Rural-Urban Disparities in Colorectal Cancer Screening, Diagnosis, Treatment, and Survivorship Care: A Systematic Review and Meta-Analysis.

BACKGROUND: Rural residents have a higher prevalence of colorectal cancer (CRC) mortality compared to urban individuals. Policies have been aimed at improving access to CRC screening to reduce these outcomes. However, little attention has been paid to other determinants of CRC-related outcomes, such as stage at diagnosis, treatment, or survivorship care. The main objective of this analysis was to evaluate literature describing differences in CRC screening, stage at diagnosis, treatment, and survivorship care between rural and urban individuals. MATERIALS AND METHODS: We conducted a systematic review of electronic databases using a combination of MeSH and free-text search terms related to CRC screening, stage at diagnosis, treatment, survivorship care, and rurality. We identified 921 studies, of which 39 were included. We assessed methodological quality using the ROBINS-E tool and summarized findings descriptively. A meta-analysis was performed of studies evaluating CRC screening using a random-effects model. RESULTS: Seventeen studies reported disparities between urban and rural populations in CRC screening, 12 on treatment disparities, and 8 on staging disparities. We found that rural individuals were significantly less likely to report any type of screening at any time period (pooled odds ratio = 0.81, 95% CI, 0.76-0.86). Results were inconclusive for disparities in staging at diagnosis and treatment. One study reported a lower likelihood of use of CRC survivorship care for rural individuals compared to urban individuals. CONCLUSION: There remains an urgent need to evaluate and address CRC disparities in rural areas. Investigators should focus future work on assessing the quality of staging at diagnosis, treatment, and survivorship care in rural areas.

Facilitators of and barriers to County Behavioral Health System Transformation and Innovation: an interview study.

BACKGROUND: Inadequate and inequitable access to quality behavioral health services and high costs within the mental health systems are long-standing problems. System-level (e.g., fee-for-service payment model, lack of a universal payor) and individual factors (e.g., lack of knowledge of existing resources) contribute to difficulties in accessing resources and services. Patients are underserved in County behavioral health systems in the United States. Orange County's (California) Behavioral Health System Transformation project sought to improve access by addressing two parts of their system: developing a template for value-based contracts that promote payor-agnostic care (Part 1); developing a digital platform to support resource navigation (Part 2). Our aim was to evaluate facilitators of and barriers to each of these system changes. METHODS: We collected interview data from County or health care agency leaders, contracted partners, and community stakeholders. Themes were informed by the Consolidated Framework for Implementation Research. RESULTS: Five themes were identified related to behavioral health system transformation, including 1) aligning goals and values, 2) addressing fit, 3) fostering engagement and partnership, 4) being aware of implementation contexts, and 5) promoting communication. A lack of fit into incentive structures and changing state guidelines and priorities were barriers to contract development. Involving diverse communities to inform design and content facilitated the process of developing digital tools. CONCLUSIONS: The study highlights the multifaceted factors that help facilitate or hinder behavioral health system transformation, such as the need for addressing systematic and process behaviors, leveraging the knowledge of leadership and community stakeholders, fostering collaboration, and adapting to implementation contexts.

Variability in the Integration of Peers in a Multi-site Digital Mental Health Innovation Project.

Peer support specialists ("peers") who have the lived experience of, and are in recovery from, mental health challenges are increasingly being integrated into mental health care as a reimbursable service across the US. This study describes the ways peers were integrated into Help@Hand, a multi-site innovation project that engaged peers throughout efforts to develop and offer digital mental health interventions across counties/cities ("sites") in California. Using a mixed methods design, we collected quantitative data via quarterly online surveys, and qualitative data via semi-annual semi-structured phone interviews with key informants from Help@Hand sites. Quantitative data were summarized as descriptive findings and qualitative data from interviews were analyzed using rapid qualitative analysis methods. In the final analytic phase, interview quotes were used to illustrate the complex realities underlying quantitative responses. 117 quarterly surveys and 46 semi-annual interviews were completed by key informants from 14 sites between September 2020 and January 2023. Peers were integrated across diverse activities for support and implementation of digital mental health interventions, including development of training and educational materials (78.6% of sites), community outreach (64.3%), technology testing (85.7%), technology piloting (90.9%), digital literacy training (71.4%), device distribution (63.6%), technical assistance (72.7%), and cross-site collaboration (66.7%). Peer-engaged activities shifted over time, reflecting project phases. Peer-provided digital literacy training and technology-related support were key ingredients for project implementations. This study indicates the wide range of ways peers can be integrated into digital mental health intervention implementations. Considering contextual readiness for peer integration may enhance their engagement into programmatic activities.

Real-World Adoption of Mental Health Support Among Adolescents: Cross-Sectional Analysis of the California Health Interview Survey.

OBJECTIVE: We aim to examine: (a) the extent to which patterns of adoption of counseling services and digital mental health interventions (DMHIs) shifted in recent years (2019-2021); (b) the impact of distress on adoption of mental health support; and (c) reasons related to adolescents' low adoption of DMHIs when experiencing distress. METHODS: Data were from three cohorts of adolescents aged 12-17 years (n = 847 in 2019; n = 1,365 in 2020; n = 1,169 in 2021) recruited as part of the California Health Interview Survey. We estimated logistic regression models to examine the likelihood of using mental health support as a function of psychological distress, sociodemographic characteristics, and cohorts. We also analyzed adolescents' self-reported reasons for not trying DMHIs as a function of distress. RESULTS: The proportion of adolescents reporting elevated psychological distress (∼50%) was higher than those adopting counseling services (<20%) or DMHIs (<10%). A higher level of distress was associated with a greater likelihood of receiving counseling (OR = 1.15), and using DMHIs to connect with a professional (Odds ratio (OR) = 1.11) and for self-help (OR = 1.17). Among those experiencing high distress, adolescents' top reason for not adopting an online tool was a lack of perceived need (19.2%). CONCLUSION: Adolescents' main barriers to DMHI adoption included a lack of perceived need, which may be explained by a lack of mental health literacy. Thoughtful marketing and dissemination efforts are needed to increase mental health awareness and normalize adoption of counseling services and DMHIs.

Understanding Mental Health App Use Among Community College Students: Web-Based Survey Study.

BACKGROUND: Mental health concerns are a significant issue among community college students, who often have less access to resources than traditional university college students. Mobile apps have the potential to increase access to mental health care, but there has been little research investigating factors associated with mental health app use within the community college population. OBJECTIVE: This study aimed to understand facilitators of and barriers to mental health app use among community college students. METHODS: A web-based survey was administered to a randomly selected sample of 500 community college students from April 16 to June 30, 2020. Structural equation modeling was used to test the relationships between the use of mental health apps, perceived stress, perceived need to seek help for mental health concerns, perceived stigma, past use of professional mental health services, privacy concerns, and social influence of other people in using mental health apps. RESULTS: Of the 500 participants, 106 (21.2%) reported use of mental health apps. Perceived stress, perceived need to seek help, past use of professional services, and social influence were positively associated with mental health app use. Furthermore, the effect of stress was mediated by a perceived need to seek help. Privacy concerns were negatively associated with mental health app use. Stigma, age, and gender did not have a statistically significant effect. CONCLUSIONS: These findings can inform development of new digital interventions and appropriate outreach strategies to engage community college students in using mental health apps.

Rise in Use of Digital Mental Health Tools and Technologies in the United States During the COVID-19 Pandemic: Survey Study.

BACKGROUND: Accompanying the rising rates of reported mental distress during the COVID-19 pandemic has been a reported increase in the use of digital technologies to manage health generally, and mental health more specifically. OBJECTIVE: The objective of this study was to systematically examine whether there was a COVID-19 pandemic-related increase in the self-reported use of digital mental health tools and other technologies to manage mental health. METHODS: We analyzed results from a survey of 5907 individuals in the United States using Amazon Mechanical Turk (MTurk); the survey was administered during 4 week-long periods in 2020 and survey respondents were from all 50 states and Washington DC. The first set of analyses employed two different logistic regression models to estimate the likelihood of having symptoms indicative of clinical depression and anxiety, respectively, as a function of the rate of COVID-19 cases per 10 people and survey time point. The second set employed seven different logistic regression models to estimate the likelihood of using seven different types of digital mental health tools and other technologies to manage one's mental health, as a function of symptoms indicative of clinical depression and anxiety, rate of COVID-19 cases per 10 people, and survey time point. These models also examined potential interactions between symptoms of clinical depression and anxiety, respectively, and rate of COVID-19 cases. All models controlled for respondent sociodemographic characteristics and state fixed effects. RESULTS: Higher COVID-19 case rates were associated with a significantly greater likelihood of reporting symptoms of depression (odds ratio [OR] 2.06, 95% CI 1.27-3.35), but not anxiety (OR 1.21, 95% CI 0.77-1.88). Survey time point, a proxy for time, was associated with a greater likelihood of reporting clinically meaningful symptoms of depression and anxiety (OR 1.19, 95% CI 1.12-1.27 and OR 1.12, 95% CI 1.05-1.19, respectively). Reported symptoms of depression and anxiety were associated with a greater likelihood of using each type of technology. Higher COVID-19 case rates were associated with a significantly greater likelihood of using mental health forums, websites, or apps (OR 2.70, 95% CI 1.49-4.88), and other health forums, websites, or apps (OR 2.60, 95% CI 1.55-4.34). Time was associated with increased odds of reported use of mental health forums, websites, or apps (OR 1.20, 95% CI 1.11-1.30), phone-based or text-based crisis lines (OR 1.20, 95% CI 1.10-1.31), and online, computer, or console gaming/video gaming (OR 1.12, 95% CI 1.05-1.19). Interactions between COVID-19 case rate and mental health symptoms were not significantly associated with any of the technology types. CONCLUSIONS: Findings suggested increased use of digital mental health tools and other technologies over time during the early stages of the COVID-19 pandemic. As such, additional effort is urgently needed to consider the quality of these products, either by ensuring users have access to evidence-based and evidence-informed technologies and/or by providing them with the skills to make informed decisions around their potential efficacy.

The costs outweigh the benefits: seeing side-effects online may decrease adherence to statins.

BACKGROUND: The prevalence of medical misinformation on the Internet has received much attention among researchers concerned that exposure to such information may inhibit patient adherence to prescriptions. Yet, little is known about information people see when they search for medical information and the extent to which exposure is directly related to their decisions to follow physician recommendations. These issues were examined using statin prescriptions as a case study. METHODS: We developed and used a tool to rank the quality of statin-related web pages based on the presence of information about side effects, clinical benefits, management of side effects, and misinformation. We then conducted an experiment in which students were presented with a hypothetical scenario in which an older relative was prescribed a statin but was unsure whether to take the medication. Participants were asked to search the web for information about statins and make a recommendation to this relative. Their search activity was logged using a web-browser add-on. Websites each participant visited were scored for quality using our tool, quality scores were aggregated for each participant and were subsequently used to predict their recommendation. RESULTS: Exposure to statin-related benefits and management of side effects during the search was significantly associated with a higher probability of recommending that an older relative adhere to their physician's recommendation. Exposure to misinformation and side effects were not associated, nor were any other participant characteristics. Bigram analyses of the top reasons participants gave for their recommendation mirrored the statistical findings, except that among participants who did not recommend following the prescription order, myriad side effects were mentioned. CONCLUSIONS: Our findings suggest that units of information people see on health-related websites are not treated equally. Our methods offer new understanding at a granular level about the impact of Internet searches on health decisions regarding evidence-based recommended medications. Our findings may be useful to physicians considering ways to address non-adherence. Preventive care should include actively engaging patients in discussions about health information they may find on the web. The effectiveness of this strategy should be examined in future studies.

Going the Extra Mile? How Provider Network Design Increases Consumer Travel Distance, Particularly for Rural Consumers.

CONTEXT: The practical accessibility to medical care facilitated by health insurance plans depends not just on the number of providers within their networks but also on distances consumers must travel to reach the providers. Long travel distances inconvenience almost all consumers and may substantially reduce choice and access to providers for some. METHODS: The authors assess mean and median travel distances to cardiac surgeons and pediatricians for participants in (1) plans offered through Covered California, (2) comparable commercial plans, and (3) unrestricted open-network plans. The authors repeat the analysis for higher-quality providers. FINDINGS: The authors find that in all areas, but especially in rural areas, Covered California plan subscribers must travel longer than subscribers in the comparable commercial plan; subscribers to either plan must travel substantially longer than consumers in open networks. Analysis of access to higher-quality providers show somewhat larger travel distances. Differences between ACA and commercial plans are generally substantively small. CONCLUSIONS: While network design adds travel distance for all consumers, this may be particularly challenging for transportation-disadvantaged populations. As distance is relevant to both health outcomes and the cost of obtaining care, this analysis provides the basis for more appropriate measures of network adequacy than those currently in use.

Certificate of need and the cost of competition in home healthcare markets.

We used 2010-16 Medicare Cost Reports for 10,737 freestanding home health agencies (HHAs) to examine the impact of home health (HH) and nursing home (NH) certificate-of-need (CON) laws on HHA caseload, total and per-patient variable costs. After adjusting for other HHA characteristics, total costs were higher in states with only HH CON laws ($2,975,698), only NH CON laws ($1,768,097), and both types of laws ($3,511,277), compared with no CON laws ($1,538,536). Higher costs were driven by caseloads, as CON reduced per-patient costs. Additional research is needed to distinguish whether this is due to skimping on quality vs. economies of scale.

A Knotty Problem: Consumer Access and the Regulation of Provider Networks.

In order to increase access to medical services, expanding coverage has long been the preferred solution of policy makers and advocates alike. The calculus appeared straightforward: provide individuals with insurance, and they will be able to see a provider when needed. However, this line of thinking overlooks a crucial intermediary step: provider networks. As provider networks offered by health insurers link available medical services to insurance coverage, their breadth mediates access to health care. Yet the regulation of provider networks is technically, logistically, and normatively complex. What does network regulation currently look like and what should it look like in the future? We take inventory of the ways private and public entities regulate provider networks. Variation across insurance programs and products is truly remarkable, not grounded in empirical justification, and at times inherently absurd. We argue that regulators should be pragmatic and focus on plausible policy levers. These include assuring network accuracy, transparency for consumers, and consumer protections from grievous inadequacies. Ultimately, government regulation provides an important foundation for ensuring minimum levels of access and providing consumers with meaningful information. Yet, information is only truly empowering if consumers can exercise at least some choice in balancing costs, access, and quality.

Impact of Nursing Home Palliative Care Teams on End-of-Life Outcomes: A Randomized Controlled Trial.

BACKGROUND: Deficits in end-of-life care in nursing homes (NHs) are reported, but the impact of palliative care teams (PCTeams) on resident outcomes remains largely untested. OBJECTIVE: Test the impact of PCTeams on end-of-life outcomes. RESEARCH DESIGN: Multicomponent strategy employing a randomized, 2-arm controlled trial with a difference-in-difference analysis, and a nonrandomized second control group to assess the intervention's placebo effect. SUBJECTS: In all, 25 New York State NHs completed the trial (5830 decedent residents) and 609 NHs were in the nonrandomized group (119,486 decedents). MEASURES: Four risk-adjusted outcome measures: place of death, number of hospitalizations, self-reported moderate-to-severe pain, and depressive symptoms. The Minimum Data Set, vital status files, staff surveys, and in-depth interviews were employed. For each outcome, a difference-in-difference model compared the pre-post intervention periods using logistic and Poisson regressions. RESULTS: Overall, we found no statistically significant effect of the intervention. However, independent analysis of the interview data found that only 6 of the 14 treatment facilities had continuously working PCTeams throughout the study period. Decedents in homes with working teams had significant reductions in the odds of in-hospital death compared to the other treatment [odds ratio (OR), 0.400; P<0.001), control (OR, 0.482; P<0.05), and nonrandomized control NHs (0.581; P<0.01). Decedents in these NHs had reduced rates of depressive symptoms (OR, 0.191; P≤0.01), but not pain or hospitalizations. CONCLUSIONS: The intervention was not equally effective for all outcomes and facilities. As homes vary in their ability to adopt new care practices, and in their capacity to sustain them, reforms to create the environment in which effective palliative care can become broadly implemented are needed.

Patients' perceptions of interactions with hospital staff are associated with hospital readmissions: a national survey of 4535 hospitals.

BACKGROUND: Reducing 30-day hospital readmissions has become a focus of the current national payment policies. Medicare requires that hospitals collect and report patients' experience with their care as a condition of payment. However, the extent to which patients' experience with hospital care is related to hospital readmission is unknown. METHODS: We established multivariate regression models in which 30-day risk-adjusted readmission rates were the dependent variables and patients' perceptions of the responsiveness of the hospital staff and communication (as measured by the Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS) scores) were the independent variables of interest. We selected six different clinical conditions for analyses, including acute myocardial infarction (AMI), chronic obstructive pulmonary disease (COPD), heart failure, hip/knee surgery, pneumonia, and stroke. Data included all acute care hospitals reporting in Hospital Compare in 2014. RESULTS: The number of hospitals with reported readmissions ranged from 2234 hospitals for AMI to 3758 hospitals for pneumonia. The average 30-day readmission rates ranged from 5.19% for knee/hip surgery to 22.7% for COPD. Patient experience of hospital-staff responsiveness as "top-box" ranged from 64% to 67% across the six clinical conditions, communication with nurses ranged from 77% to 79% and communication with doctors ranged from 80% to 81% (higher numbers are better). Our finding suggests that hospitals with better staff responsiveness were significantly more likely to have lower 30-day readmissions for all conditions. The effect size depended on the baseline readmission rates, with the largest effect on hospitals in the upper 75th quartile. A ten-percentage-point increase in staff responsiveness led to a 0.03-0.18 percentage point decrease in readmission rates. We found that neither communication with physicians nor communication with nurses was significantly associated with hospital readmissions. CONCLUSIONS: Our findings suggest that elements of care related to staff responsiveness during patients' stay may influence rehospitalization rates. Changes in staff responsiveness may offer an additional tool for hospitals to employ ongoing efforts to achieve reductions in readmissions, an important objective both financially and for patient health outcomes.

Examination of the New Short-Stay Nursing Home Quality Measures: Rehospitalizations, Emergency Department Visits, and Successful Returns to the Community.

In 2016, the Centers for Medicare & Medicaid Services (CMS) introduced 3 new quality measures (QMs) to its report card, Nursing Home Compare (NHC). These measures-rehospitalizations, emergency department visits, and successful discharges to the community-focus on short-stay residents. We offer a first analysis of nursing homes' performance in terms of these new measures. We examined their properties and distribution across nursing homes using descriptive statistics and regression models. We found that, similar to other QMs, performance varies across the country, and that there is very minimal correlation between these 3 new QMs as well as between these QMs and other NHC QMs. Regression models reveal that better performance on these QMs tends to be associated with fewer deficiencies, higher staffing and more skilled staffing, nonprofit ownership, and lower proportion of Medicaid residents. Other characteristics are associated with better performance for some but not all 3 QMs. We also found improvement in all 3 QMs in the second year of publication. This study contributes to the validity of these measures by demonstrating their relationship to these structural QMs. It also suggests that these QMs are important by demonstrating their large variation across the country, suggesting substantial room for improvement, and finding that nursing homes are already responding to the incentives created by publication of these QMs.

Assessing overall, technical, and scale efficiency among home health care agencies.

While home health care agencies (HHAs) play a vital role in the production of health, little research has been performed gauging their efficiency. Employing a robust approach to data envelopment analysis (DEA) we assessed overall, technical, and scale efficiency on a nationwide sample of HHAs. After deriving the three efficiency measures, we regressed these scores on a variety of environmental factors. We found that HHAs, on average, could proportionally reduce inputs by 28 % (overall efficiency), 23 % (technical efficiency) and 6 % (scale efficiency). For-profit ownership was positively associated with improvements in overall efficiency and technical efficiency and chain ownership was positively associated with global efficiency. There were also state-by-state variations on all the efficiency measures. As home health becomes an increasingly important player in the health care system, and its share of national health expenditures increases, it has become important to understand the cost structure of the industry and the potential for efficiencies. Therefore, further research is recommended as this sector continues to grow.

First-dollar cost-sharing for skilled nursing facility care in medicare advantage plans.

BACKGROUND: The initial days of a Medicare-covered skilled nursing facility (SNF) stay may have no cost-sharing or daily copayments depending on beneficiaries' enrollment in traditional Medicare or Medicare Advantage. Some policymakers have advocated imposing first-dollar cost-sharing to reduce post-acute expenditures. We examined the relationship between first-dollar cost-sharing for a SNF stay and use of inpatient and SNF services. METHODS: We identified seven Medicare Advantage plans that introduced daily SNF copayments of $25-$150 in 2009 or 2010. Copays began on the first day of a SNF admission. We matched these plans to seven matched control plans that did not introduce first-dollar cost-sharing. In a difference-in-differences analysis, we compared changes in SNF and inpatient utilization for the 172,958 members of intervention and control plans. RESULTS: In intervention plans the mean annual number of SNF days per 100 continuously enrolled inpatients decreased from 768.3 to 750.6 days when cost-sharing changes took effect. Control plans experienced a concurrent increase: 721.7 to 808.1 SNF days per 100 inpatients (adjusted difference-in-differences: -87.0 days [95% CI (-112.1,-61.9)]). In intervention plans, we observed no significant changes in the probability of any SNF service use or the number of inpatient days per hospitalized member relative to concurrent trends among control plans. CONCLUSIONS: Among several strategies Medicare Advantage plans can employ to moderate SNF use, first-dollar SNF cost-sharing may be one influential factor. TRIAL REGISTRATION: Not applicable.

Prototype End-of-Life Quality Measures Based on MDS 3 Data.

BACKGROUND: The Nursing Home Compare (NHC) report card does not include end-of-life (EOL) quality measures (QMs). OBJECTIVES: To develop and examine the properties of EOL QMs. SUBJECTS: A total of 39,590 nursing home decedents in 626 facilities in New York State in fiscal year 2012. DESIGN: Statistical analyses of Minimum Data Set 3 data, including multivariable regression analyses and descriptive statistics. MEASURES: Death in the hospital, number of hospitalizations, pain, and depression during the last 90 days before death. RESULTS: Overall, 32% of residents died in the hospital. They averaged 0.49 hospitalizations in the last 90 days before death, 10% reported moderate to severe pain, and 17% had depressive symptoms. The EOL QMs exhibited variation across facilities similar to that observed for other QMs. They showed low or moderate correlations. The pain and depression QMs were significantly better among nursing homes ranked by NHC as 4 and 5 stars compared with those ranked as 1 and 2 stars for most dimensions. The hospitalizations QMs were significantly better among nursing homes ranked by NHC as 4 and 5 stars compared with those ranked as 1 and 2 stars only when compared on the staffing dimension. CONCLUSIONS: The Minimum Data Set 3 includes much information that can be used to assess quality of EOL care in nursing homes. The prototype measures we developed could be improved if information about advance directives and the nonclinical aspects of care, such as comfort and emotional support for both the resident and the family and respect for resident and family preferences, were collected.

Health Care Use and Spending for Medicaid Enrollees in Federally Qualified Health Centers Versus Other Primary Care Settings.

OBJECTIVES: To compare health care use and spending of Medicaid enrollees seen at federally qualified health centers versus non-health center settings in a context of significant growth. METHODS: Using fee-for-service Medicaid claims from 13 states in 2009, we compared patients receiving the majority of their primary care in federally qualified health centers with propensity score-matched comparison groups receiving primary care in other settings. RESULTS: We found that health center patients had lower use and spending than did non-health center patients across all services, with 22% fewer visits and 33% lower spending on specialty care and 25% fewer admissions and 27% lower spending on inpatient care. Total spending was 24% lower for health center patients. CONCLUSIONS: Our analysis of 2009 Medicaid claims, which includes the largest sample of states and more recent data than do previous multistate claims studies, demonstrates that the health center program has provided a cost-efficient setting for primary care for Medicaid enrollees.

Does mandating nursing home participation in quality reporting make a difference? Evidence from Massachusetts.

BACKGROUND: Quality report cards have been shown to be effective in influencing patients' referrals and promoting quality improvement in some instances and not others. In this study, we investigate one of the mechanisms that may detract from their effectiveness: voluntary versus mandatory participation of nursing homes in public quality reporting. OBJECTIVES: To answer 2 questions: (1) Were the nursing homes choosing not to participate low-quality performers relative to those who chose to participate? (2) Once participation became mandatory, did those that did not voluntarily participate initially, improve more than those that participated voluntarily? RESEARCH DESIGN: Massachusetts published the Massachusetts Satisfaction Survey report card for nursing homes for the years 2005, 2007, and 2009. Nursing homes' participation was voluntary in 2005 and mandatory in 2007 and 2009. We performed a retrospective statistical analysis of the relationship between nursing homes' decision to participate in quality reporting and 12 quality outcomes: deficiency citations, staffing, and 8 survey domains. SUBJECTS: A total of 424 Massachusetts nursing homes. RESULTS: Sixty-seven percent of nursing homes participated in reporting voluntarily. Volunteer nursing homes had better quality for all measures (significant at the 0.05 level or trending toward significance at the 0.10 level for all but 2). Once reporting became mandatory, nonvolunteers improved more than volunteers in all but 2 staffing measures (trending toward significance at the 0.10 level in 5). CONCLUSIONS: Report cards are more effective if nursing homes' participation is mandated. Nonmandatory reporting systems, as those implemented by some states and professional associations, lead to missed opportunities for quality improvements.

Have Racial Disparities in Ambulatory Care Sensitive Admissions Abated Over Time?

BACKGROUND: Racial disparities in access to care and access to high-quality care have been persistent over many decades. They have been documented in all areas of health care, including ambulatory care. Policy initiatives have been implemented to address disparities and close the gaps in care that minorities face. Less is known about the effectiveness of these polices. OBJECTIVES: To evaluate whether disparities in quality of ambulatory care have abated during the decade of 2000 by answering 2 questions: (1) were there differences in ambulatory care sensitive hospital admissions rates by race?; (2) have these differences been declining over time? RESEARCH DESIGN: Multivariable linear regressions with fixed county effects and robust SEs of longitudinal panel data. SUBJECTS: A total of 4,032,322 discharges in 172 counties in 6 states during 2003-2009. MEASURES: Prevention Quality Indicators (PQIs) developed by the Agency for Healthcare Research and Quality, by county, and race calculated from the Healthcare Cost and Utilization Project dataset. RESULTS: In 2003 the overall PQI admission rates were higher for African Americans (around 16.5/1000) than for whites (around 15/1000). By 2009, the overall and the chronic PQI admission rates declined significantly (P<0.01) for whites. They either did not decline or increased for African Americans. Acute PQI rates declined significantly for whites and remained stable for African Americans. CONCLUSIONS: Policies addressing persisting racial disparities in quality of ambulatory care for African Americans should focus on the chronic PQIs. In addition, efforts should be made to improve data quality for race and ethnicity information on hospital discharge data to enable informed policy evaluation and planning.

The Impact of Medicaid Payer Status on Hospitalizations in Nursing Homes.

OBJECTIVES: To examine the association between payer status (Medicaid vs. private-pay) and the risk of hospitalizations among long-term stay nursing home (NH) residents who reside in the same facility. DATA AND STUDY POPULATION: The 2007-2010 National Medicare Claims and the Minimum Data Set were linked. We identified newly admitted NH residents who became long-stayers and then followed them for 180 days. ANALYSES: Three dichotomous outcomes-all-cause, discretionary, and nondiscretionary hospitalizations during the follow-up period-were defined. Linear probability model with facility fixed-effects and robust SEs were used to examine the within-facility difference in hospitalizations between Medicaid and private-pay residents. A set of sensitivity analyses were performed to examine the robustness of the findings. RESULTS: The prevalence of all-cause hospitalization during a 180-day follow-up period was 23.3% among Medicaid residents compared with 21.6% among private-pay residents. After accounting for individual characteristics and facility effects, the probability of any all-cause hospitalization was 1.8-percentage point (P<0.01) higher for Medicaid residents than for private-pay residents within the same facility. We also found that Medicaid residents were more likely to be hospitalized for discretionary conditions (5% increase in the likelihood of discretionary hospitalizations), but not for nondiscretionary conditions. The findings from the sensitivity analyses were consistent with the main analyses. CONCLUSIONS: We observed a higher hospitalization rate among Medicaid NH residents than private-pay residents. The difference is in part driven by the financial incentives NHs have to hospitalize Medicaid residents.