Health and political economy: building a new common sense in the United States

The prevailing economic paradigm, characterized by free market thinking and individualistic cultural narratives, has deeply influenced contemporary society in recent decades, including health in the United States. This paradigm, far from being natural, is iteratively intertwined with politics, social group stratification, and norms, together shaping what is known as political economy. The consequences are starkly evident in health, with millions of lives prematurely lost annually in the United States. Drawing on economic re-thinking happening in fields like climate and law, we argue for a new "common sense" towards a health-focused political economy. Central to this proposed shift is action in 3 interconnected areas: capital, care, and culture. Re-orienting capital to prioritize longer-term investments, such as in public options for health care and baby bonds, can promote health and affirmatively include historically marginalized groups. Recognizing that caregiving is economically valuable and necessary for health, approaches like local cadres of community health workers across the United States would be part of building robust caregiving infrastructures. Advancing momentum in these directions, in turn, will require displacing dominant cultural narratives. As the health arena pursues change in the face of real obstacles, recent efforts reinvigorating industrial policy and addressing concentrated market power can serve as inspiration.

Patterns of adverse childhood experiences and cardiovascular risk factors in U.S. adults

Adverse Childhood Experiences (ACEs) are associated with poor health yet, we know little about how distinct patterns of ACE types are associated with cardiovascular (cardiovascular (CVD)) risk factors. The current study 1) examined associations of latent ACE classes with modifiable CVD risk factors including high cholesterol, smoking, diabetes, hypertension, high triglycerides, physical inactivity, overweight/obesity, and lifetime depression; and 2) examined the impact of socioeconomic status-related (SES) factors on these relationships. Using a cross-sectional analysis of the National Epidemiologic Survey of Alcohol and Related Conditions-III (n = 36,309) data, four latent classes of ACEs were previously identified: 1) low adversity, 2) primarily household dysfunction, 3) primarily maltreatment, and 4) multiple adversity types. We examined the association of these classes with CVD risk factors in adulthood and subsequently, the same model accounting for SES-related factors. Tobacco smoking, overweight/obesity, and lifetime depression were each associated with higher odds of being in classes 2, 3, and 4 than class 1, respectively. These relationships held after adjusting for SES-related factors. Class 4 was associated with the most CVD risk factors, including high triglycerides and high cholesterol after controlling for SES-related factors. The consistent associations between tobacco smoking, overweight/obesity, and lifetime depression with each adverse ACE profile, even after controlling for SES, suggest behavioural CVD prevention programs should target these CVD risk factors simultaneously.

Fitting a Hearing Aid on the Better Ear, Worse Ear, or Both: Associations of Hearing-aid Fitting Laterality with Outcomes in a Large Sample of US Veterans

Longitudinal electronic health records from a large sample of new hearing-aid (HA) recipients in the US Veterans Affairs healthcare system were used to evaluate associations of fitting laterality with long-term HA use persistence as measured by battery order records, as well as with short-term HA use and satisfaction as assessed using the International Outcome Inventory for Hearing Aids (IOI-HA), completed within 180 days of HA fitting. The large size of our dataset allowed us to address two aspects of fitting laterality that have not received much attention, namely the degree of hearing asymmetry and the question of which ear to fit if fitting unilaterally. The key findings were that long-term HA use persistence was considerably lower for unilateral fittings for symmetric hearing loss (HL) and for unilateral worse-ear fittings for asymmetric HL, as compared to bilateral and unilateral better-ear fittings. In contrast, no differences across laterality categories were observed for short-term self-reported HA usage. Total IOI-HA score was poorer for unilateral fittings of symmetric HL and for unilateral better-ear fittings compared to bilateral for asymmetric HL. We thus conclude that bilateral fittings yield the best short- and long-term outcomes, and while unilateral and bilateral fittings can result in similar outcomes on some measures, we did not identify any HL configuration for which a bilateral fitting would lead to poorer outcomes. However, if a single HA is to be fitted, then our results indicate that a better-ear fitting has a higher probability of long-term HA use persistence than a worse-ear fitting.

Validation of an algorithm to identify heart failure hospitalisations in patients with diabetes within the veterans health administration

OBJECTIVES

We aimed to validate an algorithm using both primary discharge diagnosis (International Classification of Diseases Ninth Revision (ICD-9)) and diagnosis-related group (DRG) codes to identify hospitalisations due to decompensated heart failure (HF) in a population of patients with diabetes within the Veterans Health Administration (VHA) system.

DESIGN

Validation study.

SETTING

Veterans Health Administration-Tennessee Valley Healthcare System PARTICIPANTS: We identified and reviewed a stratified, random sample of hospitalisations between 2001 and 2012 within a single VHA healthcare system of adults who received regular VHA care and were initiated on an antidiabetic medication between 2001 and 2008. We sampled 500 hospitalisations; 400 hospitalisations that fulfilled algorithm criteria, 100 that did not. Of these, 497 had adequate information for inclusion. The mean patient age was 66.1 years (SD 11.4). Majority of patients were male (98.8%); 75% were white and 20% were black.

PRIMARY AND SECONDARY OUTCOME MEASURES

To determine if a hospitalisation was due to HF, we performed chart abstraction using Framingham criteria as the referent standard. We calculated the positive predictive value (PPV), negative predictive value (NPV), sensitivity and specificity for the overall algorithm and each component (primary diagnosis code (ICD-9), DRG code or both).

RESULTS

The algorithm had a PPV of 89.7% (95% CI 86.8 to 92.7), NPV of 93.9% (89.1 to 98.6), sensitivity of 45.1% (25.1 to 65.1) and specificity of 99.4% (99.2 to 99.6). The PPV was highest for hospitalisations that fulfilled both the ICD-9 and DRG algorithm criteria (92.1% (89.1 to 95.1)) and lowest for hospitalisations that fulfilled only DRG algorithm criteria (62.5% (28.4 to 96.6)).

CONCLUSIONS

Our algorithm, which included primary discharge diagnosis and DRG codes, demonstrated excellent PPV for identification of hospitalisations due to decompensated HF among patients with diabetes in the VHA system.