Risk Adjustment Tool Research Articles

Evaluating Surgeon-influenced Factors for Total Knee Arthroplasty Value-based Reimbursement.

Clinical outcome measures used under value-based reimbursement models require risk stratification of patient demographics and medical history. Only certain perioperative patient factors may be influenced by the surgeon. The study evaluated surgeon-influenced modifiable factors associated with achieving literature-defined KOOS score thresholds to serve as the foundation of the newly established alternative payment models for total knee arthroplasties (TKA). We retrospectively reviewed a consecutive cohort of 4,324 patients undergoing TKA. Surgeon-influenced modifiable risk factors included thromboprophylaxis with aspirin, tourniquet use, tranexamic acid (TXA), body mass index, smoking, alcohol or illicit drug use, surgical time, length of stay (LOS), and bilateral TKA. Outcomes included complications, 90-day readmissions, discharge disposition, knee injury and osteoarthritis outcome score (KOOS) minimal clinically important difference (MCID), KOOS patient acceptable symptom state (PASS), and short form-12 (SF-12) MCID achievement. A bivariate analysis and regression were built to determine the likelihood of primary outcomes based on modifiable factors. Bilateral TKA was associated with a higher odds ratio (OR) for home discharge (OR = 5.40, P < 0.001), KOOS MCID (OR = 2.60, P < 0.001), PASS (OR = 2.4, P ≤ 0.001), and SF-12 PCS MCID achievement (OR = 3.21, P < 0.001). Similarly, LOS was inversely associated with KOOS MCID (OR = 0.88, P = 0.002) and PASS (OR = 0.81, P < 0.001) but directly associated with home discharge (OR = 2.5, P ≤ 0.001) in-hospital complications (OR = 1.50, P < 0.001) and 90-day readmissions (OR = 1.23, P = 0.005). The KOOS MCID and PASS achievement was positively influenced by TXA (OR = 1.33, P = 0.008; OR = 1.29, P = 0.020) use and negatively influenced by aspirin use (OR = 0.68, P = 0.013; OR = 0.73, P = 0.040). In-hospital opioid use was an independent risk factor for not achieving SF-12 MCS MCID (OR = 0.56, P = 0.006). In this study, modifiable perioperative variables, such as TXA, aspirin use, opioid use, LOS, and bilateral TKA, were found to markedly increase quality metrics threshold achievement and should be considered as risk variables in the current value-based care models. Future studies should investigate the effect of modifiable risk factors on quality metrics to build new risk adjustment tools that incentivize patient perioperative optimization.

Validation of the Passive Surveillance Stroke Severity score in three Canadian provinces

ObjectiveAdjusting for stroke severity is critical in stroke outcomes research. The Passive Surveillance Stroke SeVerity (PaSSV) score is an administrative data-based measure of stroke severity, initially derived in Ontario, Canada using data between 2002-2013. We assessed its geographical and temporal external validity in British Columbia (BC), Nova Scotia (NS), and Ontario, Canada. MethodsIn each province, we identified adult in-patients with ischemic stroke or intracerebral hemorrhage and admitted from an emergency department between 2014-2019 and calculated their PaSSV score using linked administrative data. We used Cox proportional hazards models to evaluate the association between the PaSSV score and the hazard of death over 30 days and the cause-specific hazard of admission to long-term care over 365 days. We assessed the models’ discriminative values using Uno’s c-statistic, comparing models with versus without PaSSV. ResultsWe included 86,142 patients (n=18,387 in BC, n=65,082 in Ontario, n=2,673 in NS). The mean and median PaSSV were similar across provinces. Higher PaSSV score, reflecting lower stroke severity, was associated with a lower mortality (hazard ratio and 95% confidence intervals 0.70 [0.68-0.71] in BC, 0.69 [0.68-0.69] in Ontario, 0.72 [0.68-0.75] in NS) and long-term care admission (0.77 [0.76-0.79] in BC, 0.84 [0.83-0.85] in Ontario, 0.86 [0.79-0.93] in NS). Including PaSSV in the multivariable models improved model fit according to the c-statistics. ConclusionWe showed that PaSSV has geographical and temporal validity. It is a useful tool for risk-adjustment in multi-jurisdiction stroke outcomes research, and a valuable addition to be included in the national algorithm inventory.

Comparison Between Mortality Scoring Systems in Pediatric Intensive Care Unit Reliability and Effectiveness

Purpose: In pediatric intensive care unit (PICU), high mortality risk is a significant issue. Risk adjustment tools are in place for early estimation of mortality risk. Pediatric Risk of Mortality(PRISM), Pediatric Index of Mortality(PIM), Pediatric Logistic Organ Dysfunction(PELOD) and Pediatric Sequential Organ Failure Assessment(PSOFA) are commonly used. The aim of this study was to evaluate the predictive performance of mortality using PRISM III, PIM3, PELOD-2, and PSOFA. Materials and Methods: This retrospective single-center study analysed patients aged between 1month-18years who were treated in PICU for various diseases between April and December2021. Their electronic records were retrospectively examined for demographic characteristics, medical and clinical expectations, and morbidity/mortality. Results: The study included 300 patients with a hospitalization period of 56.73±105.95 days. At the end of the study, 56(18.7%) patients had died.All scoring systems and mortality correlations were statistically significant(p

Development and validation of a prognostic index for mental health and substance use disorder burden

ObjectiveTo develop an accessible index which quantifies MHSUD burden among patients of Veterans Affairs hospitals. MethodWe used 21 disorder categories provided by the diagnostic and statistical manual (DSM) to characterize diagnoses among primary care (PC) patients. For each patient, we generated counts of unique disorder categories present during the PC encounter or in the year prior. We used these counts to generate multiple indexes, which we compared in a 60% training sample of our population. Using model fit statistics generated from ordered multinomial logistic regressions, we identified the subset of DSM categories which, structured as index, were most predictive of MHSUD hospitalization and death. We validated and fine-tuned the form of the selected index in the full population using measures of calibration and discrimination. ResultsIn model development, the index (I-6) which best fit the data (R2 = 0.191) included the following six disorder categories: substance use, depressive, psychotic, bipolar, trauma, and personality. When applied in the full population and weighted by disorder severity, this index demonstrated good predictive discrimination for MHSUD death (C = 0.66) and hospitalization (C = 0.88) and was well calibrated in comparisons of observed versus predicted outcomes. ConclusionsWe recommend the I-6 as a parsimonious and effective tool for MHSUD burden risk adjustment.

Effect of emergency general surgery on postoperative performance status in patients aged over 90 years

BackgroundFunctional deterioration following emergency general surgery (EGS) poses a significant challenge in super-elderly patients. However, limited research has focused on assessing the deterioration in postoperative performance status (PS). This study aimed to investigate the impact of EGS on PS deterioration in super-elderly patients, and the extent to which deteriorated PS is recovered. MethodsThis historical cohort study comprised 77 super-elderly patients who underwent EGS between July 2015 and December 2020. Functional deterioration was evaluated by comparing preoperative and postoperative Eastern Cooperative Oncology Group Performance Status (ECOG-PS). The Emergency Surgical Score (ESS) was used as a risk-adjustment tool. Questionnaires were mailed to the patients and their families to assess post-discharge PS and obtain their impressions of EGS. ResultsPostoperative PS deteriorated in 35/77 patients (45.5 %). Significant differences were observed between the groups in terms of sex, serum C-reactive protein (CRP) levels, ESS scores, preoperative ECOG-PS, duration of operation, and major complications. Multivariate analysis of preoperative factors showed that ESS ≥7 (OR: 3.7, 95 % CI: 1.0–13), preoperative ECOG-PS ≤2 (OR: 5.9, 95 % CI: 1.7–21), and female sex (OR: 5.8, 95 % CI: 1.6–21) were associated with postoperative ECOG-PS deterioration. According to the questionnaire results, PS recovery post-discharge was observed in 6/36 (17 %) patients, and 34/36 (94 %) patients and their families expressed positive impressions of EGS. ConclusionsEGS in super-elderly patients highly caused a deterioration in their PS, particularly in patients with maintained preoperative PS. PS hardly recovered; however, most patients and their families had positive impressions of the EGS. Key messageWe assessed the pre- and postoperative performance status of super-elderly patients who underwent emergency general surgery. Surgery caused a marked deterioration in patients' functional performance, which seldom recovered postoperatively.

Principles to Inform Risk Adjustment Policy

This Viewpoint discusses the benefits and drawbacks of current risk adjustment tools, outlines the pressures clinicians may face to use these tools, and proposes principles and policy solutions to ensure that risk adjustment is clinically meaningful and to minimize gaming and waste.

Prediction of In-hospital Mortality Among Intensive Care Unit Patients Using Modified Daily Laboratory-based Acute Physiology Score, Version 2.

Mortality prediction for intensive care unit (ICU) patients frequently relies on single ICU admission acuity measures without accounting for subsequent clinical changes. Evaluate novel models incorporating modified admission and daily, time-updating Laboratory-based Acute Physiology Score, version 2 (LAPS2) to predict in-hospital mortality among ICU patients. Retrospective cohort study. ICU patients in 5 hospitals from October 2017 through September 2019. We used logistic regression, penalized logistic regression, and random forest models to predict in-hospital mortality within 30 days of ICU admission using admission LAPS2 alone in patient-level and patient-day-level models, or admission and daily LAPS2 at the patient-day level. Multivariable models included patient and admission characteristics. We performed internal-external validation using 4 hospitals for training and the fifth for validation, repeating analyses for each hospital as the validation set. We assessed performance using scaled Brier scores (SBS), c -statistics, and calibration plots. The cohort included 13,993 patients and 107,699 ICU days. Across validation hospitals, patient-day-level models including daily LAPS2 (SBS: 0.119-0.235; c -statistic: 0.772-0.878) consistently outperformed models with admission LAPS2 alone in patient-level (SBS: 0.109-0.175; c -statistic: 0.768-0.867) and patient-day-level (SBS: 0.064-0.153; c -statistic: 0.714-0.861) models. Across all predicted mortalities, daily models were better calibrated than models with admission LAPS2 alone. Patient-day-level models incorporating daily, time-updating LAPS2 to predict mortality among an ICU population performs as well or better than models incorporating modified admission LAPS2 alone. The use of daily LAPS2 may offer an improved tool for clinical prognostication and risk adjustment in research in this population.

Performance assessment of medical service for organ transplant department based on diagnosis-related groups: A programme incorporating ischemia-free liver transplantation in China.

In July 2017, the first affiliated hospital of Sun Yat-sen university carried out the world's first case of ischemia-free liver transplantation (IFLT). This study aimed to evaluate the performance of medical services pre- and post-IFLT implementation in the organ transplant department of this hospital based on diagnosis-related groups, so as to provide a data basis for the clinical practice of the organ transplant specialty. The first pages of medical records of inpatients in the organ transplant department from 2016 to 2019 were collected. The China version Diagnosis-related groups (DRGs) were used as a risk adjustment tool to compare the income structure, service availability, service efficiency and service safety of the organ transplant department between the pre- and post-IFLT implementation periods. Income structure of the organ transplant department was more optimized in the post-IFLT period compared with that in the pre-IFLT period. Medical service performance parameters of the organ transplant department in the post-IFLT period were better than those in the pre-IFLT period. Specifically, case mix index values were 2.65 and 2.89 in the pre- and post-IFLT periods, respectively (p = 0.173). Proportions of organ transplantation cases were 14.16 and 18.27%, respectively (p < 0.001). Compared with that in the pre-IFLT period, the average postoperative hospital stay of liver transplants decreased by 11.40% (30.17 vs. 26.73 days, p = 0.006), and the average postoperative hospital stay of renal transplants decreased by 7.61% (25.23 vs.23.31 days, p = 0.092). Cost efficiency index decreased significantly compared with that in the pre-IFLT period (p < 0.001), while time efficiency index fluctuated around 0.83 in the pre- and post-IFLT periods (p = 0.725). Moreover, the average postoperative hospital stay of IFLT cases was significantly shorter than that of conventional liver transplant cases (p = 0.001). The application of IFLT technology could contribute to improving the medical service performance of the organ transplant department. Meanwhile, the DRGs tool may help transplant departments to coordinate the future delivery planning of medical service.

Evaluation of timeliness and models of transporting critically ill children for intensive care: the DEPICT mixed-methods study

Background Centralisation of paediatric intensive care has increased the need for specialist critical care transport teams to transfer sick children from general hospitals to tertiary centres. National audit data show variation in how quickly transport teams reach the patient’s bedside and in the models of care provided during transport; however, the impact of this variation on clinical outcomes and the experience of patients, families and clinicians is unknown. Objectives We aimed to understand if and how clinical outcomes and experience of children transported for intensive care are affected by timeliness of access to a transport team and different models of transport care. Methods We used a mixed-methods approach with a convergent triangulation study design. There were four study workstreams: a retrospective analysis of linked national clinical audit data (2014–16) (workstream A), a prospective questionnaire study to collect experience data from parents of transported children and qualitative analysis of interviews with patients, families and clinicians (workstream B), health economic evaluation of paediatric transport services (workstream C) and mathematical modelling evaluating the potential impact of alternative service configurations (workstream D). Results Transport data from over 9000 children were analysed in workstream A. Transport teams reached the patient bedside within 3 hours of accepting the referral in &gt; 85% of transports, and there was no apparent association between time to bedside and 30-day mortality. Similarly, the grade of the transport team leader or stabilisation approach did not appear to affect mortality. Patient-related critical incidents were associated with higher mortality (adjusted odds ratio 3.07, 95% confidence interval 1.48 to 6.35). In workstream B, 2133 parents completed experience questionnaires pertaining to 2084 unique transports of 1998 children. Interviews were conducted with 30 parents and 48 staff. Regardless of the actual time to bedside, parent satisfaction was higher when parents were kept informed about the team’s arrival time and when their expectation matched the actual arrival time. Satisfaction was lower when parents were unsure who the team leader was or when they were not told who the team leader was. Staff confidence, rather than seniority, and the choice for parents to travel with their child in the ambulance were identified as key factors associated with a positive experience. The health economic evaluation found that team composition was variable between transport teams, but not significantly associated with cost and outcome measures. Modelling showed marginal benefit in changing current transport team locations, some benefit in reallocating existing teams and suggested where additional transport teams could be allocated in winter to cope with the expected surge in demand. Limitations Our analysis plans were limited by the impact of the pandemic. Unmeasured confounding may have affected workstream A findings. Conclusions There is no evidence that reducing the current 3-hour time-to-bedside target for transport teams will improve patient outcomes, although timeliness is an important consideration for parents and staff. Improving communication during transport and providing parents the choice to travel in the ambulance with their child are two key service changes to enhance patient/family experience. Future work More research is needed to develop suitable risk-adjustment tools for paediatric transport and to validate the short patient-related experience measure developed in this study. Trial registration This trial is registered as ClinicalTrials.gov NCT03520192. Funding This project was funded by the National Institute for Health and Care Research (NIHR) Health and Social Care Delivery Research programme and will be published in full in Health and Social Care Delivery Research; Vol. 10, No. 34. See the NIHR Journals Library website for further project information.

External Validation of the Passive Surveillance Stroke Severity Indicator.

The Passive Surveillance Stroke Severity (PaSSV) Indicator was derived to estimate stroke severity from variables in administrative datasets but has not been externally validated. We used linked administrative datasets to identify patients with first hospitalization for acute stroke between 2007-2018 in Alberta, Canada. We used the PaSSV indicator to estimate stroke severity. We used Cox proportional hazard models and evaluated the change in hazard ratios and model discrimination for 30-day and 1-year case fatality with and without PaSSV. Similar comparisons were made for 90-day home time thresholds using logistic regression. We also linked with a clinical registry to obtain National Institutes of Health Stroke Scale (NIHSS) and compared estimates from models without stroke severity, with PaSSV, and with NIHSS. There were 28,672 patients with acute stroke in the full sample. In comparison to no stroke severity, addition of PaSSV to the 30-day case fatality models resulted in improvement in model discrimination (C-statistic 0.72 [95%CI 0.71-0.73] to 0.80 [0.79-0.80]). After adjustment for PaSSV, admission to a comprehensive stroke center was associated with lower 30-day case fatality (adjusted hazard ratio changed from 1.03 [0.96-1.10] to 0.72 [0.67-0.77]). In the registry sample (N = 1328), model discrimination for 30-day case fatality improved with the inclusion of stroke severity. Results were similar for 1-year case fatality and home time outcomes. Addition of PaSSV improved model discrimination for case fatality and home time outcomes. The validity of PASSV in two Canadian provinces suggests that it is a useful tool for baseline risk adjustment in acute stroke.

Efficacy of POSSUM for risk adjusted surgical audit of patients undergoing emergency laparotomy

Background: The physiological and operative severity score for the enumeration of mortality and morbidity (POSSUM) is extensively used to predict mortality and morbidity in various surgical procedures and good tool for comparison and risk adjustment. This study was designed to assess the efficacy of POSSUM scoring system by comparing expected and observed rates of morbidity and mortality in cases undergoing emergency laparotomy Methods: A resource of 114 cases undergoing emergency laparotomy within 24 hours of admission at Government Medical College and Hospital, Nizamabad were recruited. The details of physiological variables and intraoperative variables of consented participants were recorded. The POSSUM score was used to predict morbidity and mortality rate. Results: Among the observed cases, 80.48% had no morbidity. Among the predicted cases, 85.96% of cases may expect morbidity. Among the death, 69.23% was observed as mortality. The overall expected mortality in observed and predicted cases was 94.73%. There is no statistical significance in the morbidity (chi-square value - 7.252, p=0.443) and mortality (chi-square value - 1.357, p=0.129). Conclusion: The POSSUM is important and most reliable for predicting postoperative mortality and morbidity in cases undergoing emergency laparotomy.

Improvement of APACHE II score system for disease severity based on XGBoost algorithm

BackgroundPrognostication is an essential tool for risk adjustment and decision making in the intensive care units (ICUs). In order to improve patient outcomes, we have been trying to develop a more effective model than Acute Physiology and Chronic Health Evaluation (APACHE) II to measure the severity of the patients in ICUs. The aim of the present study was to provide a mortality prediction model for ICUs patients, and to assess its performance relative to prediction based on the APACHE II scoring system.MethodsWe used the Medical Information Mart for Intensive Care version III (MIMIC-III) database to build our model. After comparing the APACHE II with 6 typical machine learning (ML) methods, the best performing model was screened for external validation on anther independent dataset. Performance measures were calculated using cross-validation to avoid making biased assessments. The primary outcome was hospital mortality. Finally, we used TreeSHAP algorithm to explain the variable relationships in the extreme gradient boosting algorithm (XGBoost) model.ResultsWe picked out 14 variables with 24,777 cases to form our basic data set. When the variables were the same as those contained in the APACHE II, the accuracy of XGBoost (accuracy: 0.858) was higher than that of APACHE II (accuracy: 0.742) and other algorithms. In addition, it exhibited better calibration properties than other methods, the result in the area under the ROC curve (AUC: 0.76). we then expand the variable set by adding five new variables to improve the performance of our model. The accuracy, precision, recall, F1, and AUC of the XGBoost model increased, and were still higher than other models (0.866, 0.853, 0.870, 0.845, and 0.81, respectively). On the external validation dataset, the AUC was 0.79 and calibration properties were good.ConclusionsAs compared to conventional severity scores APACHE II, our XGBoost proposal offers improved performance for predicting hospital mortality in ICUs patients. Furthermore, the TreeSHAP can help to enhance the understanding of our model by providing detailed insights into the impact of different features on the disease risk. In sum, our model could help clinicians determine prognosis and improve patient outcomes.

Performance evaluation of medical service for breast cancer patients based on diagnosis related groups

BackgroundTo evaluate the performance of medical service for patients with breast cancer in Henan Province, China, using diagnosis related groups (DRGs) indicators and to provide data to inform practices and policies for the prevention and control of breast cancer.MethodsThe data were collected from the front pages of medical records (FPMR) of all hospitals above class II that admitted breast cancer patients in Henan Province between 2016 and 2019. Breast cancer patients were the subjects in our study. China DRGs (CN-DRGs) was used as a risk adjustment tool. Three indicators, including the case mix index (CMI), number of DRGs, and total weight, were used to evaluate the range of available services for patients with breast cancer, while indicators including the charge efficiency index (CEI), time efficiency index (TEI) and inpatient mortality of low-risk group cases (IMLRG) were used to evaluate medical service efficiency and medical safety.ResultsBetween 2016 and 2019, there were 103,760 patients with breast cancer. The total weight increased over the study period at an average annual rate of 21.71%. The TEI decreased over the study period by 15.60%. The CEI exhibited an increasing trend, but the average annual rate of increase was small (2.94%). The IMLRP was 0.02, 0, 0 and 0.01% in 2016, 2017, 2018 and 2019, respectively.ConclusionThe performance of medical service improved between 2016 and 2019 for breast cancer patients discharged from study hospitals in Henan Province. The main area of improvement was in the range of available services, but medical institutions must still make efforts to improve the efficiency of medical services and ensure medical safety. DRGs is an effective evaluation tool.

The association of acute kidney injury with hospital readmission and death after pediatric cardiac surgery.

BackgroundAcute kidney injury (AKI) in children undergoing cardiac surgery (CS) is strongly associated with increased hospital mortality and length of stay. The association of AKI with postdischarge outcomes is unclear. We evaluated the association of AKI with all-cause readmissions and death within 30 days and 1 year of CS discharge.MethodsThis was a prospective, 3-center cohort study of children after CS with cardiopulmonary bypass. The primary exposures were postoperative ≥stage 1 AKI and ≥stage 2 AKI defined by Kidney Disease: Improving Global Outcomes AKI definition. Two separate outcomes were hospital readmission and death within 30 days and 1 year of discharge. Association of AKI with time to outcomes was determined using multivariable Cox-proportional hazards analysis. Age, The Society of Thoracic Surgeons-European Association for Cardio-Thoracic Surgery risk adjustment tool score ≥3, cardiopulmonary bypass >120 minutes, and cyanotic heart disease were evaluated as effect modifiers.ResultsOf 402 participants included (median age 1.8 years [interquartile range 0.4, 5.2]), 32 (8.0%) and 109 (27.1%) were readmitted; 7 (1.7%) and 9 (2.2%) died within 30 days and 1 year of CS, respectively. AKI was not associated with readmission at 30 days or 1 year postdischarge. ≥Stage 2 AKI (adjusted hazard ratio, 11.68 [1.88, 72.61]) was associated with mortality 30 days post-CS.ConclusionsPostoperative AKI was not associated with readmission at 30 days and 1-year postdischarge. However, more severe AKI (≥stage 2) appears to be associated with increased morality risk at 30 days post-CS.

Association Between Physician Risk Assessment, Hierarchical Condition Categories, and Utilization of Medical Services.

Hierarchical Condition Categories (HCCs) are a common risk adjustment tool that may support alignment of care management resources with the clinical needs of a population. The authors examined the association between HCC scores and physician-determined clinical risk (CR) scores, annual charges, and utilization of medical care. CR score was defined as the anticipated risk for "ED or a hospital admission" within the following year. For each of the top 50 high-risk patients identified by total HCC score, the patient's primary care physician (PCP) entered a CR score based on their judgement. A total of 128 PCPs entered scores on 6167 patients of all ages across 31 primary care practices in the Finger Lakes Region of New York. Multiple correlation between HCC scores and physician CR scores was 44.0% (P < 0.001); only 18.5% of PCPs had a correlation >60%. There was a positive association between CR score and charges (slope 19.7K; P < 0.001) and between HCC score and charges (slope 25.7K; P < 0.001). Both HCC and CR scores were positively correlated (P < 0.001) with medical/surgical admissions, emergency department (ED) visits, and utilization of advanced imaging. Across a broad range of patients, HCC scores had a moderate-to-weak correlation with physician-determined CR scores for patients' risk of an ED visit or hospital admission. Both CR scores and HCCs scores were positively associated with charges and utilization. HCCs may assist in the allocation of health resources, but the relatively weak correlation with physician-determined CR scores warrants caution.

PIT6 DISCRIMINATIVE ABILITY OF NEW INJURY SEVERITY SCORE TO PREDICT OUTCOMES AFTER FRACTURE REPAIRED SURGERY

New injury severity score (NISS) is the simple sum squares of the three most severe injuries (highest abbreviated injury scales) regardless of body region. It is shown to be predictive of survival after injury. Elixhauser comorbidity index (ECI) have been used as risk-adjustment tools in quality and safety data. This study aims to investigate whether NISS should be included in addition to ECI for postoperative outcomes prediction following fracture repair surgery.

&lt;p&gt;Performance of Comprehensive Risk Adjustment for the Prediction of In-Hospital Events Using Administrative Healthcare Data: The Queralt Indices&lt;/p&gt;

BackgroundAccurate risk adjustment is crucial for healthcare management and benchmarking.PurposeWe aimed to compare the performance of classic comorbidity functions (Charlson’s and Elixhauser’s), of the All Patients Refined Diagnosis Related Groups (APR-DRG), and of the Queralt Indices, a family of novel, comprehensive comorbidity indices for the prediction of key clinical outcomes in hospitalized patients.Material and MethodsWe conducted an observational, retrospective cohort study using administrative healthcare data from 156,459 hospital discharges in Catalonia (Spain) during 2018. Study outcomes were in-hospital death, long hospital stay, and intensive care unit (ICU) stay. We evaluated the performance of the following indices: Charlson’s and Elixhauser’s functions, Queralt’s Index for secondary hospital discharge diagnoses (Queralt DxS), the overall Queralt’s Index, which includes pre-existing comorbidities, in-hospital complications, and principal discharge diagnosis (Queralt Dx), and the APR-DRG. Discriminative ability was evaluated using the area under the curve (AUC), and measures of goodness of fit were also computed. Subgroup analyses were conducted by principal discharge diagnosis, by age, and type of admission.ResultsQueralt DxS provided relevant risk adjustment information in a larger number of patients compared to Charlson’s and Elixhauser’s functions, and outperformed both for the prediction of the 3 study outcomes. Queralt Dx also outperformed Charlson’s and Elixhauser’s indices, and yielded superior predictive ability and goodness of fit compared to APR-DRG (AUC for in-hospital death 0.95 for Queralt Dx, 0.77–0.93 for all other indices; for ICU stay 0.84 for Queralt Dx, 0.73–0.83 for all other indices). The performance of Queralt DxS was at least as good as that of the APR-DRG in most principal discharge diagnosis subgroups.ConclusionOur findings suggest that risk adjustment should go beyond pre-existing comorbidities and include principal discharge diagnoses and in-hospital complications. Validation of comprehensive risk adjustment tools such as the Queralt indices in other settings is needed.

Evaluation of physiological and operative severity score for enumeration of mortality and morbidity and Portsmouth modification of possum scores in patients with hollow viscus perforation

Background: The physiological and operative severity score for the enumeration of mortality and morbidity (POSSUM) is widely used to predict the morbidity and mortality in a variety of surgical settings and provides a tool for risk adjustment and comparison. The aim of this study was to assess the predicting morbidity and mortality in hollow viscus perforation by applying POSSUM and Portsmouth modification of POSSUM scores. Methods: This study was a prospective study conducted on 33 patients admitted in the Department of General Surgery, Chalmeda Anand Rao Institute of Medical Sciences, Karimnagar, from September 2016 to August 2017, and present detailed records of the parameters under evaluation of patients admitted to surgical wards with the clinical diagnosis of hollow viscus perforation (gastric/duodenal/ileal perforation). Results: During the present study period, a total of 136 patients were operated on small bowel, and of these 33 cases fulfilled all the criteria and were selected for this study. The overall mortality in this study was 6 (18.18% of the study), while the morbidity was noted in 17 cases (51% of study). Mortality rates differed with POSSUM scores over predicting the mortality. On applying POSSUM, using exponential analysis, we found that the expected number of deaths for our study group is 10 (O:E = 1.66). Conclusion: On applying POSSUM using the exponential analysis, we found that the expected number of deaths for our study group is 10 (O:E = 1.66). We found the difference between expected and observed mortality rates using the exponential analysis.

The applicability of methods for assessing comorbidities: The Cumulative Illness Rating Scale (CIRS)

Abstract Introduction It is essential to compare the results of medical care in patients suffering from multiple, and complex diseases. CIRS is a risk adjustment tool useful for assessing patients’ comorbidities although it needs to be used with precision following guidelines. The aim of this research is to assess whether organised seminars, planned to motivate the clinicians for correct data compilation, have an effect on the concordance of scores on the CIRS scores. Methods A prospective, pilot study started in November 2018 on a sample of 49 patients admitted to a private clinic between December 2018 and February 2019. In the context of a seminar, an Resident Physician in Public Health (RP), distributed and explained the CIRS guidelines to the clinicians. CIRS scores were then calculated by the ward physicians and compared with those of the RP who successively analysed the same medical records. The inter-rater agreement was calculated through Cohen’s kappa coefficient (κ), using Stata 14.2. Results Concordance was excellent or almost perfect or substantial for 8 out of 14 categories: heart disease (k = 0.82), genitourinary disease (k = 0.90) blood pressure category (p = 0.72), sense organs (k = 0.75), upper gastrointestinal system (k = 0.70), lower gastrointestinal system (k = 0.76), musculoskeletal system and skin (k = 0.66), central nervous system (k = 0.69), endocrine system and breast (k = 0.63) and psychiatric diseases (k = 0.63). The agreement was moderate for the respiratory system (k = 0.48) and for the liver (k = 0.57), and was fair for Severity Index, Comorbidity Index and the vascular system (k = 0.24, k = 0.38 and k = 0.28 respectively).No Concordance in renal diseases (k = 0.00). Conclusions Overall, the agreement of the scores between RP and clinicians was good, and it was possible to analyse the main weaknesses and difficulties of the clinicians. Subsequent seminars will be done to increase over time the concordance of the surveys. Key messages Organized seminars, planned to motivate clinicians to correctly compile the CIRS scores, were effective. The inter-rater agreement was good. Subsequent seminars will be done to increase over time the concordance of the surveys.

Risk Adjustment for Sepsis Mortality to Facilitate Hospital Comparisons Using Centers for Disease Control and Prevention's Adult Sepsis Event Criteria and Routine Electronic Clinical Data.

Retrospective cohort study. One hundred thirty-six U.S. hospitals in Cerner HealthFacts (derivation dataset) and 137 HCA Healthcare hospitals (validation dataset). A total of 95,154 hospitalized adult patients (derivation) and 201,997 patients (validation) meeting Centers for Disease Control and Prevention Adult Sepsis Event criteria. None. We created logistic regression models of increasing complexity using administrative and electronic health record data to predict in-hospital mortality. An administrative model using demographics, comorbidities, and coded markers of severity of illness at admission achieved an area under the receiver operating curve of 0.776 (95% CI, 0.770-0.783) in the Cerner cohort, with diminishing calibration at higher baseline risk deciles. An electronic health record-based model that integrated administrative data with laboratory results, vasopressors, and mechanical ventilation achieved an area under the receiver operating curve of 0.826 (95% CI, 0.820-0.831) in the derivation cohort and 0.827 (95% CI, 0.824-0.829) in the validation cohort, with better calibration than the administrative model. Adding vital signs and Glasgow Coma Score minimally improved performance. Models incorporating electronic health record data accurately predict hospital mortality for patients with Adult Sepsis Events and outperform models using administrative data alone. Utilizing laboratory test results, vasopressors, and mechanical ventilation without vital signs may achieve a good balance between data collection needs and model performance, but electronic health record-based models must be attentive to potential variability in data quality and availability. With ongoing testing and refinement of these risk-adjustment models, Adult Sepsis Event surveillance may enable more meaningful comparisons of hospital sepsis outcomes and provide an important window into quality of care.