A new comorbidity index: the health-related quality of life comorbidity index

Bhattacharya

2014

Preprint

View the peer-reviewed version (peerj.com/articles/587), which is the preferred citable publication unless you specifically need to cite this preprint.Park MD, Bhattacharya J, Park K. 2014. Differences in healthcare expenditures for inflammatory bowel disease by insurance status, income, and clinical care setting. PeerJ 2:e587 https://doi.org/10.7717/peerj.587Di ff e r e n c e s i n h e a l t h c a r e e x p e n d i t u r e s f o r i n fl a mma t o r y b o we l d i s e a s e b y i n s u r a n c e s t a t u s , i n c o me , a n d c l i n i c a l c a r e s e t t i n g Ba c k g r o u n d : S o c i o e c o n o mi c f a c t o r s a n d i n s u r a n c e s t a t u s h a v e n o t b e e n c o r r e l a t e d wi t h d i ff e r e n t i a l u s e o f h e a l t h c a r e s e r v i c e s i n i n fl a mma t o r y b o we l d i s e a s e ( I B D) . Ai m: T o d e s c r i b e I B D-r e l a t e d e x p e n d i t u r e s b a s e d o n i n s u r a n c e a n d h o u s e h o l d i n c o me wi t h t h e u s e o f i n p a t i e n t , o u t p a t i e n t , e me r g e n c y , a n d o ffi c e -b a s e d s e r v i c e s , a n d p r e s c r i b e d me d i c a t i o n s i n t h e Un i t e d S t a t e s ( US ) . Me t h o d s :We e v a l u a t e d t h e Me d i c a l E x p e n d i t u r e P a n e l S u r v e y f r o m 1 9 9 6 t o 2 0 1 1 o f i n d i v i d u a l s wi t h Cr o h n ' s d i s e a s e ( CD) o r u l c e r a t i v e c o l i t i s ( UC) . Na t i o n a l l ywe i g h t e d me a n s , p r o p o r t i o n s , a n d mu l t i v a r i a t e r e g r e s s i o n mo d e l s e x a mi n e d t h e r e l a t i o n s h i p s b e t we e n i n c o me a n d i n s u r a n c e s t a t u s wi t h e x p e n d i t u r e s . Re s u l t s : A n n u a l p e r c a p i t a me a n e x p e n d i t u r e s f o r CD, UC, a n d a l l I B D we r e $ 1 0 , 3 6 4 ( N= 2 3 8 ) , $ 7 , 8 2 7 ( N= 9 5 ) , a n d $ 9 , 5 2 8 , r e s p e c t i v e l y , s i g n i fi c a n t l y h i g h e r t h a n n o n -I B D ( $ 4 , 3 1 4 , N= 2 7 6 , 3 7 2 , p < 0 . 0 5 ) . P u b l i c l y i n s u r e d p a t i e n t s i n c u r r e d t h e h i g h e s t c o s t s ( $ 1 8 , 0 6 7 ) , o v e r p r i v a t e l y i n s u r e d ( $ 8 , 0 1 4 , p < 0 . 0 5 ) o r u n i n s u r e d p a t i e n t s ( $ 5 , 1 2 9 , p < 0 . 5 ) . A mo n g a l l I B D p a t i e n t s , i n p a t i e n t c a r e c o mp o s e d t h e h i g h e s t p r o p o r t i o n o f c o s t s ( $ 3 , 3 9 2 , p < . 5 ) . I n p a t i e n t c o s t s we r e d i s p r o p o r t i o n a t e l y h i g h e rf o r p u b l i c l y i n s u r e d p a t i e n t s . P u b l i c i n s u r a n c e h a d h i g h e r o d d s o f t o t a l c o s t s t h a n p r i v a t e ( OR 2 . 1 3 , CI 1 . 0 8 -4 . 1 9 ) o r n o i n s u r a n c e ( OR 4 . 9 4 , CI 1 . 2 6 -1 9 . 4 7 ) , wi t h i n c r e a s e d o d d s f o r i n p a t i e n t a n d e me r g e n c y c a r e . P r i v a t e i n s u r a n c e h a d h i g h e r c o s t s a s s o c i a t e d wi t h o u t p a t i e n t c a r e , o ffi c e -b a s e d c a r e , a n d p r e s c r i b e d me d i c i n e s ....

Section: Study Population and Variablesmentioning

confidence: 99%

Section: Study Population and Variablesmentioning

confidence: 99%

Differences in healthcare expenditures for inflammatory bowel disease by insurance status, income, and clinical care setting

Bhattacharya

2014

Preprint

Population Health Management

“…Each condition is assigned a point weight based on its relative influence on the HRQL outcomes (Short Form-12 Physical Component Score or Mental Component Score). 23 The final HRQL-CI physical or mental index score is the sum of weights assigned to each condition presented by the patient. The scores derived from the CCI, EI, and HRQL-CI indices were based on a list of selected ICD-9-CM diagnosis codes from inpatient and outpatient claims, while the CDS was estimated utilizing selected National Drug Code numbers from pharmacy prescription claims.…”

Section: Comorbidity Index Scoresmentioning

confidence: 99%

“…21,22 The Health-related Quality of Life Comorbidity Index (HRQL-CI) is a more recently developed, diagnosisderived measure originally designed to predict HRQL as measured by the Short Form-12 using the Medical Expenditure Panel Survey database. 23 The HRQL-CI has been demonstrated to outperform CCI in predicting HRQL outcome in a general population and an asthma subsample. 23 Further research is needed to compare the HRQL-CI with other existing indices, other types of populations, and using other types of data sources to assess its performance for other types of health care outcomes.…”

Section: Introductionmentioning

confidence: 96%

“…23 The HRQL-CI has been demonstrated to outperform CCI in predicting HRQL outcome in a general population and an asthma subsample. 23 Further research is needed to compare the HRQL-CI with other existing indices, other types of populations, and using other types of data sources to assess its performance for other types of health care outcomes. To date, no study has compared the CCI, EI, CDS, and HRQL-CI directly and comprehensively across different health care outcomes.…”

Section: Introductionmentioning

confidence: 96%

See 1 more Smart Citation

Comparative Performance of Comorbidity Indices in Predicting Health Care-Related Behaviors and Outcomes among Medicaid Enrollees with Type 2 Diabetes

Mukherjee²,

Erickson³

et al. 2012

Self Cite

No single gold standard of comorbidity measure has been identified, and the performance of comorbidity indices vary according to the outcome of interest. The authors compared the Charlson Comorbidity Index, Elixhauser Index (EI), Chronic Disease Score (CDS), and Health-related Quality of Life Comorbidity Index (HRQL-CI) in predicting health care-related behaviors (physicians' concordance with diabetes care standards and patients' oral antidiabetic drug [OAD] adherence) and outcomes (health care utilization and expenditures) among Medicaid enrollees with type 2 diabetes. A total of 9832 diabetes patients who used OAD were identified using data from the MarketScan Medicaid database from 2003 to 2007. Predictive performance of the comorbidity index was assessed using multiple regression models controlling for patient demographics, diabetes severity, and baseline health care characteristics. Among the 4 indices, the CDS was best at predicting physician's concordance with care standards. The CDS and HRQL-CI mental index performed better than other indices as predictors of medication adherence. The EI was best at predicting health care utilization and expenditures. These results suggest that, for these low-income diabetes patients, the CDS and HRQL-CI mental index were relatively better risk-adjustment tools for health care-related behavior data evaluation and the EI was the first choice for health care utilization and expenditures data. (Population Health Management 2012;15:220-229)

Association Between Medicare Policy Reforms and Changes in Hospitalized Medicare Beneficiaries' Severity of Illness

et al. 2019

Key Points Question Did the expansion of secondary diagnosis codes in January 2011 allow more diagnosis codes to be reported per hospitalization, and were incentive payments for health information technology associated with changes in measured severity of illness? Findings In this cohort study of 47 951 443 discharges at 2850 hospitals, expansion of secondary diagnosis coding positions was associated with a statistically significant increase in measured severity of illness among hospitalizations for all diagnoses, diagnoses commonly targeted by incentive programs, and untargeted diagnoses. Health information technology incentives were associated with a statistically significant increase in condition categories for all diagnoses and targeted diagnoses. Meaning Changes in Medicare policies appear to be associated with increases in measured severity of illness; related policy changes may incentivize more thorough documentation of disease burden without underlying changes in patient severity.