The relationship between effectiveness and costs measured by a risk-adjusted case-mix system: multicentre study of Catalonian population data bases

A case-mix classification system for explaining healthcare costs using administrative data in Italy

BACKGROUND

The Italian National Health Service (NHS) provides universal coverage to all citizens, granting primary and hospital care with a copayment system for outpatient and drug services. Financing of Local Health Trusts (LHTs) is based on a capitation system adjusted only for age, gender and area of residence. We applied a risk-adjustment system (Johns Hopkins Adjusted Clinical Groups System, ACG® System) in order to explain health care costs using routinely collected administrative data in the Veneto Region (North-eastern Italy).

METHODS

All residents in the Veneto Region were included in the study. The ACG system was applied to classify the regional population based on the following information sources for the year 2015: Hospital Discharges, Emergency Room visits, Chronic disease registry for copayment exemptions, ambulatory visits, medications, the Home care database, and drug prescriptions. Simple linear regressions were used to contrast an age-gender model to models incorporating more comprehensive risk measures aimed at predicting health care costs.

RESULTS

A simple age-gender model explained only 8% of the variance of 2015 total costs. Adding diagnoses-related variables provided a 23% increase, while pharmacy based variables provided an additional 17% increase in explained variance. The adjusted R-squared of the comprehensive model was 6 times that of the simple age-gender model.

CONCLUSIONS

ACG System provides substantial improvement in predicting health care costs when compared to simple age-gender adjustments. Aging itself is not the main determinant of the increase of health care costs, which is better explained by the accumulation of chronic conditions and the resulting multimorbidity.

Analysis of Hospital Volume and Factors Influencing Economic Outcomes in Cancer Surgery: Results from a Population-based Study in Korea

Objectives

To evaluate associations between hospital volume, costs, and length of stay (LOS), and clinical and demographic outcome factors for five types of cancer resection. The main dependent variables were cost and LOS; the primary independent variable was volume.

Methods

Data were obtained from claims submitted to the Korean National Health Insurance scheme. We identified patients who underwent the following surgical procedures: pneumonectomy, colectomy, mastectomy, cystectomy, and esophagectomy. Hospital volumes were divided into quartiles.

Results

Independent predictors of high costs and long LOS included old age, low health insurance contribution, non-metropolitan residents, emergency admission, Charlson score > 2, public hospital ownership, and teaching hospitals. After adjusting for relevant factors, there was an inverse relationship between volume and costs/LOS. The highest volume hospitals had the lowest procedure costs and LOS. However, this was not observed for cystectomy.

Conclusion

Our findings suggest an association between patient and clinical factors and greater costs and LOS per surgical oncologic procedure, with the exception of cystectomy. Yet, there were no clear associations between hospitals’ cost of care and risk-adjusted mortality.

Relationship between efficiency and clinical effectiveness indicators in an adjusted model of resource consumption: a cross-sectional study

Background

Adjusted clinical groups (ACG®) have been widely used to adjust resource distribution; however, the relationship with effectiveness has been questioned. The purpose of the study was to measure the relationship between efficiency assessed by ACG® and a clinical effectiveness indicator in adults attended in Primary Health Care Centres (PHCs).

Methods

Research design: cross-sectional study. Subjects: 196, 593 patients aged >14 years in 13 PHCs in Catalonia (Spain). Measures: Age, sex, PHC, basic care team (BCT), visits, episodes (diagnoses), and total direct costs of PHC care and co-morbidity as measured by ACG® indicators: Efficiency indices for costs, visits, and episodes (costs EI, visits EI, episodes EI); a complexity or risk index (RI); and effectiveness measured by a general synthetic index (SI). The relationship between EI, RI, and SI in each PHC and BCT was measured by multiple correlation coefficients (r).

Results

In total, 56 of the 106 defined ACG® were present in the study population, with five corresponding to 44.5% of the patients, 11 to 68.0% of patients, and 30 present in less than 0.5% of the sample. The RI in each PHC ranged from 0.9 to 1.1. Costs, visits, and episodes had similar trends for efficiency in six PHCs. There was moderate correlation between costs EI and visits EI (r = 0.59). SI correlation with episodes EI and costs EI was moderate (r = 0.48 and r = −0.34, respectively) and was r = −0.14 for visits EI. Correlation between RI and SI was r = 0.29.

Conclusions

The Efficiency and Effectiveness ACG® indicators permit a comparison of primary care processes between PHCs. Acceptable correlation exists between effectiveness and indicators of efficiency in episodes and costs.

Assessing socioeconomic health care utilization inequity in Israel: impact of alternative approaches to morbidity adjustment

BACKGROUND

The ability to accurately detect differential resource use between persons of different socioeconomic status relies on the accuracy of health-needs adjustment measures. This study tests different approaches to morbidity adjustment in explanation of health care utilization inequity.

METHODS

A representative sample was selected of 10 percent (~270,000) adult enrolees of Clalit Health Services, Israel's largest health care organization. The Johns-Hopkins University Adjusted Clinical Groups® were used to assess each person's overall morbidity burden based on one year's (2009) diagnostic information. The odds of above average health care resource use (primary care visits, specialty visits, diagnostic tests, or hospitalizations) were tested using multivariate logistic regression models, separately adjusting for levels of health-need using data on age and gender, comorbidity (using the Charlson Comorbidity Index), or morbidity burden (using the Adjusted Clinical Groups). Model fit was assessed using tests of the Area Under the Receiver Operating Characteristics Curve and the Akaike Information Criteria.

RESULTS

Low socioeconomic status was associated with higher morbidity burden (1.5-fold difference). Adjusting for health needs using age and gender or the Charlson index, persons of low socioeconomic status had greater odds of above average resource use for all types of services examined (primary care and specialist visits, diagnostic tests, or hospitalizations). In contrast, after adjustment for overall morbidity burden (using Adjusted Clinical Groups), low socioeconomic status was no longer associated with greater odds of specialty care or diagnostic tests (OR: 0.95, CI: 0.94-0.99; and OR: 0.91, CI: 0.86-0.96, for specialty visits and diagnostic respectively). Tests of model fit showed that adjustment using the comprehensive morbidity burden measure provided a better fit than age and gender or the Charlson Index.

CONCLUSIONS

Identification of socioeconomic differences in health care utilization is an important step in disparity reduction efforts. Adjustment for health-needs using a comprehensive morbidity burden diagnoses-based measure, this study showed relative underutilization in use of specialist and diagnostic services, and thus allowed for identification of inequity in health resources use, which could not be detected with less comprehensive forms of health-needs adjustments.

[Distribution of primary care expenditure according to sex and age group: a retrospective analysis]

OBJECTIVE

To study the primary care expenditure per person and the weight of different health resources within sex and age groups.

DESIGN

Cost analysis. Retrospective descriptive study.

SETTING

14 urban primary care centers (assigned population: 313,000).

PARTICIPANTS

All patients who visited during 2008 (227,235).

STUDY PERIOD

January to December 2008.

MAIN MEASUREMENTS

Age, sex, visits, laboratory, radiology and complementary tests and referrals to specialists were obtained from patient electronic files. Pharmacy expenditure was obtained from invoices sent to the national health system by pharmacists. Fixed/semi-fixed costs were distributed among visits and a mean cost/visit was obtained. Costs were assigned for laboratory (mean application cost), for radiology and complementary tests (rate per type of test) and for referrals (adjusted rate). Descriptive analysis of data (median, interquartile range and coefficient of variance).

RESULTS

Median expenditure was 362 € (321 € for men and 396 € for women). For the up to 2 year-old group it was 410 €, for aged 15-44 203 € and 75 and above 1,255 €.). The up to 2 years old visits represented 81% of total cost while pharmacy was 8%, while for those aged 75 and above visits accounted for 21% of the total cost and pharmacy 63%.

CONCLUSIONS

Expenditure in primary care is higher in women, although the greatest differences were observed with age. In older than 74 years the median expenditure was six-fold higher than that for 3-44 years old group. In pediatrics the main source of expenditure was visits, representing 80% of the total in up to 2 years old. From 45 years old, pharmacy was the main source of expenditure and in those older than 74 it represented over 60% of the total.