Population based resource allocation: The use of hybrid risk adjustment

The emphasis on integrated care implies new incentives that promote coordinationbetween levels of care. Considering a population as a whole, the resource allocation systemhas to adapt to this environment. This research is aimed to design a model that allows formorbidity related prospective and concurrent capitation payment. The model can be applied inpublicly funded health systems and managed competition settings.Methods: We analyze the application of hybrid risk adjustment versus either prospective orconcurrent risk adjustment formulae in the context of funding total health expenditures for thepopulation of an integrated healthcare delivery organization in Catalonia during years 2004 and2005.Results: The hybrid model reimburses integrated care organizations avoiding excessive risktransfer and maximizing incentives for efficiency in the provision. At the same time, it eliminatesincentives for risk selection for a specific set of high risk individuals through the use ofconcurrent reimbursement in order to assure a proper classification of patients.Conclusion: Prospective Risk Adjustment is used to transfer the financial risk to the healthprovider and therefore provide incentives for efficiency. Within the context of a National HealthSystem, such transfer of financial risk is illusory, and the government has to cover the deficits.Hybrid risk adjustment is useful to provide the right combination of incentive for efficiency andappropriate level of risk transfer for integrated care organizations.

Hybrid risk adjustment for pharmaceutical benefits

This paper analyses the application of hybrid risk adjustment versus either prospective orconcurrent risk adjustment formulae in the context of funding pharmaceutical benefits for thepopulation of an integrated healthcare delivery organization in Catalonia during years 2002 and2003. We apply a mixed formula and find that a hybrid risk adjustment model increasesincentives for efficiency in the provision of low risk individuals at health organizations not only asa whole but also at each internal department compared to only prospective models by reducingwithin-group variation of drug expenditures.

Criação de valor, gestão de risco e as medidas de performance ajustadas ao risco: aplicação do RAROC - Risk Adjustment Return on Capital - ao grupo crédito agrícola

Mestrado em Contabilidade e Gestão das Instituições Financeiras

Neonatal mortality: description and effect of hospital of birth after risk adjustment

OBJECTIVE: To assess the effect of hospital of birth on neonatal mortality. METHODS: A birth cohort study was carried out in Pelotas, Southern Brazil, in 2004. All hospital births were assessed by daily visits to all maternity hospitals and 4558 deliveries were included in the study. Mothers were interviewed regarding potential risk factors. Deaths were monitored through regular visits to hospitals, cemeteries and register offices. Two independent pediatricians established the underlying cause of death based on information obtained from medical records and home visits to parents. Logistic regression was used to estimate the effect of hospital of birth, controlling for confounders related to maternal and newborn characteristics, according to a conceptual model. RESULTS: Neonatal mortality rate was 12.7‰ and it was highly influenced by birthweight, gestational age, and socioeconomic variables. Immaturity was responsible for 65% of neonatal deaths, followed by congenital anomalies, infections and intrapartum asphyxia. Adjusting for maternal characteristics, a three-fold increase in neonatal mortality was seen between similar complexity hospitals. The effect of hospital remained, though lower, after controlling for newborn characteristics. CONCLUSIONS: Neonatal mortality was high, mainly related to immaturity, and varied significantly across maternity hospitals. Further investigations comparing delivery care practices across hospitals are needed to better understand NMR variation and to develop strategies for neonatal mortality reduction.

Supply-side risk adjustment and outlier payment policy

In most health care systems where a prospective payment system is implemented, an outlier payment is used to cover the hospitals' unusually high costs. When the hospital chooses its cost reduction effort before observing a patient's severity, we show that the best outlier payment is based on the realized cost when the hospital exerts the first best level of effort, for any level of severity. [Authors]

Updating and validating the Charlson comorbidity index and score for risk adjustment in hospital discharge abstracts using data from 6 countries.

With advances in the effectiveness of treatment and disease management, the contribution of chronic comorbid diseases (comorbidities) found within the Charlson comorbidity index to mortality is likely to have changed since development of the index in 1984. The authors reevaluated the Charlson index and reassigned weights to each condition by identifying and following patients to observe mortality within 1 year after hospital discharge. They applied the updated index and weights to hospital discharge data from 6 countries and tested for their ability to predict in-hospital mortality. Compared with the original Charlson weights, weights generated from the Calgary, Alberta, Canada, data (2004) were 0 for 5 comorbidities, decreased for 3 comorbidities, increased for 4 comorbidities, and did not change for 5 comorbidities. The C statistics for discriminating in-hospital mortality between the new score generated from the 12 comorbidities and the Charlson score were 0.825 (new) and 0.808 (old), respectively, in Australian data (2008), 0.828 and 0.825 in Canadian data (2008), 0.878 and 0.882 in French data (2004), 0.727 and 0.723 in Japanese data (2008), 0.831 and 0.836 in New Zealand data (2008), and 0.869 and 0.876 in Swiss data (2008). The updated index of 12 comorbidities showed good-to-excellent discrimination in predicting in-hospital mortality in data from 6 countries and may be more appropriate for use with more recent administrative data.

Risk adjustment in Switzerland

In Switzerland the new law on Health Insurance, effective since 1996, introduced pro competitive changes in the market of sickness funds. The legislator expected high mobility between sickness funds of both healthy and sick insured as open enrolment was introduced with the new law. That is why the risk adjustment scheme, that was already introduced 1993, was limited until 2005. However, consumer mobility remained low and risk selection strategies are still profitable, since risk-adjustment is based only on demographic variables. This paper describes risk adjustment, consumer mobility, risk selection activities of sickness funds and the impact of imperfect risk adjustment on the development of HMO and PPO models. The paper concludes with a description of the current political and scientific discussion in Switzerland.

Risk adjustment in aging societies

Background In Switzerland, age is the predominant driver of solidarity transfers in risk adjustment (RA). Concerns have been voiced regarding growing imbalances in cost sharing between young and old insured due to demographic changes (larger fraction of elderly >65 years and rise in average age). Particularly young adults aged 19–25 with limited incomes have to shoulder increasing solidarity burdens. Between 1996 and 2011, monthly intergenerational solidarity payments for young adults have doubled from CHF 87 to CHF 182, which corresponds to the highest absolute transfer increase of all age groups. Results By constructing models for age-specific RA growth and for calculating the lifetime sum of RA transfers we investigated the causes and consequences of demographic changes on RA payments. The models suggest that the main driver for RA increases in the past was below average health care expenditure (HCE) growth in young adults, which was only half as high (average 2% per year) compared with older adults (average 4% per year). Shifts in age group distributions were only accountable for 2% of the CHF 95 rise in RA payments. Despite rising risk adjustment debts for young insured the balance of lifetime transfers remains positive as long as HCE growth rates are greater than the discount rate used in this model (3%). Moreover, the life-cycle model predicts that the lifetime rate of return on RA payments may even be further increased by demographic changes. Nevertheless, continued growth of RA contributions may overwhelm vulnerable age groups such as young adults. We therefore propose methods to limit the burden of social health insurance for specific age groups (e.g. young adults in Switzerland) by capping solidarity payments. Conclusions Taken together, our mathematical modelling framework helps to gain a better understanding of how demographic changes interact with risk adjustment and how redistribution of funds between age groups can be controlled without inducing further selection incentives. Those methods can help to construct more equitable systems of health financing in light of population aging.

Evidence that risk adjustment is unnecessary in estimates of the User cost of money

Investors value the special attributes of monetary assets (e.g., exchangeability, liquidity, and safety) and pay a premium for holding them in the form of a lower return rate -- The user cost of holding monetary assets can be measured approximately by the difference between the returns on illiquid risky assets and those of safer liquid assets -- A more appropriate measure should adjust this difference by the differential risk of the assets in question -- We investigate the impact that time non-separable preferences has on the estimation of the risk-adjusted user cost of money -- Using U.K. data from 1965Q1 to 2011Q1, we estimate a habit-based asset pricing model with money in the utility function and find that the risk adjustment for risky monetary assets is negligible -- Thus, researchers can dispense with risk adjusting the user cost of money in constructing monetary aggregate indexes

Comorbidity adjustment index for the international classification of diseases, 10

OBJECTIVE: To develop a Charlson-like comorbidity index based on clinical conditions and weights of the original Charlson comorbidity index. METHODS: Clinical conditions and weights were adapted from the International Classification of Diseases, 10th revision and applied to a single hospital admission diagnosis. The study included 3,733 patients over 18 years of age who were admitted to a public general hospital in the city of Rio de Janeiro, southeast Brazil, between Jan 2001 and Jan 2003. The index distribution was analyzed by gender, type of admission, blood transfusion, intensive care unit admission, age and length of hospital stay. Two logistic regression models were developed to predict in-hospital mortality including: a) the aforementioned variables and the risk-adjustment index (full model); and b) the risk-adjustment index and patient's age (reduced model). RESULTS: Of all patients analyzed, 22.3% had risk scores >1, and their mortality rate was 4.5% (66.0% of them had scores >1). Except for gender and type of admission, all variables were retained in the logistic regression. The models including the developed risk index had an area under the receiver operating characteristic curve of 0.86 (full model), and 0.76 (reduced model). Each unit increase in the risk score was associated with nearly 50% increase in the odds of in-hospital death. CONCLUSIONS: The risk index developed was able to effectively discriminate the odds of in-hospital death which can be useful when limited information is available from hospital databases.

Self-selection and risk selection on the Swiss health insurance market

Abstract This thesis presents three empirical studies in the field of health insurance in Switzerland. First we investigate the link between health insurance coverage and health care expenditures. We use claims data for over 60 000 adult individuals covered by a major Swiss Health Insurance Fund, followed for four years; the data show a strong positive correlation between coverage and expenditures. Two methods are developed and estimated in order to separate selection effects (due to individual choice of coverage) and incentive effects ("ex post moral hazard"). The first method uses the comparison between inpatient and outpatient expenditures to identify both effects and we conclude that both selection and incentive effects are significantly present in our data. The second method is based on a structural model of joint demand of health care and health insurance and makes the most of the change in the marginal cost of health care to identify selection and incentive effects. We conclude that the correlation between insurance coverage and health care expenditures may be decomposed into the two effects: 75% may be attributed to selection, and 25 % to incentive effects. Moreover, we estimate that a decrease in the coinsurance rate from 100% to 10% increases the marginal demand for health care by about 90% and from 100% to 0% by about 150%. Secondly, having shown that selection and incentive effects exist in the Swiss health insurance market, we present the consequence of this result in the context of risk adjustment. We show that if individuals choose their insurance coverage in function of their health status (selection effect), the optimal compensations should be function of the se- lection and incentive effects. Therefore, a risk adjustment mechanism which ignores these effects, as it is the case presently in Switzerland, will miss his main goal to eliminate incentives for sickness funds to select risks. Using a simplified model, we show that the optimal compensations have to take into account the distribution of risks through the insurance plans in case of self-selection in order to avoid incentives to select risks.Then, we apply our propositions to Swiss data and propose a simple econometric procedure to control for self-selection in the estimation of the risk adjustment formula in order to compute the optimal compensations.

External validation of the Hospital-patient One-year Mortality Risk (HOMR) model for predicting death within 1 year after hospital admission

BACKGROUND Predicting long-term survival after admission to hospital is helpful for clinical, administrative and research purposes. The Hospital-patient One-year Mortality Risk (HOMR) model was derived and internally validated to predict the risk of death within 1 year after admission. We conducted an external validation of the model in a large multicentre study. METHODS We used administrative data for all nonpsychiatric admissions of adult patients to hospitals in the provinces of Ontario (2003-2010) and Alberta (2011-2012), and to the Brigham and Women's Hospital in Boston (2010-2012) to calculate each patient's HOMR score at admission. The HOMR score is based on a set of parameters that captures patient demographics, health burden and severity of acute illness. We determined patient status (alive or dead) 1 year after admission using population-based registries. RESULTS The 3 validation cohorts (n = 2,862,996 in Ontario, 210 595 in Alberta and 66,683 in Boston) were distinct from each other and from the derivation cohort. The overall risk of death within 1 year after admission was 8.7% (95% confidence interval [CI] 8.7% to 8.8%). The HOMR score was strongly and significantly associated with risk of death in all populations and was highly discriminative, with a C statistic ranging from 0.89 (95% CI 0.87 to 0.91) to 0.92 (95% CI 0.91 to 0.92). Observed and expected outcome risks were similar (median absolute difference in percent dying in 1 yr 0.3%, interquartile range 0.05%-2.5%). INTERPRETATION The HOMR score, calculated using routinely collected administrative data, accurately predicted the risk of death among adult patients within 1 year after admission to hospital for nonpsychiatric indications. Similar performance was seen when the score was used in geographically and temporally diverse populations. The HOMR model can be used for risk adjustment in analyses of health administrative data to predict long-term survival among hospital patients.

Effect of Oral Hygiene with 0.12% Chlorhexidine Gluconate on the Incidence of Nosocomial Pneumonia in Children Undergoing Cardiac Surgery

OBJECTIVE. To evaluate the effect of oral hygiene with 0.12% chlorhexidine gluconate on the incidence of nosocomial pneumonia and ventilator-associated pneumonia (VAP) in children undergoing cardiac surgery. DESIGN. Prospective, randomized, double-blind, placebo-controlled trial. SETTING. Pediatric intensive care unit (PICU) at a tertiary care hospital. patients. One hundred sixty children undergoing surgery for congenital heart disease, randomized into 2 groups: chlorhexidine (n = 87) and control (n = 73). INTERVENTIONS. Oral hygiene with 0.12% chlorhexidine gluconate or placebo preoperatively and twice a day postoperatively until PICU discharge or death. RESULTS. Patients in experimental and control groups had similar ages (median, 12.2 vs 10.8 months; P =. 72) and risk adjustment for congenital heart surgery 1 score distribution (66% in category 1 or 2 in both groups; P =. 17). The incidence of nosocomial pneumonia was 29.8% versus 24.6% (Pp. 46) and the incidence of VAP was 18.3% versus 15% (Pp. 57) in the chlorhexidine and the control group, respectively. There was no difference in intubation time (P =. 34), need for reintubation (P =. 37), time interval between hospitalization and nosocomial pneumonia diagnosis (P =. 63), time interval between surgery and nosocomial pneumonia diagnosis (P =. 10), and time on antibiotics (P =. 77) and vasoactive drugs (P =. 16) between groups. Median length of PICU stay (3 vs 4 days; P =. 53), median length of hospital stay (12 vs 11 days; P =. 67), and 28-day mortality (5.7% vs 6.8%; P =. 77) were also similar in the chlorhexidine and the control group. CONCLUSIONS. Oral hygiene with 0.12% chlorhexidine gluconate did not reduce the incidence of nosocomial pneumonia and VAP in children undergoing cardiac surgery.

O financiamento por capitação ajustada pelo risco em contexto de integração vertical de cuidados de saúde : a utilização dos consumos com medicamentos como proxy da carga de doença em ambulatório

RESUMO - Introdução - Com o presente projecto de investigação pretendeu-se estudar o financiamento por capitação ajustado pelo risco em contexto de integração vertical de cuidados de saúde, recorrendo particularmente a informação sobre o consumo de medicamentos em ambulatório como proxy da carga de doença. No nosso país, factores como a expansão de estruturas de oferta verticalmente integradas, inadequação histórica da sua forma de pagamento e a recente possibilidade de dispor de informação sobre o consumo de medicamentos de ambulatório em bases de dados informatizadas são três fortes motivos para o desenvolvimento de conhecimento associado a esta temática. Metodologia - Este trabalho compreende duas fases principais: i) a adaptação e aplicação de um modelo de consumo de medicamentos que permite estimar a carga de doença em ambulatório (designado de PRx). Nesta fase foi necessário realizar um trabalho de selecção, estruturação e classificação do modelo. A sua aplicação envolveu a utilização de bases de dados informatizadas de consumos com medicamentos nos anos de 2007 e 2008 para a região de Saúde do Alentejo; ii) na segunda fase foram simulados três modelos de financiamento alternativos que foram propostos para financiar as ULS em Portugal. Particularmente foram analisadas as dimensões e variáveis de ajustamento pelo risco (índices de mortalidade, morbilidade e custos per capita), sua ponderação relativa e consequente impacto financeiro. Resultados - Com o desenvolvimento do modelo PRx estima-se que 36% dos residentes na região Alentejo têm pelo menos uma doença crónica, sendo a capacidade de estimação do modelo no que respeita aos consumos de medicamentos na ordem dos 0,45 (R2). Este modelo revelou constituir uma alternativa a fontes de informação tradicionais como são os casos de outros estudos internacionais ou o Inquérito Nacional de Saúde. A consideração dos valores do PRx para efeitos de financiamento per capita introduz alterações face a outros modelos propostos neste âmbito. Após a análise dos montantes de financiamento entre os cenários alternativos, obtendo os modelos 1 e 2 níveis de concordância por percentil mais próximos entre si comparativamente ao modelo 3, seleccionou-se o modelo 1 como o mais adequado para a nossa realidade. Conclusão - A aplicação do modelo PRx numa região de saúde permitiu concluir em função dos resultados alcançados, que já existe a possibilidade de estruturação e operacionalização de um modelo que permite estimar a carga de doença em ambulatório a partir de informação relativa ao seu perfil de consumo de medicamentos dos utentes. A utilização desta informação para efeitos de financiamento de organizações de saúde verticalmente integradas provoca uma variação no seu actual nível de financiamento. Entendendo este estudo como um ponto de partida onde apenas uma parte da presente temática ficará definida, outras questões estruturantes do actual sistema de financiamento não deverão também ser olvidadas neste contexto. ------- ABSTRACT - Introduction - The main goal of this study was the development of a risk adjustment model for financing integrated delivery systems (IDS) in Portugal. The recent improvement of patient records, mainly at primary care level, the historical inadequacy of payment models and the increasing number of IDS were three important factors that drove us to develop new approaches for risk adjustment in our country. Methods - The work was divided in two steps: the development of a pharmacy-based model in Portugal and the proposal of a risk adjustment model for financing IDS. In the first step an expert panel was specially formed to classify more than 33.000 codes included in Portuguese pharmacy national codes into 33 chronic conditions. The study included population of Alentejo Region in Portugal (N=441.550 patients) during 2007 and 2008. Using pharmacy data extracted from three databases: prescription, private pharmacies and hospital ambulatory pharmacies we estimated a regression model including Potential Years of Life Lost, Complexity, Severity and PRx information as dependent variables to assess total cost as the independent variable. This healthcare financing model was compared with other two models proposed for IDS. Results - The more prevalent chronic conditions are cardiovascular (34%), psychiatric disorders (10%) and diabetes (10%). These results are also consistent with the National Health Survey. Apparently the model presents some limitations in identifying patients with rheumatic conditions, since it underestimates prevalence and future drug expenditure. We obtained a R2 value of 0,45, which constitutes a good value comparing with the state of the art. After testing three scenarios we propose a model for financing IDS in Portugal. Conclusion - Drug information is a good alternative to diagnosis in determining morbidity level in a population basis through ambulatory care data. This model offers potential benefits to estimate chronic conditions and future drug costs in the Portuguese healthcare system. This information could be important to resource allocation decision process, especially concerning risk adjustment and healthcare financing.