Risk adjustment for health care financing in chronic disease: what are we missing by failing to account for disease severity?

Effect of BMI on health care expenditures stratified by COPD GOLD severity grades: Results from the LQ-DMP study

Chronic Obstructive Pulmonary Disease (COPD) is characterized by persistent respiratory symptoms and airflow limitation, which is progressive and not fully reversible. In patients with COPD, body mass index (BMI) is an important parameter associated with health outcomes, e.g. mortality and health-related quality of life. However, so far no study evaluated the association of BMI and health care expenditures across different COPD severity grades. We used claims data and documentation data of a Disease Management Program (DMP) from a statutory health insurance fund (AOK Bayern). Patients were excluded if they had less than 4 observations in the 8 years observational period. Generalized additive mixed models with smooth functions were used to evaluate the association between BMI and health care expenditures, stratified by severity of COPD, indicated by GOLD grades 1-4. We included 30,682 patients with overall 188,725 observations. In GOLD grades 1-3 we found an u-shaped relation of BMI and expenditures, where patients with a BMI of 30 or slightly above had the lowest and underweight and obese patients had the highest health care expenditures. Contrarily, in GOLD grade 4 we found an almost linear decline of health care expenditures with increasing BMI. In terms of expenditures, the often reported obesity paradox in patients with COPD was clearly reflected in GOLD grade 4, while in all other severity grades underweight as well as severely obese patients caused the highest health care expenditures. Reduction of obesity may thus reduce health care expenditures in GOLD grades 1-3.

Unlocking the Potential of Electronic Health Records for Health Research

Electronic health records (EHRs), originally designed to facilitate health care delivery, are becoming a valuable data source for health research. EHR systems have two components, both of which have various components, and points of data entry, management, and analysis. The “front end” refers to where the data are entered, primarily by healthcare workers (e.g. physicians and nurses). The second component of EHR systems is the electronic data warehouse, or “back-end,” where the data are stored in a relational database. EHR data elements can be of many types, which can be categorized as structured, unstructured free-text, and imaging data. The Sunrise Clinical Manager (SCM) EHR is one example of an inpatient EHR system, which covers the city of Calgary (Alberta, Canada). This system, under the management of Alberta Health Services, is now being explored for research use. The purpose of the present paper is to describe the SCM EHR for research purposes, showing how this generalizes to EHRs in general. We further discuss advantages, challenges (e.g. potential bias and data quality issues), analytical capacities, and requirements associated with using EHRs in a health research context.

Combining Nonclinical Determinants of Health and Clinical Data for Research and Evaluation: Rapid Review

Background

Nonclinical determinants of health are of increasing importance to health care delivery and health policy. Concurrent with growing interest in better addressing patients’ nonmedical issues is the exponential growth in availability of data sources that provide insight into these nonclinical determinants of health.

Objective

This review aimed to characterize the state of the existing literature on the use of nonclinical health indicators in conjunction with clinical data sources.

Methods

We conducted a rapid review of articles and relevant agency publications published in English. Eligible studies described the effect of, the methods for, or the need for combining nonclinical data with clinical data and were published in the United States between January 2010 and April 2018. Additional reports were obtained by manual searching. Records were screened for inclusion in 2 rounds by 4 trained reviewers with interrater reliability checks. From each article, we abstracted the measures, data sources, and level of measurement (individual or aggregate) for each nonclinical determinant of health reported.

Results

A total of 178 articles were included in the review. The articles collectively reported on 744 different nonclinical determinants of health measures. Measures related to socioeconomic status and material conditions were most prevalent (included in 90% of articles), followed by the closely related domain of social circumstances (included in 25% of articles), reflecting the widespread availability and use of standard demographic measures such as household income, marital status, education, race, and ethnicity in public health surveillance. Measures related to health-related behaviors (eg, smoking, diet, tobacco, and substance abuse), the built environment (eg, transportation, sidewalks, and buildings), natural environment (eg, air quality and pollution), and health services and conditions (eg, provider of care supply, utilization, and disease prevalence) were less common, whereas measures related to public policies were rare. When combining nonclinical and clinical data, a majority of studies associated aggregate, area-level nonclinical measures with individual-level clinical data by matching geographical location.

Conclusions

A variety of nonclinical determinants of health measures have been widely but unevenly used in conjunction with clinical data to support population health research.

Medical expenditure estimation by Bayesian network for lung cancer patients at different severity stages

Lung cancer is one of the leading causes of mortality, and its medical expenditure has increased dramatically. Estimating the expenditure for this disease has become an urgent concern of the supporting families, medial institutes, and government. In this study, a conditional Gaussian Bayesian network (CGBN) model was developed to incorporate the comprehensive risk factors to estimate the medical expenditure of a lung cancer patient at different stages. A total of 961 patients were surveyed by the four severity stages of lung cancer. The proposed CGBN model identified the correlation and association of 15 risk factors to the medical expenditure of different severity stages of lung cancer patients. The relationships among the demographic, diagnosed-based, and prior-utilization variables are constructed. The model predicted the lung cancer-related medical expenditure with high accuracy of 32.63%, 50.30%, 50.36%, and 66.58%, respectively for stages 1-4, as compared with the reported models. A greedy search was also applied to find the upper threshold of R², while our model also shows that it approached the upper threshold.

Value-based provider payment: towards a theoretically preferred design

Worldwide, policymakers and purchasers are exploring innovative provider payment strategies promoting value in health care, known as value-based payments (VBP). What is meant by 'value', however, is often unclear and the relationship between value and the payment design is not explicated. This paper aims at: (1) identifying value dimensions that are ideally stimulated by VBP and (2) constructing a framework of a theoretically preferred VBP design. Based on a synthesis of both theoretical and empirical studies on payment incentives, we conclude that VBP should consist of two components: a relatively large base payment that implicitly stimulates value and a relatively small payment that explicitly rewards measurable aspects of value (pay-for-performance). Being the largest component, the base payment design is essential, but often neglected when it comes to VBP reform. We explain that this base payment ideally (1) is paid to a multidisciplinary provider group (2) for a cohesive set of care activities for a predefined population, (3) is fixed, (4) is adjusted for the population's risk profile and (5) includes risk-mitigating measures. Finally, some important trade-offs in the practical operationalisation of VBP are discussed.

Long-Term Effectiveness of the Live Zoster Vaccine in Preventing Shingles: A Cohort Study

A live attenuated zoster vaccine was licensed in the United States in 2006 for prevention of shingles in persons aged 60 years or older; the indication was extended in 2011 to cover those aged 50-59 years. We assessed vaccine effectiveness (VE) against shingles for 8 years after immunization at Kaiser Permanente Northern California. VE was estimated by Cox regression with a calendar timeline that was stratified by birth year. We adjusted for demographics and time-varying covariates, including comorbidities and immune compromise. From 2007 to 2014, 1.4 million people entered the study when they became age eligible for vaccination; 392,677 (29%) received the zoster vaccine. During 5.8 million person-years of follow-up, 48,889 cases of shingles were observed, including 5,766 among vaccinees. VE was 49.1% (95% confidence interval (CI): 47.5, 50.6) across all follow-up. VE was 67.5% (95% CI: 65.4, 69.5) during the first year after vaccination, waned to 47.2% (95% CI: 44.1, 50.1) during the second year after vaccination, and then waned more gradually through year 8, when VE was 31.8% (95% CI: 15.1, 45.2). Unexpectedly, VE in persons vaccinated when they were aged 80 years or older was similar to VE in younger vaccinees, and VE in persons vaccinated when immune compromised was similar to VE in persons vaccinated when immune competent.

Hospital Utilization Among Children With the Highest Annual Inpatient Cost

BACKGROUND AND OBJECTIVES

Children who experience high health care costs are increasingly enrolled in clinical initiatives to improve their health and contain costs. Hospitalization is a significant cost driver. We describe hospitalization trends for children with highest annual inpatient cost (CHIC) and identify characteristics associated with persistently high inpatient costs in subsequent years.

METHODS

Retrospective study of 265 869 children age 2 to 15 years with ≥1 admission in 2010 to 39 children's hospitals in the Pediatric Health Information System. CHIC were defined as the top 10% of total inpatient costs in 2010 (n = 26 574). Multivariate regression and regression tree modeling were used to distinguish individual characteristics and interactions of characteristics, respectively, associated with persistently high inpatient costs (≥80th percentile in 2011 and/or 2012).

RESULTS

The top 10% most expensive children (CHIC) constituted 56.9% ($2.4 billion) of total inpatient costs in 2010. Fifty-eight percent (n = 15 391) of CHIC had no inpatient costs in 2011 to 2012, and 27.0% (n = 7180) experienced persistently high inpatient cost. Respiratory chronic conditions (odds ratio [OR] = 3.0; 95% confidence interval [CI], 2.5-3.5), absence of surgery in 2010 (OR = 2.0; 95% CI, 1.8-2.1), and technological assistance (OR = 1.6; 95% CI, 1.5-1.7) were associated with persistently high inpatient cost. In regression tree modeling, the greatest likelihood of persistence (65.3%) was observed in CHIC with ≥3 hospitalizations in 2010 and a chronic respiratory condition.

CONCLUSIONS

Most children with high children's hospital inpatient costs in 1 year do not experience hospitalization in subsequent years. Interactions of hospital use and clinical characteristics may be helpful to determine which children will continue to experience high inpatient costs over time.

Identifying Future High Cost Individuals within an Intermediate Cost Population

BACKGROUND

Improving health and controlling healthcare costs requires better tools for predicting future health needs across populations. We sought to identify factors associated with transitioning of enrollees in an indigent care program from an intermediate cost segment to a high cost segment of this population.

METHODS

We analyzed data from 9,624 enrollees of the Virginia Coordinated Care program between 2010 and 2013. Each fiscal year included all enrollees who were classified in intermediate cost segment in the preceding year and also enrolled in the program in the following year. Using information from the preceding year, we built logistic regression models to identify the individuals in the top 10% of expenditures in the following year. The effect of demographics, count of chronic conditions, presence of the prevalent chronic conditions, and utilization indicators were evaluated and compared. Models were compared via the Bayesian information criterion and c-statistic.

RESULTS

The count of chronic conditions, diagnosis of congestive heart failure, and numbers of total hospital visits and prescriptions were significantly and independently associated with being in the future high cost segment. Overall, the model that included demographics and utilization indicators had a reasonable discrimination (c=0.67).

CONCLUSIONS

A simple model including demographics and health utilization indicators predicted high future costs. The count of chronic conditions and certain medical diagnoses added additional predictive value. With further validation, the approach could be used to identify high-risk individuals and target interventions that decrease utilization and improve health.

Problematic clinical features of powered wheelchair users with severely disabling multiple sclerosis

PURPOSE

The aim of this study is to describe the clinical features of powered wheelchair users with severely disabling multiple sclerosis (MS) and explore the problematic clinical features influencing prescription.

METHOD

Retrospective review of electronic and case note records of recipients of electric-powered indoor/outdoor powered wheelchairs (EPIOCs) attending a specialist wheelchair service between June 2007 and September 2008. Records were reviewed by a consultant in rehabilitation medicine, data systematically extracted and entered into a computer database. Further data were entered from clinical records. Data were extracted under three themes; demographic, diagnostic, clinical and wheelchair factors.

RESULTS

Records of 28 men mean age 57 (range 37-78, SD 12) years and 63 women mean age 57 (range 35-81, SD 11) years with MS were reviewed a mean of 64 (range 0-131) months after receiving their wheelchair. Twenty two comorbidities, 11 features of MS and 8 features of disability were thought to influence wheelchair prescription. Fifteen users were provided with specialised seating and 46 with tilt-in-space seats.

CONCLUSIONS

Our findings suggest that people with severe MS requiring an EPIOC benefit from a holistic assessment to identify problematic clinical features that influence the prescription of the EPIOC and further medical and therapeutic interventions.

IMPLICATIONS FOR REHABILITATION

People with multiple sclerosis (MS), referred for an EPIOC, require a full clinical assessment to identify problematic clinical features that are potentially treatable and/or can be accommodated through specialised seating and tilt. The beneficial effects of TIS should be considered for all EPIOC users with MS and particularly for those with comorbidity Poorly controlled spasticity, when identified in people with MS, should be managed through positioning in the chair, pressure-relieving cushion and referral for medical management.