Socio-economic inequalities in occurrence and health care costs in rheumatic and musculoskeletal diseases: results from a Spanish population-based study including 1.9 million persons.

OBJECTIVES: To explore and compare the impact of socio-economic deprivation on the occurrence of the major rheumatic and musculoskeletal diseases (RMDs) and health care costs. METHODS: Data on diagnoses, socio-demographics and health care costs of the entire adult population of the Basque Country (Spain) was used. Area deprivation index included five categories (1 to 5 (most deprived)). Cost categories included primary and specialist care, emergency room, hospitalisations, and drug prescriptions. Twenty-nine RMDs were grouped into seven groups: Rheumatoid Arthritis, Spondyloarthritis, Crystal Arthropathies, Osteoarthritis, Soft Tissue Diseases, Connective Tissue Diseases, and Vasculitis. The relations between the deprivation and the occurrence of RMD and costs were explored in regression models adjusted for relevant confounders. RESULTS: Data from 1,923,156 adults were analysed. Mean age was 49.9 (SD18.4) years, 49% were males. Soft tissue diseases were the most prevalent RMD (5.5%, n=105,656), followed by osteoarthritis (2.2%, n=41,924). Socio-economic deprivation was associated with higher likelihood to have any of the 29 RMDs. The strongest socio-economic gradient was seen for the soft tissue diseases (OR 1.82 [95%CI 1.78;1.85], most vs. least deprived), followed by osteoarthritis (OR 1.59 [1.54;1.64]). Deprivation was also associated with higher costs across the majority of the conditions however patterns were more blurred, and inverse relationship was observed for connective tissue diseases, gout, hip osteoarthritis and undifferentiated (poly)arthritis. CONCLUSIONS: Socio-economic deprivation is associated with increased occurrence of all RMDs, and in most cases more deprived patients incur higher health care costs.

Is utilization of health services for HIV patients equal by socioeconomic status? Evidence from the Basque country.

INTRODUCTION: Access to ART and health services is guaranteed under universal coverage to improve life expectancy and quality of life for HIV patients. However, it remains unknown whether patients of different socioeconomic background equally use different types of health services. METHODS: We use one-year (2010-2011) data on individual healthcare utilization and expenditures for the total population (N = 2262698) of the Basque Country. We observe the prevalence of HIV and use OLS regressions to estimate the impact on health utilization of demographic, socioeconomic characteristics, and health status in such patients. RESULTS: HIV prevalence per 1000 individuals is greater the lower the socioeconomic status (0.784 for highest; 2.135 for lowest), for males (1.616) versus females (0.729), and for middle-age groups (26-45 and 46-65). Health expenditures are 11826€ greater for HIV patients than for others, but with differences by socioeconomic group derived from a different mix of services utilization (total cost of 13058€ for poorest, 14960€ for richest). Controlling for health status and demographic variables, poor HIV patients consume more on pharmaceuticals; rich in specialists and hospital care. Therefore, there is inequity in health services utilization by socioeconomic groups. CONCLUSIONS: Equity in health provision for HIV patients represents a challenge even if access to treatment is guaranteed. Lack of information in poorer individuals might lead to under-provision while richer individuals might demand over-provision. We recommend establishing accurate clinical guidelines with the appropriate mix of health provision by validated need for all socioeconomic groups; promoting educational programs so that patients demand the appropriate mix of services, and stimulating integrated care for HIV patients with multiple chronic conditions.

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.

Prevalence of depression in adults with type 2 diabetes in the Basque Country: relationship with glycaemic control and health care costs.

BACKGROUND: The aim of the study was to estimate the prevalence of depression in the population diagnosed with diabetes type 2 and to test the hypothesis that the presence of depression in such cases was associated with a) worse glycaemic control, and b) higher healthcare costs. METHODS: We conducted a cross-sectional analysis, from 1st September 2010 to 31st August 2011, among patients with type 2 diabetes aged 35 years and over in the Basque Country. It was identified how many of them had also depression. The database included administrative individual level information on age, sex, healthcare costs, other comorbidities, and values of glycaemic control (HbA1c). Deprivation index variable was used as socioeconomic measure and, to observe the coexistent pathologies, all the patients diagnoses were categorized by Adjusted Clinical Groups. We used a measure of association, a logistic and a linear regression for analysis. RESULTS: 12.392 (9.8%) of type 2 diabetes patients were diagnosed with depression, being the prevalence 5.2% for males and 15.1% for females. This comorbidity was higher among the most deprived population. There was no association between the presence of depression and glycaemic control. We estimated that the comorbidity average cost per patient/year was 516€ higher than in patients with just type 2 diabetes (P < 0.001) adjusted by the other covariates. CONCLUSIONS: We did not find any relationship between depression and glycaemic control in patients with type 2 diabetes. However, the comorbidity was associated with significantly high healthcare costs compared to that of type 2 diabetes occurring alone, after adjusting by other illness. Thus, there is a need of more precise recognition, screening and monitoring of depression among diabetic population. Evidence-based treatment for depression should be included in type 2 diabetes clinical guidelines.

The prevalence of diabetes-related complications and multimorbidity in the population with type 2 diabetes mellitus in the Basque Country.

BACKGROUND: Type 2 diabetes mellitus is associated with a diverse range of pathologies. The aim of the study was to determine the incidence of diabetes-related complications, the prevalence of coexistent chronic conditions and to report multimorbidity in people with type 2 diabetes living in the Basque Country. METHODS: Administrative databases, in four cross sections (annually from 2007 to 2011) were consulted to analyse 149,015 individual records from patients aged ≥ 35 years with type 2 diabetes mellitus. The data observed were: age, sex, diabetes-related complications (annual rates of acute myocardial infarction, major amputations and avoidable hospitalisations), diabetes-related pathologies (prevalence of ischaemic heart disease, renal failure, stroke, heart failure, peripheral neuropathy, foot ulcers and diabetic retinopathy) and other unrelated pathologies (44 diseases). RESULTS: The annual incidence for each condition progressively decreased during the four-year period: acute myocardial infarction (0.47 to 0.40%), major amputations (0.10 to 0.08%), and avoidable hospitalisations (5.85 to 5.5%). The prevalence for diabetes-related chronic pathologies was: ischaemic heart disease (11.5%), renal failure (8.4%), stroke (7.0%), heart failure (4.3%), peripheral neuropathy (1.3%), foot ulcers (2.0%) and diabetic retinopathy (7.2%). The prevalence of multimorbidity was 90.4%. The highest prevalence for other chronic conditions was 73.7% for hypertension, 13.8% for dyspepsia and 12.7% for anxiety. CONCLUSIONS: In the type 2 diabetes mellitus population living in the Basque Country, incidence rates of diabetes complications are not as high as in other places. However, they present a high prevalence of diabetes related and unrelated diseases. Multimorbidity is very common in this group, and is a factor to be taken into account to ensure correct clinical management.

A qualitative study on clinicians' perceptions about the implementation of a population risk stratification tool in primary care practice of the Basque health service.

BACKGROUND: A prospective Population Risk Stratification (PRS) tool was first introduced in the public Basque Health Service in 2011, at the level of its several Primary Care (PC) practices. This paper aims at exploring the new tool's implementation process, as experienced by its potential adopters/users, ie. PC clinicians (doctors and nurses). Findings could help guide future PRS implementation strategies. METHODS: Three focus groups exploring clinicians' opinions and experiences related to the PRS tool and its implementation in their daily practice were conducted. A purposive sample of 12 General Practitioners and 11 PC nurses participated in the groups. Discussions were digitally recorded, transcribed verbatim and analysed by two independent researchers using thematic analysis based on Graham et al.'s Knowledge Translation Theory. RESULTS: Exploring PC clinicians' experience with the new PRS tool, allowed us to identify certain elements working as barriers and facilitators in its implementation process. This series of closely interrelated elements, which emerged as relevant in building up the complex implementation process of the new tool, as experienced by the clinicians, can be grouped into four domains: 1) clinicians' characteristics as potential adopters, 2) clinicians' perceptions of their practice settings where PRS is to implemented, 3) clinicians' perceptions of the tool, and 4) the implementation strategy used by the PRS promoter. CONCLUSIONS: Lessons from the implementation process under study point at the need to frame the implementation of a new PRS tool within a wider strategy encouraging PC clinicians to orientate their daily practice towards a population health approach. The PRS tool could also improve the perceived utility by its potential adopters, by bringing it closer to the clinicians' needs and practice, and allowing it to become context-sensitive. This would require clinicians being involved from the earliest phases of conceptualisation, design and implementation of the new tool, and mounting efforts to improve communication between clinicians and tool promoters.Graham et al.'s Knowledge Translation Theory proved a suitable framework to explore the implementation process of a new PRS tool in the public Basque Health Service's PC practice, and hence to identify implementation barriers and facilitators as experienced by the clinicians.

Prevalence of multimorbidity according to the deprivation level among the elderly in the Basque Country.

BACKGROUND: Multimorbidity is clearly a major challenge for healthcare systems. However, currently, its magnitude and impact on healthcare expenditures is still not well known. The objective of this paper is to present an overview of the prevalence of multimorbidity by deprivation level in the elderly population of the Basque Country. METHODS: We conducted a cross-sectional analysis that included all the inhabitants of the Basque Country aged 65 years and over (N = 452,698). This was based on data from primary care electronic medical records, hospital admissions, and outpatient care databases, for a 4-year period. The health problems of the patients were identified from their diagnoses and prescriptions. Multimorbidity was defined as the presence of two or more chronic diseases out of a list of 47 of the most important and common chronic conditions consistent with the literature. In addition, we explored socio-economic and demographic variables such as age, sex, and deprivation level. RESULTS: Multimorbidity was found in 66.13% of the population aged 65 and over and increases with age until 80 years. The prevalence of multimorbidity was higher in deprived (69.94%) than better-off (60.22%) areas. This pattern of differences between the most and least disadvantaged areas was observed in all age groups and more marked in female (70.96-59.78%) than in male (68.54-60.86%) populations. In almost all diseases studied (43 out of 47), 90% of patients had been diagnosed with at least one other illness. It was also frequent the coexistence of mental and physical health problems in the same person and the presence of multiple physical diseases is higher in patients with mental disease than in the rest of population (74.97% vs. 58.14%). CONCLUSION: Multimorbidity is very common among people over 65 years old in the Basque Country, particularly in unfavourable socioeconomic environments. Given the ageing population, multimorbidity and its consequences should be taken into account in healthcare policy, organization of care and medical research. Administrative health databases are readily available sources of a range of information that can be useful for such purposes.

Socioeconomic variation in the burden of chronic conditions and health care provision--analyzing administrative individual level data from the Basque Country, Spain.

BACKGROUND: Chronic diseases are posing an increasing challenge to society, with the associated burden falling disproportionally on more deprived individuals and geographical areas. Although the existence of a socioeconomic health gradient is one of the main concerns of health policy across the world, health information systems commonly do not have reliable data to detect and monitor health inequalities and inequities. The objectives of this study were to measure the level of socioeconomic-related inequality in prevalence of chronic diseases and to investigate the extent and direction of inequities in health care provision. METHODS: A dataset linking clinical and administrative information of the entire population living in the Basque Country, Spain (over 2 million individuals) was used to measure the prevalence of 52 chronic conditions and to quantify individual health care costs. We used a concentration-index approach to measure the extent and direction of inequality with respect to the deprivation of the area of residence of each individual. RESULTS: Most chronic diseases were found to be disproportionally concentrated among individuals living in more deprived areas, but the extent of the imbalance varies by type of disease and sex. Most of the variation in health care utilization was explained by morbidity burden. However, even after accounting for differences in morbidity, pro-poor horizontal inequity was present in specialized outpatient care, emergency department, prescription, and primary health care costs and this fact was more apparent in females than males; inpatient costs exhibited an equitable distribution in both sexes. CONCLUSIONS: Analyses of comprehensive administrative clinical information at the individual level allow the socioeconomic gradient in chronic diseases and health care provision to be measured to a level of detail not possible using other sources. This frequently updated source of information can be exploited to monitor trends and evaluate the impact of policy reforms.

Predictive risk modelling in the Spanish population: a cross-sectional study.

BACKGROUND: An increase in chronic conditions is currently the greatest threat to human health and to the sustainability of health systems. Risk adjustment systems may enable population stratification programmes to be developed and become instrumental in implementing new models of care.The objectives of this study are to evaluate the capability of ACG-PM, DCG-HCC and CRG-based models to predict healthcare costs and identify patients that will be high consumers and to analyse changes to predictive capacity when socio-economic variables are added. METHODS: This cross-sectional study used data of all Basque Country citizens over 14 years of age (n = 1,964,337) collected in a period of 2 years. Data from the first 12 months (age, sex, area deprivation index, diagnoses, procedures, prescriptions and previous cost) were used to construct the explanatory variables. The ability of models to predict healthcare costs in the following 12 months was assessed using the coefficient of determination and to identify the patients with highest costs by means of receiver operating characteristic (ROC) curve analysis. RESULTS: The coefficients of determination ranged from 0.18 to 0.21 for diagnosis-based models, 0.17-0.18 for prescription-based and 0.21-0.24 for the combination of both. The observed area under the ROC curve was 0.78-0.86 (identifying patients with a cost higher than P-95) and 0.83-0.90 (P-99). The values of the DCG-HCC models are slightly higher and those of the CRG models are lower, although prescription information could not be used in the latter. On adding previous cost data, differences between the three systems decrease appreciably. Inclusion of the deprivation index led to only marginal improvements in explanatory power. CONCLUSION: The case-mix systems developed in the USA can be useful in a publicly financed healthcare system with universal coverage to identify people at risk of high health resource consumption and whose situation is potentially preventable through proactive interventions.

[Stratification of the population in the Basque Country: results in the first year of implementation]. / Estratificación de la población en el País Vasco: resultados en el primer año de implantación.

Predictive models allow populations to be stratified according to their health requirements for the following year. They offer health care organizations the opportunity to act proactively, designing specific interventions adapted to the level of need of different groups of people. The "Strategy for tackling the challenge of chronic illness in the Basque Country" proposes the use of such models, integrating them with other policies. The prospective categorization of all the population assigned to Osakidetza was performed for the first time in 2010 using the Johns Hopkins Adjusted Clinical Groups predictive model (ACG-PM). For this purpose, already recorded information extracted from electronic health records of primary care and hospital discharge reports was used. This article discusses the advantages of the combined use of various sources of information, and describes the application of the stratification in three programs, targeted at chronic patients who suffer different burdens of comorbidity.

Monitoring the prevalence of chronic conditions: which data should we use?

BACKGROUND: Chronic diseases are an increasing threat to people's health and to the sustainability of health organisations. Despite the need for routine monitoring systems to assess the impact of chronicity in the population and its evolution over time, currently no single source of information has been identified as suitable for this purpose. Our objective was to describe the prevalence of various chronic conditions estimated using routine data recorded by health professionals: diagnoses on hospital discharge abstracts, and primary care prescriptions and diagnoses. METHODS: The ICD-9-CM codes for diagnoses and Anatomical Therapeutic Chemical (ATC) codes for prescriptions were collected for all patients in the Basque Country over 14 years of age (n=1,964,337) for a 12-month period. We employed a range of different inputs: hospital diagnoses, primary care diagnoses, primary care prescriptions and combinations thereof. Data were collapsed into the morbidity groups specified by the Johns Hopkins Adjusted Clinical Groups (ACGs) Case-Mix System. We estimated the prevalence of 12 chronic conditions, comparing the results obtained using the different data sources with each other and also with those of the Basque Health Interview Survey (ESCAV). Using the different combinations of inputs, Standardized Morbidity Ratios (SMRs) for the considered diseases were calculated for the list of patients of each general practitioner. The variances of the SMRs were used as a measure of the dispersion of the data and were compared using the Brown-Forsythe test. RESULTS: The prevalences calculated using prescription data were higher than those obtained from diagnoses and those from the ESCAV, with two exceptions: malignant neoplasm and migraine. The variances of the SMRs obtained from the combination of all the data sources (hospital diagnoses, and primary care prescriptions and diagnoses) were significantly lower than those using only diagnoses. CONCLUSIONS: The estimated prevalence of chronic diseases varies considerably depending of the source(s) of information used. Given that administrative databases compile data registered for other purposes, the estimations obtained must be considered with caution. In a context of increasingly widespread computerisation of patient medical records, the complementary use of a range of sources may be a feasible option for the routine monitoring of the prevalence of chronic diseases.

Inequalities in Health Care Experience of Patients with Chronic Conditions: Results from a Population-Based Study.

Patients' experience is an acknowledged key factor for the improvement of healthcare delivery quality. This study aims to explore the differences in healthcare experience among patients with chronic conditions according to individual sociodemographic and health-related variables. A population-based and cross-sectional study was conducted. The sample consisted of 3981 respondents of the Basque Health Survey (out of 8036 total respondents to the individual questionnaire), living in the Basque Country, aged 15 or older, self-reporting at least one chronic condition. Patient experience was assessed with the Instrument for Evaluation of the Experience of Chronic Patients questionnaire, which encompasses three major factors: interactions between patients and professionals oriented to improve outcomes (productive interactions); new ways of patient interaction with the health care system (the new relational model); and the ability of individuals to manage their care and improve their wellbeing based on professional-mediated interventions (self-management). We conducted descriptive and regression analyses. We estimated linear regression models with robust variances that allow testing for differences in experience according to sociodemographic characteristics, the number of comorbidities and the condition (for all chronic or for chronic patients' subgroups). Although no unique inequality patterns by these characteristics can be inferred, females reported worse global results than males and older age was related to poorer experience with the new relational model in health care. Individuals with lower education levels tend to report lower experiences. There is not a clear pattern observed for the type of occupation. Multimorbidity and several specific chronic conditions were associated (positive or negatively) with patients' experience. Health care experience was better in patients with greater quality of life. Understanding the relations among the patients' experience and their sociodemographic and health-related characteristics is an essential issue for health care systems to improve quality of assistance.

FINGER (Forming and Identifying New Groups of Expected Risks): developing and validating a new predictive model to identify patients with high healthcare cost and at risk of admission.

OBJECTIVE: Predictive statistical models used in population stratification programmes are complex and usually difficult to interpret for primary care professionals. We designed FINGER (Forming and Identifying New Groups of Expected Risks), a new model based on clinical criteria, easy to understand and implement by physicians. Our aim was to assess the ability of FINGER to predict costs and correctly identify patients with high resource use in the following year. DESIGN: Cross-sectional study with a 2-year follow-up. SETTING: The Basque National Health System. PARTICIPANTS: All the residents in the Basque Country (Spain) ≥14 years of age covered by the public healthcare service (n=1 946 884). METHODS: We developed an algorithm classifying diagnoses of long-term health problems into 27 chronic disease groups. The database was randomly divided into two data sets. With the calibration sample, we calculated a score for each chronic disease group and other variables (age, sex, inpatient admissions, emergency department visits and chronic dialysis). Each individual obtained a FINGER score for the year by summing their characteristics' scores. With the validation sample, we constructed regression models with the FINGER score for the first 12 months as the only explanatory variable. RESULTS: The annual FINGER scores obtained by patients ranged from 0 to 57 points, with a mean of 2.06. The coefficient of determination for healthcare costs was 0.188 and the area under the receiver operating characteristic curve was 0.838 for identifying patients with high costs (>95th percentile); 0.875 for extremely high costs (>99th percentile); 0.802 for unscheduled admissions; 0.861 for prolonged hospitalisation (>15 days); and 0.896 for death. CONCLUSION: FINGER presents a predictive power for high risks fairly close to other classification systems. Its simple and transparent architecture allows for immediate calculation by clinicians. Being easy to interpret, it might be considered for implementation in regions involved in population stratification programmes.

Comorbidities with chronic physical conditions and gender profiles of illness in schizophrenia. Results from PREST, a new health dataset.

OBJECTIVE: Using data from a large health dataset, the objectives are to describe the epidemiology of comorbidities with chronic physical conditions in schizophrenia, to identify gender profiles of illness and to discuss findings in the light of previous research. METHODS: The PREST health database was used which combines high quality and complementary data from numerous public health care resources in the Basque Country (Spain). RESULTS: A total number of 2,255,406 patients were included in this study and 7331 had a diagnosis of schizophrenia. 55.6% of them had one comorbid condition and 29.3% had 2 or more (e.g. multiple comorbidities). Hypertension (16.8%) was the most prevalent diagnosed comorbid condition in these patients. The risk of having neuropsychiatric disorders including Parkinson (OR up to 47.89), infectious diseases (OR up to 3.31) or diabetes (OR2.23) was increased, while the risk of having cancer (OR down to 0.76) or some cardiovascular conditions (OR down to 0.63) was reduced. Women (both with and without schizophrenia) showed higher percentages of comorbidities than men. A cluster of respiratory diseases was found only in women with schizophrenia (not in men). CONCLUSIONS: Results confirm partially previous findings and call for a more proactive and comprehensive approach to the health care of patients with schizophrenia. Specific profiles of risks for concrete disorders were identified which could be explained by selective underdiagnoses or higher exposition to risk factors in this group of patients. Results also suggest the need of a more gender oriented approach to health care in schizophrenia.

[Can primary care physicians use the ICD-9-MC? An evaluation of the quality of diagnosis coding in computerized medical records]. / 'Es factible que los médicos de primaria utilicen CIE-9-MC? Calidad de la codificación de diagnósticos en las historias clínicas informatizadas.

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.

Healthcare costs of people with type 2 diabetes mellitus in the Basque Country (Spain). / Costes sanitarios de la población con diabetes mellitus tipo 2 en el País Vasco (España).

OBJECTIVE: The aim of the study was to estimate the direct costs of healthcare provided to patients with type 2 diabetes mellitus (T2DM) in the Basque Country and to compare them with those of the population with chronic diseases. MATERIAL AND METHODS: A retrospective, cross-sectional, population-based study. Direct healthcare costs for patients aged over 35 years diagnosed with T2DM in the Basque Country (n=126,894) were calculated, stratified by age, sex and deprivation index, and compared to the costs for the population diagnosed with a chronic disease other than T2DM (n=1,347,043). RESULTS: The annual average healthcare cost of a person with T2DM was €3,432. Cost gradually increased with age to €4,313 in patients aged 80 to 84 years. Cost in males were €161 higher as compared to costs in females (P<.001). In the most socioeconomically disadvantaged areas, cost per patient was €468 (14.9%) greater than in the most privileged areas (P<.001). Moreover, cost was 68.5% higher (P<.001) for patients with T2DM than for patients with other chronic diseases. Total annual direct costs amounted to €435.5 million, or 12.78% of total public health expenditure in the region. CONCLUSIONS: Direct mean healthcare costs in the Basque Country for patients with T2DM were higher in males, in the most underprivileged areas, in patients with comorbidities, and in older age groups, and represented €3,432 per person per year.

[Technical efficiency assessment of public primary care providers in the Basque Country (Spain), 2010-2013]. / Evaluación de la eficiencia técnica de la atención primaria pública en el País Vasco, 2010-2013.

OBJECTIVE: To evaluate the technical efficiency of primary care units operating in the Basque Health Service during the period 2010-2013, corresponding to the implementation of a care integration strategy by health authorities. METHODS: This study included 11 of the 12 primary care units in the Basque Health Service during the period 2010-2013. Data envelopment analysis (DEA) was used to assess the technical efficiency of the units. In particular, we applied the extension DEA windows to analyse all units as if they were in a single period (33 observations) as well as a conditional model, which allowed incorporation of the effect of the characteristics of the population covered. The outputs considered were a quality index based on fulfilment of different requirements related to primary care delivery and the rate of avoidable hospitalizations (treated as an undesirable output). The inputs used were the number of physicians, the number of nurses and the costs of prescriptions. The morbidity index was included as an exogenous variable. RESULTS: The results showed that the efficiency of all the units improved during the study period. However, this improvement was not greater in the units incorporated in the integrated healthcare organisation. DISCUSSION: In a context of global transformation of care delivery in the Basque country in the study period, primary care units increased their efficiency. However, this effect was not larger in vertically integrated primary care providers.

Variability in potentially preventable hospitalisations: an observational study of clinical practice patterns of general practitioners and care outcomes in the Basque Country (Spain).

OBJECTIVES: To explain the variability in the frequency of potentially preventable hospitalisations (ambulatory care sensitive conditions, ACSCs) based on factors at multiple levels (individual, health professional, health centre and health district), and specifically using resource efficiency indicators for general practitioners (GPs). DESIGN: Cross-sectional study. We analysed primary care electronic health records and hospital discharge data using multilevel mixed models. SETTING: Primary care network of the Basque Health Service (Spain). PARTICIPANTS: All the residents in the Basque Country ≥14 years of age, covered by the public healthcare system (n=1,959,682), and all the GPs (n=1193) and health centres (n=130). MAIN OUTCOME MEASURES: Individuals admitted for ACSCs, over a 12- month period. RESULTS: Admissions for ACSCs were less frequent among patients who were female, middle-aged or from the highest socioeconomic classes. The health centre variables considered and GP list size were not found to be significant. After adjusting for the variables studied including morbidity, the risk of hospital admission was higher among individuals under the care of GPs with greater than expected numbers of patient visits and prescribing costs (OR=1.27 (95% CI 1.18 to 1.37); 1.16 (1.08 to 1.25)), and who make fewer referrals than the mean among their colleagues (OR=1.33 (1.22 to 1.44)). CONCLUSIONS: When assessing activities and procedure indicators in primary care, we should also define outcome-based criteria. Specifically, GPs who are repeatedly visited by their patients, have higher prescribing costs and are more reluctant to refer patients to specialists obtain poorer outcomes.

The Origin of Variation in Primary Care Process and Outcome Indicators: Patients, Professionals, Centers, and Health Districts.

Healthcare providers are often evaluated by studying variability in their indicators. However, the usefulness of this analysis may be limited if we do not distinguish the variability attributable to health professionals and organizations from that associated with their patients.Our objectives are to describe the main process and outcome indicators of primary healthcare services, analyzing the contribution to variability in these indicators from different levels: individual, health professional, health center, and health district.This is a cross-sectional study that includes all.All the individuals covered by the public Basque Health Service (children [age 0-13], n = 247,493; adults [≥14 years old], n = 1,959,682) over a 12-month period.We calculated the number of visits to primary care doctors, number of referrals, prescription costs, and potentially avoidable hospitalizations for ambulatory care sensitive conditions (ACSCs). Using multilevel analysis, we determined the percentage of variance attributable to each level.After adjusting for the characteristics of patients (demographic, socioeconomic, and morbidity), doctors (panel size), health center (size, staff satisfaction, demographic structure of the community), and health district, the variance in the indicators was mainly attributable to differences between patients, independently of the attending health professional, the center, or the healthcare organization, both in children (94.21% for visits to the doctor; 96.66% for referrals; 98.57% for prescription costs; 90.02% for potentially avoidable hospitalizations for ACSCs) and in adults (88.10%; 96.26%; 97.92%; and 93.77%, respectively).The limited contribution of health professionals and organizations to variability in indicators should be taken into account when performing evaluations and planning quality improvement strategies.

Health-related quality of life and multimorbidity in community-dwelling telecare-assisted elders in the Basque Country.

INTRODUCTION: Multimorbidity is more common in the elderly population and negatively affects health-related quality of life (QoL). The aims of the study were to report the QoL of users of the Basque telecare public service (BTPS) and to establish its relationship with multimorbidity. METHODS: The EuroQol questionnaire was administered to 1125 users of the service. Their sociodemographic and healthcare characteristics were obtained from BTPS databases and the Basque healthcare service. Multiple regression analysis was performed on the overall questionnaire index to determine the effect of chronic diseases and sociodemographic. Moreover, the effects of the different diseases on specific dimensions of the test were explored by logistic regression. RESULTS: Of the users interviewed, 82% were women, 88% ≥75 years and 66% lived alone. The average of chronic pathologies was higher among men (5.3 vs. 4.6), for the lower age range and among those not living alone (P<0.001). For QoL, men and people aged over 84 obtained better scores (0.64 and 0.61, respectively). Worse QoL was associated with being a woman, multimorbidity, and living with one or more people. The existence of multimorbidity meant impaired QoL of 2.6 points for each additional disease over the overall score (P<0.001). CONCLUSIONS: This study reveals that for the population covered by BTPS the impact of chronic pathologies, multimorbidity and their social context affects QoL very diversely. These diverse social and healthcare needs of community-dwelling elders allow the development and implementation of personalised services, such as telecare that facilitate them to remain at home.