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

Promising algorithms to perilous applications: a systematic review of risk stratification tools for predicting healthcare utilisation

OBJECTIVES

Risk stratification tools that predict healthcare utilisation are extensively integrated into primary care systems worldwide, forming a key component of anticipatory care pathways, where high-risk individuals are targeted by preventative interventions. Existing work broadly focuses on comparing model performance in retrospective cohorts with little attention paid to efficacy in reducing morbidity when deployed in different global contexts. We review the evidence supporting the use of such tools in real-world settings, from retrospective dataset performance to pathway evaluation.

METHODS

A systematic search was undertaken to identify studies reporting the development, validation and deployment of models that predict healthcare utilisation in unselected primary care cohorts, comparable to their current real-world application.

RESULTS

Among 3897 articles screened, 51 studies were identified evaluating 28 risk prediction models. Half underwent external validation yet only two were validated internationally. No association between validation context and model discrimination was observed. The majority of real-world evaluation studies reported no change, or indeed significant increases, in healthcare utilisation within targeted groups, with only one-third of reports demonstrating some benefit.

DISCUSSION

While model discrimination appears satisfactorily robust to application context there is little evidence to suggest that accurate identification of high-risk individuals can be reliably translated to improvements in service delivery or morbidity.

CONCLUSIONS

The evidence does not support further integration of care pathways with costly population-level interventions based on risk prediction in unselected primary care cohorts. There is an urgent need to independently appraise the safety, efficacy and cost-effectiveness of risk prediction systems that are already widely deployed within primary care.

Comorbidity and household income as mediators of gender inequalities in dementia risk: a real-world data population study

BACKGROUND

Low household income (HI), comorbidities and female sex are associated with an increased risk of dementia. The aim of this study was to measure the mediating effect of comorbidity and HI on the excess risk due to gender in relation to the incidence and prevalence of dementia in the general population.

METHODS

A retrospective and observational study using real-world data analysed all people over 60 who were registered with the Basque Health Service in Gipuzkoa. The study measured HI level, the Charlson comorbidity index (CCI), age and sex. The prevalence and incidence of dementia were analysed using logistic regression and Poisson regression models, respectively, adjusted by HI, sex, comorbidity and age. We estimated the combined mediation effect of HI and comorbidity on the prevalence of dementia associated with gender.

RESULTS

Of the 221,777 individuals, 3.85% (8,549) had a diagnosis of dementia as of 31 December 2021. Classification by the CCI showed a gradient with 2.90% in CCI 0-1, 10.60% in CCI 2-3 and 18.01% in CCI > 3. Both low HI and gender were associated with a higher crude prevalence of dementia. However, in the CCI-adjusted model, women had an increased risk of dementia, while HI was no longer statistically significant. The incidence analysis produced similar results, although HI was not significant in any model. The CCI was significantly higher for men and for people with low HI. The mediation was statistically significant, and the CCI and HI explained 79% of the gender effect.

CONCLUSIONS

Comorbidity and low HI act as mediators in the increased risk of dementia associated with female sex. Given the difference in the prevalence of comorbidities by HI, individual interventions to control comorbidities could not only prevent dementia but also reduce inequalities, as the risk is greater in the most disadvantaged population.

Glucagon-Like Peptide-1 Receptor Agonists and Pancreatic Cancer Risk in Patients With Type 2 Diabetes

Importance

Concerns have been raised that glucagon-like peptide-1 receptor agonists (GLP-1RA) may increase the risk of pancreatic cancer.

Objective

To investigate the association of GLP-1RA treatment with pancreatic cancer incidence over 9 years of follow-up.

Design, Setting, and Participants

In this population-based historical cohort study, adult patients (aged 21 to 89 years) with type 2 diabetes insured by Clalit Healthcare Services, the largest state-mandated health organization in Israel, were followed up from 2009, when GLP-1RA became available in Israel, until pancreatic cancer diagnosis, death, reaching age 90 years, or end of follow-up (December 2017). Data were analyzed from June 2022 to November 2023.

Exposures

Treatment with GLP-1RA was compared with basal insulin.

Main Outcome and Measures

Pancreatic cancer incidence was compared according to weighted cumulative exposures to GLP-1RA and to basal insulin in a Cox model implemented in discrete time, with time origin at 2 years after diabetes diagnosis, adjusting for confounding. In sensitivity analyses, propensity score-matched pair new-user design and prevalent new-user design were used for the comparison. Because of risk for reverse-causation bias, results in the fifth to seventh year after medication were emphasized.

Results

During a cumulative follow-up of 3 290 439 person-years of 543 595 adults with a mean (SD) age of 59.9 (12.8) years (277 502 women [51%]) with incident diabetes, 1665 patients received pancreatic cancer diagnoses. In total, 33 377 patients (6.1%) used GLP-1RA and 106 849 (19.7%) used basal insulin. The estimated hazard ratio (HR) for pancreatic cancer associated with incremental use of 1 defined daily dose per day of GLP-1RA compared with basal insulin in the fifth to seventh year previously (all other characteristics, including age, sex, ethnic background, sociodemographic status, baseline body mass index, smoking history, history of pancreatitis, other glucose-lowering medications treatment history, and length of diabetes, being equal) was 0.50 (95% CI, 0.15-1.71). The new-user and prevalent new-user designs showed HRs from the fifth year onwards following initiation of GLP-1RA vs basal insulin of 0.52 (95 % CI, 0.19-1.41) and 0.75 (95 % CI, 0.37-1.53), respectively.

Conclusions and Relevance

In this historical cohort study of adults with type 2 diabetes, no support for an increased pancreatic cancer incidence over 7 years following start of GLP-1RA treatment was found. However, monitoring for pancreatic cancer risk beyond 7 years following initiation of therapy is still required.

Trial Registration

ClinicalTrials.gov Identifier: NCT02072902.

Reverse causation biases weighted cumulative exposure model estimates, but can be investigated in sensitivity analyses

OBJECTIVES

To examine the effects of reverse causation on estimates from the weighted cumulative exposure (WCE) model that is used in pharmacoepidemiology to explore drug-health outcome associations, and to identify sensitivity analyses for revealing such effects.

STUDY DESIGN AND SETTING

314,099 patients with diabetes under Clalit Health Services, Israel, were followed over 2002-2012. The association between metformin and pancreatic cancer (PC) was explored using a WCE model within the framework of discrete-time Cox regression. We used computer simulations to explore the effects of reverse causation on estimates of a WCE model and to examine sensitivity analyses for revealing and adjusting for reverse causation. We then applied those sensitivity analyses to our data.

RESULTS

Simulation demonstrated bias in the weighted cumulative exposure model and showed that sensitivity analysis could reveal and adjust for these biases. In our data, a positive association was observed (hazard ratio (HR) = 3.24, 95% confidence interval (CI): 2.24-4.73) with metformin exposure in the previous 2 years. After applying sensitivity analysis, assuming reverse causation operated up to 4 years before cancer diagnosis, the association between metformin and PC was no longer apparent.

CONCLUSION

Reverse causation can cause substantial bias in the WCE model. When suspected, sensitivity analyses based on causal analysis are advocated.

Metformin Treatment Among Men With Diabetes and the Risk of Prostate Cancer: A Population-Based Historical Cohort Study

There is conflicting evidence regarding the association between metformin treatment and prostate cancer risk in diabetic men. We investigated this association in a population-based Israeli cohort of 145,617 men aged 21–89 years with incident diabetes who were followed over the period 2002–2012. We implemented a time-dependent covariate Cox model, using weighted cumulative exposure to relate metformin history to prostate cancer risk, adjusting for use of other glucose-lowering medications, age, ethnicity, and socioeconomic status. To adjust for time-varying glucose control variables, we used inverse probability weighting of a marginal structural model. With 666,553 person-years of follow-up, 1,592 men were diagnosed with prostate cancer. Metformin exposure in the previous year was positively associated with prostate cancer risk (per defined daily dose; without adjustment for glucose control, hazard ratio (HR) = 1.53 (95% confidence interval (CI): 1.19, 1.96); with adjustment, HR = 1.42 (95% CI: 1.04, 1.94)). However, exposure during the previous 2–7 years was negatively associated with risk (without adjustment for glucose control, HR = 0.58 (95% CI: 0.37, 0.93); with adjustment, HR = 0.60 (95% CI: 0.33, 1.09)). These positive and negative associations with previous-year and earlier metformin exposure, respectively, need to be confirmed and better understood.

Socio-demographic and -economic factors associated with 30-day readmission for conditions targeted by the hospital readmissions reduction program: a population-based study

Background

Early hospital readmissions remain common in patients with conditions targeted by the CMS Hospital Readmission Reduction Program (HRRP). There is still no consensus on whether readmission measures should be adjusted based on social factors, and there are few population studies within the U.S. examining how social characteristics influence readmissions for HRRP-targeted conditions. The objective of this study was to determine if specific socio-demographic and -economic factors are associated with 30-day readmissions in HRRP-targeted conditions: acute exacerbation of chronic obstructive pulmonary disease, pneumonia, acute myocardial infarction, and heart failure.

Methods

The Nationwide Readmissions Database was used to identify patients admitted with HRRP-targeted conditions between January 1, 2010 and September 30, 2015. Stroke was included as a control condition because it is not included in the HRRP. Multivariate models were used to assess the relationship between three social and economic characteristics (gender, urban/rural hospital designation, and estimated median household income within the patient’s zip code) and 30-day readmission rates using a hierarchical two-level logistic model. Age-adjusted models were used to assess relationship differences between Medicare vs. non-Medicare populations.

Results

There were 19,253,997 weighted index hospital admissions for all diagnoses and 3,613,488 30-day readmissions between 2010 and 2015. Patients in the lowest income quartile (≤$37,999) had an increased odds of 30-day readmission across all conditions (P < 0.0001). Female gender and rural hospital designation were associated with a decreased odds of 30-day readmission for most targeted conditions (P < 0.05). Similar findings were also seen in patients ≥65 years old.

Conclusions

Socio-demographic and -economic factors are associated with 30-day readmission rates and should be incorporated into tools or interventions to improve discharge planning and mitigate against readmission.

A systematic review of risk stratification tools internationally used in primary care settings

BACKGROUND AND AIMS

In our current healthcare situation, burden on healthcare services is increasing, with higher costs and increased utilization. Structured population health management has been developed as an approach to balance quality with increasing costs. This approach identifies sub-populations with comparable health risks, to tailor interventions for those that will benefit the most. Worldwide, the use of routine healthcare data extracted from electronic health registries for risk stratification approaches is increasing. Different risk stratification tools are used on different levels of the healthcare continuum. In this systematic literature review, we aimed to explore which tools are used in primary healthcare settings and assess their performance.

METHODS

We performed a systematic literature review of studies applying risk stratification tools with health outcomes in primary care populations. Studies in Organisation for Economic Co-operation and Development countries published in English-language journals were included. Search engines were utilized with keywords, for example, "primary care," "risk stratification," and "model." Risk stratification tools were compared based on different measures: area under the curve (AUC) and C-statistics for dichotomous outcomes and R 2 for continuous outcomes.

RESULTS

The search provided 4718 articles. Specific election criteria such as primary care populations, generic health utilization outcomes, and routinely collected data sources identified 61 articles, reporting on 31 different models. The three most frequently applied models were the Adjusted Clinical Groups (ACG, n = 23), the Charlson Comorbidity Index (CCI, n = 19), and the Hierarchical Condition Categories (HCC, n = 7). Most AUC and C-statistic values were above 0.7, with ACG showing slightly improved scores compared with the CCI and HCC (typically between 0.6 and 0.7).

CONCLUSION

Based on statistical performance, the validity of the ACG was the highest, followed by the CCI and the HCC. The ACG also appeared to be the most flexible, with the use of different international coding systems and measuring a wider variety of health outcomes.

Identification of drugs associated with reduced severity of COVID-19 - a case-control study in a large population

Background

Until coronavirus disease 2019 (COVID-19) drugs specifically developed to treat COVID-19 become more widely accessible, it is crucial to identify whether existing medications have a protective effect against severe disease. Toward this objective, we conducted a large population study in Clalit Health Services (CHS), the largest healthcare provider in Israel, insuring over 4.7 million members.

Methods

Two case-control matched cohorts were assembled to assess which medications, acquired in the last month, decreased the risk of COVID-19 hospitalization. Case patients were adults aged 18 to 95 hospitalized for COVID-19. In the first cohort, five control patients, from the general population, were matched to each case (n=6202); in the second cohort, two non-hospitalized SARS-CoV-2 positive control patients were matched to each case (n=6919). The outcome measures for a medication were: odds ratio (OR) for hospitalization, 95% confidence interval (CI), and the p-value, using Fisher's exact test. False discovery rate was used to adjust for multiple testing.

Results

Medications associated with most significantly reduced odds for COVID-19 hospitalization include: ubiquinone (OR=0.185, 95% CI [0.058 to 0.458], p<0.001), ezetimibe (OR=0.488, 95% CI [0.377 to 0.622], p<0.001), rosuvastatin (OR=0.673, 95% CI [0.596 to 0.758], p<0.001), flecainide (OR=0.301, 95% CI [0.118 to 0.641], p<0.001), and vitamin D (OR=0.869, 95% CI [0.792 to 0.954], p<0.003). Remarkably, acquisition of artificial tears, eye care wipes, and several ophthalmological products were also associated with decreased risk for hospitalization.

Conclusions

Ubiquinone, ezetimibe, and rosuvastatin, all related to the cholesterol synthesis pathway were associated with reduced hospitalization risk. These findings point to a promising protective effect which should be further investigated in controlled, prospective studies.

Funding

This research was supported in part by the Intramural Research Program of the National Institutes of Health, NCI.

Socioeconomic differences in healthcare expenditure and utilization in The Netherlands

BACKGROUND

Worldwide, socioeconomic differences in health and use of healthcare resources have been reported, even in countries providing universal healthcare coverage. However, it is unclear how large these socioeconomic differences are for different types of care and to what extent health status plays a role. Therefore, our aim was to examine to what extent healthcare expenditure and utilization differ according to educational level and income, and whether these differences can be explained by health inequalities.

METHODS

Data from 18,936 participants aged 25-79 years of the Dutch Health Interview Survey were linked at the individual level to nationwide claims data that included healthcare expenditure covered in 2017. For healthcare utilization, participants reported use of different types of healthcare in the past 12 months. The association of education/income with healthcare expenditure/utilization was studied separately for different types of healthcare such as GP and hospital care. Subsequently, analyses were adjusted for general health, physical limitations, and mental health.

RESULTS

For most types of healthcare, participants with lower educational and income levels had higher healthcare expenditure and used more healthcare compared to participants with the highest educational and income levels. Total healthcare expenditure was approximately between 50 and 150 % higher (depending on age group) among people in the lowest educational and income levels. These differences generally disappeared or decreased after including health covariates in the analyses. After adjustment for health, socioeconomic differences in total healthcare expenditure were reduced by 74-91 %.

CONCLUSIONS

In this study among Dutch adults, lower socioeconomic status was associated with increased healthcare expenditure and utilization. These socioeconomic differences largely disappeared after taking into account health status, which implies that, within the universal Dutch healthcare system, resources are being spent where they are most needed. Improving health among lower socioeconomic groups may contribute to decreasing health inequalities and healthcare spending.

Occurrence of comorbidities in newly diagnosed type 2 diabetes patients and their impact after 11 years' follow-up

The burden of type 2 diabetes is growing, not only through increased incidence, but also through its comorbidities. Concordant comorbidities for type 2 diabetes, such as cardiovascular diseases, are considered expected outcomes of the disease or disease complications, while discordant comorbidities are not considered to be directly related to type 2 diabetes and are less extensively addressed under diabetes management. Here we show that the combination of concordant and discordant comorbidities appears frequently in persons with diabetes (75%). Persons with combined comorbidities visited family physicians more than persons with discordant, concordant or no comorbidity (17.3 ± 10.2, 11.6 ± 6.5, 8.7 ± 6.8, 6.3 ± 6.6 visits/person/year respectively, p < 0.0001). The risk of death during the study period was highest in persons with combined comorbidities and discordant only comorbidities (HR = 33.4; 95% CI 12.5–89.2 and HR = 33.5; 95% CI 11.7–95.8), emphasizing the contribution of discordant comorbidities to the outcome. Our study is unique as a long-term follow-up of an 11-year cohort of 9725 persons with new-onset type 2 diabetes. The findings highlight the contribution of discordant comorbidity to the burden of the disease. The high prevalence of the combination of both concordant and discordant comorbidities, and their appearance before the onset of type 2 diabetes, indicates a continuum of morbidity.

Systematic review on the instruments used for measuring the association of the level of multimorbidity and clinically important outcomes

OBJECTIVES

There are multiple instruments for measuring multimorbidity. The main objective of this systematic review was to provide a list of instruments that are suitable for use in studies aiming to measure the association of a specific outcome with different levels of multimorbidity as the main independent variable in community-dwelling individuals. The secondary objective was to provide details of the requirements, strengths and limitations of these instruments, and the chosen outcomes.

METHODS

We conducted the review according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines (PROSPERO registration number: CRD42018105297). We searched MEDLINE, Embase and CINAHL electronic databases published in English and manually searched the Journal of Comorbidity between 1 January 2010 and 23 October 2020 inclusive. Studies also had to select adult patients from primary care or general population and had at least one specified outcome variable. Two authors screened the titles, abstracts and full texts independently. Disagreements were resolved with a third author. The modified Newcastle-Ottawa Scale was used for quality assessment.

RESULTS

Ninety-six studies were identified, with 69 of them rated to have a low risk of bias. In total, 33 unique instruments were described. Disease Count and weighted indices like Charlson Comorbidity Index were commonly used. Other approaches included pharmaceutical-based instruments. Disease Count was the common instrument used for measuring all three essential core outcomes of multimorbidity research: mortality, mental health and quality of life. There was a rise in the development of novel weighted indices by using prognostic models. The data obtained for measuring multimorbidity were from sources including medical records, patient self-reports and large administrative databases.

CONCLUSIONS

We listed the details of 33 instruments for measuring the level of multimorbidity as a resource for investigators interested in the measurement of multimorbidity for its association with or prediction of a specific outcome.

Identification of drugs associated with reduced severity of COVID-19: A case-control study in a large population

BACKGROUND

Until COVID-19 drugs specifically developed to treat COVID-19 become more widely accessible, it is crucial to identify whether existing medications have a protective effect against severe disease. Towards this objective, we conducted a large population study in Clalit Health Services (CHS), the largest healthcare provider in Israel, insuring over 4.7 million members.

METHODS

Two case-control matched cohorts were assembled to assess which medications, acquired in the last month, decreased the risk of COVID-19 hospitalization. Case patients were adults aged 18-95 hospitalized for COVID-19. In the first cohort, five control patients, from the general population, were matched to each case (n=6202); in the second cohort, two non-hospitalized SARS-CoV-2 positive control patients were matched to each case (n=6919). The outcome measures for a medication were: odds ratio (OR) for hospitalization, 95% confidence interval (CI), and the p-value, using Fisher's exact test. False discovery rate was used to adjust for multiple testing.

RESULTS

Medications associated with most significantly reduced odds for COVID-19 hospitalization include: ubiquinone (OR=0.185, 95% CI (0.058 to 0.458), p<0.001), ezetimibe (OR=0.488, 95% CI ((0.377 to 0.622)), p<0.001), rosuvastatin (OR=0.673, 95% CI (0.596 to 0.758), p<0.001), flecainide (OR=0.301, 95% CI (0.118 to 0.641), p<0.001), and vitamin D (OR=0.869, 95% CI (0.792 to 0.954), p<0.003). Remarkably, acquisition of artificial tears, eye care wipes, and several ophthalmological products were also associated with decreased risk for hospitalization.

CONCLUSIONS

Ubiquinone, ezetimibe and rosuvastatin, all related to the cholesterol synthesis pathway were associated with reduced hospitalization risk. These findings point to a promising protective effect which should be further investigated in controlled, prospective studies.

FUNDING

This research was supported in part by the Intramural Research Program of the National Institutes of Health, NCI.

Assessment of the Adjusted Clinical Groups system in Dutch primary care using electronic health records: a retrospective cross-sectional study

BACKGROUND

Within the Dutch health care system the focus is shifting from a disease oriented approach to a more population based approach. Since every inhabitant in the Netherlands is registered with one general practice, this offers a unique possibility to perform Population Health Management analyses based on general practitioners' (GP) registries. The Johns Hopkins Adjusted Clinical Groups (ACG) System is an internationally used method for predictive population analyses. The model categorizes individuals based on their complete health profile, taking into account age, gender, diagnoses and medication. However, the ACG system was developed with non-Dutch data. Consequently, for wider implementation in Dutch general practice, the system needs to be validated in the Dutch healthcare setting. In this paper we show the results of the first use of the ACG system on Dutch GP data. The aim of this study is to explore how well the ACG system can distinguish between different levels of GP healthcare utilization.

METHODS

To reach our aim, two variables of the ACG System, the Aggregated Diagnosis Groups (ADG) and the mutually exclusive ACG categories were explored. The population for this pilot analysis consisted of 23,618 persons listed with five participating general practices within one region in the Netherlands. ACG analyses were performed based on historical Electronic Health Records data from 2014 consisting of primary care diagnoses and pharmaceutical data. Logistic regression models were estimated and AUC's were calculated to explore the diagnostic value of the models including ACGs and ADGs separately with GP healthcare utilization as the dependent variable. The dependent variable was categorized using four different cut-off points: zero, one, two and three visits per year.

RESULTS

The ACG and ADG models performed as well as models using International Classification of Primary Care chapters, regarding the association with GP utilization. AUC values were between 0.79 and 0.85. These models performed better than the base model (age and gender only) which showed AUC values between 0.64 and 0.71.

CONCLUSION

The results of this study show that the ACG system is a useful tool to stratify Dutch primary care populations with GP healthcare utilization as the outcome variable.

[Primary Care frequentation determinants in Catalonia]

Objetivo

Determinar qué variables definen el tiempo de asistencia anual medio por paciente en Atención Primaria (AP) en Cataluña, para mejorar la adecuación de la asignación presupuestaria.

Diseño

Estudio ecológico transversal.

Emplazamiento

Los Equipos de Atención Primaria (EAP) del Institut Català de la Salut (ICS) en 2016.

Participantes

Los 285 EAP del ICS, que dan cobertura a un 75% de los ciudadanos mayores de 14 años en Cataluña.

Mediciones principales

Tiempo medio de visita anual en medicina familiar por paciente para cada EAP. Se estudió cómo este tiempo dependía de potenciales variables explicativas, a nivel de EAP, mediante modelos de regresión lineal.

Resultados

El tiempo medio de visita por paciente/año fue de 49 minutos, variando entre 23-87 minutos, según el EAP. Los EAP con población asignada de más edad, más comorbilidad, más atención domiciliaria, peor índice socioeconómico, mayor número de pensionistas jóvenes y mayor dispersión tuvieron más tiempo de visita, mientras que los EAP con más población y más mujeres tuvieron menos tiempo de visita. Estas variables explicaron un 64% de la variabilidad del tiempo de visita.

Conclusiones

La asignación presupuestaria en AP se puede basar en un modelo que incorpore las principales determinantes de la frecuentación de la población y se adecúe a las necesidades reales de ésta. Sería necesario profundizar en aquellos factores que dependen del profesional o de las organizaciones sanitarias para acabar de encontrar un modelo óptimo de asignación de recursos en la AP.

Assessing and coping with the financial burden of computed tomography utilization in Limbe, Cameroon: a sequential explanatory mixed-methods study

BACKGROUND

There has been a significant increase in computed tomography (CT) utilization over the past two decades with the major challenges being a high exposure to ionizing radiation and rising cost. In this study we assess the risk of financial hardship after CT utilization and elaborate on how users adapt and cope in a sub-Saharan context with user fee for services and no national health insurance policy.

METHODS

We carried out a sequential explanatory mixed methods study with a quantitative hospital-based survey of CT users followed by in-depth interviews of some purposively selected participants who reported risk of financial hardship after CT utilization. Data was summarized using frequencies, percentages and 95% confidence intervals. Logistic regression was used in multivariable analysis to determine predictors of risk of financial hardship. Identified themes from in-depth interviews were categorized. Quantitative and qualitative findings were integrated.

RESULTS

A total of 372 participants were surveyed with a male to female sex ratio of 1:1.2. The mean age (standard deviation) was 52(17) years. CT scans of the head and facial bones accounted for 63% (95%CI: 59-68%) and the top three indications were suspected stroke (27% [95%CI: 22-32%]), trauma (14% [95%CI: 10-18%]) and persistent headaches (14% [95%CI: 10-18%]). Seventy-two percent (95%CI: 67-76%) of the respondents reported being at risk of financial hardship after CT utilization and predictors in the multivariable analysis were a low socioeconomic status (aOR: 0.19 [95%CI: 0.10-0.38]; p < 0.001), being unemployed or retired (aOR: 11.75 [95%CI: 2.59-53.18]; p = 0.001) and not having any form of health insurance (aOR: 3.59 [95%CI: 1.31-9.85]; p = 0.013). Coping strategies included getting financial support from family and friends, borrowing money and obtaining discounts from the hospital administration and staff.

CONCLUSION

No health insurance ownership, being unemployed or retired and a low socioeconomic status are associated with financial hardship after CT utilization. Diverse coping strategies are utilized to lessen the financial burden, some with negative consequences. Minimizing out-of-pocket payments and/or the direct cost of CT can reduce this financial burden and improve CT access.

Multidetector computed tomography utilization in an urban sub-Saharan Africa setting: user characteristics, indications and appropriateness

Introduction

multidetector computed tomography (MDCT) is a widely used cross-sectional imaging modality despite increasing concerns about radiation exposure and overuse. The aim of this study was to describe the socio-demographic characteristics of MDCT users in an urban city in Cameroon and to assess the clinical indications for appropriateness.

Methods

we conducted a survey of MDCT users and collected data on demographic attributes and socialization patterns, clinical indications for MDCT and time to obtain MDCT. MDCT appropriateness was assessed using the American College of Radiologists Appropriateness Criteria®. Frequencies, percentages, odds ratios and 95% confidence intervals were used to summarize the data.

Results

with a response rate of 79%, 511 MDCT users were surveyed. The mean (standard deviation) age was 45(19) years and male to female sex ratio 1:1. Seventy-eight percent (95% confidence interval [CI]: 74-83%) of respondents reported not having any health insurance. Head scans accounted for 52% (95%CI: 47-56%) of all scans with trauma (19% [95%CI: 15-22%]), low back pain (18% [95%CI: 14-21%]) and suspected stroke (10% [95%CI: 7-13%]) being the most frequent indications. Sixteen percent (95%CI: 13-20%) of the scans were judged to be inappropriate. Predictors of MDCT appropriateness after multivariable logistic regression modeling were age (aOR=0.97; P=0.009; 95%CI=0.94-0.99), health insurance ownership (aOR=0.40; P=0.034; 95%CI=0.18-0.94) and being referred by non-specialist physicians (aOR=0.20; P<0.001; 95%CI=0.09-0.47).

Conclusion

people from all social strata use MDCT, mostly appropriately and especially for head scans after trauma in this urban setting. However, the proportion of inappropriate studies was considerable suggesting the need for control measures.

Outpatient primary and tertiary healthcare utilisation among public rental housing residents in Singapore

Background

Globally, public housing is utilized to provide affordable housing for low-income households. Studies have shown an association between public housing and negative health outcomes. There is paucity of data pertaining to outpatient primary and tertiary healthcare resources utilization among public rental housing residents in Singapore.

Methods

A retrospective cohort study was performed, involving patients under the care of SingHealth Regional Health System (SHRS) in Year 2012. Healthcare utilization outcomes evaluated included number of outpatient primary and specialist care clinic visits, emergency department visits and hospitalization in Year 2011. Multivariate logistical analyses were used to examine the association between public rental housing and healthcare utilization.

Results

Of 147,105 patients, 10,400 (7.1%) patients stayed in public rental housing. There were more elderly (54.8 ± 18.0 vs 49.8 ± 17.1, p < 0.001) and male patients [5279 (50.8%) vs 56,892 (41.6%), p < 0.001] residing in public rental housing. Co-morbidities such as hypertension and hyperlipidemia were more prevalent among public rental housing patients. (p < 0.05).

After adjustment for covariates, public rental housing was not associated with frequent outpatient primary care clinic or specialist outpatient clinic attendances (p > 0.05). However, it was associated with increased number of emergency department visits (OR: 2.41, 95% CI: 2.12–2.74) and frequent hospitalization (OR: 1.56, 95% CI: 1.33–1.83).

Conclusion

Residing in public rental housing was not associated with increased utilization of outpatient healthcare resources despite patients’ higher disease burden and frequency of emergency department visits and hospitalizations. Further research is required to elucidate their health seeking behaviours.

Electronic supplementary material

The online version of this article (10.1186/s12913-019-4047-8) contains supplementary material, which is available to authorized users.

Impact of a nurse-based intervention on medication outcomes in vulnerable older adults

Background

Medication-related problems are common in older adults with multiple chronic conditions. We evaluated the impact of a nurse-based primary care intervention, based on the Guided Care model of care, on patient-centered aspects of medication use.

Methods

Controlled clinical trial of the Comprehensive Care for Multimorbid Adults Project (CC-MAP), conducted among 1218 participants in 7 intervention clinics and 6 control (usual care) clinics. Inclusion criteria included age 45–94, presence of ≥3 chronic conditions, and Adjusted Clinical Groups (ACG) score > 0.19. The co-primary outcomes were number of changes to the medication regimen between baseline and 9 month followup, and number of changes to symptom-focused medications, markers of attentiveness to medication-related issues.

Results

Mean age in the intervention group was 72 years, 59% were women, and participants used a mean of 6.6 medications at baseline. The control group was slightly older (73 years) and used more medications (mean 7.1). Between baseline and 9 months, intervention subjects had more changes to their medication regimen than control subjects (mean 4.04 vs. 3.62 medication changes; adjusted difference 0.55, p = 0.001). Similarly, intervention subjects had more changes to their symptomatic medications (mean 1.38 vs. 1.26 changes, adjusted difference 0.20, p = 0.003). The total number of medications in use remained stable between baseline and follow-up in both groups (p > 0.18).

Conclusion

This nurse-based, primary care intervention resulted in substantially more changes to patients’ medication regimens than usual care, without increasing the total number of medications used. This enhanced rate of change likely reflects greater attentiveness to the medication-related needs of patients.

Trial registration

This trial is registered at https://clinicaltrials.gov, trial number NCT01811173.

Electronic supplementary material

The online version of this article (10.1186/s12877-018-0905-1) contains supplementary material, which is available to authorized users.

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.

Healthcare disparities amongst vulnerable populations of Arabs and Jews in Israel

The complex nature of studying health and healthcare disparities in general, and in the context of the Israeli healthcare system in particular, is depicted in two recent IJHPR articles. The first examines Emergency Department (ED) waiting times in a tertiary children’s hospital and the second examines disparities in the health care for people with schizophrenia of an ethnic-national minority. Contrary to other Israeli studies on wide disparities in health and healthcare, these studies show no disparities -  ED waiting times did not differ among Arab and Jewish children and report no differences in performance of Hemoglobin A1C tests or in surgical interventions in patients with cardiovascular disease between Arabs and Jews with schizophrenia. Thus, the studies reflect areas of equitable health care delivery within the Israeli healthcare system.

Future studies should account for the fact that the phenomena of health and healthcare disparities is complex and should utilize rigorous methodologies to take into consideration the various factors that may affect the manifestation of differences amongst population groups. As a result, they may help detect disparities which may otherwise be missed.

Income disparities in healthcare use remain after controlling for healthcare need: evidence from Swedish register data on psoriasis and psoriatic arthritis

We used a southern Swedish cohort of psoriasis (PSO) and psoriatic arthritis (PsA) patients and population-based referents (N = 57,800) to investigate the influence of socioeconomic and demographic factors on the probability of healthcare use and on healthcare costs when controlling for need as measured by PSO/PsA and common additional morbidities such as diabetes, depression and myocardial infarction. People with PSO/PsA were identified by ICD-10 codes in the Skåne Healthcare Register 1998-2007. Resource use and costs for years 2008-2011 were retrieved from the Skåne Healthcare Register and the Swedish Prescribed Drug Register, and socioeconomic data were retrieved from Statistics Sweden. After controlling for PSO/PsA and common additional morbidities, income, and to some extent education, had significant effects on the probability of five types of healthcare use. Overall, income showed a bell-shaped relationship to healthcare costs, with patients in income quintiles 2 and 3 having the highest mean annualized cost irrespective of model specification. Education did not have a significant effect in most specifications. Analyses including interaction effects indicated similarly higher costs across income quintiles in the PSO and PsA subgroups, though these cost differences were lower in magnitude for patients with PSO in quintile 5 and with PsA in quintile 1. In conclusion, our results show persistent socioeconomic disparities in healthcare use among a cohort of chronically ill patients and referents, even after controlling for the presence of PSO/PsA and common additional morbidities. These disparities persist even in a country with general healthcare coverage and low out-of-pocket payments.

Epidemic Use of Benzodiazepines among Older Adults in Israel: Epidemiology and Leverage Points for Improvement

BACKGROUND

Benzodiazepines and benzodiazepine-receptor agonists (BDZRAs, often known as "Z-drugs") are commonly used in older adults despite well-documented harms.

OBJECTIVE

To evaluate patterns of benzodiazepine and BDZRA use in Israel, focusing on potential leverage points where quality improvement initiatives might effectively curtail new use or the transition from intermittent to chronic use.

DESIGN AND PARTICIPANTS

We used national electronic medical data to assess a 10% random sample of adults receiving care in Clalit Health Services, which serves half of Israel's population. The sample included 267,221 adults, of whom 56,808 (21%) were age 65 and older.

MAIN MEASURES

Medication use from 2013 to 2015 was ascertained using pharmacy dispensing data.

RESULTS

In 2014, 7% of adults age 21-64 and 32% of adults age 65 and older received at least one benzodiazepine/BDZRA, including 49% of adults age 85 and older (P < 0.001). The majority of older users (59%) were long-term users of the drugs, and 21% of older adults who were short-term users in 2014 transitioned to medium- or long-term use in 2015. Older Arab Israelis were much less likely to receive benzodiazepine/BDZRAs than older Jewish Israelis (adjusted OR 0.28, 95% 0.25-0.31), but within each community there was no major variation in prescribing rates across clinics. Depression diagnosis was associated with particularly high rates of benzodiazepine/BDZRA use: 17% of older adults with depression received a benzodiazepine/BDZRA but no antidepressant, and 42% received both. Recent hospitalization increased the risk of new benzodiazepine/BDZRA use (adjusted OR 1.41, 95% CI 1.01-1.96), but the absolute risk increase was only 3%.

CONCLUSIONS

Benzodiazepines/BDZRAs are used at exceptionally high rates by older Israeli adults, especially the oldest old. Important leverage points for quality improvement efforts include curtailing the transition from short-term to long-term use, reducing use in older adults with depression, and identifying reasons that explain large differences in benzodiazepine/BDZRA prescribing between different ethnic groups.

Measuring inequality in physician distributions using spatially adjusted Gini coefficients

Objective

To measure inequality in physician distributions using Gini coefficient and spatially adjusted Gini coefficients.

Design

Measurements were based on the distribution of physician data from the Taiwan National Health Insurance Research Database (NHIRD) and population data from the Ministry of the Interior in Taiwan.

Settings

The distribution of population and physicians in Taiwan from 2001 to 2010.

Participants

This study considered 35 000 physicians who are registered in Taiwan.

Main Outcome Measures

To calculate the Gini coefficient and spatially adjusted Gini coefficients in Taiwan from 2001 to 2010.

Results

The Gini coefficient for each year, from 2001 to 2010, ranged from 0.5128 to 0.4692, while the spatially adjusted Gini coefficients based on travel time and travel distance ranged, respectively, from 0.4324 to 0.4066 and from 0.4408 to 0.4178. We found that, in each year, irrespective of the type of spatial adjustment, the spatially adjusted Gini coefficient was smaller than the Gini coefficient itself. Our empirical findings support that the Gini coefficient may overestimate the maldistribution of physicians.

Conclusions

Our simulations demonstrate that increasing the number of physicians in medium-sized cities (such as capitals of counties or provinces), and/or improving the transportation time between medium-sized cities and rural areas, could be feasible solutions to mitigate the problem of geographical maldistribution of physicians.

Health information exchange systems and length of stay in readmissions to a different hospital

BACKGROUND

Readmission to a different hospital than the original discharge hospital may result in breakdowns in continuity of care. In different-hospital readmissions (DHRs), continuity can be maintained when hospitals are connected through health information exchange (HIE) systems.

OBJECTIVE

To examine whether length of readmission stay (LORS) differs between same-hospital readmissions and DHRs, and whether in DHRs the LORS differs by the availability of HIE.

DESIGN

A retrospective cohort study of all internal medicine 30-day readmissions in 27 Israeli hospitals between January 1, 2010 and December 31, 2010.

SETTING

Clalit Health Services-Israel's largest integrated healthcare provider and payer.

POPULATION

Adult Clalit members (aged 18 and older) with at least 1 readmission during the study period.

METHODS

A multivariate marginal Cox model tested the likelihood for discharge during each readmission day in same-hospital readmissions (SHRs), DHRs with HIE, and DHRs without HIE.

RESULTS

Of the 27,057 readmissions, 3130 (11.6%) were DHRs and 792 where DHRs with HIE in both the index and readmitting hospital. Partial continuity (DHRs with HIE) was associated with decreased likelihood of discharge on any given day compared with full continuity (SHRs) (hazard ratio [HR] = 0.85, 95% confidence interval [CI]: 0.79-0.91). Similar results were obtained for no continuity (DHRs without HIE) versus full continuity (HR = 0.90, 95% CI: 0.86-0.94). The difference between DHRs with and without HIE was not significant.

CONCLUSIONS

The prolonged LORS in DHRs versus SHRs was not mitigated by the existence of HIE systems. Future research is needed to further elucidate the effects of actual use of HIE on length of DHRs. Journal of Hospital Medicine 2016;11:401-406. © 2015 Society of Hospital Medicine.

Do the Preferences of Healthcare Provider Selection Vary among Rural and Urban Patients with Different Income and Cause Different Outcome?

Background

Equal access to healthcare facilities and high-level quality of care are important strategies to eliminate the disparity in outcome of care. However, the existing literature regarding how urban or rural dwelling patients with different income level select healthcare providers is insufficient. The purposes of this study were to examine whether differences of healthcare provider selection exist among urban and rural coronary artery bypass surgery (CABG) patients with different income level. If so, we further investigated the associated impact on mortality.

Methods

A retrospective, multilevel study design was conducted using claims data from 2007–2011 Taiwan’s Universal Health Insurance Scheme. Healthcare providers’ performance and patients’ travelling distance to hospitals were used to define the patterns of healthcare provider selection. Baron and Kenny’s procedures for mediation effect were conducted.

Results

There were 10,108 CABG surgeries included in this study. The results showed that urban dwelling and higher income patients were prone to receive care from better-performance providers. The travelling distances of urban dwelling patients was 15 KM shorter, especially when they received better-performance provider’s care. The results also showed that the difference of healthcare provider selection and mortality rate existed between rural and urban dwelling patients with different income levels. After the procedure of mediation effect testing, the results showed that the healthcare provider selection partially mediated the relationships between patients’ residential areas with different income levels and 30-day mortality.

Conclusion

Preferences of healthcare provider selection vary among rural and urban patients with different income, and such differences partially mediated the outcome of care. Health authorities should pay attention to this issue, and propose appropriate solutions to eliminate the disparity in outcome of CABG care.

Sustained Reduction in Health Disparities Achieved through Targeted Quality Improvement: One-Year Follow-up on a Three-Year Intervention

OBJECTIVE

To assess a quality improvement disparity reduction intervention and its sustainability.

DATA SOURCES/STUDY SETTING

Electronic health records and Quality Index database of Clalit Health Services in Israel (2008-2012).

STUDY DESIGN

Interrupted time-series with pre-, during, and postintervention disparities measurement between 55 target clinics (serving approximately 400,000 mostly low socioeconomic, minority populations) and all other (126) clinics.

DATA COLLECTION/EXTRACTION METHODS

Data on a Quality Indicator Disparity Scale (QUIDS-7) of 7 indicators, and on a 61-indicator scale (QUIDS-61).

PRINCIPAL FINDINGS

The gap between intervention and nonintervention clinics for QUIDS-7 decreased by 66.7 percent and by 70.4 percent for QUIDS-61. Disparity reduction continued (18.2 percent) during the follow-up period.

CONCLUSIONS

Quality improvement can achieve significant reduction in disparities in a wide range of clinical domains, which can be sustained over time.

Why do outcomes of CABG care vary between urban and rural areas in Taiwan? A perspective from quality of care

OBJECTIVE

This study explores the association between coronary artery bypass surgery (CABG) patients' residence and quality of care in terms of 30-day mortality.

DESIGN

A retrospective, multilevel study design was conducted using claims data from Taiwan's Universal Health Insurance Scheme. Hospital and surgeon's CABG operation volume, risk-adjusted surgical site infection rate and risk-adjusted 30-day mortality rate in the previous year were adopted as performance indicators, and the level of quality was evaluated via K-means clustering algorithm. Baron and Kenny's procedures for mediation effect were conducted.

SETTING

Hospitals in Taiwan.

PARTICIPANTS

Patients who underwent CABG surgeries from 1 January 2008 to 30 September 2011 were identified in this study. However, patients who were under the age of 18 years or above the age of 85(n = 164), with missing data for gender (n = 3) or received surgeries from surgeons who never performed any CABG surgeries (n = 27), were excluded.

INTERVENTIONS

None.

MAIN OUTCOME MEASURES

Thirty-day mortality.

RESULTS

There were 9973 CABG surgeries included in this study. Patients who lived in urban areas received better quality of care (28.90 vs. 21.57%) and enjoyed better outcome (4.33 vs. 6.84%). After the procedure of mediation effect testing, the results showed that the relationship between patient residence's urbanization level and 30-day mortality was partially mediated by patterns of quality of care.

CONCLUSIONS

The rural-dwelling CABG patients are less likely to approach the better performing healthcare providers, and this tendency indirectly affects their treatment outcomes. Policymakers still need to develop strategies to ensure better equity in access to quality health care.

Is socioeconomic status associated with utilization of health care services in a single-payer universal health care system?

Objectives

To assess an association of Socio-economic status with utilization of health care services between years 2002 and 2008 in Israel.

Methods

We retrospectively analyzed the utilization of health care services in a cohort of 100,000 members, 21 years and older, of a Clalit Health Services. The research compared utilization according to the neighborhood SES status; and clinic’s location as another SES proxy. Data included: Charlson Score morbidity factor, utilization of health care services (visits to primary physicians and specialists, purchase of pharmaceuticals, number of hospitalization days, visits to ED, utilization of laboratory tests and imaging). The analysis was performed using Generalized Linear Model (GLM) technique.

Results

People with lower SES visited more the ED and primary physicians and were hospitalized for longer periods. People with higher SES visited more specialists, bought more prescription drugs and used more medical imaging. The associations between SES and most of the services we analyzed did not change between 2002 and 2008. However, the gap between lower and higher SES levels in ED visits and the use of prescription drugs slightly increased over time, while the gap in visits to specialists decreased.

Conclusions

The research shows that even in a universal health care system SES is associated with utilization of health care services. In order to improve equity in utilization of services the Israeli public health should reduce economic barriers and in parallel invest in making information accessible to improve “navigation skills” for all.

Do low-income coronary artery bypass surgery patients have equal opportunity to access excellent quality of care and enjoy good outcome in Taiwan?

BACKGROUND

Equity is an important issue in the healthcare research field. Many studies have focused on the relationship between patient characteristics and outcomes of care. These studies, however, have seldom examined whether patients' characteristics affected their access to quality healthcare, which further affected the care outcome. The purposes of this study were to determine whether low-income coronary artery bypass surgery (CABG) patients receive healthcare services with poorer quality, and if such differences in treatment result in different outcomes.

METHODS

A retrospective multilevel study design was conducted using claims data from Taiwan's universal health insurance scheme for 2005-2008. Patients who underwent their CABG surgery between 2006 and 2008 were included in this study. CABG patients who were under 18 years of age or had unknown gender or insured classifications were excluded. Hospital and surgeon's performance indicators in the previous one year were used to evaluate the level of quality via k-means clustering algorithm. Baron and Kenny's procedures for mediation effect were conducted to explore the relationship among patient's income, quality of CABG care, and inpatient mortality.

RESULTS

A total of 10,320 patients were included in the study. The results showed that 5.65% of the low-income patients received excellent quality of care, which was lower than that of patients not in the low-income group (5.65% vs.11.48%). The mortality rate of low-income patients (12.10%) was also higher than patients not in the low-income group (5.25%). Also, the mortality of patients who received excellent care was half as low as patients receiving non-excellent care (2.63% vs. 5.68%). Finally, after the procedure of mediation effect testing, the results showed that the relationship between patient income level and CABG mortality was partially mediated by patterns of quality of care.

CONCLUSIONS

The results of the current study implied that worse outcome in low-income CABG patients might be associated with poorer quality of received services. Health authorities should pay attention to this issue, and propose appropriate solutions.

Utilization of primary and secondary medical care among disadvantaged populations: a log-linear model analysis

AIM

We examined how, where an overall population is covered by universal health insurance, characteristics of disadvantaged populations interact to influence inequality in primary and secondary medical care utilization.

SUBJECTS & METHODS

Disadvantaged populations, the focus of the study, were defined as populations who have lower socio-economic status (SES), who are elderly and/or reside in a peripheral area. Data from the 2009 Israeli National Health Survey were analysed using log-linear models to estimate utilization of medical care.

RESULTS

The main findings were: a) pro-poor utilization of primary medical care among elderly populations, with higher odds ratios for low SES populations in the periphery; (b) lack of interaction between SES and primary medical care utilization among younger populations, between SES and secondary medical care utilization among the elderly and pro-rich utilization of secondary medical care among younger populations who did not regularly visit general practitioners (GP); (c) the odds ratios of secondary medical care utilization increased as SES decreased for both elderly and younger populations who also regularly visited a GP.

CONCLUSION

Potential policy implications for disadvantaged populations, regarding possible inequality in primary and secondary medical care utilization, can be drawn using log-linear model analysis of interactions among characteristics (SES, age, location) of disadvantaged populations.

Disparities in multiple chronic conditions within populations

Disadvantaged populations are disproportionately affected by multiple chronic conditions (MCCs), yet few studies examine the prevalence, outcomes, or effectiveness of MCC interventions in minority and socioeconomically deprived individuals and populations. An important first step in understanding MCCs, not only in such diverse population groups, but also in the general population as a whole, is to broaden the definition and scope of MCC measurement, to encompass more than the simple additive effect of clinical conditions, and to include a wide range of health and health-related aspects that interact and make up the full spectrum of multimorbidity. Only with the use of a comprehensive MCC measurement can some of the differences between the disadvantaged populations be adequately detected. Better understanding of the disparities in access to high quality health and healthcare for persons with MCCs can help guide policy and practice aimed at the prevention and amelioration of the effects of MCCs among disadvantaged groups. Indeed, disparity in MCC populations has been identified as a key goal of the U.S. Department of Health and Human Services’ Strategic Framework on MCCs. The aim of the present paper is to describe current knowledge on disparities in the population of persons with MCCs and to guide efforts for the prevention and management of MCCs in disadvantaged populations.

Journal of Comorbidity 2013;3:45–50

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.

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.

Targeting patients for multimorbid care management interventions: the case for equity in high-risk patient identification

Targeting patients for multimorbid care management interventions requires accurate and comprehensive assessment of patients’ need in order to direct resources to those who need and can benefit from them the most. Multimorbid patient selection is complicated due to the lack of clear criteria - unlike disease management programs for which patients with a specific condition are identified. This ambiguity can potentially result in inequitable selection, as biases in selection may differentially affect patients from disadvantaged population groups. Patient selection could in principal be performed in three ways: physician referral, patient screening surveys, or by statistical prediction algorithms. This paper discusses equity issues related to each method. We conclude that each method may result in inequitable selection and bias, such as physicians’ attentiveness or familiarity, or prediction models’ reliance on prior resource use, potentially affected by socio-cultural and economic barriers. These biases should be acknowledged and dealt with. We recommend combining patient selection approaches to achieve high care sensitivity, efficiency and equity.

Multimorbidity and its measurement

Multimorbidity is increasing in frequency. It can be quantitatively measured and is a major correlate of high use of health services resources of all types, especially over time. The ACG System for characterizing multimorbidity is the only widely used method that is based on combinations of different TYPES of diagnoses over time, rather than the presence or absence of particular conditions or numbers of conditions. It incorporates administrative data (as from claims forms or medical records) on all types of encounters and is not limited to diagnoses captured during hospitalizations or other places of encounter. It can be employed in any one or combination of analytic models, and can incorporate medication use if desired. It is being used in clinical care, management of health services resources, in health services research to control for degree of morbidity, and in understanding morbidity patterns over time. In addition to its research uses, it is being employed in many countries in various applications as a policy to better understand health needs of populations and tailor health services resources to health needs.