Background: Transitions of care (TOC) points are those where patient outcomes can be affected, especially patients at high risk for medication errors. Pharmacist-led postdischarge telephone counseling positively affects patient outcomes, though challenges exist relating to successful patient contact. Objective: The objective of this study was to develop and evaluate a discharge education service bridging the inpatient and outpatient setting to increase successful patient contact points during the TOC process from hospital to home. Methods: This prospective, single-centered observational study examined the impact of a discharge medication education program on successful telephone follow-up contact. The primary outcome was the percentage of high-risk patients educated at hospital discharge who were successfully reached via follow-up telephone contact within 2 business days of discharge. Secondary end points included hospital readmission rates and patient survey responses. Results: A total of 50 patients were included in the initial evaluation of this service; 78% of patients were successfully contacted within 2 business days after discharge, an increase from a 20% success rate prior to service implementation. At follow-up telephone calls, patients reported taking an average of 16 medications. The 30-day readmission rate was 10% for patients receiving this service, compared with 19% prior to implementation. When asked if they understood the medication component of their care and if they found the TOC service to be satisfactory, 100% and 96% of patients strongly agreed or agreed with these statements, respectively, and none disagreed. Conclusion and Relevance: This service demonstrates how pharmacists can interact with a high-risk population and increase contact points to optimize care at crucial health care transition points.
Background: Point-of-care (POC) testing devices allow laboratory monitoring to be performed in various settings and accessed immediately. Objective: To evaluate the outcomes of monitoring anticoagulation patients in pharmacistmanaged, multicenter clinics utilizing i-STAT POC machines. Methods: This study was a retrospective, multicenter chart review of 150 patients before and after implementation of the POC intervention for anticoagulation monitoring. Data collected included international normalized ratio (INR) results, indication for warfarin, minor and major bleeds, thromboembolic events, emergency room (ER) visits, and hospitalizations before and after i-STAT POC implementation. Results: The time in therapeutic INR range (TTR) was significantly higher after i-STAT POC implementation than before implementation (60.4% ± 21.2% and 52.5% ± 21.5%, respectively; P = .0001). There were no reports of major bleeding during the study period. Twenty-three minor bleeds were reported after i-STAT POC implementation compared to 19 events before implementation (P < .0001). One thromboembolic event was reported after i-STAT POC implementation. There was a significant difference in the number of hospitalizations before i-STAT POC implementation as opposed to after implementation (2 and 0, respectively; P < .0001). There was also a significant increase in ER visits after i-STAT POC implementation (P < .0001). Conclusion:The results of the study indicate improvement in TTR in pharmacist-managed anticoagulation clinics by 7.8%. Although the use of the i-STAT POC machine detected an increase in minor bleeds, thromboembolic events, and ER visits, there was a decrease in hospitalization. The outcomes of this multicenter study indicate that implementation on this scale provides improvement in regard to safety and cost.
Purpose: To evaluate the impact that close monitoring by a clinical pharmacist using the i-STAT point of care (POC) machine had on outcomes of anticoagulation patients. Methods: This study was a retrospective chart review of 40 patients with an average age of 58.7 who served as their own historical control. Data collected included international normalized ratio (INR) results, indication for warfarin, adverse drug events, emergency room visits, and hospitalizations both before and after the i-STAT POC implementation (November 2006 to August 2009). Results: The proportion of time within therapeutic INR range 2.0 to 3.0 was higher after i-STAT POC implementation compared to before (46.3% and 56.2%; P 5 .001). When a wider INR range was analyzed (1.8-3.2), the proportion of time within range was 64.6% versus 68.9% (P 5 .001). In terms of safety, 27 adverse events were documented before and 22 adverse events were documented after i-STAT implementation. Eighteen hospitalizations were related to bleeding or clotting and were distributed evenly between before and after i-STAT implementation. Percentages of medication nonadherence were 12.5% before and 12.1% after the implementation. Conclusion: The results of this study indicate that implementation of the i-STAT POC machine in a pharmacist-managed anticoagulation clinic increased percent of time within therapeutic INR by 9.9%. Patient INR results were better controlled at more stable levels. Furthermore, use of i-STAT POC showed improvement in terms of safety, adherence, and cost. Though the significance of these results requires further study, the promising positive outcomes will certainly encourage implementation of this model on a larger scale.
Background: While commonly prescribed today, direct oral anticoagulants (DOACs) have historically been avoided in patients with class III obesity or a weight >120 kg due to limited literature regarding the efficacy and safety in this population. Objective: The overall objective was to examine the effectiveness of DOACs compared to warfarin in a population with obesity. Methods: Patients with a diagnosis of venous thromboembolism (VTE) or atrial fibrillation and a body mass index (BMI) ≥35 kg/m2 from August 1, 2015, to August 1, 2020, were included in this retrospective cohort study. Patients receiving a DOAC were matched in a 1:2 ratio to warfarin. The primary outcome was a composite of stroke or recurrent VTE. Secondary outcomes included the individual components of the primary outcome, hospitalization for bleed, and the primary outcome in patients with a BMI ≥40 kg/m2. Results: A total of 162 patients were included, with 54 and 108 in the DOAC and warfarin groups, respectively. Baseline BMI was similar between groups (45.7 kg/m2 for DOACs vs 43.8 kg/m2 for warfarin), with approximately 70% of patients having a BMI ≥40 kg/m2. The primary outcome occurred in 1 patient (1.9%) in the DOAC group and 2 patients (1.9%) in the warfarin group. The DOAC group had a higher, nonsignificant incidence of bleeding (5.6% vs 0.9%, P = 0.11). There was no difference between groups in incidence of deep vein thrombosis (DVT), pulmonary embolism (PE), or stroke in patients with a BMI ≥40 kg/m2. Conclusion: DOACs may be as efficacious as warfarin in the prevention of stroke or recurrent VTE in patients with a BMI of ≥35 kg/m2. Prospective, randomized trials are warranted to further assess the efficacy and safety of DOACs in this population.
This study may serve as a platform for future research.
Purpose To determine whether primary care medicine clinic (PCMC) patients with a prescription drug benefit were associated with a lower rate of hospital readmissions. Methods This study was a retrospective, single-center, cohort study of PCMC patients who had at least 1 hospital readmission in 2011. Eligible patients were divided into 2 groups: patients without prescription drug benefits and patients with prescription drug benefits. Results Three hundred fifty-two patients met our inclusion criteria. The number of hospital readmissions for patients with a prescription drug benefit was higher than those with no prescription drug benefit (2.453 ± 2.49 vs 1.88 ± 1.91; P = .052). The length of index admission and the length of hospital readmission in days were higher in patients with no prescription drug benefits (index admission, 5.29 ± 6.38 vs 4.59 ± 4.50; P = .428) (readmission, 5.31 ± 5.90 vs 4.48 ± 4.33, P = .166). The number of days to readmission was higher in those with drug benefits (58.12 ± 63.54 vs 53.39 ± 53.47; P = .316). When patient data were separated by CCI scores, it was noted that patients with pharmacy benefits had significantly more hospital readmissions in each CCI score category except for patients with a CCI of 6. Conclusion Although not statistically significant, patients with prescription drug benefits had more hospital readmissions but shorter hospital lengths of stay. Significant data linking hospital readmissions and prescription insurance benefits, if found in future studies, would provide helpful guidance to health care systems.
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