Closing the Loop: Re-engineering the Assessment and Tracking of Symptoms in Primary Care.

Reliable systems that track the continuation, progression, or resolution of a patient's symptoms over time are essential for reliable diagnosis and ensuring that patients harboring more worrisome diagnoses are safely followed up. Given their first-contact role and increasing stresses on busy primary care clinicians and practices, new processes that make these tasks easier rather than creating more work for busy clinicians are especially needed.Some symptoms are sufficiently worrisome that they demand an urgent diagnosis and treatment while others result in a differential that can be more safely explored over time, or less differentiated and worrisome that they are best managed with the "test of time" to see if they resolve, worsen, or evolve into symptoms that are more worrisome. Regardless, it is essential that clinicians are able to reliably track symptoms over time, yet this capacity is rarely available or explicit. Working with systems engineers, we are developing prototypes for such systems and are working on their implementation and evaluation. In this commentary, we describe approaches to this essential, but underappreciated, problem in primary care.

Completion Rates and Timeliness of Diagnostic Colonoscopies for Rectal Bleeding in Primary Care.

BACKGROUND: Rectal bleeding is the most common presenting symptom of colorectal cancer, and guidelines recommend timely follow-up, usually with colonoscopy to ensure timely diagnoses of colorectal cancer. OBJECTIVE: Identify loop closure rates and vulnerable process points for patients with rectal bleeding. DESIGN: Retrospective cohort study, using medical record review of patients aged ≥ 40 with index diagnosis of rectal bleeding at 2 primary practices-an urban academic practice and affiliated community health center, between January 1, 2018, and December 31, 2020. Patients were classified as having completed recommended follow-up workup ("closed loop") vs. not ("open loop"). Open loop patient cases were categorized into six types of process failures. PARTICIPANTS: A total of 837 patients had coded diagnoses of rectal bleeding within study window. Sixty-seven were excluded based on prior colectomy, clinical presentation more consistent with upper GI bleed, no rectal bleeding documented on chart review, or expired during the follow-up period, leaving 770 patients included. MAIN MEASURES: Primary outcomes were percentages of patient cases classified as "open loops" and distribution of these cases into six categories of process failure that were identified. KEY RESULTS: 22.3% of patients (N = 172) failed to undergo timely recommended workup for rectal bleeding. Largest failure categories were patients for whom no procedure was ordered (N = 62, 36%), followed by patients with procedures ordered but never scheduled (N = 44, 26%) or scheduled but subsequently cancelled or not kept (N = 31, 18%). While open loops increased after the onset of the COVID-19 pandemic, this difference was not significant within our study period. CONCLUSIONS: Significant numbers of patients presenting to primary care with rectal bleeding fail to undergo recommended workup. The majority either have no procedure ordered, or procedure ordered but never scheduled or cancelled and not kept, suggesting these are important failure modes to target in future interventions. Ensuring reliable ordering and processes for timely scheduling and completion of procedures represent critical areas for improving the diagnostic process for patients with rectal bleeding in primary care.

Evaluating a patient safety learning laboratory to create an interdisciplinary ecosystem for health care innovation.

BACKGROUND: In response to the complexity, challenges, and slow pace of innovation, health care organizations are adopting interdisciplinary team approaches. Systems engineering, which is oriented to creating new, scalable processes that perform with higher reliability and lower costs, holds promise for driving innovation in the face of challenges to team performance. A patient safety learning laboratory (lab) can be an essential aspect of fostering interdisciplinary team innovation across multiple projects and organizations by creating an ecosystem focused on deploying systems engineering methods to accomplish process redesign. PURPOSE: We sought to identify the role and activities of a learning ecosystem that support interdisciplinary team innovation through evaluation of a patient safety learning lab. METHODS: Our study included three participating learning lab project teams. We applied a mixed-methods approach using a convergent design that combined data from qualitative interviews of team members conducted as teams neared the completion of their redesign projects, as well as evaluation questionnaires administered throughout the 4-year learning lab. RESULTS: Our results build on learning theories by showing that successful learning ecosystems continually create alignment between interdisciplinary teams' activities, organizational context, and innovation project objectives. The study identified four types of alignment, interpersonal/interprofessional, informational, structural, and processual, and supporting activities for alignment to occur. CONCLUSION: Interdisciplinary learning ecosystems have the potential to foster health care improvement and innovation through alignment of team activities, project goals, and organizational contexts. PRACTICE IMPLICATIONS: This study applies to interdisciplinary teams tackling multilevel system challenges in their health care organization and suggests that the work of such teams benefits from the four types of alignment. Alignment on all four dimensions may yield best results.

A mixed methods analysis of access barriers to dermatology care in a rural state.

AIMS: To identify significant patient and system access barriers and facilitators to dermatology care in one rural health system with limited dermatology appointment availability. DESIGN: Mixed methods study using data from electronic medical records, patient surveys, stakeholder semi-structured interviews, and service area dermatologist demographics. Retrospective data were collected between 1 January 2017-1 March 2018, and interviews and surveys were conducted between June 1-August 31, 2018. Participants were recruited from two primary care practices in one rural Maine regional health system. METHODS: Findings from thematic analyses, descriptive statistics, and statistical modelling were integrated using Chi-square tests for homogeneity to develop a unified understanding. Statistical modelling using odd-ratio logistic and linear regression were performed for each outcome variable of interest. RESULTS: Urgent referrals by primary care increased the likelihood of dermatology care overall (OR: 6.771; p = .007) and at nearby sites with limited availability (OR: 4.024; p = .024), but not at geographically further sites with higher capacities (p = .844). Referral under-diagnosis occurred in 20.8% of those biopsied. Older (p = .041) or non-working (p = .021) patients were more likely to remain unevaluated than seek more available but geographically further care. CONCLUSIONS: In rural areas with scarce appointment availability, primary care provider diagnostic accuracy may be an important barrier of dermatology care receipt and health outcomes, especially among at-risk populations. IMPACT: Although melanoma mortality rates are decreasing throughout the US, little is known about why rates in Maine continue to rise. This study applied a comprehensive approach to identify several patient and system access barriers to dermatology care in one underserved rural regional health system. While specific to this population and large service area, these findings will inform improvement efforts here and support broader future research efforts aimed at understanding and improving health outcomes in this rural state.

Access to specialty healthcare in urban versus rural US populations: a systematic literature review.

BACKGROUND: Access to healthcare is a poorly defined construct, with insufficient understanding of differences in facilitators and barriers between US urban versus rural specialty care. We summarize recent literature and expand upon a prior conceptual access framework, adapted here specifically to urban and rural specialty care. METHODS: A systematic review was conducted of literature within the CINAHL, Medline, PubMed, PsycInfo, and ProQuest Social Sciences databases published between January 2013 and August 2018. Search terms targeted peer-reviewed academic publications pertinent to access to US urban or rural specialty healthcare. Exclusion criteria produced 67 articles. Findings were organized into an existing ten-dimension care access conceptual framework where possible, with additional topics grouped thematically into supplemental dimensions. RESULTS: Despite geographic and demographic differences, many access facilitators and barriers were common to both populations; only three dimensions did not contain literature addressing both urban and rural populations. The most commonly represented dimensions were availability and accommodation, appropriateness, and ability to perceive. Four new identified dimensions were: government and insurance policy, health organization and operations influence, stigma, and primary care and specialist influence. CONCLUSIONS: While findings generally align with a preexisting framework, they also suggest several additional themes important to urban versus rural specialty care access.

User-Centered Collaborative Design and Development of an Inpatient Safety Dashboard.

Patient safety remains a key concern in hospital care. This article summarizes the iterative participatory development, features, functions, and preliminary evaluation of a patient safety dashboard for interdisciplinary rounding teams on inpatient medical services. This electronic health record (EHR)-embedded dashboard collects real-time data covering 13 safety domains through web services and applies logic to generate stratified alerts with an interactive check-box function. The technological infrastructure is adaptable to other EHR environments. Surveyed users perceived the tool as highly usable and useful. Integration of the dashboard into clinical care is intended to promote communication about patient safety and facilitate identification and management of safety concerns.

Computing exact bundle compliance control charts via probability generating functions.

Compliance to evidenced-base practices, individually and in 'bundles', remains an important focus of healthcare quality improvement for many clinical conditions. The exact probability distribution of composite bundle compliance measures used to develop corresponding control charts and other statistical tests is based on a fairly large convolution whose direct calculation can be computationally prohibitive. Various series expansions and other approximation approaches have been proposed, each with computational and accuracy tradeoffs, especially in the tails. This same probability distribution also arises in other important healthcare applications, such as for risk-adjusted outcomes and bed demand prediction, with the same computational difficulties. As an alternative, we use probability generating functions to rapidly obtain exact results and illustrate the improved accuracy and detection over other methods. Numerical testing across a wide range of applications demonstrates the computational efficiency and accuracy of this approach.

Review of Research Trends and Methods in Nano Environmental, Health, and Safety Risk Analysis.

Despite the many touted benefits of nanomaterials, concerns remain about their possible environmental, health, and safety (EHS) risks in terms of their toxicity, long-term accumulation effects, or dose-response relationships. The published studies on EHS risks of nanomaterials have increased significantly over the past decade and half, with most focused on nanotoxicology. Researchers are still learning about health consequences of nanomaterials and how to make environmentally responsible decisions regarding their production. This article characterizes the scientific literature on nano-EHS risk analysis to map the state-of-the-art developments in this field and chart guidance for the future directions. First, an analysis of keyword co-occurrence networks is investigated for nano-EHS literature published in the past decade to identify the intellectual turning points and research trends in nanorisk analysis studies. The exposure groups targeted in emerging nano-EHS studies are also assessed. System engineering methods for risk, safety, uncertainty, and system reliability analysis are reviewed, followed by detailed descriptions where applications of these methods are utilized to analyze nanomaterial EHS risks. Finally, the trends, methods, future directions, and opportunities of system engineering methods in nano-EHS research are discussed. The analysis of nano-EHS literature presented in this article provides important insights on risk assessment and risk management tools associated with nanotechnology, nanomanufacturing, and nano-enabled products.

Thresholds and accuracy in screening tools for early detection of psychopathology.

BACKGROUND: The accuracy of any screening instrument designed to detect psychopathology among children is ideally assessed through rigorous comparison to 'gold standard' tests and interviews. Such comparisons typically yield estimates of what we refer to as 'standard indices of diagnostic accuracy', including sensitivity, specificity, positive predictive value (PPV), and negative predictive value. However, whereas these statistics were originally designed to detect binary signals (e.g., diagnosis present or absent), screening questionnaires commonly used in psychology, psychiatry, and pediatrics typically result in ordinal scores. Thus, a threshold or 'cut score' must be applied to these ordinal scores before accuracy can be evaluated using such standard indices. To better understand the tradeoffs inherent in choosing a particular threshold, we discuss the concept of 'threshold probability'. In contrast to PPV, which reflects the probability that a child whose score falls at or above the screening threshold has the condition of interest, threshold probability refers specifically to the likelihood that a child whose score is equal to a particular screening threshold has the condition of interest. METHOD: The diagnostic accuracy and threshold probability of two well-validated behavioral assessment instruments, the Child Behavior Checklist Total Problem Scale and the Strengths and Difficulties Questionnaire total scale were examined in relation to a structured psychiatric interview in three de-identified datasets. RESULTS: Although both screening measures were effective in identifying groups of children at elevated risk for psychopathology in all samples (odds ratios ranged from 5.2 to 9.7), children who scored at or near the clinical thresholds that optimized sensitivity and specificity were unlikely to meet criteria for psychopathology on gold standard interviews. CONCLUSIONS: Our results are consistent with the view that screening instruments should be interpreted probabilistically, with attention to where along the continuum of positive scores an individual falls.

Low Rate of Completion of Recommended Tests and Referrals in an Academic Primary Care Practice with Resident Trainees.

BACKGROUND: A frequent, preventable cause of diagnostic errors involves failure to follow up on diagnostic tests, referrals, and symptoms-termed "failure to close the diagnostic loop." This is particularly challenging in a resident practice where one third of physicians graduate annually, and rates of patient loss due to these transitions may lead to more opportunities for failure to close diagnostic loops. The aim of this study was to determine the prevalence of failure of loop closure in a resident primary care clinic compared to rates in the faculty practice and identify factors contributing to failure. METHODS: This retrospective cohort study included all patient visits from January 1, 2018, to December 31, 2021, at two academic medical center-based primary care practices where residents and faculty practice in the same setting. The primary outcome was prevalence of failure to close the loop for (1) dermatology referrals, (2) colonoscopy, and (3) cardiac stress testing. The primary predictor was resident vs. faculty status of the ordering provider. The authors present an unadjusted analysis and the results of a multivariable logistic regression analysis incorporating all patient factors to determine their association with loop closure. RESULTS: Of 12,282 orders for referrals and tests for the three studied areas, 1,929 (15.7%) were ordered by a resident physician. Of resident orders for all three tests, 52.9% were completed within the designated time vs. 58.4% for orders placed by attending physicians (p < 0.01). In an unadjusted analysis by test type, a similar trend was seen for colonoscopy (51.4% completion rate for residents vs. 57.5% for attending physicians, p < 0.01) and for cardiac stress testing (55.7% completion rate for residents vs. 61.2% for attending physicians), though a difference was not seen for dermatology referrals (64.2% completion rate for residents vs. 63.7% for attending physicians). In an adjusted analysis, patients with resident orders were less likely than attendings to close the loop for all test types combined (odds ratio 0.88, 95% confidence interval 0.79-0.98), with low rates of test completion for both physician groups. CONCLUSION: Loop closure for three diagnostic interventions was low for patients in both faculty and resident primary care clinics, with lower loop closure rates in resident clinics. Failure to close diagnostic loops presents a safety challenge in primary care and is of particular concern for training programs.

Do patients who read visit notes on the patient portal have a higher rate of "loop closure" on diagnostic tests and referrals in primary care? A retrospective cohort study.

OBJECTIVES: The 2021 US Cures Act may engage patients to help reduce diagnostic errors/delays. We examined the relationship between patient portal registration with/without note reading and test/referral completion in primary care. MATERIALS AND METHODS: Retrospective cohort study of patients with visits from January 1, 2018 to December 31, 2021, and order for (1) colonoscopy, (2) dermatology referral for concerning lesions, or (3) cardiac stress test at 2 academic primary care clinics. We examined differences in timely completion ("loop closure") of tests/referrals for (1) patients who used the portal and read ≥1 note (Portal + Notes); (2) those with a portal account but who did not read notes (Portal Account Only); and (3) those who did not register for the portal (No Portal). We estimated the predictive probability of loop closure in each group after adjusting for socio-demographic and clinical factors using multivariable logistic regression. RESULTS: Among 12 849 tests/referrals, loop closure was more common among Portal+Note-readers compared to their counterparts for all tests/referrals (54.2% No Portal, 57.4% Portal Account Only, 61.6% Portal+Notes, P < .001). In adjusted analysis, compared to the No Portal group, the odds of loop closure were significantly higher for Portal Account Only (OR 1.2; 95% CI, 1.1-1.4), and Portal+Notes (OR 1.4; 95% CI, 1.3-1.6) groups. Beyond portal registration, note reading was independently associated with loop closure (P = .002). DISCUSSION AND CONCLUSION: Compared to no portal registration, the odds of loop closure were 20% higher in tests/referrals for patients with a portal account, and 40% higher in tests/referrals for note readers, after controlling for sociodemographic and clinical factors. However, important safety gaps from unclosed loops remain, requiring additional engagement strategies.

Urgent referrals from primary care to dermatology for lesions suspicious for skin cancer: patterns, outcomes, and need for systems improvement.

Ideally, urgent dermatology referrals for evaluation of a lesion concerning for skin cancer should be triaged and processed with appropriate urgency by primary care and dermatology, respectively. We performed a retrospective single-institution study by conducting chart reviews of all dermatology referrals designated by primary care as urgent for evaluation of a lesion concerning for skin cancer. We identified 320 referrals placed between January 1 and December 31, 2018. Dermatology encounters for these patients occurred on or before 30 days for 50.6% of referrals and on or after 31 days for 38.4% of referrals, with 10.9% never completed. The percentage of all races excluding whites, non-Hispanic in the delayed appointment group (≥ 31 days) was 15.1% higher (95% CI 5.3-24.9) than in the timely appointment group (≤ 30 days). Similarly, the percentage of non-English languages in the delayed group was 7.1% higher (95% CI 0.5-13.7) than in the timely group. Overall, 15.8% of these referrals yielded diagnoses of malignancy, while 76.8% and 7.4% resulted in benign and pre-malignant diagnoses, respectively. The primary care team documented referral status (i.e., completed, incomplete, or pending) during their subsequent visits with the patients in only 37.5% of these referrals. Our findings demonstrate the need to improve the reliability of urgent referrals to ensure they occur in a timely manner with confirmation of "referral loop" closure at the referring clinician's end.

Completion of Recommended Tests and Referrals in Telehealth vs In-Person Visits.

Importance: Use of telehealth has increased substantially in recent years. However, little is known about whether the likelihood of completing recommended tests and specialty referrals-termed diagnostic loop closure-is associated with visit modality. Objectives: To examine the prevalence of diagnostic loop closure for tests and referrals ordered at telehealth visits vs in-person visits and identify associated factors. Design, Setting, and Participants: In a retrospective cohort study, all patient visits from March 1, 2020, to December 31, 2021, at 1 large urban hospital-based primary care practice and 1 affiliated community health center in Boston, Massachusetts, were evaluated. Main Measures: Prevalence of diagnostic loop closure for (1) colonoscopy referrals (screening and diagnostic), (2) dermatology referrals for suspicious skin lesions, and (3) cardiac stress tests. Results: The study included test and referral orders for 4133 patients (mean [SD] age, 59.3 [11.7] years; 2163 [52.3%] women; 203 [4.9%] Asian, 1146 [27.7%] Black, 2362 [57.1%] White, and 422 [10.2%] unknown or other race). A total of 1151 of the 4133 orders (27.8%) were placed during a telehealth visit. Of the telehealth orders, 42.6% were completed within the designated time frame vs 58.4% of those ordered during in-person visits and 57.4% of those ordered without a visit. In an adjusted analysis, patients with telehealth visits were less likely to close the loop for all test types compared with those with in-person visits (odds ratio, 0.55; 95% CI, 0.47-0.64). Conclusions: The findings of this study suggest that rates of loop closure were low for all test types across all visit modalities but worse for telehealth. Failure to close diagnostic loops presents a patient safety challenge in primary care that may be of particular concern during telehealth encounters.

Increasing efficiency and accuracy of magnetic interaction calculations in colloidal simulation through machine learning.

Calculating the magnetic interaction between magnetic particles that are positioned in close proximity to one another is a surprisingly challenging task. Exact solutions for this interaction exist either through numerical expansion of multipolar interactions or through solving Maxwell's equations with a finite element solver. These approaches can take hours for simple configurations of three particles. Meanwhile, across a range of scientific and engineering problems, machine learning approaches have been developed as fast computational platforms for solving complex systems of interest when large data sets are available. In this paper, we bring the touted benefits of recent advances in science-based machine learning algorithms to bear on the problem of modeling the magnetic interaction between three particles. We investigate this approach using diverse machine learning systems including physics informed neural networks. We find that once the training data has been collected and the model has been initiated, simulation times are reduced from hours to mere seconds while maintaining remarkable accuracy. Despite this promise, we also try to lay bare the current challenges of applying machine learning to these and more complex colloidal systems.

Lessons Learned in Implementing a Chronic Opioid Therapy Management System.

OBJECTIVES: Opioid misuse has resulted in significant morbidity and mortality in the United States, and safer opioid use represents an important challenge in the primary care setting. This article describes a research collaborative of health service researchers, systems engineers, and clinicians seeking to improve processes for safer chronic opioid therapy management in an academic primary care center. We present implementation results and lessons learned along with an intervention toolkit that others may consider using within their organization. METHODS: Using iterative improvement lifecycles and systems engineering principles, we developed a risk-based workflow model for patients on chronic opioids. Two key safe opioid use process metrics-percent of patients with recent opioid treatment agreements and urine drug tests-were identified, and processes to improve these measures were designed, tested, and implemented. Focus groups were conducted after the conclusion of implementation, with barriers and lessons learned identified via thematic analysis. RESULTS: Initial surveys revealed a lack of knowledge regarding resources available to patients and prescribers in the primary care clinic. In addition, 18 clinicians (69%) reported largely "inheriting" (rather than initiating) their chronic opioid therapy patients. We tracked 68 patients over a 4-year period. Although process measures improved, full adherence was not achieved for the entire population. Barriers included team structure, the evolving opioid environment, and surveillance challenges, along with disruptions resulting from the 2019 novel coronavirus. CONCLUSIONS: Safe primary care opioid prescribing requires ongoing monitoring and management in a complex environment. The application of a risk-based approach is possible but requires adaptability and redundancies to be reliable.

Analysis of Radiology Report Recommendation Characteristics and Rate of Recommended Action Performance.

Importance: Following up on recommendations from radiologic findings is important for patient care, but frequently there are failures to carry out these recommendations. The lack of reliable systems to characterize and track completion of actionable radiology report recommendations poses an important patient safety challenge. Objectives: To characterize actionable radiology recommendations and, using this taxonomy, track and understand rates of loop closure for radiology recommendations in a primary care setting. Design, Setting, and Participants: Radiology reports in a primary care clinic at a large academic center were redesigned to include actionable recommendations in a separate dedicated field. Manual review of all reports generated from imaging tests ordered between January 1 and December 31, 2018, by primary care physicians that contained actionable recommendations was performed. For this quality improvement study, a taxonomy system that conceptualized recommendations was developed based on 3 domains: (1) what is recommended (eg, repeat a test or perform a different test, specialty referral), (2) specified time frame in which to perform the recommended action, and (3) contingency language qualifying the recommendation. Using this framework, a 2-stage process was used to review patients' records to classify recommendations and determine loop closure rates and factors associated with failure to complete recommended actions. Data analysis was conducted from April to July 2021. Main Outcomes and Measures: Radiology recommendations, time frames, and contingencies. Rates of carrying out vs not closing the loop on these recommendations in the recommended time frame were assessed. Results: A total of 598 radiology reports were identified with structured recommendations: 462 for additional or future radiologic studies and 196 for nonradiologic actions (119 specialty referrals, 47 invasive procedures, and 43 other actions). The overall rate of completed actions (loop closure) within the recommended time frame was 87.4%, with 31 open loop cases rated by quality expert reviewers to pose substantial clinical risks. Factors associated with successful loop closure included (1) absence of accompanying contingency language, (2) shorter recommended time frames, and (3) evidence of direct radiologist communication with the ordering primary care physicians. A clinically significant lack of loop closure was found in approximately 5% of cases. Conclusions and Relevance: The findings of this study suggest that creating structured radiology reports featuring a dedicated recommendations field permits the development of taxonomy to classify such recommendations and determine whether they were carried out. The lack of loop closure suggests the need for more reliable systems.

Early recognition and response to increases in surgical site infections using optimised statistical process control charts-The early 2RIS trial: A multicentre stepped wedge cluster randomised controlled trial.

Background: Traditional approaches for surgical site infection (SSI) surveillance have deficiencies that delay detection of SSI outbreaks and other clinically important increases in SSI rates. We investigated whether use of optimised statistical process control (SPC) methods and feedback for SSI surveillance would decrease rates of SSI in a network of US community hospitals. Methods: We conducted a stepped wedge cluster randomised trial of patients who underwent any of 13 types of common surgical procedures across 29 community hospitals in the Southeastern United States. We divided the 13 procedures into six clusters; a cluster of procedures at a single hospital was the unit of randomisation and analysis. In total, 105 clusters were randomised to 12 groups of 8-10 clusters. All participating clusters began the trial in a 12-month baseline period of control or "traditional" SSI surveillance, including prospective analysis of SSI rates and consultative support for SSI outbreaks and investigations. Thereafter, a group of clusters transitioned from control to intervention surveillance every three months until all clusters received the intervention. Electronic randomisation by the study statistician determined the sequence by which clusters crossed over from control to intervention surveillance. The intervention was the addition of weekly application of optimised SPC methods and feedback to existing traditional SSI surveillance methods. Epidemiologists were blinded to hospital identity and randomisation status while adjudicating SPC signals of increased SSI rates, but blinding was not possible during SSI investigations. The primary outcome was the overall SSI prevalence rate (PR=SSIs/100 procedures), evaluated via generalised estimating equations with a Poisson regression model. Secondary outcomes compared traditional and optimised SPC signals that identified SSI rate increases, including the number of formal SSI investigations generated and deficiencies identified in best practices for SSI prevention. This trial was registered at ClinicalTrials.gov, NCT03075813. Findings: Between Mar 1, 2016, and Feb 29, 2020, 204,233 unique patients underwent 237,704 surgical procedures. 148,365 procedures received traditional SSI surveillance and feedback alone, and 89,339 procedures additionally received the intervention of optimised SPC surveillance. The primary outcome of SSI was assessed for all procedures performed within participating clusters. SSIs occurred after 1171 procedures assigned control surveillance (prevalence rate [PR] 0.79 per 100 procedures), compared to 781 procedures that received the intervention (PR 0·87 per 100 procedures; model-based PR ratio 1.10, 95% CI 0.94-1.30, p=0.25). Traditional surveillance generated 24 formal SSI investigations that identified 120 SSIs with deficiencies in two or more perioperative best practices for SSI prevention. In comparison, optimised SPC surveillance generated 74 formal investigations that identified 458 SSIs with multiple best practice deficiencies. Interpretation: The addition of optimised SPC methods and feedback to traditional methods for SSI surveillance led to greater detection of important SSI rate increases and best practice deficiencies but did not decrease SSI rates. Additional research is needed to determine how to best utilise SPC methods and feedback to improve adherence to SSI quality measures and prevent SSIs. Funding: Agency for Healthcare Research and Quality.

Mandatory public reporting: build it and who will come?

Rates of healthcare-associated infections (HAI) are being reported on an increasing number of public information websites in response to legislative mandates driven by consumer advocacy. This represents a new strategy to advance patient safety and quality of care by informing a broad audience about the relative performance of individual healthcare facilities. Unlike typical consumer health informatics products, the target audience and targeted health behaviors are less easily defined; further, the impact on providers to improve care is unknown relative to other incentives to improve. To address critical knowledge gaps facing all state agencies embarking on this new frontier, we found it essential and straightforward to recruit the assistance of university research faculty from a variety of disciplines. That interdisciplinary group was quickly able to define a 5-year applied evaluation research agenda spanning a progressive set of crucial questions.

Community and Campus COVID-19 Risk Uncertainty Under University Reopening Scenarios: Model-Based Analysis.

BACKGROUND: Significant uncertainty has existed about the safety of reopening college and university campuses before the COVID-19 pandemic is better controlled. Moreover, little is known about the effects that on-campus students may have on local higher-risk communities. OBJECTIVE: We aimed to estimate the range of potential community and campus COVID-19 exposures, infections, and mortality under various university reopening plans and uncertainties. METHODS: We developed campus-only, community-only, and campus × community epidemic differential equations and agent-based models, with inputs estimated via published and grey literature, expert opinion, and parameter search algorithms. Campus opening plans (spanning fully open, hybrid, and fully virtual approaches) were identified from websites and publications. Additional student and community exposures, infections, and mortality over 16-week semesters were estimated under each scenario, with 10% trimmed medians, standard deviations, and probability intervals computed to omit extreme outliers. Sensitivity analyses were conducted to inform potential effective interventions. RESULTS: Predicted 16-week campus and additional community exposures, infections, and mortality for the base case with no precautions (or negligible compliance) varied significantly from their medians (4- to 10-fold). Over 5% of on-campus students were infected after a mean of 76 (SD 17) days, with the greatest increase (first inflection point) occurring on average on day 84 (SD 10.2 days) of the semester and with total additional community exposures, infections, and mortality ranging from 1-187, 13-820, and 1-21 per 10,000 residents, respectively. Reopening precautions reduced infections by 24%-26% and mortality by 36%-50% in both populations. Beyond campus and community reproductive numbers, sensitivity analysis indicated no dominant factors that interventions could primarily target to reduce the magnitude and variability in outcomes, suggesting the importance of comprehensive public health measures and surveillance. CONCLUSIONS: Community and campus COVID-19 exposures, infections, and mortality resulting from reopening campuses are highly unpredictable regardless of precautions. Public health implications include the need for effective surveillance and flexible campus operations.

Antibiotic stewardship from a decision-making, behavioral economics, and incentive design perspective.

Antibiotic-resistant infections cause over 20 thousand deaths and $20 billion annually in the United States. Antibiotic prescribing decision making can be described as a "tragedy of the commons" behavioral economics problem, for which individual best interests affecting human decision-making lead to suboptimal societal antibiotic overuse. In 2015, the U.S. federal government announced a $1.2 billion National Action Plan to combat resistance and reduce antibiotic use by 20% in inpatient settings and 50% in outpatient settings by 2020. We develop and apply a behavioral economics model based on game theory and "tragedy of the commons" concepts to help illustrate why rational individuals may not practice ideal stewardship and how to potentially structure three specific alternate approaches to accomplish these objectives (collective cooperative management, usage taxes, resistance penalties), based on Ostrom's economic governance principles. Importantly, while each approach can effectively incentivize ideal stewardship, the latter two do so with 10-30% lower utility to all providers. Encouraging local or state-level self-managed cooperative stewardship programs thus is preferred to national taxes and penalties, in contrast with current trends and with similar implications in other countries.