The value of admission avoidance: cost-consequence analysis of one-year activity in a consolidated service.

BACKGROUND: Many advantages of hospital at home (HaH), as a modality of acute care, have been highlighted, but controversies exist regarding the cost-benefit trade-offs. The objective is to assess health outcomes and analytical costs of hospital avoidance (HaH-HA) in a consolidated service with over ten years of delivery of HaH in Barcelona (Spain). METHODS: A retrospective cost-consequence analysis of all first episodes of HaH-HA, directly admitted from the emergency room (ER) in 2017-2018, was carried out with a health system perspective. HaH-HA was compared with a propensity-score-matched group of contemporary patients admitted to conventional hospitalization (Controls). Mortality, re-admissions, ER visits, and direct healthcare costs were evaluated. RESULTS: HaH-HA and Controls (n = 441 each) were comparable in terms of age (73 [SD16] vs. 74 [SD16]), gender (male, 57% vs. 59%), multimorbidity, healthcare expenditure during the previous year, case mix index of the acute episode, and main diagnosis at discharge. HaH-HA presented lower mortality during the episode (0 vs. 19 (4.3%); p < 0.001). At 30 days post-discharge, HaH-HA and Controls showed similar re-admission rates; however, ER visits were lower in HaH-HA than in Controls (28 (6.3%) vs. 34 (8.1%); p = 0.044). Average costs per patient during the episode were lower in the HaH-HA group (€ 1,078) than in Controls (€ 2,171). Likewise, healthcare costs within the 30 days post-discharge were also lower in HaH-Ha than in Controls (p < 0.001). CONCLUSIONS: The study showed higher performance and cost reductions of HaH-HA in a real-world setting. The identification of sources of savings facilitates scaling of hospital avoidance. REGISTRATION: ClinicalTrials.gov (26/04/2017; NCT03130283).

Applicability of the adjusted morbidity groups algorithm for healthcare programming: results of a pilot study in Italy.

BACKGROUND: Population-based Health Risk Assessment (HRA) tools are strategic for the implementation of integrated care. Various HRA algorithms have been developed in the last decades worldwide. Their full adoption being limited by technical, functional, and economical factors. This study aims to apply the Adjusted Morbidity Groups (AMG) algorithm in the context of an Italian Region, and evaluate its performance to support decision-making processes in healthcare programming. METHODS: The pilot study used five Healthcare Administrative Databases (HADs) covering the period 2015-2021. An iterative semi-automated procedure was developed to extract, filter, check and merge the data. A technical manual was developed to describe the process, designed to be standardized, reproducible and transferable. AMG algorithm was applied and descriptive analysis performed. A dashboard structure was developed to exploit the results of the tool. RESULTS: AMG produced information on the health status of Marche citizens, highlighting the presence of chronic conditions from age 45 years. Persons with high and very high level of complexity showed elevated mortality rates and an increased use of healthcare resources. A visualization dashboard was intended to provide to relevant stakeholders accessible, updated and ready-to-use aggregated information on the health status of citizens and additional insight on the use of the healthcare services and resources by specific groups of citizens. CONCLUSION: The flexibility of the AMG, together with its ability to support policymakers and clinical sector, could favour its implementation in different scenarios across Europe. A clear strategy for the adoption of HRA tools and related key elements and lessons learnt for a successful transferability at the EU level were defined. HRA strategies should be considered a pillar of healthcare policies and programming to achieve person-centred care and promote the sustainability of the EU healthcare systems.

Five years of Hospital at Home adoption in Catalonia: impact, challenges, and proposals for quality assurance.

BACKGROUND: Hospital at home (HaH) was increasingly implemented in Catalonia (7.7 M citizens, Spain) achieving regional adoption within the 2011-2015 Health Plan. This study aimed to assess population-wide HaH outcomes over five years (2015-2019) in a consolidated regional program and provide context-independent recommendations for continuous quality improvement of the service. METHODS: A mixed-methods approach was adopted, combining population-based retrospective analyses of registry information with qualitative research. HaH (admission avoidance modality) was compared with a conventional hospitalization group using propensity score matching techniques. We evaluated the 12-month period before the admission, the hospitalization, and use of healthcare resources at 30 days after discharge. A panel of experts discussed the results and provided recommendations for monitoring HaH services. RESULTS: The adoption of HaH steadily increased from 5,185 episodes/year in 2015 to 8,086 episodes/year in 2019 (total episodes 31,901; mean age 73 (SD 17) years; 79% high-risk patients. Mortality rates were similar between HaH and conventional hospitalization within the episode [76 (0.31%) vs. 112 (0.45%)] and at 30-days after discharge [973(3.94%) vs. 1112(3.24%)]. Likewise, the rates of hospital re-admissions at 30 days after discharge were also similar between groups: 2,00 (8.08%) vs. 1,63 (6.58%)] or ER visits [4,11 (16.62%) vs. 3,97 (16.03%). The 27 hospitals assessed showed high variability in patients' age, multimorbidity, severity of episodes, recurrences, and length of stay of HaH episodes. Recommendations aiming at enhancing service delivery were produced. CONCLUSIONS: Besides confirming safety and value generation of HaH for selected patients, we found that this service is delivered in a case-mix of different scenarios, encouraging hospital-profiled monitoring of the service.

Multicentric Assessment of a Multimorbidity-Adjusted Disability Score to Stratify Depression-Related Risks Using Temporal Disease Maps: Instrument Validation Study.

BACKGROUND: Comprehensive management of multimorbidity can significantly benefit from advanced health risk assessment tools that facilitate value-based interventions, allowing for the assessment and prediction of disease progression. Our study proposes a novel methodology, the Multimorbidity-Adjusted Disability Score (MADS), which integrates disease trajectory methodologies with advanced techniques for assessing interdependencies among concurrent diseases. This approach is designed to better assess the clinical burden of clusters of interrelated diseases and enhance our ability to anticipate disease progression, thereby potentially informing targeted preventive care interventions. OBJECTIVE: This study aims to evaluate the effectiveness of the MADS in stratifying patients into clinically relevant risk groups based on their multimorbidity profiles, which accurately reflect their clinical complexity and the probabilities of developing new associated disease conditions. METHODS: In a retrospective multicentric cohort study, we developed the MADS by analyzing disease trajectories and applying Bayesian statistics to determine disease-disease probabilities combined with well-established disability weights. We used major depressive disorder (MDD) as a primary case study for this evaluation. We stratified patients into different risk levels corresponding to different percentiles of MADS distribution. We statistically assessed the association of MADS risk strata with mortality, health care resource use, and disease progression across 1 million individuals from Spain, the United Kingdom, and Finland. RESULTS: The results revealed significantly different distributions of the assessed outcomes across the MADS risk tiers, including mortality rates; primary care visits; specialized care outpatient consultations; visits in mental health specialized centers; emergency room visits; hospitalizations; pharmacological and nonpharmacological expenditures; and dispensation of antipsychotics, anxiolytics, sedatives, and antidepressants (P<.001 in all cases). Moreover, the results of the pairwise comparisons between adjacent risk tiers illustrate a substantial and gradual pattern of increased mortality rate, heightened health care use, increased health care expenditures, and a raised pharmacological burden as individuals progress from lower MADS risk tiers to higher-risk tiers. The analysis also revealed an augmented risk of multimorbidity progression within the high-risk groups, aligned with a higher incidence of new onsets of MDD-related diseases. CONCLUSIONS: The MADS seems to be a promising approach for predicting health risks associated with multimorbidity. It might complement current risk assessment state-of-the-art tools by providing valuable insights for tailored epidemiological impact analyses of clusters of interrelated diseases and by accurately assessing multimorbidity progression risks. This study paves the way for innovative digital developments to support advanced health risk assessment strategies. Further validation is required to generalize its use beyond the initial case study of MDD.

Actionable Factors Fostering Health Value Generation and Scalability of Prehabilitation: A Prospective Cohort Study.

IMPORTANCE: Prehabilitation has potential for improving surgical outcomes as shown in previous randomized controlled trials. However, a marked efficacy-effectiveness gap is limiting its scalability. Comprehensive analyses of deployment of the intervention in real-life scenarios are required. OBJECTIVE: To assess health outcomes and cost of prehabilitation. DESIGN: Prospective cohort study with a control group built using propensity score-matching techniques. SETTING: Prehabilitation Unit in a tertiary-care university hospital. PARTICIPANTS: Candidates for major digestive, cardiac, thoracic, gynecologic, or urologic surgeries. INTERVENTION: Prehabilitation program, including supervised exercise training, promotion of physical activity, nutritional optimization, and psychological support. MAIN OUTCOMES AND MEASURES: The comprehensive complication index, hospital and intensive care unit length of stay, and hospital costs per patient until 30 days after surgery. Patients were classified by the degree of program completion and level of surgical aggression for sensitivity analysis. RESULTS: The analysis of the entire study group did not show differences in study outcomes between prehabilitation and control groups (n=328 each). The per-protocol analysis, including only patients completing the program (n=112, 34%), showed a reduction in mean hospital stay [9.9 (7.2) vs 12.8 (12.4) days; P =0.035]. Completers undergoing highly aggressive surgeries (n=60) additionally showed reduction in mean intensive care unit stay [2.3 (2.7) vs 3.8 (4.2) days; P =0.021] and generated mean cost savings per patient of €3092 (32% cost reduction) ( P =0.007). Five priority areas for action to enhance service efficiencies were identified. CONCLUSIONS AND RELEVANCE: The study indicates a low rate of completion of the intervention and identifies priority areas for re-design of service delivery to enhance the effectiveness of prehabilitation.

Prevention of Unplanned Hospital Admissions in Multimorbid Patients Using Computational Modeling: Observational Retrospective Cohort Study.

BACKGROUND: Enhanced management of multimorbidity constitutes a major clinical challenge. Multimorbidity shows well-established causal relationships with the high use of health care resources and, specifically, with unplanned hospital admissions. Enhanced patient stratification is vital for achieving effectiveness through personalized postdischarge service selection. OBJECTIVE: The study has a 2-fold aim: (1) generation and assessment of predictive models of mortality and readmission at 90 days after discharge; and (2) characterization of patients' profiles for personalized service selection purposes. METHODS: Gradient boosting techniques were used to generate predictive models based on multisource data (registries, clinical/functional and social support) from 761 nonsurgical patients admitted in a tertiary hospital over 12 months (October 2017 to November 2018). K-means clustering was used to characterize patient profiles. RESULTS: Performance (area under the receiver operating characteristic curve, sensitivity, and specificity) of the predictive models was 0.82, 0.78, and 0.70 and 0.72, 0.70, and 0.63 for mortality and readmissions, respectively. A total of 4 patients' profiles were identified. In brief, the reference patients (cluster 1; 281/761, 36.9%), 53.7% (151/281) men and mean age of 71 (SD 16) years, showed 3.6% (10/281) mortality and 15.7% (44/281) readmissions at 90 days following discharge. The unhealthy lifestyle habit profile (cluster 2; 179/761, 23.5%) predominantly comprised males (137/179, 76.5%) with similar age, mean 70 (SD 13) years, but showed slightly higher mortality (10/179, 5.6%) and markedly higher readmission rate (49/179, 27.4%). Patients in the frailty profile (cluster 3; 152/761, 19.9%) were older (mean 81 years, SD 13 years) and predominantly female (63/152, 41.4%, males). They showed medical complexity with a high level of social vulnerability and the highest mortality rate (23/152, 15.1%), but with a similar hospitalization rate (39/152, 25.7%) compared with cluster 2. Finally, the medical complexity profile (cluster 4; 149/761, 19.6%), mean age 83 (SD 9) years, 55.7% (83/149) males, showed the highest clinical complexity resulting in 12.8% (19/149) mortality and the highest readmission rate (56/149, 37.6%). CONCLUSIONS: The results indicated the potential to predict mortality and morbidity-related adverse events leading to unplanned hospital readmissions. The resulting patient profiles fostered recommendations for personalized service selection with the capacity for value generation.

Prospective cohort study for assessment of integrated care with a triple aim approach: hospital at home as use case.

BACKGROUND: Applicability of comprehensive assessment of integrated care services in real world settings is an unmet need. To this end, a Triple Aim evaluation of Hospital at Home (HaH), as use case, was done. As ancillary aim, we explored use of the approach for monitoring the impact of adoption of integrated care at health system level in Catalonia (Spain). METHODS: Prospective cohort study over one year period, 2017-2018, comparing hospital avoidance (HaH-HA) with conventional hospitalization (UC) using propensity score matching. Participants were after the first episode directly admitted to HaH-HA or the corresponding control group. Triple Aim assessment using multiple criteria decision analysis (MCDA) was done. Moreover, applicability of a Triple Aim approach at health system level was explored using registry data. RESULTS: HaH-HA depicted lower: i) Emergency Room Department (ER) visits (p < .001), ii) Unplanned re-admissions (p = .012); and iii) costs (p < .001) than UC. The weighted aggregation of the standardized values of each of the eight outcomes, weighted by the opinions of the stakeholder groups considered in the MCDA: i) enjoyment of life; ii) resilience; iii) physical functioning; iv) continuity of care; v) psychological wellbeing; (vi) social relationships & participation; (vii) person-centeredness; and (viii) costs, indicated better performance of HaH-HA than UC (p < .05). Actionable factors for Triple Aim assessment of the health system with a population-health approach were identified. CONCLUSIONS: We confirmed health value generation of HaH-HA. The study identified actionable factors to enhance applicability of Triple Aim assessment at health system level for monitoring the impact of adoption of integrated care. REGISTRATION: ClinicalTrials.gov (26/04/2017; NCT03130283).

Toward Sustainable Adoption of Integrated Care for Prevention of Unplanned Hospitalizations: A Qualitative Analysis.

Introduction: Complex chronic patients are prone to unplanned hospitalizations leading to a high burden on healthcare systems. To date, interventions to prevent unplanned admissions show inconclusive results. We report a qualitative analysis performed into the EU initiative JADECARE (2020-2023) to design a digitally enabled integrated care program aiming at preventing unplanned hospitalizations. Methods: A two-phase process with four design thinking (DT) sessions was conducted to analyse the management of complex chronic patients in the region of Catalonia (ES). In Phase I, Discovery, two DT sessions, October 2021 and February 2022, were done using as background information: i) the results of twenty structured interviews (five patients and fifteen professionals), ii) two governmental documents on regional deployment of integrated care and on the Catalan digital health strategy, respectively, and iii) the results of a cluster analysis of 761 hospitalizations. In Phase II, Confirmation, we examined the 30- and 90-day post-discharge periods of 49,604 hospitalizations as input for two additional DT sessions conducted in November and December 2022. Discussion: The qualitative analysis identified poor personalization of the interventions, the need for organizational changes, immature digitalization, and suboptimal services evaluation as main explanatory factors of the observed efficacy-effectiveness gap. Additionally, a program for prevention of unplanned hospitalizations, to be evaluated during the period 2024-2025, was generated. Conclusions: A digitally enabled adaptive case management approach to foster collaborative work and personalization of care, as well as organizational re-engineering, are endorsed for value-based prevention of unplanned hospitalizations.

Effectiveness of an Exercise and Educational-Based Prehabilitation Program in Patients with Breast Cancer Receiving Neoadjuvant Chemotherapy (PREOptimize) on Functional Outcomes: A Randomized Controlled Trial.

OBJECTIVE: The study objective was to determine the effectiveness of a prehabilitation program to decrease postoperative musculoskeletal impairments in patients who have breast cancer and are receiving neoadjuvant therapy (NAT). METHODS: Patients who had breast cancer and were receiving NAT before surgery were invited to participate in this randomized controlled trial. Patients randomized to the intervention group participated in a group-based prehabilitation program consisting of Nordic walking, resistance training, and therapeutic education from month 4 of NAT until before surgery. Patients in the control group received usual care (no prehabilitation). The main outcome was arm function measured with the short version of the Disabilities of the Arm, Shoulder and Hand questionnaire 1 month after surgery. Other measures included pain, range of motion, functional capacity, cancer-related fatigue, handgrip strength, physical activity, and arm circumferences. RESULTS: A total of 64 patients were randomized during the study period, and 61 completed all assessments. A significant difference in the main outcome (short version of the Disabilities of the Arm, Shoulder and Hand questionnaire) was found before surgery as patients in the control group experienced worsening in arm function (mean difference = -9.84, 95% CI = -17.7 to -2). In addition, they also showed increased symptom frequency/severity according to the combined scale of the European Organization for Research and Treatment of Cancer Quality of Life Questionnaire (EORTC-QLQ-C30) (mean difference = +6.7 points, 95% CI = 13.4 to 0.1) compared to the intervention group. Prehabilitation also improved functional capacity (mean difference = 67.6 m, 95% CI = 37.4 to 97.7) and physical activity levels and decreased cancer-related fatigue (mean difference = -1.3, 95% CI = -0.29 to -2.4) compared to the control group but had no effect on other secondary outcomes. After surgery, patients receiving prehabilitation also exhibited greater functional capacity at both 1 and 3 months. No other difference was observed. CONCLUSION: A prehabilitation program was able to maintain arm function and increase functional capacity while decreasing fatigue in patients with breast cancer receiving NAT. IMPACT: Prehabilitation programs should be offered to patients with breast cancer to maintain functionality and enhance physical performance before surgery. LAY SUMMARY: An exercise program combined with therapeutic education in patients with breast cancer who receive neoadjuvant therapy before surgery can improve functional capacity and prevent declines of arm mobility and function.

Toward Adoption of Health Risk Assessment in Population-Based and Clinical Scenarios: Lessons From JADECARE.

Introduction: Health risk assessment (HRA) strategies are cornerstone for health systems transformation toward value-based patient-centred care. However, steps for HRA adoption are undefined. This article analyses the process of transference of the Adjusted Morbidity Groups (AMG) algorithm from the Catalan Good Practice to the Marche region (IT) and to Viljandi Hospital (EE), within the JADECARE initiative (2020-2023). Description: The implementation research approach involved a twelve-month pre-implementation period to assess feasibility and define the local action plans, followed by a sixteen-month implementation phase. During the two periods, a well-defined combination of experience-based co-design and quality improvement methodologies were applied. Discussion: The evolution of the Catalan HRA strategy (2010-2023) illustrates its potential for health systems transformation, as well as its transferability. The main barriers and facilitators for HRA adoption were identified. The report proposes a set of key steps to facilitate site customized deployment of HRA contributing to define a roadmap to foster large-scale adoption across Europe. Conclusions: Successful adoption of the AMG algorithm was achieved in the two sites confirming transferability. Marche identified the key requirements for a population-based HRA strategy, whereas Viljandi Hospital proved its potential for clinical use paving the way toward value-based healthcare strategies.

Face-brain correlates as potential sex-specific biomarkers for schizophrenia and bipolar disorder.

Given the shared ectodermal origin and integrated development of the face and the brain, facial biomarkers emerge as potential candidates to assess vulnerability for disorders in which neurodevelopment is compromised, such as schizophrenia (SZ) and bipolar disorder (BD). The sample comprised 188 individuals (67 SZ patients, 46 BD patients and 75 healthy controls (HC)). Using a landmark-based approach on 3D facial reconstructions, we quantified global and local facial shape differences between SZ/BD patients and HC using geometric morphometrics. We also assessed correlations between facial and brain cortical measures. All analyses were performed separately by sex. Diagnosis explained 4.1 % - 5.9 % of global facial shape variance in males and females with SZ, and 4.5 % - 4.1 % in BD. Regarding local facial shape, we detected 43.2 % of significantly different distances in males and 47.4 % in females with SZ as compared to HC, whereas in BD the percentages decreased to 35.8 % and 26.8 %, respectively. We detected that brain area and volume significantly explained 2.2 % and 2 % of facial shape variance in the male SZ - HC sample. Our results support facial shape as a neurodevelopmental marker for SZ and BD and reveal sex-specific pathophysiological mechanisms modulating the interplay between the brain and the face.

Association between the 6MWT and other measurements of physical functioning in patients with cancer awaiting major surgery.

BACKGROUND: The Six Minute Walk Test (6MWT) is a widely used measure of functional capacity in (p)rehabilitation of cancer patients, but it is time-consuming and requires specific space conditions. In this study we explore the association between the 6MWT with other measurements of physical functioning and their predictive value in classifying patients according to their estimated functional capacity. DESIGN: This prospective study included cancer patients referred to a prehabilitation programme prior to major surgery. For each patient, data on different measurements of physical functioning including the Duke Activity Status Index (DASI), the handgrip strength, the 30" Sit-to-Stand Test and self-reported physical activity levels were collected. Bivariate associations were performed to determine the association between the 6MWT and other variables. Multivariate analyses were performed to identify potential predictive factors of 6MWT in this population. A subsequent algorithm was developed to classify patients based on their functional capacity (good performance - 6MWT>400 m or poor performance 6MWT<400 m) RESULTS: Between mid-2018 to mid 2022, 692 patients were assessed of whom the 6MWT was performed in 524 (75.7 %) (mean age 72.5 ± 11.8 years; 57.1 % men). Moderate-to-strong correlations were found between 6MWT and 30" Sit-To-Stand Test (r = 0.54, p < 0.001), DASI (r = 0.68; p < 0.001) and handgrip strength (r = 0.5; p < 0.001). Multivariate analyses confirmed that a combination of six variables were able to classify 80 % of patients in good (>400 m) or poor (<400 m) performance in the 6MWT. CONCLUSION: The 6MWT was moderately associated with several variables of physical functioning, a combination of which can be used to predict performance in the 6MWT.

Unique genetic and risk-factor profiles in clusters of major depressive disorder-related multimorbidity trajectories.

The heterogeneity and complexity of symptom presentation, comorbidities and genetic factors pose challenges to the identification of biological mechanisms underlying complex diseases. Current approaches used to identify biological subtypes of major depressive disorder (MDD) mainly focus on clinical characteristics that cannot be linked to specific biological models. Here, we examined multimorbidities to identify MDD subtypes with distinct genetic and non-genetic factors. We leveraged dynamic Bayesian network approaches to determine a minimal set of multimorbidities relevant to MDD and identified seven clusters of disease-burden trajectories throughout the lifespan among 1.2 million participants from cohorts in the UK, Finland, and Spain. The clusters had clear protective- and risk-factor profiles as well as age-specific clinical courses mainly driven by inflammatory processes, and a comprehensive map of heritability and genetic correlations among these clusters was revealed. Our results can guide the development of personalized treatments for MDD based on the unique genetic, clinical and non-genetic risk-factor profiles of patients.

Green Tea Catechins Modulate Skeletal Development with Effects Dependent on Dose, Time, and Structure in a down Syndrome Mouse Model.

Altered skeletal development in Down syndrome (DS) results in a brachycephalic skull, flattened face, shorter mandibular ramus, shorter limbs, and reduced bone mineral density (BMD). Our previous study showed that low doses of green tea extract enriched in epigallocatechin-3-gallate (GTE-EGCG), administered continuously from embryonic day 9 to postnatal day 29, reduced facial dysmorphologies in the Ts65Dn (TS) mouse model of DS, but high doses could exacerbate them. Here, we extended the analyses to other skeletal structures and systematically evaluated the effects of high and low doses of GTE-EGCG treatment over postnatal development in wild-type (WT) and TS mice using in vivo µCT and geometric morphometrics. TS mice developed shorter and wider faces, skulls, and mandibles, together with shorter and narrower humerus and scapula, and reduced BMD dynamically over time. Besides facial morphology, GTE-EGCG did not rescue any other skeletal phenotype in TS treated mice. In WT mice, GTE-EGCG significantly altered the shape of the skull and mandible, reduced the length and width of the long bones, and lowered the BMD. The disparate effects of GTE-EGCG depended on the dose, developmental timepoint, and anatomical structure analyzed, emphasizing the complex nature of DS and the need to further investigate the simultaneous effects of GTE-EGCG supplementation.