To derive and validate the health-related quality of life comorbidity index (HRQL-CI).
Of 261 clinical classification codes (CCCs) in the 2003 Medical Expenditure Panel Survey (MEPS), 44 were identified as adult, gender-neutral, chronic conditions. The least absolute shrinkage and selection operator (LASSO) procedure identified CCCs significantly associated with the Short Form-12 physical component summary (PCS) and mental component summary (MCS) scores. Regression models were fitted with the selected CCCs, resulting in two subsets corresponding to PCS and MCS, collectively called the HRQL-CI. Internal validation was assessed using 10-fold cross-validation, whereas external validation in terms of prediction accuracy was assessed in the 2005 MEPS database. Prediction errors and model R² were compared between HRQL-CI models and models using the Charlson-CI.
LASSO identified 20 CCCs significantly associated with PCS and 15 with MCS. The R² for the models, including the HRQL-CI (0.28 for PCS and 0.16 for MCS) were greater than those using the Charlson-CI (0.13 for PCS and 0.01 for MCS). The same pattern of higher R² for models using the HRQL-CI was observed in the validation tests.
The HRQL-CI is a valid risk adjustment index, outperforming the Charlson-CI. Further work is needed to test its performance in other patient populations and measures of HRQL.
"The HRQL-CI is a validated risk adjustment index that outperforms the Charlson comorbidity index when external validation was assessed in MEPS (Mukherjee et al., 2011; Ou et al., 2012). To form the HRQL-CI, Mukherjee et al. (2011) selected 44 adult, gender-neutral, chronic conditions, then identified those significantly associated with the Short Form-12 physical component summary and mental component summary. The resulting two subsets of conditions comprise the HRQL-CI, consisting of a physical component score and a mental component score. "
[Show abstract][Hide abstract] ABSTRACT: Background. Socioeconomic factors and insurance status have not been correlated with differential use of healthcare services in inflammatory bowel disease (IBD).
Aim. To describe IBD-related expenditures based on insurance and household income with the use of inpatient, outpatient, emergency, and office-based services, and prescribed medications in the United States (US).
Methods. We evaluated the Medical Expenditure Panel Survey from 1996 to 2011 of individuals with Crohn’s disease (CD) or ulcerative colitis (UC). Nationally weighted means, proportions, and multivariate regression models examined the relationships between income and insurance status with expenditures.
Results. Annual per capita mean expenditures for CD, UC, and all IBD were $10,364 (N = 238), $7,827 (N = 95), and $9,528, respectively, significantly higher than non-IBD ($4,314, N = 276, 372, p < 0.05). Publicly insured patients incurred the highest costs ($18,067) over privately insured ($8,014, p < 0.05) or uninsured patients ($5,129, p < 0.05). Among all IBD patients, inpatient care composed the highest proportion of costs ($3,392, p < 0.05). Inpatient costs were disproportionately higher for publicly insured patients. Public insurance had higher odds of total costs than private (OR 2.13, CI [1.08–4.19]) or no insurance (OR 4.94, CI [1.26–19.47]), with increased odds for inpatient and emergency care. Private insurance had higher costs associated with outpatient care, office-based care, and prescribed medicines. Low-income patients had lower costs associated with outpatient (OR 0.38, CI [0.15–0.95]) and office-based care (OR 0.21, CI [0.07–0.62]).
Conclusions. In the US, high inpatient utilization among publicly insured patients is a previously unrecognized driver of high IBD costs. Bridging this health services gap between SES strata for acute care services may curtail direct IBD-related costs.
"It would also be preferable to adjust not only for the specific disease but also for the severity of each disease. This can be done for certain conditions such as heart failure and malignant disease [30,31], but is difficult in the ICU with a heterogeneous population. "
[Show abstract][Hide abstract] ABSTRACT: Health-related quality of life (HRQoL) in patients treated in intensive care has been reported to be lower compared with age and sex-adjusted control groups. Our aim was to test whether stratifying for coexisting conditions would reduce observed differences in HRQoL between patients treated in the ICU and a control group from the normal population. We also wanted to characterise the ICU patients with the lowest HRQoL within these strata.
We did a cross-sectional comparison of scores of the short form health survey (SF-36) questionnaire in a multicenter study of patients treated in the ICU (n = 780) and those from a local public health survey (n = 6093). Analyses were in both groups adjusted for age and sex, and data stratified for coexisting conditions. Within each strata patients with low scores (below - 2 SD of the control group) were identified and characterised.
After adjustment, there were minor and insignificant differences in mean SF-36 scores between patients and controls. Eight (n = 18) and 22% (n = 51) of the patients had low scores (- 2 SD of the control group) in the physical and mental dimensions of SF-36, respectively. Patients with low scores were usually male, single, on sick leave before admission to critical care, and survived shorter after being in ICU.
After adjusting for age, sex, and coexisting conditions, mean HRQoL scores were almost equal in patients and controls. Up to 22% (n = 51) of the patients had however a poor quality of life as compared to the controls (-2 SD). This group, which more often consisted of singles, men, individuals who were on sick leave before admission to the ICU, had an increased mortality after ICU. This group should be a target for future support.
[Show abstract][Hide abstract] ABSTRACT: Background and Objective
Although the predictive ability of the Charlson Index, Elixhauser Index (EI), Chronic Disease Score (CDS), and Health-related Quality of Life Comorbidity Index (HRQL-CI) for health care outcomes has been assessed individually, little research has compared the discriminative performance of these indices directly in a single study. The current study compared these indices in discriminating among type 2 diabetes patients varying in demographics and health care outcomes characteristics.
Health Outcomes Research in Medicine 05/2011; 2(2). DOI:10.1016/j.ehrm.2011.06.002
Data provided are for informational purposes only. Although carefully collected, accuracy cannot be guaranteed. The impact factor represents a rough estimation of the journal's impact factor and does not reflect the actual current impact factor. Publisher conditions are provided by RoMEO. Differing provisions from the publisher's actual policy or licence agreement may be applicable.