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Hospital procedures concentration: how to combine quality and patient choice.
Full text linkThe main focus of this PhD thesis is the use of managerial tools in the healthcare sector. In particular, the principal topic we focus on is the volume-outcome association, a relationship that has been empirically identifed in medical specialties. According to this relationship, there exists a positive association between the number of interventions (the so called volume of activity) performed by a facility and the
quality of clinical outcomes, measured in terms of patients’ health conditions.
The volume-outcome association has been identifed back in 1979, and it has been particularly documented in the last two decades for a variety of interventions and different outcome measures. All the studies mainly reveal that there is a positive effect of volume on outcomes for each medical procedure, although its extent varies depending on the clinical area itself. The observed trend can be explained by two main factors: (i) on a hospital level, the structure by which care is organised is likely to be poorer in low volume hospitals, which might lack consistent processes for postoperative care or for dealing with ostoperative complications; (ii) on a personnel level, outcomes may also be related to the familiarity of the staff with the treatment. Despite the number of studies focusing on it, the volume–outcome association still raises interest, due to the persistence of low volumes performed in healthcare facilities, in particular in Italian hospitals.
Our starting point is the National Outcome Evaluation Program (PNE), a project sponsored by the Italian government that each year, from 2012, reports hospitals clinical performances with the objective to assess healthcare service quality levels. While many researchers have focused on the existence of the volume-outcome association from a clinical perspective, this PhD project deepens the volume-outcome
association from a managerial perspective, by including it in a planning problem. The planning problem analysed consists in the decision of how to distribute volumes of activity among wards of hospitals perating in a same geographical area. In particular, among the different specialties, we consider surgery wards, since better results for higher volumes are especially plausible for this case. Our ultimate bjective is to exploit the information contained within the volume–outcome association and, as a consequence of the existing link among volume and outcomes, to reach an optimal planning for hospital wards. In this way, the reorganization of hospitals operating in a territory (planning decision) translates into the improvement of healthcare organization outcomes (clinical result).
We take as reference healthcare system the Italian National Healthcare System (Servizio Sanitario Nazionale, SSN), a public health system that provides universal coverage for comprehensive and essential health services. The formulation of our problem varies depending on which actor is considered. In the SSN, there is a central decision maker, the commissioner, in charge of guaranteeing the compliance with the principles of universality, equality and equity. It is represented by an institutional figure at the national level, i.e., the Ministry of Health. However, all the administrative levels (e.g., Regions, municipalities, etc.) have to ollaborate in order to guarantee health quality to all the citizens. Hence, we can think of a commissioner at each layer of the system, which is responsible for the population health.
Beyond the commissioner, other actors compose the Italian healthcare system. In particular, three other categories are involved in planning problems: providers, physicians and patients. Commissioners emand to providers to supply healthcare services. Providers (i.e., hospital administrators) answer through the supply of the requested services. Medical staff (surgeons, anesthetists, nurses, etc.) are the experts who deal with patients, who in turn receive the service. It should be noticed that there is no constraint enforcing patients to choose a specifc hospital where to be treated, and no patient is forced to receive healthcare services. Each actor has its own interests and perspectives, and therefore it is relevant to keep into consideration their different behaviors and interactions.
Since the allocation of operation volumes to healthcare structures is a strategic decision that deals with territorial healthcare confguration and people health needs, we initially take the perspective of the commissioner, who is the first actor involved in this decision process. All the other actors will face the consequences of such strategic choice: providers will have to adapt the capacity of their structures to the new planned demand; medical staff will have to arrange new shifts and work organisation; patients will face new openings/closures of hospitals and will have to choose where to be treated. Among them, we reckoned as particularly worthy of attention the patients’ perspective, since their behaviour can alter the whole commissioner plan.
The thesis is structured as follows. Chapter 2 summarizes the relevant literature. The chapter is organized in two sections dedicated to the two main felds of studies we refer to, namely location and allocation problems (from the health management literature) and choice models (from the health economics literature). Moreover, a section of the chapter reports the state of the art of the researches that have been
conducted on the volume–outcome association.
Chapter 3 is dedicated to the policy maker’s perspective. We take the point of view of the commissioners, i.e., that of planning the volume to be allocated to each hospital, and we propose an approach (based on mathematical programming) to determine the number of interventions to be strategically allocated to surgery wards, given several constraints related to hospital capacity, demand satisfaction and pidemiological concerns. Concentration vs. scattering of interventions among healthcare structures are explored in terms of quality and equity offered to the whole population. The proposed approach is tested on four case studies taking into account real life factors (such as reallocation of interventions, geographical distribution of hospitals, volume threshold constraints, and dissimilarities among hospital performances), and results are compared with real data from the PNE.
Chapter 4 focuses on patients’ perspective. Specifcally, we analysed patients’ choice, in terms of hospital where they have decided to be treated, together with the list of hospitals that were available to them. By using the econometric methodology of the conditional logit, we modeled the trade-off faced by patients between hospitals’ characteristics, i.e., distance and quality. Eventually, we applied the choice model to Hospital Discharge Data for colon cancer patients in Piedmont from 2004 to 2014, showing patients’ revealed preferences. Results shed some light on how patients can react to facility specialization or closure, depending on demographic, social and clinical factors.
Chapter 5 gathers the two perspectives and merge them. The objective is to support planning decisions that (i) are effective in terms of better health outcomes and (ii) guarantee patients’ choices to respect the volumes that have been strategically planned. To this aim, we explored two distinct approaches. The frst approach enriches the one proposed in Chapter 3 with the commissioner point of view, by adding constraints involving patients, e.g., the maximum distance they are willing to travel. The second approach, instead, aims to fully integrate patients’ and policy maker’s perspectives, by inserting predictions on patients’ behaviour within the decisional process of the policy maker. Eventually, results from all the approaches are compared, in terms of organizational quality and population health
Improving surgical outcomes through optimal volumes allocation
No full textIn this paper, we propose an innovative managerial use of the volume-outcome association, a relation that associates higher volume of activity to better results. We analyze how this relation can be used to help decision makers in allocating surgery interventions among health care structures, a relevant long term planning problem. We analytically study different objective functions in order to drive the allocation process towards better health conditions for patients. We provide a decision support tool for health policy makers, which helps achieving better population health, in terms of quality and fairness. Our approach has been tested on three case studies taking into account real life factors such as geographical distribution of hospitals, specialization thresholds and hospital performance. Results have been compared to the real data from the Italian National Outcome Evaluation Program
How to direct patients to high-volume hospitals: exploring the influencing drivers
Full text linkBackground: During the last decade, planning concentration policies have been applied in healthcare systems. Among them, attention has been given to guiding patients towards high-volume hospitals that perform better, acccording to the volume-outcome association. This paper analyses which factors drive patients to choose big or small hospitals (with respect to the international standards of volumes of activity). Methods: We examined colon cancer surgeries performed in Piedmont (Italy) between 2004 and 2018. We categorised the patient choice of the hospital as big/small, and we used this outcome as main dependent variable of descriptive statistics, tests and logistic regression models. As independent variables, we included (i) patient characteristics, (ii) characteristics of the closest big hospital (which should be perceived as the most immediate to be chosen), and (iii) territorial characteristics (i.e., characteristics of the set of hospitals among which the patient can choose). We also considered interactions among variables to examine which factors influence all or a subset of patients. Results: Our results confirm that patient personal characteristics (such as age) and hospital characteristics (such as distance) play a primary role in the patient decision process. The findings seem to support the importance of closing small hospitals when they are close to big hospitals, although differences emerge between rural and urban areas. Other interesting insights are provided by examining the interactions between factors, e.g., patients affected by comorbidities are more responsive to hospital quality even though they are distant. Conclusions: Reorganising healthcare services to concentrate them in high-volume hospitals emerged as a crucial issue more than forty years ago. Evidence suggests that concentration strategies guarantee better clinical performance. However, in healthcare systems in which patients are free to choose where to be treated, understanding patients' behaviour and what drives them towards the most effective choice is of paramount importance. Our study builds on previous research that has already analysed factors influencing patients' choices, and takes a step further to enlighten which factors drive patients to choose between a small or a big hospital (in terms of volume). The results could be used by decision makers to design the best concentration strategy
Agent-based modelling for diabetic patients behaviour: examining the impact of word of mouth
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Proximal hip fractures in 71,920 elderly patients: incidence, epidemiology, mortality and costs from a retrospective observational study
No full textBackgroundThe risk of proximal femoral fractures increases with aging, causing significant morbidity, disability, mortality and socioeconomic pressure. The aims of the present work are (1) to investigate the epidemiology and incidence of these fractures among the elderly in the Region of Lombardy; (2) to identify the factors influencing survival; (3) to identify the factors influencing hospitalization and post-operative costs.MethodsThe Region of Lombardy provided anonymized datasets on hospitalized patients with a femoral neck fracture between 2011 and 2016, and anonymized datasets on extra-hospital treatments to track the patient history between 2008 and 2019. Statistical evaluations included descriptive statistics, survival analysis, Cox regression and multiple linear models.Results71,920 older adults suffered a femoral fracture in Lombardy between 2011 and 2016. 76.3% of patients were females and the median age was 84. The raw incidence of fractures was stable from year 2011 to year 2016, while the age-adjusted incidence diminished. Pertrochanteric fractures were more spread than transcervical fractures. In patients treated with surgery, receiving treatment within 48 h reduced the hazard of death within the next 24 months. Combined surgical procedures led to increased hazard in comparison with arthroplasty alone, while no differences were observed between different arthroplasties and reduction or fixation. In patients treated conservatively, age and male gender were associated with higher hazard of death. All patients considered, the type of surgery was the main factor determining primary hospitalization costs. A higher number of surgeries performed by the index hospital in the previous year was associated with financial savings. The early intervention significantly correlated with minor costs.ConclusionsThe number of proximal femoral fractures is increasing even if the age-adjusted incidence is decreasing. This is possibly due to prevention policies focused on the oldest cohort of the population. Two policies proved to be significantly beneficial in clinical and financial terms: the centralization of patients in high-volume hospitals and a time limit of 48 h from fracture to surgery.Trial registrationNon applicable
Artificial-Intelligence Cloud-Based Platform to Support Shared Decision-Making in the Locoregional Treatment of Breast Cancer: Protocol for a Multidimensional Evaluation Embedded in the CINDERELLA Clinical Trial
Full text linkBackground: Shared decision-making (SDM) plays a crucial role in breast cancer care by empowering patients and reducing decision regret. Patient decision aids (PtDAs) are valuable tools for facilitating SDM, now available in digital and artificial intelligence (AI)-powered formats to offer increasingly personalized contents. The ongoing CINDERELLA clinical trial (ClinicalTrials.gov: NCT05196269) evaluates an innovative AI cloud-based approach using a web platform and a mobile application (CINDERELLA APProach) versus the conventional approach to support SDM in breast cancer patients undergoing locoregional treatment. This protocol outlines a trial-based multidimensional evaluation, encompassing economic, financial, implementability, and environmental considerations associated with the CINDERELLA APProach. Methods: A within-trial cost-consequence and cost-utility analysis from a societal perspective will be performed using patient-level data on outcomes and resource use. The latter will be valued in monetary terms using country-specific unit costs or patient valuations. A budget impact analysis will be performed over 1 and 5 years from the budget holder perspectives. The CINDERELLA APProach implementability will be assessed through an evaluation of its usability, acceptability, organizational impact, and overall feasibility. The environmental impact will be quantitatively assessed across several dimensions, such as quantity, appropriateness, and emissions, supplemented by qualitative insights. Overall, data for the evaluation will be gathered from patient questionnaires, interviews with patients and managers, focus groups with healthcare professionals, and app electronic data. Discussion: A thorough understanding of the broad consequences of the CINDERELLA APProach may foster its successful translation into real-world settings, hopefully benefiting breast cancer patients and clinical practice
A managerial use of the volume-outcome association for hospital planning
No full textNo abstract availabl
Determinants of the economic burden of ART on the Italian NHS: insights from the Lombardy region
Full text linkAbstract With the rising spread of Assisted Reproductive Technology (ART), it becomes imperative to understand the determinants of resource utilization in ART versus spontaneous pregnancies to enhance policies directed to pregnancy care. The focus of our study is to examine the costs associated with ART from the perspective of the Italian NHS and to investigate in depth the contributing social and clinical factors. Using the healthcare informative system of Lombardy, a Region of Northern Italy, we gathered individual-level information for a cohort of women who experienced either spontaneous pregnancies or pregnancies following ART from 2007 until 2020. The information covered multiple healthcare services, and we used a propensity score matching technique to match couples of ART/No ART women based on a comprehensive set of confounders. We then applied statistical tests and regression models to identify the impact of ART on the reported cost differences. Our cohort was composed of 44652 women and results revealed significantly higher costs for ART pregnancies, especially in terms of hospital admissions (additional 1611€, 95% CI 1558-1666) and drug prescriptions (additional 216 €, CI 95% 204-228) occurring before delivery. In-depth analysis showed for ART pregnancies, i) a higher likelihood of incurring expenses related to complications and ii) higher costs associated with two established clinical practices that lack scientific evidence supporting their efficacy. Our study sheds light on the complex interplay of clinical and social factors influencing the ART burden, emphasizing the importance of tailored support and evidence-based practices in optimizing outcomes and resource allocation
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