Safety vs price in the generic drug market: metformin.

OBJECTIVES: Generic medications represent 90% of prescriptions in the US market and provide a tremendous financial benefit for patients. Recently, multiple generic drugs have been recalled due to the presence of carcinogens, predominantly N-nitrosodimethylamine (NDMA), including an extensive recall of extended-release (ER) metformin products in 2020. STUDY DESIGN: Primary pharmaceutical quality testing and database analysis. METHODS: We tested marketed metformin immediate-release (IR) and ER tablets from a wide sample of generic manufacturers for the presence of carcinogenic impurities NDMA and N,N-dimethylformamide (DMF). We examined the association of level of impurity with drug price and the impact of the 2020 FDA recalls on unit price and prescription fill rate. RESULTS: Postrecall NDMA levels were significantly lower in metformin ER samples (standardized mean difference = -2.0; P = .01); however, we found continued presence of carcinogens above the FDA threshold in 2 of 30 IR samples (6.67%). Overall, the presence of contaminant levels was not significantly associated with price for either IR (NDMA: R2 = 0.142; P = .981; DMF: R2 = 0.382; P = .436) or ER (NDMA: R2 = 0.124; P = .142; DMF: R2 = 0.199; P = .073) samples. Despite recalls, metformin ER prescription fills increased by 8.9% while unit price decreased by 19.61% (P < .05). CONCLUSIONS: Recalls of metformin ER medications were effective in lowering NDMA levels below the FDA threshold; however, some samples of generic metformin still contained carcinogens even after FDA-announced recalls. The absence of any correlation with price indicates that potentially safer products are available on the market for the same price as poorer-quality products.

Evidence for Changes in Screen Use in the United States During Early Childhood Related to COVID-19 Pandemic Parent Stressors: Repeated Cross-Sectional Study.

BACKGROUND: The COVID-19 pandemic transformed the home lives of many families in the United States, especially those with young children. Understanding the relationship between child and parent screen time and family stressors exacerbated by the pandemic may help inform interventions that aim to support early child development. OBJECTIVE: We aim to assess the changing relationship between family screen time and factors related to pandemic-induced remote work and childcare or school closures. METHODS: In the spring of 2021 we administered a survey, similar to one administered in the spring of 2019, to a national sample of parents of young children (aged 6 to 60 months). Using iterative sampling with propensity scores, we recruited participants whose sociodemographic characteristics matched the 2019 survey. Participants were aged >18 years, proficient in English or Spanish, and residing in the United States. The main outcomes were changes in child screen time (eg, mobile phone, tablet, computer, and television) and parenting technoference, defined as perceived screen-related interference with parent-child interactions. Additional survey items reported pandemic-related job loss, and changes to work hours, work location, caregiving responsibilities, day care or school access, and family health and socioeconomic status. RESULTS: We enrolled 280 parents, from diverse backgrounds. Parents reported pandemic-related changes in child screen time (mean increase of 1.1, SD 0.9 hours), and greater parenting technoference (3.0 to 3.4 devices interfering per day; P=.01). Increased child screen time and parenting technoference were highest for parents experiencing job loss (mean change in child screen time 1.46, SD 1.03; mean parenting technoference score 3.89, SD 2.05), second highest for working parents who did not lose their job (mean change in child screen time 1.02, SD 0.83; mean parenting technoference score 3.37, SD 1.94), and lowest for nonworking parents (mean change in child screen time 0.68, SD 0.66; mean parenting technoference score 2.66, SD 1.70), with differences significant at P<.01. School closure and job loss were most associated with increased child screen time during the pandemic after controlling for other stressors and sociodemographic characteristics (d=0.52, P<.001; d=0.31, P=.01). Increased child screen time and school closure were most associated with increased parenting technoference (d=0.78, P<.001; d=0.30, P=.01). CONCLUSIONS: Work and school changes due to the COVID-19 pandemic were associated with increased technology interference in the lives of young children. This study adds to our understanding of the interaction between technology use at home and social factors that are necessary to support early childhood health and development. It also supports possible enhanced recommendations for primary care providers and childcare educators to guide parents in establishing home-based "screen time rules" not only for their children but also for themselves.

ChatGPT Influence on Medical Decision-Making, Bias, and Equity: A Randomized Study of Clinicians Evaluating Clinical Vignettes.

In a randomized, pre-post intervention study, we evaluated the influence of a large language model (LLM) generative AI system on accuracy of physician decision-making and bias in healthcare. 50 US-licensed physicians reviewed a video clinical vignette, featuring actors representing different demographics (a White male or a Black female) with chest pain. Participants were asked to answer clinical questions around triage, risk, and treatment based on these vignettes, then asked to reconsider after receiving advice generated by ChatGPT+ (GPT4). The primary outcome was the accuracy of clinical decisions based on pre-established evidence-based guidelines. Results showed that physicians are willing to change their initial clinical impressions given AI assistance, and that this led to a significant improvement in clinical decision-making accuracy in a chest pain evaluation scenario without introducing or exacerbating existing race or gender biases. A survey of physician participants indicates that the majority expect LLM tools to play a significant role in clinical decision making.

Caring for People With Depression: Costs Among 43 Million Commercially Insured Patients With or Without Comorbid Illnesses.

BACKGROUND: Depression is a common comorbidity for patients with chronic medical conditions. Although the costs of treating chronic medical illness in combination with depression are believed to be significantly higher than the costs of treating each condition independently, few studies have formally modeled the cost consequences of mental health comorbidity. PURPOSE: To estimate the relative magnitude of the independent and synergistic contributions to health care costs from depression diagnosis and other chronic physical health conditions. METHODS: Cross-sectional, observational study using all individuals >18 years of age in the national Blue Cross Blue Shield (BCBS) Axis claims database (N = 43,872,144) from calendar year 2018. General linear models with and without interaction terms were used to assess the relative magnitude of independent and synergistic contributions to total annual health care costs of depression alone and in combination with coronary heart disease, chronic kidney disease, chronic obstructive pulmonary disease, diabetes (both types 1 and 2), hypertension, and arthritis. RESULTS: The incremental annual cost associated with having a diagnosis of depression was $2,951 compared to $1,986-$6,251 for the other chronic physical conditions. The interaction between depression and chronic conditions accounted for less than one-hundredth of the amount of variation in costs explained by the main effects of depression and each chronic physical condition. CONCLUSIONS: The independent increase in total annual health care costs associated with a depression diagnosis was comparable to that of many common physical chronic conditions. This finding underscores the importance of health care service and payment models that acknowledge depression as an equal contributor to overall health care costs. The combination of depression and another chronic condition did not synergistically increase total annual health care costs beyond the increases in costs associated with each condition independently. This finding has implications for simplifying risk adjustment models.

It is widely believed that depression, when combined with other chronic physical conditions, systematically inflates health care costs. For example, it is assumed that the costs of caring for a patient with both depression and heart disease are higher than the costs of caring for each condition independently. Using a database that included 43 million commercially insured people in the United States, we found that the costs of care for patients with depression were comparable to the costs for patients with other chronic medical conditions. This result supports the need for mental health parity and for trained mental health care providers in medical settings. We then considered the costs of caring for people with depression with or with or without one of seven common chronic physical condition. Contrary to expectation, the combination of depression and any of the diagnoses appeared to have largely independent relationships with health care costs. The results contradict the suggestion that depression and chronic condition diagnoses act synergistically to inflate health care expenditures.

Using Case Mix Index within Diagnosis-Related Groups to Evaluate Variation in Hospitalization Costs at a Large Academic Medical Center.

In analyzing direct hospitalization cost and clinical data from an academic medical center, commonly used metrics such as diagnosis-related group (DRG) weight explain approximately 37% of cost variability, but a substantial amount of variation remains unaccounted for by case mix index (CMI) alone. Using CMI as a benchmark, we isolate and target individual DRGs with higher than expected average costs for specific quality improvement efforts. While DRGs summarize hospitalization care after discharge, a predictive model using only information known before admission explained up to 60% of cost variability for two DRGs with a high excess cost burden. This level of variability likely reflects underlying patient factors that are not modifiable (e.g., age and prior comorbidities) and therefore less useful for health systems to target for intervention. However, the remaining unexplained variation can be inspected in further studies to discover operational factors that health systems can target to improve quality and value for their patients. Since DRG weights represent the expected resource consumption for a specific hospitalization type relative to the average hospitalization, the data-driven approach we demonstrate can be utilized by any health institution to quantify excess costs and potential savings among DRGs.

Effect of a Biopsychosocial Intervention or Postural Therapy on Disability and Health Care Spending Among Patients With Acute and Subacute Spine Pain: The SPINE CARE Randomized Clinical Trial.

Importance: Low back and neck pain are often self-limited, but health care spending remains high. Objective: To evaluate the effects of 2 interventions that emphasize noninvasive care for spine pain. Design, Setting, and Participants: Pragmatic, cluster, randomized clinical trial conducted at 33 centers in the US that enrolled 2971 participants with neck or back pain of 3 months' duration or less (enrollment, June 2017 to March 2020; final follow-up, March 2021). Interventions: Participants were randomized at the clinic-level to (1) usual care (n = 992); (2) a risk-stratified, multidisciplinary intervention (the identify, coordinate, and enhance [ICE] care model that combines physical therapy, health coach counseling, and consultation from a specialist in pain medicine or rehabilitation) (n = 829); or (3) individualized postural therapy (IPT), a postural therapy approach that combines physical therapy with building self-efficacy and self-management (n = 1150). Main Outcomes and Measures: The primary outcomes were change in Oswestry Disability Index (ODI) score at 3 months (range, 0 [best] to 100 [worst]; minimal clinically important difference, 6) and spine-related health care spending at 1 year. A 2-sided significance threshold of .025 was used to define statistical significance. Results: Among 2971 participants randomized (mean age, 51.7 years; 1792 women [60.3%]), 2733 (92%) finished the trial. Between baseline and 3-month follow-up, mean ODI scores changed from 31.2 to 15.4 for ICE, from 29.3 to 15.4 for IPT, and from 28.9 to 19.5 for usual care. At 3-month follow-up, absolute differences compared with usual care were -5.8 (95% CI, -7.7 to -3.9; P < .001) for ICE and -4.3 (95% CI, -5.9 to -2.6; P < .001) for IPT. Mean 12-month spending was $1448, $2528, and $1587 in the ICE, IPT, and usual care groups, respectively. Differences in spending compared with usual care were -$139 (risk ratio, 0.93 [95% CI, 0.87 to 0.997]; P = .04) for ICE and $941 (risk ratio, 1.40 [95% CI, 1.35 to 1.45]; P < .001) for IPT. Conclusions and Relevance: Among patients with acute or subacute spine pain, a multidisciplinary biopsychosocial intervention or an individualized postural therapy intervention, each compared with usual care, resulted in small but statistically significant reductions in pain-related disability at 3 months. However, compared with usual care, the biopsychosocial intervention resulted in no significant difference in spine-related health care spending and the postural therapy intervention resulted in significantly greater spine-related health care spending at 1 year. Trial Registration: ClinicalTrials.gov Identifier: NCT03083886.

Estimating health care delivery system value for each US state and testing key associations.

OBJECTIVE: To estimate health care systems' value in treating major illnesses for each US state and identify system characteristics associated with value. DATA SOURCES: Annual condition-specific death and incidence estimates for each US state from the Global Burden Disease 2019 Study and annual health care spending per person for each state from the National Health Expenditure Accounts. STUDY DESIGN: Using non-linear meta-stochastic frontier analysis, mortality incidence ratios for 136 major treatable illnesses were regressed separately on per capita health care spending and key covariates such as age, obesity, smoking, and educational attainment. State- and year-specific inefficiency estimates were extracted for each health condition and combined to create a single estimate of health care delivery system value for each US state for each year, 1991-2014. The association between changes in health care value and changes in 23 key health care system characteristics and state policies was measured. DATA COLLECTION/EXTRACTION METHODS: Not applicable. PRINCIPAL FINDINGS: US state with relatively high spending per person or relatively poor health-outcomes were shown to have low health care delivery system value. New Jersey, Maryland, Florida, Arizona, and New York attained the highest value scores in 2014 (81 [95% uncertainty interval 72-88], 80 [72-87], 80 [71-86], 77 [69-84], and 77 [66-85], respectively), after controlling for health care spending, age, obesity, smoking, physical activity, race, and educational attainment. Greater market concentration of hospitals and of insurers were associated with worse health care value (p-value ranging from <0.01 to 0.02). Higher hospital geographic density and use were also associated with worse health care value (p-value ranging from 0.03 to 0.05). Enrollment in Medicare Advantage HMOs was associated with better value, as was more generous Medicaid income eligibility (p-value 0.04 and 0.01). CONCLUSIONS: Substantial variation in the value of health care exists across states. Key health system characteristics such as market concentration and provider density were associated with value.

Design of the Spine Pain Intervention to Enhance Care Quality And Reduce Expenditure Trial (SPINE CARE) study: Methods and lessons from a multi-site pragmatic cluster randomized controlled trial.

BACKGROUND: Low back and neck pain (together, spine pain) are among the leading causes of medical visits, lost productivity, and disability. For most people, episodes of spine pain are self-limited; nevertheless, healthcare spending for this condition is extremely high. Focusing care on individuals at high-risk of progressing from acute to chronic pain may improve efficiency. Alternatively, postural therapies, which are frequently used by patients, may prevent the overuse of high-cost interventions while delivering equivalent outcomes. METHODS: The SPINE CARE (Spine Pain Intervention to Enhance Care Quality And Reduce Expenditure) trial is a cluster-randomized multi-center pragmatic clinical trial designed to evaluate the clinical effectiveness and healthcare utilization of two interventions for primary care patients with acute and subacute spine pain. The study was conducted at 33 primary care clinics in geographically distinct regions of the United States. Individuals ≥18 years presenting to primary care with neck and/or back pain of ≤3 months' duration were randomized at the clinic-level to 1) usual care, 2) a risk-stratified, multidisciplinary approach called the Identify, Coordinate, and Enhance (ICE) care model, or 3) Individualized Postural Therapy (IPT), a standardized postural therapy method of care. The trial's two primary outcomes are change in function at 3 months and spine-related spending at one year. 2971 individuals were enrolled between June 2017 and March 2020. Follow-up was completed on March 31, 2021. DISCUSSION: The SPINE CARE trial will determine the impact on clinical outcomes and healthcare costs of two interventions for patients with spine pain presenting to primary care. TRIAL REGISTRATION NUMBER: NCT03083886.

Reducing administrative costs in US health care: Assessing single payer and its alternatives.

OBJECTIVE: Excess administrative costs in the US health care system are routinely referenced as a justification for comprehensive reform. While there is agreement that these costs are too high, there is little understanding of what generates administrative costs and what policy options might mitigate them. DATA SOURCES: Literature review and national utilization and expenditure data. STUDY DESIGN: We developed a simulation model of physician billing and insurance-related (BIR) costs to estimate how certain policy reforms would generate savings. Our model is based on structural elements of the payment process in the United States and considers each provider's number of health plan contracts, the number of features in each health plan, the clinical and nonclinical processes required to submit a bill for payment, and the compliance costs associated with medical billing. DATA EXTRACTION: For several types of visits, we estimated fixed and variable costs of the billing process. We used the model to estimate the BIR costs at a national level under a variety of policy scenarios, including variations of a single payer "Medicare-for-All" model that extends fee-for-service Medicare to the entire population and policy efforts to reduce administrative costs in a multi-payer model. We conducted sensitivity analyses of a wide variety of model parameters. PRINCIPAL FINDINGS: Our model estimates that national BIR costs are reduced between 33% and 53% in Medicare-for-All style single-payer models and between 27% and 63% in various multi-payer models. Under a wide range of assumptions and sensitivity analyses, standardizing contracts generates larger savings with less variance than savings from single-payer strategies. CONCLUSION: Although moving toward a single-payer system will reduce BIR costs, certain reforms to payer-provider contracts could generate at least as many administrative cost savings without radically reforming the entire health system. BIR costs can be meaningfully reduced without abandoning a multi-payer system.

Assessment of Electronic Health Record Use Between US and Non-US Health Systems.

Importance: Understanding how the electronic health record (EHR) system changes clinician work, productivity, and well-being is critical. Little is known regarding global variation in patterns of use. Objective: To provide insights into which EHR activities clinicians spend their time doing, the EHR tools they use, the system messages they receive, and the amount of time they spend using the EHR after hours. Design, Setting, and Participants: This cross-sectional study analyzed the deidentified metadata of ambulatory care health systems in the US, Canada, Northern Europe, Western Europe, the Middle East, and Oceania from January 1, 2019, to August 31, 2019. All of these organizations used the EHR software from Epic Systems and represented most of Epic Systems's ambulatory customer base. The sample included all clinicians with scheduled patient appointments, such as physicians and advanced practice practitioners. Exposures: Clinician EHR use was tracked by deidentified and aggregated metadata across a variety of clinical activities. Main Outcomes and Measures: Descriptive statistics for clinician EHR use included time spent on clinical activities, note documentation (as measured by the percentage of characters in the note generated by automated or manual data entry source), messages received, and time spent after hours. Results: A total of 371 health systems were included in the sample, of which 348 (93.8%) were located in the US and 23 (6.2%) were located in other countries. US clinicians spent more time per day actively using the EHR compared with non-US clinicians (mean time, 90.2 minutes vs 59.1 minutes; P < .001). In addition, US clinicians vs non-US clinicians spent significantly more time performing 4 clinical activities: notes (40.7 minutes vs 30.7 minutes; P < .001), orders (19.5 minutes vs 8.75 minutes; P < .001), in-basket messages (12.5 minutes vs 4.80 minutes; P < .001), and clinical review (17.6 minutes vs 14.8 minutes; P = .01). Clinicians in the US composed more automated note text than their non-US counterparts (77.5% vs 60.8% of note text; P < .001) and received statistically significantly more messages per day (33.8 vs 12.8; P < .001). Furthermore, US clinicians used the EHR for a longer time after hours, logging in 26.5 minutes per day vs 19.5 minutes per day for non-US clinicians (P = .01). The median US clinician spent as much time actively using the EHR per day (90.1 minutes) as a non-US clinician in the 99th percentile of active EHR use time per day (90.7 minutes) in the sample. These results persisted after controlling for organizational characteristics, including structure, type, size, and daily patient volume. Conclusions and Relevance: This study found that US clinicians compared with their non-US counterparts spent substantially more time actively using the EHR for a wide range of clinical activities or tasks. This finding suggests that US clinicians have a greater EHR burden that may be associated with nontechnical factors, which policy makers and health system leaders should consider when addressing clinician wellness.

Association Between HEDIS Performance and Primary Care Physician Age, Group Affiliation, Training, and Participation in ACA Exchanges.

BACKGROUND: There are a limited number of studies investigating the relationship between primary care physician (PCP) characteristics and the quality of care they deliver. OBJECTIVE: To examine the association between PCP performance and physician age, solo versus group affiliation, training, and participation in California's Affordable Care Act (ACA) exchange. DESIGN: Observational study of 2013-2014 data from Healthcare Effectiveness Data and Information Set (HEDIS) measures and select physician characteristics. PARTICIPANTS: PCPs in California HMO and PPO practices (n = 5053) with part of their patient panel covered by a large commercial health insurance company. MAIN MEASURES: Hemoglobin A1c testing; medical attention nephropathy; appropriate treatment hypertension (ACE/ARB); breast cancer screening; proportion days covered by statins; monitoring ACE/ARBs; monitoring diuretics. A composite performance measure also was constructed. KEY RESULTS: For the average 35- versus 75-year-old PCP, regression-adjusted mean composite relative performance scores were at the 60th versus 47th percentile (89% vs. 86% composite absolute HEDIS scores; p < .001). For group versus solo PCPs, scores were at the 55th versus 50th percentiles (88% vs. 87% composite absolute HEDIS scores; p < .001). The effect of age on performance was greater for group versus solo PCPs. There was no association between scores and participation in ACA exchanges. CONCLUSIONS: The associations between population-based care performance measures and PCP age, solo versus group affiliation, training, and participation in ACA exchanges, while statistically significant in some cases, were small. Understanding how to help older PCPs excel equally well in group practice compared with younger PCPs may be a fruitful avenue of future research.

Cost impact of sobering centers on national health care spending in the United States.

Acute alcohol intoxication is responsible for a sizable share of emergency department visits. Intoxicated individuals without other medical needs may not require the high level of care provided by an emergency department. We estimate the impact on U.S. health care spending if individuals with uncomplicated, acute alcohol intoxication were treated in sobering centers instead of the emergency department. We performed a budget impact analysis from the perspective of the U.S. health care system based on published and gray literature reports. Ninety-five percent confidence intervals (CI) were estimated using Monte Carlo modeling with random variation for three variables (cost of an emergency department visit, cost of a sobering center visit, and start-up costs per sobering center visit) and the percentage of cases diverted from emergency departments to sobering centers. Outcomes were expressed in terms of national savings in 2017 U.S. dollars. Assuming a diversion rate of 50% based on previous studies, national savings range from $230 million to $1.0 billion annually. In the Monte Carlo modeling, we found annual national savings of $99.02 million (95% CI: $95.89-$102.19 million), $792.34 million (95% CI: $767.09-$817.58 million), and $1,185.51 million (95% CI: $1,150.64-$1,226.37 million) with diversion rates of 5%, 40%, and 60%, respectively. Implementing sobering centers as a treatment alternative for individuals with uncomplicated acute alcohol intoxication could yield substantial cost savings for the U.S. health care system.

Exploring Care Attributes of Nephrologists Ranking Favorably on Measures of Value.

BACKGROUND: Despite growth in value-based payment, attributes of nephrology care associated with payer-defined value remains unexplored. METHODS: Using national health insurance claims data from private preferred provider organization plans, we ranked nephrology practices using total cost of care and a composite of common quality metrics. Blinded to practice rankings, we conducted site visits at four highly ranked and three average ranked practices to identify care attributes more frequently present in highly ranked practices. A panel of nephrologists used a modified Delphi method to score each distinguishing attribute on its potential to affect quality and cost of care and ease of transfer to other nephrology practices. RESULTS: Compared with average-value peers, high-value practices were located in areas with a relatively higher proportion of black and Hispanic patients and a lower proportion of patients aged >65 years. Mean risk-adjusted per capita monthly total spending was 24% lower for high-value practices. Twelve attributes comprising five general themes were observed more frequently in high-value nephrology practices: preventing near-term costly health crises, supporting patient self-care, maximizing effectiveness of office visits, selecting cost-effective diagnostic and treatment options, and developing infrastructure to support high-value care. The Delphi panel rated four attributes highly on effect and transferability: rapidly adjustable office visit frequency for unstable patients, close monitoring and management to preserve kidney function, early planning for vascular access, and education to support self-management at every contact. CONCLUSIONS: Findings from this small-scale exploratory study may serve as a starting point for nephrologists seeking to improve on payer-specified value measures.

Effects of Mental Health on the Costs of Care for Chronic Illnesses.

OBJECTIVE: The study examined whether comorbid low mental health functioning inflates the cost of treating a chronic disease. METHODS: Data were from the 2015 Medical Expenditure Panel Survey (N=33,893). Costs were estimated from medical records and self-reported health care use. The mental component summary (MCS) score of the 12-item Short Form (SF-12) was used as a measure of mental health status. A general linear model estimated costs with fixed effects for chronic disease (present or absent) and mental health functioning (lowest, middle, and highest MCS score tertiles indicating low, middle, and high levels of mental health functioning, respectively). The SF-12 physical component summary score was a covariate. Eight conditions (arthritis, chronic obstructive pulmonary disease [COPD], high cholesterol, cancer, diabetes, stroke, coronary heart disease, and asthma) were analyzed separately. RESULTS: For each analysis, presence or absence of the chronic condition had a strong impact on cost. Lower mental health functioning also had a significant impact on cost. However, the interaction between mental health functioning and chronic disease diagnoses was statistically significant for only three conditions and accounted for only a small variation in cost. Sensitivity analyses using MCS score as a continuous variable, using a log10 transformation of the cost variable, and focusing only on persons with scores on the extreme low end did not significantly alter the conclusions. CONCLUSIONS: Contrary to expectation, the combination of poor mental functioning and chronic disease diagnosis did not have a strong synergistic effect on cost. Mental and general medical conditions appear to have independent effects on health care costs.

Contributions of Health Care to Longevity: A Review of 4 Estimation Methods.

PURPOSE: Health care expenditures and biomedical research funding are often justified by the belief that modern health care powerfully improves life expectancy in wealthy countries. We examined 4 different methods of estimating the effect of health care on health outcomes. METHODS: We reviewed the contributions of medical care to health outcomes using 4 methods: (1) analyses by McGinnis and Schroeder, (2) Wennberg and colleagues' studies of small area variation, (3) Park and colleagues' analysis of County Health Rankings and Roadmaps, and (4) the RAND Health Insurance Experiment. RESULTS: The 4 methods, using different data sets, produced estimates ranging from 0% to 17% of premature mortality attributable to deficiencies in health care access or delivery. Estimates of the effect of behavioral factors ranged from 16% to 65%. CONCLUSIONS: The results converge to suggest that restricted access to medical care accounts for about 10% of premature death or other undesirable health outcomes. Health care has modest effects on the extension of US life expectancy, while behavioral and social determinants may have larger effects.