Impact of primary health care reforms in Quebec Health Care System: a systematic literature review protocol.

INTRODUCTION: During the last decade the Quebec Public Health Care System (QPHCS) had an important transformation in primary care planning activity. The increase of the service demand together with a significant reduction of supply in primary care may be at risk of reducing access to health care services, with a negative impact on costs and health outcomes. The aims of this systematic literature review are to map and aggregate existing literature and evidence on the primary care provided in Quebec, showing the benefits and limitations associated with the health policies developed in the last two decades, and highlighting areas of improvement. METHODS AND ANALYSIS: PubMed, EMBASE, Web of Science and CINAHL will be searched for articles and government reports between January 2000 and January 2022 using a prespecified search strategy. This protocol adheres to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis for Protocols and has been registered with PROSPERO. A wide range of electronic databases and grey literature sources will be systematically searched using predefined keywords. The review will include any study design, with the exclusion of protocols, with a focus on the analysis of health care policies, outcomes, costs and management of the primary health care services, published in either English or French languages. Two authors will independently screen titles, abstracts, full-text articles and select studies meeting the inclusion criteria. A customised data extraction form will be used to extract data from the included studies. Results will be presented in tabular format developed iteratively by the research team. ETHICS AND DISSEMINATION: Research ethics approval is not required as exclusively secondary data will be used. Review findings will synthesise the characteristics and the impact of the reforms of QPHCS of the last two decades. Findings will therefore be disseminated in peer-reviewed journals, conference presentations and through discussions with stakeholders. PROSPERO REGISTRATION NUMBER: CRD42023421145.

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.

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.

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.

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.

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.