Health Disparities in Pharmacy Practice Within the Community: Let's Brainstorm for Solutions.

Health disparity is defined as a type of health difference that is closely linked with social, economic and/or environmental disadvantage. Over the past two decades, major efforts have been undertaken to mitigate health disparities and promote health equity in the United States. Within pharmacy practice, health disparities have also been identified to play a role in influencing pharmacists' practice across various clinical settings. However, well-characterized solutions to address such disparities, particularly within pharmacy practice, are lacking in the literature. Recognizing that a significant amount of work will be necessary to reduce or eliminate health disparities, the University of California, Irvine (UCI) School of Pharmacy and Pharmaceutical Sciences held a webinar in June 2021 to explore pertinent issues related to this topic. During the session, participants were given the opportunity to propose and discuss innovative solutions to overcome health disparities in pharmacy practice. The goal of this perspective article is to distill the essence of the presentations and discussions from this interactive session, and to synthesize ideas for practical solutions that can be translated to practice to address this public health problem

Charge and spin transport over record distances in GaAs metallic n -type nanowires

International audienceWe have investigated charge and spin transport in n-type metallic GaAs nanowires (≈ 10 17 cm −3 doping level), grown by hydride vapor phase epitaxy (HVPE) on Si substrates. For this doping level, charge and spin transport might appear difficult because of the expected localization of minority holes in the valence band potential fluctuations generated by statistical fluctuations of the donor concentration. In contrast with these expectations, it is found, using spatially-and spectrally-resolved investigation of the luminescence intensity and circular polarization under laser excitation, that i) establishment of a charge thermodynamic equilibrium between the photoelectrons and the Fermi sea occurs over a distance from the excitation spot of 2 µm. At this distance, the spin polarization is still observed, implying that photoelectrons have preserved their spin orientation and that the two spin reservoirs remain distinct. ii) Charge can be transported over record distances larger than 20 µm at 6K. iii) Spatially-resolved investigations show that a photoelectron spin polarization of 20% can even be transported over a record distance of more than 20 µm. This long distance transport occurs because of the presence of large internal electric fields of ambipolar origin, further enhanced by the spatial redistribution of the Fermi sea. These findings has potential applications for long distance spin transport in n-type doped nanowires

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

BACKGROUND: In 2012 U.S. diabetes costs were estimated to be $245 billion, with$176 billion related to direct diabetes treatment and associated complications. Although a few studies have reported positive glycemic and economic benefits for diabetes patients treated under primary care physician (PCP)-pharmacist collaborative practice models, no studies have evaluated the cost-effectiveness of an endocrinologist-pharmacist collaborative practice model treating complex diabetes patients versus usual PCP care for similar patients. OBJECTIVE: To estimate the cost-effectiveness and cost benefit of a collaborative endocrinologist-pharmacist Diabetes Intense Medical Management (DIMM) Tune-Up clinic for complex diabetes patients versus usual PCP care from 3 perspectives (clinic, health system, payer) and time frames. METHODS: Data from a retrospective cohort study of adult patients with type 2 diabetes mellitus (T2DM) and glycosylated hemoglobin A1c (A1c) ≥ 8% who were referred to the DIMM clinic at the Veterans Affairs San Diego Health System were used for cost analyses against a comparator group of PCP patients meeting the same criteria. The DIMM clinic took more time with patients, compared with usual PCP visits. It provided personalized care in three 60-minute visits over 6 months, combining medication therapy management with patient-specific diabetes education, to achieve A1c treatment goals before discharge back to the PCP. Data for DIMM versus PCP patients were used to evaluate cost-effectiveness and cost benefit. Analyses included incremental cost-effectiveness ratios (ICERs) at 6 months, 3-year estimated total medical costs avoided and return on investment (ROI), absolute risk reduction of complications, resultant medical costs, and quality-adjusted life-years (QALYs) over 10 years. RESULTS: Base case ICER results indicated that from the clinic perspective, the DIMM clinic costs $21 per additional percentage point of A1c improvement and$115-$164 per additional patient at target A1c goal level compared with the PCP group. From the health system perspective, medical cost avoidance due to improved A1c was$8,793 per DIMM patient versus $3,506 per PCP patient (P = 0.009), resulting in an ROI of$9.01 per dollar spent. From the payer perspective, DIMM patients had estimated lower total medical costs, a greater number of QALYs gained, and appreciable risk reductions for diabetes-related complications over 2-, 5- and 10-year time frames, indicating that the DIMM clinic was dominant. Sensitivity analyses indicated results were robust, and overall conclusions did not change appreciably when key parameters (including DIMM clinic effectiveness and cost) were varied within plausible ranges. CONCLUSIONS: The DIMM clinic endocrinologist-pharmacist collaborative practice model, in which the pharmacist spent more time providing personalized care, improved glycemic control at a minimal cost per additional A1c benefit gained and produced greater cost avoidance, appreciable ROI, reduction in long-term complication risk, and lower cost for a greater gain in QALYs. Overall, the DIMM clinic represents an advanced pharmacy practice model with proven clinical and economic benefits from multiple perspectives for patients with T2DM and high medication and comorbidity complexity. DISCLOSURES: No outside funding supported this study. The authors declare no potential conflicts of interest with respect to the research, authorship, and/or publication of this article. Preliminary versions of the study data were presented in abstract form at the American Pharmacists Association Annual Meeting & Exposition; March 27, 2015; San Diego, California, and the Academy of Managed Care Pharmacy Annual Meeting; April 21, 2016; San Francisco, California. Study concept and design were contributed by Hirsch, Bounthavong, and Edelman, along with Morello and Morreale. Arjmand, Ourth, Ha, Cadiz, and Zimmerman collected the data. Data interpretation was performed by Ha, Morreale, and Morello, along with Cadiz, Ourth, and Hirsch. The manuscript was written primarily by Hirsch and Zimmerman, along with Arjamand, Ourth, and Morello, and was revised by Hirsch and Cadiz, along with Bounthavong, Ha, Morreale, and Morello

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

BACKGROUND: In 2012 U.S. diabetes costs were estimated to be $245 billion, with$176 billion related to direct diabetes treatment and associated complications. Although a few studies have reported positive glycemic and economic benefits for diabetes patients treated under primary care physician (PCP)-pharmacist collaborative practice models, no studies have evaluated the cost-effectiveness of an endocrinologist-pharmacist collaborative practice model treating complex diabetes patients versus usual PCP care for similar patients. OBJECTIVE: To estimate the cost-effectiveness and cost benefit of a collaborative endocrinologist-pharmacist Diabetes Intense Medical Management (DIMM) Tune-Up clinic for complex diabetes patients versus usual PCP care from 3 perspectives (clinic, health system, payer) and time frames. METHODS: Data from a retrospective cohort study of adult patients with type 2 diabetes mellitus (T2DM) and glycosylated hemoglobin A1c (A1c) ≥ 8% who were referred to the DIMM clinic at the Veterans Affairs San Diego Health System were used for cost analyses against a comparator group of PCP patients meeting the same criteria. The DIMM clinic took more time with patients, compared with usual PCP visits. It provided personalized care in three 60-minute visits over 6 months, combining medication therapy management with patient-specific diabetes education, to achieve A1c treatment goals before discharge back to the PCP. Data for DIMM versus PCP patients were used to evaluate cost-effectiveness and cost benefit. Analyses included incremental cost-effectiveness ratios (ICERs) at 6 months, 3-year estimated total medical costs avoided and return on investment (ROI), absolute risk reduction of complications, resultant medical costs, and quality-adjusted life-years (QALYs) over 10 years. RESULTS: Base case ICER results indicated that from the clinic perspective, the DIMM clinic costs $21 per additional percentage point of A1c improvement and$115-$164 per additional patient at target A1c goal level compared with the PCP group. From the health system perspective, medical cost avoidance due to improved A1c was$8,793 per DIMM patient versus $3,506 per PCP patient (P = 0.009), resulting in an ROI of$9.01 per dollar spent. From the payer perspective, DIMM patients had estimated lower total medical costs, a greater number of QALYs gained, and appreciable risk reductions for diabetes-related complications over 2-, 5- and 10-year time frames, indicating that the DIMM clinic was dominant. Sensitivity analyses indicated results were robust, and overall conclusions did not change appreciably when key parameters (including DIMM clinic effectiveness and cost) were varied within plausible ranges. CONCLUSIONS: The DIMM clinic endocrinologist-pharmacist collaborative practice model, in which the pharmacist spent more time providing personalized care, improved glycemic control at a minimal cost per additional A1c benefit gained and produced greater cost avoidance, appreciable ROI, reduction in long-term complication risk, and lower cost for a greater gain in QALYs. Overall, the DIMM clinic represents an advanced pharmacy practice model with proven clinical and economic benefits from multiple perspectives for patients with T2DM and high medication and comorbidity complexity. DISCLOSURES: No outside funding supported this study. The authors declare no potential conflicts of interest with respect to the research, authorship, and/or publication of this article. Preliminary versions of the study data were presented in abstract form at the American Pharmacists Association Annual Meeting & Exposition; March 27, 2015; San Diego, California, and the Academy of Managed Care Pharmacy Annual Meeting; April 21, 2016; San Francisco, California. Study concept and design were contributed by Hirsch, Bounthavong, and Edelman, along with Morello and Morreale. Arjmand, Ourth, Ha, Cadiz, and Zimmerman collected the data. Data interpretation was performed by Ha, Morreale, and Morello, along with Cadiz, Ourth, and Hirsch. The manuscript was written primarily by Hirsch and Zimmerman, along with Arjamand, Ourth, and Morello, and was revised by Hirsch and Cadiz, along with Bounthavong, Ha, Morreale, and Morello

Improved Patient-Reported Medication Adherence, Patient Satisfaction, and Glycemic Control in a Collaborative Care Pharmacist-Led Diabetes "Tune-Up" Clinic.

Diabetes complications remain a leading cause of death, which may be due to poor glycemic control resulting from medication nonadherence. The relationship between adherence status and HbA1c (glycemic control) has not been well-studied for clinical pharmacist interventions. This study evaluated medication adherence, patient satisfaction, and HbA1c, in a collaborative pharmacist-endocrinologist diabetes clinic over 6 months. Of 127 referred, 83 patients met the inclusion criteria. Mean medication adherence scores, considered "good" at baseline, 1.4 ± 1.2, improved by 0.05 points (p = 0.018), and there was a 26% increase in patients with good adherence. A significant improvement of 0.40 percentage points (95% CI: -0.47, -0.34) was observed in mean HbA1c across the three time points (p < 0.001). Mean total satisfaction scores were high and increased, with mean 91.3 ± 12.2 at baseline, 94.7 ± 9.6 at 3 months, and 95.7 ± 10.8 at 6 months (p = 0.009). A multimodal personalized treatment approach from a pharmacist provider significantly and positively impacted glycemic control regardless of self-reported medication adherence, and patient satisfaction remained high despite changing to a clinical pharmacist provider and increased care intensity

Genomic organization and spatio-temporal expression of the hemoglobin genes in European sea bass (Dicentrarchus labrax)

Hemoglobins (Hb) play a critical role in satisfying the oxygen demand of vertebrate aerobic metabolism. The present study reports the characterization of the European sea bass (Dicentrarchus labrax) Hb genes, including genomic organization, phylogeny, and spatio-temporal gene expression. These Hb genes are divided into two unlinked clusters, the “MN” cluster containing eleven genes (five Hbα genes named MN-Hbα1-5 and six Hbβ genes named MN-Hbβ1–6) and the “LA” cluster consisting of three genes (two Hbα genes named LA-Hbα1-2 and one Hbβ gene named LA-Hbβ1). Comparative analysis of Hb amino acid sequences indicates that most of the important amino acid residues involved in hemoglobin-oxygen binding, particularly in the Bohr and Root effects, are generally well conserved, except in MN-Hbβ3. Six genes were mainly expressed during early life (MN-Hbα3-5, MN-Hbβ4–6), while the others were predominantly expressed at juvenile–adult stages. Adult fish expressed Hb genes at high levels in the head kidney and spleen; the main organs involved in blood formation. The Hb genes expressed in non-hematopoietic organs (intestine, gills, heart, brain, and liver) may facilitate oxygen homeostasis or be involved in antimicrobial defense. Stage- and tissue-specific gene expression patterns, together with the sequence features of the different Hb proteins, suggest a broad range of roles in European sea bass

Anomalous ambipolar transport in depleted GaAs nanowires

International audienceWe have used a polarized microluminescence technique to investigate photocarrier charge and spin transport in depleted n-type GaAs nanowires (≈10 17 cm −3 doping level). At 6 K, a long-distance tail appears in the luminescence spatial profile, indicative of charge and spin transport, and only limited by the length of the nanowire (NW). This tail weakly depends on excitation power and temperature. Using a self-consistent calculation based on the drift-diffusion and Poisson equations as well as on photocarrier statistics (Van Roosbroeck model), it is found that this tail is due to photocarrier drift in an internal electric field nearly two orders of magnitude larger than electric fields predicted by the usual ambipolar model. This large electric field appears because of two effects. First, for transport in the spatial fluctuations of the conduction band minimum and valence band maximum, the electron mobility is activated by the internal electric field. This implies, in a counterintuitive way, that the spatial fluctuations favor long-distance transport. Second, the range of carrier transport is further increased because of the finite NW length, an effect which plays a key role in one-dimensional systems

Using machine learning to develop a clinical prediction model for SSRI-associated bleeding: a feasibility study.

IntroductionAdverse drug events (ADEs) are associated with poor outcomes and increased costs but may be prevented with prediction tools. With the National Institute of Health All of Us (AoU) database, we employed machine learning (ML) to predict selective serotonin reuptake inhibitor (SSRI)-associated bleeding.MethodsThe AoU program, beginning in 05/2018, continues to recruit ≥ 18 years old individuals across the United States. Participants completed surveys and consented to contribute electronic health record (EHR) for research. Using the EHR, we determined participants who were exposed to SSRIs (citalopram, escitalopram, fluoxetine, fluvoxamine, paroxetine, sertraline, vortioxetine). Features (n = 88) were selected with clinicians' input and comprised sociodemographic, lifestyle, comorbidities, and medication use information. We identified bleeding events with validated EHR algorithms and applied logistic regression, decision tree, random forest, and extreme gradient boost to predict bleeding during SSRI exposure. We assessed model performance with area under the receiver operating characteristic curve statistic (AUC) and defined clinically significant features as resulting in > 0.01 decline in AUC after removal from the model, in three of four ML models.ResultsThere were 10,362 participants exposed to SSRIs, with 9.6% experiencing a bleeding event during SSRI exposure. For each SSRI, performance across all four ML models was relatively consistent. AUCs from the best models ranged 0.632-0.698. Clinically significant features included health literacy for escitalopram, and bleeding history and socioeconomic status for all SSRIs.ConclusionsWe demonstrated feasibility of predicting ADEs using ML. Incorporating genomic features and drug interactions with deep learning models may improve ADE prediction

Using machine learning to develop a clinical prediction model for SSRI-associated bleeding: a feasibility study

Abstract Introduction Adverse drug events (ADEs) are associated with poor outcomes and increased costs but may be prevented with prediction tools. With the National Institute of Health All of Us (AoU) database, we employed machine learning (ML) to predict selective serotonin reuptake inhibitor (SSRI)-associated bleeding. Methods The AoU program, beginning in 05/2018, continues to recruit ≥ 18 years old individuals across the United States. Participants completed surveys and consented to contribute electronic health record (EHR) for research. Using the EHR, we determined participants who were exposed to SSRIs (citalopram, escitalopram, fluoxetine, fluvoxamine, paroxetine, sertraline, vortioxetine). Features (n = 88) were selected with clinicians’ input and comprised sociodemographic, lifestyle, comorbidities, and medication use information. We identified bleeding events with validated EHR algorithms and applied logistic regression, decision tree, random forest, and extreme gradient boost to predict bleeding during SSRI exposure. We assessed model performance with area under the receiver operating characteristic curve statistic (AUC) and defined clinically significant features as resulting in > 0.01 decline in AUC after removal from the model, in three of four ML models. Results There were 10,362 participants exposed to SSRIs, with 9.6% experiencing a bleeding event during SSRI exposure. For each SSRI, performance across all four ML models was relatively consistent. AUCs from the best models ranged 0.632–0.698. Clinically significant features included health literacy for escitalopram, and bleeding history and socioeconomic status for all SSRIs. Conclusions We demonstrated feasibility of predicting ADEs using ML. Incorporating genomic features and drug interactions with deep learning models may improve ADE prediction