Using HAQ-DI to estimate HUI-3 and EQ-5D utility values for patients with rheumatoid arthritis in Spain

AbstractBackground/ObjectiveUtility values are not usually assessed in clinical trials and do not allow cost-utility analysis to be performed with the data collected. The aim of this study was to derive relation functions so that Health Assessment Questionnaire – Disability Index (HAQ-DI) scores could be used to estimate Health Utilities Index - 3 (HUI-3) and EQ-5D utility values for patients with rheumatoid arthritis (RA).MethodsAn observational, cross-sectional, naturalistic, multicentre study was conducted. A total of 244 patients aged 18 years or older, with RA according to American College of Rheumatology diagnostic criteria, were recruited. Sociodemographic and clinical variables were recorded and patients completed three generic HRQoL questionnaires: the HAQ-DI, the HUI-3, and the EQ-5D. Two linear regression models were used to predict HUI-3 and EQ-5D utility values as functions of HAQ-DI scores, age, and gender.ResultsPatient mean age was 57.8 years old (standard deviation [SD], 13.3 years); 75.8% of the patients were women and 95.9% were white. Mean disease duration was 10.8 years (SD, 9 years). Patient distribution according to HAQ-DI severity was as follows: HAQ-DI < 0.5, 29%; 0.5 ≤ HAQ-DI < 1.1, 28%; 1.1 ≤ HAQ-DI < 1.6, 16%,1.6 ≤ HAQ-DI < 2.1, 15%; and HAQ-DI ≥ 2.1, 12%. HAQ-DI and EQ-5D mean scores were 1.02 (SD, 0.78) and 63.1 (SD, 20.3), respectively. Mean utility values for HUI-3 and time trade-off (TTO) were 0.75 (SD, 0.21) and 0.65 (SD, 0.3), respectively. The equations converting HAQ-DI scores to utilities were HUI-3 = 0.9527 – (0.2018 × HAQ-DI) +ε (R2=0.56), and TTO = 0.9567 – (0.309 × HAQ-DI) + ε (R2=0.54). Error distribution was non-normal. Age and gender were found to have no bearing on the utility functions.ConclusionsHAQ-DI scores can be used to estimate HUI-3 and EQ-5D utility values for patients with RA in data obtained from studies where utility values have not been collected

Cancro familiar - testes genéticos e estratégias

Acute liver failure is a rare disease with high mortality and liver transplantation is the only life saving therapy. Accurate prognosis of ALF is crucial for proper intervention.To identify and characterize newly developed prognostic models of mortality for ALF patients, assess study quality, identify important variables and provide recommendations for the development of improved models in the future.The online databases MEDLINE® (1950-2012) and EMBASE® (1980-2012) were searched for English-language articles that reported original data from clinical trials or observational studies on prognostic models in ALF patients. Studies were included if they developed a new model or modified existing prognostic models. The studies were evaluated based on an existing framework for scoring the methodological and reporting quality of prognostic models.Twenty studies were included, of which 18 reported on newly developed models, 1 on modification of the Kings College Criteria (KCC) and 1 on the Model for End-Stage Liver Disease (MELD). Ten studies compared the newly developed models to previously existing models (e.g. KCC); they all reported that the new models were superior. In the 12-point methodological quality score, only one study scored full points. On the 38-point reporting score, no study scored full points. There was a general lack of reporting on missing values. In addition, none of the studies used performance measures for calibration and accuracy (e.g. Hosmer-Lemeshow statistics, Brier score), and only 5 studies used the AUC as a measure of discrimination.There are many studies on prognostic models for ALF but they show methodological and reporting limitations. Future studies could be improved by better reporting and handling of missing data, the inclusion of model calibration aspects, use of absolute risk measures, explicit considerations for variable selection, the use of a more extensive set of reference models and more thorough validation

Effect of changes over time in the performance of a customized SAPS-II model on the quality of care assessment

Purpose: The aim of our study was to explore, using an innovative method, the effect of temporal changes in the mortality prediction performance of an existing model on the quality of care assessment. The prognostic model (rSAPS-II) was a recalibrated Simplified Acute Physiology Score-II model developed for very elderly Intensive Care Unit (ICU) patients. Methods: The study population comprised all 12,143 consecutive patients aged 80 years and older admitted between January 2004 and July 2009 to one of the ICUs of 21 Dutch hospitals. The prospective dataset was split into 30 equally sized consecutive subsets. Per subset, we measured the model's discrimination [area under the curve (AUC)], accuracy (Brier score), and standardized mortality ratio (SMR), both without and after repeated recalibration. All performance measures were considered to be stable if 1 without and after repeated recalibration for the year 2009. Results: For all subsets, the AUCs were stable, but the Brier scores and SMRs were not. The SMR was downtrending, achieving levels significantly below 1. Repeated recalibration rendered it stable again. The proportions of hospitals with SMR>1 and SMR <1 changed from 15 versus 85% to 35 versus 65%. Conclusions: Variability over time may markedly vary among different performance measures, and infrequent model recalibration can result in improper assessment of the quality of care in many hospitals. We stress the importance of the timely recalibration and repeated validation of prognostic models over tim

Validation of the ADFICE_IT Models for Predicting Falls and Recurrent Falls in Geriatric Outpatients

Objectives: Before being used in clinical practice, a prediction model should be tested in patients whose data were not used in model development. Previously, we developed the ADFICE_IT models for predicting any fall and recurrent falls, referred as Any_fall and Recur_fall. In this study, we externally validated the models and compared their clinical value to a practical screening strategy where patients are screened for falls history alone. Design: Retrospective, combined analysis of 2 prospective cohorts. Setting and Participants: Data were included of 1125 patients (aged ≥65 years) who visited the geriatrics department or the emergency department. Methods: We evaluated the models' discrimination using the C-statistic. Models were updated using logistic regression if calibration intercept or slope values deviated significantly from their ideal values. Decision curve analysis was applied to compare the models’ clinical value (ie, net benefit) against that of falls history for different decision thresholds. Results: During the 1-year follow-up, 428 participants (42.7%) endured 1 or more falls, and 224 participants (23.1%) endured a recurrent fall (≥2 falls). C-statistic values were 0.66 (95% CI 0.63-0.69) and 0.69 (95% CI 0.65-0.72) for the Any_fall and Recur_fall models, respectively. Any_fall overestimated the fall risk and we therefore updated only its intercept whereas Recur_fall showed good calibration and required no update. Compared with falls history, Any_fall and Recur_fall showed greater net benefit for decision thresholds of 35% to 60% and 15% to 45%, respectively.Conclusions and Implications: The models performed similarly in this data set of geriatric outpatients as in the development sample. This suggests that fall-risk assessment tools that were developed in community-dwelling older adults may perform well in geriatric outpatients. We found that in geriatric outpatients the models have greater clinical value across a wide range of decision thresholds compared with screening for falls history alone.</p

The effect of ICU-tailored drug-drug interaction alerts on medication prescribing and monitoring: Protocol for a cluster randomized stepped-wedge trial

Background: Drug-drug interactions (DDIs) can cause patient harm. Between 46 and 90% of patients admitted to the Intensive Care Unit (ICU) are exposed to potential DDIs (pDDIs). This rate is twice as high as patients on general wards. Clinical decision support systems (CDSSs) have shown their potential to prevent pDDIs. However, the literature shows that there is considerable room for improvement of CDSSs, in particular by increasing the clinical relevance of the pDDI alerts they generate and thereby reducing alert fatigue. However, consensus on which pDDIs are clinically relevant in the ICU setting is lacking. The primary aim of this study is to evaluate the effect of alerts based on only clinically relevant interactions for the ICU setting on the prevention of pDDIs among Dutch ICUs. Methods: To define the clinically relevant pDDIs, we will follow a rigorous two-step Delphi procedure in which a national expert panel will assess which pDDIs are perceived clinically relevant for the Dutch ICU setting. The intervention is the CDSS that generates alerts based on the clinically relevant pDDIs. The intervention will be evaluated in a stepped-wedge trial. A total of 12 Dutch adult ICUs using the same patient data management system, in which the CDSS will operate, were invited to participate in the trial. Of the 12 ICUs, 9 agreed to participate and will be enrolled in the trial. Our primary outcome measure is the incidence of clinically relevant pDDIs per 1000 medication administrations. Discussion: This study will identify pDDIs relevant for the ICU setting. It will also enhance our understanding of the effectiveness of alerts confined to clinically relevant pDDIs. Both of these contributions can facilitate the successful implementation of CDSSs in the ICU and in other domains as well. Trial registration: Nederlands Trial register Identifier: NL6762. Registered November 26, 2018

Hospital mortality is associated with ICU admission time

Previous studies have shown that patients admitted to the intensive care unit (ICU) after "office hours" are more likely to die. However these results have been challenged by numerous other studies. We therefore analysed this possible relationship between ICU admission time and in-hospital mortality in The Netherlands. This article relates time of ICU admission to hospital mortality for all patients who were included in the Dutch national ICU registry (National Intensive Care Evaluation, NICE) from 2002 to 2008. We defined office hours as 08:00-22:00 hours during weekdays and 09:00-18:00 hours during weekend days. The weekend was defined as from Saturday 00:00 hours until Sunday 24:00 hours. We corrected hospital mortality for illness severity at admission using Acute Physiology and Chronic Health Evaluation II (APACHE II) score, reason for admission, admission type, age and gender. A total of 149,894 patients were included in this analysis. The relative risk (RR) for mortality outside office hours was 1.059 (1.031-1.088). Mortality varied with time but was consistently higher than expected during "off hours" and lower during office hours. There was no significant difference in mortality between different weekdays of Monday to Thursday, but mortality increased slightly on Friday (RR 1.046; 1.001-1.092). During the weekend the RR was 1.103 (1.071-1.136) in comparison with the rest of the week. Hospital mortality in The Netherlands appears to be increased outside office hours and during the weekends, even when corrected for illness severity at admission. However, incomplete adjustment for certain confounders might still play an important role. Further research is needed to fully explain this differenc

Assessing Quality of Care of Elderly Patients Using the ACOVE Quality Indicator Set: A Systematic Review

Background: Care of the elderly is recognized as an increasingly important segment of health care. The Assessing Care Of Vulnerable Elderly (ACOVE) quality indicators (QIs) were developed to assess and improve the care of elderly patients. Objectives: The purpose of this review is to summarize studies that assess the quality of care using QIs from or based on ACOVE, in order to evaluate the state of quality of care for the reported conditions. Methods: We systematically searched MEDLINE, EMBASE and CINAHL for English-language studies indexed by February 2010. Articles were included if they used any ACOVE QIs, or adaptations thereof, for assessing the quality of care. Included studies were analyzed and relevant information was extracted. We summarized the results of these studies, and when possible generated an overall conclusion about the quality of care as measured by ACOVE for each condition, in various settings, and for each QI. Results: Seventeen studies were included with 278 QIs (original, adapted or newly developed). The quality scores showed large variation between and within conditions. Only a few conditions showed a stable pass rate range over multiple studies. Overall, pass rates for dementia (interquartile range (IQR): 11%-35%), depression (IQR: 27%-41%), osteoporosis (IQR: 34%-43%) and osteoarthritis (IQR: 29-41%) were notably low. Medication management and use (range: 81%-90%), hearing loss (77%-79%) and continuity of care (76%-80%) scored higher than other conditions. Out of the 278 QIs, 141 (50%) had mean pass rates below 50% and 121 QIs (44%) had pass rates above 50%. Twenty-three percent of the QIs scored above 75%, and 16% scored below 25%. Conclusions: Quality of care per condition varies markedly across studies. Although there has been much effort in improving the care for elderly patients in the last years, the reported quality of care according to the ACOVE indicators is still relatively lo

Clinically relevant potential drug-drug interactions in intensive care patients:A large retrospective observational multicenter study

Purpose: Potential drug-drug interactions (pDDIs) may harm patients admitted to the Intensive Care Unit (ICU). Due to the patient's critical condition and continuous monitoring on the ICU, not all pDDIs are clinically relevant. Clinical decision support systems (CDSSs) warning for irrelevant pDDIs could result in alert fatigue and overlooking important signals. Therefore, our aim was to describe the frequency of clinically relevant pDDIs (crpDDIs) to enable tailoring of CDSSs to the ICU setting. Materials & methods: In this multicenter retrospective observational study, we used medication administration data to identify pDDIs in ICU admissions from 13 ICUs. Clinical relevance was based on a Delphi study in which intensivists and hospital pharmacists assessed the clinical relevance of pDDIs for the ICU setting. Results: The mean number of pDDIs per 1000 medication administrations was 70.1, dropping to 31.0 when considering only crpDDIs. Of 103,871 ICU patients, 38% was exposed to a crpDDI. The most frequently occurring crpDDIs involve QT-prolonging agents, digoxin, or NSAIDs. Conclusions: Considering clinical relevance of pDDIs in the ICU setting is important, as only half of the detected pDDIs were crpDDIs. Therefore, tailoring CDSSs to the ICU may reduce alert fatigue and improve medication safety in ICU patients

Clinically relevant potential drug-drug interactions in intensive care patients: A large retrospective observational multicenter study

Purpose: Potential drug-drug interactions (pDDIs) may harm patients admitted to the Intensive Care Unit (ICU). Due to the patient's critical condition and continuous monitoring on the ICU, not all pDDIs are clinically relevant. Clinical decision support systems (CDSSs) warning for irrelevant pDDIs could result in alert fatigue and overlooking important signals. Therefore, our aim was to describe the frequency of clinically relevant pDDIs (crpDDIs) to enable tailoring of CDSSs to the ICU setting. Materials & methods: In this multicenter retrospective observational study, we used medication administration data to identify pDDIs in ICU admissions from 13 ICUs. Clinical relevance was based on a Delphi study in which intensivists and hospital pharmacists assessed the clinical relevance of pDDIs for the ICU setting. Results: The mean number of pDDIs per 1000 medication administrations was 70.1, dropping to 31.0 when considering only crpDDIs. Of 103,871 ICU patients, 38% was exposed to a crpDDI. The most frequently occurring crpDDIs involve QT-prolonging agents, digoxin, or NSAIDs. Conclusions: Considering clinical relevance of pDDIs in the ICU setting is important, as only half of the detected pDDIs were crpDDIs. Therefore, tailoring CDSSs to the ICU may reduce alert fatigue and improve medication safety in ICU patients