Milbank Quarterly最新文献

Policy Points People with disabilities experience a vicious cycle of poverty, poor health, and marginalization partly because of the inequitable implementation and enforcement of laws, including underenforcement of civil rights and housing laws and overenforcement of punitive nuisance and criminal laws. Inequitable enforcement reflects policy choices that prioritize powerful entities (e.g., landlords, developers) to the detriment of people who experience intersectional structural discrimination based on, for example, race, disability, and income. Equitable enforcement, a process of ensuring compliance with the law while considering and minimizing harms to marginalized people, can promote health and disability justice by increasing access to safe, stable, and accessible housing.

Policy Points Promoting healthy public policies is a national priority, but state policy adoption is driven by a complex set of internal and external factors. This study employs new social network methods to identify underlying connections among states and to predict the likelihood of new firearm-related policy adoption given changes to this interstate network. This approach could be used to assess the likelihood that a given state will adopt a specific new firearm-related law and to identify points of influence that could either inhibit or promote wider diffusion of specific laws.

Context: US states are largely responsible for the regulation of firearms within their borders. Each state has developed a different legal environment with regard to firearms based on different values and beliefs of citizens, legislators, governors, and other stakeholders. Predicting the types of firearm laws that states may adopt is therefore challenging.

Methods: We propose a parsimonious model for this complex process and provide credible predictions of state firearm laws by estimating the likelihood they will be passed in the future. We employ a temporal exponential-family random graph model to capture the bipartite state law-state network data over time, allowing for complex interdependencies and their temporal evolution. Using data on all state firearm laws over the period 1979-2020, we estimate these models' parameters while controlling for factors associated with firearm law adoption, including internal and external state characteristics. Predictions of future firearm law passage are then calculated based on a number of scenarios to assess the effects of a given type of firearm law being passed in the future by a given state.

Findings: Results show that a set of internal state factors are important predictors of firearm law adoption, but the actions of neighboring states may be just as important. Analysis of scenarios provide insights into the mechanics of how adoption of laws by specific states (or groups of states) may perturb the rest of the network structure and alter the likelihood that new laws would become more (or less) likely to continue to diffuse to other states.

Conclusions: The methods used here outperform standard approaches for policy diffusion studies and afford predictions that are superior to those of an ensemble of machine learning tools. The proposed framework could have applications for the study of policy diffusion in other domains.

Policy Points Government and civil society should be held more accountable for creating food and beverage regulatory policies rather than assigning moral agency to the food and beverage industry. Nutrition policymaking institutions should ensure civil society's ability to design regulatory policy. Government policymaking institutions should be isolated from industry interference.

Policy Points Patients' creative ideas may inform learning and innovation that improve patient-centered care. Routinely collected patient experience surveys provide an opportunity to invite patients to share their creative ideas for improvement. We develop and assess a methodological strategy that validates question wording designed to elicit creative ideas from patients. Health care organizations should consider how to report and use these data in health care delivery and quality improvement, and policymakers should consider promoting the use of narrative feedback to better understand and respond to patients' experiences.

Context: Learning health systems (LHSs) have been promoted for a decade to achieve high-quality, patient-centered health care. Innovation driven by knowledge generated through day-to-day health care delivery, including patient insights, is critical to LHSs. However, the pace of translating patient insights into innovation is slow and effectiveness inadequate. This study aims to evaluate a method for systematically eliciting patients' creative ideas, examine the value of such ideas as a source of insight, and examine patients' creative ideas regarding how their experiences could be improved within the context of their own health systems.

Methods: The first stage of the study developed a survey and tested strategies for elicitation of patients' creative ideas with 600 patients from New York State. The second stage deployed the survey with the most generative open-ended question sequence within a health care system and involved analysis of 1,892 patients' responses, including 2,948 creative ideas.

Findings: Actionable, creative feedback was fostered by incorporating a request for transformative feedback into a sequence of narrative elicitation questions. Patients generate more actionable and creative ideas when explicitly invited to share such ideas, especially patients with negative health care experiences, those from minority racial/ethnic backgrounds, and those with chronic illness. The most frequently elicited creative ideas focused on solving challenges, proposing interventions, amplifying exceptional practices, and conveying hopes for the future.

Conclusions: A valid and reliable method for eliciting creative ideas from patients can be deployed as part of routine patient experience surveys that include closed-ended survey items and open-ended narrative items in which patients share their experiences in their own words. The elicited creative ideas are promising for patient engagement and innovation efforts. This study highlights the benefits of engaging patients for quality improvement, offers a rigorously tested method for cultivating innovation using patient-generated knowledge, and outlines how creative ideas can enable organizational learning and innovation.

Policy Points Pregnancy and childhood are periods of heightened economic vulnerability, but current policies for addressing health-related social needs, including screening and referral programs, may be insufficient because of persistent gaps, incomplete follow-up, administrative burden, and limited take-up. To bridge gaps in the social safety net, direct provision of cash transfers to low-income families experiencing health challenges during pregnancy, infancy, and early childhood could provide families with the flexibility and support to enable caregiving, increase access to health care, and improve health outcomes.

Policy Points The implementation of large-scale health care interventions relies on a shared vision, commitment to change, coordination across sites, and a spanning of siloed knowledge. Enablers of the system should include building an authorizing environment; providing relevant, meaningful, transparent, and timely data; designating and distributing leadership and decision making; and fostering the emergence of a learning culture. Attention to these four enablers can set up a positive feedback loop to foster positive change that can protect against the loss of key staff, the presence of lone disruptors, and the enervating effects of uncertainty.

Context: Large-scale transformative initiatives have the potential to improve the quality, efficiency, and safety of health care. However, change is expensive, complex, and difficult to implement and sustain. This paper advances system enablers, which will help to guide large-scale transformation in health care systems.

Methods: A realist study of the implementation of a value-based health care program between 2017 and 2021 was undertaken in every public hospital (n = 221) in New South Wales (NSW), Australia. Four data sources were used to elucidate initial program theories beginning with a set of literature reviews, a program document review, and informal discussions with key stakeholders. Semistructured interviews were then conducted with 56 stakeholders to confirm, refute, or refine the theories. A retroductive analysis produced a series of context-mechanism-outcome (CMO) statements. Next, the CMOs were validated with three health care quality expert panels (n = 51). Synthesized data were interrogated to distill the overarching system enablers.

Findings: Forty-two CMO statements from the eight initial program theory areas were developed, refined, and validated. Four system enablers were identified: (1) build an authorizing environment; (2) provide relevant, authentic, timely, and meaningful data; (3) designate and distribute leadership and decision making; and (4) support the emergence of a learning culture. The system enablers provide a nuanced understanding of large-system transformation that illustrates when, for whom, and in what circumstances large-system transformation worked well or worked poorly.

Conclusions: System enablers offer nuanced guidance for the implementation of large-scale health care interventions. The four enablers may be portable to similar contexts and provide the empirical basis for an implementation model of large-system value-based health care initiatives. With concerted application, these findings can pave the way not just for a better understanding of greater or lesser success in intervening in health care settings but ultimately to contribute higher quality, higher value, and safer care.

Policy Points Our research reveals the similarities and differences among the lobbying activities of tobacco, alcohol, gambling, and ultraprocessed food industries, which are often a barrier to the implementation of public health policies. Over 23 years, we found that just six organizations dominated lobbying expenses in the tobacco and alcohol sectors, whereas the gambling sector outsourced most of their lobbying to professional firms. Databases like OpenSecrets are a useful resource to monitor the commercial determinants of health.

Context: Commercial lobbying is often a barrier to the development and implementation of public health policies. Yet, little is known about the similarities and differences in the lobbying practices of different industry sectors or types of commercial actors. This study compares the lobbying practices of four industry sectors that have been the focus of much public health research and advocacy: tobacco, alcohol, gambling, and ultraprocessed foods.

Methods: Data on lobbying expenditures and lobbyist backgrounds were sourced from the OpenSecrets database, which monitors lobbying in the United States. Lobbying expenditure data were analyzed for the 1998-2020 period. We classified commercial actors as companies or trade associations. We used Power BI software to link, analyze, and visualize data sets.

Findings: We found that the ultraprocessed food industry spent the most on lobbying ($1.15 billion), followed by gambling ($817 million), tobacco ($755 million), and alcohol ($541 million). Overall, companies were more active than trade associations, with associations being least active in the tobacco industry. Spending was often highly concentrated, with two organizations accounting for almost 60% of tobacco spending and four organizations accounting for more than half of alcohol spending. Lobbyists that had formerly worked in government were mainly employed by third-party lobby firms.

Conclusions: Our study shows how comparing the lobbying practices of different industry sectors offers a deeper appreciation of the diversity and similarities of commercial actors. Understanding these patterns can help public health actors to develop effective counterstrategies.

Policy Points The health care sector is increasingly investing in social conditions, including availability of safe, reliable, and adequate transportation, that contribute to improving health. In this paper, we suggest ways to advance the impact of transportation interventions and highlight the limitations of how health services researchers and practitioners currently conceptualize and use transportation. Incorporating a transportation justice framework offers an opportunity to address transportation and mobility needs more comprehensively and equitably within health care research, delivery, and policy.

Policy Points The Paycheck Plus randomized controlled trial tested a fourfold increase in the Earned Income Tax Credit (EITC) for single adults without dependent children over 3 years in New York and Atlanta. In New York, the intervention improved economic, mental, and physical health outcomes. In Atlanta, it had no economic benefit or impact on physical health and may have worsened mental health. In Atlanta, tax filing and bonus receipt were lower than in the New York arm of the trial, which may explain the lack of economic benefits. Lower mental health scores in the treatment group were driven by disadvantaged men, and the study sample was in good mental health.

Context: The Paycheck Plus experiment examined the effects of an enhanced Earned Income Tax Credit (EITC) for single adults on economic and health outcomes in Atlanta, GA and New York City (NYC). The NYC study was completed two years prior to the Atlanta study and found mental and physical benefits for the subgroups that responded best to the economic incentives provided. In this article, we present the findings from the Atlanta study, in which the uptake of the treatment (tax filings and EITC bonus) were lower and economic and health benefits were not observed.

Methods: Paycheck Plus Atlanta was an unblinded randomized controlled trial that assigned n = 3,971 participants to either the standard federal EITC (control group) or an EITC supplement of up to $2,000 (treatment group) for three tax years (2017-2019). Administrative data on employment and earnings were obtained from the Georgia Department of Labor and survey data were used to examine validated measures of health and well-being.

Findings: In Atlanta, the treatment group had significantly higher earnings in the first project year but did not have significantly higher cumulative earnings than the control group overall (mean difference = $1,812, 95% CI = -150, 3,774, p = 0.07). The treatment group also had significantly lower scores on two measures of mental health after the intervention was complete: the Patient Health Questionnaire 8 (mean difference = 0.19, 95% CI = 0.06, 0.32, p = 0.005) and the Kessler 6 (mean difference = 0.15, 95% CI = 0.03, 0.27, p = 0.012). Secondary analyses suggested these results were driven by disadvantaged men, but the study sample was in good mental health.

Conclusions: The EITC experiment in Atlanta was not associated with gains in earnings or improvements in physical or mental health.