Capacity of clinical pathways--a strategic multi-level evaluation tool

[Integrated care concepts and multidisciplinary process chains in a radiological context]

Modern patient-centered and cost-efficient care concepts in hospitals require the mapping of multidisciplinary process chains into clinical pathways. Clinical decision support systems and operations research methods use algorithms to classify patients into homogeneous groups and to model a complete clinical pathway for scheduling individual procedures. An improvement of the economic situation of the care facility can be achieved through improved resource utilization, reduced patient waiting times and a shortening of the length of stay. The interdisciplinary use of centrally stored interoperable information and comprehensive care management via information technology (IT) services lay the foundation for the dissolution of traditional IT system architectures in medicine and the development of flexibly integrable modern system platforms. New IT approaches such as the semantically standardized definition of procedures and resource properties, the use of clinical decision support systems and the use of service-oriented system architectures form the basis for the deep integration of radiology services into comprehensive interdisciplinary care concepts.

How to Manage Red Alert in Emergency and Disaster Unit in the Hospital? Evidence From London

This research gave an overview of coordinated hospital planning issues. In these issues, patients desire an arrangement for different source types, ideally as quickly as time permits. This field of context has just picked up academic interest, despite its reality since 1995. The way may discover a clarification for the above aspect that managing the hospital sources is regularly performed separately without taking a bigger picture. Therefore, it is particularly valid if the sources are situated in different departments. Another subsequent clarification may be related to the notoriety of the patient flow context. Hence, patients shouldn't be planned in these issues to be queued for another source or leave the system in case of their satisfaction of solicitation for the services at a particular source. The primary contribution of the present research is assisting present and new scholars via enumeration for every progression of the study of accessible decisions in the present context. Such means could be represented by major references for scientists to discover such studies endeavors tailored to their respective requirements. This principle removes the message: scientists ought to consistently coordinate their decisions concerning the setting, the capacity, and the approaches, as not all blends are conceivable.

A two-stage robust optimization approach for the master surgical schedule problem under uncertainty considering downstream resources

This paper addresses a planning decision for operating rooms (ORs) that aim at supporting hospital management. Focusing on elective patients, we determined the master surgical schedule (MSS) on a one-week time horizon. We assigned the specialties to available sessions and allocated surgeries to them while taking into consideration the priorities of the outpatients in the ambulatory surgical discipline. Surgeries were selected from the waiting lists according to their priorities. The proposed approach considered operating theater (OT) restrictions, patients' priorities and accounted for the availability of both intensive care unit (ICU) beds and post-surgery beds. Since the management decisions of hospitals are usually made in an uncertain environment, our approach considered the uncertainty of surgery duration and availability of ICU bed. Two robust optimization approaches that kept the model computationally tractable are described and applied to deal with uncertainty. Computational results based on a medium-sized French hospital archives have been presented to compare the robust models to the deterministic counterpart and to demonstrate the price of robustness.

Surgery scheduling heuristic considering OR downstream and upstream facilities and resources

BACKGROUND

Surgical theater (ST) operations planning is a key subject in the healthcare management literature, particularly the scheduling of procedures in operating rooms (ORs). The OR scheduling problem is usually approached using mathematical modeling and made available to ST managers through dedicated software. Regardless of the large body of knowledge on the subject, OR scheduling models rarely consider the integration of OR downstream and upstream facilities and resources or validate their propositions in real life, rather using simulated scenarios. We propose a heuristic to sequence surgeries that considers both upstream and downstream resources required to perform them, such as surgical kits, post anesthesia care unit (PACU) beds, and surgical teams (surgeons, nurses and anesthetists).

METHODS

Using hybrid flow shop (HFS) techniques and the break-in-moment (BIM) concept, the goal is to find a sequence that maximizes the number of procedures assigned to the ORs while minimizing the variance of intervals between surgeries' completions, smoothing the demand for downstream resources such as PACU beds and OR sanitizing teams. There are five steps to the proposed heuristic: listing of priorities, local scheduling, global scheduling, feasibility check and identification of best scheduling.

RESULTS

Our propositions were validated in a high complexity tertiary University hospital in two ways: first, applying the heuristic to historical data from five typical ST days and comparing the performance of our proposed sequences to the ones actually implemented; second, pilot testing the heuristic during ten days in the ORs, allowing a full rotation of surgical specialties. Results displayed an average increase of 37.2% in OR occupancy, allowing an average increase of 4.5 in the number of surgeries performed daily, and reducing the variance of intervals between surgeries' completions by 55.5%. A more uniform distribution of patients' arrivals at the PACU was also observed.

CONCLUSIONS

Our proposed heuristic is particularly useful to plan the operation of STs in which resources are constrained, a situation that is common in hospital from developing countries. Our propositions were validated through a pilot implementation in a large hospital, contributing to the scarce literature on actual OR scheduling implementation.

Multi-disciplinary planning in health care: a review

Multi-disciplinary planning in health care is an emerging research field that applies to many health care areas with similar underlying planning characteristics. We provide a review of the literature and describe cross-relations between different applications. We identify multiple fields to classify the literature upon. These fields relate to the system characteristics, decision characteristics, and applicability. The relevant papers for each of these fields are discussed, which provides a broad and thorough overview of the present research, and guides readers towards identifying the applicable literature for their research based on the characteristics of their problem. Furthermore, we disclose research gaps and present open challenges for further research.

A Literature Review on Validated Simulations of the Surgical Services

The surgical department is a critical unit that oversees multiple surgical-based clinical pathways and works with various other units in a hospital. This department faces numerous challenges relating to variability in demand and management of resources. The aim of this article is to review the application of validated simulation models on hospital-wide surgical services. Each of these models is broadly classified by (i) simulation method and (ii) level of detail given to the management of "patient pathways" and "staff workflows". We remark that very few studies have given attention to the management of staff workflows in their validated simulation models.

Improving the performance of surgery-based clinical pathways: a simulation-optimization approach

This paper aims to improve the performance of clinical processes using clinical pathways (CPs). The specific goal of this research is to develop a decision support tool, based on a simulation-optimization approach, which identify the proper adjustment and alignment of resources to achieve better performance for both the patients and the health-care facility. When multiple perspectives are present in a decision problem, critical issues arise and often require the balancing of goals. In our approach, meeting patients' clinical needs in a timely manner, and to avoid worsening of clinical conditions, we assess the level of appropriate resources. The simulation-optimization model seeks and evaluates alternative resource configurations aimed at balancing the two main objectives-meeting patient needs and optimal utilization of beds and operating rooms.Using primary data collected at a Department of Surgery of a public hospital located in Genoa, Italy. The simulation-optimization modelling approach in this study has been applied to evaluate the thyroid surgical treatment together with the other surgery-based CPs. The low rate of bed utilization and the long elective waiting lists of the specialty under study indicates that the wards were oversized while the operating room capacity was the bottleneck of the system. The model enables hospital managers determine which objective has to be given priority, as well as the corresponding opportunity costs.

Impact of Diabetes E-Consults on Outpatient Clinic Workflow

BACKGROUND

An e-consult is an electronic communication system between clinicians, usually a primary care physician (PCP) and a medical or surgical specialist, regarding general or patient-specific, low complexity questions that would not need an in-person consultation. The objectives of this study were to understand and quantify the impact of the e-consult initiative on outpatient clinic workflow and outcomes.

METHODS

We collected data from 5 different Veterans Affairs (VA) outpatient clinics and interviewed several physicians and staff members. We then developed a simulation model for a primary care team at an outpatient clinic. A detailed experimental study was conducted to determine the effects of factors, such as e-consult demand, view-alert notification arrivals, walk-in patient arrivals, and PCP unavailability, on e-consult cycle time.

RESULTS

Statistical tests indicated that 4 factors related to outpatient clinic workflow were significant, and levels within each of the 4 significant factors resulted in statistically different e-consult cycle times. The arrival rate of electronic notifications, along with patient walk-ins, had a considerable effect on cycle time. Splitting the workload of an unavailable PCP among the other PCPs, instead of the current practice of allocating it to a single PCP, increases the system's ability to handle a much larger e-consult demand.

CONCLUSIONS

The full potential of e-consults can only be realized if the workflow at the outpatient clinics is designed or modified to support this initiative. This study furthers our understanding of how e-consult systems can be analyzed and alternative workflows tested using statistical and simulation modeling to improve care delivery and outcomes.

Online treatment compliance checking for clinical pathways

Compliance checking for clinical pathways (CPs) is getting increasing attention in health-care organizations due to stricter requirements for cost control and treatment excellence. Many compliance measures have been proposed for treatment behavior inspection in CPs. However, most of them look at aggregated data seen from an external perspective, e.g. length of stay, cost, infection rate, etc., which may provide only a posterior impression of the overall conformance with the established CPs such that in-depth and in near real time checking on the compliance of the essential/critical treatment behaviors of CPs is limited. To provide clinicians real time insights into violations of the established CP specification and support online compliance checking, this article presents a semantic rule-based CP compliance checking system. In detail, we construct a CP ontology (CPO) model to provide a formal grounding of CP compliance checking. Using the proposed CPO, domain treatment constraints are modeled into Semantic Web Rule Language (SWRL) rules to specify the underlying treatment behaviors and their quantified temporal structure in a CP. The established SWRL rules are integrated with the CP workflow such that a series of applicable compliance checking and evaluation can be reminded and recommended during the pathway execution. The proposed approach can, therefore, provides a comprehensive compliance checking service as a paralleling activity to the patient treatment journey of a CP rather than an afterthought. The proposed approach is illustrated with a case study on the unstable angina clinical pathway implemented in the Cardiology Department of a Chinese hospital. The results demonstrate that the approach, as a feasible solution to provide near real time conformance checking of CPs, not only enables clinicians to uncover non-compliant treatment behaviors, but also empowers clinicians with the capability to make informed decisions when dealing with treatment compliance violations in the pathway execution.

Integration between Mathematical Programming and Fuzzy Logic to Optimize Consumers Behavior

The concept of utility is used as a decision tool for consumers to choose a commodity. Analyzing consumer behavior is complicated due to the qualitative nature of the utility. Hence, this paper investigates a quantitative method to evaluate the utility of consumers. The methodology is based on linguistic expressions of fuzzy logic. Initially, the authors identify different parameters being effective on utility of a consumer. Then, using fuzzy linguistic expressions the quantitative value of utility are determined. Also some statistical analyses are set to investigate the effective parameters on the utility. Consequently, the optimization is done applying mathematical nonlinear programming. Some analysis is performed as sensitivity study. A case study is conducted to verify the applicability and effectiveness of the proposed methodology.

Modeling the patient journey from injury to community reintegration for persons with acute traumatic spinal cord injury in a Canadian centre

Background

A patient’s journey through the health care system is influenced by clinical and system processes across the continuum of care.

Methods

To inform optimized access to care and patient flow for individuals with traumatic spinal cord injury (tSCI), we developed a simulation model that can examine the full impact of therapeutic or systems interventions across the care continuum for patients with traumatic spinal cord injuries. The objective of this paper is to describe the detailed development of this simulation model for a major trauma and a rehabilitation centre in British Columbia (BC), Canada, as part of the Access to Care and Timing (ACT) project and is referred to as the BC ACT Model V1.0.

Findings

To demonstrate the utility of the simulation model in clinical and administrative decision-making we present three typical scenarios that illustrate how an investigator can track the indirect impact(s) of medical and administrative interventions, both upstream and downstream along the continuum of care. For example, the model was used to estimate the theoretical impact of a practice that reduced the incidence of pressure ulcers by 70%. This led to a decrease in acute and rehabilitation length of stay of 4 and 2 days, respectively and a decrease in bed utilization of 9% and 3% in acute and rehabilitation.

Conclusion

The scenario analysis using the BC ACT Model V1.0 demonstrates the flexibility and value of the simulation model as a decision-making tool by providing estimates of the effects of different interventions and allowing them to be objectively compared. Future work will involve developing a generalizable national Canadian ACT Model to examine differences in care delivery and identify the ideal attributes of SCI care delivery.

Doctor shopping: a concept analysis

Prescription drug abuse is a significant problem in the United States that poses a serious health risk to Americans and is therefore significant to the field of nursing. The prescription drugs that are designated in the United States as having abuse potential are called controlled or scheduled drugs. The most common types of abused prescription drugs are benzodiazepines prescribed for anxiety, opioids prescribed for pain, and stimulants prescribed for attention deficit disorder. These prescription drugs are abused by taking larger doses than prescribed for nonmedical use to achieve a high or euphoric feeling, or are sold illicitly for profit. In 2009, there were 2.4 million nonmedical users of prescription opioids in the United States. These prescription drugs are often obtained by seeing multiple prescribers, often under false pretenses or with complicity from the prescribers that leads to abuse and illicit sales. The term doctor shopping has been used not only to refer to this phenomenon but has also had other meanings throughout the past decades. Thus, concept analysis is the focus of this article for clarification using the Walker and Avant method. Health implications and suggestions for minimizing doctor shopping are included.

Tactical resource allocation and elective patient admission planning in care processes

Tactical planning of resources in hospitals concerns elective patient admission planning and the intermediate term allocation of resource capacities. Its main objectives are to achieve equitable access for patients, to meet production targets/to serve the strategically agreed number of patients, and to use resources efficiently. This paper proposes a method to develop a tactical resource allocation and elective patient admission plan. These tactical plans allocate available resources to various care processes and determine the selection of patients to be served that are at a particular stage of their care process. Our method is developed in a Mixed Integer Linear Programming (MILP) framework and copes with multiple resources, multiple time periods and multiple patient groups with various uncertain treatment paths through the hospital, thereby integrating decision making for a chain of hospital resources. Computational results indicate that our method leads to a more equitable distribution of resources and provides control of patient access times, the number of patients served and the fraction of allocated resource capacity. Our approach is generic, as the base MILP and the solution approach allow for including various extensions to both the objective criteria and the constraints. Consequently, the proposed method is applicable in various settings of tactical hospital management.

Knowledge Management of Healthcare by Clinical-Pathways

Healthcare is a knowledge-intensive service provided by professionals, such as medical doctors, nurses, and pharmacists. Clinical-pathways are used by many healthcare organisations (HCOs) as a tool for performing the healthcare process, sharing and utilising knowledge from different professionals. In this paper, case studies were performed at two HCOs that use clinical-pathways actively in the healthcare process. Theoretical model construction, sharing, utilisation, and creation of the knowledge by different professionals, were tested by the case study of two HCOs which use clinical pathways actively. The theoretical model was a knowledge creation model which creates new knowledge continuously. In this theoretical model, clinical-pathways are suggested to be an effective tool for knowledge management in healthcare.

A simulation framework for mapping risks in clinical processes: the case of in-patient transfers

OBJECTIVE

To model how individual violations in routine clinical processes cumulatively contribute to the risk of adverse events in hospital using an agent-based simulation framework.

DESIGN

An agent-based simulation was designed to model the cascade of common violations that contribute to the risk of adverse events in routine clinical processes. Clinicians and the information systems that support them were represented as a group of interacting agents using data from direct observations. The model was calibrated using data from 101 patient transfers observed in a hospital and results were validated for one of two scenarios (a misidentification scenario and an infection control scenario). Repeated simulations using the calibrated model were undertaken to create a distribution of possible process outcomes. The likelihood of end-of-chain risk is the main outcome measure, reported for each of the two scenarios.

RESULTS

The simulations demonstrate end-of-chain risks of 8% and 24% for the misidentification and infection control scenarios, respectively. Over 95% of the simulations in both scenarios are unique, indicating that the in-patient transfer process diverges from prescribed work practices in a variety of ways.

CONCLUSIONS

The simulation allowed us to model the risk of adverse events in a clinical process, by generating the variety of possible work subject to violations, a novel prospective risk analysis method. The in-patient transfer process has a high proportion of unique trajectories, implying that risk mitigation may benefit from focusing on reducing complexity rather than augmenting the process with further rule-based protocols.

Managing health care decisions and improvement through simulation modeling

Simulation modeling is a way to test changes in a computerized environment to give ideas for improvements before implementation. This article reviews research literature on simulation modeling as support for health care decision making. The aim is to investigate the experience and potential value of such decision support and quality of articles retrieved. A literature search was conducted, and the selection criteria yielded 59 articles derived from diverse applications and methods. Most met the stated research-quality criteria. This review identified how simulation can facilitate decision making and that it may induce learning. Furthermore, simulation offers immediate feedback about proposed changes, allows analysis of scenarios, and promotes communication on building a shared system view and understanding of how a complex system works. However, only 14 of the 59 articles reported on implementation experiences, including how decision making was supported. On the basis of these articles, we proposed steps essential for the success of simulation projects, not just in the computer, but also in clinical reality. We also presented a novel concept combining simulation modeling with the established plan-do-study-act cycle for improvement. Future scientific inquiries concerning implementation, impact, and the value for health care management are needed to realize the full potential of simulation modeling.

Using recommendation to support adaptive clinical pathways

Clinical pathways are among the main tools used to manage the quality in health-care concerning the standardization of care processes. This paper deals with a recommendation service to support adaptive clinical pathways. The proposed approach can guide physicians in clinical pathways by providing recommendations on possible next steps based on the measurement of the target patient status and medical knowledge from completed clinical cases. The efficiency and usability of the proposed method is validated by experiments referring to a real data set extracted from Electronic Patient Records. The experimental results indicate that the recommendation service can provide its users with advice rationales that remain consistent even when patient status has changed. This makes adaptive clinical pathways possible.