A multicenter quality improvement initiative on the impact of pharmacists’ postdischarge follow-up to reduce medication-related acute care episodes

2020 ◽  
Vol 77 (12) ◽  
pp. 938-942
Author(s):  
Lydia Noh ◽  
Kristina Heimerl ◽  
Rita Shane
Keyword(s):  
Quality Improvement ◽  
High Risk ◽  
Acute Care ◽  
Academic Medical Centers ◽  
Quality Improvement Initiative ◽  
Medical Centers ◽  
Academic Medical ◽  
Risk Patients ◽  
The Impact

Abstract Purpose This multicenter quality improvement initiative aims to measure and quantify pharmacists’ impact on reducing medication-related acute care episodes (MACEs) for high-risk patients at an increased risk for readmission due to drug-related problems (DRPs). Methods This was a prospective, multicenter quality improvement initiative conducted at 9 academic medical centers. Each participant implemented a standardized methodology for evaluating MACE likelihood to demonstrate the impact of pharmacist postdischarge follow-up (PDFU). The primary outcome was MACEs prevented, and the secondary outcome was DRPs identified and resolved by pharmacists. During PDFU, pharmacists were responsible for identification and resolution of DRPs, and cases were reviewed by physicians to confirm whether potential MACEs were prevented. Results A total of 840 patients were contacted by 9 participating academic medical centers during a 6-week data collection period. Of these, 328 cases were identified as MACEs prevented during PDFU by pharmacists, and physician reviewers confirmed that pharmacist identification of DRPs during PDFU prevented 27.9% of readmissions. Pharmacist identified 959 DRPs, 2.8% (27) of which were identified as potentially life threatening. Potentially serious or significant DRPs made up 56.6% (543) of the DRPs, and 40.6% (389) were identified as having a low capacity for harm. Conclusion The results demonstrate that PDFU of high-risk patients reduces DRPs and prevents MACEs based on physician confirmation. Implementation of MACE methodology provides health-system pharmacy departments the ability to demonstrate pharmacists’ value in transitions of care and assist in expanding pharmacist services.

scholarly journals Increased Adoption of Quality Improvement Interventions to Implement Evidence-Based Practices for Pressure Ulcer Prevention in U.S. Academic Medical Centers

2015 ◽  
Vol 12 (6) ◽  
pp. 328-336 ◽  
Author(s):  
William V. Padula ◽  
Manish K. Mishra ◽  
Mary Beth F. Makic ◽  
Heidi L. Wald ◽  
Jonathan D. Campbell ◽  
...  
Keyword(s):  
Quality Improvement ◽  
Pressure Ulcer ◽  
Academic Medical Centers ◽  
Evidence Based ◽  
Pressure Ulcer Prevention ◽  
Evidence Based Practices ◽  
Medical Centers ◽  
Academic Medical ◽  
Improvement Interventions ◽  
Quality Improvement Interventions

scholarly journals The impact of the incorporation of a feasible postoperative mortality model at the Post-Anaesthestic Care Unit (PACU) on postoperative clinical deterioration: A pragmatic trial with 5,353 patients

PLoS ONE ◽  
2021 ◽  
Vol 16 (11) ◽  
pp. e0257941
Author(s):  
Claudia de Souza Gutierrez ◽  
Katia Bottega ◽  
Stela Maris de Jezus Castro ◽  
Gabriela Leal Gravina ◽  
Eduardo Kohls Toralles ◽  
...  
Keyword(s):  
Quality Improvement ◽  
High Risk ◽  
Clinical Deterioration ◽  
Surgical Patients ◽  
Predictive Tool ◽  
Postoperative Death ◽  
High Risk Patients ◽  
Death Probability ◽  
Risk Patients ◽  
The Impact

Background Practical use of risk predictive tools and the assessment of their impact on outcome reduction is still a challenge. This pragmatic study of quality improvement (QI) describes the preoperative adoption of a customised postoperative death probability model (SAMPE model) and the evaluation of the impact of a Postoperative Anaesthetic Care Unit (PACU) pathway on the clinical deterioration of high-risk surgical patients. Methods A prospective cohort of 2,533 surgical patients compared with 2,820 historical controls after the adoption of a quality improvement (QI) intervention. We carried out quick postoperative high-risk pathways at PACU when the probability of postoperative death exceeded 5%. As outcome measures, we used the number of rapid response team (RRT) calls within 7 and 30 postoperative days, in-hospital mortality, and non-planned Intensive Care Unit (ICU) admission. Results Not only did the QI succeed in the implementation of a customised risk stratification model, but it also diminished the postoperative deterioration evaluated by RRT calls on very high-risk patients within 30 postoperative days (from 23% before to 14% after the intervention, p = 0.05). We achieved no survival benefits or reduction of non-planned ICU. The small group of high-risk patients (13% of the total) accounted for the highest proportion of RRT calls and postoperative death. Conclusion Employing a risk predictive tool to guide immediate postoperative care may influence postoperative deterioration. It encouraged the design of pragmatic trials focused on feasible, low-technology, and long-term interventions that can be adapted to diverse health systems, especially those that demand more accurate decision making and ask for full engagement in the control of postoperative morbi-mortality.

A Survey of Academic Medical Centers to Distinguish Between Quality Improvement and Research Activities

2006 ◽  
Vol 15 (4) ◽  
pp. 215-220 ◽  
Author(s):  
Nate Johnson ◽  
Lee Vermeulen ◽  
Kelly M. Smith
Keyword(s):  
Quality Improvement ◽  
Academic Medical Centers ◽  
Medical Centers ◽  
Research Activities ◽  
Academic Medical

Graduate Medical Education as the Driver for Quality Improvement and Patient Safety: A National Initiative of Independent Academic Medical Centers

2009 ◽  
Vol 66 (6) ◽  
pp. 336-339 ◽  
Author(s):  
Richard Welling ◽  
Kevin Grannan ◽  
John Boberg ◽  
Kimberly Pierce-Boggs ◽  
Amy Engel
Keyword(s):  
Medical Education ◽  
Patient Safety ◽  
Quality Improvement ◽  
Graduate Medical Education ◽  
Academic Medical Centers ◽  
Graduate Medical ◽  
Medical Centers ◽  
Academic Medical ◽  
National Initiative

scholarly journals Putting veterans with heart failure FIRST improves follow-up and reduces readmissions

2019 ◽  
Vol 8 (1) ◽  
pp. e000386 ◽  
Author(s):  
Serena Michelle Ogunwole ◽  
Jason Phillips ◽  
Amber Gossett ◽  
John Richard Downs
Keyword(s):  
Heart Failure ◽  
High Risk ◽  
Best Practices ◽  
Implementation Strategies ◽  
Quality Improvement Initiative ◽  
Medicine Department ◽  
High Risk Patients ◽  
Resource Limited ◽  
Risk Patients

BackgroundDespite improvements in length of stay and mortality, congestive heart failure (CHF) remains the most common cause of 30-day readmissions to the hospital. Though multiple studies have found that early follow-up after discharge (eg, within 7 days) is critical to improving 30-day readmissions, implementation strategies are challenging in resource-limited settings. Here we present a quality improvement initiative aimed at improving early follow-up while maximising available resources.MethodsThis was a medical resident-driven initiative. A process map of the discharge and follow-up appointment process was created that identified multiple areas for improvement. Based on these findings, a two-part intervention was implemented. First, heart failure discharge education with focus on early follow-up was disseminated to providers throughout the internal medicine department. Subsequently, improved identification of high-risk patients (Failure Intervention Risk StratificationTool) and innovative use of the existing electronic medical record (EMR) were employed to sustain and improve on gains from the first set of interventions.ResultsWe increased our 7-day follow-up rate from 47% to 57% (p=0.429) and decreased the average time to follow-up from 17.6 days to 8.7 days (p=0.016) following the first intervention. The percentage of patients readmitted within 30 days after discharge at baseline (2012–2013) and following the first intervention (education and standardisation of follow-up scheduling) and second intervention (risk stratification, intensive follow-up and EMR change) was 25% and 21%, respectively. Thirty-day mortality rate decreased from 10% in 2011 to 7.16% in December 2015.ConclusionClose hospital discharge follow-up and identification of high-risk patients with CHF are useful approaches to reduce readmissions. Using the existing EMR tool for identifying high-risk patients and improving adherence to best practices is an effective intervention. In patients with CHF these strategies improved time to follow-up and 30-day readmissions while decreasing mortality.

scholarly journals 2389

2017 ◽  
Vol 1 (S1) ◽  
pp. 38-39
Author(s):  
Molly Wasko ◽  
Elaine Morrato ◽  
Nicholas Kenyon ◽  
Suhrud Rajguru ◽  
Bruce Conway ◽  
...  
Keyword(s):  
Best Practices ◽  
Network Capacity ◽  
Lessons Learned ◽  
Academic Medical Centers ◽  
Conference Calls ◽  
Train The Trainer ◽  
Medical Centers ◽  
Academic Medical ◽  
Teaching Team ◽  
The Impact

OBJECTIVES/SPECIFIC AIMS: The goal of this abstract/presentation is to share lessons learned from participation in the NIH SBIR I-Corps Train-The-Trainer Program, discuss our experiences offering programs at our local institutions, and communicate our plans to develop an I-Corps@NCATS program that can be disseminated across the CTSA network. We believe that an I-Corps@NCATS program will enhance the process of scientific translation by taking best practices from NSF I-Corps and adapting the program to meet the needs of biomedical scientists in academic medical centers. By integrating I-Corps@NCATS training, we hypothesize that the clinical and translational investigator base will be better prepared to identify new innovations and to accelerate translation through commercialization. METHODS/STUDY POPULATION: The diverse, interdisciplinary team of investigators involved in this project span 9 CTSA Hubs, including UAB, Rockefeller, UC Denver, HMC-Penn State, UMass, UC Davis, Emory/Georgia Tech, Miami and Michigan. This team was funded by NCATS in 2015–2016 to participate in the CTSA I-Corps Train-The-Trainer Program in conjunction with the NIH-SBIR/STTR I-Corps national program. The goals were to observe the curriculum, interact with and learn from the NSF National Teaching Team and begin implementation of similar programs at our home institutions. Our I-Corps@NCATS team has been holding monthly, and more recently weekly, conference calls to discuss our experiences implementing local programs and to develop a strategy for expanding CTSA offerings that include innovation and entrepreneurship. Our experience revealed several challenges with the existing NSF/NIH I-Corps program offerings: (1) there is no standard curriculum tailored to academic clinical and translational research and biomedical innovations in the life sciences, and (2) the training process to certify instructors in the I-Corps methodology is a much more rigorous and structured process than just observing an I-Corps program (eg, requires mentored training with a national NSF I-Corps trainer). Our team is proposing to address these gaps by taking best practices from NSF I-Corps and adapting the program to create the I-Corps@NCATS Program, tailored to meet the needs of researchers and clinicians in academic medical centers. RESULTS/ANTICIPATED RESULTS: There are 3 primary anticipated results of our project. First, develop a uniform curriculum for the I-Corps@NCATS Program using the National Teaching Team of experts from the NIH’s SBIR I-Corps program. Second, build the I-Corps@NCATS network capacity through a regional Train-The-Trainer Program. Third, develop a set of common metrics to evaluate the effectiveness and impact of the I-Corps@NCATS Program across the community of CTSA Hubs and their respective collaborative networks. DISCUSSION/SIGNIFICANCE OF IMPACT: Over the past 10 years, CTSA Hubs have accelerated science by creating/supporting programs that provide research infrastructure, informatics, pilot funding, education/training, and research navigator services to investigators. These investments help to ensure that we are “doing science right” using the best practices in clinical research. Even so, it is equally important to make investments to ensure that we are “doing the right science.” Are our investigators tackling research problems that our stakeholders, patients, and communities want and need, to make sure that our investments in science have real-world impact? In order to accelerate discoveries toward better health, scientists need to have a better way to understand the needs, wants and desires of the people for whom their research will serve, and how to overcome key obstacles along the path of innovation and commercialization. To fill this gap, we propose that the CTSA Hubs should include in their portfolio of activities a hands-on, lean startup program tailored after the highly successful NSF Innovation Corps (I-Corps) program. We hypothesize that by adapting the NSF I-Corps program to create an I-Corps@NCATS program tailored to medical research, we will better prepare our scientists and engineers to extend their focus beyond the laboratory and broaden the impact of their research. Investigators trained through I-Corps@NCATS are expected to be able to produce more innovative ideas, take a more informed perspective about how to evaluate the clinical and commercial impact of an idea, and quickly prototype and test new solutions in clinical settings.

Survival in Patients with Newly Diagnosed Myeloma Undergoing Therapy with Lenalidomide and Dexamethasone: Impact of High-Risk Cytogenetic Risk Status on Outcome

Blood ◽  
2008 ◽  
Vol 112 (11) ◽  
pp. 95-95 ◽  
Author(s):  
Prashant Kapoor ◽  
Shaji Kumar ◽  
Rafael Fonseca ◽  
Martha Q. Lacy ◽  
Thomas E Witzig ◽  
...  
Keyword(s):  
High Risk ◽  
Risk Stratification ◽  
Plasma Cell ◽  
Risk Groups ◽  
Newly Diagnosed ◽  
High Risk Patients ◽  
Risk Patients ◽  
The Impact ◽  
Standard Risk

Abstract Background: Multiple myeloma (MM) is a heterogeneous disease with very divergent outcomes that are dictated in a large part by specific cytogenetic abnormalities, as well as other prognostic factors such as the proliferative rate of marrow plasma cells. Prognostic systems incorporating these factors have shown clinical utility in identifying high-risk patients, and are increasingly being utilized for treatment decision-making. However, the prognostic relevance of these factors may change with the application of novel therapies. The objective of this study was to determine the impact of risk-stratification (incorporating plasma cell metaphase cytogenetics, interphase fluorescent in-situ hybridization (FISH) and the slide-based plasma cell labeling index (PCLI)) in a cohort of patients with newly diagnosed MM treated initially with lenalidomide + dexamethasone (Rev-Dex). Methods: From March 2004 to November 2007, 100 consecutive patients treated with Rev (25mg/day) on days 1 through 21 of a 4-week cycle in combination with dexamethasone as initial therapy for newly diagnosed myeloma, were identified. High-risk MM was defined as presence of any one or more of the following: hypodiploidy, monoallelic loss of chromosome 13 or its long arm (by metaphase cytogenetics only), deletion of p53 (locus 17p13) or PCLI ≥ 3% or immunoglobulin heavy chain (IgH) translocations, t(4;14) (p16.3;q32) or t(14;16)(q32;q23) on FISH. PFS and OS survival estimates were created using the Kaplan Meier method, and compared by log-rank tests. Results: The median estimated follow-up of the entire cohort (N=100) was 36 months. The median PFS was 31 months; the median OS has not been reached. The 2- and 3-year OS estimates were 93% and 83%, respectively. 16% patients were deemed high-risk by at least one of the 3 tests (cytogenetics, FISH or PCLI). Response rates (PR or better) were 81% versus 89% in the high-risk and standard risk groups, respectively, P=NS; corresponding values for CR plus VGPR rates were 38% and 45% respectively. The median PFS was 18.5 months in high-risk patients compared to 37 months in the standard-risk patients (n=84), P<0.001(Figure). Corresponding values for TTP were 18.5 months and 36.5 months, respectively, P=<0.001. OS was not statistically significant between the two groups; 92% 2-year OS was noted in both the groups. Overall, 95 patients had at least one of the 3 tests to determine risk, while 55 patients could be adequately stratified based on the availability of all the 3 tests, or at least one test result that led to their inclusion in the high-risk category. The significant difference in PFS persisted even when the analysis was restricted to the 55 patients classified using this stringent criterion; 18.5 months vs. 36.5 months in the high-risk and standard- risk groups respectively; P<0.001. In a separate analysis, patients who underwent SCT before the disease progression were censored on the date of SCT to negate its effect, and PFS was still inferior in the high-risk group (p=0.002). Conclusion: The TTP and PFS of high-risk MM patients are inferior to that of the standard-risk patients treated with Rev-Dex, indicating that the current genetic and proliferation-based risk-stratification model remains prognostic with novel therapy. However, the TTP, PFS, and OS obtained in high-risk patients treated with Rev-Dex in this study is comparable to overall results in all myeloma patients reported in recent phase III trials. In addition, no significant impact of high-risk features on OS is apparent so far. Longer follow-up is needed to determine the impact of risk stratification on the OS of patients treated with Rev-Dex. Figure Figure

Learning Collaboratives in Medical Education: Exploring the Impact of Collaboratives’ Structure and Resources and Teams’ Experience

2019 ◽  
Vol 35 (4) ◽  
pp. 297-305
Author(s):  
Robert Dressler ◽  
Hania Janek ◽  
Lauren Sager ◽  
David S. Kountz ◽  
Judi Gravdal
Keyword(s):  
Academic Medical Centers ◽  
Learning Collaborative ◽  
Self Assessment ◽  
Medical Centers ◽  
Academic Medical ◽  
Learning Collaboratives ◽  
National Initiative ◽  
Assessment Survey ◽  
The Impact ◽  
Post Assessment

The Alliance of Independent Academic Medical Centers (AIAMC) organized and coordinated a multicenter learning collaborative, National Initiative V (NI V), focused on community health and health inequity. A pre–post descriptive study was designed to examine the outcomes of the AIAMC NI V. Data were collected from pre- and post-assessment surveys as well as a project milestone self-assessment survey. Twenty-nine institutions participated. By the conclusion of the NI, the majority of institutions had completed at least 1 of the milestones in each of the pre-work/background (65.52%), measurement (62.07%), methods (62.07%), and implement/sustain (20.69%) domains. Institutions reported a significant association between their readiness assessments prior to the start of the NI compared with their status of activities on completion. Milestone achievement is significantly associated with 3 of the assessment items. Learning collaboratives with thoughtfully integrated structure and support can be impactful on topic readiness for the participating organizations.

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