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OBJECTIVE To evaluate whether computerized provider order entry (CPOE) prompts providing patient- and pathogen-specific MDRO risk estimates could reduce use of empiric extended-spectrum antibiotics for treatment of UTI. DESIGN, SETTING, AND PARTICIPANTS Cluster-randomized trial in 59 US community hospitals comparing the effect of a CPOE stewardship bundle (education, feedback, and real-time and risk-based CPOE prompts; 29 hospitals) vs routine stewardship (n = 30 hospitals) on antibiotic selection during the first 3 hospital days (empiric period) in noncritically ill adults (Ն18 years) hospitalized with UTI with an 18-month baseline (April 1, 2017–September 30, 2018) and 15-month intervention period (April 1, 2019–June 30, 2020). INTERVENTIONS CPOE prompts recommending empiric standard-spectrum antibiotics in patients ordered to receive extended-spectrum antibiotics who have low estimated absolute risk (<10%) of MDRO UTI, coupled with feedback and education. MAIN OUTCOMES AND MEASURES The primary outcome was empiric (first 3 days of hospitalization) extended-spectrum antibiotic days of therapy. Secondary outcomes included empiric vancomycin and antipseudomonal days of therapy. Safety outcomes included days to intensive care unit (ICU) transfer and hospital length of stay. Outcomes were assessed using generalized linear mixed-effect models to assess differences between the baseline and intervention periods. RESULTS Among 127 403 adult patients (71 991 baseline and 55 412 intervention period) admitted with UTI in 59 hospitals, the mean (SD) age was 69.4 (17.9) years, 30.5% were male, and the median Elixhauser Comorbidity Index count was 4 (IQR, 2-5). Compared with routine stewardship, the group using CPOE prompts had a 17.4% (95% CI, 11.2%-23.2%) reduction in empiric extended-spectrum days of therapy (rate ratio, 0.83 [95% CI, 0.77-0.89]; P < .001). The safety outcomes of mean days to ICU transfer (6.6 vs 7.0 days) and hospital length of stay (6.3 vs 6.5 days) did not differ significantly between the routine and intervention groups, respectively. CONCLUSIONS AND RELEVANCE Compared with routine stewardship, CPOE prompts providing real-time recommendations for standard-spectrum antibiotics for patients with low MDRO risk coupled with feedback and education significantly reduced empiric extended-spectrum antibiotic use among noncritically ill adults admitted with UTI without changing hospital length of stay or days to ICU transfers.

Objectives: Current guidelines recommend broad-spectrum antibiotics for high-severity community-ac­ quired pneumonia (CAP), potentially contributing to antimicrobial resistance (AMR). We aim to compare outcomes in CAP patients treated with amoxicillin (narrow-spectrum) versus co-amoxiclav (broad-spec­ trum), to understand if narrow-spectrum antibiotics could be used more widely. Methods: We analysed electronic health records from adults (≥16 y) admitted to hospital with a primary diagnosis of pneumonia between 01-January-2016 and 30-September-2023 in Oxfordshire, United Kingdom. Patients receiving baseline ([−12 h,+24 h] from admission) amoxicillin or co-amoxiclav were included. The association between 30-day all-cause mortality and baseline antibiotic was examined using propensity score (PS) matching and inverse probability treatment weighting (IPTW) to address confounding by baseline characteristics and disease severity. Subgroup analyses by disease severity and sensitivity analyses with missing covariates imputed were also conducted. Results: Among 16,072 admissions with a primary diagnosis of pneumonia, 9685 received either baseline amoxicillin or co-amoxiclav. There was no evidence of a difference in 30-day mortality between patients receiving initial co-amoxiclav vs. amoxicillin (PS matching: marginal odds ratio 0.97 [0.76–1.27], p = 0.61; IPTW: 1.02 [0.78–1.33], p = 0.87). Results remained similar across stratified analyses of mild, moderate, and severe pneumonia. Results were also similar with missing data imputed. There was also no evidence of an association between 30-day mortality and use of additional macrolides or additional doxycycline. Conclusions: There was no evidence of co-amoxiclav being advantageous over amoxicillin for treatment of CAP in 30-day mortality at a population-level, regardless of disease severity. Wider use of narrow-spectrum empirical treatment of moderate/severe CAP should be considered to curb potential for AMR.

Background The lack of interoperability has been a well-recognised limitation associated with the use of electronic health records (EHR). However, less is known about how it manifests for frontline NHS staff when delivering care, how it impacts patient care and what its implications are on care efficiency. Objectives (1) To capture the perceptions of NHS physicians regarding the current state of EHR interoperability, (2) to investigate how poor interoperability affects patient care and safety and (3) to explore the effects it has had on care efficiency in the NHS. Methods An online Qualtrics survey was conducted between June and October 2021 to explore how NHS physicians perceived the present state of interoperability among EHR in service, its effects on patient safety and its impact on care efficiency in NHS healthcare facilities. Recruitment was performed via convenience sampling and snowballing in collaboration with contacts at Health Education England deaneries and the Royal College of General Practitioners. Descriptive statistics were used to report any notable findings observed. Results A total of 636 NHS physicians participated, of which 218 (34.3%) completed the survey fully. Participants reported that EHR interoperability is rudimentary across much of the NHS, with limited ability to read but not edit data from within their organisation. Negative perceptions were most pronounced among specialties in secondary care settings and those with less than 1 year of EHR experience or lower self-reported EHR skills. Limited interoperability prolonged hospital stays, lengthened consultation times and frequently necessitated repeat investigations to be performed. Limited EHR interoperability impaired physician access to clinical data, hampered communication between providers and was perceived to threaten patient safety. Conclusion As healthcare data continues to increase in complexity and volume, EHR interoperability must evolve to accommodate these growing changes and ensure the continued delivery of safe care. The experiences of physicians provide valuable insight into the practical challenges limited interoperability poses and can contribute to future policy solutions to better integrate EHR in the clinical environment.

Many patients experience a fragmented health care journey that involves transitions of care between different hospitals. Ineffective sharing of health data between hospitals can impair the delivery of safe, high‐quality care. This study aimed to identify the unmet need for interhospital data sharing by quantifying the movement of patients between acute hospital trusts and health record systems in the NHS in England., This retrospective observational review examined Hospital Episode Statistics (HES), a national hospital administrative dataset relating to patient encounters with the NHS in England. Outcome measures included the frequency of patient encounters with multiple hospital trusts and the frequency of consecutive encounters with hospitals using different health record systems., All adult patients with inpatient, emergency department, or outpatient encounters at acute hospitals in the NHS in England during the 12‐month period from April 2017 to April 2018 were included., 21,286,873 patients were involved in 121,351,837 encounters at 152 included NHS trusts over the one‐year period. There was limited regional alignment of electronic health record (EHR) systems in the 117 (77.0%) hospital trusts that were using EHR systems. 15,736,863 (73.9%) patients had two or more encounters with the included trusts and 3,931,255 (25.0%) of those attended two or more trusts. Over half (53.6%) of these patients had encounters shared between just 20 pairs of hospitals. Only two of these pairs of trusts used the same EHR system. On 11,017,767 (9.1%) occasions, patients presented to a hospital using a different EHR, or paper record system, to their previous hospital attendance., This study found that nearly four million patients accessed care at two or more different NHS hospital trusts over the one‐year study period, highlighting the demand for effective interhospital data sharing. Most of the pairs of hospital trusts that commonly share patients do not use the same health record systems. The fragmented distribution of health record systems that exists in the NHS in England represents a significant barrier to interhospital data sharing and interoperability., To make informed and safe decisions for patients negotiating increasingly complex health care systems, clinicians need the right information about the right patient in the right place at the right time. The findings from this study provide guidance for policy makers, clinicians, service managers, researchers, software providers, and patients to better understand and improve how data may be shared between hospitals. The methods used in this research could be applied to health care systems in other settings to guide the procurement and coordination of EHR systems to promote interoperability and effective data sharing., National Institute for Health Research (UK).

Antibiotic resistance is prevalent among the bacterial pathogens causing urinary tract infections. However, antimicrobial treatment is often prescribed 'empirically', in the absence of antibiotic susceptibility testing, risking mismatched and therefore ineffective treatment. Here, linking a 10-year longitudinal data set of over 700,000 community-acquired urinary tract infections with over 5,000,000 individually resolved records of antibiotic purchases, we identify strong associations of antibiotic resistance with the demographics, records of past urine cultures and history of drug purchases of the patients. When combined together, these associations allow for machine-learning-based personalized drug-specific predictions of antibiotic resistance, thereby enabling drug-prescribing algorithms that match an antibiotic treatment recommendation to the expected resistance of each sample. Applying these algorithms retrospectively, over a 1-year test period, we find that they greatly reduce the risk of mismatched treatment compared with the current standard of care. The clinical application of such algorithms may help improve the effectiveness of antimicrobial treatments.