Factors Informing High-Risk Primary Care Patient Choice around Telehealth Use: a Framework

BACKGROUND

While telehealth's presence in post-pandemic primary care appears assured, its exact role remains unknown. Value-based care's expansion has heightened interest in telehealth's potential to improve uptake of preventive and chronic disease care, especially among high-risk primary care populations. Despite this, the pandemic underscored patients' diverse preferences around using telehealth. Understanding the factors underlying this population's preferences can inform future telehealth strategies.

OBJECTIVE

To describe the factors informing high-risk primary care patient choice of whether to pursue primary care via telehealth, in-office or to defer care altogether.

DESIGN

Qualitative, cross-sectional study utilizing semi-structured telephone interviews of a convenience sample of 29 primary care patients between July 13 and September 30, 2020.

PARTICIPANTS

Primary care patients at high risk of poor health outcomes and/or acute care utilization who were offered a follow-up primary care visit via audiovisual, audio-only or in-office modalities.

APPROACH

Responses were analyzed via grounded theory, using a constant comparison method to refine emerging categories, distinguish codes, and synthesize evolving themes.

KEY RESULTS

Of the 29 participants, 16 (55.2%) were female and 19 (65.5%) were Black; the mean age (SD) was 64.6 (11.1). Participants identified four themes influencing their choice of visit type: perceived utility (encapsulating clinical and non-clinical utility), underlying costs (in terms of time, money, effort, and safety), modifiers (e.g., participants' clinical situation, choice availability, decision phenotype), and drivers (inclusive of their background experiences and digital environment). The relationship of these themes is depicted in a novel framework of patient choice around telehealth use.

CONCLUSIONS

While visit utility and cost considerations are foundational to participants' decisions around whether to pursue care via telehealth, underappreciated modifiers and drivers often magnify or mitigate these considerations. Policymakers, payers, and health systems can leverage these factors to anticipate and enhance equitable high-value telehealth use in primary care settings among high-risk individuals.

Training Health Policy Researchers on Policy Engagement and Research Translation for Greater Impact: Evaluation of the Amplify@LDI Program

BACKGROUND

Few researchers receive formal training in research translation and dissemination or policy engagement. We created Amplify@LDI, a training program for health services and health policy researchers, to equip them with skills to increase the visibility of their research through translation and dissemination activities.

AIMS

To describe the program's participants and curriculum, and evaluate the first 2 years of the program.

SETTING

The Leonard Davis Institute (LDI) at the University of Pennsylvania (Penn).

PARTICIPANTS

An annual cohort of 12 LDI Senior Fellows (Penn faculty) from multiple schools, disciplines, and ranks at Penn.

PROGRAM DESCRIPTION

The Amplify@LDI curriculum includes 6 sessions on different aspects of research translation and dissemination, including media and social engagement, writing Op-Eds, and policy engagement.

PROGRAM EVALUATION

Participants reported measurable increases in time spent on translation and dissemination activities, as well as new enthusiasm for and confidence in policy engagement. Participants' reach (as measured by Altmetric) increased during the program, compared to smaller increases or reductions in reach for two comparator groups.

DISCUSSION

In our preliminary evaluation of Amplify@LDI, we find strong evidence of positive impact from participant evaluations, and suggestive evidence that participation in the program is associated with significant increases in the reach of their research.

Consumer Views on Privacy Protections and Sharing of Personal Digital Health Information

IMPORTANCE

Digital health information has many potential health applications, but privacy is a growing concern among consumers and policy makers. Consent alone is increasingly seen as inadequate to safeguard privacy.

OBJECTIVE

To determine whether different privacy protections are associated with consumers' willingness to share their digital health information for research, marketing, or clinical uses.

DESIGN, SETTING, AND PARTICIPANTS

This 2020 national survey with an embedded conjoint experiment recruited US adults from a nationally representative sample with oversampling of Black and Hispanic individuals. Willingness to share digital information across 192 different scenarios reflecting the product of 4 possible privacy protections, 3 uses of information, 2 users of information, and 2 sources of digital information was evaluated. Each participant was randomly assigned 9 scenarios. The survey was administrated between July 10 and July 31, 2020, in Spanish and English. Analysis for this study was conducted between May 2021 and July 2022.

MAIN OUTCOMES AND MEASURES

Participants rated each conjoint profile on a 5-point Likert scale measuring their willingness to share their personal digital information (with 5 indicating the most willingness to share). Results are reported as adjusted mean differences.

RESULTS

Of the 6284 potential participants, 3539 (56%) responded to the conjoint scenarios. A total of 1858 participants (53%) were female, 758 (21%) identified as Black, 833 (24%) identified as Hispanic, 1149 (33%) had an annual income less than $50 000, and 1274 (36%) were 60 years or older. Participants were more willing to share health information with the presence of each individual privacy protection, including consent (difference, 0.32; 95% CI, 0.29-0.35; P < .001), followed by data deletion (difference, 0.16; 95% CI, 0.13-0.18; P < .001), oversight (difference, 0.13; 95% CI, 0.10-0.15; P < .001), and transparency of data collected (difference, 0.08; 95% CI, 0.05-0.10; P < .001). The relative importance (importance weight on a 0%-100% scale) was greatest for the purpose of use (29.9%) but when considered collectively, the 4 privacy protections together were the most important (51.5%) factor in the conjoint experiment. When the 4 privacy protections were considered separately, consent was the most important (23.9%).

CONCLUSIONS AND RELEVANCE

In this survey study of a nationally representative sample of US adults, consumers' willingness to share personal digital health information for health purposes was associated with the presence of specific privacy protections beyond consent alone. Additional protections, including data transparency, oversight, and data deletion may strengthen consumer confidence in sharing their personal digital health information.

C57 DUAL ANTIPLATELET THERAPY DID NOT PREDICT ALL–CAUSE BLEEDING AT LONG–TERM FOLLOW–UP AFTER ACS: A SUBANALYSIS FROM THE APULIA PONTE ACS STUDY

Background

Dual antiplatelet therapy (DAPT) has important implications for clinical outcomes in coronary disease. Nevertheless, the risk for bleeding often impact on the long–term administration of DAPT. The aim of this study was to evaluate the determinants of bleeding risk after ACS.

Methods

This was a subanalysis of the PONTE ACS study. The PONTE ACS study is a prospective, longitudinal, cohort study which enrolled patients who were discharged from HUB centres of ASL BARI after coronary revascularization and/or ACS. They underwent clinical evaluation at 30 days, 3, 6 and 1 year–follow–up. The data were collected after including the data in the electronic medical record of the PONTE ACS study. Anthropometric, clinical and pharmacological parameters, instrumental and laboratory examinations were included. Data were computed in order to evaluate the major determinants of all–cause bleeding at one–year follow–up.

Results

We finally enrolled 2476 patients (77.4% male, mean age: 67.2±12.0 years). Pharmacological treatments were optimized during the follow–up visits. According to anti–thrombotic therapies, 92.1% of patients persisted on DAPT at one–year follow–up. The number of patients on DAPT+anticoagulant were: 4.4%. All–cause bleeding occurred in 2.2% of patients. Anthropometric characteristics (height [β: –0.04594 ± 0.01610, p = 0.0044] and weight [β: –0.03043 ± 0.01035, p = 0.033]), male gender [β: –0.7008 ± 0.2818, p = 0.0129], and age [β: 0.02535 ± 0.01219, p = 0.0376] were the major determinants of all–cause bleeding at univariate regression analysis but they were not confirmed at multivariate regression analysis (p=ns). Kaplan Meier curve points out the impact of age on all–cause bleeding (Figure 1). Nor DAPT or triple therapy remained associated with all–cause bleeding at one year follow–up.

Conclusions

Long–term DAPT is not a predictor of all–cause bleeding in patients who suffered ACS and/or coronary revascularization.

Consumer Willingness to Share Personal Digital Information for Health-Related Uses

IMPORTANCE

Consumers routinely generate digital information that reflects on their health.

OBJECTIVE

To evaluate the factors associated with consumers' willingness to share their digital health information for research, health care, and commercial uses.

DESIGN, SETTING, AND PARTICIPANTS

This national survey with an embedded conjoint experiment recruited US adults from a nationally representative sample, with oversampling of Black and Hispanic panel members. Participants were randomized to 15 scenarios reflecting use cases for consumer digital information from a total of 324 scenarios. Attributes of the conjoint analysis included 3 uses, 3 users, 9 sources of digital information, and 4 relevant health conditions. The survey was conducted from July 10 to 31, 2020.

MAIN OUTCOMES AND MEASURES

Participants rated each conjoint profile on a 5-point Likert scale (1-5) measuring their willingness to share their personal digital information (with 5 indicating the most willingness to share). Results reflect mean differences in this scale from a multivariable regression model.

RESULTS

Among 6284 potential participants, 3543 (56%) responded. A total of 1862 participants (53%) were female, 759 (21%) identified as Black, 834 (24%) identified as Hispanic, and 1274 (36%) were 60 years or older. In comparison with information from electronic health care records, participants were less willing to share information about their finances (coefficient, -0.56; 95% CI, -0.62 to -0.50), places they visit from public cameras (coefficient, -0.28; 95% CI, -0.33 to -0.22), communication on social media (coefficient, -0.20; 95% CI -0.26 to -0.15), and their search history from internet search engines (coefficient, -0.11; 95% CI, -0.17 to -0.06). They were more willing to share information about their steps from applications on their phone (coefficient, 0.22; 95% CI, 0.17-0.28). Among the conjoint attributes, the source of information (importance weight: 59.1%) was more important than the user (17.3%), use (12.3%), and health condition (11.3%). Four clusters of consumers emerged from the sample with divergent privacy views. While the context of use was important, these 4 groups expressed differences in their overall willingness to share, with 337 participants classified as never share; 1116 classified as averse to sharing (mean rating, 1.64; 95% CI, 1.62-1.65); 1616 classified as uncertain about sharing (mean rating, 2.84; 95% CI, 2.81-2.86); and 474 classified as agreeable to sharing (mean rating, 4.18; 95% CI, 4.16-4.21). Respondents who identified as White and non-Hispanic, had higher income, and were politically conservative were more likely to be in a cluster that was less willing to share (ie, never or averse clusters).

CONCLUSIONS AND RELEVANCE

These findings suggest that although consumers' willingness to share personal digital information for health purposes is associated with the context of use, many have strong underlying privacy views that affect their willingness to share. New protections may be needed to give consumers confidence to be comfortable sharing their personal information.

Benchmarking between two different hospitals on health risk management in the covid-19 emergency

Iusse

The strategies adopted during COVID19 emergencies by two different hospitals in the Lazio Region are presented: S. Maria Goretti Hospital (SMGH) directly managed by the ASL Latina, hub and centre of the Emergency Department, and Cristo Re Classified Hospital (CRH), accredited in the territory of the ASL Roma1.

Description of the problem

SMGH has been identified as COVID19 Intervention Hospital. CRH initially was a No-COVID support structure, then included in the COVID19 network. During the COVID19 emergency, the directors of both hospitals had to simultaneously ensure activity as usual, COVID19 recovery and risk management.

Results

SMGH, while continuing the emergency, oncological, pregnancy, paediatrics and outpatient activities, COVID19 patients was isolated on 7 different floors/areas. Moreover was defined: chain of command; clinical admission criteria; COVID19 multi-professional and support teams, roles, skills and specific training; health surveillance; environmental hygiene, safety paths/procedures, vaccinal center and much more. CRH, while continuing minimum programmed activities to reduce waiting lists, in the first epidemic phase was created 4 tensile structures for Pre-triage and COVID pathways, respiratory isolation area for supsected patient; transfer admission for emergency networks, clean-dirty pathway. Moreover in the second phase, was activated beds of COVID19 network and 4 technical beds OBI; the ‘Walk-in' for antigenic testing, with molecular confirmation <24h and infectious counselling; multi-disciplinary and specialist support teams, training courses, health surveillance, vaccinal center and much more.

Lessons

During COVID19 pandemic, risk management skills linked to the technical-organisational strategy of hospital directors, making it possible to reprogramme their structure in a short period of time with flexibility and resilience of the whole organization.

Key messages

Specific skills and roles, both hygienic and organizational, are essential to risk management in hospitals during epidemic emergencies.

The multidisciplinarity, flexibility and modularity of the hospital structure are the organizational bases in cases of pandemics.

Variability in Primary Care Physician Attitudes Toward Medicaid Work Requirement Exemption Requests Made by Patients With Depression

Question

To what degree do physicians vary in their willingness to assist patients seeking exemptions from Medicaid work requirements?

Findings

In this mailed survey experiment with 715 responses, we found that 25% of physicians would assist a patient not qualifying under the state’s criteria for exemptions from Medicaid work requirements, and 54% would not, even when a patient qualifies. We found state, administrative effort, political affiliation, and perceived appropriateness to be significantly associated with willingness to assist.

Meaning

It is medically, ethically, and legally imperative that measures aimed at protecting vulnerable patients are not undermined by the burdensomeness of exemption procedures, or by physicians’ political or personal views.

Importance

Medicaid work requirements seek to promote health and personal responsibility but can also jeopardize health care access. Physicians have a central function in assisting patients with exemption requests, but it is unclear how their role affects patient welfare, professionalism, and the ethical and legal justification of programs.

Objective

To understand the degree of variability in physician response to assist patients with depression in receiving a Medicaid work requirement exemption.

Design, Setting, and Participants

We conducted a mailed survey experiment among practicing primary care physicians in the first 4 approved states (Arkansas, Kentucky, Indiana, New Hampshire) in July and October of 2019. We report response, cooperation, refusal, and contact rates in line with American Association for Public Opinion Research (AAPOR) standards.

Exposures

In each state, we used an experimental factorial design to randomize recipients to 1 of 4 patient clinical scenarios.

Main Outcomes and Measures

The primary outcome was the indicator of willingness to assist a patient reporting depression with an exemption.

Results

We received 715 responses (overall AAPOR response rate: 21%; cooperation rate: 84%; refusal rate: 4%; contact rate: 25%). Respondents’ mean (SD) age was 54 (12) years; mean (SD) time since graduation, 26 (12) years; 435 (61%) identified as male; 177 as Democrat (25%); 156 as Republican (22%); 197 as Independent/other (28%); and 185 as declined/unknown (26%); the mean (SD) share of Medicaid patients was 29% (21%). We found that 97 of 387 physicians (25%) would offer assistance even when state policy would not support an exemption, and 170 of 315 (54%) would not offer assistance when regulations would require this. Moreover, 49 of 245 respondents (20%) who deemed an exemption appropriate indicated that they would not assist. State, administrative effort, political affiliation, and perceived appropriateness were statistically associated with the odds of assisting with an exemption.

Conclusions and Relevance

In this survey study of primary care physicians, we found substantial variation regarding willingness to assist patients qualifying for a work requirement exemption where none should exist. Insofar as work requirements are implemented again, it is critical to proactively identify measures to ensure that patients qualifying for exemptions are not put at risk due to either the burdensomeness of exemption procedures, or physicians’ political or personal views.

Consumer Views on Health Applications of Consumer Digital Data and Health Privacy Among US Adults: Qualitative Interview Study

BACKGROUND

In 2020, the number of internet users surpassed 4.6 billion. Individuals who create and share digital data can leave a trail of information about their habits and preferences that collectively generate a digital footprint. Studies have shown that digital footprints can reveal important information regarding an individual's health status, ranging from diet and exercise to depression. Uses of digital applications have accelerated during the COVID-19 pandemic where public health organizations have utilized technology to reduce the burden of transmission, ultimately leading to policy discussions about digital health privacy. Though US consumers report feeling concerned about the way their personal data is used, they continue to use digital technologies.

OBJECTIVE

This study aimed to understand the extent to which consumers recognize possible health applications of their digital data and identify their most salient concerns around digital health privacy.

METHODS

We conducted semistructured interviews with a diverse national sample of US adults from November 2018 to January 2019. Participants were recruited from the Ipsos KnowledgePanel, a nationally representative panel. Participants were asked to reflect on their own use of digital technology, rate various sources of digital information, and consider several hypothetical scenarios with varying sources and health-related applications of personal digital information.

RESULTS

The final cohort included a diverse national sample of 45 US consumers. Participants were generally unaware what consumer digital data might reveal about their health. They also revealed limited knowledge of current data collection and aggregation practices. When responding to specific scenarios with health-related applications of data, they had difficulty weighing the benefits and harms but expressed a desire for privacy protection. They saw benefits in using digital data to improve health, but wanted limits to health programs' use of consumer digital data.

CONCLUSIONS

Current privacy restrictions on health-related data are premised on the notion that these data are derived only from medical encounters. Given that an increasing amount of health-related data is derived from digital footprints in consumer settings, our findings suggest the need for greater transparency of data collection and uses, and broader health privacy protections.

Evidence-Based Community Health Worker Program Addresses Unmet Social Needs And Generates Positive Return On Investment

Interventions that address socioeconomic determinants of health are receiving considerable attention from policy makers and health care executives. The interest is fueled in part by expected returns on investment. However, many current estimates of returns on investment are likely overestimated, because they are based on pre-post study designs that are susceptible to regression to the mean. We present a return-on-investment analysis that is based on a randomized controlled trial of Individualized Management for Patient-Centered Targets (IMPaCT), a standardized community health worker intervention that addresses unmet social needs for disadvantaged people. We found that every dollar invested in the intervention would return $2.47 to an average Medicaid payer within the fiscal year.

Developing an Automatic System for Classifying Chatter About Health Services on Twitter: Case Study for Medicaid

Background

The wide adoption of social media in daily life renders it a rich and effective resource for conducting near real-time assessments of consumers’ perceptions of health services. However, its use in these assessments can be challenging because of the vast amount of data and the diversity of content in social media chatter.

Objective

This study aims to develop and evaluate an automatic system involving natural language processing and machine learning to automatically characterize user-posted Twitter data about health services using Medicaid, the single largest source of health coverage in the United States, as an example.

Methods

We collected data from Twitter in two ways: via the public streaming application programming interface using Medicaid-related keywords (Corpus 1) and by using the website’s search option for tweets mentioning agency-specific handles (Corpus 2). We manually labeled a sample of tweets in 5 predetermined categories or other and artificially increased the number of training posts from specific low-frequency categories. Using the manually labeled data, we trained and evaluated several supervised learning algorithms, including support vector machine, random forest (RF), naïve Bayes, shallow neural network (NN), k-nearest neighbor, bidirectional long short-term memory, and bidirectional encoder representations from transformers (BERT). We then applied the best-performing classifier to the collected tweets for postclassification analyses to assess the utility of our methods.

Results

We manually annotated 11,379 tweets (Corpus 1: 9179; Corpus 2: 2200) and used 7930 (69.7%) for training, 1449 (12.7%) for validation, and 2000 (17.6%) for testing. A classifier based on BERT obtained the highest accuracies (81.7%, Corpus 1; 80.7%, Corpus 2) and F₁ scores on consumer feedback (0.58, Corpus 1; 0.90, Corpus 2), outperforming the second best classifiers in terms of accuracy (74.6%, RF on Corpus 1; 69.4%, RF on Corpus 2) and F₁ score on consumer feedback (0.44, NN on Corpus 1; 0.82, RF on Corpus 2). Postclassification analyses revealed differing intercorpora distributions of tweet categories, with political (400778/628411, 63.78%) and consumer feedback (15073/27337, 55.14%) tweets being the most frequent for Corpus 1 and Corpus 2, respectively.

Conclusions

The broad and variable content of Medicaid-related tweets necessitates automatic categorization to identify topic-relevant posts. Our proposed system presents a feasible solution for automatic categorization and can be deployed and generalized for health service programs other than Medicaid. Annotated data and methods are available for future studies.

Consumer Views on Using Digital Data for COVID-19 Control in the United States

IMPORTANCE

Curbing COVID-19 transmission is currently the greatest global public health challenge. Consumer digital tools used to collect data, such as the Apple-Google digital contact tracing program, offer opportunities to reduce COVID-19 transmission but introduce privacy concerns.

OBJECTIVE

To assess uses of consumer digital information for COVID-19 control that US adults find acceptable and the factors associated with higher or lower approval of use of this information.

DESIGN, SETTING, AND PARTICIPANTS

This cross-sectional survey study obtained data from a nationally representative sample of 6284 US adults recruited by email from the web-based Ipsos KnowledgePanel in July 2020. Respondents evaluated scenarios reflecting uses of digital data for COVID-19 control (case identification, digital contact tracing, policy setting, and enforcement of quarantines).

MAIN OUTCOMES AND MEASURES

Levels of support for use of personal digital data in 9 scenarios to mitigate the spread of COVID-19 infection, rated on a Likert scale, ranging from 1 (strongly disagree) to 5 (strongly agree). Multivariable linear regression models were fitted for each scenario and included factors hypothesized to be associated with views about digital data use for COVID-19 mitigation measures. Black and Hispanic survey respondents were oversampled; thus, poststratification weights were used so that results are representative of the general US population.

RESULTS

Of 6284 individuals invited to participate in the study, 3547 responded, for a completion rate of 56%. A total of 1762 participants (52%) were female, 715 (21%) identified as Black, 790 (23%) identified as Hispanic, and 1224 (36%) were 60 years or older; mean (SD) age was 51.7 (16.6) years. Approval of scenarios was low, ranging from 28% to 43% (52%-67% when neutral responses were included). Differences were found based on digital data source (smartphone vs social media: coefficient, 0.29 [95% CI, 0.23-0.35]; P < .001; smart thermometer vs social media: coefficient, 0.09 [95% CI, 0.03-0.16]; P = .004). County COVID-19 rates (coefficient, -0.02; 95% CI, -0.16 to 0.13 for quartile 4 compared with quartile 1) and prior family diagnosis of COVID-19 (coefficient, 0.00; 95% CI, -0.25 to 0.25) were not associated with support. Compared with self-described liberal individuals, conservative (coefficient, -0.81; 95% CI, -0.96 to -0.66; P < .001) and moderate (coefficient, -0.52; 95% CI, -0.67 to -0.38; P < .001) individuals were less likely to support the scenarios. Similarly, large political differences were observed in support of the Apple-Google digital contact tracing program, with less support from conservative (coefficient, -0.99; 95% CI, -1.11 to -0.87; P < .001) and moderate (coefficient, -0.59; 95% CI, -0.69 to -0.48; P < .001) individuals compared with liberal individuals. Respondents from racial/ethnic minority groups were more supportive of the scenarios than were White, non-Hispanic respondents. For example, compared with White respondents, Black respondents were more supportive of the Apple-Google contact tracing program (coefficient, 0.20; 95% CI, 0.07-0.32; P = .002).

CONCLUSIONS AND RELEVANCE

In this survey study of US adults, many were averse to their information being used on digital platforms to mitigate transmission of COVID-19. These findings suggest that in current and future pandemics, public health departments should use multiple strategies to gain public trust and accelerate adoption of tools such as digital contact tracing applications.

Ventricular arrhythmias in patients with functional mitral regurgitation and implantable cardiac devices: implications of mitral valve repair with Mitraclip

Background

Limited information has been reported regarding the impact of percutaneous mitral valve repair (PMVR) on ventricular arrhythmic (VA) burden. The aim of this study was to address the incidence of VA and appropriate antitachycardia implantable cardiac defibrillator (ICD) therapies before and after PMVR.

Methods

We retrospectively analyzed all consecutive patients with heart failure with reduce left ventricular ejection fraction, functional mitral regurgitation grade 3+ or 4+ and an active ICD or cardiac resynchronizer who underwent PMVR in any of the eleven recruiting centers. Only patients with complete available device VA monitoring from one-year before to one year after PMVR were included. Baseline clinical and echocardiographic characteristics were collected before PMVR and at 12-months follow-up.

Results

93 patients (68.2±10.9 years old, male 88.2%) were enrolled. PMVR was successfully performed in all patients and device success at discharge was 91.4%. At 12-months follow-up, we observed a significant reduction in mitral regurgitation severity, NT-proBNP and prevalence of severe pulmonary hypertension and severe kidney disease. Patients also referred a significant improvement in NYHA functional class and showed a non-significant trend to reserve left ventricular remodeling. After PMVR a significant decrease in the incidence of non-sustained ventricular tachycardia (VT) (5.0–17.8 vs 2.7–13.5, p=0.002), sustained VT or ventricular fibrillation (0.9–2.5 vs 0.5–2.9, p=0.012) and ICD antitachycardia therapies (2.5–12.0 vs 0.9–5.0, p=0.033) were observed.

Conclusion

PMVR was related to a reduction in arrhythmic burden and ICD therapies in our cohort.

Proportion of patients who presented ven

Funding Acknowledgement

Type of funding source: None

Changes in Infective Endocarditis Admissions in Pennsylvania During the Opioid Epidemic

BACKGROUND

With the current opioid crisis in the United States, infectious complications related to injection drug use are increasingly reported. Pennsylvania is at the epicenter of the opioid crisis, with the third highest rate of drug overdose deaths in the United States.

METHODS

A retrospective cohort study was performed using the Pennsylvania Health Care Cost Containment Council database of all residents hospitalized for infective endocarditis (IE) in an acute care hospital from 1 January 2013 through 31 March 2017. Patients were separated into those with and those without substance use via diagnosis codes. The primary outcome was length of stay. Secondarily, we evaluated demographics, infection history, hospital charges, and insurance status.

RESULTS

Of the 17 224 hospitalizations, 1921 (11.1%) were in patients with drug use-associated IE (DU-IE). Total quarterly IE admissions increased 20%, with a 6.5% increase in non-drug use-associated IE (non-DU-IE) admissions and a 238% increase in DU-IE admissions. In adjusted models, DU-IE was not associated with significant changes in length of stay (incidence rate ratio, 1.02; 95% confidence interval, .975-1.072; P = .36). Patients with DU-IE were predominantly insured by Medicaid (68.3% vs 13.4% for non-DU-IE), they had higher hospital charges ($86 622 vs $66 802), and they were more likely to leave against medical advice (15.7% vs 1.1%) (all P < .001).

CONCLUSIONS

Our study demonstrates an increase in IE admissions, driven by an increase in admissions for DU-IE. The higher charges, proportion of patients on Medicaid, and rates of leaving against medical advice among the DU-IE group shows the downstream effects of the opioid crisis.

Characteristics of Twitter Use by State Medicaid Programs in the United States: Machine Learning Approach

Background

Twitter is a potentially valuable tool for public health officials and state Medicaid programs in the United States, which provide public health insurance to 72 million Americans.

Objective

We aim to characterize how Medicaid agencies and managed care organization (MCO) health plans are using Twitter to communicate with the public.

Methods

Using Twitter’s public application programming interface, we collected 158,714 public posts (“tweets”) from active Twitter profiles of state Medicaid agencies and MCOs, spanning March 2014 through June 2019. Manual content analyses identified 5 broad categories of content, and these coded tweets were used to train supervised machine learning algorithms to classify all collected posts.

Results

We identified 15 state Medicaid agencies and 81 Medicaid MCOs on Twitter. The mean number of followers was 1784, the mean number of those followed was 542, and the mean number of posts was 2476. Approximately 39% of tweets came from just 10 accounts. Of all posts, 39.8% (63,168/158,714) were classified as general public health education and outreach; 23.5% (n=37,298) were about specific Medicaid policies, programs, services, or events; 18.4% (n=29,203) were organizational promotion of staff and activities; and 11.6% (n=18,411) contained general news and news links. Only 4.5% (n=7142) of posts were responses to specific questions, concerns, or complaints from the public.

Conclusions

Twitter has the potential to enhance community building, beneficiary engagement, and public health outreach, but appears to be underutilized by the Medicaid program.

Health Policy and Privacy Challenges Associated With Digital Technology

Importance

Digital technology is part of everyday life. Digital interactions generate large amounts of data that can reveal information about the health of individual consumers (the digital health footprint).

Objective

Τo describe health privacy challenges associated with digital technology.

Design, Setting, and Participants

For this qualitative study, In-depth, semistructured, qualitative interviews were conducted with 26 key experts from diverse fields in the US between January 1 and July 31, 2018. Open-ended questions and hypothetical scenarios were used to identify sources of digital information that contribute to consumers' health-relevant digital footprints and challenges for health privacy. Participants also completed a survey instrument on which they rated the health relatedness of digital data sources.

Main Outcomes and Measures

Health policy challenges associated with digital technology based on qualitative responses to expert interviews.

Results

Although experts' ratings of digital data sources suggested a possible distinction between health and nonhealth data, qualitative interviews uniformly indicated that all data can be health data, particularly when aggregated across sources and time. Five key characteristics of the digital health footprint were associated with health privacy policy challenges: invisibility (people are unaware of how their data are tracked), inaccuracy (data in the digital health footprint can be inaccurate), immortality (data have no expiration date and are aggregated over time), marketability (data have immense commercial value and are frequently bought and sold), and identifiability (individuals can be readily reidentified and anonymity is nearly impossible to achieve). There are virtually no regulatory structures in the US to protect health privacy in the context of the digital health footprint.

Conclusions and Relevance

The findings suggest that a sector-specific approach to digital technology privacy in the US may be associated with inadequate health privacy protections.

Access to primary and dental care among adults newly enrolled in Medicaid

OBJECTIVES

Adequate access to primary and dental care is essential for population health, and some state Medicaid programs have expanded insurance coverage for both. However, there are few data on new Medicaid enrollees' ability to access services. We examined the relationship between provider supply and enrollees' identification of usual sources of care.

STUDY DESIGN

Between November 2015 and February 2016, we surveyed low-income adults newly insured through Medicaid in Philadelphia, Pennsylvania, to determine if they had a usual source of care. Additionally, we used geospatial methods to calculate adult population per provider ratios by Census tract for primary and dental care providers who accepted Medicaid patients, then identified low-supply clusters.

METHODS

We used multivariable logistic regression models to describe the odds of identifying usual sources of care based on being in low- or high-supply clusters, adjusting for patient demographics.

RESULTS

Of 1000 contacted individuals, 312 completed the survey. Among respondents, 168 were previously uninsured and newly enrolled in Medicaid; 66.7% of this group identified a usual primary care provider and 42.3% identified a usual dental care provider. In adjusted analyses, individuals living in low- and high-supply areas had similar likelihoods of identifying a usual source of primary or dental care.

CONCLUSIONS

Many new Medicaid enrollees did not have usual sources of primary or dental care, regardless of nearby provider supply. Efforts to understand what improves access or engagement in healthcare among Medicaid enrollees are critical after low-income adults gain insurance.

Effect of Community Health Worker Support on Clinical Outcomes of Low-Income Patients Across Primary Care Facilities: A Randomized Clinical Trial

IMPORTANCE

Addressing the social determinants of health has been difficult for health systems to operationalize.

OBJECTIVE

To assess a standardized intervention, Individualized Management for Patient-Centered Targets (IMPaCT), delivered by community health workers (CHWs) across 3 health systems.

DESIGN, SETTING, AND PARTICIPANTS

This 2-armed, single-blind, multicenter randomized clinical trial recruited patients from 3 primary care facilities in Philadelphia, Pennsylvania, between January 28, 2015, and March 28, 2016. Patients who resided in a high-poverty zip code, were uninsured or publicly insured, and who had a diagnosis for 2 or more chronic diseases were recruited, and patients were randomized to either the CHW intervention or the control arm (goal setting only). Follow-up assessments were conducted at 6 and 9 months after enrollment. Data were analyzed using an intention-to-treat approach from June 2017 to March 2018.

INTERVENTION

Participants set a chronic disease management goal with their primary care physician; those randomized to the CHW intervention received 6 months of tailored support.

MAIN OUTCOMES AND MEASURES

The primary outcome was change in self-rated physical health. The secondary outcomes were self-rated mental health, chronic disease control, patient activation, patient-reported quality of primary care, and all-cause hospitalization.

RESULTS

Of the 592 participants, 370 (62.5%) were female, with a mean (SD) age of 52.6 (11.1) years. Participants in both arms had similar improvements in self-rated physical health (mean [SD], 1.8 [11.2] vs 1.6 [9.9]; P = .89). Patients in the intervention group were more likely to report the highest quality of care (odds ratio [OR], 1.8; 95% CI, 1.4-2.4; risk difference [RD], 0.12; P < .001) and spent fewer total days in the hospital at 6 months (155 days vs 345 days; absolute event rate reduction, 69%) and 9 months (300 days vs 471 days; absolute event rate reduction, 65%). This reduction was driven by a shorter average length of stay (difference, -3.1 days; 95% CI, -6.33 to 0.22; P = .06) and a lower mean number of hospitalizations (difference, -0.3; 95% CI, -0.6 to 0.0; P = .07) among patients who were hospitalized. Patients in the intervention group had a lower odds of repeat hospitalizations (OR, 0.4; 95% CI, 0.2-0.9; RD, -0.24; P = .02), including 30-day readmissions (OR, 0.3; 95% CI, 0.1-0.9; RD, -0.17; P = .04).

CONCLUSIONS AND RELEVANCE

A standardized intervention did not improve self-rated health but did improve the patient-perceived quality of care while reducing hospitalizations, suggesting that health systems may use a standardized intervention to address the social determinants of health.

TRIAL REGISTRATION

ClinicalTrials.gov identifier: NCT02347787.

Why Effective Interventions Do Not Work for All Patients: Exploring Variation in Response to a Chronic Disease Management Intervention

BACKGROUND

Half of all Americans have a chronic disease. Promoting healthy behaviors to decrease this burden is a national priority. A number of behavioral interventions have proven efficacy; yet even the most effective of these has high levels of nonresponse.

OBJECTIVES

In this study, we explore variation in response to an evidence-based community health worker (CHW) intervention for chronic disease management.

RESEARCH DESIGN

We used a convergent parallel design that combined a randomized controlled trial with a qualitative process evaluation that triangulated chart abstraction, in-depth interviews and participant observation.

SUBJECTS

Eligible patients lived in a high-poverty region and were diagnosed with 2 or more of the following chronic diseases: diabetes, obesity, hypertension or tobacco dependence. There were 302 patients in the trial, 150 of whom were randomly assigned to the CHW intervention. Twenty patients and their CHWs were included in the qualitative evaluation.

RESULTS

We found minimal differences between responders and nonresponders by sociodemographic or clinical characteristics. A qualitative process evaluation revealed that health behavior change was challenging for all patients and most experienced failure (ie, gaining weight or relapsing with cigarettes) along the way. Responders seemed to increase their resolve after failed attempts at health behavior change, while nonresponders became discouraged and "shut down."

CONCLUSIONS

Failure is a common and consequential aspect of health behavior change; a deeper understanding of failure should inform chronic disease interventions.

Rideshare-Based Medical Transportation for Medicaid Patients and Primary Care Show Rates: A Difference-in-Difference Analysis of a Pilot Program

BACKGROUND

Transportation to primary care is a well-documented barrier for patients with Medicaid, despite access to non-emergency medical transportation (NEMT) benefits. Rideshare services, which offer greater convenience and lower cost, have been proposed as an NEMT alternative.

OBJECTIVE

To evaluate the impact of rideshare-based medical transportation on the proportion of Medicaid patients attending scheduled primary care appointments.

DESIGN

In one of two similar practices, all eligible Medicaid patients were offered rideshare-based transportation ("rideshare practice"). A difference-in-difference analytical approach using logistic regression with robust standard errors was employed to compare show rate changes between the rideshare practice and the practice where rideshare was not offered ("control practice").

PARTICIPANTS

Our study population included residents of West Philadelphia who were insured by Medicaid and were established patients at two academic general internal medicine practices located in the same building.

INTERVENTION

We designed a rideshare-based transportation pilot intervention. Patients were offered the service during their reminder call 2 days before the appointment, and rides were prescheduled by research staff. Patients then called research staff to schedule their return trip home.

MAIN MEASURES

We assessed the effect of offering rideshare-based transportation on appointment show rates by comparing the change in the average show rate for the rideshare practice, from the baseline period to the intervention period, with the change at the control practice.

KEY RESULTS

At the control practice, the show rate declined from 60% (146/245) to 51% (34/67). At the rideshare practice, the show rate improved from 54% (72/134) to 68% (41/60). In the adjusted model, controlling for patient demographics and provider type, the odds of showing up for an appointment before and after the intervention increased 2.57 (1.10-6.00) times more in the rideshare practice than in the control practice.

CONCLUSIONS

Results of this pilot program suggest that offering a rideshare-based transportation service can increase show rates to primary care for Medicaid patients.

Association of Rideshare-Based Transportation Services and Missed Primary Care Appointments: A Clinical Trial

IMPORTANCE

Transportation barriers contribute to missed primary care appointments for patients with Medicaid. Rideshare services have been proposed as alternatives to nonemergency medical transportation programs because of convenience and lower costs.

OBJECTIVE

To evaluate the association between rideshare-based medical transportation and missed primary care appointments among Medicaid patients.

DESIGN, SETTING, AND PARTICIPANTS

In a prospective clinical trial, 786 Medicaid beneficiaries who resided in West Philadelphia and were established primary care patients at 1 of 2 academic internal medicine practices located within the same building were included. Participants were allocated to being offered complimentary ride-sharing services (intervention arm) or usual care (control arm) based on the prescheduled day of their primary care appointment reminder. Those scheduled on even-numbered weekdays were in the intervention arm and on odd-numbered weekdays, the control arm. The primary study outcome was the rate of missed appointments, estimated using an intent-to-treat approach. All individuals receiving a phone call reminder were included in the study sample, regardless of whether they answered their phone. The study was conducted between October 24, 2016, and April 20, 2017.

INTERVENTIONS

A model of providing rideshare-based transportation was designed. As part of usual care, patients assigned to both arms received automated appointment phone call reminders. As part of the study protocol, patients assigned to both arms received up to 3 additional appointment reminder phone calls from research staff 2 days before their scheduled appointment. During these calls, patients in the intervention arm were offered a complimentary ridesharing service. Research staff prescheduled rides for those interested in the service. After their appointment, patients phoned research staff to initiate a return trip home.

MAIN OUTCOMES AND MEASURES

Missed appointment rate (no shows and same-day cancellations) in the intervention compared with control arm.

RESULTS

Of the 786 patients allocated to the intervention or control arm, 566 (72.0%) were women; mean (SD) age was 46.0. (12.5) years. Within the intervention arm, 85 among 288 (26.0%) participants who answered the phone call used ridesharing. The missed appointment rate was 36.5% (144 of 394) for the intervention arm and 36.7% (144 of 392) for the control arm (P = .96).

CONCLUSIONS AND RELEVANCE

The uptake of ridesharing was low and did not decrease missed primary care appointments. Future studies trying to reduce missed appointments should explore alternative delivery models or targeting populations with stronger transportation needs.

TRIAL REGISTRATION

clinicaltrials.gov Identifier: NCT02955433.

Which Patients Report That Their Urologists Advised Them to Forgo Initial Treatment for Prostate Cancer?

OBJECTIVE

To examine how frequently patients report that their urologist recommended forgoing definitive treatment and assess the impact of these recommendations on treatment choice and perceived quality of cancer care.

METHODS

We mailed surveys to men newly diagnosed with localized prostate cancer between 2014 and 2015 (adjusted response rate of 51.3%). Men reported whether their urologist recommended forgoing definitive treatment. Using logistic regression models, we assessed patient-level predictors of receiving a recommendation to forgo definitive treatment and estimated associations of receiving this recommendation with receipt of definitive treatment and perceived quality of cancer care among men with low-risk tumors and limited life expectancies.

RESULTS

Nearly two-thirds (62.2%) of men with low-risk tumors and 46.4% with limited life expectancies received recommendations from their urologists to forgo definitive treatment. Among men with limited life expectancies, those with low-risk tumors were more likely to receive this recommendation compared with men with high-risk tumors (odds ratio [OR] 3.41; 95% confidence interval [CI] 2.17-5.37). Men with low-risk tumors who were recommended to forgo definitive treatment were less likely to receive definitive treatment (OR 0.48; 95% CI 0.32-0.73) but did not report lower perceived quality of care (OR 0.97; 95% CI 0.63-1.48).

CONCLUSION

In this population-based study, a majority of men with low-risk prostate cancer report receiving recommendations from their urologists to forgo definitive treatment. Our results suggest that urologists have a strong influence on patient treatment choice and could increase active surveillance uptake in men eligible for expectant management without patients perceiving lower quality of cancer care.

Racial Disparities In Geographic Access To Primary Care In Philadelphia

Primary care is often thought of as the gateway to improved health outcomes and can lead to more efficient use of health care resources. Because of primary care's cardinal importance, adequate access is an important health policy priority. In densely populated urban areas, spatial access to primary care providers across neighborhoods is poorly understood. We examined spatial variation in primary care access in Philadelphia, Pennsylvania. We calculated ratios of adults per primary care provider for each census tract and included buffer zones based on prespecified drive times around each tract. We found that the average ratio was 1,073; the supply of primary care providers varied widely across census tracts, ranging from 105 to 10,321. We identified six areas of Philadelphia that have much lower spatial accessibility to primary care relative to the rest of the city. After adjustment for sociodemographic and insurance characteristics, the odds of being in a low-access area were twenty-eight times greater for census tracts with a high proportion of African Americans than in tracts with a low proportion of African Americans.

Evaluating the association between the built environment and primary care access for new Medicaid enrollees in an urban environment using Walk and Transit Scores

Worse health outcomes among those living in poverty are due in part to lower rates of health insurance and barriers to care. As the Affordable Care Act reduced financial barriers, identifying persistent barriers to accessible health care continues to be important. We examined whether the built environment as reflected by Walk Score™ (a measure of walkability to neighborhood resources) and Transit Score™ (a measure of transit access) is associated with having a usual source of care among low-income adults, newly enrolled in Medicaid. We received responses from 312 out of 1000 new Medicaid enrollees in Philadelphia, a large, densely populated urban area, who were surveyed between 2015 and 2016 to determine if they had identified a usual source of outpatient primary care. Respondents living at an address with a low Walk Scores (< 70) had 84% lower odds of having a usual source of care (OR 0.16, 95% CI 0.04-0.61). Transit scores were not associated with having a usual source of care. Walk Score may be a tool for policy makers and providers of care to identify populations at risk for worse primary care access.

Community Health Worker Support for Disadvantaged Patients With Multiple Chronic Diseases: A Randomized Clinical Trial

OBJECTIVES

To determine whether a community health worker (CHW) intervention improved outcomes in a low-income population with multiple chronic conditions.

METHODS

We conducted a single-blind, randomized clinical trial in Philadelphia, Pennsylvania (2013-2014). Participants (n = 302) were high-poverty neighborhood residents, uninsured or publicly insured, and diagnosed with 2 or more chronic diseases (diabetes, obesity, tobacco dependence, hypertension). All patients set a disease-management goal. Patients randomly assigned to CHWs also received 6 months of support tailored to their goals and preferences.

RESULTS

Support from CHWs (vs goal-setting alone) led to improvements in several chronic diseases (changes in glycosylated hemoglobin: -0.4 vs 0.0; body mass index: -0.3 vs -0.1; cigarettes per day: -5.5 vs -1.3; systolic blood pressure: -1.8 vs -11.2; overall P = .08), self-rated mental health (12-item Short Form survey; 2.3 vs -0.2; P = .008), and quality of care (Consumer Assessment of Healthcare Providers and Systems; 62.9% vs 38%; P < .001), while reducing hospitalization at 1 year by 28% (P = .11). There were no differences in patient activation or self-rated physical health.

CONCLUSIONS

A standardized CHW intervention improved chronic disease control, mental health, quality of care, and hospitalizations and could be a useful population health management tool for health care systems.

TRIAL REGISTRATION

clinicaltrials.gov identifier: NCT01900470.

Development and validation of an algorithm to complete colonoscopy using standard endoscopes in patients with prior incomplete colonoscopy

BACKGROUND AND STUDY AIMS

 Incomplete colonoscopy may occur as a result of colon angulation (adhesions or diverticulosis), endoscope looping, or both. Specialty endoscopes/devices have been shown to successfully complete prior incomplete colonoscopies, but may not be widely available. Radiographic or other image-based evaluations have been shown to be effective but may miss small or flat lesions, and colonoscopy is often still indicated if a large lesion is identified. The purpose of this study was to develop and validate an algorithm to determine the optimum endoscope to ensure completion of the examination in patients with prior incomplete colonoscopy.

PATIENTS AND METHODS

 This was a prospective cohort study of 175 patients with prior incomplete colonoscopy who were referred to a single endoscopist at a single academic medical center over a 3-year period from 2012 through 2015. Colonoscopy outcomes from the initial 50 patients were used to develop an algorithm to determine the optimal standard endoscope and technique to achieve cecal intubation. The algorithm was validated on the subsequent 125 patients.

RESULTS

 The overall repeat colonoscopy success rate using a standard endoscope was 94 %. The initial standard endoscope specified by the algorithm was used and completed the colonoscopy in 90 % of patients.

CONCLUSIONS

 This study identifies an effective strategy for completing colonoscopy in patients with prior incomplete examination, using widely available standard endoscopes and an algorithm based on patient characteristics and reasons for prior incomplete colonoscopy.

Porous structure of ion exchange membranes investigated by various techniques

A comparative review of various techniques is provided: mercury intrusion porosimetry, nitrogen sorption porosimetry, differential scanning calorimetry (DSC)-based thermoporosimetry, and standard contact porosimetry (SCP), which allows determining pore volume distribution versus pore radius/water binding energy in ion-exchange membranes (IEMs). IEMs in the swollen state have a labile structure involving micro-, meso- and macropores, whose size is a function of the external water vapor pressure. For such materials, the most appropriate methods for quantifying their porosity are DSC and SCP. Especially significant information is given by the SCP method allowing measuring porosimetric curves in a very large pore size range from 1 to 10⁵nm. Experimental results of water distribution in homogeneous and heterogeneous commercial and modified IEMs are presented. The effect of various factors on water distribution is reviewed, i.e. nature of polymeric matrix and functional groups, method for membrane preparation, membrane ageing. A special attention is given to the effect of membrane modification by embedding nanoparticles in their structure. The porosimetric curves are considered along with the results of electrochemical characterization involving the measurements of membrane conductivity, as well as diffusion and electroosmotic permeability. It is shown that addition of nanoparticles may lead to either increase or decrease of water content in IEMs, different ranges of pore size being affected. Hybrid membranes modified with hydrated zirconium dioxide exhibit much higher permselectivity in comparison with the pristine membranes. The diversity of the responses of membrane properties to their modification allows for formation of membranes suitable for fuel cells, electrodialysis or other applications.

If You Book It, Will They Come? Attendance at Postdischarge Follow-Up Visits Scheduled by Inpatient Providers

BACKGROUND

Postdischarge follow-up visits (PDFVs) are widely recommended to improve inpatient-outpatient transitions of care.

OBJECTIVE

To measure PDFV attendance rates.

DESIGN

Observational cohort study.

SETTING

Medical units at an academic quaternary-care hospital and its affiliated outpatient clinics.

PATIENTS

Adult patients hospitalized between April 2014 and March 2015 for whom at least 1 PDFV with our health system was scheduled. Exclusion criteria included nonprovider visits, visits cancelled before discharge, nonaccepted health insurance, and visits scheduled for deceased patients.

MEASUREMENTS

The study outcome was the incidence of PDFVs resulting in no-shows or same-day cancellations (NS/SDCs).

RESULTS

Of all hospitalizations, 6136 (52%) with 9258 PDFVs were analyzed. Twenty-five percent of PDFVs were NS/SDCs, 23% were cancelled before the visit, and 52% were attended as scheduled. In multivariable regression models, NS/SDC risk factors included black race (odds ratio [OR] 1.94, 95% confidence interval [CI], 1.63-2.32), longer lengths of stay (hospitalizations ≥15 days: OR 1.51, 95% CI, 1.22- 1.88), and discharge to facility (OR 2.10, 95% CI, 1.70-2.60). Conversely, NS/SDC visits were less likely with advancing age (age ≥65 years: OR 0.39, 95% CI, 0.31-0.49) and driving distance (highest quartile: OR 0.65, 95% CI, 0.52-0.81). Primary care visits had higher NS/SDC rates (OR 2.62, 95% CI, 2.03-3.38) than oncologic visits. The time interval between discharge and PDFV was not associated with NS/SDC rates.

CONCLUSIONS

PDFVs were scheduled for more than half of hospitalizations, but 25% resulted in NS/SDCs. New strategies are needed to improve PDFV attendance.

Mutual Distrust: Perspectives From Researchers and Policy Makers on the Research to Policy Gap in 2013 and Recommendations for the Future

The production of health policy-relevant research is necessary, but not sufficient, to promote its utilization in policy. Our objective was to understand the perspectives of United States’ state-level policy makers and health researchers on the barriers and facilitators to the translation of health evidence into the policy process, with a particular focus on issues related to relationship building. We conducted interviews with 215 US health services and health policy researchers and 40 state-level staffers and legislators. Researchers and policy makers faced the same major barrier to research translation: lack of dedicated time to do so. Some policy makers questioned the credibility of research, and researchers questioned policy makers’ authentic desire to use evidence in decision making. For some study participants, a mutual mistrust of the other group challenges stronger relationship formation. Interventions are needed to help both groups understand a broader role that research plays in policy making and to increase personal contact, and ultimately trusted relationships, across various actors in the policy process.

Racial Differences in Prostate Cancer Treatment: The Role of Socioeconomic Status

OBJECTIVE

This study examines whether socioeconomic status (SES), measured at both the individual and neighborhood levels, is associated with receipt of definitive treatment for localized prostate cancer and whether these associations mediate racial differences in treatment between non-Hispanic White and non-Hispanic Black men.

DESIGN

The Philadelphia Area Prostate Cancer Access Study (P² Access) is a mailed, cross-sectional survey of men sampled from the Pennsylvania Cancer Registry, combined with neighborhood Census data.

SETTING

Eight counties in southeastern Pennsylvania.

PARTICIPANTS

2,386 men with prostate adenocarcinoma.

MAIN MEASURES

Receipt of definitive treatment, race, self-reported income, education, employment status, and neighborhood SES.

RESULTS

Overall, Black and White men were equally likely to receive definitive treatment. Men living in neighborhoods with higher SES were more likely to receive definitive treatment (OR 1.57, 95%CI 1.01, 2.42). Among men who received definitive treatment, Black men were significantly less likely to receive radical prostatectomy compared with White men (OR .71, 95% CI .52, .98), as were men with some college education compared with those with a high school education or less (OR .66, 95% CI .47, .94). SES does not mediate racial differences in receipt of definitive treatment or the type of definitive treatment received, and associations with income or employment status were not significant.

CONCLUSIONS

These results stress the importance of examining racial disparities within geographic areas and highlight the unique associations that different measures of SES, particularly neighborhood SES and education, may have with prostate cancer treatment.

Effect of Outreach Messages on Medicaid Enrollment

OBJECTIVES

To measure the impact of different outreach messages on health insurance enrollment among Medicaid-eligible adults.

METHODS

Between March 2015 and April 2016, we conducted a series of experiments using mail-based outreach that encouraged individuals to enroll in Pennsylvania's expanded Medicaid program. Recipients were randomized to receive 1 of 4 different messages describing the benefits of health insurance. The primary outcome was the response rate to each letter.

RESULTS

We mailed outreach letters to 32 993 adults in Philadelphia. Messages that emphasized the dental benefits of insurance were significantly more likely to result in a response than messages emphasizing the health benefits (odds ratio = 1.33; 95% confidence interval = 1.10, 1.61).

CONCLUSIONS

Medicaid enrollment outreach messages that emphasized the dental benefits of insurance were more effective than those that emphasized the health-related benefits. Public Health Implications. Although the structure and eligibility of the Medicaid program are likely to change, testing and identifying successful outreach and enrollment strategies remains important. Outreach messages that emphasize dental benefits may be more effective at motivating enrollment among individuals of low socioeconomic status.

Twitter accounts followed by Congressional health staff

OBJECTIVES

Although health policy research should inform policy making, the communication gap between researchers and policy makers limits successful translation. Social media represents a new opportunity to connect researchers and policy makers. Our objective was to assess who Congressional health policy staff follow on a major social media platform.

STUDY DESIGN

Cross-sectional study.

METHODS

Our study measured Congressional health policy staff's use of Twitter and the types of individuals and organizations they follow. To focus on more influential Twitter accounts, we restricted our sample to those followed by at least 3 individual Congressional staff members.

RESULTS

Of the 30,843 accounts followed by the 115 Congressional health policy staff, 1273 were potentially policy-related and followed by 3 or more staff. Of these, few were academically affiliated (2.4%) or explicitly health-related (5.6%) sites; many were general news media sources (50.9%) and political and governmental sources (36.4%). Health-focused accounts were frequently connected to the news media or government rather than academia. Top accounts followed (ie, highest quintile) were most likely to be national news organizations (odds ratio [OR], 5.88; 95% confidence interval [CI], 1.75-19.7) and elected officials (OR, 8.22; 95% CI, 1.75-38.6) compared with advocacy and interest groups.

CONCLUSIONS

Health-related and academic sources are largely absent from the Twitter conversations with US Congressional health policy staff. Even within social media, traditional and political news media are important information intermediaries that researchers and journals should target to disseminate health policy evidence.

The Role of Community Health Centers in Reducing Racial Disparities in Spatial Access to Primary Care

INTRODUCTION

Racial minorities are more likely to live in primary care shortage areas. We sought to understand community health centers' (CHCs) role in reducing disparities.

METHODS

We surveyed all primary care practices in an urban area, identified low access areas, and examined how CHCs influence spatial accessibility.

RESULTS

Census tracts with higher rates of public insurance (≥40% vs <10%, odds ratio [OR] = 31.06, P < .001; 30-39% vs 10%, OR = 7.84, P = 0.001) were more likely to be near a CHC and those with moderate rates of uninsurance (10%-19% vs <10%, OR = 0.42, P = .045) were less likely. Racial composition was not associated with proximity. Tracts close to a CHC were less likely (OR = 0.11, P < .0001) to be in a low access area. This association did not differ based on racial composition.

DISCUSSION

Although CHCs were more likely to be in areas with a greater fraction of racial minorities, location was more strongly influenced by public insurance rates. CHCs reduced the likelihood of being in low access areas but the effect did not vary by tract racial composition.

Perspectives of Patients With Cancer on the Ethics of Rapid-Learning Health Systems

Purpose To inform the evolving implementation of CancerLinQ and other rapid-learning systems for oncology care, we sought to evaluate perspectives of patients with cancer regarding ethical issues. Methods Using the GfK Group online research panel, representative of the US population, we surveyed 875 patients with cancer; 621 (71%) responded. We evaluated perceptions of appropriateness (scored from 1 to 10; 10, very appropriate) using scenarios and compared responses by age, race, and education. We constructed a scaled measure of comfort with secondary use of deidentified medical information and evaluated its correlates in a multivariable model. Results Of the sample, 9% were black and 9% Hispanic; 38% had completed high school or less, and 59% were age ≥ 65 years. Perceptions of appropriateness were highest when consent was obtained and university researchers used data to publish a research study (weighted mean appropriateness, 8.47) and lowest when consent was not obtained and a pharmaceutical company used data for marketing (weighted mean appropriateness, 2.7). Most respondents (72%) thought secondary use of data for research was very important, although those with lower education were less likely to endorse this (62% v 78%; P < .001). Overall, 35% believed it was necessary to obtain consent each time such research was to be performed; this proportion was higher among blacks/Hispanics than others (48% v 33%; P = .02). Comfort with the use of deidentified information from medical records varied by scenario and overall was associated with distrust in the health care system. Conclusion Perceptions of patients with cancer regarding secondary data use depend on the user and the specific use of the data, while also frequently differing by patient sociodemographic factors. Such information is critical to inform ongoing efforts to implement oncology learning systems.

A multidimensional view of racial differences in access to prostate cancer care

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Background: Racial differences in prostate cancer treatment and outcomes are widespread and poorly understood. We sought to determine whether access to care, measured across multiple dimensions, contribute to racial differences in prostate cancer. Methods: The Philadelphia Area Prostate Cancer Access Study (P2 Access) included 2374 men diagnosed with localized prostate cancer from 2012 to 2014. Patient survey data was used to determine experiences of accessing prostate cancer care (response rate 51.1%). An audit survey using simulated patient calls was used to determine appointment availability and wait times at 151 urology practices. Patient and practice addresses were geocoded to construct distance measures. We used multivariable logistic regression models to determine the association between five different domains of access—availability, accessibility, accommodation, affordability, and acceptability—and receipt of definitive treatment with radical prostatectomy or radiation, satisfaction with care, and doctor-patient communication. Results: There were 1907 non-Hispanic white and 394 black men in our cohort, the majority (71%) with stage 1 disease. Overall, 85% of men received definitive treatment with no differences by race. None of the access domains were significantly associated with definitive treatment overall or with radical prostatectomy in adjusted models. Black men were less likely to report good doctor-patient communication (60% vs 71%, p < 0.001) and high satisfaction with their care (69% vs 81%, p < 0.001). Communication ratings remained significantly lower among black men compared to white men in adjusted models (odds ratio = 1.49, 95% Confidence Interval 1.03, 2.16). Each domain of access was significantly associated with lower satisfaction with care and worse communication; however, differences in access did not mediate racial disparities for these measures. Conclusions: This study presents the first comprehensive assessment of access to prostate cancer care, showing that while access was related to overall satisfaction and better doctor-patient communication, it did not appear to explain racial differences in these measures of cancer care.