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.

Optimization and planning of operating theatre activities: an original definition of pathways and process modeling.

BACKGROUND: The Operating Room (OR) is a key resource of all major hospitals, but it also accounts for up 40% of resource costs. Improving cost effectiveness, while maintaining a quality of care, is a universal objective. These goals imply an optimization of planning and a scheduling of the activities involved. This is highly challenging due to the inherent variable and unpredictable nature of surgery. METHODS: A Business Process Modeling Notation (BPMN 2.0) was used for the representation of the "OR Process" (being defined as the sequence of all of the elementary steps between "patient ready for surgery" to "patient operated upon") as a general pathway ("path"). The path was then both further standardized as much as possible and, at the same time, keeping all of the key-elements that would allow one to address or define the other steps of planning, and the inherent and wide variability in terms of patient specificity. The path was used to schedule OR activity, room-by-room, and day-by-day, feeding the process from a "waiting list database" and using a mathematical optimization model with the objective of ending up in an optimized planning. RESULTS: The OR process was defined with special attention paid to flows, timing and resource involvement. Standardization involved a dynamics operation and defined an expected operating time for each operation. The optimization model has been implemented and tested on real clinical data. The comparison of the results reported with the real data, shows that by using the optimization model, allows for the scheduling of about 30% more patients than in actual practice, as well as to better exploit the OR efficiency, increasing the average operating room utilization rate up to 20%. CONCLUSIONS: The optimization of OR activity planning is essential in order to manage the hospital's waiting list. Optimal planning is facilitated by defining the operation as a standard pathway where all variables are taken into account. By allowing a precise scheduling, it feeds the process of planning and, further up-stream, the management of a waiting list in an interactive and bi-directional dynamic process.

Assessment of physician performance for diabetes: a bias-corrected data envelopment analysis model.

BACKGROUND: In most national health systems, especially when universal coverage is provided, family physicians act as gatekeepers, because most healthcare services are only delivered if there is a formal prescription provided by a primary care physician. Although the consumption of healthcare resources is initiated by prescriptions coming from family physicians, studies that evaluate their performance, especially those using a consolidated methodology (e.g.quality and efficiency) are limited in the literature. The specific aim of this paper is to propose a method for assessing primary care performance. METHODS: The novelty of the proposed model is twofold. First, physician performance is assessed following a clinical pathway that focuses on homogeneous groups of patients, in this case, diabetes patients. Second, we argue that performance should not be limited to efficiency, but should encompass clinical effectiveness. Performance assessment is not based on the physician practice as a whole, but on a single disease, in this paper, diabetes. Data were collected from a sample of family physician practices in Italy, and Data Envelopment Analysis (DEA) is used to evaluate their efficiency performance. RESULTS: We found that 35 of 96 practices were efficient based on the standard DEA model. The number of efficient practices decreased based on three restricted models that explored various behavioural preferences of physicians in relation to patient visits, medication administration and referrals to hospitals. CONCLUSION: The efficiency assessment is completed by a post-hoc evaluation of effectiveness, which in this study is defined as patient care adherence to the prescribed guideline. This study identified best practices both in terms of efficiency and effectiveness. The methods used in this paper are generalisable and could be applied to many other chronic conditions, which may constitute the prevalent activities within the primary care.

The role of regional health systems on the waiting time inequalities in health care services: Evidences from Italy.

Inequalities in effective access to healthcare are present among countries and within the same country. Despite in Italy exist the principle of equity in access to health system, there are evidence of different access rates in the form of unequal waiting time within the country. Waiting times are an instruments to ration healthcare services dealing with resource scarsity. Theoretically, it is a fair tool because waiting times should depend only on health needs and not on the ability to pay. However, a growing literature has pointed out that belonging to a particular socioeconomic status leads to waiting times inequalities for healthcare services. Many countries have socioeconomic disparities among regions, and healthcare organizations need to take into account these differences. The increasing power of Regional Health Authorities in decentralized health systems, as in the case of Italy, has generated different organizational ways to provide health care, possibly leading to different access rates in the form of unequal waiting time within the country. This paper aims to understand if the administrative area (Regional Health Authorities) in charge of health services affects waiting times lowering or strengthening health care access inequalities. Using a series of logistic regression models, this work suggests the presence of two vectors: socioeconomic inequalities and regional inequalities. Health organizations need to implement different kinds of answers for each vectors of inequalities.

A model to prioritize access to elective surgery on the basis of clinical urgency and waiting time.

BACKGROUND: Prioritization of waiting lists for elective surgery represents a major issue in public systems in view of the fact that patients often suffer from consequences of long waiting times. In addition, administrative and standardized data on waiting lists are generally lacking in Italy, where no detailed national reports are available. This is true although since 2002 the National Government has defined implicit Urgency-Related Groups (URGs) associated with Maximum Time Before Treatment (MTBT), similar to the Australian classification. The aim of this paper is to propose a model to manage waiting lists and prioritize admissions to elective surgery. METHODS: In 2001, the Italian Ministry of Health funded the Surgical Waiting List Info System (SWALIS) project, with the aim of experimenting solutions for managing elective surgery waiting lists. The project was split into two phases. In the first project phase, ten surgical units in the largest hospital of the Liguria Region were involved in the design of a pre-admission process model. The model was embedded in a Web based software, adopting Italian URGs with minor modifications. The SWALIS pre-admission process was based on the following steps: 1) urgency assessment into URGs; 2) correspondent assignment of a pre-set MTBT; 3) real time prioritization of every referral on the list, according to urgency and waiting time. In the second project phase a prospective descriptive study was performed, when a single general surgery unit was selected as the deployment and test bed, managing all registrations from March 2004 to March 2007 (1809 ordinary and 597 day cases). From August 2005, once the SWALIS model had been modified, waiting lists were monitored and analyzed, measuring the impact of the model by a set of performance indexes (average waiting time, length of the waiting list) and Appropriate Performance Index (API). RESULTS: The SWALIS pre-admission model was used for all registrations in the test period, fully covering the case mix of the patients referred to surgery. The software produced real time data and advanced parameters, providing patients and users useful tools to manage waiting lists and to schedule hospital admissions with ease and efficiency. The model protected patients from horizontal and vertical inequities, while positive changes in API were observed in the latest period, meaning that more patients were treated within their MTBT. CONCLUSION: The SWALIS model achieves the purpose of providing useful data to monitor waiting lists appropriately. It allows homogeneous and standardized prioritization, enhancing transparency, efficiency and equity. Due to its applicability, it might represent a pragmatic approach towards surgical waiting lists, useful in both clinical practice and strategic resource management.

Material versus social deprivation and health: a case study of an urban area.

Socioeconomic factors are one of the main determinants of health inequalities. However, which component of socioeconomic status affects health most and how that relationship should be measured remains an open question. The aim of this study was to compare material and social deprivation indexes in order to determine which better explains health inequalities within an urban area. Following a review of the literature on small area deprivation indexes, a case study of the Italian city Genoa is presented. The city of Genoa is split into 71 small areas [urbanistic units (UU)], each of which has about 9,500 inhabitants. For each small area, socioeconomic indicators were extracted from the 2001 Census, whereas health indicators were computed from the death registry for 2001-2003. Factorial analyses was used to choose the deprivation variables, which were utilised to create two distinct deprivation indexes referring to material and social deprivation, respectively. Both deprivation indexes are positively correlated with health status proxied by standardised mortality ratios (SMRs) under 65. The material index, however, correlates more highly with SMRs than the social index, and thus the material index is the more suitable measure to explain variations in premature mortality within an urban area. Moreover, the two indexes must be kept distinct.

Socioeconomic Status and Waiting Times for Health Services: Current Evidences and Next Area of Research.

Waiting times are an issue in many countries, excessive waiting for treatments may deteriorate patient's health status and reduce treatment effectiveness potentially, becoming a barrier in the access to health care services. Waiting time to be equitable should be related only to the health need, people with the same health need have to wait the same time, without any difference due to socioeconomic status. In the commentary, the results of the extensive literature review and policy implications are discussed.

Socioeconomic status and waiting times for health services: An international literature review and evidence from the Italian National Health System.

In the absence of priority criteria, waiting times are an implicit rationing instrument where the absence or limited use of prices creates an excess of demand. Even in the presence of priority criteria, waiting times may be unfair because they reduce health care demand of patients in lower socio-economic conditions due to high opportunity costs of time or a decay in their health level. Significant evidence has shown a relationship between socioeconomic status and the length of waiting time. The first phase of the study involved an extensive review of the existent literature for the period of 2002-2016 in the main databases (Scopus, PubMed and Science Direct). Twenty-eight met the eligibility criteria. The 27 papers were described and classified. The e mpirical objective of this study was to determine whether socioeconomic characteristics affect waiting time for different health services in the Italian national health system. The services studied were specialist visits, diagnostics tests and elective surgeries. A classification tree and logistic regression models were implemented. Data from the 2013 Italian Health National Survey were used. The analysis found heterogeneous results for different types of service. Individuals with lower education and economic resources have a higher risk of experiencing excessive waiting times for diagnostic and specialist visits. For elective surgery, socioeconomic inequalities are present but appear to be lower.

Vaccinating Italian infants with a new multicomponent vaccine (Bexsero®) against meningococcal B disease: A cost-effectiveness analysis.

The European Medicines Agency has approved a multicomponent serogroup B meningococcal vaccine (Bexsero®) for use in individuals of 2 months of age and older. A cost-effectiveness analysis (CEA) from the societal and Italian National Health Service perspectives was performed in order to evaluate the impact of vaccinating Italian infants less than 1 y of age with Bexsero®, as opposed to non-vaccination. The analysis was carried out by means of Excel Version 2011 and the TreeAge Pro® software Version 2012. Two basal scenarios that differed in terms of disease incidence (official and estimated data to correct for underreporting) were considered. In the basal scenarios, we considered a primary vaccination cycle with 4 doses (at 2, 4, 6 and 12 months of age) and 1 booster dose at the age of 11 y, the societal perspective and no cost for death. Sensitivity analyses were carried out in which crucial variables were changed over probable ranges. In Italy, on the basis of official data on disease incidence, vaccination with Bexsero® could prevent 82.97 cases and 5.61 deaths in each birth cohort, while these figures proved to be three times higher on considering the estimated incidence. The results of the CEA showed that the Incremental Cost Effectiveness Ratio (ICER) per QALY was €109,762 in the basal scenario if official data on disease incidence are considered and €26,599 if estimated data are considered. The tornado diagram indicated that the most influential factor on ICER was the incidence of disease. The probability of sequelae, the cost of the vaccine and vaccine effectiveness also had an impact. Our results suggest that vaccinating infants in Italy with Bexsero® has the ability to significantly reduce meningococcal disease and, if the probable underestimation of disease incidence is considered, routine vaccination is advisable.

Telematic integration of health data: a practicable contribution.

The patients' clinical and healthcare data should virtually be available everywhere, both to provide a more efficient and effective medical approach to their pathologies, as well as to make public healthcare decision makers able to verify the efficacy and efficiency of the adopted healthcare processes. Unfortunately, customised solutions adopted by many local Health Information Systems in Italy make it difficult to share the stored data outside their own environment. In the last years, worldwide initiatives have aimed to overcome such sharing limitation. An important issue during the passage towards standardised, integrated information systems is the possible loss of previously collected data. The herein presented project realises a suitable architecture able to guarantee reliable, automatic, user-transparent storing and retrieval of information from both modern and legacy systems. The technical and management solutions provided by the project avoid data loss and overlapping, and allow data integration and organisation suitable for data-mining and data-warehousing analysis.

Tactical and operational decisions for operating room planning: efficiency and welfare implications.

In this paper, we evaluate the impact on welfare implications of a 0-1 linear programming model to solve the Operating Room (OR) planning problem, taking a patient perspective. In particular, given a General Surgery Department made up of different surgical sub-specialties sharing a given number of OR block times, the model determines, during a given planning period, the allocation of those blocks to surgical sub-specialties, i.e. the so called Master Surgical Schedule Problem (MSSP), together with the subsets of elective patients to be operated on in each block time, i.e. the so called Surgical Case Assignment Problem (SCAP). The innovation of the model is two-fold. The first is that OR allocation is "optimal" if the available OR blocks are scheduled simultaneously to the proper subspecialty, at the proper time to the proper patient. The second is defining what "proper" means and include that in the objective function. In our approach what is important is not number of patients who can be treated in a given period but how much welfare loss, due to clinical deterioration or other negative consequences related to excessive waiting, can be prevented. In other words we assume a societal perspective in that we focus on "outcome" (health improving or preventing from worsening) rather than on "output" (delivered procedures). The model can be used both to develop weekly OR planning with given resources (operational decision), and to perform "what if" scenario analysis regarding how to increase the amount of OR time available for the entire department (tactical decision). The model performance is verified by applying it to a real scenario, the elective admissions of the General Surgery Department of the San Martino University Hospital in Genova (Italy). Despite the complexity of this NP-hard combinatorial optimization problem, computational results indicate that the model can solve all test problems within 600 s and an average optimality tolerance of less than 0.01%.

A three-phase approach for operating theatre schedules.

In this paper we develop a three-phase, hierarchical approach for the weekly scheduling of operating rooms. This approach has been implemented in one of the surgical departments of a public hospital located in Genova (Genoa), Italy. Our aim is to suggest an integrated way of facing surgical activity planning in order to improve overall operating theatre efficiency in terms of overtime and throughput as well as waiting list reduction, while improving department organization. In the first phase we solve a bin packing-like problem in order to select the number of sessions to be weekly scheduled for each ward; the proposed and original selection criterion is based upon an updated priority score taking into proper account both the waiting list of each ward and the reduction of residual ward demand. Then we use a blocked booking method for determining optimal time tables, denoted Master Surgical Schedule (MSS), by defining the assignment between wards and surgery rooms. Lastly, once the MSS has been determined we use the simulation software environment Witness 2004 in order to analyze different sequencings of surgical activities that arise when priority is given on the basis of a) the longest waiting time (LWT), b) the longest processing time (LPT) and c) the shortest processing time (SPT). The resulting simulation models also allow us to outline possible organizational improvements in surgical activity. The results of an extensive computational experimentation pertaining to the studied surgical department are here given and analyzed.