Disentangling the value equation: a step forward in value-based healthcare.

BACKGROUND: The value equation of value-based healthcare (VBHC) as a single figure remains ambiguous, closer to a theoretical framework than a useful tool for decision making. The challenge lies in the way patient-centred outcomes (PCOs) might be combined to produce a single value of the numerator. This paper aims to estimate the weights of PCOs to provide a single figure in the numerator, which ultimately will allow a VBHC figure to be reached. METHODS: A cohort of patients diagnosed with breast cancer (n = 690) with a 6-month follow-up recruited in 2019-20 across six European hospitals was used. Patient-reported outcomes (PROs), clinical-related outcomes (CROs), and clinical and socio-demographic variables were collected. The numerator was defined as a composite indicator of the PCOs (CI-PCO), and regression analysis was applied to estimate their weights and consequently arrive at a single figure. RESULTS: Pain showed as the highest weight followed by physical functioning, emotional functioning, and ability to work, and then by a symptom, either arm or breast. PCOs weights were robust to sensitivity analysis. The CI-PCO value was found to be more informative than the health-related quality of life (HRQoL) value. CONCLUSIONS: To the best of our knowledge, this is the first research to combine the PCOs proposed by ICHOM to provide a single figure in the numerator of the value equation. This figure shows a step forward in VBHC to reach a holistic benchmarking across healthcare centres and a value-based payment. This research might also be applied in other medical conditions as a methodological pathway.

European value-based healthcare benchmarking: moving from theory to practice.

BACKGROUND: Value-based healthcare (VBHC) is a conceptual framework to improve the value of healthcare by health, care-process and economic outcomes. Benchmarking should provide useful information to identify best practices and therefore a good instrument to improve quality across healthcare organizations. This paper aims to provide a proof-of-concept of the feasibility of an international VBHC benchmarking in breast cancer, with the ultimate aim of being used to share best practices with a data-driven approach among healthcare organizations from different health systems. METHODS: In the VOICE community-a European healthcare centre cluster intending to address VBHC from theory to practice-information on patient-reported, clinical-related, care-process-related and economic-related outcomes were collected. Patient archetypes were identified using clustering techniques and an indicator set following a modified Delphi was defined. Benchmarking was performed using regression models controlling for patient archetypes and socio-demographic characteristics. RESULTS: Six hundred and ninety patients from six healthcare centres were included. A set of 50 health, care-process and economic indicators was distilled for benchmarking. Statistically significant differences across sites have been found in most health outcomes, half of the care-process indicators, and all economic indicators, allowing for identifying the best and worst performers. CONCLUSIONS: To the best of our knowledge, this is the first international experience providing evidence to be used with VBHC benchmarking intention. Differences in indicators across healthcare centres should be used to identify best practices and improve healthcare quality following further research. Applied methods might help to move forward with VBHC benchmarking in other medical conditions.

Assessment of the Effectiveness, Socio-Economic Impact and Implementation of a Digital Solution for Patients with Advanced Chronic Diseases: The ADLIFE Study Protocol.

Due to population ageing and medical advances, people with advanced chronic diseases (ACD) live longer. Such patients are even more likely to face either temporary or permanent reduced functional reserve, which typically further increases their healthcare resource use and the burden of care on their caregiver(s). Accordingly, these patients and their caregiver(s) may benefit from integrated supportive care provided via digitally supported interventions. This approach may either maintain or improve their quality of life, increase their independence, and optimize the healthcare resource use from early stages. ADLIFE is an EU-funded project, aiming to improve the quality of life of older people with ACD by providing integrated personalized care via a digitally enabled toolbox. Indeed, the ADLIFE toolbox is a digital solution which provides patients, caregivers, and health professionals with digitally enabled, integrated, and personalized care, supporting clinical decisions, and encouraging independence and self-management. Here we present the protocol of the ADLIFE study, which is designed to provide robust scientific evidence on the assessment of the effectiveness, socio-economic, implementation, and technology acceptance aspects of the ADLIFE intervention compared to the current standard of care (SoC) when applied in real-life settings of seven different pilot sites across six countries. A quasi-experimental trial following a multicenter, non-randomized, non-concurrent, unblinded, and controlled design will be implemented. Patients in the intervention group will receive the ADLIFE intervention, while patients in the control group will receive SoC. The assessment of the ADLIFE intervention will be conducted using a mixed-methods approach.

Stratified cost-utility analysis of total hip arthroplasty in displaced femoral neck fracture.

OBJECTIVE: To conduct a stratified cost-utility analysis of total versus partial hip arthroplasty as a function of clinical subtype. METHOD: All cases of this type of intervention were analysed between 2010 and 2016 in the Basque Health Service, gathering data on clinical outcomes and resource use to calculate the cost and utility in quality-adjusted life years (QALYs) at individual level. The statistical analysis included applying the propensity score to balance the groups, and seemingly unrelated regression models to calculate the incremental cost-utility ratio and plot the cost-effectiveness plane. The interaction between age group and American Society of Anesthesiologists (ASA) risk class was assessed in the multivariate analysis. RESULTS: The study identified 5867 patients diagnosed with femoral neck fracture, of whom 1307 and 4560 were treated with total and partial hip arthroplasty, respectively. In the cost-utility analysis based on the seemingly unrelated regression, total hip arthroplasty was found to have a higher cost and higher utility (2465€ and 0.42 QALYs). Considering a willingness-to-pay threshold of €22,000 per QALY, total hip arthroplasty was cost-effective in the under-80-year-old subgroup. Among patients above this age, hemiarthroplasty was cost-effective in ASA class I-II patients and dominant in ASA class III-IV patients. CONCLUSIONS: Subgroup analysis supports current daily clinical practice in displaced femoral neck fractures, namely, using partial replacement in most patients and reserving total replacement for younger patients.

Estimation of the epidemiology of dementia and associated neuropsychiatric symptoms by applying machine learning to real-world data.

INTRODUCTION: Incidence rates of dementia-related neuropsychiatric symptoms (NPS) are not known and this hampers the assessment of their population burden. The objective of this study was to obtain an approximate estimate of the population incidence and prevalence of both dementia and NPS. METHODS: Given the dynamic nature of the population with dementia, a retrospective study was conducted within the database of the Basque Health Service (real-world data) at the beginning and end of 2019. Validated random forest models were used to identify separately depressive and psychotic clusters according to their presence in the electronic health records of all patients diagnosed with dementia. RESULTS: Among the 631,949 individuals over 60 years registered, 28,563 were diagnosed with dementia, of whom 15,828 (55.4%) showed psychotic symptoms and 19,461 (68.1%) depressive symptoms. The incidence of dementia in 2019 was 6.8/1000 person-years. Most incident cases of depressive (72.3%) and psychotic (51.9%) NPS occurred in cases of incident dementia. The risk of depressive-type NPS grows with years since dementia diagnosis, living in a nursing home, and female sex, but falls with older age. In the psychotic cluster model, the effects of male sex, and older age are inverted, both increasing the probability of this type of symptoms. CONCLUSIONS: The stigmatization factor conditions the social and attitudinal environment, delaying the diagnosis of dementia, preventing patients from receiving adequate care and exacerbating families' suffering. This study evidences the synergy between big data and real-world data for psychiatric epidemiological research.

Impact of an organised population screening programme for colorectal cancer: Measurement after first and second rounds.

OBJECTIVE: The first and second rounds of the Basque programme for organised colorectal cancer screening were implemented between 2009 and 2014. Our objective was to measure the changes in incidence, tumour, node, metastasis staging distribution and tumour, node, metastasis-adjusted survival of patients with colorectal cancer from 2003 to 2014. METHOD: Colorectal cancer cases with screening (patients <70 years old) and without screening (patients ≥70 years old) were compared during three four-year periods: 2003-2006, 2007-2010 and 2011-2014 (fully implemented phase). Cox regression, five-year relative survival and cancer probability of death were calculated for each four-year period, age group and tumour, node, metastasis stage. Adjusted incidence rates were analysed by joinpoint regression. RESULTS: In an analysis of 23,301 cases of colorectal cancer, the incidence in patients younger than 70 years in 2013 showed a 17% annual decrease. The survival hazard ratios for stages I, II and III for 2003-2006 and 2007-2010 were compared to those for 2011-2014. From the first to the third period, diagnosis in the early stages (I and II) rose from 45.1% to 50.9% in the younger patient group and remained stable in the older group (49.6% and 49.4%). Additionally, the five-year relative survival rate increased significantly from 0.67 to 0.82 in those patients younger than 70 years, whereas in patients 70 years or older the rate did not change significantly (0.61 and 0.65). CONCLUSION: The screening reduced incidence and improved survival by anticipating the diagnosis and by reducing mortality for each tumour, node, metastasis stage in the target population. The effect on survival could also be due to lead-time bias.

Quality of life in patients with nonvalvular atrial fibrillation treated with oral anticoagulants.

OBJECTIVES: Health-related quality of life (HRQL) is a key factor in making anticoagulant treatment decisions. The objective of this study was to assess the HRQL of patients with nonvalvular atrial fibrillation by treatment type: direct oral anticoagulants (DOACs) or vitamin K antagonists (VKAs). METHODS: We carried out a cross-sectional observational study with clinical practice data, gathering demographic and clinical variables. HRQL was measured using the 5-level 5-dimension EuroQol questionnaire (EQ-5D-5L). Differences between the study groups in HRQL as measured by the EQ-5D-5L were analyzed using two-part multivariate regression models. First, using logistic regression, the adjusted probability, p(x), of having perfect health was estimated in each subgroup. Secondly, generalized linear models were used to estimate mean disutility values, w(x), in a population that does not have perfect health, i.e. utility less than 1 or 1-w(x). RESULTS: We recruited 333 patients, of whom 126 were on DOACs and 207 on VKAs. A significant difference was observed in the EQ-5D-5L anxiety/depression dimension, with a higher percentage of patients classified in the 'no problems' category in the DOAC group. The same type of analysis did not identify significant differences in any of the other dimensions (mobility, self-care, usual activities or pain/discomfort). DISCUSSION: In the multivariate model, utility was significantly higher in the DOAC group than in the VKA group, although the difference was small (0.0121). This difference is attributable to patients on DOACs having less anxiety/depression. CONCLUSION: Patients treated with DOACs report a slightly better quality of life than those treated with VKAs.

Dynamic evaluation of the comparative effectiveness of an integrated program for heart failure care.

RATIONALE, AIMS AND OBJECTIVES: An integrated care program for heart failure (HF) was developed in the Basque Country in 2013. The objective of this research was to evaluate its effectiveness through the number of hospital admissions in three integrated healthcare organizations (IHOs), taking into account the longitudinal nature of the disease and the intensity of the implementation. METHODS: A retrospective observational study was carried out, based on data entered in administrative and clinical databases between 2014 and 2018 for a total population of 230 000. In addition to conventional statistical analyses, Andersen-Gill models for recurrent events were used, incorporating dynamic variables that allowed assessment of the intervention's intensity before each hospitalization. RESULTS: A total of 6768 patients were analysed. Age (hazard ratio [HR] = 1.016; 95% confidence interval [CI] 1.011-1.022), the Charlson index (HR = 1.067, 95% CI 1.047-1.087), and the number of previous hospitalizations (HR = 1.632, 95% CI 1.557-1.712) were risk factors for readmission. Differences between IHOs were also statistically significant. Greater intervention intensity was associated with a lower hospitalization rate (HR = 0.995, 95% CI 0.990-1.000). As indicated by the interaction between intervention intensity and IHO, differences between IHOs disappeared when intensity rose. No inequities in hospitalization were found as a function of deprivation index or sex. Nonetheless, inequity in the implementation of the program by sex was clear, women with HF receiving less intense intervention than men with the same level of comorbidity and age. CONCLUSIONS: The extent of program implementation measured by intervention intensity is a main driver of the effectiveness of an educational and monitoring program for HF. The evaluation of HF program effectiveness on readmissions must take into account the entire natural history of the disease. Implementation intensity explains differences between IHOs.

Estimation of the epidemiology of dementia and associated neuropsychiatric symptoms by applying machine learning to real-world data.

INTRODUCTION: Incidence rates of dementia-related neuropsychiatric symptoms (NPS) are not known and this hampers the assessment of their population burden. The objective of this study was to obtain an approximate estimate of the population incidence and prevalence of both dementia and NPS. METHODS: Given the dynamic nature of the population with dementia, a retrospective study was conducted within the database of the Basque Health Service (real-world data) at the beginning and end of 2019. Validated random forest models were used to identify separately depressive and psychotic clusters according to their presence in the electronic health records of all patients diagnosed with dementia. RESULTS: Among the 631,949 individuals over 60 years registered, 28,563 were diagnosed with dementia, of whom 15,828 (55.4%) showed psychotic symptoms and 19,461 (68.1%) depressive symptoms. The incidence of dementia in 2019 was 6.8/1000 person-years. Most incident cases of depressive (72.3%) and psychotic (51.9%) NPS occurred in cases of incident dementia. The risk of depressive-type NPS grows with years since dementia diagnosis, living in a nursing home, and female sex, but falls with older age. In the psychotic cluster model, the effects of male sex, and older age are inverted, both increasing the probability of this type of symptoms. CONCLUSIONS: The stigmatization factor conditions the social and attitudinal environment, delaying the diagnosis of dementia, preventing patients from receiving adequate care and exacerbating families' suffering. This study evidences the synergy between big data and real-world data for psychiatric epidemiological research.

Validation of Random Forest Machine Learning Models to Predict Dementia-Related Neuropsychiatric Symptoms in Real-World Data.

BACKGROUND: Neuropsychiatric symptoms (NPS) are the leading cause of the social burden of dementia but their role is underestimated. OBJECTIVE: The objective of the study was to validate predictive models to separately identify psychotic and depressive symptoms in patients diagnosed with dementia using clinical databases representing the whole population to inform decision-makers. METHODS: First, we searched the electronic health records of 4,003 patients with dementia to identify NPS. Second, machine learning (random forest) algorithms were applied to build separate predictive models for psychotic and depressive symptom clusters in the training set (N = 3,003). Third, calibration and discrimination were assessed in the test set (N = 1,000) to assess the performance of the models. RESULTS: Neuropsychiatric symptoms were noted in the electronic health record of 58% of patients. The area under the receiver operating curve reached 0.80 for the psychotic cluster model and 0.74 for the depressive cluster model. The Kappa index and accuracy also showed better discrimination in the psychotic model. Calibration plots indicated that both types of model had less predictive accuracy when the probability of neuropsychiatric symptoms was <25%. The most important variables in the psychotic cluster model were use of risperidone, level of sedation, use of quetiapine and haloperidol and the number of antipsychotics prescribed. In the depressive cluster model, the most important variables were number of antidepressants prescribed, escitalopram use, level of sedation, and age. CONCLUSION: Given their relatively good performance, the predictive models can be used to estimate prevalence of NPS in population databases.

Economic evaluation of supplementing the diet with Souvenaid in patients with prodromal Alzheimer's disease.

BACKGROUND: The LipiDiDiet trial showed that Souvenaid, a medical food, might delay progression to dementia in prodromal Alzheimer's disease (AD). The objective of this study was to assess the cost-utility of Souvenaid compared to placebo in patients with prodromal AD under the conditions applied in that trial. METHODS: A discrete event simulation model was developed based on the LipiDiDiet trial and a literature review to assess the cost-utility of Souvenaid from a societal perspective considering direct and indirect costs. For both intervention and control groups, patient trajectories in terms of functional decline on the Clinical Dementia Rating Sum of Boxes (CDR-SB) scale in LipiDiDiet were reproduced statistically with mixed models by assigning time until events to simulated patients. From the societal perspective, four scenarios were analysed by combining different options for treatment duration and diagnostic test cost. Univariate sensitivity analysis assessed parameter uncertainties. RESULTS: Validation results at year 2 of disease progression fit with CDR-SB progression in LipiDiDiet. The incremental cost-utility ratio (ICUR) in the baseline case was €22,743/quality-adjusted life year (QALY). All scenarios rendered an ICUR lower than €25,000/QALY (the societal threshold). Moreover, the treatment option was cost-saving and increased health benefits when diagnostic costs were not considered and treatment was only administered during the prodromal stage. CONCLUSIONS: Treating prodromal AD with Souvenaid is a cost-effective intervention in all scenarios analysed. The LipiDiDiet trial showed a modest improvement in disease course but as the social costs of AD are very high, the intervention was efficient. Assessing small benefits at specific stages of AD is relevant because it is reasonable to expect that no effective, safe and affordable disease-modifying therapies will become available in the short to medium term.