Search

Enhancing the eco-efficiency of municipal solid waste (MSW) services is pivotal for the shift toward a circular economy. Although the Data Envelopment Analysis (DEA) method is widely used, it is susceptible to overfitting, potentially distorting eco-efficiency assessments. This study applies the efficiency analysis tree (EAT) method, which synergizes machine learning and linear programming, offering a more reliable framework for eco-efficiency evaluation in the MSW sector. This innovative approach provides deeper insights into the optimal levels of operational costs and unsorted waste. The research encompasses a case study of 98 Chilean municipalities from 2015 to 2019, uncovering significant disparities in optimal operational expenses and unsorted waste quantities, which underscores the necessity for customized waste management approaches. The average eco-efficiency scores for 2015–2019 range between 0.561 and 0.566. This means that assessed municipalities can reduce unsorted waste by amounts ranging from 1,632,409 tons/year (2016) to 1,822,663 tons/year (2018). Potential economic savings estimated are 105,973 USD/year (2019), which represents 44% of the total MSW management costs. Additionally, the investigation into the effects of external factors on eco-efficiency furnishes nuanced perspectives that can guide policymakers and municipal authorities in developing effective, context-specific waste management strategies. Beyond refining eco-efficiency evaluations, this study contributes to more informed decision-making processes, aiding the progression toward sustainable waste management practices.

Abstract Understanding the water-energy-carbon nexus in water supply is essential for water regulators and utilities. This study employs a non-radial Data Envelopment Analysis (DEA) model to assess eco-productivity (ecoP) change, a synthetic indicator that integrates carbon emissions, energy costs, and water delivered. It also evaluates its components—eco-efficiency change and eco-technological change—across water companies in England and Wales from 2011 to 2018. The analysis reveals an annual improvement in ecoP of 1.1%, driven by a 2.1% gain in eco-efficiency but offset by a 1.0% decline in technological advancement. The reduction in GHG emissions emerged as the most significant positive contributor, enhancing ecoP by 3.22% annually, while energy costs detracted ecoP by –0.09%. The results underscore the negative impacts of increased water delivery (–1.74%) and the number of connected properties (–1.27%) on ecoP, highlighting the need for demand management policies.

Abstract Within the context of the water-energy nexus in drinking water provision, it is crucial to evaluate temporal shifts in energy efficiency. Utilizing the Stochastic Nonparametric Envelopment of Data (StoNED) approach, this research estimates longitudinal variations in the energy efficiency of drinking water services integrating multiple environmental variables. The analysis, conducted in England and Wales from 2008 to 2020, indicates that the source and quality of raw water, as well as population density, influenced the energy performance of water utilities. Quantitative findings evidenced marked disparity in energy efficiency among different companies, with an average efficiency of 0.617 and a range from 0.437 to 0.944. The dynamic assessment indicates an average annual enhancement of 1.1% in the sector, predominantly propelled by technical advancements (0.9%) rather than by improvements in efficiency (0.2%). This study emphasizes the critical need for bespoke policies and incentives to boost energy efficiency and support sustainable urban water management.

The transition to a zero-carbon water industry presents significant challenges for water companies and regulators. This study conducts both static and longitudinal assessments of carbon performance of water companies in England and Wales from 2008 to 2020. Carbon efficiency (CE) and carbon productivity (CP) metrics were estimated using the stochastic semi non-parametric envelopment of data method, which addresses the limitations of traditional parametric and non-parametric techniques. The average CE in 2020 was 0.628, indicating a 37.2% potential reduction in carbon emissions can be achieved by water companies. Despite regulatory efforts, the dynamic assessment shows negligible improvement in carbon performance, with average CP index value of 1.0009. The lack of technological innovation is identified as a key barrier, as technical change contributed negatively (0.9929) to CP, while efficiency change was positive (1.0091). The results highlight the critical role of raw water quality in achieving net-zero GHG emissions. Some strategies to accelerate the decarbonization of the water industry include prioritizing raw water protection, incentivizing technological advancements, and fostering knowledge sharing among companies.

BackgroundLow back pain (LBP) presents with diverse manifestations, necessitating personalized treatment approaches that recognize various phenotypes within the same diagnosis, which could be achieved through precision medicine. Although prediction strategies have been explored, including those employing artificial intelligence (AI), they still lack scalability and real-time capabilities. Digital care programs (DCPs) facilitate seamless data collection through the Internet of Things and cloud storage, creating an ideal environment for developing and implementing an AI predictive tool to assist clinicians in dynamically optimizing treatment. ObjectiveThis study aims to develop an AI tool that continuously assists physical therapists in predicting an individual’s potential for achieving clinically significant pain relief by the end of the program. A secondary aim was to identify predictors of pain nonresponse to guide treatment adjustments. MethodsData collected actively (eg, demographic and clinical information) and passively in real-time (eg, range of motion, exercise performance, and socioeconomic data from public data sources) from 6125 patients enrolled in a remote digital musculoskeletal intervention program were stored in the cloud. Two machine learning techniques, recurrent neural networks (RNNs) and light gradient boosting machine (LightGBM), continuously analyzed session updates up to session 7 to predict the likelihood of achieving significant pain relief at the program end. Model performance was assessed using the area under the receiver operating characteristic curve (ROC-AUC), precision-recall curves, specificity, and sensitivity. Model explainability was assessed using SHapley Additive exPlanations values. ResultsAt each session, the model provided a prediction about the potential of being a pain responder, with performance improving over time (P

BackgroundRace/ethnicity and gender concordance between patients and providers is a potential strategy to improve health care interventions. In digital health, where human interactions occur both synchronously and asynchronously, the effect of concordance between patients and providers is unknown. ObjectiveThis study aimed to evaluate the impact of race/ethnicity or gender concordance between patients and physical therapists (PTs) in engagement and the clinical outcomes following a digital care program (DCP) in patients with musculoskeletal (MSK) conditions. MethodsThis secondary analysis of 2 prospective longitudinal studies (originally focused on assessing the acceptance, engagement, and clinical outcomes after a remote DCP) examined the impact of both race/ethnicity concordance and gender concordance between patients and PTs on outcomes for a digital intervention for MSK conditions. Outcomes included engagement (measured by the completion rate and communication, assessed by text interactions), satisfaction, and clinical outcomes (response rate, ie, percentage of patients achieving at least a minimal clinically important change in pain, measured by the Numerical Pain Rating Scale [NPRS]; anxiety, measured by the Generalized Anxiety Disorder 7-item scale [GAD-7]; depression, measured by the Patient Health Questionnaire 9-item [PHQ-9]; and daily activity impairment, measured by the Work Productivity and Activity Impairment [WPAI] questionnaire). ResultsOf 71,201 patients, 63.9% (n=45,507) were matched with their PT in terms of race/ethnicity, while 61.2% (n=43,560) were matched for gender. Concordant dyads showed a higher completion rate among White (adjusted odds ratio [aOR] 1.11, 95% CI 1.05-1.19, P8.52, 95% CI 8.27-8.77) reported across all dyads. Response rates for pain, anxiety, and daily activity impairment were unaffected by race/ethnicity concordance. An exception was observed for depression, with White patients reporting a higher response rate when matched with PTs from other races/ethnicities (aOR 1.20, 95% CI 1.02-1.39, P=.02). In terms of gender, men had a slightly higher pain response rate in discordant dyads (aOR 1.08, 95% CI 1.01-1.15, P=.03) and a higher depression response rate in concordant dyads (aOR 1.23, 95% CI 1.05-1.47, P=.01). ConclusionsRace/ethnicity and gender concordance between patients and PTs does not translate into higher satisfaction or improvement for most clinical outcomes, aside from a positive effect on treatment completion. These results highlight the importance of other PT characteristics, in addition to race/ethnicity or gender concordance, suggesting the potential benefit of experience, languages spoken, and cultural safety training as ways to optimize care. Trial RegistrationClinicalTrials.gov NCT04092946, NCT05417685; https://clinicaltrials.gov/study/NCT05417685, https://clinicaltrials.gov/study/NCT04092946

Abstract Water treatment processes are known to consume substantial amounts of energy, making it crucial to understand their efficiency, drivers, and potential energy savings. In this study, we apply Efficiency Analysis Tree (EAT), which combines machine learning and linear programming techniques to assess the energy performance of 146 Chilean drinking water treatment plants (DWTPs) for 2020. Additionally, we utilize bootstrap regression techniques to examine the influence of operating characteristics on energy efficiency. The results indicate that the evaluated DWTPs exhibited poor energy performance, with an average energy efficiency score of 0.197. The estimated potential energy savings were found to be 0.005 kWh/m3. Several factors, such as the age of the facility, source of raw water, and treatment technology, were identified as significant drivers of energy efficiency in DWTPs. The insights gained from our study can be valuable for policymakers in making informed decisions regarding the adoption of practices that promote efficient and sustainable energy use within the water cycle.

Abstract Digital interventions have emerged as a solution for time and geographical barriers, however, their potential to target other social determinants of health is largely unexplored. In this post-hoc analysis, we report the impact of social deprivation on engagement and clinical outcomes after a completely remote multimodal musculoskeletal (MSK) digital care program managed by a culturally-sensitive clinical team. Patients were stratified in five categories according to their social deprivation index, and cross-referenced with their race/ethnicity, rurality and distance to healthcare facilities. From a total of 12,062 patients from all U.S. states, 8569 completed the program. Higher social deprivation was associated with greater baseline disease burden. We observed that all categories reported pain improvements (ranging from −2.0 95%CI −2.1, −1.9 to −2.1 95%CI −2.3, −1.9, p

Abstract Low back pain (LBP) is the world’s leading cause of years lived with disability. Digital exercise-based interventions have shown great potential in the management of musculoskeletal conditions, promoting access and easing the economic burden. However, evidence of their effectiveness for chronic LBP (CLBP) management compared to in-person physiotherapy has yet to be unequivocally established. This randomized controlled trial (RCT) aims to compare the clinical outcomes of patients with CLBP following a digital intervention versus evidence-based in-person physiotherapy. Our results demonstrate that patient satisfaction and adherence were high and similar between groups, although a significantly lower dropout rate is observed in the digital group (11/70, 15.7% versus 24/70, 34.3% in the conventional group; P = 0.019). Both groups experience significant improvements in disability (primary outcome), with no differences between groups in change from baseline (median difference: −0.55, 95% CI: −2.42 to 5.81, P = 0.412) or program-end scores (−1.05, 95% CI: −4.14 to 6.37; P = 0.671). Likewise, no significant differences between groups are found for secondary outcomes (namely pain, anxiety, depression, and overall productivity impairment). This RCT demonstrates that a remote digital intervention for CLBP can promote the same levels of recovery as evidence-based in-person physiotherapy, being a potential avenue to ease the burden of CLBP.

Abstract Benchmarking the dynamic performance of water companies is a powerful tool to develop sound policies. However, it requires the use of reliable and robust methods and quality of data. In this study, the stochastic nonparametric envelopment of data (StoNED) method was employed to assess productivity change and eco-productivity change of a sample of Chilean water companies over the period 2010–2018. The StoNED approach overcomes the main limitations of stochastic frontier analysis and data envelopment analysis techniques which are the most commonly used to evaluate performance of water companies. Productivity change metric focused on the economic performance, whereas eco-productivity change evaluated economic and quality of service performance by including non-revenue water and unplanned water supply interruptions. Hence, this study analyzed the impact of quality of service variables on the dynamic eco-efficiency of water companies. The annual average productivity change and eco-productivity change estimations were 0.18% and −0.14%, respectively. It was evidenced that on average the Chilean water companies have put as priority to reduce operational costs than to improve quality of service. In both performance metrics, efficiency change was the main contributor to performance changes, whereas the role of technical change was negligible. It was illustrated that full private water companies performed better than concessionary companies and the public company. Reducing non-revenue water and unplanned water supply interruptions was particularly costly for concessionary water companies. The methodology and conclusions of this study are of great interest for water regulators and water utilities to improve the benchmarking process in the provision of drinking water services.

Abstract The regulation of water companies (WCs) is essential to protect the interests of citizens, as companies are natural monopolies. Consequently, several methodological approaches are applied by water regulators to benchmark the performance of WCs, with data envelopment analysis (DEA) being one of the most widely applied. However, traditional DEA models allocate different weights to variables considered in efficiency assessments of each WC. By contrast, this study proposes and applies a common set weights (CSW) DEA model to a sample of Chilean WCs. The results showed that the DEA-CSW approach had greater discriminatory capacity compared to traditional DEA techniques. Moreover, weights allocated to input and output variables involved in efficiency assessment diverged among WCs when the traditional DEA model was employed. By contrast, the DEA-CSW approach generated reliable ranking of WCs based on their efficiency scores, thus facilitating the regulatory decision-making process.

Moving towards a circular and sustainable economy requires improving the management of municipal solid waste (MSW) increasing recycling rates while minimising unsorted waste and operational costs. It is essential to evaluate the economic and environmental efficiency of MSW services. Previous studies focused on developed countries and employed radial parametric and non-parametric methods. By contrast, this study assessed the technical efficiency, environmental efficiency and eco-efficiency of several Chilean municipalities employing the non-radial range adjusted measure approach. A second stage of assessment was conducted to explore the influence of a set of environmental variables on efficiency scores. Results revealed that the evaluated Chilean municipalities performed poorly from a technical perspective since the average technical efficiency score was 0.484. By contrast, average environmental efficiency and eco-efficiency scores were 0.899 and 0.922, respectively. Nevertheless, the percentage of eco-efficient municipalities was lower than 1%. It was also found that tourism had a major and negative impact on all types of efficiency. By contrast, population density had a significant and positive impact on environmental efficiency. The assessment of three types of efficiency provides relevant information to policymakers to define specific strategies to improve MSW management according to sustainability and circular economic objectives.

BackgroundAging is closely associated with an increased prevalence of musculoskeletal conditions. Digital musculoskeletal care interventions emerged to deliver timely and proper rehabilitation; however, older adults frequently face specific barriers and concerns with digital care programs (DCPs). ObjectiveThis study aims to investigate whether known barriers and concerns of older adults impacted their participation in or engagement with a DCP or the observed clinical outcomes in comparison with younger individuals. MethodsWe conducted a secondary analysis of a single-arm investigation assessing the recovery of patients with musculoskeletal conditions following a DCP for up to 12 weeks. Patients were categorized according to age: ≤44 years old (young adults), 45-64 years old (middle-aged adults), and ≥65 years old (older adults). DCP access and engagement were evaluated by assessing starting proportions, completion rates, ability to perform exercises autonomously, assistance requests, communication with their physical therapist, and program satisfaction. Clinical outcomes included change between baseline and program end for pain (including response rate to a minimal clinically important difference of 30%), analgesic usage, mental health, work productivity, and non–work-related activity impairment. ResultsOf 16,229 patients, 12,082 started the program: 38.3% (n=4629) were young adults, 55.7% (n=6726) were middle-aged adults, and 6% (n=727) were older adults. Older patients were more likely to start the intervention and to complete the program compared to young adults (odds ratio [OR] 1.72, 95% CI 1.45-2.06; P

BackgroundChronic shoulder pain (CSP) is a common condition with various etiologies, including rotator cuff disorders, adhesive capsulitis, shoulder instability, and shoulder arthritis. It is associated with substantial disability and psychological distress, resulting in poor productivity and quality of life. Physical therapy constitutes the mainstay treatment for CSP, but several barriers exist in accessing care. In recent years, telerehabilitation has gained momentum as a potential solution to overcome such barriers. It has shown numerous benefits, including improving access and convenience, promoting patient adherence, and reducing costs. However, to date, no previous randomized controlled trial has compared fully remote digital physical therapy to in-person rehabilitation for nonoperative CSP. ObjectiveThe aim of this study is to compare clinical outcomes between digital physical therapy and conventional in-person physical therapy in patients with CSP. MethodsWe conducted a single-center, parallel-group, randomized controlled trial involving 82 patients with CSP referred for outpatient physical therapy. Participants were randomized into digital or conventional physical therapy (8-week interventions). The digital intervention consisted of home exercise, education, and cognitive behavioral therapy (CBT), using a device with movement digitalization for biofeedback and asynchronous physical therapist monitoring through a cloud-based portal. The conventional group received in-person physical therapy, including exercises, manual therapy, education, and CBT. The primary outcome was the change (baseline to 8 weeks) in function and symptoms using the short-form of Disabilities of the Arm, Shoulder, and Hand questionnaire. Secondary outcome measures included self-reported pain, surgery intent, analgesic intake, mental health, engagement, and satisfaction. All questionnaires were delivered electronically. ResultsA total of 90 participants were randomized into digital or conventional physical therapy, with 82 receiving the allocated intervention. Both groups experienced significant improvements in function measured by the short-form of the Disabilities of the Arm, Shoulder, and Hand questionnaire, with no differences between groups (–1.8, 95% CI –13.5 to 9.8; P=.75). For secondary outcomes, no differences were observed in surgery intent, analgesic intake, and mental health or worst pain. Higher reductions were observed in average and least pain in the conventional group, which, given the small effect sizes (least pain 0.15 and average pain 0.16), are unlikely to be clinically meaningful. High adherence and satisfaction were observed in both groups, with no adverse events. ConclusionsThis study shows that fully remote digital programs can be viable care delivery models for CSP given their scalability and effectiveness, assessed through comparison with high-dosage in-person rehabilitation. Trial RegistrationClinicalTrials.gov (NCT04636528); https://clinicaltrials.gov/study/NCT04636528

Background Musculoskeletal conditions are the leading cause of disability worldwide. Telerehabilitation may be a viable option in the management of these conditions, facilitating access and patient adherence. Nevertheless, the impact of biofeedback-assisted asynchronous telerehabilitation remains unknown. Objective To systematically review and assess the effectiveness of exercise-based asynchronous biofeedback-assisted telerehabilitation on pain and function in individuals with musculoskeletal conditions. Methods This systematic review followed Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines. The search was conducted using three databases: PubMed, Scopus, and PEDro. Study criteria included articles written in English and published from January 2017 to August 2022, reporting interventional trials evaluating exercise-based asynchronous telerehabilitation using biofeedback in adults with musculoskeletal disorders. The risks of bias and certainty of evidence were appraised using the Cochrane tool and Grading of Recommendations, Assessment, Development, and Evaluation (GRADE), respectively. The results are narratively summarized, and the effect sizes of the main outcomes were calculated. Results Fourteen trials were included: 10 using motion tracker technology ( N = 1284) and four with camera-based biofeedback ( N = 467). Telerehabilitation with motion trackers yields at least similar improvements in pain and function in people with musculoskeletal conditions (effect sizes: 0.19–1.45; low certainty of evidence). Uncertain evidence exists for the effectiveness of camera-based telerehabilitation (effect sizes: 0.11–0.13; very low evidence). No study found superior results in a control group. Conclusions Asynchronous telerehabilitation may be an option in the management of musculoskeletal conditions. Considering its potential for scalability and access democratization, additional high-quality research is needed to address long-term outcomes, comparativeness, and cost-effectiveness and identify treatment responders.

BackgroundMusculoskeletal (MSK) conditions are the number one cause of disability worldwide. Digital care programs (DCPs) for MSK pain management have arisen as alternative care delivery models to circumvent challenges in accessibility of conventional therapy. Despite the potential of DCPs to reduce inequities in accessing care, the outcomes of such interventions in rural and urban populations have yet to be studied. ObjectiveThe aim of this study was to assess the impact of urban or rural residency on engagement and clinical outcomes after a multimodal DCP for MSK pain. MethodsThis study consists of an ad hoc analysis of a decentralized single-arm investigation into engagement and clinical-related outcomes after a multimodal DCP in patients with MSK conditions. Patients were coded according to their zip codes to a specific rural-urban commuting area code and grouped into rural and urban cohorts. Changes in their engagement and clinical outcomes from baseline to program end were assessed. Latent growth curve analysis was performed to estimate change trajectories adjusting for the following covariates: age, gender, BMI, employment status, and pain acuity. Outcomes included engagement, self-reported pain, and the results of the Generalized Anxiety Disorder 7-item, Patient Health Questionnaire 9-item, and Work Productivity and Activity Impairment scales. A minimum clinically important difference (MCID) of 30% was considered for pain. ResultsPatients with urban and rural residency across the United States participated in the program (n=9992). A 73.8% (7378/9992) completion rate was observed. Both groups reported high satisfaction scores and similar engagement with exercise sessions, with rural residents showing higher engagement with educational content (P

Abstract Background Acute musculoskeletal (MSK) pain is very common and associated with impaired productivity and high economic burden. Access to timely and personalized, evidence-based care is key to improve outcomes while reducing healthcare expenditure. Digital interventions can facilitate access and ensure care scalability. Objective Present the feasibility and results of a fully remote digital care program (DCP) for acute MSK conditions affecting several body areas. Methods Interventional single-arm study of individuals applying for digital care programs for acute MSK pain. Primary outcome was the mean change between baseline and end-of-program in self-reported Numerical Pain Rating Scale (NPRS) score and secondary outcomes were change in analgesic consumption, intention to undergo surgery, anxiety (GAD-7), depression (PHQ-9), fear-avoidance beliefs (FABQ-PA), work productivity (WPAI-GH) and engagement. Results Three hundred forty-three patients started the program, of which 300 (87.5%) completed the program. Latent growth curve analysis (LGCA) revealed that changes in NPRS between baseline and end-of-program were both statistically (p

Abstract The path to a sustainable management of the urban water cycle requires the assessment of both operational and quality-adjusted efficiency in a unified manner. This can be done by the use of non-radial Data Envelopment Analysis models. This study used Range Adjusted Measure models to evaluate the operational, quality-adjusted, and operational & quality-adjusted efficiency (O&QAE) scores of the Chilean water industry including water leakage and unplanned interruptions as undesirable outputs. It was found that on average water utilities presented large O&QAE scores over time. The mean O&QAE score was 0.964 which means that water utilities could further reduce costs and undesirable outputs by 3.6% on average, while trying to expand the scale of operation. This finding suggests that excellent quality-adjusted efficiency at an efficient expenditure could be feasible. It was also evidenced that customer density, mixed water resources, and ownership influenced the O&QAE of Chilean water companies.

Abstract. Introduction:. Wrist and hand represent the third most common body part in work-related injuries, being associated with long-term absenteeism. Telerehabilitation can promote access to treatment, patient adherence, and engagement, while reducing health care–related costs. Objective:. Report the results of a fully remote digital care program (DCP) for wrist and hand pain (WP). Methods:. A single-arm interventional study was conducted on individuals with WP applying for a DCP. Primary outcome was the mean change in the Numerical Pain Rating Scale after 8 weeks (considering a minimum clinically important change of 30%). Secondary outcomes were: disability (Quick Disabilities of the Arm, Shoulder, and Hand questionnaire), analgesic intake, surgery intention, mental health (patient health questionnaire [PHQ-9] and generalized anxiety disorder [GAD-7]), fear-avoidance beliefs (FABQ-PA), work productivity and activity impairment, and engagement. Results:. From 189 individuals starting the DCP, 149 (78.8%) completed the intervention. A significant pain improvement was observed (51.3% reduction (2.26, 95% CI 1.73; 2.78)) and 70.4% of participants surpassing minimum clinically important change. This change correlated with improvements in disability (52.1%), FABQ-PA (32.2%), and activities impairment recovery (65.4%). Improvements were also observed in other domains: surgery intent (76.1%), mental health (67.0% in anxiety and 72.7% in depression), and overall productivity losses (68.2%). Analgesic intake decreased from 22.5% to 7.1%. Mean patient satisfaction score was 8.5/10.0 (SD 1.8). Conclusions:. These findings support the feasibility and utility of a fully remote DCP for patients with WP. Clinically significant improvements were observed in all health-related and productivity-related outcomes, alongside very high patient adherence rates and satisfaction. This study strengthens that management of WP is possible through a remote DCP, decreasing access barriers and potentially easing health care expenditure.

BackgroundMusculoskeletal (MSK) pain disproportionately affects people from different ethnic backgrounds through higher burden and less access to care. Digital care programs (DCPs) can improve access and help reduce inequities. However, the outcomes of such programs based on race and ethnicity have yet to be studied. ObjectiveWe aimed to assess the impact of race and ethnicity on engagement and outcomes in a multimodal DCP for MSK pain. MethodsThis was an ad hoc analysis of an ongoing decentralized single-arm investigation into engagement and clinical-related outcomes after a multimodal DCP in patients with MSK conditions. Patients were stratified by self-reported racial and ethnic group, and their engagement and outcome changes between baseline and 12 weeks were compared using latent growth curve analysis. Outcomes included program engagement (number of sessions), self-reported pain scores, likelihood of surgery, Generalized Anxiety Disorder 7-item scale, Patient Health Questionnaire 9-item, and Work Productivity and Activity Impairment. A minimum clinically important difference (MCID) of 30% was calculated for pain, and multivariable logistic regression was performed to evaluate race as an independent predictor of meeting the MCID. ResultsA total of 6949 patients completed the program: 65.5% (4554/6949) of them were non-Hispanic White, 10.8% (749/6949) were Black, 9.7% (673/6949) were Asian, 9.2% (636/6949) were Hispanic, and 4.8% (337/6949) were of other racial or ethnic backgrounds. The population studied was diverse and followed the proportions of the US population. All groups reported high engagement and satisfaction, with Hispanic and Black patients ranking first among satisfaction despite lower engagement. Black patients had a higher likelihood to drop out (odds ratio [OR] 1.19, 95% CI 1.01-1.40, P=.04) than non-Hispanic White patients. Hispanic and Black patients reported the highest level of pain, surgical intent, work productivity, and impairment in activities of daily living at baseline. All race groups showed a significant improvement in all outcomes, with Black and Hispanic patients reporting the greatest improvements in clinical outcomes. Hispanic patients also had the highest response rate for pain (75.8%) and a higher OR of meeting the pain MCID (OR 1.74, 95% CI 1.24-2.45, P=.001), when compared with non-Hispanic White patients, independent of age, BMI, sex, therapy type, education level, and employment status. No differences in mental health outcomes were found between race and ethnic groups. ConclusionsThis study advocates for the utility of a DCP in improving access to MSK care and promoting health equity. Engagement and satisfaction rates were high in all the groups. Black and Hispanic patients had higher MSK burden at baseline and lower engagement but also reported higher improvements, with Hispanic patients presenting a higher likelihood of pain improvement.

BackgroundComorbidity between musculoskeletal (MSK) pain and depression is highly common, and is associated with a greater symptom burden and greater loss of work productivity than either condition alone. Multimodal care programs tackling both physical and mental health components may maximize productivity recovery and return to work. Digital delivery of such programs can facilitate access, ensure continuity of care, and enhance patient engagement. ObjectiveThe aim of this study was to assess the impact of a completely remote multimodal digital care program (DCP) for MSK pain on mental health and work-related outcomes stratified by baseline depression levels. MethodsAd hoc analysis of an interventional, single-arm, cohort study of individuals with MSK pain undergoing a DCP was performed. Three subgroups with different baseline depression severity levels were established based on responses to the Patient Health Questionnaire (PHQ-9): cluster 1 (score

BackgroundAnkle sprains are one of the most prevalent soft-tissue injuries worldwide. Physical therapy, especially progressive exercise, has proven effective in improving function, while preventing recurrence. ObjectiveWe aim to present the results of a fully remote and digitally guided rehabilitation program for acute ankle sprains. MethodsWe performed a prospective longitudinal cohort study of individuals eligible for workers’ compensation, who were referred for digital rehabilitation therapy for a sprained ankle. Therapeutic exercise sessions were to be performed independently by the patient at home using the biofeedback device provided by SWORD Health. Primary endpoints were the change in self-reported Numerical Pain Rating Scale (NPRS) and Foot and Ankle Ability Measure–activities of daily living (FAAM–ADL) and FAAM–Sports scores. Participants were assessed at baseline, end of the program, and 6 months after program completion. Secondary outcomes included digital therapy dosage, pain and fatigue during sessions, and satisfaction. ResultsIn total, 93 (89.4%) patients completed the program and 79 (76.0%) were available for follow-up. Changes in the primary outcomes between baseline and the 6-month follow-up were both significant (P

Evaluating the performance and analyzing the cost drivers of water utilities is of great interest for water regulators and water sector managers. This study uses a quadratic cost function to investigate the existence of economies of scale and scope in the Chilean water and sewerage industry over the period 2010-2017. We also estimate and decompose productivity growth into technical change and scale efficiency change. Technical change is further broken into pure, non-neutral and scale-augmenting technical change. The results indicate that cost savings can be achieved by increases in the scale of production and the separation of water and sewerage services. Productivity progressed favorably throughout the whole period at an annual rate of 8.4%, which was attributed to the scale effect, the adoption of new technologies and a good allocation of resources. Some policy implications are finally discussed based on our findings.

Study region: The largest 23 water utilities in Chile providing water and sanitation services to 97.9 % of total urban customers. Study focus: This study introduces an innovative methodological framework based on inverse data envelopment analysis technique to quantify the additional operational costs required for water utilities to enhance their water supply and sanitation continuity while maintaining their techno-economic efficiency. This framework is pivotal for setting realistic continuity targets and assessing potential impacts on water and sanitation tariffs, thereby aiding in policy and operational planning within the water sector. New hydrological insights for the region: The analysis was performed across four distinct continuity scenarios revealing substantial cost variability contingent on continuity targets, current service levels, and the efficiency of each utility. Results showed a median operational cost increase that varied from 28.41 % in the most stringent scenario to just 0.27 % in the most lenient. The financial implications of meeting these costs through water and sanitation tariffs would necessitate a median monthly increase in water bills, ranging from $17.24 per household in the most demanding scenarios to only $0.01 per household in the more lenient scenarios. This research provides a valuable tool for water sector regulators and managers, enabling informed decision-making by balancing service improvement objectives with economic considerations and customer willingness to pay for enhanced service continuity.