ABSTRACT Purpose To explore the opioid decision‐making process of prescribers in primary care, surgery, and subspecialty pain management. Methods This was a multistage qualitative‐qualitative study with clinicians involved in opioid prescribing and management from a single healthcare organization with locations in Minnesota, Florida, Arizona, and Wisconsin. Clinicians in this study included physicians, nurse practitioners (NPs), and physician assistants (PAs) practicing in primary care, surgery, or pain medicine. The interview guide was organized in three domains of a conceptual model for opioid use: (1) prescriber characteristics, (2) patient characteristics, and (3) practice environment characteristics. Individual interviews ( N = 20) were performed first, and data were summarized using a rapid template‐based approach. Subsequently, focus groups (FGs) ( N = 4) were conducted with an additional 21 clinicians to confirm and explore interview results. Data from interviews and FGs were analyzed using a common codebook. Results Findings were organized as decision factors into the three domains. Factors in the prescriber domain included characteristics such as formal pain management training, as well as factors that influenced knowledge and beliefs (e.g., advice from or observation of supervising clinicians and expert colleagues). Decision factors in the patient domain included patient pain etiology, comorbid medical or mental health conditions, and demographic characteristics. Clinicians' perceptions of these factors, such as viewing older age as having lesser risk for opioid misuse, influenced prescribing decisions. Clinicians also described challenges associated with “legacy patients” whose therapy was previously managed by a different clinician. Primary care clinicians, in particular, expressed difficulties managing post‐surgical or trauma‐related pain after care transition. Relevant decision factors reported by prescribers in the practice environment domain included guidelines and practice oversight. Most participants reported practicing in an environment that promoted conservative opioid use and having access to standardized institutional guidelines that reduced perceived decision‐making burden. Clinicians described how they used prescribing guidelines to help them communicate with patients about opioid use and prescribing decisions. Conclusions Intersecting prescriber, patient, and practice environment factors shape opioid analgesic prescribing decisions. Available resources in the practice environment, including peer input and institutional guidelines, may support clinician decision‐making and conversations with patients at the point of care, including in cases where patients have complex histories or personal characteristics that influence decision making.
Safety in a hybrid hospital‐at‐home program versus traditional inpatient care: A pragmatic randomized controlled trial
Abstract Background Hospital‐at‐home programs (HaH) in the United States have evolved to include a virtual‐hybrid delivery model, where all physician encounters are virtual and partnered with a home care team. Objective To examine whether a virtual hybrid HaH program enabled by technology has similar clinical outcomes to traditional brick‐and‐mortar (B&M) hospital care. Methods We conducted a pragmatic trial at three hospitals, randomizing 1150 acutely ill patients requiring hospital care between July 10, 2023, and October 31, 2023 one‐to‐one into two groups: intervention (HaH) and control (B&M). The primary analysis was an intention‐to‐treat non‐inferiority analysis of the primary outcome, which was a composite of 30‐day all‐cause mortality and unplanned readmissions. Secondary outcomes included 30‐day readmission, all‐cause mortality, and patient experience. Results The mean age was 67.8 (standard deviation [SD] 16.3) years, and 52.2% were female. The primary outcome occurred in 99 (17.3%) HaH patients and 114 (19.8%) B&M patients (odds ratio [OR] 0.85, 95% confidence interval [CI] 0.63–1.14, p = .28), meeting the non‐inferiority criterion. Thirty‐day unplanned readmission occurred in 84 (14.7%) HaH patients and 101 (17.5%) B&M patients (OR 0.81, 95% CI 0.59–1.11, p = .19). Thirty‐day all‐cause mortality occurred in 25 (4.4%) HaH patients and 19 (3.3%) B&M patients (OR 1.34, 95% CI 0.73–2.46, p = .35). No HaH patients died while receiving their hospital care at home. HaH program was associated with a higher likelihood of patients reporting feeling extremely comfortable or very comfortable (84.4% HaH; 60.9% B&M, p = .001). Conclusion A hybrid HaH model is a safe and comfortable alternative to traditional B&M hospital care.