Recent tapering from long-term opioid therapy and odds of opioid-related hospital use.

PURPOSE: The number of patients tapered from long-term opioid therapy (LTOT) has increased in recent years in the United States. Some patients tapered from LTOT report improved quality of life, while others face increased risks of opioid-related hospital use. Research has not yet established how the risk of opioid-related hospital use changes across LTOT dose and subsequent tapering. Our objective was to examine associations between recent tapering from LTOT with odds of opioid-related hospital use. METHODS: Case-crossover design using 2014-2018 health information exchange data from Indiana. We defined opioid-related hospital use as hospitalizations, and emergency department (ED) visits for a drug overdose, opioid abuse, and dependence. We defined tapering as a 15% or greater dose reduction following at least 3 months of continuous opioid therapy of 50 morphine milligram equivalents (MME)/day or more. We used conditional logistic regression to estimate odds ratios (OR) with 95% confidence intervals (CI). RESULTS: Recent tapering from LTOT was associated with increased odds of opioid-related hospital use (OR: 1.50, 95%CI: 1.34-1.63), ED visit (OR: 1.52; 95%CI: 1.35-1.72), and inpatient hospitalization (OR: 1.40; 95%CI: 1.20-1.65). We found no evidence of heterogeneity of the effect of tapering on opioid-related hospital use by gender, age, and race. Recent tapering among patients on a high baseline dose (>300 MME) was associated with increased odds of opioid-related hospital use (OR: 2.95, 95% CI: 2.12-4.11, p < 0.001) compared to patients on a lower baseline doses. CONCLUSIONS: Recent tapering from LTOT is associated with increased odds of opioid-related hospital use.

Unmet mental health need and subsequent substance use in individuals with a history of depression: Are there differences between metro and nonmetro areas?

BACKGROUND AND OBJECTIVES: More than nine million U.S. adults have a co-occurring mental health and substance use disorder. The self-medication hypothesis suggests that individuals with unmet need may alleviate the symptoms of their mental illness by using alcohol or drugs. We examine the relationship between unmet mental health need and subsequent substance use among individuals with a history of depression as well as differences in metro and nonmetro areas. METHODS: We used repeated cross-sectional data from the National Survey on Drug Use and Health (NSDUH), 2015-2018 after identifying individuals with depression in the past year (n = 12,211). We used logistic regressions with interaction terms to examine the association between unmet need for mental health care and substance use by geographic location. RESULTS: Unmet mental health need was associated with increased use of marijuana (odds ratio [OR] = 1.32, 95% confidence interval [CI]: 1.08-1.64), illicit drugs (OR = 1.75, 95% CI: 1.19-2.58), and prescription drugs (OR = 1.89, 95% CI: 1.19-3.00) among individuals with depression, which did not vary by geographic location. Unmet need was not associated with increased heavy alcohol drinking (OR = 0.87, 95% CI: 0.60-1.26). DISCUSSION AND CONCLUSIONS: No differences in substance usage between metro and nonmetro populations were observed for those with an unmet need for mental health care. We found support for the self-medication hypothesis among individuals with depression with respect to alcohol. SCIENTIFIC SIGNIFICANCE: We examine whether individuals with depression and unmet care needs are more likely to self-medicate with substances including prescription drugs. Due to higher unmeet needs in nonmetro areas, we examine whether the likelihood of self-medication differs in metro and nonmetro areas.

Pain and Associated Factors in Nursing Home Residents.

BACKGROUND: Understanding factors associated with risk of pain allows residents and clinicians to plan care and set priorities, however, factors associated with pain in nursing home residents has not been conclusively studied. AIM: To evaluate the association between pain and nursing home (NH) resident demographic and clinical characteristics. DESIGN: Retrospective analysis of Minimum Data Set 3.0 records of nursing home residents residing in 44 Indiana NHs between September 27, 2011 and December 27, 2019 (N = 9,060). RESULTS: Pain prevalence in this sample of NH residents was 23.7%. Of those with pain, 28.0% experienced moderate to severe/frequent pain and 54.6% experienced persistent pain. Risk factors for moderate to severe/frequent pain include female sex; living in a rural setting; intact, mildly, or moderately impaired cognition; arthritis; contracture; anxiety; and depression. In contrast, stroke and Alzheimer's disease and Alzheimer's-disease related dementias (AD/ADRD) were associated with decreased risk of reporting moderate to severe/frequent pain, likely representing both the under-assessment and under-reporting of pain among cognitively impaired NH residents. Risk factors for persistent pain included age <70, Black race, living in a rural location, intact cognition, contracture, and depression. CONCLUSIONS: Pain remains a pressing problem for NH residents. In this study, we identified demographic and clinical factors associated with moderate to severe frequent pain and persistent pain. Residents with a diagnosis of AD/ADRD were less likely to report pain, likely representing the difficulty of evaluating pain in these residents. It is important to note that those with cognitive impairment may not experience any less pain, but assessment and reporting difficulties may make them appear to have less pain. Knowledge of factors associated with pain for NH residents has the potential for improving the ability to predict, prevent, and provide better pain care in NH residents.

Characteristics and outcomes associated with two asthma quality of care measures.

OBJECTIVE: We investigated asthma quality measures to understand patient characteristics associated with non-attainment of quality care and measure the association with asthma-related emergency department (ED) visits or inpatient hospitalizations (IPs). METHODS: Using administrative data from ALL Kids, Alabama's Children's Health Insurance Program, from 2013 to 2019 we calculated non-attainment of the Medication Management for Asthma (MMA) and Asthma Medication Ratio (AMR) quality measures. Patient characteristics and asthma-related ED visits and IPs associated with non-attainment of the MMA and AMR measures were assessed using logit regression models and Marginal effects at the mean. RESULTS: Among 2528 children with asthma, 53.2% failed to attain the MMA measure and 8.5% the AMR measure. Prior asthma-related ED visits or IP stays increased likelihood of non-attainment by 14.8 percentage points (95% CI 8.6-20.9) for MMA and 7.3 percentage points (95% CI 2.8-11.8) for AMR. Among 868 children (34.3%) with three years of continuous enrollment, AMR non-attainment was associated with a 6.1 percentage point increase in ED or IP utilization (95% CI 1.3-10.9), however MMA non-attainment was not associated with either outcome. Prior ED visit/IP stay was associated with a 17.2 percentage point (95% CI 8.3-26.1) increase in the likelihood of a subsequent ED visit/IP stay among those with non-attainment MMA and a 15.5 percentage point increase (95% CI 6.9-24.2) for non-attainment AMR. CONCLUSIONS: Patient characteristics associated with non-attainment of asthma quality measures presents actionable evidence to guide improvement efforts as non-attainment AMR increases the risk of subsequent ED visits and IP stays.

Age-specific rates of hospital transfers in long-stay nursing home residents.

INTRODUCTION: hospital transfers and admissions are critical events in the care of nursing home residents. We sought to determine hospital transfer rates at different ages. METHODS: a cohort of 1,187 long-stay nursing home residents who had participated in a Centers for Medicare and Medicaid demonstration project. We analysed the number of hospital transfers of the study participants recorded by the Minimum Data Set. Using a modern regression technique, we depicted the annual rate of hospital transfers as a smooth function of age. RESULTS: transfer rates declined with age in a nonlinear fashion. Rates were the highest among residents younger than 60 years of age (1.30-2.15 transfers per year), relatively stable between 60 and 80 (1.17-1.30 transfers per year) and lower in those older than 80 (0.77-1.17 transfers per year). Factors associated with increased risk of transfers included prior diagnoses of hip fracture (annual incidence rate ratio or IRR: 2.057, 95% confidence interval (CI): [1.240, 3.412]), dialysis (IRR: 1.717, 95% CI: [1.313, 2.246]), urinary tract infection (IRR: 1.755, 95% CI: [1.361, 2.264]), pneumonia (IRR: 1.501, 95% CI: [1.072, 2.104]), daily pain (IRR: 1.297, 95% CI: [1.055,1.594]), anaemia (IRR: 1.229, 95% CI [1.068, 1.414]) and chronic obstructive pulmonary disease (IRR: 1.168, 95% CI: [1.010,1.352]). Transfer rates were lower in residents who had orders reflecting preferences for comfort care (IRR: 0.79, 95% CI: [0.665, 0.936]). DISCUSSION: younger nursing home residents may require specialised interventions to reduce hospital transfers; declining transfer rates with the oldest age groups may reflect preferences for comfort-focused care.

Measuring rurality in health services research: a scoping review.

PURPOSE: This study is a scoping review of the different methods used to measure rurality in the health services research (HSR) literature. METHODS: We identified peer-reviewed empirical studies from 2010-2020 from seven leading HSR journals, including the Journal of Rural Health, that used any definition to measure rurality as a part of their analysis. From each study, we identified the geographic unit (e.g., county, zip code) and definition (e.g., Rural Urban Continuum Codes, Rural Urban Commuting Areas) used to classify categories of rurality. We analyzed whether geographic units and definitions used to classify rurality differed by focus area of studies, including costs, quality, and access to care. Lastly, we examined the number of rural categories used by authors to assess rural areas. FINDINGS: In 103 included studies, five different geographic units and 11 definitions were used to measure rurality. The most common geographic units used to measure rurality were county (n = 59, 57%), which was used most frequently in studies examining cost (n = 12, 75%) and access (n = 33, 57.9%). Rural Urban Commuting Area codes were the most common definition used to measure rurality for studies examining access (n = 13, 22.8%) and quality (n = 10, 44%). The majority of included studies made rural versus urban comparisons (n = 82, 80%) as opposed to focusing on rural populations only (n = 21, 20%). Among studies that compared rural and urban populations, most studies used only one category to identify rural locations (n = 49 of 82 studies, 60%). CONCLUSION: Geographic units and definitions to determine rurality were used inconsistently within and across studies with an HSR focus. This finding may affect how health disparities by rural location are determined and thus how resources and federal funds are allocated. Future research should focus on developing a standardized system to determine under what circumstances researchers should use different geographic units and methods to determine rurality by HSR focus area.

Institutional factors associated with hospital partnerships for population health: A pooled cross-sectional analysis.

BACKGROUND: Hospitals are increasingly engaging in partnerships to address population health in response to national policies, such as value-based payment models. However, little is known about how institutional factors influence hospital partnerships for population health. PURPOSE: Guided by institutional theory, we examine the association between institutional pressures (coercive, normative, and mimetic isomorphism) and hospital partnerships for population health. METHODOLOGY: A pooled cross-sectional analysis used an unbalanced panel of 10,777 hospital-year observations representing respondents to a supplemental question of the American Hospital Association's annual survey (2015-2017). The analysis included descriptive and bivariate statistics, and regression models that adjusted for repeated observations to examine the relationship between key independent variables and partnerships over time. FINDINGS: In regression analyses, we found the most support for measures of coercive (e.g., regulatory factors) isomorphism, with nonprofit status, participation in accountable care organizations, and acceptance of bundled payments, all being consistently and significantly associated with partnerships across all organization types. Modest increases were observed from 2015 to 2017 for hospital partnerships with public health organizations (+2.8% points, p < .001), governmental organizations (+2.0% points, p = .009), schools (+4.1% points, p < .001), and businesses (+2.2% points, p = .007). PRACTICE IMPLICATIONS: Our results suggest that institutional factors, particularly those related to regulatory policies and programs, may influence hospital partnerships to support population health. Findings from this study can assist hospital leaders in assessing the factors that can support or impede the creation of partnerships to support their population health efforts.

Assessing Variation in State Opioid Tapering Laws: Comparing State Laws with the CDC Guideline.

OBJECTIVE: In 2016, the Center for Disease Control and Prevention released an opioid prescribing guideline for primary care in response to opioid overdose deaths. Despite efforts to encourage safer prescribing practices, experts and federal agencies suspect prescribing guidelines may be misapplied in clinical practice, resulting in abrupt tapering from opioid therapy. Although state laws likely influence prescriber behavior, little is known about state tapering laws. Thus, we examined the scope and variation of state tapering laws compared with federal opioid guidelines. METHODS: We conducted a comprehensive review of state laws through December 31, 2019, using keyword searches in LexisNexus. Identified laws were coded based on the inclusion of attributes derived from federal opioid guidelines and an expert consensus panel report. We examined whether law attributes were associated with state characteristics, including region, population, governor's political affiliation, opioid prescribing rates, and opioid overdose rates. RESULTS: We found 27 states and one federal district had law(s) mentioning tapering. Most laws were authored by medical boards or workers' compensation groups (65.6%) while some laws included a penalty (32.8%). Approximately half of guideline attributes (54.2%) were included in state laws; however, only two state's laws cautioned against abrupt tapering. States with higher overdose death rates were more likely to enact a tapering law (P < 0.001) and have a penalty (P = 0.007). CONCLUSIONS: State tapering laws incorporate some federal guideline attributes but most lack attributes deemed critical by experts. Without clear instruction, patients risk inappropriate tapering and discontinuation of opioid therapy. Given these findings, policymakers should consider addressing this gap.

Facility and resident characteristics associated with variation in nursing home transfers: evidence from the OPTIMISTIC demonstration project.

BACKGROUND: Centers for Medicare and Medicaid Services (CMS) funded demonstration project to evaluate financial incentives for nursing facilities providing care for 6 clinical conditions to reduce potentially avoidable hospitalizations (PAHs). The Optimizing Patient Transfers, Impacting Medical Quality, and Improving Symptoms: Transforming Institutional Care (OPTIMISTIC) site tested payment incentives alone and in combination with the successful nurse-led OPTIMISTIC clinical model. Our objective was to identify facility and resident characteristics associated with transfers, including financial incentives with or without the clinical model. METHODS: This was a longitudinal analysis from April 2017 to June 2018 of transfers among nursing home residents in 40 nursing facilities, 17 had the full clinical + payment model (1726 residents) and 23 had payment only model (2142 residents). Using CMS claims data, the Minimum Data Set, and Nursing Home Compare, multilevel logit models estimated the likelihood of all-cause transfers and PAHs (based on CMS claims data and ICD-codes) associated with facility and resident characteristics. RESULTS: The clinical + payment model was associated with 4.1 percentage points (pps) lower risk of all-cause transfers (95% confidence interval [CI] - 6.2 to - 2.1). Characteristics associated with lower PAH risk included residents aged 95+ years (- 2.4 pps; 95% CI - 3.8 to - 1.1), Medicare-Medicaid dual-eligibility (- 2.5 pps; 95% CI - 3.3 to - 1.7), advanced and moderate cognitive impairment (- 3.3 pps; 95% CI - 4.4 to - 2.1; - 1.2 pps; 95% CI - 2.2 to - 0.2). Changes in Health, End-stage disease and Symptoms and Signs (CHESS) score above most stable (CHESS score 4) increased the risk of PAH by 7.3 pps (95% CI 1.5 to 13.1). CONCLUSIONS: Multiple resident and facility characteristics are associated with transfers. Facilities with the clinical + payment model demonstrated lower risk of all-cause transfers compared to those with payment only, but not for PAHs.

Hospital Partnerships for Population Health: A Systematic Review of the Literature.

EXECUTIVE SUMMARY: The U.S. healthcare system continues to experience high costs and suboptimal health outcomes that are largely influenced by social determinants of health. National policies such as the Affordable Care Act and value-based payment reforms incentivize healthcare systems to engage in strategies to improve population health. Healthcare systems are increasingly expanding or developing new partnerships with community-based organizations to support these efforts. We conducted a systematic review of peer-reviewed literature in the United States to identify examples of hospital-community partnerships; the main purposes or goals of partnerships; study designs used to assess partnerships; and potential outcomes (e.g., process- or health-related) associated with partnerships. Using robust keyword searches and a thorough reference review, we identified 37 articles published between January 2008 and December 2019 for inclusion. Most studies employed descriptive study designs (n = 21); health needs assessments were the most common partnership focus (n = 15); and community/social service (n = 21) and public health organizations (n = 15) were the most common partner types. Qualitative findings suggest hospital-community partnerships hold promise for breaking down silos, improving communication across sectors, and ensuring appropriate interventions for specific populations. Few studies in this review reported quantitative findings. In those that did, results were mixed, with the strongest support for improvements in measures of hospitalizations. This review provides an initial synthesis of hospital partnerships to address population health and presents valuable insights to hospital administrators, particularly those leading population health efforts.

Examination of nursing home financial distress via Porter's five competitive forces framework.

BACKGROUND: Nursing homes face increased risk of closure because of poor financial performance. PURPOSE: Using resource dependency theory, Porter's Five Forces of Competition framework, and Altman's Z -score model, this study examines the relationship between market factors and nursing home financial distress. METHODOLOGY/APPROACH: This study utilizes Medicare Cost Reports, LTCFocus, Certification and Survey Provider Enhanced Reporting, Online Survey Certification and Reporting, and the Area Health Resource File to examine an average of 10,454 nursing homes per year from 2000 to 2015. Using Porter's framework, market factors were conceptualized as the bargaining power of buyers and suppliers, threat of substitutes and new entrants, and industry rivalry. Organizational control variables include occupancy, payer mix, size, and chain affiliation. Data were analyzed using multinomial logistic regression with robust clustering, year, and state fixed effects. RESULTS: Distressed nursing homes (Relative Risk Ratios [RRR] = 0.991) were less likely to be in counties with higher Medicaid concentration. Distressed (RRR = 0.717) and at-risk-of-distress nursing homes (RRR = 0.807) were less likely to be in markets with home health agencies, and nursing homes at risk of distress (RRR = 1.005) were more likely to be in markets with a higher number of hospital-based skilled nursing facility beds compared to healthy organizations. The organizational-level variables, occupancy, payer mix, size, and chain affiliation had a significant impact on nursing home financial distress. CONCLUSIONS: The effects of external market forces on nursing home financial distress were limited; however, organizational-level variables had a significant impact on nursing home financial distress. PRACTICAL IMPLICATIONS: Study findings can inform policy makers on specific factors associated with nursing home financial distress and provide greater insight as it relates to designing new policies and interventions.

Decreasing deceased donor transplant rates among children (≤6 years) under the new kidney allocation system.

The Kidney Allocation System (KAS) was implemented in December 2014 with unknown impact on the pediatric waitlist. To understand the effect of KAS on pediatric registrants, deceased donor kidney transplant (DDKT) rate was assessed using interrupted time series analysis and time-to-event analysis. Two allocation eras were defined with an intermediary washout period: Era 1 (01/01/2013-09/01/2014), Era 2 (09/01/2014-03/01/2015), and Era 3(03/01/2015-03/01/2017). When using Cox proportional hazards, there was no significant association between allocation era and DDKT likelihood as compared to Era 1 (Era 3: aHR: 1.07, 95% CI: 0.97-1.18, P = .17). However, this was not consistent across all subgroups. Specifically, while highly sensitized pediatric registrants were consistently less likely to be transplanted than their less sensitized counterparts, this disparity was attenuated in Era 3 (Era 1 aHR: 0.04, 95%CI: 0.01-0.14, P < .001; Era 3 aHR: 0.33, 95% CI: 0.21-0.53, P < .001) whereas the youngest registrants aged 0-6 experienced a 21% decrease in DDKT likelihood in Era 3 as compared to Era 1 (aHR: 0.79, 95% CI: 0.64-0.98, P = .03). Thus, while overall DDKT likelihood remained stable with the introduction of KAS, registrants ≤ 6 years of age were disadvantaged, warranting further study to ensure equitable access to transplantation.

Nursing Home Chain Affiliation and Its Impact on Specialty Service Designation for Alzheimer Disease.

Specialty care units (SCUs) in nursing homes (NHs) grew in popularity during the 1990s to attract residents while national policies and treatment paradigms changed. Alzheimer disease has consistently been the dominant form of SCU. This study explored the extent to which chain affiliation, which is common among NHs, affected SCU bed designation. Using data from the Online Survey Certification and Reporting (OSCAR) from 1996 through 2010 with 207 431 NH-year observations, we described trends and compared chain-affiliated NHs with independent NHs. Designation of beds for Alzheimer disease SCUs grew from 1996 to 2003 and then declined. At the peak, 19.6% of all NHs had at least one Alzheimer disease SCU bed. In general, chain affiliation promoted Alzheimer disease SCU bed designation across time, chain size, and NH profit status. During the period of largest growth from 1996 to 2003, the likelihood of designation of Alzheimer disease SCU beds was 1.55 percentage points higher among for-profit NHs affiliated with large chains than independent for-profit NHs ( P < .001) and remained 1.28 percentage points higher from 2004 to 2010. However, chain-affiliated NHs generally had a lower percentage of residents with dementia than independent NHs. For example, although for-profit NHs affiliated with large chains had more Alzheimer disease SCU beds, they had nearly 3% fewer residents with dementia than independent NHs ( P < .001). We conclude that organizational decisions to designate beds for Alzheimer disease SCUs may be related to marketing strategies to attract residents since adoption of Alzheimer disease SCUs has fluctuated over time, but did not appear driven by demand.

Medical therapy following hospitalization for heart failure with reduced ejection fraction and association with discharge to long-term care: a cross-sectional analysis of the REasons for Geographic And Racial Differences in Stroke (REGARDS) population.

BACKGROUND: Less intensive treatment for heart failure with reduced ejection fraction (HFrEF) may be appropriate for patients in long-term care settings because of limited life expectancy, frailty, comorbidities, and emphasis on quality of life. METHODS: We compared treatment patterns between REasons for Geographic And Racial Differences in Stroke (REGARDS) study participants discharged to long-term care versus home following HFrEF hospitalizations. We examined medical records and Medicare pharmacy claims for 147 HFrEF hospitalizations among 80 participants to obtain information about discharge disposition and medication prescriptions and fills. RESULTS: Discharge to long-term care followed 22 of 147 HFrEF hospitalizations (15%). Participants discharged to long-term care were more likely to be prescribed beta-blockers and less likely to be prescribed aldosterone receptor antagonists and hydralazine/isosorbide dinitrate (96%, 14%, and 5%, respectively) compared to participants discharged home (81%, 22%, and 23%, respectively). The percentages of participants discharged to long-term care and home who had claims for filled prescriptions were similar for beta-blockers (68% versus 66%) and angiotensin converting enzyme inhibitors or angiotensin receptor blockers (ACEI/ARBs) (45% versus 47%) after 1 year. Smaller percentages of participants discharged to long-term care had claims for filled prescriptions of other medications compared to participants discharged home (diuretics: long-term care-50%, home-72%; hydralazine/isosorbide dinitrate: long-term care-5%, home-23%; aldosterone receptor antagonists: long-term care-5%, home-23%). CONCLUSIONS: Differences in medication prescriptions and fills among individuals with HFrEF discharged to long-term care versus home may reflect prioritization of some medical therapies over others for patients in long-term care.

Addressing Stroke Risk Factors in Black and White Americans: Findings from the National Health and Nutrition Examination Survey, 2009-2010.

OBJECTIVE: Recurrent stroke affects 5%-15% of stroke survivors, is higher among Blacks, and preventable with secondary stroke prevention medications. Our study aimed to examine racial differences in risk factors being addressed (defined as either on active treatment or within guideline levels) among stroke survivors and those at risk for stroke. METHODS: A cross-sectional study using NHANES 2009-2010 standardized interviews of Whites and Blacks aged ≥18 years. Risk factors were defined as being addressed if: 1) for hypertension, SBP <140, DBP <90 (SBP<130, DBP<80 for diabetics) or using BP-lowering medications; 2) for current smoking, using cessation medications; and 3) for hyperlipidemia, LDL<100 (LDL<70 for stroke survivors) or using lipid-lowering medications. Participants were stratified by stroke history. Prevalence of addressed risk factors was compared by race. RESULTS: Among 4005 participants (mean age 48, 52% women, 15% Black), 4% reported a history of stroke. Among stroke survivors, there were no statistically significant differences in Blacks and Whites having their hypertension or hyperlipidemia addressed. Among stroke naïve participants, the prevalence of addressed hypertension (P<.01) and hyperlipidemia (P<.01) was lower in Blacks compared with Whites. CONCLUSIONS: We found that addressed hypertension and hyperlipidemia in stroke naïve participants were significantly lower in Blacks than Whites. Our observations call attention to areas that require further investigation, such as why Black Americans may not be receiving evidence-based pharmacologic therapy for hypertension and hyperlipidemia or why Black Americans are not at goal blood pressure or goal LDL. A better understanding of this information is critical to preventing stroke and other vascular diseases.

The impact of texting bans on motor vehicle crash-related hospitalizations.

We used a panel design and the Nationwide Inpatient Sample from 19 states between 2003 and 2010 to examine the impact of texting bans on crash-related hospitalizations. We conducted conditional negative binomial regressions with state, year, and month fixed effects to examine changes in crash-related hospitalizations in states after the enactment of a texting ban relative to those in states without such bans. Results indicate that texting bans were associated with a 7% reduction in crash-related hospitalizations among all age groups. Texting bans were significantly associated with reductions in hospitalizations among those aged 22 to 64 years and those aged 65 years or older. Marginal reductions were seen among adolescents. States that have not passed strict texting bans should consider doing so.

Can Nonurgent Emergency Department Care Costs be Reduced? Empirical Evidence from a U.S. Nationally Representative Sample.

BACKGROUND: A well-functioning primary care system has the capacity to provide effective care for patients to avoid nonurgent emergency department (ED) use and related costs. OBJECTIVE: This study examined how patients' perceived deficiency in ambulatory care is associated with nonurgent ED care costs nationwide. METHODS: This retrospective cohort study used data from the 2010-2011 Medical Expenditure Panel Survey. This study chose usual source of care, convenience of needed medical care, and patient evaluation of care quality as the main independent variables. The marginal effect following a multivariate logit model was employed to analyze the urgent vs. nonurgent ED care costs in 2011, after controlling for covariates in 2010. The endogeneity was accounted for by the time lag effect and controlling for education levels. Sample weights and variance were adjusted with the survey procedures to make results nationally representative. RESULTS: Patient-perceived poor and intermediate levels of primary care quality had higher odds of nonurgent ED care costs (odds ratio [OR] = 2.22, p = 0.035, and OR = 2.05, p = 0.011, respectively) compared to high-quality care, with a marginal effect (at means) of 13.0% and 11.5% higher predicted probability of nonurgent ED care costs. Costs related to these ambulatory care quality deficiencies amounted to $229 million for private plans (95% confidence interval [CI] $100 million-$358 million), $58.5 million for public plans (95% CI $33.9 million-$83.1 million), and an overall of $379 million (95% CI $229 million-$529 million) nationally. CONCLUSIONS: These findings highlight the improvement in ambulatory care quality as the potential target area to effectively reduce nonurgent ED care costs.

Impact of texting laws on motor vehicular fatalities in the United States.

Using a panel study design, we examined the effects of different types of texting bans on motor vehicular fatalities. We used the Fatality Analysis Reporting System and a difference-in-differences approach to examine the incidence of fatal crashes in 2000 through 2010 in 48 US states with and without texting bans. Age cohorts were constructed to examine the impact of these bans on age-specific traffic fatalities. Primarily enforced laws banning all drivers from texting were significantly associated with a 3% reduction in traffic fatalities in all age groups, and those banning only young drivers from texting had the greatest impact on reducing deaths among those aged 15 to 21 years. Secondarily enforced restrictions were not associated with traffic fatality reductions in any of our analyses.