Use of the DMAIC Lean Six Sigma quality improvement framework to improve beta-lactam antibiotic adequacy in the critically ill.

Beta-lactam antibiotics are widely used in the intensive care unit due to their favorable effectiveness and safety profiles. Beta-lactams given to patients with sepsis must be delivered as soon as possible after infection recognition (early), treat the suspected organism (appropriate), and be administered at a dose that eradicates the infection (adequate). Early and appropriate antibiotic delivery occurs in >90% of patients, but less than half of patients with sepsis achieve adequate antibiotic exposure. This project aimed to address this quality gap and improve beta-lactam adequacy using the Define, Measure, Analyze, Improve, and Control Lean Six Sigma quality improvement framework. A multidisciplinary steering committee was formed, which completed a stakeholder analysis to define the gap in practice. An Ishikawa cause and effect (Fishbone) diagram was used to identify the root causes and an impact/effort grid facilitated prioritization of interventions. An intervention that included bundled education with the use of therapeutic drug monitoring (TDM; i.e. drug-level testing) was projected to have the highest impact relative to the amount of effort and selected to address beta-lactam inadequacy in the critically ill. The education and TDM intervention were deployed through a Plan, Do, Study, Act cycle. In the 3 months after "go-live," 54 episodes of beta-lactam TDM occurred in 41 unique intensive care unit patients. The primary quality metric of beta-lactam adequacy was achieved in 94% of individuals after the intervention. Ninety-four percent of clinicians gauged the education provided as sufficient. The primary counterbalance of antimicrobial days of therapy, a core antimicrobial stewardship metric, was unchanged over time (favorable result; P = .73). Application of the Define, Measure, Analyze, Improve, and Control Lean Six Sigma quality improvement framework effectively improved beta-lactam adequacy in critically ill patients. The approach taken in this quality improvement project is widely generalizable to other drugs, drug classes, or settings to increase the adequacy of drug exposure.

Evaluating ChatGPT's efficacy in assessing the safety of non-prescription medications and supplements in patients with kidney disease.

Background: This study investigated the efficacy of ChatGPT-3.5 and ChatGPT-4 in assessing drug safety for patients with kidney diseases, comparing their performance to Micromedex, a well-established drug information source. Despite the perception of non-prescription medications and supplements as safe, risks exist, especially for those with kidney issues. The study's goal was to evaluate ChatGPT's versions for their potential in clinical decision-making regarding kidney disease patients. Method: The research involved analyzing 124 common non-prescription medications and supplements using ChatGPT-3.5 and ChatGPT-4 with queries about their safety for people with kidney disease. The AI responses were categorized as "generally safe," "potentially harmful," or "unknown toxicity." Simultaneously, these medications and supplements were assessed in Micromedex using similar categories, allowing for a comparison of the concordance between the two resources. Results: Micromedex identified 85 (68.5%) medications as generally safe, 35 (28.2%) as potentially harmful, and 4 (3.2%) of unknown toxicity. ChatGPT-3.5 identified 89 (71.8%) as generally safe, 11 (8.9%) as potentially harmful, and 24 (19.3%) of unknown toxicity. GPT-4 identified 82 (66.1%) as generally safe, 29 (23.4%) as potentially harmful, and 13 (10.5%) of unknown toxicity. The overall agreement between Micromedex and ChatGPT-3.5 was 64.5% and ChatGPT-4 demonstrated a higher agreement at 81.4%. Notably, ChatGPT-3.5's suboptimal performance was primarily influenced by a lower concordance rate among supplements, standing at 60.3%. This discrepancy could be attributed to the limited data on supplements within ChatGPT-3.5, with supplements constituting 80% of medications identified as unknown. Conclusion: ChatGPT's capabilities in evaluating the safety of non-prescription drugs and supplements for kidney disease patients are modest compared to established drug information resources. Neither ChatGPT-3.5 nor ChatGPT-4 can be currently recommended as reliable drug information sources for this demographic. The results highlight the need for further improvements in the model's accuracy and reliability in the medical domain.

Role of a Pharmacist in Postdischarge Care for Patients With Kidney Disease: A Scoping Review.

OBJECTIVE: The objective was to explore and describe the role of pharmacists in providing postdischarge care to patients with kidney disease. DATA SOURCES: PubMed, Embase (Elsevier), CINAHL (Ebscohost), Web of Science Core Collection, and Scopus were searched on January 30, 2023. Publication date limits were not included. Search terms were identified based on 3 concepts: kidney disease, pharmacy services, and patient discharge. Experimental, quasi-experimental, observational, and qualitative studies, or study protocols, describing the pharmacist's role in providing postdischarge care for patients with kidney disease, excluding kidney transplant recipients, were eligible. STUDY SELECTION AND DATA EXTRACTION: Six unique interventions were described in 10 studies meeting inclusion criteria. DATA SYNTHESIS: Four interventions targeted patients with acute kidney injury (AKI) during hospitalization and 2 evaluated patients with pre-existing chronic kidney disease. Pharmacists were a multidisciplinary care team (MDCT) member in 5 interventions and were the sole provider in 1. Roles commonly identified include medication review, medication reconciliation, medication action plan formation, kidney function assessment, drug dose adjustments, and disease education. Some studies showed improvements in diagnostic coding, laboratory monitoring, medication therapy problem (MTP) resolution, and patient education; prevention of hospital readmission was inconsistent. Limitations include lack of standardized reporting of kidney disease, transitions of care processes, and differences in outcomes evaluated. RELEVANCE TO PATIENT CARE AND CLINICAL PRACTICE: This review identifies potential roles of a pharmacist as part of a postdischarge MDCT for patients with varying degrees of kidney disease. CONCLUSIONS: The pharmacist's role in providing postdischarge care to patients with kidney disease is inconsistent. Multidisciplinary care teams including a pharmacist provided consistent identification and resolution of MTPs, improved patient education, and increased self-awareness of diagnosis.

Drug stewardship in chronic kidney disease to achieve effective and safe medication use.

People living with chronic kidney disease (CKD) often experience multimorbidity and require polypharmacy. Kidney dysfunction can also alter the pharmacokinetics and pharmacodynamics of medications, which can modify their risks and benefits; the extent of these changes is not well understood for all situations or medications. The principle of drug stewardship is aimed at maximizing medication safety and effectiveness in a population of patients through a variety of processes including medication reconciliation, medication selection, dose adjustment, monitoring for effectiveness and safety, and discontinuation (deprescribing) when no longer necessary. This Review is aimed at serving as a resource for achieving optimal drug stewardship for patients with CKD. We describe special considerations for medication use during pregnancy and lactation, during acute illness and in patients with cancer, as well as guidance for the responsible use of over-the-counter drugs, herbal remedies, supplements and sick-day rules. We also highlight inequities in medication access worldwide and suggest policies to improve access to quality and essential medications for all persons with CKD. Further strategies to promote drug stewardship include patient education and engagement, the use of digital health tools, shared decision-making and collaboration within interdisciplinary teams. Throughout, we position the person with CKD at the centre of all drug stewardship efforts.

Determining steady-state trough range in vancomycin drug dosing using machine learning.

BACKGROUND: Vancomycin is a renally eliminated, nephrotoxic, glycopeptide antibiotic with a narrow therapeutic window, widely used in intensive care units (ICU). We aimed to predict the risk of inappropriate vancomycin trough levels and appropriate dosing for each ICU patient. METHODS: Observed vancomycin trough levels were categorized into sub-therapeutic, therapeutic, and supra-therapeutic levels to train and compare different classification models. We included adult ICU patients (≥ 18 years) with at least one vancomycin concentration measurement during hospitalization at Mayo Clinic, Rochester, MN, from January 2007 to December 2017. RESULT: The final cohort consisted of 5337 vancomycin courses. The XGBoost models outperformed other machine learning models with the AUC-ROC of 0.85 and 0.83, specificity of 53% and 47%, and sensitivity of 94% and 94% for sub- and supra-therapeutic categories, respectively. Kinetic estimated glomerular filtration rate and other creatinine-based measurements, vancomycin regimen (dose and interval), comorbidities, body mass index, age, sex, and blood pressure were among the most important variables in the models. CONCLUSION: We developed models to assess the risk of sub- and supra-therapeutic vancomycin trough levels to improve the accuracy of drug dosing in critically ill patients.

Toward Equitable Kidney Function Estimation in Critical Care Practice: Guidance From the Society of Critical Care Medicine's Diversity, Equity, and Inclusion in Renal Clinical Practice Task Force.

OBJECTIVES: Accurate glomerular filtration rate (GFR) assessment is essential in critically ill patients. GFR is often estimated using creatinine-based equations, which require surrogates for muscle mass such as age and sex. Race has also been included in GFR equations, based on the assumption that Black individuals have genetically determined higher muscle mass. However, race-based GFR estimation has been questioned with the recognition that race is a poor surrogate for genetic ancestry, and racial health disparities are driven largely by socioeconomic factors. The American Society of Nephrology and the National Kidney Foundation (ASN/NKF) recommend widespread adoption of new "race-free" creatinine equations, and increased use of cystatin C as a race-agnostic GFR biomarker. DATA SOURCES: Literature review and expert consensus. STUDY SELECTION: English language publications evaluating GFR assessment and racial disparities. DATA EXTRACTION: We provide an overview of the ASN/NKF recommendations. We then apply an Implementation science methodology to identify facilitators and barriers to implementation of the ASN/NKF recommendations into critical care settings and identify evidence-based implementation strategies. Last, we highlight research priorities for advancing GFR estimation in critically ill patients. DATA SYNTHESIS: Implementation of the new creatinine-based GFR equation is facilitated by low cost and relative ease of incorporation into electronic health records. The key barrier to implementation is a lack of direct evidence in critically ill patients. Additional barriers to implementing cystatin C-based GFR estimation include higher cost and lack of test availability in most laboratories. Further, cystatin C concentrations are influenced by inflammation, which complicates interpretation. CONCLUSIONS: The lack of direct evidence in critically ill patients is a key barrier to broad implementation of newly developed "race-free" GFR equations. Additional research evaluating GFR equations in critically ill patients and novel approaches to dynamic kidney function estimation is required to advance equitable GFR assessment in this vulnerable population.

Challenges in the Care of Patients with AKI Receiving Outpatient Dialysis: AKINow Recovery Workgroup Report.

BACKGROUND: Up to one third of survivors of AKI that required dialysis (AKI-D) during hospitalization remain dialysis dependent at hospital discharge. Of these, 20%-60%, depending on the clinical setting, eventually recover enough kidney function to stop dialysis, and the remainder progress to ESKD. METHODS: To describe the challenges facing those still receiving dialysis on discharge, the AKINow Committee conducted a group discussion comprising 59 participants, including physicians, advanced practitioners, nurses, pharmacists, and patients. The discussion was framed by a patient who described gaps in care delivery at different transition points and miscommunication between care team members and the patient. RESULTS: Group discussions collected patient perspectives of ( 1 ) being often scared and uncertain about what is happening to and around them and ( 2 ) the importance of effective and timely communication, a comfortable physical setting, and attentive and caring health care providers for a quality health care experience. Provider perspectives included ( 1 ) the recognition of the lack of evidence-based practices and quality indicators, the significant variability in current care models, and the uncertain reimbursement incentives focused on kidney recovery and ( 2 ) the urgency to address communication barriers among hospital providers and outpatient facilities. CONCLUSIONS: The workgroup identified key areas for future research and policy change to ( 1 ) improve communication among hospital providers, dialysis units, and patients/care partners; ( 2 ) develop tools for risk classification, subphenotyping, and augmented clinical decision support; ( 3 ) improve education to providers, staff, and patients/care partners; ( 4 ) identify best practices to improve relevant outcomes; ( 5 ) validate quality indicators; and ( 6 ) assess the effect of social determinants of health on outcomes. We urge all stakeholders involved in the process of AKI-D care to align goals and work together to fill knowledge gaps and optimize the care to this highly vulnerable patient population.

Development and validation of a model to predict acute kidney injury following high-dose methotrexate in patients with lymphoma.

STUDY OBJECTIVE: To develop and validate a model for predicting acute kidney injury (AKI) after high-dose methotrexate (HDMTX) exposure. DESIGN: Retrospective analysis. SETTING: Multisite integrated health system throughout Minnesota and Wisconsin. PATIENTS: Adult patients with lymphoma who received HDMTX as a 4-h infusion. MEASUREMENTS AND MAIN RESULTS: LASSO methodology was used to identify factors available at the outset of therapy that predicted incident AKI within 7 days following HDMTX. The model was then validated in an independent cohort. The incidence of AKI within 7 days following HDMTX was 21.6% (95% confidence interval (CI) 18.4%-24.8%) in the derivation cohort (435 unique patients who received a total of 1642 doses of HDMTX) and 15.6% (95% CI 5.3%-24.8%) in the validation cohort (55 unique patients who received a total of 247 doses of HDMTX). Factors significantly associated with AKI after HDMTX in the multivariable model included age ≥ 55 years, male sex, and lower HDMTX dose number. Other factors that were not found to be significantly associated with AKI on multivariable analysis, but were included in the final model, were body surface area, Charlson Comorbidity Index, and estimated glomerular filtration rate. The c-statistic of the model was 0.72 (95% CI 0.69-0.75) in the derivation cohort and 0.72 (95% CI 0.60-0.84) in the validation cohort. CONCLUSION: This model utilizing identified sociodemographic and clinical factors is predictive of AKI following HDMTX administration in adult patients with lymphoma.

Early machine learning prediction of hospitalized patients at low risk of respiratory deterioration or mortality in community-acquired pneumonia: Derivation and validation of a multivariable model.

Current prognostic tools for pneumonia predominantly focus on mortality, often neglecting other crucial outcomes such as the need for advanced respiratory support. The objective of this study was to develop and validate a tool that predicts the early risk of non-occurrence of respiratory deterioration or mortality. We conducted a single-center, retrospective cohort study involving hospitalized adult patients with community-acquired pneumonia (CAP) and acute hypoxic respiratory failure from January 2009 to December 2019 (n = 4379). We employed the gradient boosting machine (GBM) learning to create a model that estimates the likelihood of patients requiring advanced respiratory support (high flow nasal cannula [HFNC], non-invasive mechanical ventilation [NIMV], and invasive mechanical ventilation [IMV]) or facing mortality during hospitalization. This model utilized readily available data including demographic, physiologic, and laboratory data, sourced from electronic health records and obtained within the first six hours of admission. Out of the cohort, 890 patients (25.2%) either required advanced respiratory support or died during their hospital stay. Our predictive model displayed superior discrimination and higher sensitivity (cross-validation C-statistic = 0.71; specificity = 0.56; sensitivity = 0.72) compared to the pneumonia severity index (PSI) (C-statistic = 0.65; specificity = 0.91; sensitivity = 0.24; P value < 0.001), while maintaining a negative predictive value (NPV) of approximately 0.85. These data demonstrate that our machine learning model predicted the non-occurrence of respiratory deterioration or mortality among hospitalized CAP patients more accurately than the PSI. The enhanced sensitivity of this model holds potential for reliably excluding low-risk patients from pneumonia clinical trials.

Optimum Care of AKI Survivors Not Requiring Dialysis after Discharge: An AKINow Recovery Workgroup Report.

AKI survivors experience gaps in care that contribute to worse outcomes, experience, and cost.Challenges to optimal care include issues with information transfer, education, collaborative care, and use of digital health tools.Research is needed to study these challenges and inform optimal use of diagnostic and therapeutic interventions to promote recovery AKI affects one in five hospitalized patients and is associated with poor short-term and long-term clinical and patient-centered outcomes. Among those who survive to discharge, significant gaps in documentation, education, communication, and follow-up have been observed. The American Society of Nephrology established the AKINow taskforce to address these gaps and improve AKI care. The AKINow Recovery workgroup convened two focus groups, one each focused on dialysis-independent and dialysis-requiring AKI, to summarize the key considerations, challenges, and opportunities in the care of AKI survivors. This article highlights the discussion surrounding care of AKI survivors discharged without the need for dialysis. On May 3, 2022, 48 patients and multidisciplinary clinicians from diverse settings were gathered virtually. The agenda included a patient testimonial, plenary sessions, facilitated small group discussions, and debriefing. Core challenges and opportunities for AKI care identified were in the domains of transitions of care, education, collaborative care delivery, diagnostic and therapeutic interventions, and digital health applications. Integrated multispecialty care delivery was identified as one of the greatest challenges to AKI survivor care. Adequate templates for communication and documentation; education of patients, care partners, and clinicians about AKI; and a well-coordinated multidisciplinary posthospital follow-up plan form the basis for a successful care transition at hospital discharge. The AKINow Recovery workgroup concluded that advancements in evidence-based, patient-centered care of AKI survivors are needed to improve health outcomes, care quality, and patient and provider experience. Tools are being developed by the AKINow Recovery workgroup for use at the hospital discharge to facilitate care continuity.

Impact of Various Estimated Glomerular Filtration Rate Equations on the Pharmacokinetics of Meropenem in Critically Ill Adults.

IMPORTANCE: Meropenem dosing is typically guided by creatinine-based estimated glomerular filtration rate (eGFR), but creatinine is a suboptimal GFR marker in the critically ill. OBJECTIVES: This study aimed to develop and qualify a population pharmacokinetic model for meropenem in critically ill adults and to determine which eGFR equation based on creatinine, cystatin C, or both biomarkers best improves model performance. DESIGN SETTING AND PARTICIPANTS: This single-center study evaluated adults hospitalized in an ICU who received IV meropenem from 2018 to 2022. Patients were excluded if they had acute kidney injury, were on kidney replacement therapy, or were treated with extracorporeal membrane oxygenation. Two cohorts were used for population pharmacokinetic modeling: a richly sampled development cohort (n = 19) and an opportunistically sampled qualification cohort (n = 32). MAIN OUTCOMES AND MEASURES: A nonlinear mixed-effects model was developed using parametric methods to estimate meropenem serum concentrations. RESULTS: The best-fit structural model in the richly sampled development cohort was a two-compartment model with first-order elimination. The final model included time-dependent weight normalized to a 70-kg adult as a covariate for volume of distribution (Vd) and time-dependent eGFR for clearance. Among the eGFR equations evaluated, eGFR based on creatinine and cystatin C expressed in mL/min best-predicted meropenem clearance. The mean (se) Vd in the final model was 18.2 (3.5) liters and clearance was 11.5 (1.3) L/hr. Using the development cohort as the Bayesian prior, the opportunistically sampled cohort demonstrated good accuracy and low bias. CONCLUSIONS AND RELEVANCE: Contemporary eGFR equations that use both creatinine and cystatin C improved meropenem population pharmacokinetic model performance compared with creatinine-only or cystatin C-only eGFR equations in adult critically ill patients.

Posthospital Multidisciplinary Care for AKI Survivors: A Feasibility Pilot.

Rationale & Objective: Innovative models are needed to address significant gaps in kidney care follow-up for acute kidney injury (AKI) survivors. Study Design: This quasi-experimental pilot study reports the feasibility of the AKI in Care Transitions (ACT) program, a multidisciplinary approach to AKI survivor care based in the primary care setting. Setting & Participants: The study included consenting adults with stage 3 AKI discharged home without dialysis. Interventions: The ACT intervention included predischarge education from nurses and coordinated postdischarge follow-up with a primary care provider and pharmacist within 14 days. ACT was implemented in phases (Usual Care, Education, ACT). Outcomes: The primary outcome was feasibility. Secondary outcomes included process and clinical outcomes. Results: In total, 46 of 110 eligible adults were enrolled. Education occurred in 18/18 and 14/15 participants in the Education and ACT groups, respectively. 30-day urine protein evaluation occurred in 15%, 28%, and 87% of the Usual Care, Education, and ACT groups, respectively (P < 0.001). Cumulative incidence of provider (primary care or nephrologist) and laboratory follow-up at 14 and 30 days was different across groups (14 days: Usual care 0%, Education 11%, ACT 73% [P < 0.01]; 30 days: 0%, 22%, and 73% [P < 0.01]). 30-day readmission rates were 23%, 44%, and 13% in the Usual Care, Education, and ACT groups, respectively (P = 0.13). Limitations: Patients were not randomly assigned to treatment groups. The sample size limited the ability to detect some differences or perform multivariable analysis. Conclusions: This study demonstrated the feasibility of multidisciplinary AKI survivor follow-up beginning in primary care. We observed a higher cumulative incidence of laboratory and provider follow-up in ACT participants. Trial Registration: ClinicalTrials.gov (NCT04505891). Plain-Language Summary: Abrupt loss of kidney function in hospitalized patients, acute kidney injury (AKI), increases the chances of long-term kidney disease and a worse health care experience for patients. One out of 3 people who experience AKI do not get the follow-up kidney care they need. We performed a pilot study to test whether a program that facilitates structured AKI follow-up in primary care called the AKI in Care Transitions (ACT) program was possible. ACT brings together the unique expertise of nurses, doctors, and pharmacists to look at the patient's kidney health plan from all angles. The study found that the ACT program was possible and led to more complete kidney care follow-up after discharge than the normal approach to care.

Moving toward a contemporary classification of drug-induced kidney disease.

Drug-induced kidney disease (DIKD) accounts for about one-fourth of all cases of acute kidney injury (AKI) in hospitalized patients, especially in critically ill setting. There is no standard definition or classification system of DIKD. To address this, a phenotype definition of DIKD using expert consensus was introduced in 2015. Recently, a novel framework for DIKD classification was proposed that incorporated functional change and tissue damage biomarkers. Medications were stratified into four categories, including "dysfunction without damage," "damage without dysfunction," "both dysfunction and damage," and "neither dysfunction nor damage" using this novel framework along with predominant mechanism(s) of nephrotoxicity for drugs and drug classes. Here, we briefly describe mechanisms and provide examples of drugs/drug classes related to the categories in the proposed framework. In addition, the possible movement of a patient's kidney disease between certain categories in specific conditions is considered. Finally, opportunities and barriers to adoption of this framework for DIKD classification in real clinical practice are discussed. This new classification system allows congruencies for DIKD with the proposed categorization of AKI, offering clarity as well as consistency for clinicians and researchers.

Population pharmacokinetic model of cefepime for critically ill adults: a comparative assessment of eGFR equations.

Cefepime exhibits highly variable pharmacokinetics in critically ill patients. The purpose of this study was to develop and qualify a population pharmacokinetic model for use in the critically ill and investigate the impact of various estimated glomerular filtration rate (eGFR) equations using creatinine, cystatin C, or both on model parameters. This was a prospective study of critically ill adults hospitalized at an academic medical center treated with intravenous cefepime. Individuals with acute kidney injury or on kidney replacement therapy or extracorporeal membrane oxygenation were excluded. A nonlinear mixed-effects population pharmacokinetic model was developed using data collected from 2018 to 2022. The 120 included individuals contributed 379 serum samples for analysis. A two-compartment pharmacokinetic model with first-order elimination best described the data. The population mean parameters (standard error) in the final model were 7.84 (0.24) L/h for CL1 and 15.6 (1.45) L for V1. Q was fixed at 7.09 L/h and V2 was fixed at 10.6 L, due to low observed interindividual variation in these parameters. The final model included weight as a covariate for volume of distribution and the eGFRcr-cysC (mL/min) as a predictor of drug clearance. In summary, a population pharmacokinetic model for cefepime was created for critically ill adults. The study demonstrated the importance of cystatin C to prediction of cefepime clearance. Cefepime dosing models which use an eGFR equation inclusive of cystatin C are likely to exhibit improved accuracy and precision compared to dosing models which incorporate an eGFR equation with only creatinine.

The Quality of Discharge Summaries After Acute Kidney Injury.

Background: Acute kidney injury (AKI) increases the risk of hospital readmission, chronic kidney disease, and death. Therefore, effective communication in discharge summaries is essential for safe transitions of care. Objective: The objectives of this study were to determine the quality of discharge summaries in AKI survivors and identify predictors of higher quality discharge summaries. Design: Retrospective chart review. Setting: Tertiary care academic center in Ontario, Canada. Patients: We examined the discharge summary quality of 300 randomly selected adult patients who survived a hospitalization with AKI at our tertiary care hospital, stratified by AKI severity. We included 150 patients each from 2015 to 2016 and 2018 to 2019, before and after introduction of a post-AKI clinic in 2017. Measurements: We reviewed charts for 9 elements of AKI care to create a composite score summarizing discharge summary quality. Methods: We used multivariable logistic regression to identify predictors of discharge summary quality. Results: The median discharge summary composite score was 4/9 (interquartile range, 2-6). The least frequently mentioned elements were baseline creatinine (n = 55, 18%), AKI-specific follow-up labs (n = 66, 22%), and medication recommendations (n = 80, 27%). The odds of having a higher quality discharge summary (composite score ≥4/9) was greater for every increase in baseline creatinine of 25 µmol/L (adjusted odds ratio [aOR]: 1.27; 95% confidence interval [CI]: 1.03, 1.56), intrarenal etiology (aOR: 2.32; 95% CI: 1.26, 4.27), and increased AKI severity (stage 2 aOR: 2.57; 95% CI: 1.35, 4.91 and stage 3 aOR: 3.36; 95% CI: 1.56, 7.22). There was no association between discharge summary quality and the years before and after introduction of a post-AKI clinic (aOR: 0.77; 95% CI: 0.46, 1.29). Limitations: The single-center study design limits generalizability. Conclusions: Most discharge summaries are missing key AKI elements, even in patients with severe AKI. These gaps suggest several opportunities exist to improve discharge summary communication following AKI.

Contexte: L'insuffisance rénale aiguë (IRA) augmente le risque de réadmission à l'hôpital, d'insuffisance rénale chronique et de décès. Une communication efficace est essentielle dans le résumé de départ pour assurer une transition sécuritaire des soins. Objectifs: Cette étude visait à évaluer la qualité des résumés de départ des survivants d'un épisode d'IRA et à identifier les facteurs prédictifs d'un résumé de départ de meilleure qualité. Conception: Examen rétrospectif des dossiers médicaux. Cadre: Un centre universitaire de soins tertiaires d'Ottawa (Ontario) au Canada. Sujets: Nous avons examiné la qualité du résumé de départ de 300 patients adultes ayant survécu à une hospitalisation pour IRA dans notre hôpital de soins tertiaires. Les patients ont été sélectionnés au hasard et stratifiés selon la gravité de l'IRA. Nous avons retenu 150 patients pour la période 2015-2016 et 150 patients pour la période 2018-2019; soit les périodes précédant et suivant l'introduction d'une clinique post-IRA en 2017. Mesures: Nous avons examiné les dossiers médicaux à la recherche de neuf éléments des soins d'IRA afin de créer un score composite évaluant la qualité du résumé de départ. Méthodologie: La régression logistique multivariée a été employée pour identifier les facteurs prédictifs de la qualité d'un résumé de départ. Résultats: Le score composite médian était de 4/9 (intervalle interquartile: 2-6). Les éléments les moins souvent mentionnés dans le résumé de départ étaient le taux de créatinine initial (n= 55; 18 %), les analyses de laboratoires liées spécifiquement au suivi de l'IRA (n= 66; 22 %) et les recommandations portant sur la médication (n= 80; 27 %). Les probabilités d'avoir un résumé de départ de qualité supérieure (score composite ≥4/9) étaient plus élevées pour chaque augmentation de 25 µmol/L de la créatinine initiale (RC corrigé [RCc] = 1,27; IC 95: 1,03-1,56), lorsque l'étiologie était intrarénale (RCc: 2,32; IC 95: 1,26-4,27) et la gravité de l'IRA accrue ([stade 2] RCc: 2,57; IC 95: 1,35-4,91; et [stade 3] RCc: 3,36; IC 95: 1,56-7,22). Aucune association n'a été observée entre la qualité du résumé de départ et la période étudiée, soit avant ou après l'introduction de la clinique post-IRA (RCc: 0,77; IC 95: 0,46-1,29). Limites: L'étude est monocentrique, ce qui limite la généralisabilité des résultats. Conclusion: Certains éléments clés des soins de l'IRA étaient absents de la plupart des résumés de départ, même chez les patients gravement atteints d'IRA. Ces lacunes indiquent qu'il est possible d'améliorer la communication du résumé de départ à la suite d'un épisode d'IRA.

'How to' Guide for Pharmacist-led Implementation of Beta-Lactam Therapeutic Drug Monitoring in the Critically Ill.

Beta-lactam therapeutic drug monitoring (TDM) can improve precision dosing and clinical outcomes in critically ill patients, but has not been implemented widely in the United States. Mayo Clinic recently implemented a beta-lactam TDM program. This single-center experience forms the basis of the manuscript which outlines practical considerations involved with implementation, including the pharmacist's role as a leader. Our implementation effort focused on three primary domains. First, we aimed to ensure a supportive organizational infrastructure. Early leadership engagement by the pharmacist-led core team facilitated advocacy for the clinical need, allocation of resources, and assay development. Second, core clinical workflows were developed that addressed the preferred patient population for use, desirable pharmacokinetic and pharmacodynamic targets, and the preferred sampling strategy. Clinical tools to guide pharmacists in interpreting the results (e.g., pharmacokinetics calculator) and documenting decisions were developed. Third, stakeholders were offered repeated exposure to evidence and expertise to facilitate understanding and application of the new practice. This act of 'individual internalization' seems to be uniquely important to beta-lactam TDM implementation compared with implementation of other antimicrobial TDM programs. Educational strategies and supportive materials that were developed were focused on providing substantive and varied information tailored to the stakeholders' role in the process. For pharmacists, this included both clinical and operational considerations. A continuous improvement plan to support management of the process was instituted to address necessary updates and changes that inevitably emerged. In summary, the described approach to implementation of a pharmacist led beta-lactam TDM program could be used as a roadmap to aid other institutions that aim to develop such a program.

Digital health and acute kidney injury: consensus report of the 27th Acute Disease Quality Initiative workgroup.

Acute kidney injury (AKI), which is a common complication of acute illnesses, affects the health of individuals in community, acute care and post-acute care settings. Although the recognition, prevention and management of AKI has advanced over the past decades, its incidence and related morbidity, mortality and health care burden remain overwhelming. The rapid growth of digital technologies has provided a new platform to improve patient care, and reports show demonstrable benefits in care processes and, in some instances, in patient outcomes. However, despite great progress, the potential benefits of using digital technology to manage AKI has not yet been fully explored or implemented in clinical practice. Digital health studies in AKI have shown variable evidence of benefits, and the digital divide means that access to digital technologies is not equitable. Upstream research and development costs, limited stakeholder participation and acceptance, and poor scalability of digital health solutions have hindered their widespread implementation and use. Here, we provide recommendations from the Acute Disease Quality Initiative consensus meeting, which involved experts in adult and paediatric nephrology, critical care, pharmacy and data science, at which the use of digital health for risk prediction, prevention, identification and management of AKI and its consequences was discussed.

Discrepancy between perceptions and acceptance of clinical decision support Systems: implementation of artificial intelligence for vancomycin dosing.

BACKGROUND: Artificial intelligence (AI) tools are more effective if accepted by clinicians. We developed an AI-based clinical decision support system (CDSS) to facilitate vancomycin dosing. This qualitative study assesses clinicians' perceptions regarding CDSS implementation. METHODS: Thirteen semi-structured interviews were conducted with critical care pharmacists, at Mayo Clinic (Rochester, MN), from March through April 2020. Eight clinical cases were discussed with each pharmacist (N = 104). Following initial responses, we revealed the CDSS recommendations to assess participants' reactions and feedback. Interviews were audio-recorded, transcribed, and summarized. RESULTS: The participants reported considerable time and effort invested daily in individualizing vancomycin therapy for hospitalized patients. Most pharmacists agreed that such a CDSS could favorably affect (N = 8, 62%) or enhance (9, 69%) their ability to make vancomycin dosing decisions. In case-based evaluations, pharmacists' empiric doses differed from the CDSS recommendation in most cases (88/104, 85%). Following revealing the CDSS recommendations, we noted 78% (69/88) discrepant doses. In discrepant cases, pharmacists indicated they would not alter their recommendations. The reasons for declining the CDSS recommendation were general distrust of CDSS, lack of dynamic evaluation and in-depth analysis, inability to integrate all clinical data, and lack of a risk index. CONCLUSION: While pharmacists acknowledged enthusiasm about the advantages of AI-based models to improve drug dosing, they were reluctant to integrate the tool into clinical practice. Additional research is necessary to determine the optimal approach to implementing CDSS at the point of care acceptable to clinicians and effective at improving patient outcomes.

Development and Implementation of an Acute Kidney Injury Remote Patient Monitoring Program: Research Letter.

Acute kidney injury (AKI) survivors have a dynamic posthospital course which warrants close monitoring. Remote patient monitoring (RPM) could be used to improve quality and efficiency of AKI survivor care. Objective: The objective of this report was to describe the development and preliminary feasibility of an AKI RPM program launched in October 2021. Setting: Academic medical center. Patients: Patients enrolled in the AKI RPM program were those who experienced AKI during a hospitalization and underwent nephrology consultation. Measurements/Methods: At enrollment, patients were provided with home monitoring technology and underwent weekly laboratory assessments. Nurses evaluated the data daily and adhered to prespecified protocols for management and escalation of care if needed. Results: Twenty patients were enrolled in AKI RPM in the first 5 months. Median duration of program participation was 36 (31, 40) days. Eight patients (40%) experienced an unplanned readmission, or an emergency department visit, half (N = 4) of which were attributed to AKI and related circumstances. Of the 9 postgraduation survey respondents, all were satisfied with the RPM program and 89% would recommend RPM to other patients with similar health conditions. Limitations: Acute kidney injury RPM was made possible by the existing infrastructure in our integrated health system and the robust resources available in the Mayo Clinic Center for Digital Health. Such infrastructure may not be universally available which could limit scale and generalizability of such a program. Conclusions: Remote patient monitoring can offer a unique opportunity to bridge the care transition from hospital to home and increase access to quality care for the AKI survivors.

Les survivants d'un épisode d'insuffisance rénale aiguë (IRA) ont un parcours post-hospitalier dynamique qui justifie une surveillance étroite. La télésurveillance des patients (TSP) pourrait être employée pour améliorer la qualité et l'efficacité des soins pour les survivants de l'IRA. Objectif: L'objectif de ce rapport était de décrire le développement et la faisabilité préliminaire d'un programme de TSP-IRA (télésurveillance des patients atteints d'IRA) en octobre 2021. Cadre: Centre médical universitaire. Sujets: Les patients inscrits au programme de TSP-IRA étaient des patients qui avaient vécu un épisode d'IRA lors d'une hospitalisation et obtenu une consultation en néphrologie. Mesures et méthodologie: Au moment de l'inclusion, les patients ont reçu un dispositif de surveillance à domicile et se sont soumis à des évaluations de laboratoire hebdomadaires. Les infirmières ont évalué les données quotidiennement et ont respecté des protocoles prédéfinis pour la gestion et l'escalade des soins si nécessaire. Résultats: Vingt patients ont été inclus dans le programme de TSP-IRA au cours des cinq premiers mois. La durée médiane de participation au programme était de 36 (31, 40) jours. Huit patients (40%) ont dû être réadmis de façon non planifiée ou ont dû faire une visite aux urgences; pour la moitié d'entre eux (N = 4) en raison de l'IRA et de circonstances connexes. Parmi les neuf répondants qui ont répondu au sondage à la complétion du programme, tous se sont dits satisfaits du programme de TSP et 89% le recommanderaient à d'autres patients ayant des problèmes de santé similaires. Limites: Le programme de TSP-IRA a été rendu possible grâce à l'infrastructure existante dans notre système de santé intégré et aux ressources robustes disponibles au Mayo Clinic Center for Digital Health. Une telle infrastructure n'est peut-être pas universellement disponible, ce qui pourrait limiter l'ampleur et la généralisabilité d'un tel programme. Conclusion: La TSP peut offrir une occasion unique de faciliter la transition des soins entre l'hôpital et le domicile et d'accroître l'accès à des soins de qualité pour les survivants d'un épisode d'IRA.