| Literature DB >> 31771404 |
Jangus B Whitner1, Lisa A Mueller2, Alexa Sevin Valentino1,3.
Abstract
Objectives: The primary objective of this study is to determine the effect of proactive pharmacist identification of high-risk patients eligible for diagnostic spirometry testing on the percentage of appropriate spirometry referrals ordered and the percentage of spirometry tests completed in those that qualify.Entities:
Keywords: ambulatory care; chronic obstructive pulmonary disease (COPD); community health center; federally qualified health center; pharmacist; primary care; pulmonary function test; smoker; spirometry; spirometry screening
Mesh:
Year: 2019 PMID: 31771404 PMCID: PMC6882036 DOI: 10.1177/2150132719889715
Source DB: PubMed Journal: J Prim Care Community Health ISSN: 2150-1319
Exclusion Criteria for Diagnostic Spirometry Screening.[a]
| Active | • Pregnancy | • Inability to follow directions (eg, cognitive impairment/ learning disability) |
| Active and/or history of | • Aneurysm (aortic—thoracic/cerebral/abdominal) | • Pneumothorax |
| Recent (within past 1 month) | • Myocardial infarction | |
| Recent surgery (within past 6 weeks) | • Thoracic/abdominal | • Eye/ophthalmic |
| Infection | Active and/or history of within past 2 weeks: | Active: |
Abbreviations: CVA, cerebrovascular accident; TIA, transient ischemic attack.
The criteria (and durations) for exclusion were based on existing literature on absolute and relative contraindications and the consideration that if this criterion were present, it would be too complicated for a primary care setting or would pose an infection control risk.[9-16]
Figure 1.Patient algorithm.
Abbreviations: yo, years old; Dx, diagnosis; COPD, chronic obstructive pulmonary disease; EHR, electronic health record; PCP, primary care provider.
Patient Demographics.
| Intervention Site (n = 125) | Control Site (n = 65) |
| |
|---|---|---|---|
| Age, years, mean ± SD | 54.6 ± 7.6 | 54.3 ± 8.7 | .82[ |
| Gender, female, n (%) | 68 (54.4) | 30 (46.2) | .29[ |
| Race/ethnicity, n (%) | |||
| White or Caucasian | 63 (50.4) | 34 (52.3) | <.001[ |
| Black or African American | 60 (48.0) | 15 (23.1) | |
| Other/unreported | 2 (1.6) | 16 (24.6) | |
| Primary language, n (%) | |||
| English | 122 (97.6) | 53 (81.5) | <.001[ |
| Other | 3 (2.4) | 12 (18.5) | |
| Primary insurance, n (%) | |||
| Medicaid | 84 (67.2) | 39 (60.0) | 0.24[ |
| Medicare | 20 (16.0) | 11 (16.9) | |
| Private insurance | 13 (10.4) | 7 (10.8) | |
| Uninsured | 8 (6.4) | 8 (12.3) |
Two-sided Student’s t test. Significance level of .05.
Two-sided Fisher’s exact test (if a cell count is <5). Significance level of .05.
Figure 2.Spirometry referral rate in high-risk patients with and without pharmacist intervention.
aTwo-sided Fisher’s exact test. The significance level was .05.
Spirometry Screening Test Completion Rate.
| Intervention Site | Control Site |
| ||
|---|---|---|---|---|
| Number of spirometry screenings completed | 29 | 2 | ||
| Completion rate of high-risk patients identified |
| 23.2% (29/125) | 3.1% (2/65) | <.001[ |
| Completion rate of referrals ordered |
| 49.2% (29/59) | 40% (2/5) | .999[ |
| Pooled: 48.4% | ||||
Two-sided Fisher’s exact test (if a cell count is <5). Significance level of .05.
Small sample sizes affect P values.
Figure 3.Impact of the spirometry findings on chronic obstructive pulmonary disease (COPD) diagnosis (n = 31).