Major Traffic Safety Reform and Road Traffic Injuries Among Low-Income New York Residents, 2009-2021.

Objectives. To evaluate the effects of a comprehensive traffic safety policy-New York City's (NYC's) 2014 Vision Zero-on the health of Medicaid enrollees. Methods. We conducted difference-in-differences analyses using individual-level New York Medicaid data to measure traffic injuries and expenditures from 2009 to 2021, comparing NYC to surrounding counties without traffic reforms (n = 65 585 568 person-years). Results. After Vision Zero, injury rates among NYC Medicaid enrollees diverged from those of surrounding counties, with a net impact of 77.5 fewer injuries per 100 000 person-years annually (95% confidence interval = -97.4, -57.6). We observed marked reductions in severe injuries (brain injury, hospitalizations) and savings of $90.8 million in Medicaid expenditures over the first 5 years. Effects were largest among Black residents. Impacts were reversed during the COVID-19 period. Conclusions. Vision Zero resulted in substantial protection for socioeconomically disadvantaged populations known to face heightened risk of injury, but the policy's effectiveness decreased during the pandemic period. Public Health Implications. Many cities have recently launched Vision Zero policies and others plan to do so. This research adds to the evidence on how and in what circumstances comprehensive traffic policies protect public health. (Am J Public Health. 2024;114(6):633-641. https://doi.org/10.2105/AJPH.2024.307617).

Robotic Prostatectomy and Prostate Cancer-Related Medicaid Spending: Evidence from New York State.

BACKGROUND: Robotic prostatectomy is a costly new technology, but the costs may be offset by changes in treatment patterns. The net effect of this technology on Medicaid spending has not been assessed. OBJECTIVE: To identify the association of the local availability of robotic surgical technology with choice of initial treatment for prostate cancer and total prostate cancer-related treatment costs. DESIGN AND PARTICIPANTS: This cohort study used New York State Medicaid data to examine the experience of 9564 Medicaid beneficiaries 40-64 years old who received a prostate biopsy between 2008 and 2017 and were diagnosed with prostate cancer. The local availability of robotic surgical technology was measured as distance from zip code centroids of patient's residence to the nearest hospital with a robot and the annual number of robotic prostatectomies performed in the Hospital Referral Region. MAIN MEASURES: Multivariate linear models were used to relate regional access to robots to the choice of initial therapy and prostate cancer treatment costs during the year after diagnosis. KEY RESULTS: The mean age of the sample of 9564 men was 58 years; 30% of the sample were White, 26% were Black, and 22% were Hispanic. Doubling the distance to the nearest hospital with a robot was associated with a reduction in robotic surgery rates of 3.7 percentage points and an increase in the rate of use of radiation therapy of 5.2 percentage points. Increasing the annual number of robotic surgeries performed in a region by 10 was associated with a decrease in the probability of undergoing radiation therapy of 0.6 percentage point and a $434 reduction in total prostate cancer-related costs per Medicaid patient. CONCLUSIONS: A full accounting of the costs of a new technology will depend on when it is used and the payment rate for its use relative to payment rates for substitutes.

Who Entered and Exited the Individual Health Insurance Market Before and After the Affordable Care Act? Evidence from the Medical Expenditure Panel Survey.

Issue: The Affordable Care Act (ACA) made it easier for older adults and those with medical conditions to enroll in individual-market coverage by eliminating risk rating and limiting age rating. While the ACA also encourages young and healthy people to enroll through subsidies and the individual mandate, it's not clear whether these incentives have been sufficient to prevent the risk pool from becoming disproportionately old and sick. Goal: To assess whether patterns in individual-market participation changed following ACA implementation. Methods: Comparison of Medical Expenditure Panel Survey (MEPS) data for the periods 2003­09 and 2014­15. Findings and Conclusion: The analysis found few differences in individual-insurance market participation before and after the ACA. Adverse selection occurred during both: people switching into individual insurance coverage after being uninsured were higher utilizers prior to the switch than were those who remained uninsured. Those who disenrolled from individual plans tended to be lower utilizers of care before switching compared with those who kept their coverage. The main difference was that more people--especially young adults--switched from Medicaid to individual insurance, and vice versa, after the ACA. Adverse enrollment or disenrollment in the individual market did not increase following ACA implementation. The combination of easing rating rules and encouraging participation appears to have maintained market stability.

How Would Americans' Out-of-Pocket Costs Change If Insurance Plans Were Allowed to Exclude Coverage for Preexisting Conditions?

Issue: A current Republican legislative proposal would permit insurers to offer plans that exclude coverage of treatment for preexisting health conditions, even while the bill would maintain the Affordable Care Act's rule prohibiting denial of coverage to people with a preexisting condition. Goal: Estimate patients' out-of-pocket costs for five common preexisting conditions if the bill were to become law and assess any additional impact on out-of-pocket expenditures if spending on care for preexisting conditions no longer counted against plan deductibles. Methods: Analysis of 2014­2016 Medical Expenditure Panel Survey data for the privately insured adult population under age 65; and the proposed Ensuring Coverage for Patients with Pre-Existing Conditions Act (S. 3388). Findings and Conclusion: If preexisting conditions were excluded from coverage, nearly all people with these conditions would see increased out-of-pocket costs. Average out-of-pocket costs for those with cancer or diabetes would triple, while costs for arthritis, asthma, and hypertension care would rise by 27 percent to 39 percent. Some individuals would see much larger increases: for example, 10 percent of diabetes patients could expect to incur over $9,200 annually in out-of-pocket costs. Many with preexisting conditions also would spend more on conditions that are not excluded, since out-of-pocket spending on their preexisting conditions would no longer count toward the deductible and out-of-pocket maximum.

The Potential Implications of Work Requirements for the Insurance Coverage of Medicaid Beneficiaries: The Case of Kentucky.

Issue: With encouragement from the Trump administration, 14 states have received approval for or are pursuing work requirements for nondisabled Medicaid beneficiaries. The requirements have sparked controversy, including two legal challenges. Goal: To predict the effect of work requirements on the insurance coverage of Medicaid enrollees over time. Methods: Analysis of the coverage patterns of a national cohort of nondisabled adults in the federal Medical Expenditure Panel Survey. Their experience is applied to a similar cohort of adults in Kentucky (which has received approval for work requirements, subject to a legal challenge) to project the potential effects of work requirements on their insurance coverage. Findings and Conclusions: Adding a new administrative hurdle in the form of work requirements in Kentucky would double the number of enrollees who disenroll from the program over a two-year period. We estimate that as many as 118,000 adults enrolled in Medicaid would either become uninsured for an extended period of time or experience a gap in insurance over a two-year period. These findings should be of concern to policymakers: research has found that adults who experience coverage gaps report problems getting health care or paying medical bills at rates nearly as high as those who are uninsured continuously.

Hospital Revisits Within 30 Days After Conventional and Robotically Assisted Hysterectomy.

OBJECTIVES: To compare the rates of hospital readmissions, emergency department, and outpatient clinic visits after discharge for robotically assisted (RA) versus nonrobotic hysterectomy in women age 30 or more with nonmalignant conditions. DATA SOURCES: Discharges for 2011 for 8 states (CA, FL, GA, IA, MO, NE, NY, TN) (>86,000 inpatient hysterectomies) were drawn from the statewide databases of the Healthcare Cost and Utilization Project. Data from 4 of these states were used to study revisits after 29,000 outpatient hysterectomies. METHODS: Matched pairs of patients were constructed with propensity scores derived from each patient's age group, severity of illness, insurance coverage, and type of procedure. Both the full set of revisits and a set limited to diagnoses for revisits judged in other research to be related to the initial surgery (about 70% of all revisits) were analyzed. The analyses were repeated with an instrumental variables regression design. KEY RESULTS: Using the propensity score matched pairs, revisits, and specifically readmissions, after inpatient hysterectomy were greater for RA versus non-RA patients (relative risk of readmission=124%, P<0.01). Similar results were found for readmissions after outpatient hysterectomy, and readmissions after inpatient hysterectomy for the restricted set of related revisits. In the method with instrumental variables, RA was associated with an increase of 32% in the likelihood of any revisit (P<0.01). CONCLUSIONS: Using 2 different methods to control for selection, this study found higher rates of revisits among women undergoing RA versus non-RA hysterectomy for benign conditions. While selection bias cannot be ruled out completely in an observational study, the study supports broader use of revisits for analyses of outcomes of hysterectomy.

The Norwood operation: Relative effects of surgeon and institutional volumes on outcomes and resource utilization.

BACKGROUND: Hypoplastic left heart syndrome is the most expensive birth defect managed in the United States, with a 5-year survival rate below 70%. Increasing evidence suggests that hospital volumes are inversely associated with mortality for infants with single ventricles undergoing stage 1 surgical palliation. Our aim was to examine the relative effects of surgeon and institutional volumes on outcomes and resource utilisation for these children. METHODS: A retrospective study was conducted using the Pediatric Health Information System database to examine the effects of the number of procedures performed per surgeon and per centre on mortality, costs, and post-operative length of stay for infants undergoing Risk Adjustment for Congenital Heart Surgery risk category six operations at tertiary-care paediatric hospitals, from 1 January, 2004 to 31 December, 2013. Multivariable modelling was used, adjusting for patient and institutional characteristics. Gaussian kernel densities were constructed to show the relative distributions of the effects of individual institutions and surgeons, before and after adjusting for the number of cases performed. RESULTS: A total of 2880 infants from 35 institutions met the inclusion criteria. Mortality was 15.0%. Median post-operative length of stay was 24 days (IQR 14-41). Median standardized inpatient hospital costs were $156,000 (IQR $108,000-$248,000) in 2013 dollars. In the multivariable analyses, higher institutional volume was inversely associated with mortality (p=0.001), post-operative length of stay (p=0.004), and costs (p=0.001). Surgeon volume was associated with none of the measured outcomes. Neither institutional nor surgeon volumes explained much of the wide variation in outcomes and resource utilization observed between institutions and between surgeons. CONCLUSIONS: Increased institutional - but not surgeon - volumes are associated with reduced mortality, post-operative length of stay, and costs for infants undergoing stage 1 palliation.

Comparative effectiveness of upfront treatment strategies in elderly women with ovarian cancer.

BACKGROUND: Observational studies comparing neoadjuvant chemotherapy to primary surgery for advanced-stage ovarian cancer are limited by strong selection bias. Multiple methods were used to control for confounding and selection bias to estimate the effect of primary treatment on survival for ovarian cancer. METHODS: The Surveillance, Epidemiology, and End Results (SEER)-Medicare database was used to identify women ≥ 65 years of age with stage II-IV epithelial ovarian cancer who survived > 6 months from the date of diagnosis and received treatment from 1991 through 2007. Traditional regression analysis, propensity score-based analysis, and an instrumental variable analysis (IVA) using geographic location as an instrument were used to compare survival between neoadjuvant chemotherapy and primary surgery. RESULTS: A total of 9587 patients with stage II-IV ovarian cancer were identified. Use of primary surgery decreased from 63.2% in 1991 to 49.5% by 2007, whereas primary chemotherapy increased from 19.7% in 1991 to 31.8% in 2007 (P < .0001). In the observational cohort survival (hazard ratio [HR] = 1.27; 95% confidence interval [CI] = 1.19-1.35) was inferior for patients treated with neoadjuvant chemotherapy; both median survival (15.8 versus 28.8 months) and 2-year survival (36% versus 56%) were lower in the neoadjuvant chemotherapy group compared to those who underwent surgery. In the IVA, primary treatment had minimal effect on overall survival (HR = 1.04; 95% CI = 0.67-1.60). The median survival for patients with a value of the instrument less than the median (24.0 months, 95% CI = 23.0-25.0) and greater than or equal to median value of the IV (24.0 months, 95% CI = 23.0-26.0) were similar. CONCLUSIONS: Use of neoadjuvant therapy has increased over time. Survival with neoadjuvant chemotherapy did not differ significantly from primary surgery in elderly women in the United States.

Factors associated with adoption of robotic surgical technology in US hospitals and relationship to radical prostatectomy procedure volume.

OBJECTIVE: Robotic technology has diffused rapidly despite high costs and limited additive reimbursement by major payers. We aimed to identify the factors associated with hospitals' decisions to adopt robotic technology and the consequences of these decisions. METHODS: This observational study used data on hospitals and market areas from 2005 to 2009. Included were hospitals in census-based statistical areas within states in the State Inpatient Database that participated in the American Hospital Association annual surveys and performed radical prostatectomies. The likelihood that a hospital would acquire a robotic facility and the rates of radical prostatectomy relative to the prevalence of robots in geographic market areas were assessed using multivariable analysis. RESULTS: Hospitals in areas where a higher proportion of other hospitals had already acquired a robot were more likely to acquire one (P=0.012), as were those with more than 300 beds (P<0.0001) and teaching hospitals (P<0.0001). There was a significant association between years with a robot and the change in the number of radical prostatectomies (P<0.0001). More radical prostatectomies were performed in areas where the number of robots per 100,000 men was higher (P<0.0001). Adding a single robot per 100,000 men in an area was associated with a 30% increase in the rate of radical prostatectomies. CONCLUSIONS: Local area robot competition was associated with the rapid spread of robot technology in the United States. Significantly more radical prostatectomies were performed in hospitals with robots and in market areas of hospitals with robotic technology.

The impact of managed care contracting on physicians.

BACKGROUND: Prior literature suggests that the fragmented U.S. health care system places a large administrative burden on physicians. Less is known about how this burden varies with physician contracting practices. OBJECTIVE: To assess the extent to which physician practice outcomes vary with the number of managed care contracts held or the availability of such contracts. DESIGN, PARTICIPANTS, AND MAIN MEASURES: We perform secondary data analyses of the first four rounds of the nationally representative Community Tracking Study Physician Survey (1996-2005), which includes 36,340 physicians (21,567 PCPs [primary care physicians] and 14,773 specialists) across the four survey periods. Our measures include reported hours in patient care, share of hours outside patient care, adequacy of time with patients, career satisfaction, and income. RESULTS: Doctors who contract with more plans report spending more time in patient care (per 11 additional contracts, about 30 min per week for PCPs and 20 min per week for specialists), report spending a modestly larger share of their time outside patient care (per 11 additional contracts, about 10 min per week for PCPs and specialists), are slightly more likely to report inadequate time with patients (odds ratio 1.005 per additional contract for PCPs), and earn higher incomes (per 11 additional contracts, about 3 % more per year for specialists). CONCLUSIONS: Contracting opportunities confer significant benefits on physicians, although they do add modest costs in terms of time spent outside patient care and lower adequacy of time with patients. Simplifications that reduce the administrative burden of contracting may improve care by optimizing allocation of physician effort.

Unwinding And The Medicaid Undercount: Millions Enrolled In Medicaid During The Pandemic Thought They Were Uninsured.

Policy responses to the March 31, 2023, expiration of the Medicaid continuous coverage provision need to consider the difference between self-reported Medicaid participation on government surveys and administrative records of Medicaid enrollment. The difference between the two is known as the "Medicaid undercount." The size of the undercount increased substantially after the continuous coverage provision took effect in March 2020. Using longitudinal data from the Current Population Survey, we examined this change. We found that assuming that all beneficiaries who ever reported enrolling in Medicaid during the COVID-19 pandemic public health emergency remained enrolled through 2022 (as required by the continuous coverage provision) eliminated the worsening of the undercount. We estimated that nearly half of the 5.9 million people who we projected were likely to become uninsured after the provision expired, or "unwound," already reported that they were uninsured in the 2022 Current Population Survey. This finding suggests that the impact of ending the continuous coverage provision on the estimated uninsurance rate, based on self-reported survey data, may have been smaller than anticipated. It also means that efforts to address Medicaid unwinding should include people who likely remain eligible for Medicaid but believe that they are already uninsured.

Housing-Sensitive Health Conditions Can Predict Poor-Quality Housing.

Improving housing quality may improve residents' health, but identifying buildings in poor repair is challenging. We developed a method to improve health-related building inspection targeting. Linking New York City Medicaid claims data to Landlord Watchlist data, we used machine learning to identify housing-sensitive health conditions correlated with a building's presence on the Watchlist. We identified twenty-three specific housing-sensitive health conditions in five broad categories consistent with the existing literature on housing and health. We used these results to generate a housing health index from building-level claims data that can be used to rank buildings by the likelihood that their poor quality is affecting residents' health. We found that buildings in the highest decile of the housing health index (controlling for building size, community district, and subsidization status) scored worse across a variety of housing quality indicators, validating our approach. We discuss how the housing health index could be used by local governments to target building inspections with a focus on improving health.

Improving Labor Outcomes among People with Mild or Moderate Mental Illness through Law and Policy Reform.

Mild and moderate mental illnesses can hinder labor force participation, lead to work interruptions, and hamper earning potential. Targeted interventions have proven effective at addressing these problems. But their potential depends on labor protections that enable people to take advantage of these interventions while keeping jobs and income.

Hospital concentration and low-income populations: Evidence from New York State Medicaid.

While a large body of evidence has examined hospital concentration, its effects on health care for low-income populations are less explored. We use comprehensive discharge data from New York State to measure the effects of changes in market concentration on hospital-level inpatient Medicaid volumes. Holding fixed hospital factors constant, a one percent increase in HHI leads to a 0.6% (s.e. = 0.28%) decrease in the number of Medicaid admissions for the average hospital. The strongest effects are on admissions for birth (-1.3%, s.e. = 0.58%). These average hospital-level decreases largely reflect redistribution of Medicaid patients across hospitals, rather than overall reductions in hospitalizations for Medicaid patients. In particular, hospital concentration leads to a redistribution of admissions from non-profit hospitals to public hospitals. We find evidence that for births, physicians serving high shares of Medicaid beneficiaries in particular experience reduced admissions as concentration increased. These reductions may reflect preferences among these physicians or reduced admitting privileges by hospitals as a means to screen out Medicaid patients.

Health Savings Accounts No Longer Promote Consumer Cost-Consciousness.

Two decades ago Congress enabled Americans to open tax-favored health savings accounts (HSAs) in conjunction with qualifying high-deductible health plans (HDHPs). This HSA tax break is regressive: Higher-income Americans are more likely to have HSAs and fund them at higher levels. Proponents, however, have argued that this regressivity is offset by reductions in wasteful health care spending because consumers with HDHPs are more cost-conscious in their use of care. Using published sources and our own analysis of National Health Interview Survey data, we argue that HSAs no longer appreciably achieve this cost-consciousness aim because cost sharing has increased so much in non-HSA-qualified plans. Indeed, people who have HDHPs with HSAs are becoming less likely than others with private insurance to report financial barriers to care. In sum, promised gains in efficiency from HSAs have not borne out, so it is difficult to justify maintaining this regressive tax break.

Association of Insurance Mix and Diagnostic Coding Practices in New York State Hospitals.

Importance: Given higher reimbursement rates, hospitals primarily serving privately insured patients may invest more in intensive coding than hospitals serving publicly insured patients. This may lead these hospitals to code more diagnoses for all patients. Objective: To estimate whether, for the same Medicaid enrollee with multiple hospitalizations, a hospital's share of privately insured patients is associated with the number of diagnoses on claims. Design, Setting, and Participants: This cross-sectional study used patient-level fixed effects regression models on inpatient Medicaid claims from Medicaid enrollees with at least 2 admissions in at least 2 different hospitals in New York State between 2010 and 2017. Analyses were conducted from 2019 to 2021. Exposures: The annual share of privately insured patients at the admitting hospital. Main Outcomes and Measures: Number of diagnostic codes per admission. Probability of diagnoses being from a list of conditions shown to be intensely coded in response to payment incentives. Results: This analysis included 1 614 630 hospitalizations for Medicaid-insured patients (mean [SD] age, 48.2 [20.1] years; 829 684 [51.4%] women and 784 946 [48.6%] men). Overall, 74 998 were Asian (4.6%), 462 259 Black (28.6%), 375 591 Hispanic (23.3%), 486 313 White (30.1%), 128 896 unknown (8.0%), and 86 573 other (5.4%). When the same patient was seen in a hospital with a higher share of privately insured patients, more diagnoses were recorded (0.03 diagnoses per percentage point [pp] increase in share of privately insured; 95% CI, 0.02-0.05; P < .001). Patients discharged from hospitals in the bottom quartile of privately insured patient share received 1.37 more diagnoses when they were subsequently discharged from hospitals in the top quartile, relative to patients whose admissions were both in the bottom quartile (95% CI, 1.21-1.53; P < .001). Those going from hospitals in the top quartile to the bottom had 1.67 fewer diagnoses (95% CI, -1.84 to -1.50; P < .001). Diagnoses in hospitals with a higher private payer share were more likely to be for conditions sensitive to payment incentives (0.08 pp increase for each pp increase in private share; 95% CI, 0.06-0.10; P < .001). These findings were replicated in 2016 to 2017 data. Conclusions and Relevance: In this cross-sectional study of Medicaid enrollees, admission to a hospital with a higher private payer share was associated with more diagnoses on Medicaid claims. This suggests payment policy may drive differential investments in infrastructure to document diagnoses. This may create a feedback loop that exacerbates resource inequity.

Eviction, Healthcare Utilization, and Disenrollment Among New York City Medicaid Patients.

INTRODUCTION: Although growing evidence links residential evictions to health, little work has examined connections between eviction and healthcare utilization or access. In this study, eviction records are linked to Medicaid claims to estimate short-term associations between eviction and healthcare utilization, as well as Medicaid disenrollment. METHODS: New York City eviction records from 2017 were linked to New York State Medicaid claims, with 1,300 evicted patients matched to 261,855 non-evicted patients with similar past healthcare utilization, demographics, and neighborhoods. Outcomes included patients' number of acute and ambulatory care visits, healthcare spending, Medicaid disenrollment, and pharmaceutical prescription fills during 6 months of follow-up. Coarsened exact matching was used to strengthen causal inference in observational data. Weighted generalized linear models were then fit, including censoring weights. Analyses were conducted in 2019-2021. RESULTS: Eviction was associated with 63% higher odds of losing Medicaid coverage (95% CI=1.38, 1.92, p<0.001), fewer pharmaceutical prescription fills (incidence rate ratio=0.68, 95% CI=0.52, 0.88, p=0.004), and lower odds of generating any healthcare spending (OR=0.72, 95% CI=0.61, 0.85, p<0.001). However, among patients who generated any spending, average spending was 20% higher for those evicted (95% CI=1.03, 1.40, p=0.017), such that evicted patients generated more spending on balance. Marginally significant estimates suggested associations with increased acute, and decreased ambulatory, care visits. CONCLUSIONS: Results suggest that eviction drives increased healthcare spending while disrupting healthcare access. Given previous research that Medicaid expansion lowered eviction rates, eviction and Medicaid disenrollment may operate cyclically, accumulating disadvantage. Preventing evictions may improve access to care and lower Medicaid costs.

We all want it, but we don't know what it is: toward a standard of affordability for health insurance premiums.

The 2010 Patient Protection and Affordable Care Act (P.L. 111-148), or ACA, requires that U.S. citizens either purchase health insurance or pay a fine. To offset the financial burden for lower-income households, it also provides subsidies to ensure that health insurance premiums are affordable. However, relatively little work has been done on how such affordability standards should be set. The existing literature on affordability is not grounded in social norms and has methodological and theoretical flaws. To address these issues, we developed a series of hypothetical vignettes in which individual and household sociodemographic characteristics were varied. We then convened a panel of eighteen experts with extensive experience in affordability standards to evaluate the extent to which each vignette character could afford to pay for one of two health insurance plans. The panel varied with respect to political ideology and discipline. We find that there was considerable disagreement about how affordability is defined. There was also disagreement about what might be included in an affordability standard, with substantive debate surrounding whether savings, debt, education, or single parenthood is relevant. There was also substantial variation in experts' assessed affordability scores. Nevertheless, median expert affordability assessments were not far from those of ACA.