Implementing a Pharmacist-Led Medication Management Pilot to Improve Care Transitions

Purpose: The purpose of this project was to design and pilot a pharmacist-led process to address medication management across the continuum of care within a large integrated health-system.Summary: A care transitions pilot took place within a health-system which included a 150-bed community hospital. The pilot process expanded the pharmacist’s medication management responsibilities to include providing discharge medication reconciliation, a patient-friendly discharge medication list, discharge medication education, and medication therapy management (MTM) follow-up.Adult patients with a predicted diagnosis-related group (DRG) of congestive heart failure or chronic obstructive pulmonary disease admitted to the medical-surgical and intensive care units who utilized a primary care provider within the health-system were included in the pilot. Forty patients met the inclusion criteria and thirty-four (85%) received an intervention from an inpatient or MTM pharmacist. Within this group of patients, 88 drug therapy problems (2.6 per patient) were identified and 75% of the drug therapy recommendations made by the pharmacist were accepted by the care provider. The 30-day all-cause readmission rates for the intervention and comparison groups were 30.5% and 35.9%, respectively. The number of patients receiving follow-up care varied with 10 (25%) receiving MTM follow-up, 26 (65%) completing a primary care visit after their first hospital discharge, and 23 (58%) receiving a home care visit.Conclusion: Implementation of a pharmacist-led medication management pilot across the continuum of care resulted in an improvement in the quality of care transitions within the health-system through increased identification and resolution of drug therapy problems and MTM follow-up. The lessons learned from the implementation of this pilot will be used to further refine pharmacy care transitions programs across the health-system

Implementing a Pharmacist-Led Medication Management Pilot to Improve Care Transitions

Purpose: The purpose of this project was to design and pilot a pharmacist-led process to address medication management across the continuum of care within a large integrated health-system. Summary: A care transitions pilot took place within a health-system which included a 150-bed community hospital. The pilot process expanded the pharmacist's medication management responsibilities to include providing discharge medication reconciliation, a patient-friendly discharge medication list, discharge medication education, and medication therapy management (MTM) follow-up. Adult patients with a predicted diagnosis-related group (DRG) of congestive heart failure or chronic obstructive pulmonary disease admitted to the medical-surgical and intensive care units who utilized a primary care provider within the health-system were included in the pilot. Forty patients met the inclusion criteria and thirty-four (85%) received an intervention from an inpatient or MTM pharmacist. Within this group of patients, 88 drug therapy problems (2.6 per patient) were identified and 75% of the drug therapy recommendations made by the pharmacist were accepted by the care provider. The 30-day all-cause readmission rates for the intervention and comparison groups were 30.5% and 35.9%, respectively. The number of patients receiving follow-up care varied with 10 (25%) receiving MTM follow-up, 26 (65%) completing a primary care visit after their first hospital discharge, and 23 (58%) receiving a home care visit. Conclusion: Implementation of a pharmacist-led medication management pilot across the continuum of care resulted in an improvement in the quality of care transitions within the health-system through increased identification and resolution of drug therapy problems and MTM follow-up. The lessons learned from the implementation of this pilot will be used to further refine pharmacy care transitions programs across the health-system.   Type: Original Researc

The influence of biological sex and sex hormones on bile acid synthesis and cholesterol homeostasis.

Obesity and elevated serum lipids are associated with a threefold increase in the risk of developing atherosclerosis, a condition that underlies stroke, myocardial infarction, and sudden cardiac death. Strategies that aim to reduce serum cholesterol through modulation of liver enzymes have been successful in decreasing the risk of developing atherosclerosis and reducing mortality. Statins, which inhibit cholesterol biosynthesis in the liver, are considered among the most successful compounds developed for the treatment of cardiovascular disease. However, recent debate surrounding their effectiveness and safety prompts consideration of alternative cholesterol-lowering therapies, including increasing cholesterol catabolism through bile acid (BA) synthesis. Targeting the enzymes that convert cholesterol to BAs represents a promising alternative to other cholesterol-lowering approaches that treat atherosclerosis as well as fatty liver diseases and diabetes mellitus. Compounds that modify the activity of these pathways have been developed; however, there remains a lack of consideration of biological sex. This is necessary in light of strong evidence for sexual dimorphisms not only in the incidence and progression of the diseases they influence but also in the expression and activity of the proteins affected and in the manner in which men and women respond to drugs that modify lipid handling in the liver. A thorough understanding of the enzymes involved in cholesterol catabolism and modulation by biological sex is necessary to maximize their therapeutic potential.</p

Relationship between a Weighted Multi-Gene Algorithm and Blood Pressure Control in Hypertension

Hypertension (HTN) is a complex disease with interactions among multiple organ systems, including the heart, vasculature, and kidney with a strong heritable component. Despite the multifactorial nature of HTN, no clinical guidelines utilize a multi-gene approach to guide blood pressure (BP) therapy. Non-smokers with a family history of HTN were included in the analysis (n = 384; age = 61.0 ± 0.9, 11% non-white). A total of 17 functional genotypes were weighted according to the previous effect size in the literature and entered into an algorithm. Pharmacotherapy was ranked from 1⁻4 as most to least likely to respond based on the algorithmic assessment of individual patient's genotypes. Three-years of data were assessed at six-month intervals for BP and medication history. There was no difference in BP at diagnosis between groups matching the top drug recommendation using the multi-gene weighted algorithm (n = 92) vs. those who did not match (n = 292). However, from diagnosis to nadir, patients who matched the primary recommendation had a significantly greater drop in BP when compared to patients who did not. Further, the difference between diagnosis to current 1-year average BP was lower in the group that matched the top recommendation. These data suggest an association between a weighted multi-gene algorithm on the BP response to pharmacotherapy.Geneticure Inc.Open access journalThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

The Structural and Functional Basis for Recurring Sulfa Drug Resistance Mutations in Staphylococcus aureus Dihydropteroate Synthase

Staphylococcal species are a leading cause of bacterial drug-resistant infections and associated mortality. One strategy to combat bacterial drug resistance is to revisit compromised targets, and to circumvent resistance mechanisms using structure-assisted drug discovery. The folate pathway is an ideal candidate for this approach. Antifolates target an essential metabolic pathway, and the necessary detailed structural information is now available for most enzymes in this pathway. Dihydropteroate synthase (DHPS) is the target of the sulfonamide class of drugs, and its well characterized mechanism facilitates detailed analyses of how drug resistance has evolved. Here, we surveyed clinical genetic sequencing data in S. aureus to distinguish natural amino acid variations in DHPS from those that are associated with sulfonamide resistance. Five mutations were identified, F17L, S18L, T51M, E208K, and KE257_dup. Their contribution to resistance and their cost to the catalytic properties of DHPS were evaluated using a combination of biochemical, biophysical and microbiological susceptibility studies. These studies show that F17L, S18L, and T51M directly lead to sulfonamide resistance while unexpectedly increasing susceptibility to trimethoprim, which targets the downstream enzyme dihydrofolate reductase. The secondary mutations E208K and KE257_dup restore trimethoprim susceptibility closer to wild-type levels while further increasing sulfonamide resistance. Structural studies reveal that these mutations appear to selectively disfavor the binding of the sulfonamides by sterically blocking an outer ring moiety that is not present in the substrate. This emphasizes that new inhibitors must be designed that strictly stay within the substrate volume in the context of the transition state

Helping the Working Poor: Employer- vs. Employee-Based Subsidies

In the United States and Europe there has been renewed interest in subsidizing firms that employ disadvantaged workers as a means of addressing poverty and other social problems. In contrast, the prevailing practice is largely to provide social welfare benefits directly to individuals. Which approach is better? We re-examine the relative merits of employee- versus employer-based labor market subsidies and conclude there are good reasons to continue to rely on the direct, employee-based approach. In practice, low-wage workers are seldom either low-skill or low-income workers. Furthermore, workers who might quality for a firm-based subsidy are reluctant to so identify themselves for fear of being stigmatized or labeled as needy. Thus, employer-based subsidy programs have lower participation rates and correspondingly higher per capita expenditures than employee-based subsidy programs

Learning a Prior on Regulatory Potential from eQTL Data

Genome-wide RNA expression data provide a detailed view of an organism's biological state; hence, a dataset measuring expression variation between genetically diverse individuals (eQTL data) may provide important insights into the genetics of complex traits. However, with data from a relatively small number of individuals, it is difficult to distinguish true causal polymorphisms from the large number of possibilities. The problem is particularly challenging in populations with significant linkage disequilibrium, where traits are often linked to large chromosomal regions containing many genes. Here, we present a novel method, Lirnet, that automatically learns a regulatory potential for each sequence polymorphism, estimating how likely it is to have a significant effect on gene expression. This regulatory potential is defined in terms of “regulatory features”—including the function of the gene and the conservation, type, and position of genetic polymorphisms—that are available for any organism. The extent to which the different features influence the regulatory potential is learned automatically, making Lirnet readily applicable to different datasets, organisms, and feature sets. We apply Lirnet both to the human HapMap eQTL dataset and to a yeast eQTL dataset and provide statistical and biological results demonstrating that Lirnet produces significantly better regulatory programs than other recent approaches. We demonstrate in the yeast data that Lirnet can correctly suggest a specific causal sequence variation within a large, linked chromosomal region. In one example, Lirnet uncovered a novel, experimentally validated connection between Puf3—a sequence-specific RNA binding protein—and P-bodies—cytoplasmic structures that regulate translation and RNA stability—as well as the particular causative polymorphism, a SNP in Mkt1, that induces the variation in the pathway

Utilizing CryoSat-2 sea ice thickness to initialize a coupled ice-ocean modeling system

Two CryoSat-2 sea ice thickness products derived with independent algorithms are used to initialize a coupled ice-ocean modeling system in which a series of reanalysis studies are performed for the period of March 15, 2014–September 30, 2015. Comparisons against moored upward looking sonar, drifting ice mass balance buoy, and NASA Operation IceBridge ice thickness data show that the modeling system exhibits greatly reduced bias using the satellite-derived ice thickness data versus the operational model run without these data. The model initialized with CryoSat-2 ice thickness exhibits skill in simulating ice thickness from the initial period to up to 6 months. We find that the largest improvements in ice thickness occur over multi-year ice. Based on the data periods examined here, we find that for the 18-month study period, when compared with upward looking sonar measurements, the CryoSat-2 reanalyses show significant improvement in bias (0.47–0.75) and RMSE (0.89–1.04) versus the control run without these data (1.44 and 1.60, respectively). An ice drift comparison reveals little change in ice velocity statistics for the Pan Arctic region; however some improvement is seen during the summer/autumn months in 2014 for the Bering/Beaufort/Chukchi and Greenland/Norwegian Seas. These promising results suggest that such a technique should be used to reinitialize operational sea ice modeling systems

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead