Jean-Christophe Luthi

Coding algorithms for defining comorbidities in ICD-9-CM and ICD-10 administrative data.

Objectives:Implementation of the International Statistical Classification of Disease and Related Health Problems, 10th Revision (ICD-10) coding system presents challenges for using administrative data. Recognizing this, we conducted a multistep process to develop ICD-10 coding algorithms to define Charlson and Elixhauser comorbidities in administrative data and assess the performance of the resulting algorithms. Methods:ICD-10 coding algorithms were developed by “translation” of the ICD-9-CM codes constituting Deyos (for Charlson comorbidities) and Elixhausers coding algorithms and by physicians’ assessment of the face-validity of selected ICD-10 codes. The process of carefully developing ICD-10 algorithms also produced modified and enhanced ICD-9-CM coding algorithms for the Charlson and Elixhauser comorbidities. We then used data on in-patients aged 18 years and older in ICD-9-CM and ICD-10 administrative hospital discharge data from a Canadian health region to assess the comorbidity frequencies and mortality prediction achieved by the original ICD-9-CM algorithms, the enhanced ICD-9-CM algorithms, and the new ICD-10 coding algorithms. Results:Among 56,585 patients in the ICD-9-CM data and 58,805 patients in the ICD-10 data, frequencies of the 17 Charlson comorbidities and the 30 Elixhauser comorbidities remained generally similar across algorithms. The new ICD-10 and enhanced ICD-9-CM coding algorithms either matched or outperformed the original Deyo and Elixhauser ICD-9-CM coding algorithms in predicting in-hospital mortality. The C-statistic was 0.842 for Deyos ICD-9-CM coding algorithm, 0.860 for the ICD-10 coding algorithm, and 0.859 for the enhanced ICD-9-CM coding algorithm, 0.868 for the original Elixhauser ICD-9-CM coding algorithm, 0.870 for the ICD-10 coding algorithm and 0.878 for the enhanced ICD-9-CM coding algorithm. Conclusions:These newly developed ICD-10 and ICD-9-CM comorbidity coding algorithms produce similar estimates of comorbidity prevalence in administrative data, and may outperform existing ICD-9-CM coding algorithms.

Cross-national comparative performance of three versions of the ICD-10 Charlson index.

Objective:The Charlson comorbidity index has been widely used for risk adjustment in outcome studies using administrative health data. Recently, 3 International Statistical Classification of Diseases, Tenth Revision (ICD-10) translations have been published for the Charlson comorbidities. This study was conducted to compare the predictive performance of these versions (the Halfon, Sundararajan, and Quan versions) of the ICD-10 coding algorithms using data from 4 countries. Methods:Data from Australia (N = 2000–2001, max 25 diagnosis codes), Canada (N = 2002–2003, max 16 diagnosis codes), Switzerland (N = 1999–2001, unlimited number of diagnosis codes), and Japan (N = 2003, max 11 diagnosis codes) were analyzed. Only the first admission for patients age 18 years and older, with a length of stay of ≥2 days was included. For each algorithm, 2 logistic regression models were fitted with hospital mortality as the outcome and the Charlson individual comorbidities or the Charlson index score as independent variables. The c-statistic (representing the area under the receiver operating characteristic curve) and its 95% probability bootstrap distribution were employed to evaluate model performance. Results:Overall, within each populations data, the distribution of comorbidity level categories was similar across the 3 translations. The Quan version produced slightly higher median c-statistics than the Halfon or Sundararajan versions in all datasets. For example, in Japanese data, the median c-statistics were 0.712 (Quan), 0.709 (Sundararajan), and 0.694 (Halfon) using individual comorbidity coefficients. In general, the probability distributions between the Quan and the Sundararajan versions overlapped, whereas those between the Quan and the Halfon version did not. Conclusions:Our analyses show that all of the ICD-10 versions of the Charlson algorithm performed satisfactorily (c-statistics 0.70–0.86), with the Quan version showing a trend toward outperforming the other versions in all data sets.

Is readmission to hospital an indicator of poor process of care for patients with heart failure

Background: Controversy exists about the appropriateness of using readmission as an indicator of the quality of care. A study was undertaken to measure the validity and predictive ability of readmission in this context. Methods: An evaluation study was performed in patients discharged alive with heart failure from three Swiss academic medical centres. Process quality indicators were derived from evidence based guidelines for the management and treatment of heart failure. Readmissions were calculated from hospital administrative data. The predictive ability of readmissions was evaluated using bivariate and multivariate analyses, and validity by calculating sensitivity, specificity, positive and negative predictive value, using process indicators as the “gold standard”. Results: Of 1055 eligible patients discharged alive, 139 (13.2%) were readmitted within 30 days. The adjusted odds ratio (OR) for absence of measurement of left ventricular function was 0.70 (95% CI 0.45 to 1.08) for readmissions. In patients with left ventricular systolic dysfunction, three dose categories of angiotensin converting enzyme inhibitor were examined using ordinal logistic regression. The adjusted OR for these categories was 1.07 (95% CI 0.56 to 2.06) for readmissions. When using process indicators as the gold standard to assess the validity of readmissions, sensitivity ranged from 0.08 to 0.17 and specificity from 0.86 to 0.93. Conclusions: Readmission did not predict and was not a valid indicator of the quality of care for patients with heart failure admitted to three Swiss university hospitals.

Anemia and chronic kidney disease are potential risk factors for mortality in stroke patients: a historic cohort study

BackgroundChronic kidney disease (CKD) is associated to a higher stroke risk. Anemia is a common consequence of CKD, and is also a possible risk factor for cerebrovascular diseases. The purpose of this study was to examine if anemia and CKD are independent risk factors for mortality after stroke.MethodsThis historic cohort study was based on a stroke registry and included patients treated for a first clinical stroke in the stroke unit of one academic hospital over a three-year period. Mortality predictors comprised demographic characteristics, CKD, glomerular filtration rate (GFR), anemia and other stroke risk factors. GFR was estimated by means of the simplified Modification of Diet in Renal Disease formula. Renal function was assessed according to the Kidney Disease Outcomes Quality Initiative (K/DOQI)-CKD classification in five groups. A value of hemoglobin < 120 g/L in women and < 130 g/L in men on admission defined anemia. Kaplan-Meier survival curves and Cox models were used to describe and analyze one-year survival.ResultsAmong 890 adult stroke patients, the mean (Standard Deviation) calculated GFR was 64.3 (17.8) ml/min/1.73 m2 and 17% had anemia. Eighty-two (10%) patients died during the first year after discharge. Among those, 50 (61%) had K/DOQI CKD stages 3 to 5 and 32 (39%) stages 1 or 2 (p < 0.001). Anemia was associated with an increased risk of death one year after discharge (p < 0.001). After adjustment for other factors, a higher hemoglobin level was independently associated with decreased mortality one year after discharge [hazard ratio (95% CI) 0.98 (0.97-1.00)].ConclusionsBoth CKD and anemia are frequent among stroke patients and are potential risk factors for decreased one-year survival. The inclusion of patients with a first-ever clinical stroke only and the determination of anemia based on one single measure, on admission, constitute limitations to the external validity. We should investigate if an early detection and management of both CKD and anemia could improve survival in stroke patients.

Prevalence of Frailty Indicators and Association with Socioeconomic Status in Middle-Aged and Older Adults in a Swiss Region with Universal Health Insurance Coverage: A Population-Based Cross-Sectional Study

Frailty prevalence in older adults has been reported but is largely unknown in middle-aged adults. We determined the prevalence of frailty indicators among middle-aged and older adults from a general Swiss population characterized by universal health insurance coverage and assessed the determinants of frailty with a special focus on socioeconomic status. Participants aged 50 and more from the population-based 2006–2010 Bus Santé study were included (N = 2,930). Four frailty indicators (weakness, shrinking, exhaustion, and low activity) were measured according to standard definitions. Multivariate logistic regressions were used to determine associations. Overall, 63.5%, 28.7%, and 7.8% participants presented no frailty indicators, one frailty indicator, and two or more frailty indicators, respectively. Among middle-aged participants (50–65 years), 75.1%, 22.2%, and 2.7% presented 0, 1, and 2 or more frailty indicators. The number of frailty indicators was positively associated with age, hypertension, and current smoking and negatively associated with male gender, body mass index, waist-to-hip ratio, and serum total cholesterol level. Lower income level but not education was associated with higher number of frailty indicators. Frailty indicators are frequently encountered in both older and middle-aged adults from the Swiss general population. Despite universal health insurance coverage, household income is independently associated with frailty.

The Effect of External Feedback on the Management of Medicare Inpatients With Congestive Heart Failure

The purpose of this study was to compare the effect of 2 feedback strategies on the adherence to congestive heart failure (CHF) guidelines. Thirty-two hospitals in 4 states were randomized to receive either a written feedback intervention (low-intensity intervention [LII]) or an intervention involving feedback, a physician liaison, and quality improvement tools (high-intensity intervention [HII]). CHF quality indicators were assessed, and quality managers were interviewed at baseline and remeasurement. No significant changes in quality indicators were found as a result of either intervention. Seventy-eight percent of quality managers indicated that hospital project implementation had not begun until shortly before remeasurement. HII quality managers perceived the CHF project as significantly more successful compared with LII quality managers (63% versus 13%, P < .01). Evaluation of the effects of external feedback on practice behavior requires sufficient time for organizational and individual clinician change to occur. Physician liaisons may play a role in facilitating this change.

Pre-esrd Care and Mortality in Incident Esrd Patients With Multiple Myeloma

Objectives: The relationship between mortality and pre-ESRD (end-stage renal disease) nephrology care in incident ESRD patients with multiple myeloma (MM) as the primary cause of renal failure has not been examined. Materials and Methods: Among 439,206 incident US hemodialysis patients with MM as the primary cause of ESRD (June 1, 2005 to May 31, 2009) identified using the US Renal Data System, adjusted odds ratios (OR) for reported pre-ESRD nephrology care for ESRD due to MM (n=4561) versus other causes (n=434,645) were calculated. The association of pre-ESRD nephrology care with subsequent mortality in MM-ESRD patients was examined. Results: MM-ESRD patients were less likely to have any predialysis nephrology care in the year before initiation of dialysis (34.8% vs. 58.5%; OR=0.38; 95% confidence interval [CI], 0.34-0.43) compared with patients with ESRD due to other causes. MM-ESRD patients compared with others were more likely to have catheters on first dialysis (91.8% vs. 75.6%; OR=4.15; 95% CI, 3.54-4.86). Incident MM-ESRD patients receiving predialysis care for ≥6 months had significantly lower 1-year mortality (hazard ratio 0.89; 95% CI, 0.82-0.97 and 0.88; 95% CI, 0.80-0.96, respectively), relative to those without this care. A catheter for dialysis access was associated with a 1.6-fold increase in 1-year mortality in incident MM-ESRD (hazard ratio 1.55; 95% CI, 1.32-1.83). Conclusions: MM-ESRD patients were less likely to have predialysis nephrology care and more likely to use catheters on first dialysis. However, predialysis care is independently associated with lower mortality in MM-ESRD patients. Predialysis care should be prioritized in MM patients approaching ESRD.