      PMCID: PMC8867744          DOI: 10.1016/j.japh.2020.03.008

Source DB:  PubMed          Journal:  J Am Pharm Assoc (2003)        ISSN: 1086-5802


  14 in total

1.  American Geriatrics Society 2015 Updated Beers Criteria for Potentially Inappropriate Medication Use in Older Adults.

Authors: 
Journal:  J Am Geriatr Soc       Date:  2015-10-08       Impact factor: 5.562

Review 2.  Systematic review of outcomes from home-based primary care programs for homebound older adults.

Authors:  Nathan Stall; Mark Nowaczynski; Samir K Sinha
Journal:  J Am Geriatr Soc       Date:  2014-11-04       Impact factor: 5.562

3.  Frailty and polypharmacy in elderly patients are associated with a high readmission risk.

Authors:  Elizabeth Rosted; Martin Schultz; Suzanne Sanders
Journal:  Dan Med J       Date:  2016-09       Impact factor: 1.240

4.  Impact of a pharmacist-physician collaborative care model on patient outcomes and health services utilization.

Authors:  Gary R Matzke; Leticia R Moczygemba; Karen J Williams; Michael J Czar; William T Lee
Journal:  Am J Health Syst Pharm       Date:  2018-05-22       Impact factor: 2.637

5.  Epidemiology of the Homebound Population in the United States.

Authors:  Katherine A Ornstein; Bruce Leff; Kenneth E Covinsky; Christine S Ritchie; Alex D Federman; Laken Roberts; Amy S Kelley; Albert L Siu; Sarah L Szanton
Journal:  JAMA Intern Med       Date:  2015-07       Impact factor: 21.873

Review 6.  Pharmacist and physician collaboration in the patient's home.

Authors:  Nadia A Amruso; Michael L O'Neal
Journal:  Ann Pharmacother       Date:  2004-04-27       Impact factor: 3.154

7.  Cost-Effectiveness of a Physician-Pharmacist Collaboration Intervention to Improve Blood Pressure Control.

Authors:  Linnea A Polgreen; Jayoung Han; Barry L Carter; Gail P Ardery; Christopher S Coffey; Elizabeth A Chrischilles; Paul A James
Journal:  Hypertension       Date:  2015-11-02       Impact factor: 10.190

8.  Estimated Cost-Effectiveness, Cost Benefit, and Risk Reduction Associated with an Endocrinologist-Pharmacist Diabetes Intense Medical Management "Tune-Up" Clinic.

Authors:  Jan D Hirsch; Mark Bounthavong; Anisa Arjmand; David R Ha; Christine L Cadiz; Andrew Zimmerman; Heather Ourth; Anthony P Morreale; Steven V Edelman; Candis M Morello
Journal:  J Manag Care Spec Pharm       Date:  2017-03

9.  Evaluating the predictive strength of the LACE index in identifying patients at high risk of hospital readmission following an inpatient episode: a retrospective cohort study.

Authors:  Sarah Damery; Gill Combes
Journal:  BMJ Open       Date:  2017-07-13       Impact factor: 2.692

10.  Development and validation of an electronic frailty index using routine primary care electronic health record data.

Authors:  Andrew Clegg; Chris Bates; John Young; Ronan Ryan; Linda Nichols; Elizabeth Ann Teale; Mohammed A Mohammed; John Parry; Tom Marshall
Journal:  Age Ageing       Date:  2016-03-03       Impact factor: 10.668

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  2 in total

Review 1.  Identifying Frail Patients by Using Electronic Health Records in Primary Care: Current Status and Future Directions.

Authors:  Jianzhao Luo; Xiaoyang Liao; Chuan Zou; Qian Zhao; Yi Yao; Xiang Fang; John Spicer
Journal:  Front Public Health       Date:  2022-06-22

2.  Pharmacist medication review: An integrated team approach to serve home-based primary care patients.

Authors:  Michele Monzón-Kenneke; Paul Chiang; Nengliang Aaron Yao; Mark Greg
Journal:  PLoS One       Date:  2021-05-25       Impact factor: 3.240

  2 in total

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