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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

Systems engineering analysis of diagnostic referral closed-loop processes.

BACKGROUND: Closing loops to complete diagnostic referrals remains a significant patient safety problem in most health systems, with 65%-73% failure rates and significant delays common despite years of improvement efforts, suggesting new approaches may be useful. Systems engineering (SE) methods increasingly are advocated in healthcare for their value in studying and redesigning complex processes. OBJECTIVE: Conduct a formative SE analysis of process logic, variation, reliability and failures for completing diagnostic referrals originating in two primary care practices serving different demographics, using dermatology as an illustrating use case. METHODS: An interdisciplinary team of clinicians, systems engineers, quality improvement specialists, and patient representatives collaborated to understand processes of initiating and completing diagnostic referrals. Cross-functional process maps were developed through iterative group interviews with an urban community-based health centre and a teaching practice within a large academic medical centre. Results were used to conduct an engineering process analysis, assess variation within and between practices, and identify common failure modes and potential solutions. RESULTS: Processes to complete diagnostic referrals involve many sub-standard design constructs, with significant workflow variation between and within practices, statistical instability and special cause variation in completion rates and timeliness, and only 21% of all process activities estimated as value-add. Failure modes were similar between the two practices, with most process activities relying on low-reliability concepts (eg, reminders, workarounds, education and verification/inspection). Several opportunities were identified to incorporate higher reliability process constructs (eg, simplification, consolidation, standardisation, forcing functions, automation and opt-outs). CONCLUSION: From a systems science perspective, diagnostic referral processes perform poorly in part because their fundamental designs are fraught with low-reliability characteristics and mental models, including formalised workaround and rework activities, suggesting a need for different approaches versus incremental improvement of existing processes. SE perspectives and methods offer new ways of thinking about patient safety problems, failures and potential solutions.

Patient engagement in system redesign teams: a process of social identity.

PURPOSE: Studies demonstrate how patient roles in system redesign teams reflect a continuum of involvement and influence. This research shows the process by which patients move through this continuum and effectively engage within redesign projects. DESIGN/METHODOLOGY/APPROACH: The authors studied members of redesign teams, consisting of 5-10 members: clinicians, systems engineers, health system staff and patient(s), from three health systems working on separate projects in a patient safety learning lab. Weekly team meetings were observed, January 2016-April 2018, 17 semi-structured interviews were conducted and findings through a patient focus group were refined. Grounded theory was used to analyze field notes and transcripts. FINDINGS: Results show how the social identity process enables patients to move through stages in a patient engagement continuum (informant, partner and active change agent). Initially, patient and team member perceptions of the patient's role influence their respective behaviors (activating, directing, framing and sharing). Subsequently, patient and team member behaviors influence patient contributions on the team, which can redefine patient and team member perceptions of the patient's role. ORIGINALITY/VALUE: As health systems grow increasingly complex and become more interested in responding to patient expectations, understanding how to effectively engage patients on redesign teams gains importance. This research investigates how and why patient engagement on redesign teams changes over time and what makes different types of patient roles valuable for team objectives. Findings have implications for how redesign teams can better prepare, anticipate and support the changing role of engaged patients.

Systems Analysis of a Dedicated Ambulatory Respiratory Unit for Seeing and Ensuring Follow-up of Patients With COVID-19 Symptoms.

COVID-19 necessitated significant care redesign, including new ambulatory workflows to handle surge volumes, protect patients and staff, and ensure timely reliable care. Opportunities also exist to harvest lessons from workflow innovations to benefit routine care. We describe a dedicated COVID-19 ambulatory unit for closing testing and follow-up loops characterized by standardized workflows and electronic communication, documentation, and order placement. More than 85% of follow-ups were completed within 24 hours, with no observed staff, nor patient infections associated with unit operations. Identified issues include role confusion, staffing and gatekeeping bottlenecks, and patient reluctance to visit in person or discuss concerns with phone screeners.

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.

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.

Evaluation of a Patient-Centered Fall-Prevention Tool Kit to Reduce Falls and Injuries: A Nonrandomized Controlled Trial.

Importance: Falls represent a leading cause of preventable injury in hospitals and a frequently reported serious adverse event. Hospitalization is associated with an increased risk for falls and serious injuries including hip fractures, subdural hematomas, or even death. Multifactorial strategies have been shown to reduce falls in acute care hospitals, but evidence for fall-related injury prevention in hospitals is lacking. Objective: To assess whether a fall-prevention tool kit that engages patients and families in the fall-prevention process throughout hospitalization is associated with reduced falls and injurious falls. Design, Setting, and Participants: This nonrandomized controlled trial using stepped wedge design was conducted between November 1, 2015, and October 31, 2018, in 14 medical units within 3 academic medical centers in Boston and New York City. All adult inpatients hospitalized in participating units were included in the analysis. Interventions: A nurse-led fall-prevention tool kit linking evidence-based preventive interventions to patient-specific fall risk factors and designed to integrate continuous patient and family engagement in the fall-prevention process. Main Outcomes and Measures: The primary outcome was the rate of patient falls per 1000 patient-days in targeted units during the study period. The secondary outcome was the rate of falls with injury per 1000 patient-days. Results: During the interrupted time series, 37 231 patients were evaluated, including 17 948 before the intervention (mean [SD] age, 60.56 [18.30] years; 9723 [54.17%] women) and 19 283 after the intervention (mean [SD] age, 60.92 [18.10] years; 10 325 [53.54%] women). There was an overall adjusted 15% reduction in falls after implementation of the fall-prevention tool kit compared with before implementation (2.92 vs 2.49 falls per 1000 patient-days [95% CI, 2.06-3.00 falls per 1000 patient-days]; adjusted rate ratio 0.85; 95% CI, 0.75-0.96; P = .01) and an adjusted 34% reduction in injurious falls (0.73 vs 0.48 injurious falls per 1000 patient-days [95% CI, 0.34-0.70 injurious falls per 1000 patient-days]; adjusted rate ratio, 0.66; 95% CI, 0.53-0.88; P = .003). Conclusions and Relevance: In this nonrandomized controlled trial, implementation of a fall-prevention tool kit was associated with a significant reduction in falls and related injuries. A patient-care team partnership appears to be beneficial for prevention of falls and fall-related injuries. Trial Registration: ClinicalTrials.gov Identifier: NCT02969343.

Early recognition and response to increases in surgical site infections using optimized statistical process control charts-the Early 2RIS Trial: a multicenter cluster randomized controlled trial with stepped wedge design.

BACKGROUND: Surgical site infections (SSIs) cause significant patient suffering. Surveillance and feedback of SSI rates is an evidence-based strategy to reduce SSIs, but traditional surveillance methods are slow and prone to bias. The objective of this cluster randomized controlled trial (RCT) is to determine if using optimized statistical process control (SPC) charts for SSI surveillance and feedback lead to a reduction in SSI rates compared to traditional surveillance. METHODS: The Early 2RIS Trial is a prospective, multicenter cluster RCT using a stepped wedge design. The trial will be performed in 29 hospitals in the Duke Infection Control Outreach Network (DICON) and 105 clusters over 4 years, from March 2016 through February 2020; year one represents a baseline period; thereafter, 8-9 clusters will be randomized to intervention every 3 months over a 3-year period using a stepped wedge randomization design. All patients who undergo one of 13 targeted procedures at study hospitals will be included in the analysis; these procedures will be included in one of six clusters: cardiac, orthopedic, gastrointestinal, OB-GYN, vascular, and spinal. All clusters will undergo traditional surveillance for SSIs; once randomized to intervention, clusters will also undergo surveillance and feedback using optimized SPC charts. Feedback on surveillance data will be provided to all clusters, regardless of allocation or type of surveillance. The primary endpoint is the difference in rates of SSI between the SPC intervention compared to traditional surveillance and feedback alone. DISCUSSION: The traditional approach for SSI surveillance and feedback has several major deficiencies because SSIs are rare events. First, traditional statistical methods require aggregation of measurements over time, which delays analysis until enough data accumulate. Second, traditional statistical tests and resulting p values are difficult to interpret. Third, analyses based on average SSI rates during predefined time periods have limited ability to rapidly identify important, real-time trends. Thus, standard analytic methods that compare average SSI rates between arbitrarily designated time intervals may not identify an important SSI rate increase on time unless the "signal" is very strong. Therefore, novel strategies for early identification and investigation of SSI rate increases are needed to decrease SSI rates. While SPC charts are used throughout industry and healthcare to improve and optimize processes, including other types of healthcare-associated infections, they have not been evaluated as a tool for SSI surveillance and feedback in a randomized trial. TRIAL REGISTRATION: ClinicalTrials.gov NCT03075813 , Registered March 9, 2017.

Potential Community and Campus Covid-19 Outcomes Under University and College Reopening Scenarios.

BACKGROUND: Significant uncertainty exists in many countries about the safety of, and best strategies for, reopening college and university campuses until the Covid-19 pandemic is better controlled. Little also is known about the effects on-campus students may have on local higher-risk communities. We aimed to estimate potential community and campus Covid-19 exposures, infections, and mortality due to various university reopening and precaution plans under current ranges of assumptions and uncertainties. METHODS: We developed and calibrated campus-only, community-only, and campus-x-community epidemic differential equation and agent-based models. Input parameters for campus and surrounding communities were estimated via published and grey literature, scenario development, expert opinion, accuracy optimization algorithms, and Monte Carlo simulation; models were cross-validated against each other using February-June 2020 data from heterogeneous U.S. counties and states. Campus opening plans (spanning various fully open, hybrid, and fully virtual approaches) were identified from websites and publications. All scenarios were simulated assuming 16-week semesters and estimated ranges for Covid-19 prevalence among community residents and arriving students, precaution compliance, contact frequency, virus attack rates, and tracing and isolation effectiveness. Additional student and community exposures, infections, and mortality were estimated under each scenario, with 10% trimmed medians, standard deviations, and probability intervals computed to omit extreme outlier scenarios. Factorial analyses were conducted to identify intervention inputs with largest and smallest effects. RESULTS: As a base case with no precautions (or no compliance), predicted 16-week student infections and mortality under normal operations ranged significantly from 471 to 9,495 (median: 2,286, SD: 2,627) and 0 to 123 (median: 9, SD: 14) per 10,000 students, respectively. The maximum active exposures across a semester was 15.76% of all students warranting tracing. Total additional community exposures, infections, and mortality ranged from 1 to 187, 13 to 820, and 1 to 21 per 10,000 residents, respectively. 1% and 5% of on-campus students were infected after a mean (SD) of 11 (3) and 76 (17) days, respectively; >10% students infected by the end of a semester in 34.8% of scenarios, with the greatest increase (first inflection point) occurring on aver-age on day 84 (SD: 10.2 days). Common reopening precautions reduced infections by 24% to 26% and mortality by 36% to 50% in both populations. Uncertainties in many factors, however, produced tremendous variability in all results, ranging from medians by -67% to +342%. CONCLUSIONS: Consequences on community and student Covid-19 exposures, infections, and mortality of reopening physical campuses are very highly unpredictable, depending on a combination of random chance, controllable (e.g. physical layouts), and uncontrollable (e.g. human behavior) factors. Implications include needs for criteria to adapt campus operations mid-semester, methods to detect when necessary, and contingency plans for doing so.