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.

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.

Dementia, nurse staffing, and health outcomes in nursing homes.

OBJECTIVE: To estimate and contrast the relationships between nurse staffing and health outcomes in nursing homes with low and high dementia census, to understand the association of staffing hours with dementia care quality. DATA SOURCES AND STUDY SETTING: A national sample of nursing homes during 2017-2019 (pre-COVID). Data included the Payroll-Based Journal, Medicare Claims, Nursing Home Care Compare, and Long-Term Care Focus. STUDY DESIGN: Retrospective, regression analyses. We estimated separate linear models predicting six long-term facility-level outcomes. Independent variables included staffing hours per resident-day (HPRD) interacted with the facility percentage of dementia residents, controlling for other resident and facility characteristics. DATA COLLECTION/EXTRACTION METHODS: Hospital-based nursing homes, those with fewer than 30% dementia residents, and missing data were excluded. PRINCIPAL FINDINGS: We found that registered nurses and certified nurse assistants HPRDs were likely to exhibit positive returns in terms of outcomes throughout most of the range of HPRD for both high and low-census dementia facilities, although, high- and low-dementia facilities differed in most outcome rates at all staffing levels. Average predicted antipsychotics and activities of daily living as functions of HPRD were worse in higher dementia facilities, independent movement, and hospitalizations did not differ significantly, and Emergency Rooms and pressure sores were worse in lower dementia facilities. Average marginal effects were not statistically different [CI included zero] between the high and low dementia facilities for any outcome. CONCLUSIONS: These findings suggest that increasing staffing will improve outcomes by similar increments in both low- and high-dementia facilities for all outcomes. However, at any given level of staffing, absolute differences in outcomes between low- and high-dementia facilities remain, suggesting that additional staffing alone will not suffice to close these gaps. Further studies are required to identify opportunities for improvement in performance for both low- and high-dementia census facilities.

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.

Dementia Care Is Widespread In US Nursing Homes; Facilities With The Most Dementia Patients May Offer Better Care.

More than three million US nursing home residents were diagnosed with Alzheimer's disease and related dementias (ADRD) between 2017 and 2019. This number is expected to increase as the population ages and ADRD prevalence increases. People with ADRD require specialized care from trained staff. This study addressed two questions: Are residents with ADRD concentrated in nursing homes where they are the majority? If not, what are the implications for their quality of care and life? We answered the first question by determining the ADRD census for each nursing home in the country during the period 2017-19. Using the Minimum Data Set and Medicare claims, we compared characteristics of nursing homes with high and low ADRD census along several dimensions, including staffing, resident outcomes, and resident characteristics. We found that residents with ADRD were dispersed throughout all nursing homes, with fewer than half residing in nursing homes where residents with ADRD accounted for 60-90 percent of the census. Furthermore, only facilities exceeding 90 percent of residents with ADRD seemed to offer better care. These findings raise concerns about the quality of care and life for the majority of residents with ADRD, suggesting that current National Institutes of Health dementia research initiatives and the Biden administration's policies to improve nursing home care should be coordinated.

Facilitators of and Barriers to Integrating Digital Mental Health Into County Mental Health Services: Qualitative Interview Analyses.

BACKGROUND: Digital mental health interventions (DMHIs) represent a promising solution to address the growing unmet mental health needs and increase access to care. Integrating DMHIs into clinical and community settings is challenging and complex. Frameworks that explore a wide range of factors, such as the Exploration, Preparation, Implementation, Sustainment (EPIS) framework, can be useful for examining multilevel factors related to DMHI implementation efforts. OBJECTIVE: This paper aimed to identify the barriers to, facilitators of, and best practice recommendations for implementing DMHIs across similar organizational settings, according to the EPIS domains of inner context, outer context, innovation factors, and bridging factors. METHODS: This study stems from a large state-funded project in which 6 county behavioral health departments in California explored the use of DMHIs as part of county mental health services. Our team conducted interviews with clinical staff, peer support specialists, county leaders, project leaders, and clinic leaders using a semistructured interview guide. The development of the semistructured interview guide was informed by expert input regarding relevant inner context, outer context, innovation factors, and bridging factors in the exploration, preparation, and implementation phases of the EPIS framework. We followed a recursive 6-step process to conduct qualitative analyses using inductive and deductive components guided by the EPIS framework. RESULTS: On the basis of 69 interviews, we identified 3 main themes that aligned with the EPIS framework: readiness of individuals, readiness of innovations, and readiness of organizations and systems. Individual-level readiness referred to the extent to which clients had the necessary technological tools (eg, smartphones) and knowledge (digital literacy) to support the DMHI. Innovation-level readiness pertained to the accessibility, usefulness, safety, and fit of the DMHI. Organization- and system-level readiness concerned the extent to which providers and leadership collectively held positive views about DMHIs as well as the extent to which infrastructure (eg, staffing and payment model) was appropriate. CONCLUSIONS: The successful implementation of DMHIs requires readiness at the individual, innovation, and organization and system levels. To improve individual-level readiness, we recommend equitable device distribution and digital literacy training. To improve innovation readiness, we recommend making DMHIs easier to use and introduce, clinically useful, and safe and adapting them to fit into the existing client needs and clinical workflow. To improve organization- and system-level readiness, we recommend supporting providers and local behavioral health departments with adequate technology and training and exploring potential system transformations (eg, integrated care model). Conceptualizing DMHIs as services allows the consideration of both the innovation characteristics of DMHIs (eg, efficacy, safety, and clinical usefulness) and the ecosystem around DMHIs, such as individual and organizational characteristics (inner context), purveyors and intermediaries (bridging factor), client characteristics (outer context), as well as the fit between the innovation and implementation settings (innovation factor).

New Dimensions of Staffing Patterns in Nursing Homes and Nursing Home Quality: Comparing Staffing Instability to Staffing Turnover.

OBJECTIVE: This study examines how measures of staffing-turnover and instability-are associated with one another and how they independently contribute to quality of care in nursing homes. DESIGN: Cross-sectional analysis of 2021-2022 administrative data. Data included the Payroll Based Journal for daily staffing information, merged with Nursing Home Care Compare (NHCC) data for nursing home characteristics, total staffing turnover, and nursing home quality. SETTING AND PARTICIPANTS: A total of 11,840 nursing homes nationally reporting data on daily staffing and staffing turnover. METHODS: We explored correlations between measures of staffing and estimated facility-level regression models with robust standard errors. The dependent variables were indicators of nursing home quality included in the NHCC 5-star ratings. The independent variables of interest were average total staffing hours per resident-day, total staffing turnover, and total staffing instability. RESULTS: For the 11,840 nursing homes in the study, there was a weak positive correlation between turnover and instability, with some overlap between nursing homes with high instability and high turnover. Regression analysis revealed that staffing instability and turnover contributed independently to nursing home quality, with instability having a stronger association with some measures of quality and turnover with others. Staffing instability was positively and more strongly associated with long-stay residents' decline in activities of daily living levels and receipt of antipsychotic drugs and short-stay residents' functioning at discharge. Turnover was positively and more strongly associated with long-stay residents' prevalence of pressure ulcers and worsening mobility, and short-stay residents' hospitalizations. CONCLUSION AND IMPLICATIONS: Instability and turnover in total nursing home staffing independently contribute to nursing home quality. This suggests that adding measures of staffing instability to the existing measures of average staffing and staff turnover in NHCC may enhance the report card's value for providers engaged in quality improvement and consumers searching for high-quality nursing homes.

Examining California nursing home profitability and related factors before and during the COVID-19 pandemic.

BACKGROUND: The financial status of nursing homes (NHs) is a policy concern, especially during a pandemic, because of the higher costs associated with infection prevention and resident care. METHODS: This exploratory study was designed to assess the impact of the federal and state COVID-19 funding support on California NHs profitability during 2020, the first year of the pandemic, compared with 2019, the last pre-pandemic year. The study examined the association of Medicare and Medicaid days, related-party transactions, as well as other facility characteristics on net income profit margins, using cross-sectional regression analysis of data from state NH cost reports and federal NH provider data for 2019 and 2020. RESULTS: California skilled NHs had average reported net income profit margins of 2.26% in 2019 and 7.0% in 2020 with wide variations (from a loss of about 48% to a gain of 74% in 2020). Regression analysis found that the number of beds, occupancy rates, high-quality rating scores, and medium and high proportions of Medicare resident days were positively associated with net income margins in 2019 and 2020. Chains in 2020 (but not 2019), related-party expenditures in 2019 and 2020, median Medicaid days (in 2019), high Medicaid resident days (71%-73% or higher) in 2019 and 2020, and medium and high managed care resident days were negatively associated with net income margins in both years. CONCLUSIONS: Although NH admissions and occupancy rates declined substantially between 2019 and 2020, some (but not all) California NHs had a substantial increase in profit margins in 2020 over 2019. More studies of nursing home financial patterns and profitability are needed to examine trends over time and variations across states.

Association of Staffing Instability With Quality of Nursing Home Care.

Importance: Recent work suggests that instability in nursing home staffing levels may be an important marker of nursing home quality. Whether that association holds when controlling for average staffing levels is unknown. Objective: To examine whether staffing instability, defined as the percentage of days below average staffing levels, is associated with nursing home quality when controlling for average staffing levels. Design, Setting, and Participants: This quality improvement study of 14 717 nursing homes used the merged Centers for Medicare & Medicaid Services Payroll Based Journal, Minimum Data Set, Nursing Home Care Compare, and Long-Term-Care Focus data for fiscal years 2017 to 2019. Statistical analysis was performed from February 8 to November 14, 2022. Main Outcomes and Measures: Linear, random-effect models with state fixed effects and robust SEs were estimated for 12 quality indicators as dependent variables, percentage of below-average staffing days as independent variables, controlling for average staffing hours per resident-day for registered nurses, licensed practical nurses, and certified nurse aides. Below-average staffing days were defined as those 20% below the facility average, by staffing type. Quality indicators included deficiency citations; long-stay residents receiving an antipsychotic; percentage of high-risk long-stay residents with pressure ulcers (2 different measures for pressure ulcers were used); and percentage of long-stay residents with activities of daily living decline, mobility decline, emergency department visits, and hospitalizations; and short-stay residents with new antipsychotic medication, mobility decline, emergency department visits, and rehospitalizations. Results: For the 14 717 nursing homes in this study, the mean (SD) percentage of days with below-average staffing was 30.2% (12.0%) for registered nurses, 16.4% (11.3%) for licensed practical nurses, and 5.1% (5.3%) for certified nurse aides. Mean (SD) staffing hours per resident-day were 0.44 (0.40) for registered nurses, 0.80 (0.32) for licensed practical nurses, and 2.20 (0.50) for certified nurse aides. In regression models that included average staffing, a higher percentage of below-average staffing days was significantly associated with worse quality for licensed practical nurses in 10 of 12 models, with the largest association for decline of activities of daily living among long-stay residents (regression coefficient, 0.020; P < .001). A higher percentage of below-average staffing days was significantly associated with worse quality for certified nurse aides in 9 of 12 models, with the largest association for short-stay functioning (regression coefficient, 0.030; P = .01). Conclusions and Relevance: This study suggests that holding average staffing levels constant, day-to-day staffing stability, especially avoiding days with low staffing of licensed practical nurses and certified nurse aides, is a marker of better quality of nursing homes. Future research should investigate the causes and potential solutions for instability in staffing in all facilities, including those that may appear well-staffed on average.

Understanding the Role of Support in Digital Mental Health Programs With Older Adults: Users' Perspective and Mixed Methods Study.

BACKGROUND: Digital mental health interventions have the potential to increase mental health support among isolated older adults. However, the older adult population can experience several barriers to accessing and using digital health resources and may need extra support to experience its benefits. OBJECTIVE: This paper aimed to understand what older adults experience as an important aspect of support during engagement in a digital mental health program. The program entailed 3 months of staff support to participate in digital literacy training and engage with the digital mental health platform myStrength, which offers support for a range of mental health challenges, including depression and anxiety. METHODS: A total of 30 older adults participated in surveys and interviews to assess their experience of participating in a digital mental health program provided by county mental health services. As part of the program, participants attended 4 classes of digital literacy training, had access to the digital mental health platform myStrength for 2 months with staff support (and 10 months after the program without support), and received support from program staff during the entire 3-month program. Survey data were analyzed using descriptive statistics, and interview data were analyzed using thematic analysis. RESULTS: A thematic analysis of the interview data revealed that participants valued ongoing support in 3 main areas: technical support to assist them in using technology, guided support to remind them to use myStrength and practice skills they had learned, and social support to enable them to connect with others through the program. Furthermore, participants reported that social connections was the most important aspect of the program and that they were mainly motivated to participate in the program because it was recommended to them by trusted others such as a community partner or because they believed it could potentially help others. CONCLUSIONS: Our findings can be used to inform the design of future digital mental health programs for older adults who may have unique support needs in terms of dedicated technical support and ongoing guided support to use technology and social support to increase social connectedness.

Associations Between Daily Nurse Staffing Levels and Daily Hospitalizations and ED Visits in Nursing Homes.

OBJECTIVES: Although many prior studies have shown that high average levels of nurse staffing in nursing homes are associated with fewer hospitalizations, some studies have not, suggesting that the average nursing level may mask a more complex relationship. This study examines this issue by investigating the associations of daily staffing patterns and daily hospitalizations and emergency department (ED) visits. DESIGN: Retrospective analyses of national Payroll Based Journal (PBJ) staffing data merged with the Minimum Data Set. SETTING AND PARTICIPANTS: A total of 15,718 nursing homes nationally reporting PBJ data during 2017-2019, their staff, and residents. METHODS: We estimated facility-day-level models as conditional facility fixed-effect Poisson regressions with robust standard errors. The dependent variables were daily numbers of hospitalization and ED visits and the independent variables of interest were the number of registered nurse (RN), licensed practical nurse (LPN), and certified nurse assistant (CNA) hours on the same and prior days. RESULTS: The daily number of hospital transfers averaged 0.28 (SD 0.21). Daily total direct-care staffing hours averaged 288.7 (SD 188.2), with RNs accounting for 35.0, LPNs for 68.7, and CNAs for 185.0. Higher staffing was associated with more hospitalizations on the concurrent day. Higher staffing on the day prior was associated with fewer hospitalizations. The effect size was larger for RNs and LPNs (same day = ∼2%; prior day = approximately -0.7% to -0.9%) than for CNAs (same day <1%; prior day < -0.5%). ED visits not leading to hospitalizations, and analyses for subsamples exhibited similar findings. CONCLUSIONS AND IMPLICATIONS: Our findings suggest that staff can address developing problems and prevent admissions the next day and identify emergent problems and hospitalize the same day. They also underscore the complex array of nursing home factors involved in hospitalization and ED visits, including the influence of daily staffing variation, suggesting the need for further research to better understand the associations between staffing and appropriate resident transfers to the hospital or the ED, and the potential implications for quality metrics in these domains.

Hospitals serving nursing home residents disproportionately penalized under hospital readmissions reduction program.

BACKGROUND: Risk factors common to nursing home (NH) residents are potentially not fully captured by the Hospital Readmissions Reduction Program (HRRP). The unique challenges faced by hospitals that disproportionately serve NH residents who are at greater risk of readmissions have not been studied. METHODS: Using 100% Medicare Provider Analysis and Review File and the Minimum Data Set from 2010-2013, we constructed a measure of hospital share of NH-originating hospitalizations (NOHs). We defined hospital share of NOHs as the proportion of inpatient stays by patients aged 65 or older who were directly admitted from NHs. To evaluate the impact of the share of NOHs on readmission penalties, we categorized hospitals into quartiles according to their share of NOHs and estimated the differences in the adjusted penalties across hospital quartiles after accounting for hospital characteristics, market characteristics and state fixed effects. We repeated the analyses for the penalties incurred in each year between 2015 and 2019. RESULTS: Hospitals varied substantially in the share of NOHs (median [interquartile range], 11.3% [8.2%-15.1%]), with limited variation over time. In 2015, hospitals in the highest quartile of NOH received on average 0.58% Medicare payment reduction compared to 0.44% reduction among those in the lowest quartile (32.9% higher penalties, p < 0.001). The increase in penalties continued to grow in 2017 and 2018 when the HRRP expanded to include additional target conditions (47.3% and 66.7%, respectively, p < 0.001 for both). Although the effect diminished in 2019 following the additional adjustment for hospital's dual-eligible share, hospitals in the highest quartile of NOH still incurred 43.0% (p < 0.001) higher penalties than those in the lowest quartile. CONCLUSIONS: Hospitals varied considerably in their share of NOHs. Hospitals having a higher share of NOHs were disproportionately penalized for excess readmissions, even under the revised policy that adjusts for the share of dual-eligible admissions.

Understanding the Potential of Mental Health Apps to Address Mental Health Needs of the Deaf and Hard of Hearing Community: Mixed Methods Study.

BACKGROUND: Mental health concerns are a significant issue among the deaf and hard of hearing (D/HH) community, but community members can face several unique challenges to accessing appropriate resources. OBJECTIVE: The aim of this study was to investigate the mental health needs of the D/HH community and how mental health apps may be able to support these needs. METHODS: A total of 10 members of the D/HH community participated in a focus group and survey to provide their perspectives and experiences. Participants were members of the Center on Deafness Inland Empire team, which comprises people with lived experience as members of and advocates for the D/HH community. RESULTS: Findings identified a spectrum of needs for mental health apps, including offering American Sign Language and English support, increased education of mental health to reduce stigma around mental health, direct communication with a Deaf worker, and apps that are accessible to a range of community members in terms of culture, resources required, and location. CONCLUSIONS: These findings can inform the development of digital mental health resources and outreach strategies that are appropriate for the D/HH community.

Daily Variation in Nursing Home Staffing and Its Association With Quality Measures.

Importance: Average staffing measures are a focus of nursing homes' quality assessments and reporting. They may, however, mask daily variation in staffing, additional information that could be important for understanding nursing home quality and relative ranking. Objective: To examine daily variation in staffing, its association with quality, and whether daily variation provides information regarding quality ranking of nursing homes over and above the information provided by average staffing levels. Design, Setting, and Participants: This quality improvement study included registered nurses (RNs) and certified nurse aide (CNAs) at 13 339 certified nursing homes throughout the United States during 2017 to 2018. Retrospective analyses of the Payroll-Based Journal, Medicare Cost Reports, and Nursing Home Care Compare were conducted. Data were analyzed from January 2017 to December 2018. Main Outcomes and Measures: Three measures of daily variation, ie, coefficient of variation (COV), total outlier days (TOD), and low outlier days (LOD), were calculated for RNs and CNAs. The association between these measures and quality rankings and other facility characteristics were evaluated. Results: A total of 13 339 nursing homes were included in this study, with 9476 (71%) for-profit facilities. The mean (SD) hours-per-resident-day were 0.41 (0.29) for RNs and 2.16 (0.49) for CNAs, and a mean (SD) 55% (26%) of residents were Medicaid beneficiaries. Outcome measures were as follows: mean (SD) COV, 0.5 (0.6) for RNs and 0.1 (0.1) for CNAs; mean (SD) TOD, 220 (69) for RNs and 44 (45) for CNAs; and mean (SD) LOD, 116 (45) for RNs and 22 (24) for CNAs. All 3 variation measures, for both RNs and CNAs, were significantly associated with both the 5-Star Quality Measures (COV among RNs, -0.014 [95% CI, -0.021 to -0.007]; P < .001; COV among CNAs: -0.004 [95% CI, -0.006 to -0.003]; P < .001; TOD among RNs, -3.79 [95% CI, -4.59 to -2.99]; P < .001; TOD among CNAs, -2.52 [95% CI, -3.08 to -1.96]; P < .001; LOD among RNs, -2.46 [95% CI, -3.03 to -1.88]; P < .001; LOD among CNAs, -1.29 [95% CI, -1.58 to -0.99]; P < .001) and the 5-Star Survey rankings (COV among RNs,-0.026 [95% CI, -0.033 to -0.019]; P < .001; COV among CNAs: -0.006 [95% CI, -0.007 to -0.004]; P < .001; TOD among RNs, -5.10 [95% CI, -5.97 to -4.23]; P < .001; TOD among CNAs, -4.16 [95% CI, -4.77 to -3.55]; P < .001; LOD among RNs, -3.04 [95% CI, -3.65 to -2.44]; P < .001; LOD among CNAs, -1.97 [95% CI, -2.29 to -1.65]; P < .001) published in Nursing Home Care Compare. Low κ values, ranging from 0.23 to 0.63, indicated that the variation measures add information about ranking to the information provided by average staffing measure. Conclusions and Relevance: These findings highlight the importance of reporting daily variation in staffing to improve understanding of the relationship between staffing and quality. They suggest that 2 facilities with the same average staffing achieve different quality of resident care and survey ratings in association with on the day-to-day variation in staffing. Measures of daily staffing may enhance the value of Nursing Home Care Compare for nursing homes and others engaged in quality improvement and consumers searching for high quality nursing homes.

Home Health Care Quality, Its Costs and Implications for Home Health Value-Based Purchasing.

The Home Health Value-based Purchasing (HHVBP) demonstration, incorporating a payment formula designed to incentivize both high-quality care and quality improvement, is expected to become a national program after 2022, when the demonstration ends. This study investigated the relationship between costs and several quality dimensions, to inform HHVBP policy. Using Medicare cost reports, OASIS and Home Health Compare data for 7,673 home health agencies nationally, we estimated cost functions with instrumental variables for quality. The estimated net marginal costs varied by composite quality measure, baseline quality, and agency size. For four of the five composite quality measures, the net marginal cost was negative for low-quality agencies, suggesting that quality improvement was cost saving for this agency type. As the magnitude of the net marginal cost is commensurate with the payment incentive planned for HHVBP, it should be considered when designing the incentives for HHVBP, to maximize their effectiveness.

Who Visits Relatives in Nursing Homes? Predictors of at Least Weekly Visiting.

OBJECTIVES: Within the context of a single study, assess the relative importance of the 6 factors identified in a 2019 systematic review as associated with the likelihood that family members will visit nursing home residents. DESIGN: Retrospective statistical analysis of an existing survey data set. SETTINGS AND PARTICIPANTS: A national survey conducted with 4350 relatives of long-term nursing home residents. METHODS: Probit models of the probability of visiting a family member at least once weekly, stratified by age of the visitor, were estimated. To account for possible endogeneity of respondent involvement in the choice of nursing home and visit rate, visit rates were estimated using 2-stage residual inclusion in which the first stage explained involvement in nursing home choice. RESULTS: Involvement in nursing home choice has a substantively and statistically significant positive effect on visit probability for all age groups of respondents. Travel time has a substantively and statistically significant negative association on visit probability for all age groups. Younger women are more likely to visit than younger men. For all but the oldest respondents, higher income and full-time employment contribute to involvement in nursing home choice as does being Black or Hispanic. CONCLUSIONS AND IMPLICATIONS: As in previous research, travel time is an important determinant of visit rates. The strong association of involvement in nursing home choice with visit probability suggests a strong psychological motivation for visiting. To improve visiting, future research should focus on better understanding of the psychological factors that are associated with it and rely on better data and improved statistical methods. Our findings also suggest that nursing home administrators should consider adopting initiatives to facilitate and empower family members' involvement in nursing home choice, which in turn may lead to increased visitations.

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.

Curating the Digital Mental Health Landscape With a Guide to Behavioral Health Apps: A County-Driven Resource.

With more than 10,000 mental health apps available, consumers and clinicians who want to adopt such tools can be overwhelmed by the multitude of options and lack of clear evaluative standards. Despite the increasing prevalence of curated lists, or app guides, challenges remain. Organizations providing mental health services to consumers have an opportunity to address these challenges by producing guides that meet relevant standards of quality and are tailored to local needs. This column summarizes an example of the collaborative process of app guide development in a publicly funded mental health service context and highlights opportunities and barriers identified through the process.

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.