Hospital-acquired venous thromboembolism (HA VTE) is a preventable complication in hospitalized patients.
We aimed to examine the use of pharmacologic prophylaxis (pPPX) and compare two risk assessment methods for HA VTE: a retrospective electronic Padua Score (ePaduaKP) and admitting clinician's choice of risk within the admission orderset (low, moderate, or high).
We retrospectively analyzed prophylaxis orders for adult medical admissions (2013–2019) at Kaiser Permanente Northern California, excluding surgical and ICU patients.
ePaduaKP was calculated for all admissions. For a subset of these admissions, clinician-assigned HA VTE risk was extracted.
Descriptive pPPX utilization rates between ePaduaKP and clinician-assigned risk as well as concordance between ePaduaKP and clinician-assigned risk.
Among 849,059 encounters, 82.2% were classified as low risk by ePaduaKP, with 42.3% receiving pPPX. In the subset with clinician-assigned risk (608,512 encounters), low and high ePaduaKP encounters were classified as moderate risk in 87.5% and 92.0% of encounters, respectively. Overall, 56.7% of encounters with moderate clinician-assigned risk received pPPX, compared to 7.2% of encounters with low clinician-assigned risk. pPPX use occurred in a large portion of low ePaduaKP risk encounters. Clinicians frequently assigned moderate risk to encounters at admission irrespective of their ePaduaKP risk when retrospectively examined. We hypothesize that the current orderset design may have negatively influenced clinician-assigned risk choice as well as pPPX utilization. Future work should explore optimizing pPPX for high-risk patients only.
Medicare previously announced plans for new billing reforms for inpatient visits that are shared by physicians and advanced practice providers (APPs) whereby the clinician spending the most time on the patient visit would bill for the visit.
To understand how inpatient hospital medicine teams utilize APPs in patient care and how the proposed billing policies might impact future APP utilization.
We conducted focus groups with hospitalist physicians, APPs, and other leaders from 21 academic hospitals across the United States. Utilizing rapid qualitative methods, focus groups were analyzed using a mixed inductive and deductive method at the semantic level with templated summaries and matrix analysis. Thirty-three individuals (physicians [n = 21], APPs [n = 10], practice manager [n = 1], and patient representative [n = 1]) participated in six focus groups.
Four themes emerged from the analysis of the focus groups, including: (1) staffing models with APPs are rapidly evolving, (2) these changes were felt to be driven by staffing shortages, financial models, and governance with minimal consideration to teamwork and relationships, (3) time-based billing was perceived to value tasks over cognitive workload, and (4) that the proposed billing changes may create unintended consequences impacting collaboration and professional satisfaction.
Physician and APP collaborative care models are increasingly evolving to independent visits often driven by workloads, financial drivers, and local regulations such as medical staff rules and hospital bylaws. Understanding which staffing models produce optimal patient, clinician, and organizational outcomes should inform billing policies rather than the reverse.
Scientific writing is a core component of academic hospital medicine, and yet finding time to engage in deeply focused writing is difficult in part due to the highly clinical, 24/7 nature of the specialty that can limit opportunities for writing-focused collaboration and mentorship.
Our objective was to develop and evaluate an academic writing retreat program.
We drafted a set of key retreat features to guide implementation of a 3-day, 2-night retreat program held within a 2 h radius of our hospital. Agendas included writing blocks ranging from 45 to 90 min interspersed with breaks and opportunities for feedback, exercise, and preparing meals together. After each retreat, we distributed an evaluation with multiple choice and free text response options to characterize retreat helpfulness and later gathered data on the status of each paper and grant worked on.
We held 4 retreats between September 2022 and October 2023, engaging 18 faculty and fellows at a cost of $296 per attendee per retreat. In evaluations, nearly 80% reported that the retreat was extremely helpful, and comments praised the highly mentored environment, enriching community of colleagues, and release from commitments that get in the way of writing. Of the 24 papers attendees worked on, 12 have been accepted and 6 are under review. Of the 4 grant proposals, 2 are under review.
We implemented a low-cost, productive writing retreat program that attendees reported was helpful in supporting deep work and represented a meaningful step toward building a community centered around academic writing.
New-onset atrial fibrillation (AF) during sepsis is common, but models designed to stratify stroke risk excluded patients with secondary AF. We assessed the predictive validity of CHA2DS2VASc scores among patients with new-onset AF during sepsis and developed a novel stroke prediction model incorporating presepsis and intrasepsis characteristics.
We included patients ≥40 years old who survived hospitalizations with sepsis and new-onset AF across 21 Kaiser Permanente Northern California hospitals from January 1, 2011 to September 30, 2017. We calculated the area under the receiver operating curve (AUC) for CHA2DS2VASc scores to predict stroke or transient ischemic attack (TIA) within 1 year after a hospitalization with new-onset AF during sepsis using Fine-Gray models with death as competing risk. We similarly derived and validated a novel model using presepsis and intrasepsis characteristics associated with 1-year stroke/TIA risk.
Among 82,748 adults hospitalized with sepsis, 3992 with new-onset AF (median age: 80 years, median CHA2DS2VASc of 4) survived to discharge, among whom 70 (2.1%) experienced stroke or TIA outcome and 1393 (41.0%) died within 1 year of sepsis. The CHA2DS2VASc score was not predictive of stroke risk after sepsis (AUC: 0.50, 95% confidence interval [CI]: 0.48–0.52). A newly derived model among 2555 (64%) patients in the derivation set and 1437 (36%) in the validation set included 13 variables and produced an AUC of 0.61 (0.49–0.73) in derivation and 0.54 (0.43–0.65) in validation.
Current models do not accurately stratify risk of stroke following new-onset AF secondary to sepsis. New tools are required to guide anticoagulation decisions following new-onset AF in sepsis.
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