Surgery Sequencing Coordination with Recovery Resource Constraints

Surgical practice administrators need to determine the sequence of surgeries and reserved operating room (OR) time for each surgery in the surgery scheduling process. Both decisions require coordination among multiple ORs and the recovery resource in the postanesthesia care unit (PACU) in a surgical suite. Although existing studies have addressed OR time reservation, surgery sequencing coordination is an open challenge in the stochastic surgical environment. In this paper, we propose an algorithmic solution to this problem based on stochastic optimization. The proposed methodology involves the development of a surrogate objective function that is highly correlated with the original one. The resulting surrogate model has network-structured subproblems after Lagrangian relaxation and decomposition, which makes it easier to solve than the impractically difficult original problem. We show that our proposed approach finds near-optimal solutions in small instances and outperforms benchmark methods by 13%–51% or equivalently an estimated saving of $760–$7,420 per day in surgical suites with 4–10 ORs. Our results illustrate a mechanism to alleviate congestion in the PACU. We also recommend that practice administrators prioritize sequencing coordination over the optimization of OR time reservation in an effort for performance improvement. Furthermore, we demonstrate how administrators should consider the impact of sequencing decisions when making strategic capacity adjustments for the PACU. Summary of Contribution: Our work provides an algorithmic solution to an open question in the field of healthcare operations management. This solution approach involves formulating a surrogate optimization model and exploiting its decomposability and network-structure. In computational experiments, we quantitatively benchmark its performance and assess its benefits. Our numerical results provide unique managerial insights for healthcare leadership.

Flexibility during the COVID-19 Pandemic Response: Healthcare Facility Assessment Tools for Resilient Evaluation

Healthcare facilities are facing huge challenges due to the outbreak of COVID-19. Around the world, national healthcare contingency plans have struggled to cope with the population health impact of COVID-19, with healthcare facilities and critical care systems buckling under the extraordinary pressures. COVID-19 has starkly highlighted the lack of reliable operational tools for assessing the level sof flexibility of a hospital building to support strategic and agile decision making. The aim of this study was to modify, improve and test an existing assessment tool for evaluating hospital facilities flexibility and resilience. We followed a five-step process for collecting data by (i) doing a literature review about flexibility principles and strategies, (ii) reviewing healthcare design guidelines, (iii) examining international healthcare facilities case studies, (iv) conducting a critical review and optimization of the existing tool, and (v) assessing the usability of the evaluation tool. The new version of the OFAT framework (Optimized Flexibility Assessment Tool) is composed of nine evaluation parameters and subdivided into measurable variables with scores ranging from 0 to 10. The pilot testing of case studies enabled the assessment and verification the OFAT validity and reliability in support of decision makers in addressing flexibility of hospital design and/or operations. Healthcare buildings need to be designed and built based on principles of flexibility to accommodate current healthcare operations, adapting to time-sensitive physical transformations and responding to contemporary and future public health emergencies.

How to Realize the Benefits of Point-of-Care Testing at the General Practice: A Comparison of Four High-Income Countries

Background: In some countries, such as the Netherlands and Norway, point of care testing (POCT) is more widely implemented in general practice compared to countries such as England and Australia. To comprehend what is necessary to realize the benefits of POCT, regarding its integration in primary care, it would be beneficial to have an overview of the structure of healthcare operations and the transactions between stakeholders (also referred to as value networks). The aim of this paper is to identify the current value networks in place applying to POCT implementation at general practices (GPs) in England, Australia, Norway and the Netherlands and to compare these networks in terms of seven previously published factors that support the successful implementation, sustainability and scale-up of innovations. Methods: The value networks were described based on formal guidelines and standards published by the respective governments, organizational bodies and affiliates. The value network of each country was validated by at least two relevant stakeholders from the respective country. Results: The analysis revealed that the biggest challenge for countries with low POCT uptake was the lack of effective communication between the several organizations involved with POCT as well as the high workload for GPs aiming to implement POCT. It is observed that countries with a single national authority responsible for POCT have a better uptake as they can govern the task of POCT roll-out and management and reduce the workload for GPs by assisting with set-up, quality control, training and support. Conclusion: Setting up a single national authority may be an effective step towards realizing the full benefits of POCT. Although it is possible for day-to-day operations to fall under the responsibility of the GP, this is only feasible if support and guidance are readily available to ensure that the workload associated with POCT is limited and as low as possible.

Common good in the era of data-intensive healthcare

In recent years, scholars studying data-intensive healthcare have argued that data-driven technologies bind together new actors and goals as part of healthcare. By combining the expectation studies with justification theory, this article adopts a novel theoretical perspective to understand how these actors and goals are enroled in healthcare. Drawing on a case study of Apotti, a Finnish social services and healthcare information system renewal project, the article shows how new emerging health data assemblages stress the aims of producing the common good in public healthcare. The project is studied by analysing interviews of the project’s key actors and various documents produced in the project. The paper shows how, in the collective expectations, the new information system is justified by multiple understandings of the common good, which might be contradictory with each other. Along with the established goals of improving public healthcare operations, the new information system is expected to empower clients and patients, audit and manage personnel, promote national digital social and healthcare service markets, provide better data and tools for research, and promote Finnish research and business in international competition. These expectations are not all based on the settled understanding of the common good of public healthcare as promoting health; the common good is also defined in other terms such as improving research, promoting markets and business, and making Finland famous and a leading country in the digital social services and healthcare field. These goals and expectations are purposely ambiguous to be loose enough to gain attention and maintain it even when the promises are not met. The paper identifies the ambiguity and plurality of the common good as strategies of data-intensive healthcare and raises concerns of how this might shape public healthcare in the future. As the plural understandings of the common good might not support each other, the paper calls for further assessments of how this will affect public healthcare’s core objectives and for seeking solutions that carefully balance the goals of the current and evolving multi-stakeholder environment of data-intensive healthcare.

Mohalla Clinic: A Case on Healthcare Service Operations and Quality

The study presents a case study on service operations and service quality aspects of Mohalla Clinics, the public healthcare service setups in the innermost densely inhibited, yet unserved urban neighbourhoods of National Capital Territory of Delhi. It also describes the scalability consideration of public healthcare services. The case presents analysis of operational challenges in delivery of public healthcare services in developing countries. It characterizes the public healthcare service offering by the elements of service package and illustrates the adoption of service blueprint as a tool for service process planning. Additionally, it allows to comprehend the phenomena of quality management in healthcare service delivery and adoption of technology-driven innovations in healthcare service delivery. The case illustrates the challenges of healthcare operations and health service design in the low-cost and high-volume environments.

A High-Fidelity Model to Predict Length of Stay in the Neonatal Intensive Care Unit

Having an interpretable, dynamic length-of-stay model can help hospital administrators and clinicians make better decisions and improve the quality of care. The widespread implementation of electronic medical record (EMR) systems has enabled hospitals to collect massive amounts of health data. However, how to integrate this deluge of data into healthcare operations remains unclear. We propose a framework grounded in established clinical knowledge to model patients’ lengths of stay. In particular, we impose expert knowledge when grouping raw clinical data into medically meaningful variables that summarize patients’ health trajectories. We use dynamic, predictive models to output patients’ remaining lengths of stay, future discharges, and census probability distributions based on their health trajectories up to the current stay. Evaluated with large-scale EMR data, the dynamic model significantly improves predictive power over the performance of any model in previous literature and remains medically interpretable. Summary of Contribution: The widespread implementation of electronic health systems has created opportunities and challenges to best utilize mounting clinical data for healthcare operations. In this study, we propose a new approach that integrates clinical analysis in generating variables and implementations of computational methods. This approach allows our model to remain interpretable to the medical professionals while being accurate. We believe our study has broader relevance to researchers and practitioners of healthcare operations.

Value configurations for balancing standardization and customization in chronic care: a qualitative study

Background Demands for both customization and standardization are increasing in healthcare. At the same time, resources are scarce, and healthcare managers are urged to improve efficiency. A framework of three value configurations – shop, chain, and network – has been proposed for how healthcare operations can be designed and organized for efficient value creation. In this paper, use of value configurations for balancing of standardization and customization is explored in the context of care for chronic mental conditions. Methods A typical case is presented to illustrate the manifestations of conflicting demands between customization and standardization, and the potential usefulness of the value configurations framework. Qualitative data were collected from managers and care developers in two focus groups and six semi-structured interviews, completed by a national document describing a care pathway. Data were coded and analysed using an insider-outsider approach. Results Operationalization of the balance between standardization and customization were found to be highly delegated and ad hoc. Also, the conflict between the two demands was often seen as aggravated by scarce resources. Value configurations can be fruitful as a means of discussing and redesigning care operations if applied at a suitable level of abstraction. Applied adequately, all three value configurations were recognized in the care operations for the patient group, with shop as the overarching configuration. Some opportunities for improved efficiency were identified, yet all configurations were seen as vital in the chronic care process. Conclusions The study challenges the earlier proposed organizational separation of care corresponding to different value configurations. Instead, as dual demand for customization and standardization permeates healthcare, parallel but explicated value configurations may be a path to improved quality and efficiency. Combined and intermediate configurations should also be further investigated.

Focusing Provider Attention: An Empirical Examination of Incentives and Feedback in Flu Vaccinations

Background. Influenza imposes heavy societal costs through healthcare expenditures, missed days of work, and numerous hospitalizations each year. Considering these costs, the healthcare and behavioral science literature offers suggestions on increasing demand for flu vaccinations. Yet, the adult flu vaccination rate fluctuated between 37% and 46% between 2010 and 2019. Aim. Although a demand-side approach represents one viable strategy, an operations management approach would also highlight the need to consider a supply-side approach. In this paper, we investigate how to improve clinic vaccination rates by altering provider behavior. Methodology. We implement and study a flu vaccine intervention among 145 clinics from nine different states. This intervention randomly assigned these clinics to a control group or one of two separate treatment arms that received either relative performance feedback or financial incentives. Results. We find clinics that received relative performance feedback outperformed all others: Our intervention led to a 12% increase in flu shots for this group of clinics. Moreover, we also find clinics in this group exhibit rank response behavior, specifically last-place aversion; in particular, clinics near last place outperform the corresponding control clinics by 23% points. Conclusion. Overall, we find that clinic-level performance feedback can effectively drive operational improvement. Even a small increase in the U.S. adult flu vaccination rate might confer hundreds of millions of dollars in societal benefits and prevents thousands of hospitalizations. We discuss the implications of our work for healthcare operations theory, healthcare providers, and healthcare administrators. This paper was accepted by Charles Corbett, operations management.