A quality improvement study on how a simulation model can help decision making on organization of ICU wards.

BACKGROUND: Intensive Care Unit (ICU) capacity management is essential to provide high-quality healthcare for critically ill patients. Yet, consensus on the most favorable ICU design is lacking, especially whether ICUs should deliver dedicated or non-dedicated care. The decision for dedicated or non-dedicated ICU design considers a trade-off in the degree of specialization for individual patient care and efficient use of resources for society. We aim to share insights of a model simulating capacity effects for different ICU designs. Upon request, this simulation model is available for other ICUs. METHODS: A discrete event simulation model was developed and used, to study the hypothetical performance of a large University Hospital ICU on occupancy, rejection, and rescheduling rates for a dedicated and non-dedicated ICU design in four different scenarios. These scenarios either simulate the base-case situation of the local ICU, varying bed capacity levels, potential effects of reduced length of stay for a dedicated design and unexpected increased inflow of unplanned patients. RESULTS: The simulation model provided insights to foresee effects of capacity choices that should be made. The non-dedicated ICU design outperformed the dedicated ICU design in terms of efficient use of scarce resources. CONCLUSIONS: The choice to use dedicated ICUs does not only affect the clinical outcome, but also rejection- rescheduling and occupancy rates. Our analysis of a large university hospital demonstrates how such a model can support decision making on ICU design, in conjunction with other operation characteristics such as staffing and quality management.

Opt-out choice framing attenuates gender differences in the decision to compete in the laboratory and in the field.

Research shows that women are less likely to enter competitions than men. This disparity may translate into a gender imbalance in holding leadership positions or ascending in organizations. We provide both laboratory and field experimental evidence that this difference can be attenuated with a default nudge-changing the choice to enter a competitive task from a default in which applicants must actively choose to compete to a default in which applicants are automatically enrolled in competition but can choose to opt out. Changing the default affects the perception of prevailing social norms about gender and competition as well as perceptions of the performance or ability threshold at which to apply. We do not find associated negative effects for performance or wellbeing. These results suggest that organizations could make use of opt-out promotion schemes to reduce the gender gap in competition and support the ascension of women to leadership positions.

Meritus Health: Driving Data-Informed Decision-Making at Every Level.

With so much data available, health system leaders are challenged with sifting through it all to find the most useful information for decision-making. Meritus Health implemented effective approaches to understand, use, and communicate large amounts of data to alleviate some of this burden. These processes include system-wide daily huddles, dashboards, and standardized communication write-ups.

Governing the Access to COVID-19 Tools Accelerator: towards greater participation, transparency, and accountability.

The Access to COVID-19 Tools Accelerator (ACT-A) is a multistakeholder initiative quickly constructed in the early months of the COVID-19 pandemic to respond to a catastrophic breakdown in global cooperation. ACT-A is now the largest international effort to achieve equitable access to COVID-19 health technologies, and its governance is a matter of broad public importance. We traced the evolution of ACT-A's governance through publicly available documents and analysed it against three principles embedded in the founding mission statement of ACT-A: participation, transparency, and accountability. We found three challenges to realising these principles. First, the roles of the various organisations in ACT-A decision making are unclear, obscuring who might be accountable to whom and for what. Second, the absence of a clearly defined decision making body; ACT-A instead has multiple centres of legally binding decision making and uneven arrangements for information transparency, inhibiting meaningful participation. Third, the nearly indiscernible role of governments in ACT-A, raising key questions about political legitimacy and channels for public accountability. With global public health and billions in public funding at stake, short-term improvements to governance arrangements can and should now be made. Efforts to strengthen pandemic preparedness for the future require attention to ethical, legitimate arrangements for governance.

Distemper, extinction, and vaccination of the Amur tiger.

Canine distemper virus (CDV) has recently emerged as an extinction threat for the endangered Amur tiger (Panthera tigris altaica). CDV is vaccine-preventable, and control strategies could require vaccination of domestic dogs and/or wildlife populations. However, vaccination of endangered wildlife remains controversial, which has led to a focus on interventions in domestic dogs, often assumed to be the source of infection. Effective decision making requires an understanding of the true reservoir dynamics, which poses substantial challenges in remote areas with diverse host communities. We carried out serological, demographic, and phylogenetic studies of dog and wildlife populations in the Russian Far East to show that a number of wildlife species are more important than dogs, both in maintaining CDV and as sources of infection for tigers. Critically, therefore, because CDV circulates among multiple wildlife sources, dog vaccination alone would not be effective at protecting tigers. We show, however, that low-coverage vaccination of tigers themselves is feasible and would produce substantive reductions in extinction risks. Vaccination of endangered wildlife provides a valuable component of conservation strategies for endangered species.

Human factors in healthcare IT: Management considerations and trends.

A range of human factors issues are recognized as critical to the success of projects involving Health Information Technology (HIT). Problems related to the usability of HIT have come to the fore, with continued reports of systems that are non-intuitive and difficult to use and that may even pose safety risks. In this article, we consider a number of approaches from usability engineering and human factors that can be applied to improve the chances of system success and adoption. A range of methods focused around human factors can be employed throughout the system development cycle of HIT. The purpose of this article is to discuss human factors approaches that can be used to improve the likelihood of successful system adoption and also provide input into the selection and procurement process of HIT. The article concludes with recommendations regarding how understanding of human factors can be integrated into healthcare organizational decision making.

Guiding organisational decision-making about COVID-19 asymptomatic testing in workplaces: mixed-method study to inform an ethical framework.

BACKGROUND: Workplace programmes to test staff for asymptomatic COVID-19 infection have become common, but raise a number of ethical challenges. In this article, we report the findings of a consultation that informed the development of an ethical framework for organisational decision-making about such programmes. METHODS: We conducted a mixed-method consultation - a survey and semi-structured interviews during November-December 2020 in a UK case study organisation that had introduced asymptomatic testing for all staff working on-site in its buildings. Analysis of closed-ended survey data was conducted descriptively. An analysis approach based on the Framework Method was used for the open-ended survey responses and interview data. The analyses were then integrated to facilitate systematic analysis across themes. Inferences were based on the integrated findings and combined with other inputs (literature review, ethical analysis, legal and public health guidance, expert discussions) to develop an ethical framework. RESULTS: The consultation involved 61 staff members from the case study organisation (50 survey respondents and 11 interview participants). There was strong support for the asymptomatic testing programme: 90% of the survey respondents viewed it as helpful or very helpful. Open-ended survey responses and interviews gave insight into participants' concerns, including those relating to goal drift, risk of false negatives, and potential negative impacts for household members and people whose roles lacked contractual and financial stability. Integration of the consultation findings and the other inputs identified the importance of a whole-system approach with appropriate support for the key control measure of isolation following positive tests. The need to build trust in the testing programme, for example through effective communication from leaders, was also emphasised. CONCLUSIONS: The consultation, together with other inputs, informed an ethical framework intended to support employers. The framework may support organisational decision-making in areas ranging from design and operation of the programme through to choices about participation. The framework is likely to benefit from further consultation and refinement in new settings.

Investigating the cognitive capacity constraints of an ICU care team using a systems engineering approach.

BACKGROUND: ICU operational conditions may contribute to cognitive overload and negatively impact on clinical decision making. We aimed to develop a quantitative model to investigate the association between the operational conditions and the quantity of medication orders as a measurable indicator of the multidisciplinary care team's cognitive capacity. METHODS: The temporal data of patients at one medical ICU (MICU) of Mayo Clinic in Rochester, MN between February 2016 to March 2018 was used. This dataset includes a total of 4822 unique patients admitted to the MICU and a total of 6240 MICU admissions. Guided by the Systems Engineering Initiative for Patient Safety model, quantifiable measures attainable from electronic medical records were identified and a conceptual framework of distributed cognition in ICU was developed. Univariate piecewise Poisson regression models were built to investigate the relationship between system-level workload indicators, including patient census and patient characteristics (severity of illness, new admission, and mortality risk) and the quantity of medication orders, as the output of the care team's decision making. RESULTS: Comparing the coefficients of different line segments obtained from the regression models using a generalized F-test, we identified that, when the ICU was more than 50% occupied (patient census > 18), the number of medication orders per patient per hour was significantly reduced (average = 0.74; standard deviation (SD) = 0.56 vs. average = 0.65; SD = 0.48; p < 0.001). The reduction was more pronounced (average = 0.81; SD = 0.59 vs. average = 0.63; SD = 0.47; p < 0.001), and the breakpoint shifted to a lower patient census (16 patients) when at a higher presence of severely-ill patients requiring invasive mechanical ventilation during their stay, which might be encountered in an ICU treating patients with COVID-19. CONCLUSIONS: Our model suggests that ICU operational factors, such as admission rates and patient severity of illness may impact the critical care team's cognitive function and result in changes in the production of medication orders. The results of this analysis heighten the importance of increasing situational awareness of the care team to detect and react to changing circumstances in the ICU that may contribute to cognitive overload.

Does access to care play a role in liver cancer survival? The ten-year (2006-2015) experience from a population-based cancer registry in Southern Italy.

BACKGROUND: Hepatocellular carcinoma (HCC) is the most frequent primary invasive cancer of the liver. During the last decade, the epidemiology of HCC has been continuously changing in developed countries, due to more effective primary prevention and to successful treatment of virus-related liver diseases. The study aims to examine survival by level of access to care in patients with HCC, for all patients combined and by age. METHODS: We included 2018 adult patients (15-99 years) diagnosed with a primary liver tumour, registered in the Palermo Province Cancer Registry during 2006-2015, and followed-up to 30 October 2019. We obtained a proxy measure of access to care by linking each record to the Hospital Discharge Records and the Ambulatory Discharge Records. We estimated net survival up to 5 years after diagnosis by access to care ("easy access to care" versus "poor access to care"), using the Pohar-Perme estimator. Estimates were age-standardised using International Cancer Survival Standard (ICSS) weights. We also examined survival by access to care and age (15-64, 65-74 and ≥ 75 years). RESULTS: Among the 2018 patients, 62.4% were morphologically verified and 37.6% clinically diagnosed. Morphologically verified tumours were more frequent in patients aged 65-74 years (41.6%), while tumours diagnosed clinically were more frequent in patients aged 75 years or over (50.2%). During 2006-2015, age-standardised net survival was higher among HCC patients with "easy access to care" than in those with "poor access to care" (68% vs. 48% at 1 year, 29% vs. 11% at 5 years; p < 0.0001). Net survival up to 5 years was higher for patients with "easy access to care" in each age group (p < 0.0001). Moreover, survival increased slightly for patients with easier access to care, while it remained relatively stable for patients with poor access to care. CONCLUSIONS: During 2006-2015, 5-year survival was higher for HCC patients with easier access to care, probably reflecting progressive improvement in the effectiveness of health care services offered to these patients. Our linkage algorithm could provide valuable evidence to support healthcare decision-making in the context of the evolving epidemiology of hepatocellular carcinoma.

Upgrades to intensive care: The effects of COVID-19 on decision-making in the emergency department.

INTRODUCTION: The initial surge of critically ill patients in the COVID-19 pandemic severely disrupted processes at acute care hospitals. This study examines the frequency and causes for patients upgraded to intensive care unit (ICU) level care following admission from the emergency department (ED) to non-critical care units. METHODS: The number of ICU upgrades per month was determined, including the percentage of upgrades noted to have non-concordant diagnoses. Charts with non-concordant diagnoses were examined in detail as to the ED medical decision-making, clinical circumstances surrounding the upgrade, and presence of a diagnosis of COVID-19. For each case, a cognitive bias was assigned. RESULTS: The percentage of upgraded cases with non-concordant diagnoses increased from a baseline range of 14-20% to 41.3%. The majority of upgrades were due to premature closure (72.2%), anchoring (61.1%), and confirmation bias (55.6%). CONCLUSION: Consistent with the behavioral literature, this suggests that stressful ambient conditions affect cognitive reasoning processes.

Effect of Shared Governance on Nurse-Sensitive Indicator and Satisfaction Outcomes: An International Comparison.

OBJECTIVE: Researchers examined associations between Index for Professional Nursing Governance (IPNG) scores and outcomes, by US and international hospitals. BACKGROUND: Nursing governance and effects on nurse-related outcomes are not well studied. METHODS: Associations were evaluated using average IPNG scores from 2170 RNs and nurse-sensitive indicators (NSIs) and patient and RN satisfaction outcomes (n = 205 study units, 20 hospitals, 4 countries). RESULTS: International units had better IPNG shared governance scores (113.5; US = 100.6; P < 0.001), and outcomes outperforming unit benchmarks (6 of 15, 40.0%; US = 2 of 15, 13.3%). Shared governance significantly outperformed traditional governance for 5 of 20 (25.0%) US outcomes (patient satisfaction = 1, RN satisfaction = 4) and for 3 of 11 (27.3%) international (patient satisfaction = 1, RN satisfaction = 2). Internationally, self-governance significantly outperformed traditional governance and shared governance for 5 of 12 (41.7%) outcomes (NSI = 2, patient satisfaction = 3). CONCLUSIONS: Shared governance is a strategy that can be considered by nurse leaders for improving select outcomes.

[The disaster task force medical officer as a pivotal decision maker in the superordinate pandemic hospital capacity management : A field report covering the initial COVID-19 surge in a Bavarian district]. / Der Ärztliche Leiter Führungsgruppe Katastrophenschutz als zentrale Entscheidungsinstanz bei der Steuerung regionaler Krankenhauskapazitäten in der Pandemie : Ein Erfahrungsbericht zur ersten Welle der COVID-19-Pandemie in einem bayerischen Regierungsbezirk.

BACKGROUND AND OBJECTIVE: During the initial phase of the COVID-19 pandemic the government of the state of Bavaria, Germany, declared a state of emergency for its entire territory for the first time in history. Some areas in eastern Bavaria were among the most severely affected communities in Germany, prompting authorities and hospitals to build up capacities for a surge of COVID-19 patients. In some areas, intensive care unit (ICU) capacities were heavily engaged, which occasionally made a redistribution of patients necessary. MATERIAL AND METHODS: For managing COVID-19-related hospital capacities and patient allocation, crisis management squads in Bavaria were expanded by disaster task force medical officers ("Ärztlicher Leiter Führungsgruppe Katastrophenschutz" [MO]) with substantial executive authority. The authors report their experiences as MO concerning the superordinate patient allocation management in the district of Upper Palatinate (Oberpfalz) in eastern Bavaria. RESULTS: By abandoning routine patient care and building up additional ICU resources, surge capacity for the treatment of COVID-19 patients was generated in hospitals. In parts of the Oberpfalz, ICU capacities were almost entirely occupied by patients with corona virus infections, making reallocation to other hospitals within the district and beyond necessary. The MO managed patient pathways in an escalating manner by defining local (within the region of responsibility of a single MO), regional (within the district), and cross-regional (over district borders) reallocation lanes, as needed. When regional or cross-regional reallocation lanes had to be established, an additional management level located at the district government was involved. Within the determined reallocation lanes, emitting and receiving hospitals mutually agreed on any patient transfer without explicitly involving the MO, thereby maintaining the established interhospital routine transfer procedures. The number of patients and available treatment resources at each hospital were monitored with the help of a web-based treatment capacity registry. If indicated, reallocation lanes were dynamically revised according to the present situation. To oppose further virus spreading in nursing homes, the state government prohibited patient allocation to these facilities, which led to considerably longer hospital length of stay of convalescent elderly and/or dependent patients. In parallel to the flattening of the COVID-19 incidence curve, routine hospital patient care could be re-established in a stepwise manner. CONCLUSION: Patient allocation during the state of emergency by the MO sought to keep up routine interhospital reallocation procedures as much as possible, thereby reducing management time and effort. Occasionally, difficulties were observed during patient allocations crossing district borders, if other MO followed different management principles. The nursing home blockade and conflicting financial interests of hospitals posed challenges to the work of the disaster task force medical officers.

Applied systems thinking: The impact of system optimization strategies on financial and quality performance in a team-based simulation.

At its core, this research was undertaken to explore the extent to which system optimization leadership strategies such as innovation, collaboration, and data-driven decision-making affect financial and quality performance in organizations. A quasi-experimental pretest-posttest research design was used to examine the increase or decrease in system performance as a result of treatment in the form of a systems thinking workshop and strategy discussion. The application of three-core system strategies lead to significant gains in financial performance across all teams, and an increase in quality performance in all but one team. In addition to an increase in performance, this research also revealed the tendency of social systems to reflexively sub-optimize their performance and at times lose focus on higher order system goals. Helpful recommendations for leadership practice and future research are presented with a view to helping optimize whole systems and not solely their parts.

COVID-19, Workforce Autonomy and the Health Supply Chain.

During the COVID-19 pandemic, the rapid surge in demand for critical supplies and public health efforts needed to guard against virus transmission have placed enormous pressure on health systems worldwide. These pressures and the uncertainty they have created have impacted the health workforce in a substantial way. This paper examines the relationship between health supply chain capacity and the impact of the COVID-19 pandemic on Canada's health workforce. The findings of this research also highlight the impact of the pandemic on health workers, specifically the relationship between the health supply chain and the autonomy of the health workforce.

Mental Health Clinician Leaders in "Lockstep" as a Necessary Means to Address Care Challenges during the Pandemic.

Clinical environments that provide mental health and addictions care have been challenged during the COVID-19 pandemic due to health human resource shortages. This paper provides some insights gleaned from nurse and physician leaders working together during the pandemic in the mental health context to tackle some of these challenges. Key takeaways are provided.

Social determinants of health, data science, and decision-making: Forging a transdisciplinary synthesis.

Sandro Galea and co-authors discuss a forthcoming Collection on data science and social determinants of health.

Integration of Health and Social Services at the Systems Level: A Framework for Addressing Funding and Jurisdictional Silos.

Objectives. To examine spending and resource allocation decision-making to address health and social service integration challenges within and between governments.Methods. We performed a mixed methods case study to examine the integration of health and social services in a large US metropolitan area, including a city and a county government. Analyses incorporated annual budget data from the city and the county from 2009 to 2018 and semistructured interviews with 41 key leaders, including directors, deputies, or finance officers from all health care-, health-, or social service-oriented city and county agencies; lead budget and finance managers; and city and county executive offices.Results. Participants viewed public health and social services as qualitatively important, although together these constituted only $157 or $1250 total per capita spending in 2018, and per capita public health spending has declined since 2009. Funding streams can be siloed and budget approaches can facilitate or impede service integration.Conclusions. Health and social services should be integrated through greater attention to the budgetary, jurisdictional, and programmatic realities of health and social service agencies and to the budget models used for driving the systems-level pursuit of population health.

Evaluation of the National Institute for Health and Care Excellence Diagnostics Assessment Program Decisions: Incremental Cost-Effectiveness Ratio Thresholds and Decision-Modifying Factors.

OBJECTIVES: The National Institute for Health and Care Excellence (NICE) Diagnostics Assessment Programme (DAP) evaluates the cost-effectiveness of diagnostic technologies. A decision-making process benchmarking the incremental cost-effectiveness ratio (ICER) against a threshold while considering decision-modifying factors is common to NICE evaluations. This study investigated whether DAP decisions are consistent with the ICER thresholds described in the DAP manual, and to assess the impact of decision-modifying factors. METHODS: DAP evaluations published before March 2018 were reviewed, and the following items were extracted: diagnostic technologies evaluated, decision problems assessed, Diagnostics Advisory Committee (DAC) decisions, incremental quality-adjusted life years (QALYs), incremental costs, ICERs considered to be most plausible by the DAC, and decision justifications. RESULTS: All 30 evaluations were reviewed; 8 were excluded because the DAC concluded there was "insufficient evidence" for decision making. In the remaining 22 evaluations, 91 decision problems were identified for further analysis, of which 52, 15, and 24 received "recommended," "not recommended," and "not recommended-only in research" guidance, respectively. The overall consistency rate of the DAC decisions with the £20 000/QALY threshold was 73.6%. Diagnostic technologies that were not recommended, despite an ICER less than £20 000/QALY, were associated with a larger number of decision-modifying factors favoring the comparator, versus recommended diagnostic technologies with ICERs less than £20 000/QALY. For technologies with ICERs greater than £20 000/QALY, the number of decision-modifying factors was comparable for positive and negative recommendations. CONCLUSIONS: Most DAP decisions were consistent with the ICER threshold. However, cost-effectiveness was not the only determining factor in decision making; recommendations also considered patient- and healthcare-centric factors and uncertainty.

Prioritizing Additional Data Collection to Reduce Decision Uncertainty in the HIV/AIDS Response in 6 US Cities: A Value of Information Analysis.

OBJECTIVES: The ambitious goals of the US Ending the HIV Epidemic initiative will require a targeted, context-specific public health response. Model-based economic evaluation provides useful guidance for decision making while characterizing decision uncertainty. We aim to quantify the value of eliminating uncertainty about different parameters in selecting combination implementation strategies to reduce the public health burden of HIV/AIDS in 6 US cities and identify future data collection priorities. METHODS: We used a dynamic compartmental HIV transmission model developed for 6 US cities to evaluate the cost-effectiveness of a range of combination implementation strategies. Using a metamodeling approach with nonparametric and deep learning methods, we calculated the expected value of perfect information, representing the maximum value of further research to eliminate decision uncertainty, and the expected value of partial perfect information for key groups of parameters that would be collected together in practice. RESULTS: The population expected value of perfect information ranged from $59 683 (Miami) to $54 108 679 (Los Angeles). The rank ordering of expected value of partial perfect information on key groups of parameters were largely consistent across cities and highest for parameters pertaining to HIV risk behaviors, probability of HIV transmission, health service engagement, HIV-related mortality, health utility weights, and healthcare costs. Los Angeles was an exception, where parameters on retention in pre-exposure prophylaxis ranked highest in contributing to decision uncertainty. CONCLUSIONS: Funding additional data collection on HIV/AIDS may be warranted in Baltimore, Los Angeles, and New York City. Value of information analysis should be embedded into decision-making processes on funding future research and public health intervention.

Partitioned Survival and State Transition Models for Healthcare Decision Making in Oncology: Where Are We Now?

OBJECTIVES: Partitioned survival models (PSMs) are routinely used to inform reimbursement decisions for oncology drugs. We discuss the appropriateness of PSMs compared to the most common alternative, state transition models (STMs). METHODS: In 2017, we published a National Institute for Health and Care Excellence (NICE) Technical Support Document (TSD 19) describing and critically reviewing PSMs. This article summarizes findings from TSD 19, reviews new evidence comparing PSMs and STMs, and reviews recent NICE appraisals to understand current practice. RESULTS: PSMs evaluate state membership differently from STMs and do not include a structural link between intermediate clinical endpoints (eg, disease progression) and survival. PSMs directly consider clinical trial endpoints and can be developed without access to individual patient data, but limit the scope for sensitivity analyses to explore clinical uncertainties in the extrapolation period. STMs facilitate these sensitivity analyses but require development of robust survival models for individual health-state transitions. Recent work has shown PSMs and STMs can produce substantively different survival extrapolations and that extrapolations from STMs are heavily influenced by specification of the underlying survival models. Recent NICE appraisals have not generally included both model types, reviewed individual clinical event data, or scrutinized life-years accrued in individual health states. CONCLUSIONS: The credibility of survival predictions from PSMs and STMs, including life-years accrued in individual health states, should be assessed using trial data on individual clinical events, external data, and expert opinion. STMs should be used alongside PSMs to support assessment of clinical uncertainties in the extrapolation period, such as uncertainty in post-progression survival.