In response to the COVID-19 pandemic, we rapidly implemented a plasma coordination center, within two months, to support transfusion for two outpatient randomized controlled trials. The center design was based on an investigational drug services model and a Food and Drug Administration-compliant database to manage blood product inventory and trial safety.

A core investigational team adapted a cloud-based platform to randomize patient assignments and track inventory distribution of control plasma and high-titer COVID-19 convalescent plasma of different blood groups from 29 donor collection centers directly to blood banks serving 26 transfusion sites.

We performed 1,351 transfusions in 16 months. The transparency of the digital inventory at each site was critical to facilitate qualification, randomization, and overnight shipments of blood group-compatible plasma for transfusions into trial participants. While inventory challenges were heightened with COVID-19 convalescent plasma, the cloud-based system, and the flexible approach of the plasma coordination center staff across the blood bank network enabled decentralized procurement and distribution of investigational products to maintain inventory thresholds and overcome local supply chain restraints at the sites.

The rapid creation of a plasma coordination center for outpatient transfusions is infrequent in the academic setting. Distributing more than 3,100 plasma units to blood banks charged with managing investigational inventory across the U.S. in a decentralized manner posed operational and regulatory challenges while providing opportunities for the plasma coordination center to contribute to research of global importance. This program can serve as a template in subsequent public health emergencies.

The number of patient preference studies in health has increased dramatically. There is growing use of patient preferences in a wide variety of contexts, including health technology assessment. Patient preference studies can help inform decision makers on the needs and priorities of patients and the tradeoffs they are willing to make about health technologies.

This International Society for Pharmacoeconomics and Outcomes Research (ISPOR) Task Force included international experts, health preference researchers and others from diverse backgrounds, including regulatory, health technology assessment, medicine, patient advocacy, and the pharmaceutical industry. The report underwent two rounds of written reviews by ISPOR Preferences Special Interest Group members until a final consensus was reached. The Task Force focused on developing a roadmap that would: (i) apply to the wide variety of preference methods, (ii) identify key domains to guide researchers and other stakeholders in making patient preference studies more useful to decision makers, and (iii) detail important questions to guide researchers conducting preference studies and those critically appraising them.

This Task Force report provides a novel roadmap that invites patient-preference researchers to work with decision makers, patients and other stakeholders to do even more to ensure that studies are useful and impactful. The ISPOR Roadmap consists of five key elements: (i) Context; (ii) Purpose; (iii) Population; (iv) Method; and (v) Impact. In this report, we define these five elements and provide good practices on how patient-preference researchers can actively contribute to increasing the usefulness and impact of patient preference studies in decision-making. We also present a set of key questions that can support researchers and other stakeholders in assessing efforts that promote preference studies’ intended and unintended impact.

This roadmap can help increase the usefulness and impact of patient preference studies in decision-making by challenging researchers to engage and partner with decision makers, patients and others, and together consider the intended and unintended impacts of patient preference studies on decision-making while actively fostering positive impact.

To conduct a process evaluation of a respiratory culture diagnostic stewardship intervention.

Mixed-methods study.

Tertiary-care pediatric intensive care unit (PICU).

Critical care, infectious diseases, and pulmonary attending physicians and fellows; PICU nurse practitioners and hospitalist physicians; pediatric residents; and PICU nurses and respiratory therapists.

This mixed-methods study was conducted concurrently with a diagnostic stewardship intervention to reduce the inappropriate collection of respiratory cultures in mechanically ventilated children. We quantified baseline respiratory culture utilization and indications for ordering using quantitative methods. Semistructured interviews informed by these data and the Consolidated Framework for Implementation Research (CFIR) were then performed, recorded, transcribed, and coded to identify salient themes. Finally, themes identified in these interviews were used to create a cross-sectional survey.

The number of cultures collected per day of service varied between attending physicians (range, 2.2–27 cultures per 100 days). In total, 14 interviews were performed, and 87 clinicians completed the survey (response rate, 47%) and 77 nurses or respiratory therapists completed the survey (response rate, 17%). Clinicians varied in their stated practices regarding culture ordering, and these differences both clustered by specialty and were associated with perceived utility of the respiratory culture. Furthermore, group “default” practices, fear, and hierarchy were drivers of culture orders. Barriers to standardization included fear of a missed diagnosis and tension between practice standardization and individual decision making.

We identified significant variation in utilization and perceptions of respiratory cultures as well as several key barriers to implementation of this diagnostic test stewardship intervention.

To compare the cost and affordability of two fortnightly diets (representing the national guidelines and current consumption) across areas containing Australia’s major supermarkets.

The Healthy Diets Australian Standardised Affordability and Pricing protocol was used.

Price data were collected online and via phone calls in fifty-one urban and inner regional locations across Australia.

Not applicable.

Healthy diets were consistently less expensive than current (unhealthy) diets. Nonetheless, healthy diets would cost 25–26 % of the disposable income for low-income households and 30–31 % of the poverty line. Differences in gross incomes (the most available income metric which overrepresents disposable income) drove national variations in diet affordability (from 14 % of the median gross household incomes in the Australian Capital Territory and Northern Territory to 25 % of the median gross household income in Tasmania).

In Australian cities and regional areas with major supermarkets, access to affordable diets remains problematic for families receiving low incomes. These findings are likely to be exacerbated in outer regional and remote areas (not included in this study). To make healthy diets economically appealing, policies that reduce the (absolute and relative) costs of healthy diets and increase the incomes of Australians living in poverty are required.

To conduct a pilot study implementing combined genomic and epidemiologic surveillance for hospital-acquired multidrug-resistant organisms (MDROs) to predict transmission between patients and to estimate the local burden of MDRO transmission.

Pilot prospective multicenter surveillance study.

The study was conducted in 8 university hospitals (2,800 beds total) in Melbourne, Australia (population 4.8 million), including 4 acute-care, 1 specialist cancer care, and 3 subacute-care hospitals.

All clinical and screening isolates from hospital inpatients (April 24 to June 18, 2017) were collected for 6 MDROs: vanA VRE, MRSA, ESBL Escherichia coli (ESBL-Ec) and Klebsiella pneumoniae (ESBL-Kp), and carbapenem-resistant Pseudomonas aeruginosa (CRPa) and Acinetobacter baumannii (CRAb). Isolates were analyzed and reported as routine by hospital laboratories, underwent whole-genome sequencing at the central laboratory, and were analyzed using open-source bioinformatic tools. MDRO burden and transmission were assessed using combined genomic and epidemiologic data.

In total, 408 isolates were collected from 358 patients; 47.5% were screening isolates. ESBL-Ec was most common (52.5%), then MRSA (21.6%), vanA VRE (15.7%), and ESBL-Kp (7.6%). Most MDROs (88.3%) were isolated from patients with recent healthcare exposure.

Combining genomics and epidemiology identified that at least 27.1% of MDROs were likely acquired in a hospital; most of these transmission events would not have been detected without genomics. The highest proportion of transmission occurred with vanA VRE (88.4% of patients).

Genomic and epidemiologic data from multiple institutions can feasibly be combined prospectively, providing substantial insights into the burden and distribution of MDROs, including in-hospital transmission. This analysis enables infection control teams to target interventions more effectively.

A gap exists between the evidence for reducing risk of knee osteoarthritis (KOA) progression and its application in patients’ daily lives. We aimed to bridge this gap by identifying patient and family physician (FP) self-management priorities to conceptualize and develop a mobile-health application (m-health app). Our co-design approach combined priorities and concerns solicited from patients and FPs with evidence on risk of progression to design and develop a KOA self-management tool.

Parallel qualitative research of patient and FP perspectives was conducted to inform the co-design process. Researchers from the Enhancing Alberta Primary Care Research Networks (EnACT) evaluated the mental models of FPs using cognitive task analysis through structured interviews with four FPs. Using grounded theory methods, patient researchers from the Patient and Community Engagement Research (PaCER) program interviewed five patients to explore their perspectives about needs and interactions within primary care. In three co-design sessions relevant stakeholders (four patients, five FPs, and thirteen researchers) participated to: (i) identify user needs with regard to KOA self-management; and (ii) conceptualize and determine design priorities and functionalities of an m-health app using a modified nominal group process.

Priority measures for symptoms, activities, and quality of life from the user perspective were determined in the first two sessions. The third co-design session with our industry partner resulted in finalization of priorities through interactive patient and FP feedback. The top three features were: (i) a symptoms graph and summary; (ii) information and strategies; and (iii) setting goals. These features were used to inform the development of a minimum viable product.

The novel use of co-design created directive dialog around the needs of patients, highlighting the contrasting views that exist between patients and FPs and emphasizing how exploring these differences might lead to strong design options for patient-oriented m-health apps. Characterizing these disjunctions has important implications for operationalizing patient-centered health care.

Because a majority of urinary tract stones (UTSs) pass spontaneously and clinically significant alternative pathology is rare, we hypothesize that many computed tomographic (CT) scans to diagnose them are likely unnecessary. We sought to measure the impact of renal CT scans on resource use and to justify a prospective study to derive a score that predicts an emergent diagnosis in patients with suspected UTS by doing so in our retrospective series.

We conducted a retrospective study of ED patients who had noncontrast CT of the abdomen for suspected UTS. A split-sample was used to derive and validate a score to predict the presence of an emergent diagnosis on CT.

Of the 2,315 patients (50.8% female, mean age 45 years), 49 (2.1%) had an emergent outcome observed on CT. An additional 12 (0.5%) patients had an urgent outcome and 239 (10.6%) had a urologic procedure within 8 weeks of the CT. Serum white blood cell count, highest temperature, urine red blood cell count, and the presence of abdominal pain were significant predictors of the primary outcome. A score derived using these predictors had a potential range of 22 (0.26% predicted risk, 0.5% actual risk of the outcome) to 6 (52% predicted risk). The score was moderately discriminatory with c-statistics of 0.752 (derivation) and 0.668 (validation) and accurate with Hosmer-Lemeshow statistics of 10.553 (p = 0.228, derivation) and 9.70 (p = 0.286, validation).

A sensible, relevant score derived and validated on all patients presenting with symptoms suggestive of renal colic could be useful in reducing abdominal CT scan ordering.