Bottom-up perspectives on hospital-wide patient flow – A multi-site qualitative study of solutions to organizational paradoxes

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Prior research suggests hospital-wide patient flow improvements can enhance efficiency but has largely neglected the insights of frontline healthcare professionals without managerial responsibilities. This study explores their perspectives on enabling efficient patient flow across hospitals. Methods: Semi-structured interviews were conducted with 15 nurses and 15 physicians at six Swedish tertiary and secondary care hospitals. A thematic analysis followed, based on inductive reasoning to identify meaningful subjects and themes. Results : Participants identified seven paradoxes hindering patient flow, linked to leadership, organizational design, routines, professional culture, and technology. These tensions intensify under operational stress and often lead to overtime or compromised care. Professionals emphasized the need for more aligned structures, clearer patient flow strategies, and performance metrics that support efficient transitions of patients. They advocated for more centralized coordination, better adherence to standardized routines, and investment in IT tools to improve decision-making. A critical finding is the gap between nurses’ understanding of patient flow and patient progression and their limited authority and mandates to progress patients, highlighting the need for stronger nurse-physician collaboration. Conclusions : Enhancing hospital-wide patient flow requires increased system-level coordination, better aligned hospital structures, and improved operational planning. The solutions proposed by frontline professionals also largely align with previously identified managerial strategies for improved hospital-wide patient flows, suggesting a shared understanding that could be leveraged to drive meaningful change. Healthcare Efficiency Productivity Throughput Frontline System-wide Improvement Challenges Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Background Healthcare systems worldwide are facing increasing pressure due to rising patient demand ( 1 ), chronic staffing shortages ( 2 ), and continuously increasing healthcare expenditures as a percentage of national GDP ( 3 ), limiting hospitals' ability to provide appropriate care at the right time ( 4 ). Previous research has highlighted the importance of improving patient flow to enhance hospital efficiency ( 5 ). Studies have shown that focusing more on the movement of patients through hospitals can lead to reduced length of stay (LoS), more efficient discharge processes, and better patient throughput ( 5 – 8 ). Beyond efficiency gains, enhancing patient flow has also been linked to improved medical outcomes, patient safety, and overall satisfaction ( 9 , 10 ). Several studies also highlight the need to take a hospital-wide view when addressing patient flow improvements, referring to the coordinated movement of patients through various stages of care, from admission to discharge, while ensuring efficiency and quality of service ( 11 – 14 ). However, research on how to enable efficient hospital-wide patient flows has centered on the views of healthcare managers and managerial strategies, with little attention given to the perspectives of frontline healthcare professionals who interact directly with patients throughout their hospital journey. Healthcare professionals, including nurses, physicians, and other clinical staff, play a crucial role in the daily management of patient flow. Their perspectives provide valuable insights into the practical challenges and opportunities for improving hospital-wide efficiency ( 14 ). However, previous research, focusing on managerial interventions, overlooks these frontline views and experiences, which oftentimes are central to the success of improvement projects ( 15 – 17 ) and may provide valuable perspectives on how flow strategies should be implemented in practice. Given that hospitals are complex organizations with often competing departmental objectives ( 18 – 20 ), understanding the enablers and barriers to effective patient flow from a healthcare professional's standpoint is essential for creating sustainable improvements ( 15 , 21 ). Therefore, this study aims to explore the perspectives of healthcare professionals, without managerial responsibilities, on how to enable efficient hospital-wide patient flow. Specifically, it examines the factors they identify as hindrances and enablers to improving flow across departments and along care pathways. By incorporating their insights, this research aims to contribute to a more comprehensive understanding of hospital-wide patient flow challenges and potential solutions, ultimately supporting the development of more effective and contextually relevant hospital-wide strategies. To address this aim, a multi-site interview study has been conducted with physicians and nurses at six Swedish hospitals to explore their views on what is preventing or enabling an efficient hospital-wide patient flow and to understand their perspectives on how to improve the flow of patients across their organizations. Healthcare organizations often function as "job shops," where autonomous departments provide specialized services to address specific medical issues ( 22 , 23 ). Depending on the severity of their condition and treatment needs, patients referred to a hospital may visit one or several specialized departments. Patient flow across hospitals is often viewed in terms of process throughput, how quickly patients move through the system from admission to discharge, with the goal of improving efficiency and productivity ( 5 , 7 , 24 ). Effective flow management, therefore, relies on minimizing process delays, with Length of Stay (LoS) serving as a key metric that reflects the duration of a patient's hospital stay, influenced by both medical complexity and operational inefficiencies ( 5 , 25 ). However, many stakeholders within the patient care pathway prioritize their own departmental efficiency over the broader hospital-wide flow, inadvertently creating bottlenecks ( 26 , 27 ). These bottlenecks, whether administrative delays, inefficient clinical handovers, or resource shortages, can escalate costs, compromise care quality, and increase risks such as hospital-acquired infections and complications ( 7 ). To enhance patient flow, hospitals must address these inefficiencies by reducing errors, streamlining coordination, and implementing joint capacity planning ( 13 , 14 , 28 ). One of the most pressing challenges contributing to these inefficiencies is hospital overcrowding ( 4 , 9 ). Overcrowding is particularly evident in Emergency Departments (EDs), where a lack of available inpatient beds leads to delays in patient transfers. This 'blocking' effect not only prolongs ED wait times but also forces patients into inappropriate wards, where staff may lack expertise in managing their specific conditions, ultimately affecting care quality ( 5 , 25 ). Additionally, hospital overcrowding occurs when admissions exceed available capacity, leading to overutilized beds and occupancy rates exceeding 100%. Persistent overcrowding lengthens throughput times, increases LoS, and exacerbates staff burnout ( 4 , 9 ). To mitigate these issues, hospitals must focus on effective bed management strategies and LoS optimization, ensuring efficient patient movement while maintaining high standards of care ( 6 , 7 , 12 , 14 ). While systemic strategies are crucial for improving patient flow, the perspectives of front-line healthcare staff provide essential insights that may not always be visible to hospital administrators. Studies suggest that nurses, junior doctors, and other hands-on staff are often best positioned to identify workflow disruptions, communication breakdowns, and operational inefficiencies in real-time ( 29 ). For example, they frequently encounter delays in diagnostic procedures, unpredictable surges in patient volume, and resource shortages, allowing them to pinpoint critical bottlenecks ( 30 ). Integrating front-line feedback into patient flow strategies aligns with the principles of bottom-up healthcare improvement, which emphasize that staff engagement in process redesign leads to more sustainable and effective interventions ( 31 ). Research has shown that hospitals that actively incorporate staff perspectives experience reduced wait times, improved bed turnover, and higher job satisfaction ( 21 ). A more integrated approach, one that combines managerial oversight with front-line expertise, is likely to be the most effective strategy for optimizing patient flow ( 15 – 17 ). By incorporating the insights of front-line staff with existing knowledge, healthcare institutions can develop more pragmatic and adaptive strategies that account for real-world constraints. Ultimately, improving patient flow reflects a fundamental challenge in healthcare management: balancing efficiency with quality of care. On one hand, hospitals strive to enhance productivity by reducing process times and increasing throughput; on the other, they must uphold high clinical standards to ensure patient safety and well-being. This tension is particularly evident among front-line professionals, who must navigate these competing demands while delivering high-quality care and ensuring timely patient progression along their treatment pathways. This paper extends previous research on barriers ( 32 ) and solutions ( 13 ) to achieving efficient hospital-wide patient flows. Building on the process categories proposed by Holweg et al. ( 33 ), Åhlin et al. ( 32 ) developed a comprehensive hospital-wide process model that identifies five key themes of barriers patients may encounter as they navigate the hospital system. These themes are: entry, related to patient admission into the hospital; transfer, involving the movement of patients between clinical departments; internal, concerning care processes within individual clinics or departments; management system, related to the hospital-wide coordination and control of patient flow; and discharge, linked to the transition of patients out of the hospital. These themes are visually represented in Fig. 1 , below. The model offers a holistic view of patient progression from admission to discharge, encompassing both core hospital processes and supporting functions. Additionally, Åhlin et al. ( 13 ) developed a framework to outline the key obstacles and solutions to achieving efficient hospital-wide patient flows, see Fig. 2 . This framework presents 12 primary barriers and 15 associated root causes, systematically categorized across the five overarching themes. It also proposes 50 potential solutions, organized into eight summarizing categories. They describe the importance for hospitals to align their organizations; build coordination and transfer structures; ensure physical capacity capabilities; develop standards, checklists, and routines; invest in digital and analytical tools; improve their management of operations; optimize capacity utilization and occupancy rates; and seek external solutions and policy changes. Serving as a foundational reference, this framework informs the present study, which explores the perspectives of healthcare professionals without managerial responsibility. By integrating these insights, this study aims to provide healthcare managers, policymakers, and decision-makers with a deeper understanding of the challenges faced and offer appropriate strategies for improving hospital-wide patient flow. Methods Design In this study, a deductive methodological approach was employed, using previous research as a foundation to extend the framework for efficient hospital-wide patient flows presented by Åhlin et al. (13), with new perspectives. This framework informed both the data collection method and the analysis of the study subjects' environment, challenges, and contextual factors. However, a thematic analysis of the collected data was also conducted using an inductive research approach to thoroughly explore the subjective perspectives of the study participants, as recommended by Braun and Clarke (34), and Dixon and Woods (35). This approach was chosen instead of predefining categories based on prior research. Finally, the emerging themes from the thematic analysis were integrated back into the framework to refine and expand its applicability. Data Collection In conducted in-depth, semi-structured interviews as the primary data collection method, following an interview guide (see Appendix A) to ensure consistency across interviews while allowing participants the flexibility to freely share their perspectives (36). The interview questions were designed to explore the barriers and enablers of hospital-wide patient flow while remaining open to emergent themes and new insights. Hospitals were selected through purposeful sampling to ensure a diverse representation of healthcare professionals from both secondary care (services provided by medical specialists, often at hospitals, who in general do not have the first contact with patients) and tertiary care (highly specialized care delivered in a hospital or similar care setting) (37). Three tertiary care hospitals and three secondary care hospitals were included in the study. Initial contact was made with the general directors of the selected hospitals, who were provided with information on the study’s purpose and asked to facilitate access to nurses and physicians actively engaged in patient flow management. Nurses and physicians were chosen as study participants, as they represent the two predominant healthcare professions most directly involved in patient flow. Upon receiving the study invitation, the general directors referred the research proposal to relevant department managers, who subsequently identified and facilitated contact with eligible participants. To capture perspectives from different hospital settings, healthcare managers were asked to recruit participants from emergency settings (EDs), surgical settings (surgical clinics, inpatient care units, and operating units (ORs)), and medical settings (medical clinics and inpatient care units). Eligibility criteria required that participants (i) had no managerial responsibilities and (ii) were not newly employed. Each hospital provided five participants, with one or two individuals from each setting, resulting in a total of 30 interviews conducted between May and October 2023, see Table 1. No participant chose to withdraw from the study. To ensure transparency, the interview guide was shared with all participants in advance. Interviews were conducted online via Zoom by a single researcher, with each session lasting between 55 and 70 minutes. Table 1 : Interview study participant list Data Analysis During the interview process, extensive notes were taken, and early potential themes were identified. This was followed by an open coding of the verbatim transcripts, aiming to capture all perspectives shared by healthcare professionals regarding the factors that either hinder or facilitate hospital-wide patient flow. Each code was classified as either a barrier or an enabler to ensure a comprehensive representation of viewpoints. The coding process followed an iterative approach, with emerging themes continuously analyzed to refine categorizations and identify patterns. This ensured that the analysis remained grounded in empirical data rather than being constrained by pre-existing frameworks. Once all open codes were established, they were aggregated into broader themes, progressing toward higher levels of abstraction. Toward the final stages of analysis, however, it became apparent that the most striking characteristic of the thematic patterns was paradox. Time and again, healthcare professionals articulated an ideal vision of how things should be, while simultaneously describing experiences that starkly contrasted with these ideals. They expressed core values intended to guide the development of healthcare organizations, yet the resulting realities often contradicted those very principles. Consequently, it felt compelling to explore literature on how to understand paradoxes and contradictions within organizations. Paradoxes or contradictions, as phenomena, are repeatedly found as leaders address fundamental questions on how to design and develop organisations, establishing boundaries that create distinctions and dichotomies (38). In the process of forming organizations, Smith and Lewis (39) note that “leaders must decide what they are going to do, how they are going to do it, who will be responsible for it, and within what timeframe. By defining their objectives, leaders simultaneously establish what falls outside their scope.” This process clarifies strategic goals while also generating tensions, such as global versus local priorities, social versus financial values, loose versus tight coupling, centralization versus decentralization, and flexibility versus control. Paradoxes can be understood as “contradictory yet interdependent elements that exist simultaneously and endure over time” (39). In other words, they represent tensions that emerge within organizations due to competing demands (40). In their influential paper, Smith and Lewis (39) introduce a dynamic equilibrium model of organizing, offering a step toward developing a broader theory of paradoxes, see Figure 3. The model underscores some key aspects. First , paradoxical tensions within organizations exist both in latent and salient forms. Two , responses to these tensions involve cycling through different management approaches. Three, consequences or influences of these management strategies on sustainability. While tensions persist within organizational frameworks, they may remain dormant, unnoticed, or overlooked until external conditions or cognitive efforts highlight their contradictory and interconnected nature. When latent tensions surface, they become more pronounced, leading organizational members to directly experience their conflicting and inconsistent characteristics. Smith and Lewis (39) argue that environmental factors, specifically plurality, change, and scarcity, transform latent tensions into salient (visible) ones. Plurality refers to the coexistence of multiple perspectives in environments where power is dispersed (41). This diversity amplifies uncertainty, revealing clashing objectives and misaligned processes. Similarly, change introduces fresh opportunities for sensemaking as individuals navigate conflicting short- and long-term priorities (42) alongside competing yet interdependent roles and emotions. Lastly, scarcity pertains to constraints on resources, whether time, finances, or human capital. As leaders make allocation decisions, these limitations intensify the struggle between competing yet interlinked alternatives (43). Collectively, plurality, change, and scarcity push the boundaries of rational decision-making and strain organizational systems. Consequently, individuals are more likely to fragment interconnected elements into either/or choices, actions, and interpretations, obscuring their inherent interdependence. As the data analysis progressed, it became clear that the most compelling aspect of the dataset was the exploration of paradoxes. Consequently, the dynamic organizing model of paradoxes proposed by Smith and Lewis (39) was applied to the data set. Within this framework, the first aspect of the model was used, addressing the emergence and recognition of paradoxical tensions, as well as the last step, which examines strategies for resolving these tensions. The third step was deliberately omitted, which explores the cyclical responses to paradoxes, as the primary objective was to identify existing barriers and evaluate optimal strategies for their resolution rather than analyzing how organizations transition between different management approaches over time. Accordingly, in the subsequent data analysis, the paradoxical tensions revealed by the previously identified themes of barriers were examined. How these tensions were initially latent and what factors rendered them salient where also investigated. Finally, the solutions proposed by healthcare professionals were explored, aiming to resolve these paradoxical tensions in the context of enabling efficient hospital-wide patient flow. Results This study identifies seven paradoxes experienced by frontline healthcare professionals associated with hospitals’ efforts to enable efficient hospital-wide patient flow, see Table 2 . The characteristics of each paradox are outlined below and supported by representative quotes from the interviews. In total, the interviews generated 650 unique opinions and recommendations, which were synthesized into these seven paradoxes. Table 2 presents a structured overview, beginning with a description of each paradox and the associated latent tensions. It then outlines the salient tensions that emerge and the factors that transform these tensions from latent to salient. Table 2 : Seven paradoxes to efficient hospital-wide patient flow Paradox #1: System-wide patient trajectories but local patient focus There is a divergence of opinions among healthcare providers regarding whether a clear flow-oriented focus exists within their hospital. Some argue that, at the local level, their unit actively engages with flow-related issues and seeks to identify flow-related bottlenecks. However, many others believe that such a focus is absent and that they do not work with flow principles at all. Some participants perceive that hospital management discusses patient flow but that these discussions seldom transform into something tangible for frontline healthcare professionals. “I imagine a bunch of managers having a picture of how the patient flow should be done. But how is it communicated down? In my world, it doesn't seem to be. It doesn't seem to trickle down to all the different units, but gets stuck somewhere along the way.” – [nurse, emergency department, tertiary care hospital, case A] The lack of a clearly defined vision from the hospital management regarding patient flow improvements is a common concern among many participants, and they desire a clearer strategy translated into concrete implications for different departments, units, and divisions within the hospital. The lack of a flow strategy hampers collaboration with adjacent units on flow improvements due to the ambiguity surrounding its meaning, implementation, and objectives. It also becomes unclear what to prioritize, and how to prioritize, related to the flow of patients. The missing hospital-wide approach becomes clear when facing overcrowding, and protectionism or patient responsibility avoidance appears. It also becomes evident when clinics choose to expand their services without considering consequences for others and new and many times problematic constraints or bottlenecks appear. Therefore, several study participants expressed a desire for the hospital to develop an increased and clearer central coordination and effectively communicated strategy or framework to facilitate improved patient flow throughout the entire organization. “The general goal is for the flow of patients to go quickly but each department gets to develop its own routines. However, no one connects them across the hospital, so that it is really a working plan, put in place in different departments or different parts of the hospital, to really provide some improved flow. That is what we would need” – [physician (surgeon), surgical clinic, secondary care hospital, case D]. Previous research has demonstrated how most patient flows within hospitals are interconnected, as they rely on the same resources to facilitate processes and advance patients along their care journey. The allocation of available resources (staff, equipment, hospital beds, etc.) to appropriate departments and an optimal distribution among patient groups necessitates central coordination, which is often insufficient. Physicians and nurses confirm this and highlight a lack of effective central coordination of shared resources. The coordination of hospital beds is typically managed by an ED-based bed coordinator who has limited authority over patient placements and faces significant challenges navigating between clinics, which often attempt to avoid assuming responsibility for a patient, suggested to them. Whether undertaken by a bed coordinator or a senior physician (on-call hospitalist), the task of overseeing patient placements across the hospital is frequently described as stressful and unrewarding. Paradox #2: Advocating for less rigidity, but specialization builds rigidity Nurses and physicians often oppose the thought of standardizing healthcare processes, arguing that the healthcare system must be able to address each patient's unique set of problems. However, many participants perceive that there is an ongoing strong trend towards standardization driven mostly by the increasing specialization of medical expertise but to some extent also by nursing. They observe that their patients increasingly seek healthcare with multiple, concurrent symptoms and diagnoses and that in the past, it was easier than today to categorize patients into different groups and assign them to the most appropriate department for care. The increasing specialization has, however, made transfers of patients between hospital departments increasingly difficult, as many departments are reluctant to accept patients with multiple conditions that fall outside their specialized scope. Departments prefer to treat only those patients for whom they have specialist expertise. This protectionism is also most strongly experienced when the hospital is facing overcrowding when fast transfers are more important than ever. This specialisation trend exacerbates the challenge of moving patients across the hospital in a swift and timely fashion. “Take as an example an oncology patient with brain metastases quite far along in their disease, who has palliative treatment in its final stages. They come into the emergency room with neurological problems and a headache. All signs that there is a process in the brain. Then there can be a tug of war, or rather a push and pull between the neurologist and oncologist about who should take care of the patient. When the oncologist says that this is an isolated neurological problem and the neurologist says that this is a complex oncological disease with an expected outcome that the oncologist can absolutely treat. But, the oncologist is full. The neurologist has one place left. It can be a discussion that can last for hours while the patient remains in the emergency room.” - [physician, emergency department, tertiary care hospital, case F] The same dilemma also applies to surgical procedures, where surgeons continually seek to sub-specialize, resulting in an even narrower patient group they are willing to operate on. Today, planning the surgical program comes with significant scheduling challenges as there is little operational flexibility. In the end, there is little margin if anyone is sick or if any patient group is overrepresented, increasing the risk for canceled surgeries. Despite this, there is a well-established belief that greater specialization improves medical quality. However, increased specialization also necessitates that patient cohorts become more homogeneous and care processes more standardized, something that healthcare professionals generally resist. This tension gives rise to a standardization paradox. Rather than the healthcare profession adapting to the needs of the patient, the patient must conform to the structures of the healthcare profession. This approach is inherently at odds with the goal of providing individualized and tailored care to complex and multi-morbid patients who present in emergency settings or are scheduled for surgery. “The trend in the hospital, and healthcare in general, towards becoming increasingly specialized means that it is a fairly fine-meshed net for patients to get through to get the care they need, and the flow of patients is slowing down.” - [physician, medical clinic, tertiary care hospital, case B] Paradox #3: Mandate with doctors, but flow understanding with nurses Healthcare professionals operate based on various underlying logics that influence their reasoning, work ethics, and areas of focus. A notable distinction frequently observed by both physicians and nurses is that nurses often possess a more intuitive understanding of patient flow compared to physicians. Nurses appear to be better trained in considering the patient’s entire care trajectory and the need for coordination to ensure continuous progression along this journey. In contrast, physicians tend to concentrate more on the immediate clinical situation, making medical assessments and treatment decisions based primarily on the patient's current condition, while also prioritizing acute cases among patients with diverse needs. “There is a lot to remember to do and it feels very extensive. It is very complex. At the same time, we are faced with this problem that we cannot do everything with everyone. At the same time, we are not used to thinking about flow either. If I do this for this patient now, is someone else being displaced? We are not trained in it that much.” – [physician, medical clinic, secondary care hospital, case C] A key challenge arises when decisions regarding patient progression must be made, as the authority to do so rests solely with the physician, given their legal responsibility for the patient. The absence of a comprehensive understanding of patient flow can lead to unnecessary congestion and bottlenecks, where less medically urgent patients remain in the system, causing significant delays in overall patient movement. This issue is particularly pronounced in inpatient wards, where patients are typically prioritized from the most to the least critically ill. Consequently, ward rounds often conclude with patients who are merely awaiting discharge orders. Nurses, who are essential in assisting physicians with coordinating patient flow, bear a heavy and sometimes impractical workload, despite lacking the authority to influence progression. Frustration escalates when patients remain in the hospital longer than necessary, and discharge plans are not met. Several participants emphasized the need for stronger collaboration between professional groups to facilitate knowledge exchange, with some suggesting that nurses should be granted greater authority in managing patient flow. Similarly, in surgical scheduling, the responsibility for determining the timing of procedures lies with the surgeons. However, there is often a lack of awareness regarding the downstream effects of the surgical schedule on postoperative units and, ultimately, inpatient care. The impact of this is particularly felt on wards during periods of overcrowding, where increased congestion could be mitigated with a better understanding of downstream flow, ultimately reducing pressure and achieving a more balanced system. “The surgical program could really be designed more according to the consequences it has on our departments. It feels like the surgeons only plan surgeries based on medical priority and very rarely based on what benefits the flow the most. Patients have much more predictable treatment times than many seem to believe and thus the flow out could be much smoother.” – [nurse, medical ward, tertiary care hospital, case A] Paradox #4: Seeking workflow control, receiving workflow disorder Hospitals are frequently characterized as among the most complex organizations in existence. They manage the simultaneous care of large numbers of patients with diverse needs, ranging from acute and semi-acute to scheduled and chronic conditions, while delivering advanced treatments that require coordination across multiple medical specialties and the integration of sophisticated technological and clinical systems. Many physicians and nurses underscore the substantial cognitive burden placed on doctors, who are expected to retain and process vast volumes of information each day to oversee the progression of all patients under their care. This challenge becomes particularly acute during periods of overcrowding, when numerous critical decisions must be made concurrently under intense time pressure. It happens that I forget things, not because I'm careless, but there are many things to do at the same time. I have to focus on a task. In many cases you don't even have the opportunity to take notes. It can happen that I get a call and I'm standing in a sterile gown operating or doing something. It means a lot of stress, in some cases an extremely high workload, and basically almost every day I feel that I'm not satisfied with certain parts of my work. I'm fully aware that I don't have time to do everything that needs to be done. I simply forget certain things. – [ physician (surgeon), surgical clinic, secondary care hospital, case E) The substantial volume of information that must be retained often results in critical details being overlooked, necessitating that nurses devote considerable time to supporting physicians with prioritization and coordination tasks. “Doctors sit and read beforehand, but might not take into account checking whether the patient has anything else planned, and then it's a bit of luck whether the patient is in the room or not. Quite a lot is up to me anyway, to keep track of different parts and sort of coordinate a bit so doctors don’t miss important things. Then, we also have social coordinators on the ward who help with care planning and such. And when they are involved, they can be a good support. Either way, if we believe that a patient is going home on a certain date, then we have to think about preparing many things, and unfortunately, many things fall between cracks.” - [nurse, medical ward, secondary care hospital, case D] Despite various efforts, maintaining a clear overview of care priorities remains challenging, particularly during periods of high stress and overcrowding. Under conditions of cognitive overload, healthcare professionals tend to focus primarily on the most critically ill patients. Both nurses and physicians report the negative consequences of concentrating too much responsibility in the hands of one or a few individuals, especially when patients remain hospitalized beyond their expected discharge dates. Participants consistently emphasized the need for a more equitable distribution of responsibility, along with system-level support capable of visualizing patient care processes and identifying subsequent steps in the care trajectory. Such tools, they argue, would reduce reliance on individual memory and enhance overall workflow efficiency. Paradox #5: Seeking routine compliance, receiving routine negligence Like all operational elements, processes are subject to variation, which should be minimized to enhance performance (Holweg et al., 2018). Variation introduces unpredictability, impairs effective planning, and contributes to deficiencies in quality. One strategy for reducing variation involves the implementation of clear routines and standardized procedures, consistently followed by all personnel. Healthcare exemplifies a routine-driven sector, where the use of checklists and treatment protocols is intended to safeguard high standards of medical care. However, findings from this study reveal that most participants perceive a lack of well-established routines and, more critically, a widespread failure to adhere to those that do exist. Participants emphasized that healthcare professionals, particularly physicians, frequently deviate from standard procedures and make autonomous decisions. While professional autonomy is widely regarded as essential to high-quality care, such deviations are often difficult for colleagues to interpret and can lead to frustration. This autonomy also diminishes the overall predictability of the healthcare system for both staff and patients. A particularly concerning issue raised was the tendency of physicians to revise treatment plans during shift changes, resulting in redundant tests, additional examinations, and prolonged hospital stays. “A physician decides something for a patient at the end of the week. Then another one comes along and says something completely different and changes the plans. The new physician wants to make his own opinion and assessment of the patient. It might take a day or two to do that. And then everyone starts with something new, some new thought. And then the next week comes along with some new doctor again who wants to form their own opinion about the patient. So I think we have a lot to work with there, on continuity.” – [nurse, medical ward, tertiary care hospital, case B] Experienced colleagues who work closely with the same patients often report seeing little tangible benefit from repeated interventions; instead, they perceive that physicians, in particular, tend to prioritize their own clinical judgment over adherence to established guidelines. During periods of hospital overcrowding, when staff must collaborate intensively to manage the workload, sudden and seemingly arbitrary changes in treatment plans can be especially disheartening. One commonly cited example involves surgeons routinely underestimating the duration of procedures, leading to operating room schedules that frequently run over time, an issue that generates considerable frustration among colleagues. These practices contribute to an already strained healthcare system becoming even more unpredictable. As a result, many healthcare professionals emphasize the need for stricter adherence to standardized routines, arguing that such compliance would improve not only patient flow management but also the overall quality of care. “Surgeons have been given operating blocks to deal with but plan surgeries so that they will be finished before the end of the block time even though they have never performed a surgery within the intended time. Then we have to work overtime. We usually realize this immediately when we see the schedule for the day. It doesn't feel great that the original planning and staffing schedules are not respected. It creates a lot of variation, unpredictability, and overtime work for the unit.” – [nurse, operating room, tertiary care hospital, case F] Paradox #6: Believing in proactivity, working reactively Healthcare operates within a dynamic environment, where patients’ conditions may improve or deteriorate rapidly, necessitating corresponding adjustments in healthcare operations. Professionals recognize that plans often shift throughout the course of a single shift, both with respect to patient treatment and the optimal allocation of resources such as staff, treatment rooms, and equipment. However, a recurring concern expressed in several interviews is that the planning horizon is often too short. Greater foresight in operational planning is seen as a potential enabler of more efficient patient flow. Frustration arises when patients remain in care longer than necessary simply because short-term planning prevents timely transitions or discharges. “In the best of worlds, it would have been that we think more about the continuous patient trajectory, and I think it would have been better if you had a plan for the patient already when they are admitted. But unfortunately, it often happens that we only plan half days ahead, until next round, and after the round, and then until the following afternoon.” – [nurse, medical ward, secondary care hospital, case C] Healthcare personnel perceive hospital bed coordination as predominantly reactive, lacking a strategic role in optimizing patient flow across the hospital or in planning patient movement with consideration for downstream effects. Many physicians and nurses express the view that a more clearly defined coordination structure, endowed with greater authority, would support more efficient transfers between the emergency department, acute care units, intensive care units, and hospital wards. Although many bottlenecks are predictable, the absence of centralized coordination often results in recurring delays in patient progression, which several respondents described as disheartening. Interviewees also emphasized that patient care trajectories are more predictable than commonly assumed and suggested that a proactive, forward-looking approach to planning could significantly improve flow. Furthermore, new technologies, or innovative applications of existing technologies, were identified as potential tools to support healthcare professionals in adopting a more anticipatory strategy, enabling more accurate assessments of patient care trajectories through the application of statistical analysis. ”Patients come in clear prototypes, and you can determine with a fair amount of certainty how many days they will need to be cared for. And with new technology, we should be even better at being able to determine when a patient is likely to be discharged. This allows us to be much more proactive, than we are many times today, in care planning several days before discharge, with everything that needs to be done.” – [physician (surgeon), operating room, secondary care hospital, case D] Paradox #7: Emphasizing statistical feedback, only not for flow Improving performance necessitates an understanding of current performance levels. While healthcare providers routinely engage in extensive measurement, particularly through the continuous monitoring of medical quality outcomes, which is central to healthcare operations and development, the use of metrics related to patient flow appears inconsistent. When asked whether they utilize indicators reflecting patient flow performance, physicians and nurses offered varied responses. Some reported using flow-related metrics, such as Length of Stay (LoS), average discharge time, and the average number of discharges before noon. Others, however, indicated that they do not employ any measures specifically linked to patient flow. “No, we no longer get any information about whether we perform well or badly or how many patients we are discharging at a certain time. I actually have no idea about anything related to patient flow, we get no feedback.” – [nurse, surgical ward, secondary care hospital, case E] A few respondents reported receiving feedback from management, although this occurs infrequently. Notably, all participants working in units that employ flow metrics perceived these measures as lacking motivational value. While the metrics themselves were not viewed as inherently problematic, the associated performance targets were frequently described as unrealistic and largely unattainable. Consequently, participants expressed low motivation to engage with these measures and reported little effort to meet the prescribed targets. “Even though there are a lot of things measured in association with surgical procedures related to the flow of patients, few or no one directly follows them or cares. The goals are not realistic, either. They are simply not motivating. That is a problem .” – [physician (anaestesiologist), operating room, tertiary care hospital, case F] The consequences of failing to measure patient throughput performance often become apparent when new management or hospital leadership express dissatisfaction with production outcomes and introduce new performance targets or staff-to-patient ratios. In such cases, the unit may lack the necessary data to assess its current capabilities, determine the feasibility of the new requirements, or predict the impact of these changes on patient flow performance. Resolutions to paradoxes This study identifies seven paradoxes that impede healthcare professionals' efforts to improve patient flow across hospital systems. While illuminating such paradoxes and contradictions in healthcare delivery is essential, the principal aim of this research is to deepen the understanding of hospital-wide patient flow challenges and explore potential solutions. Drawing on the perspectives of frontline healthcare professionals, those without formal managerial responsibilities, whose voices are frequently underrepresented in the literature ( 15 – 17 ), the study presents a series of proposed resolutions to the identified paradoxes, see Fig. 4 . First , participants advocate for stricter adherence to routines, greater continuity in scheduling, and enhanced transparency in planning processes to foster compliance and create a more predictable work environment. Second , they emphasize the importance of centralized flow coordination, a clearly articulated patient flow strategy, and strengthened inter-organizational collaboration to promote a more integrated, system-wide perspective on patient flow. Third , to reduce systemic rigidity, respondents suggest expanding the competence profiles of healthcare staff and establishing a centralized mandate for patient placement. Fourth , improved control over workflows is seen as achievable through the deployment of advanced IT system support and broader distribution of responsibilities among clinical staff. Fifth , a more proactive approach to care delivery is deemed attainable through increased central flow coordination, the implementation of supportive IT solutions, and the advancement of forward-looking patient flow planning. Sixth , participants stress the need for more visible and engaged leadership, the development of meaningful performance metrics, and the alignment of these metrics with day-to-day operations to enhance their motivational impact. Seventh , they call for improved understanding of patient flow dynamics among physicians, a more prominent role for nurses in flow decision-making, and strengthened interprofessional collaboration to enhance collective performance in managing flow progression. Discussion Improving patient throughput at hospitals is crucial to meeting the growing demands of future healthcare and prior research highlights that enhanced patient flow is a key factor in boosting hospital productivity ( 5 – 8 ). As patients increasingly navigate complex care pathways involving multiple professionals, departments, and administrative units, a system-wide perspective has become essential ( 11 – 14 ). However, most existing studies on hospital-wide patient flow have focused on managerial perspectives and strategies, largely overlooking the experiences of frontline healthcare professionals, those who interact most directly with patients throughout their hospital journey. This study present that although healthcare organizations often articulate a clear idea for achieving efficient patient flows, healthcare professionals experiences frequently diverge from those ideals. They acknowledge organizational objectives and values concerning patient flow, yet routinely encounter situations that contradict them. Based on these findings, this study identifies seven paradoxes associated with enabling efficient hospital-wide patient flows in which non-managerial staff at large hospitals perceive direct conflicts among the hospital’s stated values, philosophies, and objectives. These contradictions contribute to a work environment characterized by frustration, stress, and unpredictability. Paradoxes in patient flow have been previously studied by Kreindler ( 14 ), who examined systemic barriers by conducting interviews with a large number of hospital managers within a Canadian region. The study identified three key paradoxes: ( 1 ) "initiatives improve parts of the system but fail to address underlying systemic constraints," ( 2 ) "local innovation clashes with regional integration," and most notably, ( 3 ) "rules that improve service organization for my patients create obstacles for yours." A common theme among these paradoxes, as identified by Kreindler ( 14 ), is their emergence largely due to the absence of a system-wide approach to patient flow and its optimization. Enhancements in one part of the system often create unintended challenges elsewhere, and such improvements may not align with the workflows of the broader system. This study confirms but also refines these paradoxes, emphasizing that while autonomy benefits independent actors, it can disadvantage those who depend on others. Similarly, while specialization alleviates burdens for some, it often shifts the workload onto others. This study highlights the strong institutional belief in the capacities of physicians, leading hospitals to assign them mandates and decision-making responsibilities that they may not be equipped to fully comprehend or manage. Delegating certain physician responsibilities to other professional groups appears not only beneficial for patient flow but also advantageous for the professional development and effectiveness of physicians ( 44 , 45 ). These paradoxes further underscore the perspectives of many healthcare professionals, who argue for designing workflows based on patient movement rather than the rigid structures of medical specializations ( 6 ). Many professionals find the prevailing local focus on patient flow, coupled with a reactive rather than proactive organizational approach, increasingly outdated, especially in light of technological advancements and emerging organizational models that support a more anticipatory healthcare system ( 13 ). Finally, choosing not to measure patient flow, despite the centrality of medical quality in hospital performance, appears unwise. Patient flow directly impacts individual patients, facilitating faster transfers and reducing iatrogenic complications, while also improving healthcare system efficiency by increasing overall accessibility ( 10 , 46 ). Most of the paradoxes discussed above become visible to healthcare professionals when facing some form of scarcity, whether of beds, staff, space, or operating room (OR) time. Healthcare professionals frequently encounter resource constraints and often attribute inefficient patient flow to a lack of adequate resources. The emergence of bottlenecks is one of the most common indicators of systemic inefficiencies ( 7 ). For instance, when auxiliary beds are required due to ward overcrowding, deficiencies become apparent. Similarly, when OR cases consistently exceed scheduled capacity, forcing staff to work overtime for consecutive days, the limitations of the system become unmistakable. Paradoxes also arise in response to change, whether through modifications in routines, new regulatory requirements, or the expansion and restructuring of services. People are generally resistant to change, particularly when it is perceived as irrational or difficult to comprehend, which often brings paradoxes to the forefront ( 42 ). Additionally, some paradoxes emerge due to plurality, conflicting ideas, interests, or mandates, and decision-making processes ( 41 ). These tensions become evident when there is disagreement over where to place multimorbid patients or when a culture of professional autonomy leads to shifts in patient care trajectories with every change in staff. This study, however, underscores that many of these paradoxes, whether driven by scarcity, change, or conflicting interests, can likely be mitigated through enhanced system-wide collaboration, a deeper understanding of patient flow dynamics, and greater adherence to standardized routines and operational planning. These findings also align with previous research advocating for reducing unnecessary variation in healthcare processes to improve overall efficiency ( 13 ). This study offers a bottom-up perspective on solutions for improved hospital-wide patient flows that complements the patient flow improvement framework proposed by Åhlin et al. ( 13 ), which is grounded in the viewpoints of healthcare managers. The association between paradoxes and paradoxical resolutions presented in Fig. 4 , has, therefore, been linked to the solutions categories presented in the framework on hospital-wide patient flows (Fig. 2 ) by Åhlin et al ( 13 ) in a comparison of bottom-up and top-down solutions for the improvement of hospital-wide patient flows, see Fig. 5 . This comparison presents that frontline healthcare professionals largely align with senior management in their views on how to enhance hospital-wide patient flow. Similar to senior leaders, frontline healthcare professionals emphasize the importance of developing standards, checklists, and routines , as they highlight the need to improve adherence to routines and set schedules. They also see the benefits of building a coordination and transfer structure , as they highlight the need for central flow coordination and placement mandate, but also the need to expand and better use competencies among healthcare professionals to promote patient flow. Healthcare professionals also highlight the need for improving the management of operations by making production planning more transparent and proactive, and using more meaningful flow metrics, as well as making the management more visible and engaged in patient flow improvements. Aligning the organisation is seen as important, enabling clearer flow strategies, increased system-wide understanding of the patient flow, and stronger collaboration between both professional groups as well as inter-organisational units. Last, they also want hospitals to invest in digital and analytical tools to improve the support healthcare professionals can receive from IT systems in progressing patients along their care trajectories and to develop visible and better synchronized flow metrics across their organisations. Concerning the three categories without connections: optimize capacity utilization and occupancy rates , ensure physical capacity capabilities , and seek external solutions and policy changes , no paradoxes or paradoxical resolutions seem to be associated. The reason behind this is likely that they are associated with the factors rendering latent paradoxes salient instead of imposing organisational paradoxes on the patient flow. Smith and Lewis ( 39 ) explain that paradoxes evolve in the process of designing and forming organisations. In this study, healthcare professionals articulated an ideal vision of how to improve the flow of patients throughout their organisations, while simultaneously describing experiences that starkly contrasted with these ideals. The three top-down solution categories without connections to the bottom-up solutions seem to be more connected to needed resources (staff, beds, rooms, facilities) instead of work methods. Consequently, if these categories of solutions are met, i.e, when there is little resource scarcity, then the seven paradoxes identified in this study may remain latent without being rendered salient. A novel contribution of this bottom-up perspective lies in its focus on how healthcare professionals might reconfigure their roles, competencies, and responsibilities to better support patient flow. A critical issue identified is the misalignment between nurses’ understanding of flow dynamics and their lack of authority to influence patient progression decisions. There seem to be two paths ahead: either hospitals need to expand nurses’ mandates to progress patients along their care trajectories, or an enhanced collaboration between nurses and physicians becomes essential to ensure that flow-related knowledge is effectively translated into action, thereby improving overall patient throughput. Limitations and Future Research This study is subject to several limitations. Firstly, it relies on a single analyst. While employing multiple coders would have been preferable, rigorous participant validation ensured the integration of diverse perspectives. A well-structured, semi-standardized interview guide was utilized, facilitating a more consistent comparison across participants. Furthermore, the study’s robustness was enhanced by the substantial number of participants and the inclusion of six different hospitals, thereby strengthening the validity and generalizability of the findings. Another limitation pertains to the online format, as all interviews were conducted via Zoom. This virtual setting posed challenges in accurately capturing non-verbal cues such as body language and facial expressions, potentially constraining the comprehensive interpretation of participants’ responses. Additionally, the researcher’s background in Operations Management introduces inherent biases and preconceptions. This challenge is further reinforced by the researcher’s prior professional experience in a hospital setting, collaborating closely with doctors and nurses, which may have influenced their understanding of the participants’ challenges and perspectives. There are several promising avenues for future research. One potential topic is to investigate the differences in patient flow management and outcomes across hospitals, particularly in relation to the extent of authority and autonomy granted to nurses. Another area of interest is examining how a hospital-wide focus on patient flow is operationalized at various managerial levels, and how it can be tailored to be meaningful and motivating at each level of the organization. Finally, it would be valuable to explore the appropriate degree of independence and autonomy that healthcare professionals, especially physicians, should be granted. While such autonomy is often regarded as essential for efficient and responsive healthcare, it can also introduce confusion, inconsistency, and unpredictability in the delivery of care. Conclusions This study examines the perspectives of frontline healthcare professionals regarding the factors that hinder and facilitate hospital-wide patient flow. Nurses and physicians report experiencing significant contradictions between the ideals guiding how work should be carried out and the realities of how it is actually performed. The analysis identifies seven key paradoxes related to leadership and organizational structures, routines and procedures, professional culture, and the use of technology and performance metrics. These paradoxes become particularly pronounced under organizational pressure, during changes to work routines, when patient care is compromised, or when staff are required to work overtime. The study presents multiple strategies aimed at addressing these paradoxes and enhancing the overall flow of patients throughout the hospital. Frontline healthcare professionals largely align with senior management on strategies to improve hospital-wide patient flow, emphasizing the need for aligned structures, objectives, and performance metrics. They advocate for centralized coordination, adherence to standardized routines, and responsive hospital designs. Importantly, professionals highlight the need to redefine roles and empower nurses, addressing the gap between their flow-related knowledge and limited decision-making authority. Strengthening nurse-physician collaboration is essential to translating this knowledge into improved patient flow. Declarations Ethics approval and consent to participate This study has been conducted in Sweden according to Swedish laws and regulations and adheres to the Declaration of Helsinki. Participants were interviewed in their professional role, and no personal or sensitive information was obtained. According to the Swedish Ethical Review Act ( Lag om etikprövning av forskning som avser människor 2003:460 ), this study does not need ethical clearance by a Regional Ethical Review Authority as it does not include any primary empirical data on biological material or sensitive personal information. No ethics approval has consequently been applied for before conducting this study. Informed consent has been obtained from all participants, and all quotes have been approved by the party concerned before publication. Consent for publication Not applicable Availability of data and materials All datasets generated or analyzed during this study are included in the main manuscript [and its supplementary information files]. Competing interests The author declares that there are no competing interests concerning the material discussed in this manuscript. This accounts for interests of either financial nature (such as grants, consultancies, equities, or other employments) or non-financial nature (such as professional, personal relationships, or subjective beliefs). Funding The only source of funding has come from Chalmers University of Technology to support the author with a salary to conduct the research. Furthermore, Chalmers University of Technology has, in its role as sponsor, not in any way been involved in, nor interfered with the design, execution, or presentation of the research. Authors' contributions This study has been designed and conducted by one independent researcher. The manuscript has also only been written by the same independent researcher. The author of the manuscript is accountable for all aspects of the accuracy and integrity of the manuscript. The article is original and has not already been published in a journal and is not currently under consideration by another journal. The researcher agrees to the terms of the BioMed Central Copyright and License Agreement. Authors' information Department of Technology Management and Economics, Chalmers University of Technology, Vera Sandbergs Allé 8, Göteborg 412 96, Sweden References OECD EC. Healthcare at a Glance: Europe 2024: State of the Health in the EU Cycle. Paris; 2024. Stadhouders N, Kruse F, Tanke M, Koolman X, Jeurissen P. Effective healthcare cost-containment policies: A systematic review. Health Policy. 2019;123:71-9. Lorenzoni L, Martino A, Morgan D, James C. OECD Health spending projections to 2030. Report. 2019. Davis Z, Zobel C, Khansa L, Glick R. Emergency department resilience to disaster‐level overcrowding: A component resilience framework for analysis and predictive modeling. J Oper Manag. 2019;66(1-2):54-66. Johnson M, Burgess N, Sethi S. Temporal pacing of outcomes for improving patient flow: Design science research in a National Health Service hospital. J Oper Manag. 2020(66):35-53. 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Supplementary Files Table2.pdf Table1.pdf AppendixA.pdf Cite Share Download PDF Status: Published Journal Publication published 20 Feb, 2026 Read the published version in BMC Health Services Research → Version 1 posted Editorial decision: Revision requested 14 Jul, 2025 Reviews received at journal 02 Jul, 2025 Reviews received at journal 29 Jun, 2025 Reviewers agreed at journal 27 Jun, 2025 Reviews received at journal 27 Jun, 2025 Reviews received at journal 26 Jun, 2025 Reviewers agreed at journal 23 Jun, 2025 Reviewers agreed at journal 19 Jun, 2025 Reviewers agreed at journal 17 Jun, 2025 Reviewers invited by journal 13 Jun, 2025 Editor assigned by journal 11 Jun, 2025 Editor invited by journal 21 May, 2025 Submission checks completed at journal 20 May, 2025 First submitted to journal 20 May, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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(32)\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-6663600/v1/01461f4f57ab48404b0d2b46.png"},{"id":84857833,"identity":"dbcffafd-3c43-4bff-895e-83e859560467","added_by":"auto","created_at":"2025-06-18 06:27:12","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":188877,"visible":true,"origin":"","legend":"\u003cp\u003eThe patient flow improvement framework, Åhlin et al. (13)\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-6663600/v1/b3b10a02cadfec1bda10ada0.png"},{"id":84858554,"identity":"39ae5c6b-781a-43c8-8066-c975dafd3d34","added_by":"auto","created_at":"2025-06-18 06:35:12","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":134099,"visible":true,"origin":"","legend":"\u003cp\u003eOrganizing model on paradoxes adapted from Smith and Lewis (39)\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-6663600/v1/9a23c699cdec16355650024e.png"},{"id":84856722,"identity":"d317305c-ce53-4107-90fc-848a0d173712","added_by":"auto","created_at":"2025-06-18 06:19:12","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":101547,"visible":true,"origin":"","legend":"\u003cp\u003eParadoxes and resolutions to hospital-wide patient flows\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-6663600/v1/99393eac7529b524e8f352c0.png"},{"id":84856723,"identity":"49cf7670-cc2b-4916-a5b9-81c3c96dcc54","added_by":"auto","created_at":"2025-06-18 06:19:12","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":159542,"visible":true,"origin":"","legend":"\u003cp\u003eComparison of bottom-up and top-down solutions for the improvement of hospital-wide patient flows\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-6663600/v1/d1deaeff6d17b20392123da0.png"},{"id":103251197,"identity":"c625fcd6-1390-495b-970b-9eb4cc0d00af","added_by":"auto","created_at":"2026-02-23 16:06:00","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1671798,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6663600/v1/472411cb-0208-4efe-acfc-3745f436a565.pdf"},{"id":84856717,"identity":"39c638ed-9db5-4499-aa68-0a1f51ea05c2","added_by":"auto","created_at":"2025-06-18 06:19:12","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":78466,"visible":true,"origin":"","legend":"","description":"","filename":"Table2.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6663600/v1/81d1c467dba8d7a930aca309.pdf"},{"id":84856716,"identity":"a5dbf918-1ac7-4e83-bdfc-b32dbe40ad25","added_by":"auto","created_at":"2025-06-18 06:19:11","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":35269,"visible":true,"origin":"","legend":"","description":"","filename":"Table1.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6663600/v1/0aed89280f53d050f353f4d0.pdf"},{"id":84856720,"identity":"d06de611-d21d-4368-869a-e8184aca444a","added_by":"auto","created_at":"2025-06-18 06:19:12","extension":"pdf","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":166676,"visible":true,"origin":"","legend":"","description":"","filename":"AppendixA.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6663600/v1/0d59dade881dc34bcd270a27.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Bottom-up perspectives on hospital-wide patient flow – A multi-site qualitative study of solutions to organizational paradoxes","fulltext":[{"header":"Background","content":"\u003cp\u003eHealthcare systems worldwide are facing increasing pressure due to rising patient demand (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e), chronic staffing shortages (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e), and continuously increasing healthcare expenditures as a percentage of national GDP (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e), limiting hospitals' ability to provide appropriate care at the right time (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). Previous research has highlighted the importance of improving patient flow to enhance hospital efficiency (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). Studies have shown that focusing more on the movement of patients through hospitals can lead to reduced length of stay (LoS), more efficient discharge processes, and better patient throughput (\u003cspan additionalcitationids=\"CR6 CR7\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). Beyond efficiency gains, enhancing patient flow has also been linked to improved medical outcomes, patient safety, and overall satisfaction (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). Several studies also highlight the need to take a hospital-wide view when addressing patient flow improvements, referring to the coordinated movement of patients through various stages of care, from admission to discharge, while ensuring efficiency and quality of service (\u003cspan additionalcitationids=\"CR12 CR13\" citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e). However, research on how to enable efficient hospital-wide patient flows has centered on the views of healthcare managers and managerial strategies, with little attention given to the perspectives of frontline healthcare professionals who interact directly with patients throughout their hospital journey.\u003c/p\u003e \u003cp\u003eHealthcare professionals, including nurses, physicians, and other clinical staff, play a crucial role in the daily management of patient flow. Their perspectives provide valuable insights into the practical challenges and opportunities for improving hospital-wide efficiency (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e). However, previous research, focusing on managerial interventions, overlooks these frontline views and experiences, which oftentimes are central to the success of improvement projects (\u003cspan additionalcitationids=\"CR16\" citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e) and may provide valuable perspectives on how flow strategies should be implemented in practice. Given that hospitals are complex organizations with often competing departmental objectives (\u003cspan additionalcitationids=\"CR19\" citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e), understanding the enablers and barriers to effective patient flow from a healthcare professional's standpoint is essential for creating sustainable improvements (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e). Therefore, this study aims to explore the perspectives of healthcare professionals, without managerial responsibilities, on how to enable efficient hospital-wide patient flow. Specifically, it examines the factors they identify as hindrances and enablers to improving flow across departments and along care pathways. By incorporating their insights, this research aims to contribute to a more comprehensive understanding of hospital-wide patient flow challenges and potential solutions, ultimately supporting the development of more effective and contextually relevant hospital-wide strategies. To address this aim, a multi-site interview study has been conducted with physicians and nurses at six Swedish hospitals to explore their views on what is preventing or enabling an efficient hospital-wide patient flow and to understand their perspectives on how to improve the flow of patients across their organizations.\u003c/p\u003e \u003cp\u003eHealthcare organizations often function as \"job shops,\" where autonomous departments provide specialized services to address specific medical issues (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e). Depending on the severity of their condition and treatment needs, patients referred to a hospital may visit one or several specialized departments. Patient flow across hospitals is often viewed in terms of process throughput, how quickly patients move through the system from admission to discharge, with the goal of improving efficiency and productivity (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e). Effective flow management, therefore, relies on minimizing process delays, with Length of Stay (LoS) serving as a key metric that reflects the duration of a patient's hospital stay, influenced by both medical complexity and operational inefficiencies (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e). However, many stakeholders within the patient care pathway prioritize their own departmental efficiency over the broader hospital-wide flow, inadvertently creating bottlenecks (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e). These bottlenecks, whether administrative delays, inefficient clinical handovers, or resource shortages, can escalate costs, compromise care quality, and increase risks such as hospital-acquired infections and complications (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e). To enhance patient flow, hospitals must address these inefficiencies by reducing errors, streamlining coordination, and implementing joint capacity planning (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eOne of the most pressing challenges contributing to these inefficiencies is hospital overcrowding (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). Overcrowding is particularly evident in Emergency Departments (EDs), where a lack of available inpatient beds leads to delays in patient transfers. This 'blocking' effect not only prolongs ED wait times but also forces patients into inappropriate wards, where staff may lack expertise in managing their specific conditions, ultimately affecting care quality (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e). Additionally, hospital overcrowding occurs when admissions exceed available capacity, leading to overutilized beds and occupancy rates exceeding 100%. Persistent overcrowding lengthens throughput times, increases LoS, and exacerbates staff burnout (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). To mitigate these issues, hospitals must focus on effective bed management strategies and LoS optimization, ensuring efficient patient movement while maintaining high standards of care (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eWhile systemic strategies are crucial for improving patient flow, the perspectives of front-line healthcare staff provide essential insights that may not always be visible to hospital administrators. Studies suggest that nurses, junior doctors, and other hands-on staff are often best positioned to identify workflow disruptions, communication breakdowns, and operational inefficiencies in real-time (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e). For example, they frequently encounter delays in diagnostic procedures, unpredictable surges in patient volume, and resource shortages, allowing them to pinpoint critical bottlenecks (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e). Integrating front-line feedback into patient flow strategies aligns with the principles of bottom-up healthcare improvement, which emphasize that staff engagement in process redesign leads to more sustainable and effective interventions (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e). Research has shown that hospitals that actively incorporate staff perspectives experience reduced wait times, improved bed turnover, and higher job satisfaction (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e). A more integrated approach, one that combines managerial oversight with front-line expertise, is likely to be the most effective strategy for optimizing patient flow (\u003cspan additionalcitationids=\"CR16\" citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e). By incorporating the insights of front-line staff with existing knowledge, healthcare institutions can develop more pragmatic and adaptive strategies that account for real-world constraints. Ultimately, improving patient flow reflects a fundamental challenge in healthcare management: balancing efficiency with quality of care. On one hand, hospitals strive to enhance productivity by reducing process times and increasing throughput; on the other, they must uphold high clinical standards to ensure patient safety and well-being. This tension is particularly evident among front-line professionals, who must navigate these competing demands while delivering high-quality care and ensuring timely patient progression along their treatment pathways.\u003c/p\u003e \u003cp\u003eThis paper extends previous research on barriers (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e) and solutions (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e) to achieving efficient hospital-wide patient flows. Building on the process categories proposed by Holweg et al. (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e), \u0026Aring;hlin et al. (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e) developed a comprehensive hospital-wide process model that identifies five key themes of barriers patients may encounter as they navigate the hospital system. These themes are: entry, related to patient admission into the hospital; transfer, involving the movement of patients between clinical departments; internal, concerning care processes within individual clinics or departments; management system, related to the hospital-wide coordination and control of patient flow; and discharge, linked to the transition of patients out of the hospital. These themes are visually represented in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, below. The model offers a holistic view of patient progression from admission to discharge, encompassing both core hospital processes and supporting functions.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eAdditionally, \u0026Aring;hlin et al. (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e) developed a framework to outline the key obstacles and solutions to achieving efficient hospital-wide patient flows, see Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThis framework presents 12 primary barriers and 15 associated root causes, systematically categorized across the five overarching themes. It also proposes 50 potential solutions, organized into eight summarizing categories. They describe the importance for hospitals to align their organizations; build coordination and transfer structures; ensure physical capacity capabilities; develop standards, checklists, and routines; invest in digital and analytical tools; improve their management of operations; optimize capacity utilization and occupancy rates; and seek external solutions and policy changes. Serving as a foundational reference, this framework informs the present study, which explores the perspectives of healthcare professionals without managerial responsibility. By integrating these insights, this study aims to provide healthcare managers, policymakers, and decision-makers with a deeper understanding of the challenges faced and offer appropriate strategies for improving hospital-wide patient flow.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cstrong\u003e\u003cem\u003eDesign\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn this study, a deductive methodological approach was employed, using previous research as a foundation to extend the framework for efficient hospital-wide patient flows presented by \u0026Aring;hlin et al. (13), with new perspectives. This framework informed both the data collection method and the analysis of the study subjects\u0026apos; environment, challenges, and contextual factors. However, a thematic analysis of the collected data was also conducted using an inductive research approach to thoroughly explore the subjective perspectives of the study participants, as recommended by Braun and Clarke (34), and Dixon and Woods (35). This approach was chosen instead of predefining categories based on prior research. Finally, the emerging themes from the thematic analysis were integrated back into the framework to refine and expand its applicability.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eData Collection\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn conducted in-depth, semi-structured interviews as the primary data collection method, following an interview guide (see Appendix A) to ensure consistency across interviews while allowing participants the flexibility to freely share their perspectives (36). The interview questions were designed to explore the barriers and enablers of hospital-wide patient flow while remaining open to emergent themes and new insights. Hospitals were selected through purposeful sampling to ensure a diverse representation of healthcare professionals from both secondary care (services provided by medical specialists, often at hospitals, who in general do not have the first contact with patients) and tertiary care (highly specialized care delivered in a hospital or similar care setting) (37). Three tertiary care hospitals and three secondary care hospitals were included in the study. Initial contact was made with the general directors of the selected hospitals, who were provided with information on the study\u0026rsquo;s purpose and asked to facilitate access to nurses and physicians actively engaged in patient flow management. Nurses and physicians were chosen as study participants, as they represent the two predominant healthcare professions most directly involved in patient flow. Upon receiving the study invitation, the general directors referred the research proposal to relevant department managers, who subsequently identified and facilitated contact with eligible participants. To capture perspectives from different hospital settings, healthcare managers were asked to recruit participants from emergency settings (EDs), surgical settings (surgical clinics, inpatient care units, and operating units (ORs)), and medical settings (medical clinics and inpatient care units). Eligibility criteria required that participants (i) had no managerial responsibilities and (ii) were not newly employed. Each hospital provided five participants, with one or two individuals from each setting, resulting in a total of 30 interviews conducted between May and October 2023, see Table 1. No participant chose to withdraw from the study. To ensure transparency, the interview guide was shared with all participants in advance. Interviews were conducted online via Zoom by a single researcher, with each session lasting between 55 and 70 minutes.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e1\u003c/strong\u003e\u003cstrong\u003e:\u0026nbsp;\u003c/strong\u003eInterview study participant list\u003c/p\u003e\n\u003cp\u003e\u003cimg 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RvST6j8PAPNmx3JMrxuSMbay8dZ9JX/znCdN6T2hQc1XIY23n8wq0GglaHVKatYm4Mq+BVb8AdAM6Rk66z5xQomZr+zsgPabnulIzsglYM3AYVhmXBz+C+PNhJU/83L4BM406fLJzHTbrpuyzJSNpcwc4Trtt08cdcesELDly6sM+FNxHXPU/zRVytNxrx1HeoLyfThYV3m42gqNucfxtcIarsYcphJvkNwZcFiBpROURlPPOD0mzi0n+7Go24rZU7y21XtlHAAgjN3qPcHRxzjaniDN5xNvbn98nGTLKFXGulyS/VXUlhdohy0cdssp8yhdljpjbOerU+smXXds6XHVd9d1Uz6WMLL5dJSlhaD6f+ZYdVlBOW1rGjfWsDWVNV+ZNMZ1Nu3CV4KWS7+lvlcEK/4A2BOt3jXdqBnYaG+Q5axP7Yuu89jzEKrNIOjVbJ0rykzMmlnP20/WWetsvGa2O7UySs+CDl6MrDMvQIo/PUOs94Mo3IPCrEYsmjHbE1zPu92ucnKcfVumpGWW9W22LviVgU8da9H9S/5jOaYn09AVFw2Wp8OW5W2/B2S1gVpWYNk3pQoF4bboAV1eXrIb0ICVlKySkJWS3XQDqvYDSjp9vQqXsv+KWRVwF62u4Po36w83q0H2FS8A4OA4XL0nlNN89nhPV/P1oiV9m3yZvVdNf91+ENk2XjKk32awlWsRLm2QKXOjTyx7CMb7pR0IrRG9nUiCZvSyjoqfwvb7w0/3lf/Nc3Y0pfeEQ9R8XGdvEprL6K6O6K70StCCeL3Tv2Mw8AfATmlR7/omFoTcEtC43cSPuE0HmFxmL68aqGZ2SzHopdbst31xoQZnNq4d/upA7zE34xxc4tWP6JWPnM2ODx6zKestfdpvm21B26/zgFN52AwGA/Vqyp0cglJFQ3jUsd61vJor1Vp+cOlXrrxsV7085fXM6bBL3SrP0UGyoKG8HiOvGK3YhvpqdTzC7Y3o+vo6cjc3dKdevRb7JoTUYkgX7Ta1t1zV9pVFaeowH/lRr8bgTHuwr3gBAAfMrvSeAM1XO+l8rT6qsrw0M4KZ14F1uTpeLRSqa4Pj0XtCa/QiKsPx64bq/TZ+uq/m+n+yNKX3hEPWfNuoSZxIePGjrkP2idcn/XsAA38A7AURhG+jU4Uo53TTCkSzlbLgSjqzSGjIaqvOYE7JrV5iOrL3iN4vJO1uQmZtU3ufrKf0UmnAxzV3HLtEi2rupor3rABbcH274U5PnHSAmVO9SuFTx3rc2d5x/ZXOthOtuGjXs+Iij/W0y/H0aXx7SVfzOc2Vm6gO/7hhoXYhe5TIflE37tNmHTPl0b51tj0yPcNN02L76r204h9mvee6vJPOskolKI15g2y6PdhXvACAI6B5vSdA89XN9sr77GCmOf1X29SscnSMdp6uNsijR8/1qr/d7FkcoPtqq/+nSFN6T9ix5iuVxhR6dW8clq/mS2JL/x7AwB8Ae8MMJjUBN6x9liAs+KQDnEwu6XLCDdPqjm4yCnAjbqjV4v8sLvLoTfIVCfuM8/ERbQTL8qUp1V6aA34ttEF861hLOluZbdOvSY4Ld5quUp4Leq2miwc0v5FBzh71lHtEDyIPR8qapt1oY2IRatYfka37FI2N28rN9fq0R7hB8A/suMyNS0QYlEafwX4jGvcVLwDgOGhS7wnQfPWTHNgzr4dur7RraaPefloXrHKsSxscn95rjfSg9+wlTT9F15omX/fVX/9Pi6b0nrBDzVc6jT4UaL4DBgN/ADSO61SgBSmd4PgRlx5gUie2iW4I4VZ62R6NRtd0PeKGydouGUFa40x077nq6GV5/2t1guuRv/LBmFcWSPass04fyqlNQ6rlAKgg8uzHadp9gnZDaB3Tr+0UU0N5Zl7D0a+WHCUi1KLXXwbzuxyhpld92Mpt8Tpqu7ZWgPiGyz4d72hHP7S4uC0nKNoJS2O8gibrOWq7vfdy2le8AIDdske9J0Dz1Yo5tXj2/vX2/n6G+HXg1/TeMjCYobI2cNuudJ1pnM0+kONx1Ge7qO05MFh1XwP1/2RoSu8Ju9Z8ZdJoZ/FaXkv2jbeu9DfEXQqc6gvqYLUKO/3mpDGnBHXkVKD53XzObiKn/UQn/WRPM9KnoanvIv+TQXRSWHRP9nQr64lI+sSirJNTIV1xRmkU+4mbzyd3AzmVKB1+TryGrfi3jk06YuSUJpMnOaFpMonKSNknKj9VJK7ysV13lqX7NLOM3/gkqlQdk2v7KvuCE7W2CCmDBM46puJO1mV5hiJ/W8mpUp7We0165bqOWz1D0bVMPkrme5fMdbmp9mvAdT7tOJ8xeeVmng2Nf7imLBJhxm2iXA8so4A0btlzIM+6+N/YM+jR2kO8thN6yzgA9oN+Djr8DOgrB495znes94TGNF9BvIaT1HyJtjjbTkfEfVluGSXadFPepbQBY+lL4jpjC2tXmHRZbZ8sR1sfVsNzoOJP1meH7lME/uY5E5rSe8JeNF9QGqM60eHfdhMdp6kPUbp9TygPTb+0Bcn4dNria9XqYnpcDwN/R8l2A5rn9tF4xZ3/yXT81VnFDU3SSaPgsA83VhtBwE4aIvYaNZweHSAT+eU44sYj2ahYOkLuJLfiNI7jzmpGDyGYaHD3UA2bQ5WTacA3TjqLuJxc5WO77ixL85z72TtTZ8TfwLejagBjf592IKQMkjjrGN8Xd7LGWZ63KuXpvDf9HEXxZp5doWy+d4ZHX5MWQ5Zyy7YhYeFu/0DauI4MCKSLzgevNGps7SI//5MyEe84XtsgXhkHDgfbs6AGh8s8BwfPobSDYexD7wmNab6CeGM4H6eo+aJyFWevh5sBz6J816ENNPz9Vh1z1ZldYuzv0nxx/XBMXlV+Djx1nyHkN89Z0JTeE/ao+bzTKF5tbTfHyxU2JNqw9HM9TPnbdtWe5/S43oX8jwOOefbsGb1580b/BQ6VxXRI7z/qP4TbGc2W3MR1BnSpljBHPHj8vKbN9JMsaNp9Se8ur+jtdXYD1PViSE9e3tLl1Vu69t6181wwR37LPhLqQj7see3rN4mcONSfcTu6opu0DdZT6sppSoM53TnWWptlyrLXRXn0Bq6dyclulBuVUwn7NImqM1VtdywU17HKNipdntGzfh52sKHbOs5/nSVQT9tkCEljnfnZTbxfv37Vn6px7949/QnsFd2vs9KjweSKHt8n+vT+HY1Z/Fn7+qPHvBo2oPndtdcrWYeFfnb5yfVqrthzKb0nQPMdEVG9qKUPq1JnDpUa8hSq++rVFeeIbuu4/OouwfpsE5JG7beGZ2vfdSs9roeBvxNBnRY1XspESw2bZRaBzv3Qya0PeQKxTnYVDzhfUMcAcIKBv1PCDIJ1aLJKnYTIPywWrMSOZG/xAI594G93QPMBAABIkx7Xw+EeZ8p6LRsQR5sQR2PRWcwotYivtfarPiduWPEf4i8dxubeFHw9ipedyw9jj1v/XXCf+9vzId6QuN+l7nBKU1WGUxoOu0qYUWdALxoVZizYX0YrE66wCz1oBNQxAMC5YTmFsJU/6Oej9wyR3mKXo7MUcZgLkXVWtrSa8Z8brtF77jBj2IOJH1oSmg8AAIAHsuIvCfb4O07MHhPWfROSJPZY2DjLHgh6DwXZKyT5nnqvl7wv4ZIR2/ZfsL1jL07es9deYhxxSxQmn1thG5z7Ppwpq2gz0U68H130WTYbbbyEdD3b6x5z4LRBHQMgF9t+fWUcOAQ2eyQV6jyDr94TWD/Z/Ga8+mq5WMdZ9nay6L6VJX7Z5D+zxx+0pBtoPgAAAAlwuMeJ4jXwZ0Tg1qaWDjGphY9yyr8+dUaflKQ2olSbVEYnIW119BbRJOlLb0Bt0pzZCNYZN38X5yErLszGxsem1QAAAIC6sQ3ilXHgQEhoo8LNxkP0nvErA2yst9QlvfH91uBX7C95yMzqbm60XFKX2XQcu/ighGQCUuEqTcn3R9fE8f2xV2hJAAAAwAcM/J0oPgN/TjFjBFDy5lgwbQTXhs3An1UX6XuLZ0u1CE2Hkxu3Ea7pfBSkCQAAADgjbIN4ZRw4HNIr41wDgCF6z3egywza2XRm5juj4zKaLKvVnOHGA4I2LZgEWhIAAABIkx7Xwx5/Z8OaPt3yP50rymy/0XpEV6yu6PZTZk+TzuR58xsqLz/SSn9MYo+7RaMXLMtoSe8+JFK7eE+yu8jgBQ4bAQAAAMDp0epd083diuaDjtrTbTnrU/uiS9Mt8Rai97Rf296BWxh/A3psEYW9x6LLJNhtFdm5epTSZG16oBJudF9OuCatvkBLAgAAAE4w8Hc2rOjjkv9ZjlkkXtDFlpNT0yJfTSIbTE+HXepWjbf3mCUiZ+XdBy1cRaspqWYVpAAAAAAAp0GLetc38QCgDF6N20NaRF8yIXpP++08oHZ0wUGBv/aDaCDyo23oLQ/f+DdASwIAAADhYODv3OhMaL5a0crmbpqb4VxPu9Ru92l8e0lX8znNlZuQ0qzB9EhNLi/fkZqoXU9JHSY2eNz86kQAAAAAgL0jA4BvaaJ01Izeb0b+Inap91YfqczYWyjQkgAAAEA5MPB3Nmxer6BWi/+zuMhjAyzotZqOHdD85ppGvR71lHtEDyIPwUSvlUSvaKw/vFOCc4ApWgAAAACcDS26f6k/xoTovfSrty7y/a2j93Wp88B33Z7BN34BWhIAAAAoCwb+zgYjDi2zwsFooRZK5lUO/YpHGXrP1Sz3cvyaXr+LhCC0GgAAAABOjwUtFom96GIWpN5OpQ5txtxC9F6e33Uiznx/H5QO69BVZlPBItzhrqdP7K/wQksCAAAAwWDg74zoXc9Z0rC86ndpOF3Qer1WbrGY0rDbpe727tA5aKG2HNMTDkfun+bea2Z0I/8qXhVnn6VeWVr0SO36PKOZ0mp4NQMAAAAAJ8j6E73st+mCtZrot8WC3XRIXa2jOpO3NEqMuYXovd7zidqfz/iNw75oU//9Zh3ext8FdYfTyJ8KL9pjL50GX2zxyx5+7bEMJSaBlgQAAADKgoG/s6JH1ysWg50lzcZ9arfbyvX7Y5Y8l/QiYKbWCLUlhyP3j3M3dG7R6EbijfyrePvviK5kY2rtpQStR1daFHZo8hxSDQAAAAAnSGtEbycD6iwj/dbvsxvPaLns0GCyopvMiFuA3uOwb1ayT9522Bwwra4T2kr501puNo78SXjONHgi4bIY7NAmftnDb7K6IXXwbgy0JAAAAFCWiztGf1Y8e/aM3rx5o/8Cp4zMlgqy30tpZMZ1a7+YImTWuWKcMQsaXvRp1mFx2uDBJAAAAMCx8fXrV/2pGvfu3dOfwGEQ6SgZCPOVUt56TzQd/1Os0cLT4IWK3ydMaEkAAAAgj/S4Xo0r/tY07UZH63eHlTeRAztABFNl0SRh6I9+1BCnYfE+esXl6hGEGgAAALBr1jJoEmm/2MmrpPqV1Gi4CdRLpKNCpJS33vP1VyINXniH6ZtOD6AlAQAAnAH1DfytP5DaF5dZzt4Thv5As6xp+lJJtRKbSZ87epC+O916Ts2KgDJUufckWQyjSRDL3pdVy+okyzqnvJoG9R6AKnwidZ5rp0ODwSByag9g/YrpRZeG1kMpADgEoCUBAACcB7UN/C1ej2lJIvpkp4w6To4FIAc90NwZXNFxaLXEqojUgJsd9q9X0Ir/Rn42LT/qD1yc067aL+eixGrdKvceJ2u98bm2j3Zqs/MCQ1Utq6Mqa8tKIFkFFJXTYQwEoN77sV7IIQIpW3K+7VbkH9LD7pbfi+6QbGO6IeEqvwl/kd+ybaN/GlU9TqVRHbBQYjArqBxrjHcnXL6g6+tr7W7o5u6OVmbftn6b0639AXBINKElbatgE24fE1wgkFAb2vyf28rnRBk467ie5EV/cLg0pfeE/Wi+sDSqepxOo/xuD49YER1AJeEMnb/9w8q8IrLHX5KffvpJfwphfjfgoGgwv7tbTe465jMAIMI8F9p1Jiv9hZ3VpBP7JRrwE1Ynq7tJZztc/oF21+l07gYF6bJR5d7jg9s6VXbiOM+DQeQ4/1u24jKx2blqWR1VWZs6L+mNy8mUXapsHOXVNKj3xcRtUWzHzqYty/Tzpm1hWw4md/P5/G4S++/cJYsqJFzjt9MZ3E04zPlEyt7utxj/NMZ1WJ71Ccdr4lbX6C4k6qByrCneL1++1OJyKdJ8+tmmzoRLHoAzwNb3JRw/0uDQCbWh1X+ijZe2fH7iLWDcb0X5tUoj3R8Ed9tgJzSl94T9aL6wNG7qMKdRay/xr+IN/i3Occf3uu8PK/Nw0uN69Qz8bT3IppDrHqwA4IgxjYk81OoBz/sRpAfSucGLBkrqfpbwjJZlPpBykw5knrXfijsItpkqU90m7nog66CI63yqlsUda6L+obwOltV8wsIrZZeEOEqaLBZraTtaBn+CwmW/2d9Mup20ibccgtKo/Wa0l6tu51CmHKvGaxvEK+NyKUyT6W/C7ATA0VKifQAHRqgNc/yrSUL5jt1JVwldBjIhqvpSW2Z1P4tH4zBpSu8J+9B8YWl0axVnOE42aR3I4GHOb+6QcilDelyvlld9F+9lf4wBPVan4Lfo0RUnl2b0EsvZAUjxmB5za0DLd/TB9XjojaYHL57Tg+iKlfV6QYuFuOgUPjf8vfK34Hv0JQtF+5WZMGyvabru3bpu0lsUj3e+dsxiSH21FdCE3l73spuAt3o0urkm1QzmYCurkHKqYqeDoDWiF/IM5G0JkVsGcpqjO2/yXfLbZH2yUaU8c+/l76J47fcatsLwfEZ2Sas3olEvVdtbj0h187Skjyt1hVnTB7XR74BejFL+e8+JhY/aXsB49w838pv2StSmB8pvCGFpXH0Uvx160I7+rkJIfuuMd/8YTbikd85OD4DzJdkHxP1V+lGJ+xO/Z8hHR23iNRox5TOOU7Rj1O8qp7+2ERYv49nn2fvhKD0uitK6K1q9a7qZK9FDs5cNbd1zQCwvX5DK7qwf9Eqv05Zix9RXG7/8na5vSYp0XxKfOnsuNKX3hN1rvtA0riiSXtltH1qPrliRifdkjvJ5MJnT6u6Grnv5Qi6kXGpBDwDGhK/406OayeF7M1KZu6oJgDPCPBPynCQ/Z0iuxnOszItnApJOliVnn7bkTKNxnYll9kHPflhnMyxhSHyxV9e9+rq83hDFl3BmZVySgHztA7Paz2umsqBMtq6HlJMrXIG/y7XTrsmp55kVTXG+TN1MuFQZ5M68JctnxX1TOqx0eVQpT9e9nO9svOxsdV6H4f2MHAwmvcny1FrA0e9Hz09RfbSF68LMqIaUU1gaXXUtfPbXhT2/dcVrW71XxuWS259p8p4zAE4Nn2fCkNsHRO3UfOt1Mbme0+b56qg43u1+MkoypyUdZ9LZ8hUcry2/9j7S1Q97a4EyhNhQKPQf0rcdKckyMJ/TfW1sf/23wXU9LrdE3Yj9Wuquj+4z+NbZs8dWd8O0lJuQ50LH6a35AtPoqrOK0LiTWOpwIfW1F7Wv+FtPX0ark6LlfhFmpDJvVRMA54p5PmynX5uNpifP7SvH1lPqtse07AyIdZMM3LNb0aQjJyimNlBnv0/6M1pShybzFa1W7Lilo3GfxjKr4YPEp8KQ+FYqvtVqTgOOz3f1hmzsPtb3SxokCbScUT+Z2JB87YU1fYqOrmxsFY5XObmowU67w8zCZctyKXWzoAzimbd3HzKzs9Hq8+h0xsXrPs2WXPcT9Wk+uaL7kdd8KpTn+sM7ur2cJOox38s9eJ4tK9l+L+iZUbqk+2aicq1Pd728n10Ny7TVVG3R7KUlXCtrWgzZvvzJ2VbaCExja/RWzQovuQ0yGy2rQ12kAZWVv+lZ5GDs+W0+3t2yjhpPAICDqA+QfkP6gLlejTKmJ90L9aaB0XDzvL6khI6a9aUd1X3PfE6PuU9eT5/QeMbKcRL1farvlD6J+9aBpOM61eKWitdTF+b0w75a4DA4s5XP5s0OrsOvG5IxtrrrrftK1NnzpSm9JzSo+ULT2LrPqXBR5g2TKviWSwm4sm8RtuJvM4o5Wa3uuPHeuNpmxAE4AVKzga7ng8VPYoQ/O0uw/X2CVPhC5NcygxbPcmVn0PLT48A1s6qvcyudmj3JzsKE5Gs/BM72FJTJ1vWAcnKF62WnXeOwnan7tnx5lQF/ip6LdH6TfrWfTHgpqpSn4147jvQE5ftwsLZfBc+quSfvUc7TDeYwlXiD586AwwosnVJpXLGZdJ3VTlam1kFefuuI17Z6r4zLxaONzs8nACeGeSZsLv2cuPoAcz23n9smSEfF4ac1jaOvynnOS8Xr0ecV98M+WqAkITYUcsonRuf9ZNvBdBnEZZj9rZEpJtf12MbZMLzrroWgOnvmWPvvgnKya6ksedqgsuYLTqOpa3wtlR7Zhy9Tl72x1OEC6tRM9a7406uTiGY0brepnXR6SZFtJgaAc6c1ekEsTFLPx4Ki7TJfkH1Bh151Ztl/IF5FePtJh2dWqJm9NxPEewcUYcKoNuPQuXqUmm3RMyfx3goh+TpdisvJRT12aoxZn7rdrnJyRH20amlA87ejzCycXxm0aBRNJW/PnMd7Y0q4LbovU3eyYmIaeiR+g+XpsGV52++B9ZSeqP7dsm9KFQrCbdEDury8ZDegAStBWR0iq0a66b2E1X5ASaevl2W9ove3kZ5hEar+XY5f0rBqvEXl6BvvEWD2LDyc1TcA7IDOhObz+bZ7bn9lINMHtB+o1WxZPejqG8rpqKAV01ZKxuurC3P7YR8tUJEAGxZxdiufWyN6OxGjNrPnf7bu+uq+cnX2LGlK7wkHp/m4PXk7Ue2urPq8uEj8bumPuZVJUVu8KZosc6bSwJ+80qTk3CTVKGo3UI04XvcFIEsvc8iH9bX5LfTSX+7U2twQSWO0ce3U67vab+cBy6my1BGGDyH52hdalNItfTq49mxXdqrOYDBQryzdySEoVfqz3mPuEuXx2Qycbx8yxV6uoz5IXh+WeqVemfSyXfXylM2ip0MWDQdXj6uyoKG8HsPSaLJiG+qr1fEItzei6+vryN3c0J165UvsmxCCiyFdpCch28Pslgq+cHjdtnmd6I5u4nij14HKx1uQX994jwEWsS/l0bT9yALglLm8T71eb9u1PB+C3NfObNSlozaDJ8lXNM3vvaw+bUq/efbDHlqgElVsCDaLHMavy/fDAfjpvqbq7KnRlN4TDlTztUZ0o14Pn/DvFRl0vKSJOqRDXgPn7017VHe8MU2WeUSFgb/kaSmpRlG7az0TM27qBX8AjpheNPKnn4/N81QoVmQGUu+LknE3Ncxw7ouDzpcWw2yv2k9YOnUGczVwIU468MzpVaVIDZybwYXB40RHyX3QjdkTqEPLGQvBdpeaHjNRe7G1+zS+vaSreCKMRYSIhqOGBcmFDEbJPk83jlXJjGOm3H1SrWe4aVpGY0g10D/6es+3Jh8jZ1nR4pXGNU25Uqn9pZID1RLvDdcp/rgcP4nqk2+8iqL8BsR76KyNiOVHs47VNwCAfGrQUZE2lcX6MhASTWDJSv0O9+Xp7f1i9qbffLTAYXCeK5979Fyv+tvNnsUBuu9Uf0vVQlN6T9ix5gtOY4t6o82g42jU4yt6sNjsFxik+XwpWS6BlB/4M6/55jWueiaGbIcYAHDumOPE5flYvFazTPmvXWxehaBWi/+zuMgjU8ergnWE4UNIvvZHtBGsmOvQWrNd2emwMAPn8oqPezWCVCkRgjckm7qI/+KJqCrluaDXaro4GrQZxRNhj+hB5OFIWdO0K4KEc8aCxPrjz6xQsZab67Utj3CDYMGWmHyMXCLCkDQajWNdcaJ/bMYUxBvjkd+geA+I25c0HA5j1+1e0IVatSj92qoG2wIA3NSlo/jHp5wmMpiTOmRkckmXE/5RKyuPrQ9xU/rNvx/21QJ75YxXPpvDqmj2kqafomtNk6/7mqqzp0JTek/YoeYrnUYLevuATjxK6Kv5fKm7XNyUHvjza1yNSJ3Rwf1WBmDvmFO+ZtQXoUVFM4Fm1ZnP8+T2q05sk4e3kLz41rRY2OZQyhCSr/1hXllQe9ZZpw/l1Kkh1VYs3uzKTgeGHjiXV0he+6yWNRNRhdRQnplBGz1beJSIIIlefxnM73IESU5/ryc2ticKfcNln453tKNXuuS3VHq/KBcBafQSjSF45rf2eHfEckmz2Sx28qqKrBBayYBBU1PXAABNzTrqVkZoejQaXdO1vNXlfISb0m8B/XCoFtg1Z7/yebMX43gc9dku0hPr/r9XHFh1X1N19hRoSu8Ju9Z8ZdJoQ0+GcE1qYs+9kHKpg9IDf63RjTr+uiiBvevomOymMwLAMdJ6dMU/jzTOQz02qP0r+N9Zv0tD2byWG0dxi8WUhnKAQmJAqvdcb1Kq/S4W0b5jrD82cRZgC2MxHVL3ok3990XzsP6E5Gt/9Oh6PlDlIXtMXHSHnNZplEYuV9kbpD+7pR1NaG6xKzsdFpuB81m6A19POe/JuiR1X8+mefwiKF+eZiZZby4tcas6HMV9jCyGkSChDmfs/WZFV+w4nwZnuemJjcnzTdn7h7umD0+ijZbjMNlJW6aCDRRj/mnciMY+P+tT/qG5qUv6x4hHm23wz2+98TaO2hMn0nlbTl7vZ+HXOpR0ArBrUqtgjYsf9ZqpR0fpVzNl/7N2cu+z6LXfoWXiqyn95t8P52iBqoTaECuf7Zg3nFzEbwjKxPqmj1e/V/LuSxKg+47jN8fuaUrvCfvQfOFpFH/yuy7hN3799jqgXeH6ZMJYfKCP6hr/PoyvbepXSJnXAgu0LdLH/gIAaiDnWPHoWHnPY+yF1fxuYI43T7oO+0uf/C3Hoaf8yOngUZyJcPXx+Najwznt6fg6g8Rx+a57nWHWkK99otIZHbWedJ1kOkPKJKScnH6ZIjvtmoKj9LcIrSsGEwd1VL3ewPcN0jbqZI7or1SeznvT9TiKN/PMCWXzvTNMOnJcJ1XHLOWWfYbDwl3NLWGy67CfUm2DVxoFsVtnuw1Vjq9N5tv5ziW0HOuJ98uXL7U4AEAAcb9kd1vtfV4/Iv4z/WdB3+Cro3L6vqiv4n5rPr+bx27TZlq79MrxOvJV1A8b4jJPa4GShNhQcPlnrdjhAlvVkaZDx5SBS/Mlysheh1K25rojxez/e4XrkI/uMxzLb46dEapTmLTNlB9b+YWFXavm806jeM3+titXH3T77XSmPpco80DS43oX8j8OOObZs2f05s0b/RcA4JCRGSpB9qTIRWazSPau0H+XQYXhEVcNeOdrz0TprFiudbNDO+0fvRluZ+LcjLmyjUqXJ9/HN56HHWxE+ZeCr7ME6m0bAtKo6wF7Fu+7o0K8X79+1Z+qce/ePf0JAHAslGor5bTK/ox/a66yr+jLiip5ZXUwp7ucpWuN6DfdDrrDLNYC4EhQtq7Wz4bqvkbq7FkRoKUCqc82AWlkj5HX468P6XE9DPwBAAA4TvJ+pABw5mDgDwAQgjqVfryURVvZ11IPub+FFgAAgAzpcb3yp/qCgyJ+l1yPjFvh7+L31nP8mdF1/qTDzfqVvRPMe+o5MQIAQEOsaRodk1dwKA4AAJwWhZqvRr0nQPOdB2bfadkTqzuc0lTZXO9jLPtidZra4L4K0AIAAOADBv6OnYVsPHlB7X6f+uLa0YaYW/uSrmWzUtlgth35Mf66Q8psGcnhtfm7IXf2w25bhyt/6+/V5qkcX1uHw9+11QackIIAgB2y/kBygF9ncEXQ+gCAs6BI89Wp9wRovvNCDutZzWkiJx/cvqOxsvk7ur0lGkzmtLoJ2eB+R0ALAACAFxj4O2ZEkPVntKQBzVcrdZLeijvsQWdJ7z5sRNn6A3falxP2szlxbzXpEC1n1N9SeBtm3NnPdLir+Zwet/mixCf7e3TkuglrRROObzZOiUUAAGgSfZrozTX28wEAnAEemq82vSdA850nrR6Nrm/o5uZG2zz6fD3qHWZfCy0AAABeYI+/I2YxvKD+rEOT1Q2Fr7xf07TbpjGlNsLV+2SQiMC77Zk9Z3xGHBZs+AsAAACA3YA9/k6L8povXO8J0HwAAADA8YI9/k6GNX26lX8v6X6QAEyx/Egr/TFJZ/I8JQJ1fB3LUvrWI7qSTUFuP7EvAAAAAABQHzVoPm+9J0DzAQAAAKcEBv6OlhV9XPI/nQdk3srIQzZmng67aq+WC+XaNJb7vdHxLcfUjsMoGxYAAAAAAPDDX/NV13sCNB8AAABwSmDg7wxQx/O3+zS+vaSr+Zzmyk1oIDO2oXRk75gVrWwu+QoJAAAAAADYGbXqPQGaDwAAADgJMPB3tLTpgQg5x6sbGxb0Wk3NDmh+c02jXo96yj2iB5EHTzbxUavF/1lc5BEAAAAAANSGj+arS+8J0HwAAADAKYGBv6OlRfcv5d8Zvc+crLamxSK180rm9RD9Goc3efEBAAAAAIBmCNB8lfWeAM0HAAAAnBIY+Dties8nJBOys36XhtMFCz920yF1L9rUf2/mhM2s7ZiesJ/1ek3rxZSG3T7LuTB613Ma8L8mPhUWu4UKr0vdKbZ5BgAAAACom2LNV5/eE6D5AAAAgNMBA3/HTGtENyvZu2VJs3Gf+n12Y5Z3gwmtrs0ZbS0a3bB4YzG4ZD/tdpva/XdEVyuai6ILokfXKwkrik+Fxa7fH7OovKQXmaPfAAAAAABAZQo1X516T4DmAwAAAE6FiztGf1Y8e/aM3rx5o/8CR4PMxPI/su+KG5mtLfLjj8z8CnWFBwAAAIB6+Pr1q/5UjXv37ulP4GAo1Hz16j0Bmg8AAAA4HtLjeljxdyqwECsWYz5+/JGwIAABAAAAAHZIof6qX59B8wEAAADHCwb+AADgZFnTtHtBF90pYX92AAAA4Nyw6wCzgrMMVe4FTQG9BwDIBwN/AOyIaJNt7pQvNq475A4a+unwWQwjmw0dcsp8z4LLbs4FDXO/b5jlR/1hh6x1nqWeuzaB1+XmKlZwGKzZTt1M27Vw1GX+8THsbvm96A7JVgVCwlV+E/4iv2WfJ/80qnqcTqP8sCoVsU+8+sdb0k/GDdFvAHCwbPo+v0GYRBvTpEZI6ID1tKv2a3Rqmhyq3HsUGD3nyp/5HnpvG2i+k6ApvSfsR/OFpbFezSfBmd/+rNv0tS0Sz03WOe6pAAb+ANgF3IC1ZUPsZYcGkwnN5xOaDDq0nI3p5YeSrQnYHb3H6nRDuv1k76A+3UYfWHCZ87S3WH8i5ePyPp3Pi1I6z8xy/MTdyYKDRv3I689oSdx2DQbsOupk0eWsT+2MepdBqzaNZ+x7IO3cXLVzneWMxu3uVh0ICdf45UBpwmHOJwPqyAEG3H5m01CEfxo5Yuq2+7rd5ni13+VyTP12qCALiPeSr3MGs05/L+CNSwAOE9PfC9xWvCzo/NbTl9zG6D9cGqJu7l+qNmXwoK0vBFDl3mMAeq8k0HzHTlN6T9iP5gtLY+2abyj5kN/++pIV89yIxku7B1R7KyuHeyT56aef9CcAQD2s7iYduuOH+m6y0pcMq9XdPH0NHCA5Noy/i9xgri8nWE06zu+axaRtcLf7qCd33E/fcecVlY0t8/PBnsoF+LKaT+4m6UZK2zb9PJh63kk/JNrO1JlwjYwICpf9ZtvJ+R3/OMv4LcI/je5n3hlGDiFl48SUj+cD8+XLl1ocACCA+DkdRG1U7rOt27EO+22sr96jDjhKoPdKAc139DSl94R9aL6wNNap+TZpHczn+c+lLoOmnon0uB5W/AGwMy7pfnr6r9WinmVK0Ll/Cl9Pf7Xxy98tFrRIr0fm7xfq+kL5jZ3+Os16HfmVcFx+BHu8Udgu8uI9bFr06IqbZlrSu8wKzRV9XHLzLrMz/NfsfXZW7MM7me4Z0ONedGULLhNjn0VO2Qn2Mk9irout9aU9s7x8QXPuAWnWD3q9w1mP+Hr6q+JyET+6jC3fJfGt/+dCqzeiUbqRaj0i9Tjw8/AxXvKwqecvRin/vefEwoe9b1ZI+Icb+c22k216oPyGEJLG6LmmzhU9yiTzKpqpTiYyl7CycbF4PeaS4VCsDQkA4LB4TI+l71u+I+eLHYv3NON/Bi+e04PoihP/vslPB+RqNX2/S5PY7t26ZtKalwDN4fW5Deo9gcskym9++RTrGj8775pD0Hy+ek+A5tvQlN4Tdq/5QtNYp+YjejCZ0+ruhq57B7YyWg8AxmDFHwB1s5kh9BrRd86IWWbzYr9zPVucjIf9D/TMm82lI4hnXpKuczewzXA44v0fdXzWWRF9j/+MyYFhyiddbsmykO8zs/uO6xxesuxi13HMCuXamoPj79P260wKZpqaJFle5nO6DOI86b8NruvBzwCz2r4eOcuMYUj9P3tsM6Ou+h/BPwRS/m3YwnWh4wuq2wFpdNVZRWjcNZRNbnrs2FbvlXEAgABsfV+2M2OS/ZmlbzME9E3eOkD3m7aVMLa4trzZ7o37YZOPhHNpmoB87RyX3eJ8utr0nLaew/TWfMl4EveY5Byc3hOSZWY+p8shzpf+2+C6bnsu8srGV+8Jh1z/DgqbLsup54yf3hNsYbvQcXrX78A0uuqsIjTuJDltu6Djzdb9esCKPwB2TotGL7jJYGb9vE1SyzPr92lGA5qvVrSaz+lxm2g9fRLtazBZyQA/u1U0C0cd7pfZ33ViOlLtazCmZUfCEL+R/0lnSbNx2zlrl473P13pWZF3HzJ5XLyXee0OXaWnUo4FMzM1e7+1z0O034vM7vbss/t6Rr9z9Whrv5f1h3d0ezlJlPcdrbh3oOWM+jnTpDZbi/2e6L0zJmJb9R0nZtynscxg7ZvWiNQjsBzT64AZ4BCs5cIsXkf7dXDnHtfr+eSK7kdfR5Ss/+eLnhlNrmIu2NeoraZqt2d1s1jCtbKmxVDszc/V5Dl5r38LSWPrPqfCReDMcw1lI+2Fmrt+MbKGAQA4QBy6QbH+QLIgJbcNC+mbquoAiUvdH/WjSpOs5jTguLIr3+zM+m0am36YndKc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style=\"width: 1277px; height: 532.583px;\" width=\"1277\" height=\"532.583\"\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eData Analysis\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDuring the interview process, extensive notes were taken, and early potential themes were identified. This was followed by an open coding of the verbatim transcripts, aiming to capture all perspectives shared by healthcare professionals regarding the factors that either hinder or facilitate hospital-wide patient flow. Each code was classified as either a barrier or an enabler to ensure a comprehensive representation of viewpoints. The coding process followed an iterative approach, with emerging themes continuously analyzed to refine categorizations and identify patterns. This ensured that the analysis remained grounded in empirical data rather than being constrained by pre-existing frameworks. Once all open codes were established, they were aggregated into broader themes, progressing toward higher levels of abstraction. Toward the final stages of analysis, however, it became apparent that the most striking characteristic of the thematic patterns was paradox. Time and again, healthcare professionals articulated an ideal vision of how things should be, while simultaneously describing experiences that starkly contrasted with these ideals. They expressed core values intended to guide the development of healthcare organizations, yet the resulting realities often contradicted those very principles. Consequently, it felt compelling to explore literature on how to understand paradoxes and contradictions within organizations.\u003c/p\u003e\n\u003cp\u003eParadoxes or contradictions, as phenomena, are repeatedly found as leaders address fundamental questions on how to design and develop organisations, establishing boundaries that create distinctions and dichotomies (38). In the process of forming organizations, Smith and Lewis (39) note that \u0026ldquo;leaders must decide what they are going to do, how they are going to do it, who will be responsible for it, and within what timeframe. By defining their objectives, leaders simultaneously establish what falls outside their scope.\u0026rdquo; This process clarifies strategic goals while also generating tensions, such as global versus local priorities, social versus financial values, loose versus tight coupling, centralization versus decentralization, and flexibility versus control. Paradoxes can be understood as \u0026ldquo;contradictory yet interdependent elements that exist simultaneously and endure over time\u0026rdquo; (39). In other words, they represent tensions that emerge within organizations due to competing demands (40).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn their influential paper, Smith and Lewis (39) introduce a dynamic equilibrium model of organizing, offering a step toward developing a broader theory of paradoxes, see Figure 3.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe model underscores some key aspects. \u003cem\u003eFirst\u003c/em\u003e, paradoxical tensions within organizations exist both in latent and salient forms. \u003cem\u003eTwo\u003c/em\u003e, responses to these tensions involve cycling through different management approaches. \u003cem\u003eThree,\u003c/em\u003e consequences or influences of these management strategies on sustainability. While tensions persist within organizational frameworks, they may remain dormant, unnoticed, or overlooked until external conditions or cognitive efforts highlight their contradictory and interconnected nature. When latent tensions surface, they become more pronounced, leading organizational members to directly experience their conflicting and inconsistent characteristics. Smith and Lewis (39) argue that environmental factors, specifically plurality, change, and scarcity, transform latent tensions into salient (visible) ones. Plurality refers to the coexistence of multiple perspectives in environments where power is dispersed (41). This diversity amplifies uncertainty, revealing clashing objectives and misaligned processes. Similarly, change introduces fresh opportunities for sensemaking as individuals navigate conflicting short- and long-term priorities (42) alongside competing yet interdependent roles and emotions. Lastly, scarcity pertains to constraints on resources, whether time, finances, or human capital. As leaders make allocation decisions, these limitations intensify the struggle between competing yet interlinked alternatives (43). Collectively, plurality, change, and scarcity push the boundaries of rational decision-making and strain organizational systems. Consequently, individuals are more likely to fragment interconnected elements into either/or choices, actions, and interpretations, obscuring their inherent interdependence.\u003c/p\u003e\n\u003cp\u003eAs the data analysis progressed, it became clear that the most compelling aspect of the dataset was the exploration of paradoxes. Consequently, the dynamic organizing model of paradoxes proposed by Smith and Lewis (39) was applied to the data set. Within this framework, the first aspect of the model was used, addressing the emergence and recognition of paradoxical tensions, as well as the last step, which examines strategies for resolving these tensions. The third step was deliberately omitted, which explores the cyclical responses to paradoxes, as the primary objective was to identify existing barriers and evaluate optimal strategies for their resolution rather than analyzing how organizations transition between different management approaches over time. Accordingly, in the subsequent data analysis, the paradoxical tensions revealed by the previously identified themes of barriers were examined. How these tensions were initially latent and what factors rendered them salient where also investigated. Finally, the solutions proposed by healthcare professionals were explored, aiming to resolve these paradoxical tensions in the context of enabling efficient hospital-wide patient flow.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eThis study identifies seven paradoxes experienced by frontline healthcare professionals associated with hospitals\u0026rsquo; efforts to enable efficient hospital-wide patient flow, see Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e. The characteristics of each paradox are outlined below and supported by representative quotes from the interviews. In total, the interviews generated 650 unique opinions and recommendations, which were synthesized into these seven paradoxes. Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e presents a structured overview, beginning with a description of each paradox and the associated latent tensions. It then outlines the salient tensions that emerge and the factors that transform these tensions from latent to salient.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003cstrong\u003e:\u003c/strong\u003e Seven paradoxes to efficient hospital-wide patient flow\u003c/p\u003e\n\u003cp\u003e\u003cimg 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\" style=\"width: 1264px;\" width=\"1264\" height=\"895\"\u003e\u003cbr\u003e\u003c/p\u003e\n\u003ch3\u003eParadox #1: System-wide patient trajectories but local patient focus\u003c/h3\u003e\n\u003cp\u003eThere is a divergence of opinions among healthcare providers regarding whether a clear flow-oriented focus exists within their hospital. Some argue that, at the local level, their unit actively engages with flow-related issues and seeks to identify flow-related bottlenecks. However, many others believe that such a focus is absent and that they do not work with flow principles at all. Some participants perceive that hospital management discusses patient flow but that these discussions seldom transform into something tangible for frontline healthcare professionals.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u0026ldquo;I imagine a bunch of managers having a picture of how the patient flow should be done. But how is it communicated down? In my world, it doesn\u0026apos;t seem to be. It doesn\u0026apos;t seem to trickle down to all the different units, but gets stuck somewhere along the way.\u0026rdquo;\u003c/em\u003e \u0026ndash; [nurse, emergency department, tertiary care hospital, case A]\u003c/p\u003e\n\u003cp\u003eThe lack of a clearly defined vision from the hospital management regarding patient flow improvements is a common concern among many participants, and they desire a clearer strategy translated into concrete implications for different departments, units, and divisions within the hospital. The lack of a flow strategy hampers collaboration with adjacent units on flow improvements due to the ambiguity surrounding its meaning, implementation, and objectives. It also becomes unclear what to prioritize, and how to prioritize, related to the flow of patients. The missing hospital-wide approach becomes clear when facing overcrowding, and protectionism or patient responsibility avoidance appears. It also becomes evident when clinics choose to expand their services without considering consequences for others and new and many times problematic constraints or bottlenecks appear. Therefore, several study participants expressed a desire for the hospital to develop an increased and clearer central coordination and effectively communicated strategy or framework to facilitate improved patient flow throughout the entire organization.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u0026ldquo;The general goal is for the flow of patients to go quickly but each department gets to develop its own routines. However, no one connects them across the hospital, so that it is really a working plan, put in place in different departments or different parts of the hospital, to really provide some improved flow. That is what we would need\u0026rdquo;\u003c/em\u003e \u0026ndash; [physician (surgeon), surgical clinic, secondary care hospital, case D].\u003c/p\u003e\n\u003cp\u003ePrevious research has demonstrated how most patient flows within hospitals are interconnected, as they rely on the same resources to facilitate processes and advance patients along their care journey. The allocation of available resources (staff, equipment, hospital beds, etc.) to appropriate departments and an optimal distribution among patient groups necessitates central coordination, which is often insufficient. Physicians and nurses confirm this and highlight a lack of effective central coordination of shared resources. The coordination of hospital beds is typically managed by an ED-based bed coordinator who has limited authority over patient placements and faces significant challenges navigating between clinics, which often attempt to avoid assuming responsibility for a patient, suggested to them. Whether undertaken by a bed coordinator or a senior physician (on-call hospitalist), the task of overseeing patient placements across the hospital is frequently described as stressful and unrewarding.\u003c/p\u003e\n\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\n \u003ch2\u003eParadox #2: Advocating for less rigidity, but specialization builds rigidity\u003c/h2\u003e\n \u003cp\u003eNurses and physicians often oppose the thought of standardizing healthcare processes, arguing that the healthcare system must be able to address each patient\u0026apos;s unique set of problems. However, many participants perceive that there is an ongoing strong trend towards standardization driven mostly by the increasing specialization of medical expertise but to some extent also by nursing. They observe that their patients increasingly seek healthcare with multiple, concurrent symptoms and diagnoses and that in the past, it was easier than today to categorize patients into different groups and assign them to the most appropriate department for care. The increasing specialization has, however, made transfers of patients between hospital departments increasingly difficult, as many departments are reluctant to accept patients with multiple conditions that fall outside their specialized scope. Departments prefer to treat only those patients for whom they have specialist expertise. This protectionism is also most strongly experienced when the hospital is facing overcrowding when fast transfers are more important than ever. This specialisation trend exacerbates the challenge of moving patients across the hospital in a swift and timely fashion.\u003c/p\u003e\n \u003cp\u003e\u003cem\u003e\u0026ldquo;Take as an example an oncology patient with brain metastases quite far along in their disease, who has palliative treatment in its final stages. They come into the emergency room with neurological problems and a headache. All signs that there is a process in the brain. Then there can be a tug of war, or rather a push and pull between the neurologist and oncologist about who should take care of the patient. When the oncologist says that this is an isolated neurological problem and the neurologist says that this is a complex oncological disease with an expected outcome that the oncologist can absolutely treat. But, the oncologist is full. The neurologist has one place left. It can be a discussion that can last for hours while the patient remains in the emergency room.\u0026rdquo;\u003c/em\u003e - [physician, emergency department, tertiary care hospital, case F]\u003c/p\u003e\n \u003cp\u003eThe same dilemma also applies to surgical procedures, where surgeons continually seek to sub-specialize, resulting in an even narrower patient group they are willing to operate on. Today, planning the surgical program comes with significant scheduling challenges as there is little operational flexibility. In the end, there is little margin if anyone is sick or if any patient group is overrepresented, increasing the risk for canceled surgeries. Despite this, there is a well-established belief that greater specialization improves medical quality. However, increased specialization also necessitates that patient cohorts become more homogeneous and care processes more standardized, something that healthcare professionals generally resist. This tension gives rise to a standardization paradox. Rather than the healthcare profession adapting to the needs of the patient, the patient must conform to the structures of the healthcare profession. This approach is inherently at odds with the goal of providing individualized and tailored care to complex and multi-morbid patients who present in emergency settings or are scheduled for surgery.\u003c/p\u003e\n \u003cp\u003e\u003cem\u003e\u0026ldquo;The trend in the hospital, and healthcare in general, towards becoming increasingly specialized means that it is a fairly fine-meshed net for patients to get through to get the care they need, and the flow of patients is slowing down.\u0026rdquo;\u003c/em\u003e - [physician, medical clinic, tertiary care hospital, case B]\u003c/p\u003e\n\u003c/div\u003e\n\u003ch3\u003eParadox #3: Mandate with doctors, but flow understanding with nurses\u003c/h3\u003e\n\u003cp\u003eHealthcare professionals operate based on various underlying logics that influence their reasoning, work ethics, and areas of focus. A notable distinction frequently observed by both physicians and nurses is that nurses often possess a more intuitive understanding of patient flow compared to physicians. Nurses appear to be better trained in considering the patient\u0026rsquo;s entire care trajectory and the need for coordination to ensure continuous progression along this journey. In contrast, physicians tend to concentrate more on the immediate clinical situation, making medical assessments and treatment decisions based primarily on the patient\u0026apos;s current condition, while also prioritizing acute cases among patients with diverse needs.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u0026ldquo;There is a lot to remember to do and it feels very extensive. It is very complex. At the same time, we are faced with this problem that we cannot do everything with everyone. At the same time, we are not used to thinking about flow either. If I do this for this patient now, is someone else being displaced? We are not trained in it that much.\u0026rdquo;\u003c/em\u003e \u0026ndash; [physician, medical clinic, secondary care hospital, case C]\u003c/p\u003e\n\u003cp\u003eA key challenge arises when decisions regarding patient progression must be made, as the authority to do so rests solely with the physician, given their legal responsibility for the patient. The absence of a comprehensive understanding of patient flow can lead to unnecessary congestion and bottlenecks, where less medically urgent patients remain in the system, causing significant delays in overall patient movement. This issue is particularly pronounced in inpatient wards, where patients are typically prioritized from the most to the least critically ill. Consequently, ward rounds often conclude with patients who are merely awaiting discharge orders. Nurses, who are essential in assisting physicians with coordinating patient flow, bear a heavy and sometimes impractical workload, despite lacking the authority to influence progression. Frustration escalates when patients remain in the hospital longer than necessary, and discharge plans are not met. Several participants emphasized the need for stronger collaboration between professional groups to facilitate knowledge exchange, with some suggesting that nurses should be granted greater authority in managing patient flow. Similarly, in surgical scheduling, the responsibility for determining the timing of procedures lies with the surgeons. However, there is often a lack of awareness regarding the downstream effects of the surgical schedule on postoperative units and, ultimately, inpatient care. The impact of this is particularly felt on wards during periods of overcrowding, where increased congestion could be mitigated with a better understanding of downstream flow, ultimately reducing pressure and achieving a more balanced system.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u0026ldquo;The surgical program could really be designed more according to the consequences it has on our departments. It feels like the surgeons only plan surgeries based on medical priority and very rarely based on what benefits the flow the most. Patients have much more predictable treatment times than many seem to believe and thus the flow out could be much smoother.\u0026rdquo;\u003c/em\u003e \u0026ndash; [nurse, medical ward, tertiary care hospital, case A]\u003c/p\u003e\n\u003ch3\u003eParadox #4: Seeking workflow control, receiving workflow disorder\u003c/h3\u003e\n\u003cp\u003eHospitals are frequently characterized as among the most complex organizations in existence. They manage the simultaneous care of large numbers of patients with diverse needs, ranging from acute and semi-acute to scheduled and chronic conditions, while delivering advanced treatments that require coordination across multiple medical specialties and the integration of sophisticated technological and clinical systems. Many physicians and nurses underscore the substantial cognitive burden placed on doctors, who are expected to retain and process vast volumes of information each day to oversee the progression of all patients under their care. This challenge becomes particularly acute during periods of overcrowding, when numerous critical decisions must be made concurrently under intense time pressure.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eIt happens that I forget things, not because I\u0026apos;m careless, but there are many things to do at the same time. I have to focus on a task. In many cases you don\u0026apos;t even have the opportunity to take notes. It can happen that I get a call and I\u0026apos;m standing in a sterile gown operating or doing something. It means a lot of stress, in some cases an extremely high workload, and basically almost every day I feel that I\u0026apos;m not satisfied with certain parts of my work. I\u0026apos;m fully aware that I don\u0026apos;t have time to do everything that needs to be done. I simply forget certain things. \u0026ndash;\u003c/em\u003e [ physician (surgeon), surgical clinic, secondary care hospital, case E)\u003c/p\u003e\n\u003cp\u003eThe substantial volume of information that must be retained often results in critical details being overlooked, necessitating that nurses devote considerable time to supporting physicians with prioritization and coordination tasks.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u0026ldquo;Doctors sit and read beforehand, but might not take into account checking whether the patient has anything else planned, and then it\u0026apos;s a bit of luck whether the patient is in the room or not. Quite a lot is up to me anyway, to keep track of different parts and sort of coordinate a bit so doctors don\u0026rsquo;t miss important things. Then, we also have social coordinators on the ward who help with care planning and such. And when they are involved, they can be a good support. Either way, if we believe that a patient is going home on a certain date, then we have to think about preparing many things, and unfortunately, many things fall between cracks.\u0026rdquo;\u003c/em\u003e - [nurse, medical ward, secondary care hospital, case D]\u003c/p\u003e\n\u003cp\u003eDespite various efforts, maintaining a clear overview of care priorities remains challenging, particularly during periods of high stress and overcrowding. Under conditions of cognitive overload, healthcare professionals tend to focus primarily on the most critically ill patients. Both nurses and physicians report the negative consequences of concentrating too much responsibility in the hands of one or a few individuals, especially when patients remain hospitalized beyond their expected discharge dates. Participants consistently emphasized the need for a more equitable distribution of responsibility, along with system-level support capable of visualizing patient care processes and identifying subsequent steps in the care trajectory. Such tools, they argue, would reduce reliance on individual memory and enhance overall workflow efficiency.\u003c/p\u003e\n\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\n \u003ch2\u003eParadox #5: Seeking routine compliance, receiving routine negligence\u003c/h2\u003e\n \u003cp\u003eLike all operational elements, processes are subject to variation, which should be minimized to enhance performance (Holweg et al., 2018). Variation introduces unpredictability, impairs effective planning, and contributes to deficiencies in quality. One strategy for reducing variation involves the implementation of clear routines and standardized procedures, consistently followed by all personnel. Healthcare exemplifies a routine-driven sector, where the use of checklists and treatment protocols is intended to safeguard high standards of medical care. However, findings from this study reveal that most participants perceive a lack of well-established routines and, more critically, a widespread failure to adhere to those that do exist. Participants emphasized that healthcare professionals, particularly physicians, frequently deviate from standard procedures and make autonomous decisions. While professional autonomy is widely regarded as essential to high-quality care, such deviations are often difficult for colleagues to interpret and can lead to frustration. This autonomy also diminishes the overall predictability of the healthcare system for both staff and patients. A particularly concerning issue raised was the tendency of physicians to revise treatment plans during shift changes, resulting in redundant tests, additional examinations, and prolonged hospital stays.\u003c/p\u003e\n \u003cp\u003e\u003cem\u003e\u0026ldquo;A physician decides something for a patient at the end of the week. Then another one comes along and says something completely different and changes the plans. The new physician wants to make his own opinion and assessment of the patient. It might take a day or two to do that. And then everyone starts with something new, some new thought. And then the next week comes along with some new doctor again who wants to form their own opinion about the patient. So I think we have a lot to work with there, on continuity.\u0026rdquo;\u003c/em\u003e \u0026ndash; [nurse, medical ward, tertiary care hospital, case B]\u003c/p\u003e\n \u003cp\u003eExperienced colleagues who work closely with the same patients often report seeing little tangible benefit from repeated interventions; instead, they perceive that physicians, in particular, tend to prioritize their own clinical judgment over adherence to established guidelines. During periods of hospital overcrowding, when staff must collaborate intensively to manage the workload, sudden and seemingly arbitrary changes in treatment plans can be especially disheartening. One commonly cited example involves surgeons routinely underestimating the duration of procedures, leading to operating room schedules that frequently run over time, an issue that generates considerable frustration among colleagues. These practices contribute to an already strained healthcare system becoming even more unpredictable. As a result, many healthcare professionals emphasize the need for stricter adherence to standardized routines, arguing that such compliance would improve not only patient flow management but also the overall quality of care.\u003c/p\u003e\n \u003cp\u003e\u003cem\u003e\u0026ldquo;Surgeons have been given operating blocks to deal with but plan surgeries so that they will be finished before the end of the block time even though they have never performed a surgery within the intended time. Then we have to work overtime. We usually realize this immediately when we see the schedule for the day. It doesn\u0026apos;t feel great that the original planning and staffing schedules are not respected. It creates a lot of variation, unpredictability, and overtime work for the unit.\u0026rdquo;\u003c/em\u003e \u0026ndash; [nurse, operating room, tertiary care hospital, case F]\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\n \u003ch2\u003eParadox #6: Believing in proactivity, working reactively\u003c/h2\u003e\n \u003cp\u003eHealthcare operates within a dynamic environment, where patients\u0026rsquo; conditions may improve or deteriorate rapidly, necessitating corresponding adjustments in healthcare operations. Professionals recognize that plans often shift throughout the course of a single shift, both with respect to patient treatment and the optimal allocation of resources such as staff, treatment rooms, and equipment. However, a recurring concern expressed in several interviews is that the planning horizon is often too short. Greater foresight in operational planning is seen as a potential enabler of more efficient patient flow. Frustration arises when patients remain in care longer than necessary simply because short-term planning prevents timely transitions or discharges.\u003c/p\u003e\n \u003cp\u003e\u003cem\u003e\u0026ldquo;In the best of worlds, it would have been that we think more about the continuous patient trajectory, and I think it would have been better if you had a plan for the patient already when they are admitted. But unfortunately, it often happens that we only plan half days ahead, until next round, and after the round, and then until the following afternoon.\u0026rdquo; \u0026ndash;\u003c/em\u003e [nurse, medical ward, secondary care hospital, case C]\u003c/p\u003e\n \u003cp\u003eHealthcare personnel perceive hospital bed coordination as predominantly reactive, lacking a strategic role in optimizing patient flow across the hospital or in planning patient movement with consideration for downstream effects. Many physicians and nurses express the view that a more clearly defined coordination structure, endowed with greater authority, would support more efficient transfers between the emergency department, acute care units, intensive care units, and hospital wards. Although many bottlenecks are predictable, the absence of centralized coordination often results in recurring delays in patient progression, which several respondents described as disheartening. Interviewees also emphasized that patient care trajectories are more predictable than commonly assumed and suggested that a proactive, forward-looking approach to planning could significantly improve flow. Furthermore, new technologies, or innovative applications of existing technologies, were identified as potential tools to support healthcare professionals in adopting a more anticipatory strategy, enabling more accurate assessments of patient care trajectories through the application of statistical analysis.\u003c/p\u003e\n \u003cp\u003e\u003cem\u003e\u0026rdquo;Patients come in clear prototypes, and you can determine with a fair amount of certainty how many days they will need to be cared for. And with new technology, we should be even better at being able to determine when a patient is likely to be discharged. This allows us to be much more proactive, than we are many times today, in care planning several days before discharge, with everything that needs to be done.\u0026rdquo;\u003c/em\u003e \u0026ndash; [physician (surgeon), operating room, secondary care hospital, case D]\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\n \u003ch2\u003eParadox #7: Emphasizing statistical feedback, only not for flow\u003c/h2\u003e\n \u003cp\u003eImproving performance necessitates an understanding of current performance levels. While healthcare providers routinely engage in extensive measurement, particularly through the continuous monitoring of medical quality outcomes, which is central to healthcare operations and development, the use of metrics related to patient flow appears inconsistent. When asked whether they utilize indicators reflecting patient flow performance, physicians and nurses offered varied responses. Some reported using flow-related metrics, such as Length of Stay (LoS), average discharge time, and the average number of discharges before noon. Others, however, indicated that they do not employ any measures specifically linked to patient flow.\u003c/p\u003e\n \u003cp\u003e\u003cem\u003e\u0026ldquo;No, we no longer get any information about whether we perform well or badly or how many patients we are discharging at a certain time. I actually have no idea about anything related to patient flow, we get no feedback.\u0026rdquo;\u003c/em\u003e \u0026ndash; [nurse, surgical ward, secondary care hospital, case E]\u003c/p\u003e\n \u003cp\u003eA few respondents reported receiving feedback from management, although this occurs infrequently. Notably, all participants working in units that employ flow metrics perceived these measures as lacking motivational value. While the metrics themselves were not viewed as inherently problematic, the associated performance targets were frequently described as unrealistic and largely unattainable. Consequently, participants expressed low motivation to engage with these measures and reported little effort to meet the prescribed targets.\u003c/p\u003e\n \u003cp\u003e\u003cem\u003e\u0026ldquo;Even though there are a lot of things measured in association with surgical procedures related to the flow of patients, few or no one directly follows them or cares. The goals are not realistic, either. They are simply not motivating. That is a problem\u003c/em\u003e.\u0026rdquo; \u0026ndash; [physician (anaestesiologist), operating room, tertiary care hospital, case F]\u003c/p\u003e\n \u003cp\u003eThe consequences of failing to measure patient throughput performance often become apparent when new management or hospital leadership express dissatisfaction with production outcomes and introduce new performance targets or staff-to-patient ratios. In such cases, the unit may lack the necessary data to assess its current capabilities, determine the feasibility of the new requirements, or predict the impact of these changes on patient flow performance.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\n \u003ch2\u003eResolutions to paradoxes\u003c/h2\u003e\n \u003cp\u003eThis study identifies seven paradoxes that impede healthcare professionals\u0026apos; efforts to improve patient flow across hospital systems. While illuminating such paradoxes and contradictions in healthcare delivery is essential, the principal aim of this research is to deepen the understanding of hospital-wide patient flow challenges and explore potential solutions. Drawing on the perspectives of frontline healthcare professionals, those without formal managerial responsibilities, whose voices are frequently underrepresented in the literature (\u003cspan class=\"CitationRef\"\u003e15\u003c/span\u003e\u0026ndash;\u003cspan class=\"CitationRef\"\u003e17\u003c/span\u003e), the study presents a series of proposed resolutions to the identified paradoxes, see Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e. \u003cem\u003eFirst\u003c/em\u003e, participants advocate for stricter adherence to routines, greater continuity in scheduling, and enhanced transparency in planning processes to foster compliance and create a more predictable work environment. \u003cem\u003eSecond\u003c/em\u003e, they emphasize the importance of centralized flow coordination, a clearly articulated patient flow strategy, and strengthened inter-organizational collaboration to promote a more integrated, system-wide perspective on patient flow. \u003cem\u003eThird\u003c/em\u003e, to reduce systemic rigidity, respondents suggest expanding the competence profiles of healthcare staff and establishing a centralized mandate for patient placement. \u003cem\u003eFourth\u003c/em\u003e, improved control over workflows is seen as achievable through the deployment of advanced IT system support and broader distribution of responsibilities among clinical staff. \u003cem\u003eFifth\u003c/em\u003e, a more proactive approach to care delivery is deemed attainable through increased central flow coordination, the implementation of supportive IT solutions, and the advancement of forward-looking patient flow planning. \u003cem\u003eSixth\u003c/em\u003e, participants stress the need for more visible and engaged leadership, the development of meaningful performance metrics, and the alignment of these metrics with day-to-day operations to enhance their motivational impact. \u003cem\u003eSeventh\u003c/em\u003e, they call for improved understanding of patient flow dynamics among physicians, a more prominent role for nurses in flow decision-making, and strengthened interprofessional collaboration to enhance collective performance in managing flow progression.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eImproving patient throughput at hospitals is crucial to meeting the growing demands of future healthcare and prior research highlights that enhanced patient flow is a key factor in boosting hospital productivity (\u003cspan additionalcitationids=\"CR6 CR7\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). As patients increasingly navigate complex care pathways involving multiple professionals, departments, and administrative units, a system-wide perspective has become essential (\u003cspan additionalcitationids=\"CR12 CR13\" citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e). However, most existing studies on hospital-wide patient flow have focused on managerial perspectives and strategies, largely overlooking the experiences of frontline healthcare professionals, those who interact most directly with patients throughout their hospital journey. This study present that although healthcare organizations often articulate a clear idea for achieving efficient patient flows, healthcare professionals experiences frequently diverge from those ideals. They acknowledge organizational objectives and values concerning patient flow, yet routinely encounter situations that contradict them. Based on these findings, this study identifies seven paradoxes associated with enabling efficient hospital-wide patient flows in which non-managerial staff at large hospitals perceive direct conflicts among the hospital\u0026rsquo;s stated values, philosophies, and objectives. These contradictions contribute to a work environment characterized by frustration, stress, and unpredictability.\u003c/p\u003e \u003cp\u003eParadoxes in patient flow have been previously studied by Kreindler (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e), who examined systemic barriers by conducting interviews with a large number of hospital managers within a Canadian region. The study identified three key paradoxes: (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e) \"initiatives improve parts of the system but fail to address underlying systemic constraints,\" (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) \"local innovation clashes with regional integration,\" and most notably, (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e) \"rules that improve service organization for my patients create obstacles for yours.\" A common theme among these paradoxes, as identified by Kreindler (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e), is their emergence largely due to the absence of a system-wide approach to patient flow and its optimization. Enhancements in one part of the system often create unintended challenges elsewhere, and such improvements may not align with the workflows of the broader system. This study confirms but also refines these paradoxes, emphasizing that while autonomy benefits independent actors, it can disadvantage those who depend on others. Similarly, while specialization alleviates burdens for some, it often shifts the workload onto others.\u003c/p\u003e \u003cp\u003eThis study highlights the strong institutional belief in the capacities of physicians, leading hospitals to assign them mandates and decision-making responsibilities that they may not be equipped to fully comprehend or manage. Delegating certain physician responsibilities to other professional groups appears not only beneficial for patient flow but also advantageous for the professional development and effectiveness of physicians (\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e, \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e). These paradoxes further underscore the perspectives of many healthcare professionals, who argue for designing workflows based on patient movement rather than the rigid structures of medical specializations (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). Many professionals find the prevailing local focus on patient flow, coupled with a reactive rather than proactive organizational approach, increasingly outdated, especially in light of technological advancements and emerging organizational models that support a more anticipatory healthcare system (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e). Finally, choosing not to measure patient flow, despite the centrality of medical quality in hospital performance, appears unwise. Patient flow directly impacts individual patients, facilitating faster transfers and reducing iatrogenic complications, while also improving healthcare system efficiency by increasing overall accessibility (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eMost of the paradoxes discussed above become visible to healthcare professionals when facing some form of scarcity, whether of beds, staff, space, or operating room (OR) time. Healthcare professionals frequently encounter resource constraints and often attribute inefficient patient flow to a lack of adequate resources. The emergence of bottlenecks is one of the most common indicators of systemic inefficiencies (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e). For instance, when auxiliary beds are required due to ward overcrowding, deficiencies become apparent. Similarly, when OR cases consistently exceed scheduled capacity, forcing staff to work overtime for consecutive days, the limitations of the system become unmistakable. Paradoxes also arise in response to change, whether through modifications in routines, new regulatory requirements, or the expansion and restructuring of services. People are generally resistant to change, particularly when it is perceived as irrational or difficult to comprehend, which often brings paradoxes to the forefront (\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e). Additionally, some paradoxes emerge due to plurality, conflicting ideas, interests, or mandates, and decision-making processes (\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e). These tensions become evident when there is disagreement over where to place multimorbid patients or when a culture of professional autonomy leads to shifts in patient care trajectories with every change in staff. This study, however, underscores that many of these paradoxes, whether driven by scarcity, change, or conflicting interests, can likely be mitigated through enhanced system-wide collaboration, a deeper understanding of patient flow dynamics, and greater adherence to standardized routines and operational planning. These findings also align with previous research advocating for reducing unnecessary variation in healthcare processes to improve overall efficiency (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThis study offers a bottom-up perspective on solutions for improved hospital-wide patient flows that complements the patient flow improvement framework proposed by \u0026Aring;hlin et al. (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e), which is grounded in the viewpoints of healthcare managers. The association between paradoxes and paradoxical resolutions presented in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e, has, therefore, been linked to the solutions categories presented in the framework on hospital-wide patient flows (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e) by \u0026Aring;hlin et al (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e) in a comparison of bottom-up and top-down solutions for the improvement of hospital-wide patient flows, see Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThis comparison presents that frontline healthcare professionals largely align with senior management in their views on how to enhance hospital-wide patient flow. Similar to senior leaders, frontline healthcare professionals emphasize the importance of \u003cem\u003edeveloping standards, checklists, and routines\u003c/em\u003e, as they highlight the need to improve adherence to routines and set schedules. They also see the benefits of \u003cem\u003ebuilding a coordination and transfer structure\u003c/em\u003e, as they highlight the need for central flow coordination and placement mandate, but also the need to expand and better use competencies among healthcare professionals to promote patient flow. Healthcare professionals also highlight the need for \u003cem\u003eimproving the management of operations\u003c/em\u003e by making production planning more transparent and proactive, and using more meaningful flow metrics, as well as making the management more visible and engaged in patient flow improvements. \u003cem\u003eAligning the organisation\u003c/em\u003e is seen as important, enabling clearer flow strategies, increased system-wide understanding of the patient flow, and stronger collaboration between both professional groups as well as inter-organisational units. Last, they also want hospitals to \u003cem\u003einvest in digital and analytical tools\u003c/em\u003e to improve the support healthcare professionals can receive from IT systems in progressing patients along their care trajectories and to develop visible and better synchronized flow metrics across their organisations.\u003c/p\u003e \u003cp\u003eConcerning the three categories without connections: \u003cem\u003eoptimize capacity utilization and occupancy rates\u003c/em\u003e, \u003cem\u003eensure physical capacity capabilities\u003c/em\u003e, and \u003cem\u003eseek external solutions and policy changes\u003c/em\u003e, no paradoxes or paradoxical resolutions seem to be associated. The reason behind this is likely that they are associated with the factors rendering latent paradoxes salient instead of imposing organisational paradoxes on the patient flow. Smith and Lewis (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e) explain that paradoxes evolve in the process of designing and forming organisations. In this study, healthcare professionals articulated an ideal vision of how to improve the flow of patients throughout their organisations, while simultaneously describing experiences that starkly contrasted with these ideals. The three top-down solution categories without connections to the bottom-up solutions seem to be more connected to needed resources (staff, beds, rooms, facilities) instead of work methods. Consequently, if these categories of solutions are met, i.e, when there is little resource scarcity, then the seven paradoxes identified in this study may remain latent without being rendered salient.\u003c/p\u003e \u003cp\u003eA novel contribution of this bottom-up perspective lies in its focus on how healthcare professionals might reconfigure their roles, competencies, and responsibilities to better support patient flow. A critical issue identified is the misalignment between nurses\u0026rsquo; understanding of flow dynamics and their lack of authority to influence patient progression decisions. There seem to be two paths ahead: either hospitals need to expand nurses\u0026rsquo; mandates to progress patients along their care trajectories, or an enhanced collaboration between nurses and physicians becomes essential to ensure that flow-related knowledge is effectively translated into action, thereby improving overall patient throughput.\u003c/p\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eLimitations and Future Research\u003c/h2\u003e \u003cp\u003eThis study is subject to several limitations. Firstly, it relies on a single analyst. While employing multiple coders would have been preferable, rigorous participant validation ensured the integration of diverse perspectives. A well-structured, semi-standardized interview guide was utilized, facilitating a more consistent comparison across participants. Furthermore, the study\u0026rsquo;s robustness was enhanced by the substantial number of participants and the inclusion of six different hospitals, thereby strengthening the validity and generalizability of the findings. Another limitation pertains to the online format, as all interviews were conducted via Zoom. This virtual setting posed challenges in accurately capturing non-verbal cues such as body language and facial expressions, potentially constraining the comprehensive interpretation of participants\u0026rsquo; responses. Additionally, the researcher\u0026rsquo;s background in Operations Management introduces inherent biases and preconceptions. This challenge is further reinforced by the researcher\u0026rsquo;s prior professional experience in a hospital setting, collaborating closely with doctors and nurses, which may have influenced their understanding of the participants\u0026rsquo; challenges and perspectives.\u003c/p\u003e \u003cp\u003eThere are several promising avenues for future research. One potential topic is to investigate the differences in patient flow management and outcomes across hospitals, particularly in relation to the extent of authority and autonomy granted to nurses. Another area of interest is examining how a hospital-wide focus on patient flow is operationalized at various managerial levels, and how it can be tailored to be meaningful and motivating at each level of the organization. Finally, it would be valuable to explore the appropriate degree of independence and autonomy that healthcare professionals, especially physicians, should be granted. While such autonomy is often regarded as essential for efficient and responsive healthcare, it can also introduce confusion, inconsistency, and unpredictability in the delivery of care.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThis study examines the perspectives of frontline healthcare professionals regarding the factors that hinder and facilitate hospital-wide patient flow. Nurses and physicians report experiencing significant contradictions between the ideals guiding how work should be carried out and the realities of how it is actually performed. The analysis identifies seven key paradoxes related to leadership and organizational structures, routines and procedures, professional culture, and the use of technology and performance metrics. These paradoxes become particularly pronounced under organizational pressure, during changes to work routines, when patient care is compromised, or when staff are required to work overtime. The study presents multiple strategies aimed at addressing these paradoxes and enhancing the overall flow of patients throughout the hospital. Frontline healthcare professionals largely align with senior management on strategies to improve hospital-wide patient flow, emphasizing the need for aligned structures, objectives, and performance metrics. They advocate for centralized coordination, adherence to standardized routines, and responsive hospital designs. Importantly, professionals highlight the need to redefine roles and empower nurses, addressing the gap between their flow-related knowledge and limited decision-making authority. Strengthening nurse-physician collaboration is essential to translating this knowledge into improved patient flow.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study has been conducted in Sweden according to Swedish laws and regulations and adheres to the Declaration of Helsinki. Participants were interviewed in their professional role, and no personal or sensitive information was obtained. According to the Swedish Ethical Review Act (\u003cem\u003eLag om etikpr\u0026ouml;vning av forskning som avser m\u0026auml;nniskor 2003:460\u003c/em\u003e), this study does not need ethical clearance by a Regional Ethical Review Authority as it does not include any primary empirical data on biological material or sensitive personal information. No ethics approval has consequently been applied for before conducting this study. Informed consent has been obtained from all participants, and all quotes have been approved by the party concerned before publication.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll datasets generated or analyzed during this study are included in the main manuscript [and its supplementary information files].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe author declares that there are no competing interests concerning the material discussed in this manuscript. This accounts for interests of either financial nature (such as grants, consultancies, equities, or other employments) or non-financial nature (such as professional, personal relationships, or subjective beliefs).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe only source of funding has come from Chalmers University of Technology to support the author with a salary to conduct the research. Furthermore, Chalmers University of Technology has, in its role as sponsor, not in any way been involved in, nor interfered with the design, execution, or presentation of the research.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study has been designed and conducted by one independent researcher. The manuscript has also only been written by the same independent researcher. The author of the manuscript is accountable for all aspects of the accuracy and integrity of the manuscript. The article is original and has not already been published in a journal and is not currently under consideration by another journal. The researcher agrees to the terms of the BioMed Central Copyright and License Agreement.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; information\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDepartment of Technology Management and Economics, Chalmers University of Technology, Vera Sandbergs All\u0026eacute; 8, G\u0026ouml;teborg 412 96, Sweden\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eOECD EC. Healthcare at a Glance: Europe 2024: State of the Health in the EU Cycle. Paris; 2024.\u003c/li\u003e\n\u003cli\u003eStadhouders N, Kruse F, Tanke M, Koolman X, Jeurissen P. Effective healthcare cost-containment policies: A systematic review. 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Critical Success Factors for Successful Implementation of Healthcare 4.0: A Literature Review and Future Research Agenda. Int J Environ Res Public Health. 2023;20(5).\u003c/li\u003e\n\u003cli\u003eGlouberman S, Mintzberg H. Managing the care of health and the cure of disease--Part I: Differentiation. Health Care Manag rev. 2001;26(1):56-69.\u003c/li\u003e\n\u003cli\u003ePorter M. What is Value in Health Care? N Engl J Med. 2010;363(26).\u003c/li\u003e\n\u003cli\u003eRadnor Z, Holweg M, Waring J. Lean in healthcare: the unfilled promise? Soc Sci Med. 2012;74(3):364-71.\u003c/li\u003e\n\u003cli\u003evan den Oetelaar W, van Stel H, van Rhenen W, Stellato R, Grolman W. Balancing nurses\u0026apos; workload in hospital wards: study protocol of developing a method to manage workload. BMJ Open. 2016;6(11):e012148.\u003c/li\u003e\n\u003cli\u003eHans E, van Houdenhoven M, Hulshof P. A Framework for Healthcare Planning and Control. In: Hall R, editor. Handbook of Healthcare System Scheduling. 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Toward a theory of paradox: A dynamic equilibrium model of organizing. Acad Manage J. 2011;36(2).\u003c/li\u003e\n\u003cli\u003eErthal A, Frangeskou M, Marques L. Cultural tensions in lean healthcare implementation: A paradox theory lens. Int J Prod Econ. 2021;233.\u003c/li\u003e\n\u003cli\u003eDenis J, Langley A, Rouleau L. The Practice of Leadership in the Messy World of Organizations. Leadership. 2010;6(1):67-88.\u003c/li\u003e\n\u003cli\u003eL\u0026uuml;scher L, Lewis M. Organizational Change and Managerial Sensemaking: Working Through Paradox. Acad Manage J. 2008;51(2):221-40.\u003c/li\u003e\n\u003cli\u003eSmith W, Tushman M. Managing Strategic Contradictions: A Top Management Model for Managing Innovation Streams. Organ Sci. 2005;16(5):522-36.\u003c/li\u003e\n\u003cli\u003eEscrig-Pinol A, Hempinstall M, McGilton K. Unpacking the multiple dimensions and levels of responsibility of the charge nurse role in long-term care facilities. Int J Older People Nurs. 2019;14(4):e12259.\u003c/li\u003e\n\u003cli\u003eJulnes S, Myrvang T, Reitan L, Ronning G, Vatne S. Nurse leaders\u0026apos; experiences of professional responsibility towards developing nursing competence in general wards: A qualitative study. J Nurs Manag. 2022;30(7):2743-50.\u003c/li\u003e\n\u003cli\u003eHowell MD, Stevens JP. Rationing Without Contemplation: Why Attention to Patient Flow Is Important and How to Make It Better. In: Scales DC, Rubenfeld GD, editors. The Organization of Critical Care: An Evidence-Based Approach to Improving Quality. New York, NY: Springer New York; 2014. p. 155-75.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-health-services-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bhsr","sideBox":"Learn more about [BMC Health Services Research](http://bmchealthservres.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/BHSR/default.aspx","title":"BMC Health Services Research","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Healthcare, Efficiency, Productivity, Throughput, Frontline, System-wide, Improvement, Challenges","lastPublishedDoi":"10.21203/rs.3.rs-6663600/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6663600/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e: As healthcare demand outpaces capacity, improving hospital productivity is critical. Prior research suggests hospital-wide patient flow improvements can enhance efficiency but has largely neglected the insights of frontline healthcare professionals without managerial responsibilities. This study explores their perspectives on enabling efficient patient flow across hospitals.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods: \u003c/strong\u003eSemi-structured interviews were conducted with 15 nurses and 15 physicians at six Swedish tertiary and secondary care hospitals. A thematic analysis followed, based on inductive reasoning to identify meaningful subjects and themes.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e: Participants identified seven paradoxes hindering patient flow, linked to leadership, organizational design, routines, professional culture, and technology. These tensions intensify under operational stress and often lead to overtime or compromised care. Professionals emphasized the need for more aligned structures, clearer patient flow strategies, and performance metrics that support efficient transitions of patients. They advocated for more centralized coordination, better adherence to standardized routines, and investment in IT tools to improve decision-making. A critical finding is the gap between nurses’ understanding of patient flow and patient progression and their limited authority and mandates to progress patients, highlighting the need for stronger nurse-physician collaboration.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions\u003c/strong\u003e: Enhancing hospital-wide patient flow requires increased system-level coordination, better aligned hospital structures, and improved operational planning. The solutions proposed by frontline professionals also largely align with previously identified managerial strategies for improved hospital-wide patient flows, suggesting a shared understanding that could be leveraged to drive meaningful change.\u003c/p\u003e","manuscriptTitle":"Bottom-up perspectives on hospital-wide patient flow – A multi-site qualitative study of solutions to organizational paradoxes","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-06-18 06:19:07","doi":"10.21203/rs.3.rs-6663600/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-07-14T10:02:10+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-07-02T15:31:39+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-06-29T19:58:37+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"335259246575554939623697273227836581019","date":"2025-06-27T12:37:54+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-06-27T09:13:38+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-06-26T15:03:42+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"284286945303103528534432668330220551649","date":"2025-06-23T07:09:20+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"48119171094889366366632519004183847938","date":"2025-06-19T07:04:34+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"162141531156181861816192141069749211526","date":"2025-06-17T14:10:01+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-06-13T07:54:12+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-06-11T10:00:35+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-05-21T04:32:35+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-05-20T08:51:45+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Health Services Research","date":"2025-05-20T08:50:37+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-health-services-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bhsr","sideBox":"Learn more about [BMC Health Services Research](http://bmchealthservres.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/BHSR/default.aspx","title":"BMC Health Services Research","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"f041e75b-fd03-4e75-96cc-ca9b3ceddc10","owner":[],"postedDate":"June 18th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2026-02-23T16:03:10+00:00","versionOfRecord":{"articleIdentity":"rs-6663600","link":"https://doi.org/10.1186/s12913-026-14214-w","journal":{"identity":"bmc-health-services-research","isVorOnly":false,"title":"BMC Health Services Research"},"publishedOn":"2026-02-20 15:59:30","publishedOnDateReadable":"February 20th, 2026"},"versionCreatedAt":"2025-06-18 06:19:07","video":"","vorDoi":"10.1186/s12913-026-14214-w","vorDoiUrl":"https://doi.org/10.1186/s12913-026-14214-w","workflowStages":[]},"version":"v1","identity":"rs-6663600","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6663600","identity":"rs-6663600","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}