Community Pharmacist Telephonic Medication Reviews with Uncontrolled Asthma Patients: A Pilot Study.
Kathryn A HartleyKendall D GuthrieSteven C StonerJustin R MayD Matthew HartwigYifei LiuPublished in: Pharmacy (Basel, Switzerland) (2021)
This study reports the process of telephonic medication reviews conducted by community pharmacists for patients with asthma. The study occurred at an independent community chain in association with a Missouri Medicaid consulting group. Participants were identified utilizing claims data and met the National Quality Forum criteria for uncontrolled moderate-to-severe persistent asthma. A pharmacist performed the initial encounter via telephone which included a knowledge questionnaire, symptom control assessment, and medication review. Pharmacists identified drug-related problems (DRPs) and faxed recommendations to patients' primary care providers (PCPs). Thirty days later, pharmacists called to follow up with the patients and faxed PCPs to resolve any outstanding DRPs, new DRPs, or recommendations. Questionnaire scores and symptom control assessments were compared and analyzed utilizing a paired t-test, Chi-squared test, or Fisher's exact test. The number and categories of DRPs, recommendations made by pharmacists, and intervention time were reported. Fourteen participants completed initial encounters with twelve completing follow-up. The majority answered 'yes' to at least one symptom control assessment question indicating partially controlled to uncontrolled asthma. The average knowledge assessment score was 5.17 out of 7 initially and 5.42 for the follow-up. Pharmacists identified 43 DRPs and made 41 recommendations with a mean intervention time of 65 min.
Keyphrases
- end stage renal disease
- healthcare
- primary care
- chronic obstructive pulmonary disease
- ejection fraction
- chronic kidney disease
- mental health
- randomized controlled trial
- patient reported
- lung function
- prognostic factors
- peritoneal dialysis
- systematic review
- clinical practice
- emergency department
- deep learning
- machine learning
- adverse drug
- quality improvement
- artificial intelligence
- patient reported outcomes
- electronic health record
- molecular dynamics