A multi-step approach to evaluate the sustainable use of groundwater resources for human consumption and agriculture.

The rapid decline in both quality and availability of freshwater resources on our planet necessitates their thorough assessment to ensure sustainable usage. The growing demand for water in industrial, agricultural, and domestic sectors poses significant challenges to managing both surface and groundwater resources. This study tests and proposes a hybrid evaluation approach to determine Groundwater Quality Indices (GQIs) for irrigation (IRRI), seawater intrusion (SWI), and potability (POT), finalized to the spatial distribution of groundwater suitability involving water quality indicator along with hydrogeological and socio-economic factors. Mean Decrease Accuracy (MDA) and Information Gain Ratio (IGR) were used to state the importance of chosen factors such as level of groundwater above the sea, thickness of the aquifer, land cover, distance from coastline, silt soil content, recharge, distance from river and lagoons, depth to water table from ground, distance from agricultural wells, hydraulic conductivity, and lithology for each quality index, separately. The results of both methods showed that recharge is the most important parameter for GQIIRRI and GQIPOT, while the distance from the coastline and the rivers, are the most important for GQISWI. The spatial modelling of GQIIRRI and GQIPOT in the study area has been achieved applying three machine learning (ML) algorithms: the Boosted Regression Tree (BRT), the Random Forest (RF), and the Support Vector Machine (SVM). Validation results showed that RF has the highest prediction for GQIIRRI, while the SVM model has the highest prediction for the GQIPOT index. It is worth to mention that the future utilization and testing of new algorithms could produce even better results. Finally, GQIIRRI and GQIPOT were combined and compared using two combine and overlay methods to prepare a hybrid map of multi-GQIs. The results showed that 69% of the study area is suitable for irrigation and potable use, due to both geogenic and anthropogenic activities which contribute to make some water resources unsuitable for either use. Specifically, the northern, western, and eastern portions of the study area are in the "very high and high quality" classes while the southern portion shows "very low and low quality" classes. In conclusion, the developed map and approach can serve as a practical guide for enhancing groundwater management, identifying suitable areas for various uses and pinpointing regions requiring improved management practices.

Identifying patient subgroups with different trends of patient-reported outcomes (PROMs) after elective knee arthroplasty.

BACKGROUND: Patient-reported outcome measures (PROMs) are increasingly being used to assess the effectiveness of elective total knee arthroplasty (TKA). However, little is known about how PROMs scores change over time in these patients. The aim of this study was to identify the trajectories of quality of life and joint functioning, and their associated demographic and clinical features in patients undergoing elective TKA. METHODS: A prospective, cohort study was conducted, in which PROMs questionnaires (Euro Quality 5 Dimensions 3L, EQ-5D-3L, and Knee injury and Osteoarthritis Outcome Score Patient Satisfaction, KOOS-PS) were administered to patients at a single center undergoing elective TKA before surgery, and at 6 and 12 months after surgery. Latent class growth mixture models were used to analyze the patterns of change in PROMs scores over time. Multinomial logistic regression was used to investigate the association between patient characteristics and PROMs trajectories. RESULTS: A total of 564 patients were included in the study. The analysis highlighted differential patterns of improvement after TKA. Three distinct PROMs trajectories were identified for each PROMs questionnaire, with one trajectory indicating the most favorable outcome. Female gender appears to be associated with a presentation to surgery with worse perceived quality of life and joint function than males, but also more rapid improvement after surgery. Having an ASA score greater than 3 is instead associated with a worse functional recovery after TKA. CONCLUSION: The results suggest three main PROMs trajectories in patients undergoing elective TKA. Most patients reported improved quality of life and joint functioning at 6 months, which then stabilized. However, other subgroups showed more varied trajectories. Further research is needed to confirm these findings and to explore the potential clinical implications of these results.

Patient reported outcomes measures (PROMs) trajectories after elective hip arthroplasty: a latent class and growth mixture analysis.

BACKGROUND: Patient-reported outcome measures (PROMs) are an extensively used tool to assess and improve the quality of healthcare services. PROMs can be related to individual demographic and clinical characteristics in patients undergoing hip arthroplasty (HA). The aim of this study is to identify distinct subgroups of patients with unique trajectories of PROMS scores and to determine patients' features associated with these subgroups. METHODS: We conducted a prospective, cohort study in which PROMs questionnaires (Euro Quality 5 Dimensions 3L, EQ-5D-3L, Euro-Quality-Visual-Analytic-Score, EQ-VAS, Hip disability and Osteoarthritis Outcome Score, HOOS-PS) were administered to patients undergoing elective HA pre-operatively, and at 6 and 12 months after surgery. For each measure, latent class growth analysis and growth mixture models were used to identify subgroups of patients with distinct trajectories of scores. Demografic and clinical predictors of the latent classes in growth mixture model were identified using a 3-step approach. RESULTS: We found three distinct trajectories for each PROM score. These trajectories indicated a response heterogeneity to the HA among the patients (n = 991). Patient's gender, ASA score, and obesity were significantly associated with different PROMs trajectories. CONCLUSIONS: We identified three distinct trajectories for each of the three PROMs indicators. Several demographic and clinical characteristics are associated with the different trajectories of PROMs at 6 and 12 months after HA and could be used to identify groups of patients with different outcomes following HA surgery. These findings underline the importance of patient-centered care, supporting the usefulness of integrating PROMs data alongside routinely collected healthcare records for guiding clinical care and maximizing patients' positive outcomes. TRIAL REGISTRATION: Protocol version (1.0) and trial registration data are available on the platform www. CLINICALTRIAL: gov with the identifier NCT03790267, posted on December 31, 2018.

Adherence to and early adverse events of COVID-19 vaccine in a cohort of 600 Italian breastfeeding and pregnant physicians.

Pregnant and breastfeeding women (PBW) have been excluded from COVID-19 vaccine registry and the majority of post-marketing trials, despite the recognized increased risk of severe infections and complications. The lack of efficacy and safety data prevented the formulation of specific indications/guidelines for vaccination and could have also contributed to increased vaccine hesitancy (VH) in PBW. The aim of this cross-sectional study is to assess the rate and predictors of VH, and early adverse events (AEFI) following COVID-19 vaccine in PBW with a cross-sectional study. In January 2021, a purposely designed questionnaire was administered to 600 PBW part of a Facebook group of physicians, immunized with two doses of Comirnaty®. Thirty-eight (29%) pregnant women and 13 (2.8%) breastfeeders were hesitant. The only statistically significant negative predictor of COVID-19 VH appeared to be having had the flu shot in 2020/2021 (OR: 0.35; 95% CI: 0.13-0.97; p = .044). Approximately 27% of PBW reported hesitancy toward the 2020/2021 season influenza vaccine. Among the vaccinated subjects, 51.6% of pregnant and 75.2% of breastfeeding women reported at least one symptom after the first, and 82.4% and 81.6%, respectively, after the second dose. Nausea/vomiting, fatigue, headache and arthralgia/myalgia were the most common symptoms; dizziness, shivering, syncope and limb paresthesia were rarely reported. Among infants of breastfeeding mothers, six experienced fever, five rash and four moderate and self-limiting diarrhea. Preliminary data on mRNA COVID-19 vaccine in PBW and in their infants are reassuring since AEFI, although frequent, are typically mild and similar to those occurring in the general population, and in PBW after other vaccines. Larger studies with longer follow-up after vaccination are strongly recommended to develop recommendations in these patients.

Geochemical characterization and health risk assessment in two diversified environmental settings (Southern Italy).

An integrated approach using chemical and microbial indicators has been tested in two different sites of the Campania Plain (Southern Italy) with different land use covering and different hydrogeological features in order: (1) to define the water-rock interaction processes, (2) to differentiate sources of pollution in a detailed way (3) to evaluate the degree of water quality in the studied alluvial aquifer and (4) to identify the most worrying elements for human's health. Groundwater have showed a HCO3-Ca signature for both investigated sites, and a progressive enrichment in alkali ions has been highlighted moving from the boundary of the plain toward the coastal areas, due to groundwater interaction with volcanic rocks along the flow path. The application of the Factor Analysis allowed to identify different sources of pollution, which were attributed to (a) leaks in the sewer system for the Agro-Aversano Area and also the spreading of manure as fertilizers in agricultural activities for the Caiazzo Plain. Furthermore, it has been highlighted that the use of major elements, trace elements and microbiological indicators, allows to accurately differentiate contamination processes in progress. In fact, from the results of the Factor Analysis applied in the Agro-Aversano area, no significant statistically relationships between major elements and microbiological indicators of fecal contamination were highlighted, unlike the Caiazzo plain where statistically significant correlations have been found between major and trace elements and microbiological indicators. The use of a Groundwater Quality Index has shown general poor water quality for the majority of analyzed samples due to the high amount of Nitrate and Fecal indicators. The use of a Health Risk Assessment highlighted that Nitrate coupled with Fluoride represent the most important concern for human health compared to the all investigated parameters in both sites.

Tracing groundwater circulation in a valuable mineral water basin with geochemical and isotopic tools: the case of FERRARELLE, Riardo basin, Southern Italy.

The Riardo basin hosts groundwater exploited for the production of high quality, naturally sparkling, bottled water (e.g., Ferrarelle water), and circulating in a system constituted by highly fractured Mesozoic carbonates, overlain by more impervious volcanic rocks of the Roccamonfina complex. The two formations are locally in hydraulic connection and dislocated by deep-rooted faults. The study aimed at elucidating groundwater origin and circulation, using isotopic tracers (δ18O, δ2H, δ11B and 87Sr/86Sr) coupled to groundwater dating (Tritium, CFCs and SF6). Besides recharge by local precipitation over the Riardo hydrogeological basin, stable isotope ratios in water indicated an extra-basin recharge, likely from the elevated surrounding carbonate reliefs (e.g., Maggiore and Matese Mts.). The mineralization process, promoted by the deep CO2 flux, controls the B and Sr contents. However, their isotopic ratios did not allow discriminating between circulation in the volcanic and in the carbonate aquifers, as in the latter the isotopic composition differed from the original marine signature. Groundwater model ages ranged from ~ 30 years for the volcanic endmember to > 70 years for the deep, mineralized end-member, with longer circuits recharged at higher elevations. Overall, the results of this study were particularly relevant for mineral water exploitation. A recharge from outside the hydrogeological basin could be evidenced, especially for the more mineralized and valuable groundwater, and an active recent recharge was detected for the whole Riardo system. Both findings will contribute to the refinement of the hydrogeological model and water budget, and to a sustainable development of the resource.

Fe and As geochemical self-removal dynamics in mineral waters: evidence from the Ferrarelle groundwater system (Riardo Plain, Southern Italy).

A theoretical pattern for Fe and As co-precipitation was tested directly in a groundwater natural system. Several monitoring wells were sampled to identify the different endmembers that govern the hydrodynamics of the Ferrarelle Groundwater System in the Riardo Plain (Southern Italy). In agreement with recent investigations, we found a mix of a deep and a shallow component in different proportions, resulting in a specific chemical composition of groundwater in each well depending on the percentages of each component. The shallow component was characterized by EC ~ 430 µS/cm, Eh ~ 300 mV, Fe ~ 0.06 µmol/L and As ~ 0.01-0.12 µmol/L, while the deep component was characterized by EC ~ 3400 µS/cm, Eh ~ 170 mV, Fe ~ 140 µmol/L and As ~ 0.59 µmol/L. A general attenuation of As and Fe concentration that was not due to a simple dilution effect was observed in the mixing process. The oxidation of Fe(II) to Fe(III) produces solid precipitates which adsorb As from solution and then co-precipitate. The reactions pattern of Fe(II) oxidation and As adsorption gave a linear function between [As] and [Fe], where the angular coefficient depends on the [O2]/[H+] ratio. Chemical data obtained from our samples showed a very good agreement with this theoretical relationship. The investigated geochemical dynamics represented a natural process of attenuation of Fe and As, two undesirable elements that usually affect groundwater quality in volcanic aquifers in central-southern Italy, which are exploited to supply drinking water.

Hesitant or Not Hesitant? A Systematic Review on Global COVID-19 Vaccine Acceptance in Different Populations.

Vaccination currently appears to be the only strategy to contain the spread of COVID-19. At the same time, vaccine hesitancy (VH) could limit its efficacy and has, therefore, attracted the attention of Public Health Systems. This systematic review aimed at assessing anti-COVID-19 vaccine acceptance rates worldwide and at identifying populations more prone to vaccine hesitancy, for which specific interventions should be planned. PubMed database was searched using a purposely formulated string. One hundred out of the 9243 studies retrieved were considered pertinent and thus included in the analyses. VH rate was analyzed according to patient geographical origin, ethnicity, age, study setting, and method used for data collection; data from specific populations were separately analyzed. Overall, this study demonstrated significant differences in terms of VH in the general population and in the specific subgroups examined according to geographical, demographic factors, as well as associated comorbidities, underlining the need for purposely designed studies in specific populations from the different countries, to design targeted programs aimed at increasing awareness for confidence and complacency toward COVID-19 vaccines.

Higher 90-Day Mortality after Surgery for Hip Fractures in Patients with COVID-19: A Case-Control Study from a Single Center in Italy.

The mortality of hip fracture (HF) patients is increased by concomitant COVID-19; however, evidence is limited to only short follow-up. A retrospective matched case-control study was designed with the aim to report the 90-day mortality and determine the hazard ratio (HR) of concomitant HF and COVID-19 infection. Cases were patients hospitalized for HF and diagnosed with COVID-19. Controls were patients hospitalized for HF not meeting the criteria for COVID-19 diagnosis and were individually matched with each case through a case-control (1:3) matching algorithm. A total of 89 HF patients were treated during the study period, and 14 of them were diagnosed as COVID-19 positive (overall 15.7%). Patients' demographic, clinical, and surgical characteristics were similar between case and control groups. At 90 days after surgery, 5 deaths were registered among the 14 COVID-19 cases (35.7%) and 4 among the 42 HF controls (9.5%). COVID-19-positive cases had a higher risk of mortality at 30 days (HR = 4.51; p = 0.0490) and 90 days (HR = 4.50; p = 0.025) with respect to controls. Patients with concomitant HF and COVID-19 exhibit high perioperative mortality, which reaches a plateau of nearly 30-35% after 30 to 45 days and is stable up to 90 days. The mortality risk is more than four-fold higher in patients with COVID-19.

Predictive modeling of selected trace elements in groundwater using hybrid algorithms of iterative classifier optimizer.

Trace element (TE) pollution in groundwater resources is one of the major concerns in both developing and developed countries as it can directly affect human health. Arsenic (As), Barium (Ba), and Rubidium (Rb) can be considered as TEs naturally present in groundwater due to water-rock interactions in Campania Plain (CP) aquifers, in South Italy. Their concentration could be predicted via some readily available input variables using an algorithm like the iterative classifier optimizer (ICO) for regression, and novel hybrid algorithms with additive regression (AR-ICO), attribute selected classifier (ASC-ICO) and bagging (BA-ICO). In this regard, 244 groundwater samples were collected from water wells within the CP and analyzed with respect to the electrical conductivity, pH, major ions and selected TEs. To develop the models, the available dataset was divided randomly into two subsets for model training (70% of the dataset) and evaluation (30% of the dataset), respectively. Based on the correlation coefficient (r), different input variables combinations were constructed to find the most effective one. Each model's performance was evaluated using common statistical and visual metrics. Results indicated that the prediction of As and Ba concentrations strongly depends on HCO3-, while Na+ is the most effective variable on Rb prediction. Also, the findings showed that the most powerful predictive models were those that used all the available input variables. According to models' performance evaluation metrics, the hybrid ASC-ICO outperformed other hybrid (BA- and AR-ICO) and standalone (ICO) algorithms to predict As and Ba concentrations, while both hybrid ASC- and BA-ICO models had higher accuracy and lower error than other algorithms for Rb prediction.

Improvement in Patient Safety May Precede Policy Changes: Trends in Patient Safety Indicators in the United States, 2000-2013.

OBJECTIVES: Quality and safety improvement are global priorities. In the last two decades, the United States has introduced several payment reforms to improve patient safety. The Agency for Healthcare Research and Quality (AHRQ) developed tools to identify preventable inpatient adverse events using administrative data, patient safety indicators (PSIs). The aim of this study was to assess changes in national patient safety trends that corresponded to U.S. pay-for-performance reforms. METHODS: This is a retrospective, longitudinal analysis to estimate temporal changes in 13 AHRQ's PSIs. National inpatient sample from the AHRQ and estimates were weighted to represent a national sample. We analyzed PSI trends, Center for Medicaid and Medicare Services payment policy changes, and Inpatient Prospective Payment System regulations and notices between 2000 and 2013. RESULTS: Of the 13 PSIs studied, 10 had an overall decrease in rates and 3 had an increase. Joinpoint analysis showed that 12 of 13 PSIs had decreasing or stable trends in the last 5 years of the study. Central-line blood stream infections had the greatest annual decrease (-31.1 annual percent change between 2006 and 2013), whereas postoperative respiratory failure had the smallest decrease (-3.5 annual percent change between 2005 and 2013). With the exception of postoperative hip fracture, significant decreases in trends preceded federal payment reform initiatives. CONCLUSIONS: National in-hospital patient safety has significantly improved between 2000 and 2015, as measured by PSIs. In this study, improvements in PSI trends often proceeded policies targeting patient safety events, suggesting that intense public discourses targeting patient safety may drive national policy reforms and that these improved trends may be sustained by the Center for Medicare and Medicaid Services policies that followed.

Deep carbon degassing in the Matese massif chain (Southern Italy) inferred by geochemical and isotopic data.

The Italian Apennines are among the most important sources of freshwater for several Italian regions. With evidences of deep CO2-rich fluids intruding into aquifers in the nearby central-southern Apennines, a thorough investigation into the geochemistry of groundwater became critical to ensure the water quality in the area. Here, we show the main hydrogeochemical processes occurring in the Matese Massif (MM) aquifer through the investigation of 98 water samples collected from springs and water wells. All waters were classified as HCO3 type with Ca dominance (from 50% up to 97%) and variable amount of Mg (from 1% up to 49%). A multivariate statistical approach through the application of the factor analysis (FA) highlighted three main hydrogeochemical processes: (i) water-carbonate rock interactions mostly enhanced in peripheral areas of the MM by CO2 deep degassing; (ii) addition of NaCl-rich components linked to recharging process and to water mixing processes of the groundwater with a thermal component relatively rich in Cl, Na, and CO2; (iii) anthropogenic activities influencing groundwater composition at the foothills of MM. Furthermore, the first detailed TDIC, pCO2, and δ13C-TDIC distribution maps of the MM area have been created, which track chemical and isotopic anomalies in several peripheral areas (Pratella, Ailano, and Telese) throughout the region. These maps systematically highlight that the greater the amount of dissolved carbon occurs the heavier the C isotope enrichment, especially in the peripheral areas. Conversely, spring waters emerging at higher altitudes within MM are only slightly mineralized and associated with δ13C-TDIC values mainly characterized by recharging processes with the addition of biogenic carbon during the infiltration process through the soil.

Developing a SINTACS-based method to map groundwater multi-pollutant vulnerability using evolutionary algorithms.

In this study, the modified SINTACS method, a rating-based groundwater vulnerability approach, was applied to data from the Campanian Plain, southern Italy, to identify groundwater vulnerable areas accurately. To mitigate the subjectivity of SINTACS rating and weighting schemes, a modified SINTACS model was formulated by optimizing parameter ratings using the Wilcoxon rank-sum test, and the weight scores using the evolutionary algorithms including artificial bee colony (ABC) and genetic algorithm (GA) methods. The validity of the models was verified by analyzing the correlation coefficient between the vulnerability index and nitrate (NO3) and sulfate (SO4) concentrations found in the groundwater. The correlation coefficients between the pollutant concentrations and the relevant vulnerability index increased significantly from - 0.35 to 0.43 for NO3 and from - 0.28 to 0.33 for SO4 after modifying the ratings and weights of typical SINTACS. Besides, a multi-pollutant vulnerability map considering both NO3 and SO4 pollutants was produced by amalgamating the best calibrated vulnerability maps based on the obtained correlation values (i.e., the Wilcoxon-ABC-based SINTACS vulnerability map for NO3 and the Wilcoxon-GA-based SINTACS vulnerability map for SO4). The resultant multi-pollutant vulnerability map coincided significantly with a land use map of the study area, where anthropogenic activities represented the main sources of pollution.

The COVID-19 outbreak in Italy: perspectives from an orthopaedic hospital.

PURPOSE: Italy is one of the more severely affected countries in the world by the recent COVID-19 outbreak. The aim of this report is to describe how COVID-19 affected the life and organization of one of the main orthopaedic hospitals of the country, and which measures were implemented to face the outbreak. METHODS: A personal interview has been conducted with four doctors involved in the management of COVID-19 outbreak in one of the main orthopaedic hospitals of Italy. RESULTS: Hospital was re-organized, elective surgeries were cancelled, and only trauma surgeries were allowed, together with oncologic and urgent cases. Since the number of cases among patients and healthcare workers increased, the hospital management responded not only with a massive testing campaign aimed at detecting contact histories but also with an additional testing campaign for asymptomatic healthcare workers. CONCLUSION: The main lection is that any actions should be quick and decisive, for 1 week during the COVID-19 epidemic could make the difference.

Enhancing nitrate and strontium concentration prediction in groundwater by using new data mining algorithm.

Groundwater resources constitute the main source of clean fresh water for domestic use and it is essential for food production in the agricultural sector. Groundwater has a vital role for water supply in the Campanian Plain in Italy and hence a future sustainability of the resource is essential for the region. In the current paper novel data mining algorithms including Gaussian Process (GP) were used in a large groundwater quality database to predict nitrate (contaminant) and strontium (potential future increasing) concentrations in groundwater. The results were compared with M5P, random forest (RF) and random tree (RT) algorithms as a benchmark to test the robustness of the modeling process. The dataset includes 246 groundwater quality samples originating from different wells, municipals and agricultural. It was divided for the modeling process into two subgroups by using the 10-fold cross validation technique including 173 samples for model building (training dataset) and 73 samples for model validation (testing dataset). Different water quality variables including T, pH, EC, HCO3-, F-, Cl-, SO42-, Na+, K+, Mg2+, and Ca2+ have been used as an input to the models. At first stage, different input combinations have been constructed based on correlation coefficient and thus the optimal combination was chosen for the modeling phase. Different quantitative criteria alongside with visual comparison approach have been used for evaluating the modeling capability. Results revealed that to obtain reliable results also variables with low correlation should be considered as an input to the models together with those variables showing high correlation coefficients. According to the model evaluation criteria, GP algorithm outperforms all the other models in predicting both nitrate and strontium concentrations followed by RF, M5P and RT, respectively. Result also revealed that model's structure together with the accuracy and structure of the data can have a relevant impact on the model's results.

School Gardening Activities Aimed at Obesity Prevention Improve Body Mass Index and Waist Circumference Parameters in School-Aged Children: A Systematic Review and Meta-Analysis.

Background: Childhood obesity, due to its increasing prevalence, is one of the most challenging problems in public health and prevention. Recent strategies have been implemented to tackle this trend, including school gardening projects. This systematic review analyzes the main elements of school gardening with a specific meta-analysis about its impact on anthropometric parameters. Materials and Methods: We searched studies in PubMed, EMBASE, and Cochrane Library on school gardening projects carried out until February 2019 and addressed to children aged 6 to 13 years. Results: Thirty-three studies passed the screening selection. Outcomes analyzed were fruits and vegetables consumption/knowledge, nutritional attitudes and behavior, anthropometric outcomes (i.e., BMI, waist circumference-WC) and other outcomes (i.e., blood pressure, science achievement, and physical activity). We performed descriptive analyses of these outcomes and found a general benefit from school gardening projects. We subsequently performed a meta-analysis on anthropometric outcomes, highlighting a significant reduction of both BMI percentile (%) (-1.37%) and WC (-1.30 cm). Conclusions: Although more high-quality studies are needed on this topic, along with a greater homogeneity of anthropometric measurements, the results of our article show a modest but positive impact of school gardening projects on anthropometric measures and more generally on children's health.

Trajectory analysis for postoperative pain using electronic health records: A nonparametric method with robust linear regression and K-medians cluster analysis.

Postoperative pain scores are widely monitored and collected in the electronic health record, yet current methods fail to fully leverage the data with fast implementation. A robust linear regression was fitted to describe the association between the log-scaled pain score and time from discharge after total knee replacement. The estimated trajectories were used for a subsequent K-medians cluster analysis to categorize the longitudinal pain score patterns into distinct clusters. For each cluster, a mixture regression model estimated the association between pain score and time to discharge adjusting for confounding. The fitted regression model generated the pain trajectory pattern for given cluster. Finally, regression analyses examined the association between pain trajectories and patient outcomes. A total of 3442 surgeries were identified with a median of 22 pain scores at an academic hospital during 2009-2016. Four pain trajectory patterns were identified and one was associated with higher rates of outcomes. In conclusion, we described a novel approach with fast implementation to model patients' pain experience using electronic health records. In the era of big data science, clinical research should be learning from all available data regarding a patient's episode of care instead of focusing on the "average" patient outcomes.