BACKGROUND: Up to 50% of antibiotic prescriptions for upper respiratory infections (URIs) are inappropriate. Clinical decision support (CDS) systems to mitigate unnecessary antibiotic prescriptions have been implemented into electronic health records, but their use by providers has been limited.
OBJECTIVE: As a delegation protocol, we adapted a validated electronic health record-integrated clinical prediction rule (iCPR) CDS-based intervention for registered nurses (RNs), consisting of triage to identify patients with low-acuity URI followed by CDS-guided RN visits. It was implemented in February 2022 as a randomized controlled stepped-wedge trial in 43 primary and urgent care practices within 4 academic health systems in New York, Wisconsin, and Utah. While issues were pragmatically addressed as they arose, a systematic assessment of the barriers to implementation is needed to better understand and address these barriers.
METHODS: We performed a retrospective case study, collecting quantitative and qualitative data regarding clinical workflows and triage-template use from expert interviews, study surveys, routine check-ins with practice personnel, and chart reviews over the first year of implementation of the iCPR intervention. Guided by the updated CFIR (Consolidated Framework for Implementation Research), we characterized the initial barriers to implementing a URI iCPR intervention for RNs in ambulatory care. CFIR constructs were coded as missing, neutral, weak, or strong implementation factors.
RESULTS: Barriers were identified within all implementation domains. The strongest barriers were found in the outer setting, with those factors trickling down to impact the inner setting. Local conditions driven by COVID-19 served as one of the strongest barriers, impacting attitudes among practice staff and ultimately contributing to a work infrastructure characterized by staff changes, RN shortages and turnover, and competing responsibilities. Policies and laws regarding scope of practice of RNs varied by state and institutional application of those laws, with some allowing more clinical autonomy for RNs. This necessitated different study procedures at each study site to meet practice requirements, increasing innovation complexity. Similarly, institutional policies led to varying levels of compatibility with existing triage, rooming, and documentation workflows. These workflow conflicts were compounded by limited available resources, as well as an implementation climate of optional participation, few participation incentives, and thus low relative priority compared to other clinical duties.
CONCLUSIONS: Both between and within health care systems, significant variability existed in workflows for patient intake and triage. Even in a relatively straightforward clinical workflow, workflow and cultural differences appreciably impacted intervention adoption. Takeaways from this study can be applied to other RN delegation protocol implementations of new and innovative CDS tools within existing workflows to support integration and improve uptake. When implementing a system-wide clinical care intervention, considerations must be made for variability in culture and workflows at the state, health system, practice, and individual levels.
BACKGROUND: ClinicalTrials.gov NCT04255303; https://clinicaltrials.gov/ct2/show/NCT04255303.

BACKGROUND: Warfarin dosing in cardiac surgery patients is complicated by a heightened sensitivity to the drug, predisposing patients to adverse events. Predictive algorithms are therefore needed to guide warfarin dosing in cardiac surgery patients.
OBJECTIVE: This study aimed to develop and validate an algorithm for predicting the warfarin dose needed to attain a therapeutic international normalized ratio (INR) at the time of discharge in cardiac surgery patients.
METHODS: We abstracted variables influencing warfarin dosage from the records of 1031 encounters initiating warfarin between April 1, 2011, and November 29, 2019, at St Michael\'s Hospital in Toronto, Ontario, Canada. We compared the performance of penalized linear regression, k-nearest neighbors, random forest regression, gradient boosting, multivariate adaptive regression splines, and an ensemble model combining the predictions of the 5 regression models. We developed and validated separate models for predicting the warfarin dose required for achieving a discharge INR of 2.0-3.0 in patients undergoing all forms of cardiac surgery except mechanical mitral valve replacement and a discharge INR of 2.5-3.5 in patients receiving a mechanical mitral valve replacement. For the former, we selected 80% of encounters (n=780) who had initiated warfarin during their hospital admission and had achieved a target INR of 2.0-3.0 at the time of discharge as the training cohort. Following 10-fold cross-validation, model accuracy was evaluated in a test cohort comprised solely of cardiac surgery patients. For patients requiring a target INR of 2.5-3.5 (n=165), we used leave-p-out cross-validation (p=3 observations) to estimate model performance. For each approach, we determined the mean absolute error (MAE) and the proportion of predictions within 20% of the true warfarin dose. We retrospectively evaluated the best-performing algorithm in clinical practice by comparing the proportion of cardiovascular surgery patients discharged with a therapeutic INR before (April 2011 and July 2019) and following (September 2021 and May 2, 2022) its implementation in routine care.
RESULTS: Random forest regression was the best-performing model for patients with a target INR of 2.0-3.0, an MAE of 1.13 mg, and 39.5% of predictions of falling within 20% of the actual therapeutic discharge dose. For patients with a target INR of 2.5-3.5, the ensemble model performed best, with an MAE of 1.11 mg and 43.6% of predictions being within 20% of the actual therapeutic discharge dose. The proportion of cardiovascular surgery patients discharged with a therapeutic INR before and following implementation of these algorithms in clinical practice was 47.5% (305/641) and 61.1% (11/18), respectively.
CONCLUSIONS: Machine learning algorithms based on routinely available clinical data can help guide initial warfarin dosing in cardiac surgery patients and optimize the postsurgical anticoagulation of these patients.

Direct oral anticoagulant (DOAC) medications are frequently associated with inappropriate prescribing and adverse events. To improve the safe use of DOACs, health systems are implementing population health tools within their electronic health record (EHR). While EHR informatics tools can help increase awareness of inappropriate prescribing of medications, a lack of empowerment (or insufficient empowerment) of nonphysicians to implement change is a key barrier.
This study examined how the individual authority of clinical pharmacists and anticoagulation nurses is impacted by and changes the implementation success of an EHR DOAC Dashboard for safe DOAC medication prescribing.
We conducted semistructured interviews with pharmacists and nurses following the implementation of the EHR DOAC Dashboard at 3 clinical sites. Interview transcripts were coded according to the key determinants of implementation success. The intersections between individual clinician authority and other determinants were examined to identify themes.
A high level of individual clinician authority was associated with high levels of key facilitators for effective use of the DOAC Dashboard (communication, staffing and work schedule, job satisfaction, and EHR integration). Conversely, a lack of individual authority was often associated with key barriers to effective DOAC Dashboard use. Positive individual authority was sometimes present with a negative example of another determinant, but no evidence was found of individual authority co-occurring with a positive instance of another determinant.
Increased individual clinician authority is a necessary antecedent to the effective implementation of an EHR DOAC Population Management Dashboard and positively affects other aspects of implementation.
RR2-10.1186/s13012-020-01044-5.

BACKGROUND: Nonadherence to pharmaceutical antidepressant treatment is common among patients with depression. Digitalized follow-up (ie, self-monitoring systems through mobile apps) has been suggested as an effective adjunct to conventional antidepressant treatment to increase medical adherence, improve symptoms of depression, and reduce health care resource use.
OBJECTIVE: The aim of this study was to determine patients\' experience of digitalized follow-up using a mobile app as an adjunct to treatment concurrent with a new prescription, a change of antidepressant, or a dose increase.
METHODS: This was a qualitative, descriptive study. Patients at 2 psychiatric outpatient clinics were recruited at the time of changing antidepressant medication. After using a mobile app (either a commercial app or a public app) for 4-6 weeks with daily registrations of active data, such as medical intake and questions concerning general mental health status, individual semistructured interviews were conducted. Recorded data were transcribed and then analyzed using content analysis.
RESULTS: In total, 13 patients completed the study. The mean age was 35 (range 20-67) years, 8 (61.5%) were female, and all reported high digital literacy. Overall, the emerging themes indicated that the patients found the digital app to be a valuable adjunct to antidepressant treatment but with potential for improvement. Both user adherence and medical adherence were positively affected by a daily reminder and the app\'s ease of use. User adherence was negatively affected by the severity of depression. The positive experience of visually presented data as graphs was a key finding, which was beneficial for self-awareness, the patient-physician relationship, and user adherence. Finally, the patients had mixed reactions to the app\'s content and requested tailored content.
CONCLUSIONS: The patients identified several factors addressing both medical adherence and user adherence to a digital app when using it for digitalized follow-up concurrent with the critical time related to changes in antidepressant medication. The findings highlight the need for rigorous evidence-based empirical studies to generate sustainable research results.

State policies can impact opioid prescribing or dispensing. Some state opioid policies have been widely examined in empirical studies, including prescription drug monitoring programs and pain clinic licensure requirements. Other relevant policies might exist that have received limited attention. Our objective was to identify and categorize a wide range of state policies that could affect opioid prescribing/dispensing.
We used stratified random sampling to select 16 states and Washington, DC, for our sample. We collected state regulations and statutes effective during 2020 from each jurisdiction, using search terms related to opioids, pain management, and prescribing/dispensing. We then conducted qualitative template analysis of the data to identify and categorize policy categories.
We identified three dimensions of opioid prescribing/dispensing laws: the prescribing/dispensing rule, its applicability, and its disciplinary consequences. Policy categories of prescribing/dispensing rules included clinic licensure, staff credentials, evaluating the appropriateness of opioids, limiting the initiation of opioids, preventing the diversion or misuse of opioids, and enhancing patient safety. Policy categories related to applicability of the law included the pain type, substance type, practitioner, setting, payer, and prescribing situation. The disciplinary consequences dimension included specific consequences and inspection processes.
Policy categories within each dimension of opioid prescribing/dispensing laws could become a foundation for creating variables to support empirical analyses of policy effects, improving operationalization of policies in empirical studies, and helping to disentangle the effects of multiple state laws enacted at similar times to address the opioid crisis. Several of the policy categories we identified have been underexplored in previous empirical studies.

The purpose of this study is to investigate physicians\' knowledge, attitudes and practice of generic medicine substitutions in China. We conducted a cross-sectional online questionnaire survey on physicians from secondary or tertiary hospitals in China from 2020 December to 2021 April. Descriptive statistical and ordered logistic regression were used for analysis. A total of 1225 physicians were included in the final analysis, and only 330 (26.94%) of them scored 4 or above in the knowledge part, which means that the physicians have a good knowledge of generic substitutions. Of the total, 586 (47.83%) agreed or strongly agreed that generic drugs could be substituted for originator drugs and 585 (47.75%) always or often prescribed generic medicines. The percentage of physicians with a positive attitude toward or that practice prescribing generic medicine is below 50%, which needs to be improved in China. Physicians\' knowledge, their attitude toward generic substitution, if familiar with the policy of generic substitution, and incentives for prescribing generic medicines are influencing factors for the practice of generic substitution. Our studies show that the practice of generic substitution by physicians could be improved by several measures in China. We suggested that the physicians should be taught more about the bulk-buy policy and the generic-originator equivalence evaluation policy. Moreover, government incentives to promote generic substitution should be established. Our study also suggested that physicians with less working experience and female physicians should learn more about generic substitution.

Background: Lasmiditan is a selective serotonin (1F) receptor agonist approved for acute treatment of migraine with 3 doses: 50, 100, and 200 mg.Objective: To help provide dosing insights, we assessed the efficacy and safety of lasmiditan in patients who treated two migraine attacks with the same or different lasmiditan doses.Methods: Integrated analyses used data from the migraine attack treated in either of two controlled, Phase 3, single attack studies (SAMURAI/SPARTAN), and after the first attack treated in the open-label GLADIATOR extension study. Eight patient groups were created based on the initial dose received in SAMURAI or SPARTAN and the subsequent dose in GLADIATOR: placebo-100, placebo-200, 50-100, 50-200, 100-100, 100-200, 200-100, 200-200. Migraine pain freedom, migraine-related functional disability freedom, most bothersome symptom (MBS) freedom, and pain relief were evaluated at 2-h post-dose. The occurrence of most common treatment-emergent adverse events (MC-TEAE) was evaluated. Shift analyses were performed for pain freedom and ≥1 MC-TEAE. The incidence of patients with a specific outcome from the first and subsequent doses were compared within each dose change group using McNemar\'s test.Results: Small, but consistent, increases in incidences of pain freedom, migraine-related functional disability freedom, MBS freedom, and pain relief occurred when the second lasmiditan dose was higher than the initial dose. For patients starting on 50 mg, increasing to 100 or 200 mg provided a positive efficacy-TEAE balance, despite an increase in incidence of ≥1 MC-TEAE. For patients starting on 100 mg, increasing to 200 mg provided a positive efficacy-TEAE balance. If the initial dose was 100 or 200 mg, the incidence of patients experiencing ≥1 MC-TEAE decreased or stayed the same with their subsequent dose, regardless of dose. Decreasing from 200 to 100 mg led to a decrease in patients with pain freedom and ≥1 MC-TEAE, resulting in a neutral efficacy-TEAE balance. Shift analyses supported these findings.Conclusion: A positive efficacy-TEAE balance exists for patients increasing their lasmiditan dose for treatment of a subsequent migraine attack. These results could be important for optimizing dosing for individual patients.Clinicaltrials.gov: SAMURAI (NCT02439320); SPARTAN (NCT02605174); GLADIATOR (NCT02565186).

The penicillins remain the class of antibiotics most commonly prescribed to children worldwide. In an era when the risks posed by antimicrobial resistance are growing, an understanding of antibiotic pharmacology and how to apply these principles in clinical practice is increasingly important. This paper provides an overview of the pharmacology of penicillins, focusing on those aspects of pharmacokinetics, pharmacodynamics and toxicity that are clinically relevant in paediatric prescribing. Penicillin allergy is frequently reported but a detailed history of suspected adverse reactions is essential to identify whether a clinically relevant hypersensitivity reaction is likely or not. The importance of additional factors such as antibiotic palatability, concordance and stewardship are also discussed, highlighting their relevance to optimal prescribing of the penicillins for children.