scholarly journals Prediction of medical costs and the outcome through the utilization of the national health insurance reimbursement claim system. A study of stroke and cancer patients.

1988 ◽  
Vol 55 (5) ◽  
pp. 478-490 ◽  
Author(s):  
Toru Takahashi
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Sanghee Lee ◽  
Yoon Jung Chang ◽  
Hyunsoon Cho

Abstract Background Cancer patients’ prognoses are complicated by comorbidities. Prognostic prediction models with inappropriate comorbidity adjustments yield biased survival estimates. However, an appropriate claims-based comorbidity risk assessment method remains unclear. This study aimed to compare methods used to capture comorbidities from claims data and predict non-cancer mortality risks among cancer patients. Methods Data were obtained from the National Health Insurance Service-National Sample Cohort database in Korea; 2979 cancer patients diagnosed in 2006 were considered. Claims-based Charlson Comorbidity Index was evaluated according to the various assessment methods: different periods in washout window, lookback, and claim types. The prevalence of comorbidities and associated non-cancer mortality risks were compared. The Cox proportional hazards models considering left-truncation were used to estimate the non-cancer mortality risks. Results The prevalence of peptic ulcer, the most common comorbidity, ranged from 1.5 to 31.0%, and the proportion of patients with ≥1 comorbidity ranged from 4.5 to 58.4%, depending on the assessment methods. Outpatient claims captured 96.9% of patients with chronic obstructive pulmonary disease; however, they captured only 65.2% of patients with myocardial infarction. The different assessment methods affected non-cancer mortality risks; for example, the hazard ratios for patients with moderate comorbidity (CCI 3–4) varied from 1.0 (95% CI: 0.6–1.6) to 5.0 (95% CI: 2.7–9.3). Inpatient claims resulted in relatively higher estimates reflective of disease severity. Conclusions The prevalence of comorbidities and associated non-cancer mortality risks varied considerably by the assessment methods. Researchers should understand the complexity of comorbidity assessments in claims-based risk assessment and select an optimal approach.


2007 ◽  
Vol 17 (5) ◽  
pp. 424-429 ◽  
Author(s):  
K. Nakamura ◽  
T. Okamura ◽  
H. Kanda ◽  
T. Hayakawa ◽  
A. Okayama ◽  
...  

2015 ◽  
Vol 33 (29_suppl) ◽  
pp. 55-55
Author(s):  
Ruey Kuen Hsieh ◽  
Yu-Lin Lin ◽  
Chao-Hsiun Tang

55 Background: Pain assessment and management had been adopted as an important criteria in hospital accreditation in Taiwan. National health insurance database may help to determine factors influencing patterns of strong opioid use in advanced cancer patients in their final 12 months of life. Methods: Cancer patients who died from cancer during 2008-2011 were included in the analysis. Data in prescription of strong opioids during their last 12 months of life were collected and analyzed using National Health Insurance Research Database (NHIRD). Patient’s characteristics, such as cancer types, birthdate and gender, as well as information on the provider’s characteristics, such as specialty, gender and age of the physician, the ownership and level of accreditation of the hospital, and the level of urbanization of the hospital where it is located, were also retrieved and included as the controlled variables in the analysis. Results: Of the 162,679 cancer deaths, 57,578 were prescribed strong opioids in their last year of life (35.4 percent). Strong opioid prescription steadily decreased with the corresponding increase in patient age. Besides there are difference in different cancer types. Association with prescription prevalence has also been noted among physician characteristics such as subspecialty, gender and age, as well among hospital characteristics, such as public vs private and accreditation level. Conclusions: There are significant difference in strong opioids prescription among different care providers for advanced cancer patients. Information from this study can guide further efforts in improving supportive care and education for advanced cancer care providers.


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