Application of the ambulatory care groups in the primary care of a European national health care system: does it work?

The role of organization of care in GPs' prevention practice

BACKGROUND

General practitioners (GPs) do not systematically include preventive recommendations in their practice, and some characteristics of health care organization are associated with more systematic prevention. But the characteristics of health care organization may act in a nonuniform manner depending on the type of preventive care. Thus, one characteristic can be positively associated with one type of preventive care and negatively associated with another. Our aim was to investigate the association between health care organization in general practice and different areas of preventive care (immunization and addiction prevention), in search of nonuniform associations.

METHODS

We used a representative survey of 1,813 French GPs conducted in 2009. Four preventive care practices were studied: immunization through flu and HPV vaccination, and prevention of addictive behaviors concerning tobacco and alcohol use.Characteristics of GPs' health care organization and the social context of their practice were collected (spatial accessibility to GPs and socioeconomic level of the area of practice). We constructed mixed models to study associations and interactions between the organization variables and preventive care.

RESULTS

Four out of five characteristics of GPs' organization have uneven impacts on different types of preventive care (p-interaction < 10-4). For example, number of daily consultations is associated with better immunization prevention but with poorer prevention counseling in addictive behaviors. In contrast, working with digital medical files is uniformly associated with both types of preventive care (OR = 1.29 [1.15-1.45]; P < 10-4).

CONCLUSION

An approach centered on specific types of preventive care should help deepen our understanding of prevention and possibly help to identify a new typology for preventive care.

Impact of heart failure and other comorbidities on mortality in patients with chronic obstructive pulmonary disease: a register-based, prospective cohort study

BACKGROUND

Multimorbidity has already become common in primary care and will be a challenge in the future. Primary care in Sweden participates to a great extent in the care of patients with two severe, chronic conditions: chronic obstructive pulmonary disease (COPD) and heart failure. Both conditions are characterized by high mortality and often coexist. Age, sex, heart failure and other comorbidities are considered to be the major predictors of mortality in patients with COPD. We aimed to study the impact of heart failure, other comorbidities, age and sex on mortality in patients with COPD.

METHODS

A register-based, prospective cohort study conducted in Blekinge County in Sweden with about 150,000 inhabitants. The study population was comprised of people aged ≥35 years. The data about diagnoses of COPD and heart failure came from the 2007 health care register, in which we found 984 individuals with a diagnosis of COPD. Date of death was collected from January 1st, 2008 -August 31st, 2015. The diagnosis-based Adjusted Clinical Groups (ACG) Case-Mix System 7.1 was used to describe comorbidity. Each individual was assigned one of six comorbidity levels called resource utilization bands (RUB) graded from 0 to 5.

RESULTS

Estimated eight year mortality in patients with COPD and coexisting heart failure was seven times higher than in patients with COPD alone - odds ratio 7.06 (95% CI 3.88-12.84). Adjusting for age and male sex resulted in odds ratio 3.75 (95% CI 1.97-7.15). Further adjusting for other comorbidities resulted in odds ratio 3.26 (95% CI 1.70-6.25). The mortality was strongly associated with the highest comorbidity level - RUB 5 where the odds ratio was 5.19 (95% CI 2.59-10.38).

CONCLUSION

Heart failure has an important impact on mortality in patients with COPD. The mortality in patients with COPD and coexisting heart failure was strongly associated with age, male sex and other comorbidities. Of those three predictors, only other comorbidities can be influenced. Heart failure and other comorbidities should be recognized early and properly treated in order to improve survival in patients with coexisting COPD and heart failure.

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.

A Review on Methods of Risk Adjustment and their Use in Integrated Healthcare Systems

INTRODUCTION

Effective risk adjustment is an aspect that is more and more given weight on the background of competitive health insurance systems and vital healthcare systems. The objective of this review was to obtain an overview of existing models of risk adjustment as well as on crucial weights in risk adjustment. Moreover, the predictive performance of selected methods in international healthcare systems should be analysed.

THEORY AND METHODS

A comprehensive, systematic literature review on methods of risk adjustment was conducted in terms of an encompassing, interdisciplinary examination of the related disciplines.

RESULTS

In general, several distinctions can be made: in terms of risk horizons, in terms of risk factors or in terms of the combination of indicators included. Within these, another differentiation by three levels seems reasonable: methods based on mortality risks, methods based on morbidity risks as well as those based on information on (self-reported) health status.

CONCLUSIONS AND DISCUSSION

After the final examination of different methods of risk adjustment it was shown that the methodology used to adjust risks varies. The models differ greatly in terms of their included morbidity indicators. The findings of this review can be used in the evaluation of integrated healthcare delivery systems and can be integrated into quality- and patient-oriented reimbursement of care providers in the design of healthcare contracts.

Heart failure and levels of other comorbidities in patients with chronic obstructive pulmonary disease in a Swedish population: a register-based study

Background

Despite the fact that heart failure and chronic obstructive pulmonary disease (COPD) often exist together and have serious clinical and economic implications, they have mostly been studied separately. Our aim was to study prevalence of coexisting heart failure and COPD in a Swedish population. A further goal was to describe levels of other comorbidity and investigate where the patients received care: primary, secondary care or both.

Methods

We conducted a register-based, cross-sectional study. The population included all people older than 19 years, living in Östergötland County in Sweden. The data were obtained from the Care Data Warehouse register from the year 2006. The diagnosis-based Adjusted Clinical Groups Case-Mix System 7.1 was used to describe the comorbidity level.

Results

The prevalence of the diagnosis of heart failure in patients with COPD was 18.8 % while it was 1.6 % in patients without COPD. Age standardized prevalence was 9.9 and 1.5 %, respectively. Standardized relative risk for the diagnosis of heart failure in patients with COPD was 6.6. The levels of other comorbidity were significantly higher in patients with coexisting heart failure and COPD compared to patients with either heart failure or COPD alone. Primary care was the only care provider for 36.2 % of patients with the diagnosis of heart failure and 20.7 % of patients with coexisting diagnoses of heart failure and COPD. Primary care participated furthermore in shared care of 21.5 % of patients with the diagnosis of heart failure and 21.7 % of patients with coexisting diagnoses of heart failure and COPD. The share of care between primary and secondary care varied depending on levels of comorbidity both in patients with coexisting heart failure and COPD and patients with heart failure alone.

Conclusion

Patients with coexisting diagnoses of heart failure and COPD are common in the Swedish population. Patients with coexisting heart failure and COPD have higher levels of other comorbidity than patients with heart failure or COPD alone. Primary care in Sweden participates to a great extent in care of patients with diagnoses of heart failure alone and coexisting heart failure and COPD.

Association between age, gender and multimorbidity level and receiving home health care: a population-based Swedish study

Background

Home health care is an important part of primary health care. How delivery of home health care is organised is probably important for sustainability of the healthcare system as a whole. More than 50 % of individuals over 65 years old have multimorbidity, which increases with higher age, also influencing the needs of home health care. Our aim was to study the proportion of the population above 65 years receiving home health care according to age, gender and multimorbidity level.

Methods

The study population comprised 32,130 people aged 65 or more, living in Blekinge County in southern Sweden. We analysed data from patient electronic medical records for patients receiving home health care delivered in patients’ own homes by nurses, physiotherapists and occupational therapists. We used the Adjusted Clinical Groups Case-Mix System in order to group individuals according to diagnoses into six levels of multimorbidity. In order to analyse the differences between individuals receiving home health care and those who did not, we used Chi squared test. Logistic regression analysis was conducted in order to study how the dependent variable was influenced by the independent variables.

Results

A total of 7860 (28 %) of the studied population received home health care in 2011. Logistic regression analysis showed that men had 26 % lower odds of receiving home care compared to women (OR = 0.74, 95 % CI 0.69–0.78). There was also a substantial group (22 %) with low multimorbidity level among people receiving home health care. Adjusting for gender and age showed no differences in odds of receiving home health care for patients with lower levels of multimorbidity. However, for patients with higher levels of morbidity the odds increased dramatically for both genders.

Conclusion

The question of to whom and to what extent home health care should be provided is an important challenge for policy makers. Our results show that there are differences in the use of home health care dependent on gender, age and multimorbidity level, but also that home health care is provided to individuals with low morbidity. Further studies could explain the factors influencing home health care use.

Incidence of severe hypoglycaemic episodes in patients with type 2 diabetes in the Basque country: impact on healthcare costs

BACKGROUND

Hypoglycaemia is an acute complication of diabetes mellitus which poses a serious threat. This study aims to describe the annual rate of people suffering episodes of severe hypoglycaemia and to estimate the healthcare costs for individuals who have suffered such events.

METHODS

A descriptive study involving all patients with type 2 diabetes (T2DM) from the Basque Country (period: 1/09/2010 to 31/08/2011) aged ≥35 years (N = 134,413). The rate of hypoglycaemic episodes treated in hospitals (Accident and Emergency and in-patient services) was calculated using an algorithm based on diagnostics and laboratory tests. The variables recorded included demographic, comorbidity (diagnoses categorised using the Adjusted Clinical Groups case-mix system) and socioeconomic variables (deprivation index of the area of residence). The annual healthcare cost for people with T2DM who suffered those episodes was compared with those who did not by regression analysis.

RESULTS

The incidence of hypoglycaemia in the Basque Country was 0.56 %. This percentage was higher among women and people with a lower socioeconomic status. These episodes were associated with age and high values of glycosylated haemoglobin (HbA1c) > 7 %. Adjusting for the other variables, on average, people who suffered hypoglycaemia accounted for an additional €2509 in annual healthcare costs.

CONCLUSIONS

Hypoglycaemia has high morbi-mortality and a major economic impact. As such, health services must monitor its appearance and promote specific actions, especially in the higher risk sub-populations.

Is use of fall risk-increasing drugs in an elderly population associated with an increased risk of hip fracture, after adjustment for multimorbidity level: a cohort study

Background

Risk factors for hip fracture are well studied because of the negative impact on patients and the community, with mortality in the first year being almost 30% in the elderly. Age, gender and fall risk-increasing drugs, identified by the National Board of Health and Welfare in Sweden, are well known risk factors for hip fracture, but how multimorbidity level affects the risk of hip fracture during use of fall risk-increasing drugs is to our knowledge not as well studied. This study explored the relationship between use of fall risk-increasing drugs in combination with multimorbidity level and risk of hip fracture in an elderly population.

Methods

Data were from Östergötland County, Sweden, and comprised the total population in the county aged 75 years and older during 2006. The odds ratio (OR) for hip fracture during use of fall risk-increasing drugs was calculated by multivariate logistic regression, adjusted for age, gender and individual multimorbidity level. Multimorbidity level was estimated with the Johns Hopkins ACG Case-Mix System and grouped into six Resource Utilization Bands (RUBs 0–5).

Results

2.07% of the study population (N = 38,407) had a hip fracture during 2007. Patients using opioids (OR 1.56, 95% CI 1.34-1.82), dopaminergic agents (OR 1.78, 95% CI 1.24-2.55), anxiolytics (OR 1.31, 95% CI 1.11-1.54), antidepressants (OR 1.66, 95% CI 1.42-1.95) or hypnotics/sedatives (OR 1.31, 95% CI 1.13-1.52) had increased ORs for hip fracture after adjustment for age, gender and multimorbidity level. Vasodilators used in cardiac diseases, antihypertensive agents, diuretics, beta-blocking agents, calcium channel blockers and renin-angiotensin system inhibitors were not associated with an increased OR for hip fracture after adjustment for age, gender and multimorbidity level.

Conclusions

Use of fall risk-increasing drugs such as opioids, dopaminergic agents, anxiolytics, antidepressants and hypnotics/sedatives increases the risk of hip fracture after adjustment for age, gender and multimorbidity level. Fall risk-increasing drugs, high age, female gender and multimorbidity level, can be used to identify high-risk patients who could benefit from a medication review to reduce the risk of hip fracture.

Is use of fall risk-increasing drugs in an elderly population associated with an increased risk of hip fracture, after adjustment for multimorbidity level: a cohort study

BACKGROUND

Risk factors for hip fracture are well studied because of the negative impact on patients and the community, with mortality in the first year being almost 30% in the elderly. Age, gender and fall risk-increasing drugs, identified by the National Board of Health and Welfare in Sweden, are well known risk factors for hip fracture, but how multimorbidity level affects the risk of hip fracture during use of fall risk-increasing drugs is to our knowledge not as well studied. This study explored the relationship between use of fall risk-increasing drugs in combination with multimorbidity level and risk of hip fracture in an elderly population.

METHODS

Data were from Östergötland County, Sweden, and comprised the total population in the county aged 75 years and older during 2006. The odds ratio (OR) for hip fracture during use of fall risk-increasing drugs was calculated by multivariate logistic regression, adjusted for age, gender and individual multimorbidity level. Multimorbidity level was estimated with the Johns Hopkins ACG Case-Mix System and grouped into six Resource Utilization Bands (RUBs 0-5).

RESULTS

2.07% of the study population (N = 38,407) had a hip fracture during 2007. Patients using opioids (OR 1.56, 95% CI 1.34-1.82), dopaminergic agents (OR 1.78, 95% CI 1.24-2.55), anxiolytics (OR 1.31, 95% CI 1.11-1.54), antidepressants (OR 1.66, 95% CI 1.42-1.95) or hypnotics/sedatives (OR 1.31, 95% CI 1.13-1.52) had increased ORs for hip fracture after adjustment for age, gender and multimorbidity level. Vasodilators used in cardiac diseases, antihypertensive agents, diuretics, beta-blocking agents, calcium channel blockers and renin-angiotensin system inhibitors were not associated with an increased OR for hip fracture after adjustment for age, gender and multimorbidity level.

CONCLUSIONS

Use of fall risk-increasing drugs such as opioids, dopaminergic agents, anxiolytics, antidepressants and hypnotics/sedatives increases the risk of hip fracture after adjustment for age, gender and multimorbidity level. Fall risk-increasing drugs, high age, female gender and multimorbidity level, can be used to identify high-risk patients who could benefit from a medication review to reduce the risk of hip fracture.

Association between fee-for-service expenditures and morbidity burden in primary care

BACKGROUND

In primary care, fee-for-services (FFS) tariffs are often based on political negotiation rather than costing systems. The potential for comprehensive measures of patient morbidity to explain variation in negotiated FFS expenditures has not previously been examined.

OBJECTIVES

To examine the relative explanatory power of morbidity measures and related general practice (GP) clinic characteristics in explaining variation in politically negotiated FFS expenditures.

METHODS

We applied a multilevel approach to consider factors that explain FFS expenditures among patients and GP clinics. We used patient morbidity characteristics such as diagnostic markers, multimorbidity casemix adjustment based on resource utilisation bands (RUB) and related GP clinic characteristics for the year 2010. Our sample included 139,527 patients visiting GP clinics.

RESULTS

Out of the individual expenditures, 31.6% were explained by age, gender and RUB, and around 18% were explained by RUB. Expenditures increased progressively with the degree of resource use (RUB0-RUB5). Adding more patient-specific morbidity measures increased the explanatory power to 44%; 3.8-9.4% of the variation in expenditures was related to the GP clinic in which the patient was treated.

CONCLUSIONS

Morbidity measures were significant patient-related FFS expenditure drivers. The association between FFS expenditure and morbidity burden appears to be at the same level as similar studies in the hospital sector, where fees are based on average costing. However, our results indicate that there may be room for improvement of the association between politically negotiated FFS expenditures and morbidity in primary care.

Keep it simple? Predicting primary health care costs with clinical morbidity measures

Models of the determinants of individuals' primary care costs can be used to set capitation payments to providers and to test for horizontal equity. We compare the ability of eight measures of patient morbidity and multimorbidity to predict future primary care costs and examine capitation payments based on them. The measures were derived from four morbidity descriptive systems: 17 chronic diseases in the Quality and Outcomes Framework (QOF); 17 chronic diseases in the Charlson scheme; 114 Expanded Diagnosis Clusters (EDCs); and 68 Adjusted Clinical Groups (ACGs). These were applied to patient records of 86,100 individuals in 174 English practices. For a given disease description system, counts of diseases and sets of disease dummy variables had similar explanatory power. The EDC measures performed best followed by the QOF and ACG measures. The Charlson measures had the worst performance but still improved markedly on models containing only age, gender, deprivation and practice effects. Comparisons of predictive power for different morbidity measures were similar for linear and exponential models, but the relative predictive power of the models varied with the morbidity measure. Capitation payments for an individual patient vary considerably with the different morbidity measures included in the cost model. Even for the best fitting model large differences between expected cost and capitation for some types of patient suggest incentives for patient selection. Models with any of the morbidity measures show higher cost for more deprived patients but the positive effect of deprivation on cost was smaller in better fitting models.

Can gender difference in prescription drug use be explained by gender-related morbidity?: a study on a Swedish population during 2006

Background

It has been reported that there is a difference in drug prescription between males and females. Even after adjustment for multi-morbidity, females tend to use more prescription drugs compared to males. In this study, we wanted to analyse whether the gender difference in drug treatment could be explained by gender-related morbidity.

Methods

Data was collected on all individuals 20 years and older in the county of Östergötland in Sweden. The Johns Hopkins ACG Case-Mix System was used to calculate individual level of multi-morbidity. A report from the Swedish National Institute of Public Health using the WHO term DALY was the basis for gender-related morbidity. Prescription drugs used to treat diseases that mainly affect females were excluded from the analyses.

Results

The odds of having prescription drugs for males, compared to females, increased from 0.45 (95% confidence interval (CI) 0.44-0.46) to 0.82 (95% CI 0.81-0.83) after exclusion of prescription drugs that are used to treat diseases that mainly affect females.

Conclusion

Gender-related morbidity and the use of anti-conception drugs may explain a large part of the difference in prescription drug use between males and females but still there remains a difference between the genders at 18%. This implicates that it is of importance to take the gender-related morbidity into consideration, and to exclude anti-conception drugs, when performing studies regarding difference in drug use between the genders.

Frequency of metabolic syndrome and 25-hydroxyvitamin D3 levels in patients with non-alcoholic fatty liver disease

AIM

It is known that insulin resistance has an important role in the pathogenesis of non-alcoholic fatty liver disease (NAFLD) and that serum 25-hidroksivitamin D3 [25-(OH)D] levels are found low in the presence of insulin resistance. Metabolic syndrome (MetS) is characterized by insulin resistance. The purpose of the present study was to determine the levels of 25-(OH)D and the frequency of MetS in patients with NAFLD, and to evaluate the association of 25-(OH)D with the histology of NAFLD and metabolic parameters.

METHOD

Sixty-three patients with NAFLD confirmed by liver biopsy (29 females and 34 males, mean age 42.70±9.82 years) and 46 healthy controls (16 females and 30 males, mean age 37.54±8.56 years) were included in the study. International Diabetes Federation criteria were used for MetS diagnosis. Insulin resistance was determined according to the Homeostasis Model of Assessment (HOMA-IR) method. The groups were compared for 25-(OH)D levels and MetS frequencies. Correlation analysis was used to evaluate relationships between 25-(OH)D and metabolic parameters and/or NAFLD histology.

RESULTS

25-(OH)D levels were lower in the NAFLD group compared to the control group (36.06±13.07 ng/mL vs. 51.19±23.45 ng/mL, respectively, P<0.01), while MetS frequency was higher (66.7% vs. 15.2%, P<0.01). In the NAFLD group, 25-(OH)D levels were negatively correlated with non-alcoholic steatohepatitis scores and HOMA-IR (r=-0.317, P=0.011 and r=-0.437, P=0.001, respectively).

CONCLUSION

The present study demonstrated higher frequency of MetS and lower levels of 25-(OH)D in patients with NAFDL, and a negative association of 25-(OH)D levels with non-alcoholic steatohepatitis scores and insulin resistance.

Resources allocation and health care needs in diabetes care in Danish GP clinics

BACKGROUND

In several countries, morbidity burdens have prompted authorities to change the system for allocating resources among patients from a demographic-based to a morbidity-based casemix system. In Danish general practice clinics, there is no morbidity-based casemix adjustment system.

AIM

The aim of this paper was to assess what proportions of the variation in fee-for-service (FFS) expenditures are explained by type 2 diabetes mellitus (T2DM) patients' co-morbidity burden and illness characteristics.

METHODS AND DATA

We use patient morbidity characteristics such as diagnostic markers and co-morbidity casemix adjustments based on resource utilisation bands and FFS expenditures for a sample of 6706 T2DM patients in 59 general practices for the year 2010. We applied a fixed-effect approach.

RESULTS

Average annual FFS expenditures were approximately 398 euro per T2DM patient. Expenditures increased progressively with the patients' degree of co-morbidity and were higher for patients who suffered from diagnostic markers. A total of 17-25% of the expenditure variation was explained by age, gender and patients' morbidity patterns.

CONCLUSION

T2DM patient morbidity characteristics are significant patient related FFS expenditure drivers in diabetes care. To address the specific health care needs of T2DM patients in GP clinics, our study indicates that it may be advisable to introduce a morbidity based casemix adjustment system.

Distance to hospital and socioeconomic status influence secondary health care use

OBJECTIVE

The aim of this study was to investigate how distance to hospital and socioeconomic status (SES) influence the use of secondary health care (SHC) when taking comorbidity into account.

DESIGN AND SETTING

A register-based study in Östergötland County.

SUBJECTS

The adult population of Östergötland County.

MAIN OUTCOME MEASURES

Odds of SHC use in the population and ates of SHC use by patients were studied after taking into account comorbidity level assigned using the Adjusted Clinical Groups (ACG) Case-Mix System. The baseline for analysis of SES was individuals with the lowest education level (level 1) and the lowest income (1st quartile).

RESULTS

The study showed both positive and negative association between SES and use of SHC. The risk of incurring SHC costs was 12% higher for individuals with education level 1. Individuals with income in the 2nd quartile had a 4% higher risk of incurring SHC costs but a 17% lower risk of emergency department visits. Individuals with income in the 4th quartile had 9% lower risk of hospitalization. The risk of using SHC services for the population was not associated with distance to hospital. Patients living over 40 km from hospital and patients with higher SES had lower use of SHC services.

CONCLUSIONS

It was found that distance to hospital and SES influence SHC use after adjusting for comorbidity level, age, and gender. These results suggest that GPs and health care managers should pay a higher degree of attention to this when planning primary care services in order to minimize the potentially redundant use of SHC.

Licit prescription drug use in a Swedish population according to age, gender and socioeconomic status after adjusting for level of multi-morbidity

Background

There is a great variability in licit prescription drug use in the population and among patients. Factors other than purely medical ones have proven to be of importance for the prescribing of licit drugs. For example, individuals with a high age, female gender and low socioeconomic status are more likely to use licit prescription drugs. However, these results have not been adjusted for multi-morbidity level. In this study we investigate the odds of using licit prescription drugs among individuals in the population and the rate of licit prescription drug use among patients depending on gender, age and socioeconomic status after adjustment for multi-morbidity level.

Methods

The study was carried out on the total population aged 20 years or older in Östergötland county with about 400 000 inhabitants in year 2006. The Johns Hopkins ACG Case-mix was used as a proxy for the individual level of multi-morbidity in the population to which we have related the odds ratio for individuals and incidence rate ratio (IRR) for patients of using licit prescription drugs, defined daily doses (DDDs) and total costs of licit prescription drugs after adjusting for age, gender and socioeconomic factors (educational and income level).

Results

After adjustment for multi-morbidity level male individuals had less than half the odds of using licit prescription drugs (OR 0.41 (95% CI 0.40-0.42)) compared to female individuals. Among the patients, males had higher total costs (IRR 1.14 (95% CI 1.13-1.15)). Individuals above 80 years had nine times the odds of using licit prescription drugs (OR 9.09 (95% CI 8.33-10.00)) despite adjustment for multi-morbidity. Patients in the highest education and income level had the lowest DDDs (IRR 0.78 (95% CI 0.76-0.80), IRR 0.73 (95% CI 0.71-0.74)) after adjustment for multi-morbidity level.

Conclusions

This paper shows that there is a great variability in licit prescription drug use associated with gender, age and socioeconomic status, which is not dependent on level of multi-morbidity.

Quantifying morbidity burdens and medical utilization of children with intellectual disabilities in Taiwan: a nationwide study using the ACG case-mix adjustment system

The purpose of this study was to quantify morbidity burdens of children with intellectual disability (ID) and to examine its association with total medical utilization and expenditure on a national basis in Taiwan. People under 18 years of age that had been continuously enrolled in the National Health Insurance (NHI) between year 2008 and 2010 were selected from one million randomly-sampled NHI beneficiaries. The Johns Hopkins Adjusted Clinical Group (ACG) System was applied to evaluate an individual's morbidity burden using 2008-2010 claims data, including age, sex, diagnosis, pharmacy, ambulatory, and inpatient utilization and expenditure (in New Taiwan Dollars, NTDs). The ID prevalence rate was 0.69% for people aged under 18. People with ID could be assigned to 20 mutually exclusive ACGs and to five simplified morbidity categories: healthy (0.1%), low (1.5%), moderate (31.9%), high (44.0%), and very high (22.4%). People with ID had more per capita visits (108.4 vs. 51.5, p<0.001), hospital admission (27.7% vs. 13.1%, p<0.001), pharmacy (NTD 21,069 vs. 4983, p<0.001) and total expenditure (NTD 144,962 vs. 29,764, p<0.001) than those without ID over 3 years. Those who assigned to the high-morbid categories cost more in ambulatory and inpatient services than those with low to moderate morbidities. In conclusion, the morbidity burdens of people with ID can be quantified by the ACG System based on readily available data. Regularly evaluating morbidity burdens and medical utilization has particular relevance for planning high-quality and efficient care. People's disabilities and comorbid illnesses shall be treated by integrated multidisciplinary teams.

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.

Impact of comorbidity on the individual's choice of primary health care provider

OBJECTIVE. This study examined whether age, gender, and comorbidity were of importance for an individual's choice of listing with either a public or a private primary health care (PHC) practice. DESIGN AND SETTING. The study was a register-based closed cohort study in one private and one public PHC practice in Blekinge County in southern Sweden. Subjects. A cohort (12 696 individuals) was studied comprising all those listed with the public or private PHC practice on 1 October 2005 who were also listed with the public PHC practice on 1 October 2004. MAIN OUTCOME MEASURES. The listing/re-listing behaviour of the population in this cohort was studied at two points in time, 1 October 2005 and 1 October 2006, with respect to age, gender, and comorbidity level as measured by the ACG Case-Mix system. RESULTS. Individuals listed with the public practice both on 1 October 2005 and one year later were significantly older, were more often females, and had a higher comorbidity level than individuals listed with the private practice. Individuals with a higher comorbidity level were more likely to re-list or to stay listed with the public practice. CONCLUSIONS. This study shows that the probability of choosing a public instead of private PHC provider increased with higher age and comorbidity level of the individuals. It is suggested that using a measure of comorbidity can help us understand more about the chronically ill individual's choice of health care provider. This would be of importance when health care policy-makers decide on reimbursement system or organization of PHC.

Evaluation of guideline-concordant care for bipolar disorder among privately insured youth

OBJECTIVE

To describe and quantify the prevalence of treatments and services for youth with bipolar disorder and to assess whether concordance with treatment guidelines is associated with inpatient hospitalization and emergency department visits.

METHOD

Insurance claims of 423 privately insured youth (ages 6-18) having prescription drug coverage and diagnosed with bipolar disorder were examined from the 2000-2001 Thomson Medstat MarketScan database, a national (US) dataset. Treatments and services were examined for the 6 months following the index bipolar disorder diagnosis, defined as the first diagnosis after a diagnosis-free period of 6 months.

RESULTS

The majority of youth did not receive guideline-concordant care. Only 26% (n = 109) received a mood stabilizer or antipsychotic, as recommended, within 1 month of a bipolar diagnosis. Antidepressant monotherapy, which is contraindicated in therapeutic guidelines, was observed for 33% (n = 140) of youth. Less than 40% of youth received adjunctive psychotherapy. Guideline concordance was statistically significantly related to a lower likelihood of an inpatient hospitalization or an emergency department visit.

CONCLUSIONS

Although deviation from guidelines may be warranted in some cases due to individual variation and patient complexity or patient and/or family preferences, these findings suggest that evidence-based guidelines are not followed in clinical practice. Incorporation of guideline-concordant care may increase the likelihood of overall better quality of care and presage better long-term outcomes for youths diagnosed with bipolar disorder.

Validation of ACG Case-mix for equitable resource allocation in Swedish primary health care

Background

Adequate resource allocation is an important factor to ensure equity in health care. Previous reimbursement models have been based on age, gender and socioeconomic factors. An explanatory model based on individual need of primary health care (PHC) has not yet been used in Sweden to allocate resources. The aim of this study was to examine to what extent the ACG case-mix system could explain concurrent costs in Swedish PHC.

Methods

Diagnoses were obtained from electronic PHC records of inhabitants in Blekinge County (approx. 150,000) listed with public PHC (approx. 120,000) for three consecutive years, 2004-2006. The inhabitants were then classified into six different resource utilization bands (RUB) using the ACG case-mix system. The mean costs for primary health care were calculated for each RUB and year. Using linear regression models and log-cost as dependent variable the adjusted R² was calculated in the unadjusted model (gender) and in consecutive models where age, listing with specific PHC and RUB were added. In an additional model the ACG groups were added.

Results

Gender, age and listing with specific PHC explained 14.48-14.88% of the variance in individual costs for PHC. By also adding information on level of co-morbidity, as measured by the ACG case-mix system, to specific PHC the adjusted R² increased to 60.89-63.41%.

Conclusion

The ACG case-mix system explains patient costs in primary care to a high degree. Age and gender are important explanatory factors, but most of the variance in concurrent patient costs was explained by the ACG case-mix system.

Quantifying morbidities by Adjusted Clinical Group system for a Taiwan population: a nationwide analysis

Background

The Adjusted Clinical Group (ACG) system has been used in measuring an individual's and a population's morbidities. Although all required inputs for running the ACG system are readily available, patients' morbidities and their associations to health care utilizations have been rarely studied in Taiwan. Therefore, the objective of this study was using the ACG system to quantify morbidities for Taiwanese population and to examine their relationship to ambulatory utilizations and costs.

Methods

This secondary analysis examined claims data for ambulatory services provided to 2.71 million representative Taiwanese in 2002 and 2003. People were grouped by the ACG system according to age, gender, and all ambulatory diagnosis codes in a given year. The software collapses the full set of ACGs into six morbidity categories (Non-users, Healthy, Low-morbidity, Moderate-, High- and Very-high) termed Resource Utilization Bands (RUBs). Each ACG was assigned a relative weight (RW), which was calculated as the ratio of mean ambulatory cost for each ACG to that for the overall. The distribution of morbidities was compared between years 2002 and 2003. The consistency of the distributions of visits, costs, and RWs of each ACG were examined for a two-year period. The relationship between people's morbidities and their ambulatory utilizations and costs was assessed.

Results

Ninety-eight percent of the subjects were correctly assigned to ACGs. Except for non-users (7.9 ~ 8.3%), most subjects were assigned to ACGs of acute and minor diseases and ACGs of moderate-to-high-morbid chronic diseases. The distributions of ACG-based morbidities were highly consistent (r = 0.949, p < 0.001) between 2002 and 2003. The ACG-specific visits (r = 0.955, p < 0.001), costs (r = 0.966, p < 0.001) and RWs (r = 0.991, p < 0.001) were correlated across two years. People grouped to the high-morbid ACGs had more visits and costs than those grouped to the low-morbid ACGs. Forty-six percent of the total ambulatory costs were spent by eighteen percent of the population, who were grouped to the High- and Very-high-morbidity RUBs.

Conclusion

This study demonstrated the feasibility, validity, and reliability of using the ACG system to measure morbidities in a Taiwan population and to explain their associations with ambulatory utilizations and costs for the whole country.

Explanatory ability of the ACG system regarding the utilization and expenditure of the national health insurance population in Taiwan--a 5-year analysis

BACKGROUND

The adjusted clinical group (ACG) is a diagnosis-based case-mix adjustment system, which has been widely evaluated in several countries other than Taiwan. The aim of this study was to assess the performance of the ACG system on the National Health Insurance (NHI) population in Taiwan.

METHODS

We conducted longitudinal data analysis using the claims data of 1% of randomly sampled NHI enrollees from 2000 to 2004. The ACG software was used to assign each individual to 1 ACG category based on age, gender and aggregating diagnoses in each year from 2000 to 2004, respectively. The ACG distribution patterns and their relationships to expenditure were examined. Explanatory ability as measured by adjusted R2 of the ACG system for same-year and next-year ambulatory and inpatient expenditure were examined by multivariate regression models for each year.

RESULTS

The quality of NHI claim data was satisfactory in that 98.1% of the population could be assigned to ACG categories. The population's ACG patterns were substantially consistent but unequally distributed across the 5 years. Eighty percent of NHI expenditure were spent on people assigned to 21 ACGs. The explanatory abilities of individual's ACG and its components with respect to the variance of same-year and next-year 99% truncated visits, ambulatory expenditure, inpatient expenditure, and total NHI expenditure were quite consistent across years and were superior to age and gender. The explanatory performance was better for ambulatory than inpatient expenditure and was comparable to the statistics demonstrated in other countries.

CONCLUSION

The ACG system worked well for Taiwanese ambulatory visits and expenditure across years. Health care authorities can introduce the ACG system to quantify the population's morbidity burdens and medical needs.

Illness severity and total visits in family medicine

OBJECTIVE

The purpose of this study was to estimate the independent effect of clinical severity on visit utilization by family medicine patients so that disease management programmes can be targeted accurately and immediately towards patients most likely to benefit from them.

DESIGN

A convenience sample of 698 primary care patients was analysed. All patients had been referred to a medical specialist. Utilization of all types of medical services including laboratory, radiology and ancillary services was used to classify patients as high-utilizers (the top 20%) or not high-utilizers. Patients were stratified into three severity categories based on point scores assigned to specific diseases. The diagnoses included in the Charlson severity index were used to score each patient and the Charlson point scores were used to measure severity. The odds of being a high-utilizer were adjusted for severity category and demographic variables.

RESULTS

Severity was independently related to the odds of being a high-user (adjusted odds ratio = 2.7 for severity = 1 and 5.7 for severity = 2, with the reference category being severity = 0). Age was related to high-use in univariate analyses but not in multivariate analyses.

CONCLUSIONS

Case management programmes in primary care practices should consider using disease severity to identify cases. Severity data can be abstracted by medical secretaries who review narrative problem lists as well as billing codes.

Evaluating the relative clinical efficiency of family medicine satellite clinics

A study was conducted to evaluate the impact of decentralization in family medicine clinic services by comparing utilization of services in 3 satellite clinics to utilization patterns of patients served at the hub clinic. It was expected that a hub clinic would be more efficient than satellite clinics because of tighter administrative control and economies of scale. Stable chronically ill patients were used as a homogeneous tracer condition in a secondary analysis of 12 months of archival data. Three types of service use were analyzed: laboratory visits, x-ray visits, and visits to specialists. Among 1,410 stable chronically ill family medicine patients, 303 (21.5%) had 10 more laboratory visits, 222 (15.7%) had 2 or more x-ray visits, and 617 (43.8 %) had 2 or more visits to a specialist. Patients at one of the satellite clinics had greater odds of receiving 2 or more x-rays but lower odds of receiving 10 or more laboratory visits, in comparison with the hub clinic. Patients at the other 2 satellite clinics did not differ from hub patients for any type of service use. Overall, stable chronically ill patients were treated with approximately equal clinical efficiency in our satellite clinics. Some differences in efficiency may occur in some clinics, but these appear to be idiosyncratic rather than due to clinic size or distance from central control.

[Can primary care physicians use the ICD-9-MC? An evaluation of the quality of diagnosis coding in computerized medical records]

OBJECTIVES

To determine the completeness and accuracy of ICD-9-CM codes allocated by primary health care physicians in their computerized medical records and evaluate the effects of improvement procedures.

METHODS

The codes of 87,806 patients assigned to 56 primary care physicians in the Basque National Health Service in Spain, were evaluated 3 times over a 1-year period according to the following criteria: correspondence to a valid ICD-9-CM code, agreement between diagnosis and code, and the percentage of visits with an unspecified reason for consultation. Finally, the mean number of unique diagnoses and rates of diagnostic groups in the 84,136 patients that remained with the same physician for a minimum of 6 months were contrasted with another previously registered morbidity database. Two interventions were performed to improve coding: detected errors were corrected centrally and physicians were assessed and given information on their individual results.

RESULTS

Diagnoses lacking an ICD-9-DIC code decreased from 59% in the first assessment to 2% at the end of the study period. The percentage of coding mistakes (discrepancies in episode diagnosis and ICD-9-CM code) decreased from 17% to 3%. The mean annual number of diagnoses per patient was slightly lower than that in the reference database (2.26 versus 2.43). The same result was observed in the rates of some diagnostic groups.

CONCLUSIONS

Primary care doctors can achieve a high degree of quality in ICD-9-CM diagnosis coding. Implementing procedures for evaluating coding, rectifying mistakes, and providing information to physicians markedly improved the initial results.

[Retrospective application of adjusted clinical groups (ACGs) at a primary care centre]

OBJECTIVE

To evaluate retrospectively the application of adjusted clinical groups (ACGs) at a primary care centre.

DESIGN

Descriptive, retrospective examination.

SETTING

Urban.

PARTICIPANTS

All patients seen by the team in 2000 were included in the study. Those who moved or died during the study period were excluded.

MAIN MEASUREMENTS

Universal variables (age and sex), dependant variables (visits, episodes, and costs), and case-mix or comorbidity variables (ACGs 2.0) were measured. The model of cost per patient was established by distinguishing the costs of the PCC from the variables. The ICPC was converted to the ICD-9-CM and a multiple linear regression analysis was performed to predict the models.

RESULTS

The total number of patients studied was 15 983, with an average of 5.0+/-3.2 episodes and 8.0+/-7.7 visits during the year. The power of explanation of the variability of the classification between the number of episodes was 71.9%; of the visits, 50.0% (with refinement, 56.3%); and cost, 30.2% (with refinement, 55.0%) (P=.000).

CONCLUSIONS

ACGs were shown to be an acceptable system for classifying patients according to the consumption of resources used in primary care. In addition, the methodology used was adequate for integrating clinical and economic information at the PCC.

[Comparative study at 4 health centres of efficiency, measured on the basis of ambulatory care groups]

OBJECTIVE

To measure efficiency in the use of resources for the care lists of four primary care centres (PCC), by using ambulatory care Groups (ACGs).

DESIGN

Retrospective, observational study.

SETTING

Four PC teams.

PARTICIPANTS

All patients attended during 2003.

MEASUREMENTS

Dependent variables (costs per patient, between medical lists [family medicine, paediatrics] and PCCs) and case load variables. The model of costs for each patient was set by differentiating the semi-fixed and variable costs. The efficiency index (EI) was set as the quotient between the observed real cost and the expected cost on the basis of ACG distribution, by indirect standardization. The study population was 62,311 patients seen, with an average of 4.8+/-3.2 episodes/patient/year.

MAIN RESULTS

The total health care cost reached 24,135,236.62 euro, of which 65.2% was for prescription, 28.9% for semi-fixed costs, and 2.9% for cost of specialist referrals. The average total cost per patient/year was 387.34 euro+/-145.87 euro (average relative weight). The EI for each centre was: 0.93 (95% CI, 0.85-1.01), 0.97 (95% CI, 0.89-1.05), 1.04 (95% CI, 0.96-1.12), and 1.05 (95% CI, 0.97-1.13), P < .0001. In addition, differences between the medical lists (rank, 0.63-1.56) and between the paediatrics lists (rank, 0.73-1.26) were found (P = .005).

CONCLUSIONS

The ACGs enabled us to estimate the efficiency of our PCCs and care lists. Efficiency cannot be isolated from other dimensions of the quality of health care delivery. Study of the EI improved our understanding of the profile of professionals and health centres.

Validating the Johns Hopkins ACG Case-Mix System of the elderly in Swedish primary health care

Background

Individualbased measures for comorbidity are of increasing importance for planning and funding health care services. No measurement for individualbased healthcare costs exist in Sweden. The aim of this study was to validate the Johns Hopkins ACG Case-Mix System's predictive value of polypharmacy (regular use of 4 or more prescription medicines) used as a proxy for health care costs in an elderly population and to study if the prediction could be improved by adding variables from a population based study i.e. level of education, functional status indicators and health perception.

Methods

The Johns Hopkins ACG Case-Mix System was applied to primary health care diagnoses of 1402 participants (60–96 years) in a cross-sectional community based study in Karlskrona, Sweden (the Swedish National study on Ageing and Care) during a period of two years before they took part in the study. The predictive value of the Johns Hopkins ACG Case-Mix System was modeled against the regular use of 4 or more prescription medicines, also using age, sex, level of education, instrumental activity of daily living- and measures of health perception as covariates.

Results

In an exploratory biplot analysis the Johns Hopkins ACG Case-Mix System, was shown to explain a large part of the variance for regular use of 4 or more prescription medicines. The sensitivity of the prediction was 31.9%, whereas the specificity was 88.5%, when the Johns Hopkins ACG Case-Mix System was adjusted for age. By adding covariates to the model the sensitivity was increased to 46.3%, with a specificity of 90.1%. This increased the number of correctly classified by 5.6% and the area under the curve by 11.1%.

Conclusion

The Johns Hopkins ACG Case-Mix System is an important factor in measuring comorbidity, however it does not reflect an individual's capability to function despite a disease burden, which has importance for prediction of comorbidity. In this study we have shown that information on such factors, which can be obtained from short questionnaires increases the probability to correctly predict an individual's use of resources, such as medications.

Medida de los pesos relativos del coste de la asistencia como efecto de la aplicación retrospectiva de los adjusted clinical groups en atención primaria

OBJECTIVE

The objective of the study is to obtain the cost's relative average weights of the assistance with the retrospective application of the Adjusted Clinical Groups (ACG's) in four teams of Primary Care with an attended population in the habitual clinical practice situation.

METHODS

Descriptive study of retrospective character. It was included in the study all attended patients by four teams of Primary Care during year 2003. The main measures were: universal variables (age and gender), dependents (visits and costs) and casuistic and co morbidity. The model of cost per each patient was established differencing the fix costs and the variable ones. Was effected a multiple lineal regression analysis for the prediction of models. The relative cost of each ACG was obtained dividing the average cost of each category among the average cost of each population of reference.

RESULTS

The total number of the studied patients was 62,311 (intensity of use: 76.7%), with an average 4.8 +/- 3.2 episodes and 7.8 +/- 7.5 visits/patient/year. The distribution of costs was 24,135,236.41 euro, 28.9% for fix. The total unitary cost per visit/year was 49.62 +/- 24.71 euro and the average of the total cost per patient/year 387.34 +/- 145.87 euro (relative weights of reference). The explicative power of the classification of ACG was 50.1% in visits and 54.9% for total costs.

CONCLUSIONS

The ACG are an acceptable system of classification of patients in situation of habitual clinic practice. In case results were confirmed will make possible an improvement in the practice application of ACG as a possible tool for the clinical management in Primary Care centers.

Adjusted Clinical Groups (ACGs) explain the utilization of primary care in Spain based on information registered in the medical records: A cross-sectional study

BACKGROUND

Previous studies have shown the validity of Adjusted Clinical Groups (ACGs) in the primary care setting, but the absence of administrative databases is a problem for the implementation of this system.

OBJECTIVES

To assess the validity of physicians' notes in computerized clinical records for the implementation of ACGs, and to determine the ability of the ACGs system to explain the use of primary care resources in real conditions of the daily practice.

RESEARCH DESIGN

Cross-sectional study.

SUBJECTS

All patients who were continuously assigned to 56 physicians from public primary health care centers in the Bizkaia Basque Country (Spain) over at least a 6-month period were included.

MEASURES

Patients were classified by means of the ACGs system using the ICD-9-CM diagnostic codes according to three scenarios: (1) those annotated by the physicians in the computerized medical record, (2) codification of computerized medical records diagnoses by the research team, and (3) computerized medical records diagnoses complemented by hospital discharge codes.

RESULTS

The ACGs system explained more than 50% of the variance in visits made to primary care physicians, 25-40% of prescriptions, 25-30% of referrals and requests of laboratory tests, and 14-16% of radiographs. The coefficients of determination remained almost invariable after the addition of hospital diagnoses or correction of coding errors. Fifty-two physicians (93%) registered their patients' diagnosis quite acceptably, whereas only 29 (52%) included this datum in the prescriptions.

CONCLUSIONS

The ACGs system is a useful tool to explain the use of primary care services in a national health care system within the European Union. The implementation of ACGs from the physician's annotations in the computerized medical records is feasible.

Clinical categories of patients and encounter rates in primary health care - a three-year study in defined populations

Background

The objective was to estimate the proportion of inhabitants with a diagnosis-registered encounter with a general practitioner, and to elucidate annual variations of clinical categories of patients in terms of their individual comorbidity.

Methods

A three-year retrospective study of encounter data from electronic patient records, with an annual-based application of the Johns Hopkins Adjusted Clinical Groups (ACG) system. Data were retrieved from every patient with a diagnosis-registered encounter with a GP during the period 2001–2003 at 13 publicly managed primary health care centres in Blekinge county, southeastern Sweden, with about 150000 inhabitants. Main outcome measures: Proportions of inhabitants with a diagnosis-registered encounter, and ranges of the annual proportions of categories of patients according to ACGs.

Results

The proportion of inhabitants with a diagnosis-registered encounter ranged from about 64.0% to 90.6% for the primary health care centres, and averaged about 76.5% for all inhabitants. In a three-year perspective the average range of categories of patients was about 0.4% on the county level, and about 0.9% on the primary health care centre level. About one third of the patients each year had a constellation of two or more types of morbidity.

Conclusion

About three fourths of all inhabitants had one or more diagnosis-registered encounters with a general practitioner during the three-year period. The annual variation of categories of patients according to ACGs was small on both the county and the primary health care centre level. The ACG system seems useful for demonstrating and predicting various aspects of clinical categories of patients in Swedish primary health care.

The importance of comorbidity in analysing patient costs in Swedish primary care

Background

The objective was to explore the usefulness of the morbidity risk adjustment system Adjusted Clinical Groups^® (ACG), in comparison with age and gender, in explaining and estimating patient costs on an individual level in Swedish primary health care. Data were retrieved from two primary health care centres in southeastern Sweden.

Methods

A cross-sectional observational study. Data from electronic patient registers from the two centres were retrieved for 2001 and 2002, and patients were grouped into ACGs, expressing the individual combination of diagnoses and thus the comorbidity. Costs per patient were calculated for both years in both centres. Cost data from one centre were used to create ACG weights. These weights were then applied to patients at the other centre. Correlations between individual patient costs, age, gender and ACG weights were studied. Multiple linear regression analyses were performed in order to explain and estimate patient costs.

Results

The variation in individual patient costs was substantial within age groups as well as within ACG weight groups. About 37.7% of the individual patient costs could be explained by ACG weights, and age and gender added about 0.8%. The individual patient costs in 2001 estimated 22.0% of patient costs in 2002, whereas ACG weights estimated 14.3%.

Conclusion

ACGs was an important factor in explaining and estimating individual patient costs in primary health care. Costs were explained to only a minor extent by age and gender. However, the usefulness of the ACG system appears to be sensitive to the accuracy of classification and coding of diagnoses by physicians.

Predicting persistently high primary care use

PURPOSE

We wanted to identify risk factors for persistently high use of primary care.

METHODS

We analyzed outpatient office visits to practitioners in family medicine, general internal medicine, general pediatrics, and obstetrics for 1997-1999 among patients in a small Midwestern city covered by a fee-for-service insurance plan with no co-payments for physician visits and no requirement for referral to specialty care. Logistic regression was used to predict which patients with 10 or more primary care visits in 1997 would repeat high use in 1998 based on demographic and diagnostic categories (adjusted clinical groups [ACGs]). A confirmatory data set (high primary care use in 1998 persistent into 1999) was used to evaluate the model.

RESULTS

Two percent of the 54,074 patients had 10 or more primary care visits in 1997, and of these, almost 19% had 10 or more visits in the next year. Among adults, 4 ambulatory diagnosis groups (ADGs) were simultaneously positive predictors of repeated high primary care visits: unstable chronic medical conditions, see and reassure conditions, minor time-limited psychosocial conditions, and minor signs and symptoms. Meanwhile, pregnancy was negatively associated. The area under the receiver operating characteristic (ROC) curve was 0.794 for adults in the developmental data set and 0.752 in the confirmatory data set, indicating a moderately accurate assessment. A satisfactory model was not developed for pediatric patients.

CONCLUSIONS

Many persistently high primary care users appear to be overserviced but underserved, with underlying problems not addressed by a medical approach. Some may benefit from psychosocial support, whereas others may be good candidates for disease management interventions.

Types of morbidity and categories of patients in a Swedish county. Applying the Johns Hopkins Adjusted Clinical Groups System to encounter data in primary health care

OBJECTIVE

To elucidate types of morbidity and categories of patients in a large population.

DESIGN

A one-year retrospective study of encounter data from electronic patient record databases in primary health care, with application of the Johns Hopkins Adjusted Clinical Groups System.

SETTING

Blekinge County Council, southeastern Sweden, with 149 552 inhabitants.

SUBJECTS

All patients with a diagnosis-registered encounter with a GP in 2002 at 13 publicly managed PHC centres.

MAIN OUTCOME MEASURES

Anonymous identification number, age, gender, type of morbidity (Aggregated Diagnostic Groups), and category of patient (Adjusted Clinical Groups).

RESULTS

About 45% of the county's inhabitants had at least one diagnosis-registered encounter with a GP during the year. The most common types of morbidity were "time limited" (24.0% of all types), "likely to recur" (19.6%), and "signs/symptoms" (19.0%). About 33.3% of all patients had one and only one time-limited condition, about 16.8% had one and only one recurring condition, and about 12.1% of the patients had only a chronic condition.

CONCLUSION

Types of morbidity in primary health care are dominated by nearly equal proportions of "time limited", "likely to recur", "chronic", and "signs/symptoms". The predominant categories of patients are those with only one type of morbidity, while about one-third of the patients had a constellation of two or more types of morbidity during a one-year period.

[Factors conditioning primary care services utilization. Empirical evidence and methodological inconsistencies]

INTRODUCTION

In Spain, the degree and characteristics of primary care services utilization have been the subject of analysis since at least the 1980s. One of the main reasons for this interest is to assess the extent to which utilization matches primary care needs. In fact, the provision of an adequate health service for those who most need it is a generally accepted priority.

FACTORS CONDITIONING USE

The evidence shows that individual characteristics, mainly health status, are the factors most closely related to primary care utilization. Other personal characteristics, such as gender and age, could act as modulators of health care need. Some family and/or cultural variables, as well as factors related to the health care professional and institutions, could explain some of the observed variability in primary care services utilization. Socioeconomic variables, such as income, reveal a paradox. From an aggregate perspective, income is the main determinant of utilization as well as of health care expenditure. When data are analyzed for individuals, however, income is not related to primary health utilization.

METHODOLOGICAL INCONSISTENCIES

The situation is controversial, with methodological implications and, above all, consequences for the assessment of the efficiency in primary care utilization. Review of the literature reveals certain methodological inconsistencies that could at least partly explain the disparity of the empirical results. Among others, the following flaws can be highlighted: design problems, measurement errors, misspecification, and misleading statistical methods.Some solutions, among others, are quasi-experiments, the use of large administrative databases and of primary data sources (design problems); differentiation between types of utilization and between units of analysis other than consultations, and correction of measurement errors in the explanatory variables (measurement errors); consideration of relevant explanatory variables (misspecification); and the use of multilevel models (statistical methods).

[Models to explain and predict medical case-loads: their use in calculating the maximum family medicine list that allows at least ten minutes per consultation]

OBJECTIVE

To calculate the maximum family medicine list that gives at least ten minutes per consultation.Design. Transversal.

SETTING

Three health centres.

SUBJECTS

45 826 inhabitants.

MEASUREMENTS

We used the appointments made at three centres to calculate the annual time employed per patient and we adjusted it to allocate a minimum of ten minutes per consultation. We established a cubic regression model to predict the mean case-load per age of patient in general medicine and calculated the maximum list if 70% of the working day were dedicated to care. The results contrasted two centres with greater nursing involvement and one with less. We showed the R2 coefficients. We calculated the maximum lists for the health centres of Navarra and showed them in five clusters worked out on the basis of the percentage of patients >=65.

RESULTS

Age explained 86.1% of variability in mean case-load at each age (84% in children and 93.5% in adults). According to the mean percentage of those >=65 years old, the average maximum lists for centres with more or less nursing involvement are as follows: 7.0%>=65 (2025 and 1989); 14.0% (1834 and 1715); 21.2% (1691 and 1558); 27.0% (1648 and 1460), 34.0% (1560 and 1340).

CONCLUSION

To a great extent, age explains the variability in case-load and lets us calculate the maximum number of patients on the list that still ensures a minimum time for each consultation.

Performance of diagnosis-based risk adjustment measures in a population of sick Australians

OBJECTIVE

Australia is beginning to explore 'managed competition' as an organising framework for the health care system. This requires setting fair capitation rates, i.e. rates that adjust for the risk profile of covered lives. This paper tests two US-developed risk adjustment approaches using Australian data.

METHODS

Data from the 'co-ordinated care' dataset (which incorporates all service costs of 16,538 participants in a large health service research project conducted in 1996-99) were grouped into homogenous risk categories using risk adjustment 'grouper software'. The grouper products yielded three sets of homogenous categories: Diagnostic Groups and Diagnostic cost Groups. A two-stage analysis of predictive power was used: probability of any service use in the concurrent year, next year and the year after (logistic regression) and, for service users, a regression of logged cost of service use. The independent variables were diagnosis gender, a SES variable and the

RESULTS

Age, gender and diagnosis-based risk adjustment measures explain around 40-45% of variation in costs of service use in the current year for untrimmed data (compared with around 15% for age and gender alone). Prediction of subsequent use is much poorer (around 20%). Using more information to assign people to risk categories generally improves prediction.

CONCLUSIONS

Predictive power of diagnosis-base risk adjusters on this Australian dataset is similar to that found in

IMPLICATIONS

Low predictive power carries policy risks of cream skimming rather than managing population health and care. Competitive funding models with risk adjustment on prior year experience could reduce system efficiency if implemented with current risk adjustment technology.

Patient based 'burden-of-illness' in Swedish primary health care. Applying the Johns Hopkins ACG case-mix system in a retrospective study of electronic patient records

Patients from one municipality in Sweden utilizing primary health care (PHC) during 1998 and 1999 have been categorized into 81 groups. The groups show each patient's own case-mix in terms of illness. Grouping was carried out using the case-mix instrument adjusted clinical groups (ACG), developed by the School of Hygiene and Public Health at Johns Hopkins University in Baltimore, USA. The resulting pattern provided a more adequate reflection of the scope of primary care's task than that yielded by diagnoses alone. Changes over time in terms of illness patterns for a population could be described, analysed and assessed from medical and health economic perspectives. One of the conclusions from this study was that the ACG instrument is a relevant tool in describing the outcome of work by the primary health care centre. The ACG is of interest in the improvement of the quality of primary care in Sweden. The ACG should be a driving force in the development of health indices in both national and international comparisons, as a result of its focus on the health status of patients and populations instead of on diagnoses and diseases.

Assessing population health care need using a claims-based ACG morbidity measure: a validation analysis in the Province of Manitoba

OBJECTIVES

To assess the ability of an Adjusted Clinical Group (ACG)-based morbidity measure to assess the overall health service needs of populations. Data Sources/Study Setting. Three population-based secondary data sources: registration and health service utilization data from fiscal year 1995-1996; mortality data from vital statistics reports from 1996-1999; and Canadian census data. The study included all continuously enrolled residents in the universal health care plan in Manitoba.

STUDY DESIGN

Using 60 small geographic areas as the units of analysis, we compared a population-based "ACG morbidity index," derived from individual ACG assignments in fiscal year 1995-1996, with the standardized mortality ratio (ages < 75 years) for 1996-1999. Key variables included a population-based socioeconomic status measure and age- and sex-standardized physician utilization ratios.

DATA EXTRACTION METHODS

The ACGs were assigned based on the complement of diagnoses assigned to persons on physician claims and hospital separation abstracts. The ACG index was created by weighting the ACGs using average health care expenditures.

PRINCIPAL FINDINGS

The ACG morbidity index had a strong positive linear relationship with the subsequent rate of premature death in the small areas of Manitoba. The ACG index was able to explain the majority of the relationships between mortality and both socioeconomic status and physician utilization.

CONCLUSIONS

In Manitoba, ACGs are closely related to premature mortality, commonly accepted as the best single indicator for health service need in populations. Issues in applying ACGs in settings where needs adjustment is a primary objective are discussed.

Assessing comorbidity using claims data: an overview

Comorbidity, additional disease beyond the condition under study that increases a patient's total burden of illness, is one dimension of health status. For investigators working with observational data obtained from administrative databases, comorbidity assessment may be a useful and important means of accounting for differences in patients' underlying health status. There are multiple ways of measuring comorbidity. This paper provides an overview of current approaches to and issues in assessing comorbidity using claims data, with a particular focus on established indices and the SEER-Medicare database. In addition, efforts to improve measurement of comorbidity using claims data are described, including augmentation of claims data with medical record, patient self-report, or health services utilization data; incorporation of claims data from sources other than inpatient claims; and exploration of alternative conditions, indices, or ways of grouping conditions. Finally, caveats about claims data and areas for future research in claims-based comorbidity assessment are discussed. Although the use of claims databases such as SEER-Medicare for health services and outcomes research has become increasingly common, investigators must be cognizant of the limitations of comorbidity measures derived from these data sources in capturing and controlling for differences in patient health status. The assessment of comorbidity using claims data is a complex and evolving area of investigation.

Comparing apples with apples in clinical populations: applications of the adjusted Clinical Group System in British Columbia

This article reviews the Adjusted Clinical Group Case-Mix System and describes how it is being applied in the management of physician services in British Columbia. Developed in the United States for management and research, adjusted clinical groups are used to measure the illness burden and health service needs of individuals and, when aggregated, of populations, by grouping the range of conditions coded on physician claims and hospital care records over a defined time period, typically one year. In Canadian and United States settings, adjusted clinical groups are up to five times more predictive of ambulatory resource use than are age and sex groups alone. The article describes how adjusted clinical groups are being applied to adjust capitation payments for physician groups in British Columbia's Primary Care Demonstration Project and profiles of physician practice activity.

Performance of the ACG case-mix system in two Canadian provinces

BACKGROUND

While the adjusted clinical group (ACG) system has been extensively validated in the United States, its use in other developed nations has been limited. This article examines the performance of the system in 2 Canadian provinces and assesses the extent to which ACGs can account for same-year and next-year health care expenditures.

METHODS

The study population included all residents of Manitoba and British Columbia who were continuously enrolled in the provincial health plans from April 1, 1995, to March 31, 1997. ACGs were assigned through diagnoses from fee-for-service physician claims and hospital separation records. "Physician" costs were calculated from the fee-for-service tariffs, and for Manitobans, "total" costs were also computed by combining physician and hospital costs. Linear regression was used to examine the ability of the ACG system to explain variation in individual costs (truncated at the 99th percentile).

RESULTS

The British Columbia and Manitoba data were generally acceptable, with fewer than 2% rejected diagnoses. Higher costs were associated with both the accumulation of morbidities and their relative severity. For physician costs, the ACG system explained approximately 50% and approximately 25% of the variation in same-year and next-year truncated costs, respectively. For total costs, the system explained approximately 40% and approximately 14% of these respective costs.

CONCLUSIONS

The application of ACGs in Canada is feasible using existing data. The ability of the ACG system to explain variation in costs is similar to that found in US health systems. While application of ACGs in Canada shows promise, further research is required to examine how closely they reflect population morbidity burdens and health care needs.

Prevention in routine general practice: activity patterns and potential promoting factors

BACKGROUND

Primary care physicians have a unique opportunity to deliver preventive services, but a desired level of involvement is not always attained.

METHODS

We analyzed self-reported preventive activity in a stratified random sample of 635 primary care physicians to determine how often they deliver effective interventions for the prevention of cardiovascular diseases, cancer, and acquired immunodeficiency syndrome as well as to assess factors associated with a greater implementation of preventive activity in routine practice.

RESULTS

More than 63% reported to ask about tobacco use or alcohol consumption or to check blood pressure to most of their new patients. On the other hand, only 33% asked about intravenous drug use, 14% about sexually transmitted diseases, and 6% about the number of sexual partners and less than 33% reported to have an appropriate criterion for any periodic preventive activity in routine daily practice. Correlates of high preventive activity included group practice, specific register of preventive activities, participation in the Program of Preventive Activities of the Spanish Society of Community and Family Medicine, and specific nursing consultation.

CONCLUSIONS

Organizational factors could be used to improve preventive activity which is far from being an adequate component of routine general practice especially with regard to human immunodeficiency virus infection and periodic preventive activity for chronic diseases.

[Is it necessary that some patients come to see us so often? Factors associated with primary care use in pediatrics]

OBJECTIVES

To analyze the relationship between pediatric patients morbidity and their level of primary health care services use; and to establish if the patients level of use affects the health promotion and immunization schedule completion.

METHODS

All patients assigned to a pediatric practice of the Basque National Health Service in Astrabudua (Bizkaia, Spain) over a 6-year period were categorized into different utilization patterns according to their age and number of primary care visits (whose principal reason for encounter was different from health promotion activities). Bivariate and multivariate analyses were performed comparing three groups of subjects: 116 consistently high users, 115 consistently low users and 123 patients classified as consistently medium or erratic users. Ambulatory care Groups (ACGs) case-mix system was used to manage pathologies.

RESULTS

High use patients experienced several morbidity types most frequently than low use ones: asthma (OR = 44.7; 95% CI = 5.5-206.1), diseases likely to recurr (OR = 33.5; 95% CI = 8.5-131.6), specialty unstable chronic conditions (OR = 10.8; 95% CI = 2.2-52.8), psychosocial conditions (OR = 5.7; 95% CI = 2.1-15.2), chronic medical stable conditions (OR = 4.0; 95% CI = 1.9-8.6), eye/dental diseases (OR = 3.5; 95% CI = 1.5-8.1). On the other hand, low users were more likely to be lacking completion of the immunization (OR = 3.0; 95% CI = 1.1-8.8) and the well-child care program visits schedules (OR = 4.3; 95% CI = 2.3-8.0).

CONCLUSION

Our data confirm that high utilization, far from being inadequate behavior, is an adequate response to the higher health care needs showed by such patients. Primary care pediatricians should assess preventive care needs of the children who consult them infrequently.