Youran Fan

A new Elixhauser-based comorbidity summary measure to predict in-hospital mortality.

Background:Recently, van Walraven developed a weighted summary score (VW) based on the 30 comorbidities from the Elixhauser comorbidity system. One of the 30 comorbidities, cardiac arrhythmia, is currently excluded as a comorbidity indicator in administrative datasets such as the Nationwide Inpatient Sample (NIS), prompting us to examine the validity of the VW score and its use in the NIS. Methods:Using data from the 2009 Maryland State Inpatient Database, we derived weighted summary scores to predict in-hospital mortality based on the full (30) and reduced (29) set of comorbidities and compared model performance of these and other comorbidity summaries in 2009 NIS data. Results:Weights of our derived scores were not sensitive to the exclusion of cardiac arrhythmia. When applied to NIS data, models containing derived summary scores performed nearly identically (c statistics for 30 and 29 variable-derived summary scores: 0.804 and 0.802, respectively) to the model using all 29 comorbidity indicators (c=0.809), and slightly better than the VW score (c=0.793). Each of these models performed substantially better than those based on a simple count of Elixhauser comorbidities (c=0.745) or a categorized count (0, 1, 2, or ≥3 comorbidities; c=0.737). Conclusions:The VW score and our derived scores are valid in the NIS and are statistically superior to summaries using simple comorbidity counts. Researchers wishing to summarize the Elixhauser comorbidities with a single value should use the VW score or those derived in this study.

The PROMIS physical function scale: A promising scale for use in patients with ischemic stroke

Objective: To evaluate the performance of the Patient Reported Outcomes Measurement Information System (PROMIS) physical function (PF) scale compared to the validated Stroke Impact Scale–16 (SIS-16) in ischemic stroke patients seen in an ambulatory cerebrovascular clinic. Methods: This was a retrospective cohort study. PROMIS PF (computer adaptive testing version) and SIS-16 measures were electronically collected on 1,946 ischemic stroke patients seen in a cerebrovascular clinic using an electronic platform from September 12, 2012, to June 16, 2015. Distribution of scores was compared to assess ceiling and floor effects. Correlations with other commonly used functional status scales were performed to assess convergent validity. Results: The SIS-16 and PROMIS PF had a 19.6% and <1% ceiling effect, respectively. Patients completed 16 SIS-16 items and a median of 4 (interquartile range 4–4) PROMIS PF items. Internal consistency of both SIS-16 and PROMIS PF was excellent. The SIS-16 had slightly but significantly higher correlations with the other functional scales than PROMIS PF. Conclusions: The use of PROMIS to obtain electronic patient-reported functional status in an ambulatory setting is feasible. PROMIS PF is an option for measurement of physical function in ischemic stroke patients. It had similar test characteristics as the SIS-16 but with lower patient burden and minimal ceiling effect.

The Challenges of Data Quality Evaluation in a Joint Data Warehouse.

Introduction: The use of clinically derived data from electronic health records (EHRs) and other electronic clinical systems can greatly facilitate clinical research as well as operational and quality initiatives. One approach for making these data available is to incorporate data from different sources into a joint data warehouse. When using such a data warehouse, it is important to understand the quality of the data. The primary objective of this study was to determine the completeness and concordance of common types of clinical data available in the Knowledge Program (KP) joint data warehouse, which contains feeds from several electronic systems including the EHR. Methods: A manual review was performed of specific data elements for 250 patients from an EHR, and these were compared with corresponding elements in the KP data warehouse. Completeness and concordance were calculated for five categories of data including demographics, vital signs, laboratory results, diagnoses, and medications. Results: In general, data elements for demographics, vital signs, diagnoses, and laboratory results were present in more cases in the source EHR compared to the KP. When data elements were available in both sources, there was a high concordance. In contrast, the KP data warehouse documented a higher prevalence of deaths and medications compared to the EHR. Discussion: Several factors contributed to the discrepancies between data in the KP and the EHR—including the start date and frequency of data feeds updates into the KP, inability to transfer data located in nonstructured formats (e.g., free text or scanned documents), as well as incomplete and missing data variables in the source EHR. Conclusion: When evaluating the quality of a data warehouse with multiple data sources, assessing completeness and concordance between data set and source data may be better than designating one to be a gold standard. This will allow the user to optimize the method and timing of data transfer in order to capture data with better accuracy.

Scale Linking to Enable Patient-Reported Outcome Performance Measures Assessed with Different Patient-Reported Outcome Measures

BACKGROUND Patient-reported outcome performance measures (PRO-PMs) incorporate outcomes from the patients perspective into performance measures and may have great potential to impact health care. The various patient-reported outcome measures (PROMs) used to assess the same outcome challenge widespread use of PRO-PMs. A potential solution is to statistically link PROMs to provide equivalent PRO-PM conclusions to be drawn regardless of which PROM was used. OBJECTIVES To determine the level of agreement in the performance of two depression-related PRO-PMs assessed using the nine-item Patient Health Questionnaire (PHQ-9) depression scale and the eight-item Patient-Reported Outcomes Measurement Information System (PROMIS) Depression short form and the PHQ-9 cocalibrated on the PROMIS metric. METHODS We conducted a retrospective cohort study of patients who visited one of eight ambulatory neurological and psychiatric clinics at the Cleveland Clinic between January 23 and June 15, 2012, and who completed both the PHQ-9 and PROMIS Depression scales at the same visit. The level of agreement was measured between PRO-PM performance assessed with standard scoring of the PHQ-9, the PROMIS cocalibrated scoring of the PHQ-9, and the PROMIS score for two depression-related PRO-PMs. RESULTS Of the 5736 enrolled patients, 701 had PROMs from two or more visits. Differences in performance of the depression remission PRO-PM ranged from 0.4% to 2.1%, and differences in the progress toward remission PRO-PM ranged from 0.9% to 5.1%, depending on which depression score was used. CONCLUSIONS There was a high level of agreement in the PRO-PM for depression when incorporating different PROMs. These findings support the ability to use linkage of scale scores to assess performance of PRO-PMs with different PROMs.

Prevalence and Predictors of Depression Among Patients With Epilepsy, Stroke, and Multiple Sclerosis Using the Cleveland Clinic Knowledge Program Within the Neurological Institute

BACKGROUND Neurological conditions carry a high risk of depression. Given this risk, the Neurological Institute (NI) at Cleveland Clinic has initiated systematic screening for depression using the 9-item Patient Health Questionnaire-9 (PHQ-9) embedded within its electronic medical record and its data capture system, the Knowledge Program (KP)1. OBJECTIVE We sought to (1) estimate the prevalence of depression among patients with epilepsy, stroke, and multiple sclerosis (MS); (2) identify risk factors for depression within each disease; and (3) determine differential risks and predictors across neurological disorders. METHODS The KP1 database provided information on approximately 23,000 visits involving 7946 outpatients with epilepsy, stroke, or MS seen in neurology specialty clinics. The primary outcome measure was depression as defined as a PHQ-9 ≥ 10. RESULTS Overall, the point prevalence of depression was 29.0%. For stroke, epilepsy, and MS, prevalence of depression was 23% (95% CI: 21-25%), 33% (95% CI: 31-35%), and 29% (95% CI: 28-30%), respectively. For all 3 conditions, increasing disease severity and decreased health-related quality of life were independent predictors of depression. In multivariable models, there was a significant interaction between age and condition, and condition with disease severity. In stroke and MS, increasing age was associated with reduced odds for depression, whereas in epilepsy, increasing age was associated with an increased odds for depression. CONCLUSIONS Although depression is common among patients with neurological disorders, our data suggest that predictors of depression such as age and disease severity varied by condition, supporting important possible phenomenological and pathophysiological differences of depression across these neurological conditions.

Failed Removal of Indwelling Urinary Catheters in Patients With Acute Stroke: Incidence and Risk Factors

Reducing the incidence of indwelling urinary catheter (IUC) use and early removal of the devices that are inserted are appropriate priorities for quality patient care. Just like symptomatic bacteriuria, failed catheter removal as a complication of IUC use is associated with considerable morbidity. In the ideal setting, patients who need IUCs have them, and patients who do not need them will have them removed safely, with the goal of reducing medical complications and facilitating the rehabilitation phase of care.