The Impact Of Telemedicine On Medicare Utilization, Spending, And Quality, 2019-22

Telemedicine use remains substantially higher than it was before the COVID-19 pandemic, although it has fallen from pandemic highs. To inform the ongoing debate about whether to continue payment for telemedicine visits, we estimated the association of greater telemedicine use across health systems with utilization, spending, and quality. In 2020, Medicare patients receiving care at health systems in the highest quartile of telemedicine use had 2.5 telemedicine visits per person (26.8 percent of visits) compared with 0.7 telemedicine visits per person (9.5 percent of visits) in the lowest quartile of telemedicine use. In 2021-22, relative to those in the lowest quartile, Medicare patients of health systems in the highest quartile had an increase of 0.21 total outpatient visits (telemedicine and in-person) per patient per year (2.2 percent relative increase), a decrease of 14.4 annual non-COVID-19 emergency department visits per 1,000 patients per year (2.7 percent relative decrease), a $248 increase in per patient per year spending (1.6 percent relative increase), and increased adherence for metformin and statins. There were no clear differential changes in hospitalizations or receipt of preventive care.

Trends in Integration Between Physician Organizations and Pharmacies for Self-Administered Drugs

Importance

Increasing integration across medical services may have important implications for health care quality and spending. One major but poorly understood dimension of integration is between physician organizations and pharmacies for self-administered drugs or in-house pharmacies.

Objective

To describe trends in the use of in-house pharmacies, associated physician organization characteristics, and associated drug prices.

Design, Setting, and Participants

A cross-sectional study was conducted from calendar years 2011 to 2019. Participants included 20% of beneficiaries enrolled in fee-for-service Medicare Parts A, B, and D. Data analysis was performed from September 15, 2020, to December 20, 2023.

Exposures

Prescriptions filled by in-house pharmacies.

Main Outcomes and Measures

The share of Medicare Part D spending filled by in-house pharmacies by drug class, costliness, and specialty was evaluated. Growth in the number of physician organizations and physicians in organizations with in-house pharmacies was measured in 5 specialties: medical oncology, urology, infectious disease, gastroenterology, and rheumatology. Characteristics of physician organizations with in-house pharmacies and drug prices at in-house vs other pharmacies are described.

Results

Among 8 020 652 patients (median age, 72 [IQR, 66-81] years; 4 570 114 [57.0%] women), there was substantial growth in the share of Medicare Part D spending on high-cost drugs filled at in-house pharmacies from 2011 to 2019, including oral anticancer treatments (from 10% to 34%), antivirals (from 12% to 20%), and immunosuppressants (from 2% to 9%). By 2019, 63% of medical oncologists, 20% of urologists, 29% of infectious disease specialists, 21% of gastroenterologists, and 22% of rheumatologists were in organizations with specialty-relevant in-house pharmacies. Larger organizations had a greater likelihood of having an in-house pharmacy (0.75 percentage point increase [95% CI, 0.56-0.94] per each additional physician), as did organizations owning hospitals enrolled in the 340B Drug Discount Program (10.91 percentage point increased likelihood [95% CI, 6.33-15.48]). Point-of-sale prices for high-cost drugs were 1.76% [95% CI, 1.66%-1.87%] lower at in-house vs other pharmacies.

Conclusions and Relevance

In this cross-sectional study of physician organization-operated pharmacies, in-house pharmacies were increasingly used from 2011 to 2019, especially for high-cost drugs, potentially associated with organizations' financial incentives. In-house pharmacies offered high-cost drugs at lower prices, in contrast to findings of integration in other contexts, but their growth highlights a need to understand implications for patient care.

The New Role of Private Investment in Health Care Delivery

This JAMA Forum discusses the good and bad of innovation in health care delivery, tax policy, an escrow account for failure, and state monitoring.

Active steps to reduce administrative spending associated with financial transactions in US health care

US health care administrative spending is approximately $1 trillion annually. A major operational area is the financial transactions ecosystem, which has approximately $200 billion in spending annually. Efficient financial transactions ecosystems from other industries and countries exhibit 2 features: immediate payment assurance and high use of automation throughout the process. The current system has an average transaction cost of $12 to $19 per claim across private payers and providers for more than 9 billion claims per year; each claim on average takes 4 to 6 weeks to process and pay. For simple claims, the transaction cost is $7 to $10 across private payers and providers; for complex claims, $35 to $40. Prior authorization on approximately 5000 codes has an average cost of $40 to $50 per submission for private payers and $20 to $30 for providers. Interventions aligned with a more efficient financial transactions ecosystem could reduce spending by $40 billion to $60 billion; approximately half is at the organizational level (scaling interventions being implemented by leading private payers and providers) and half at the industry level (adopting a centralized automated claims clearinghouse, standardizing medical policies for a subset of prior authorizations, and standardizing physician licensure for a national provider directory).

Health System Change in the Wake of COVID-19

This JAMA Forum discusses resiliency, telehealth, the health care labor force, and public health in the context of the health system changes occurring since the start of the COVID-19 pandemic.

Organization of Cancer Specialists in US Physician Practices and Health Systems

PURPOSE

To describe the supply of cancer specialists, the organization of cancer care within versus outside of health systems, and the distance to multispecialty cancer centers.

METHODS

Using the 2018 Health Systems and Provider Database from the National Bureau of Economic Research and 2018 Medicare data, we identified 46,341 unique physicians providing cancer care. We stratified physicians by discipline (adult/pediatric medical oncologists, radiation oncologists, surgical/gynecologic oncologists, other surgeons performing cancer surgeries, or palliative care physicians), system type (National Cancer Institute [NCI] Cancer Center system, non-NCI academic system, nonacademic system, or nonsystem/independent practice), practice size, and composition (single disciplinary oncology, multidisciplinary oncology, or multispecialty). We computed the density of cancer specialists by county and calculated distances to the nearest NCI Cancer Center.

RESULTS

More than half of all cancer specialists (57.8%) practiced in health systems, but 55.0% of cancer-related visits occurred in independent practices. Most system-based physicians were in large practices with more than 100 physicians, while those in independent practices were in smaller practices. Practices in NCI Cancer Center systems (95.2%), non-NCI academic systems (95.0%), and nonacademic systems (94.3%) were primarily multispecialty, while fewer independent practices (44.8%) were. Cancer specialist density was sparse in many rural areas, where the median travel distance to an NCI Cancer Center was 98.7 miles. Distances to NCI Cancer Centers were shorter for individuals living in high-income areas than in low-income areas, even for individuals in suburban and urban areas.

CONCLUSION

Although many cancer specialists practiced in multispecialty health systems, many also worked in smaller-sized independent practices where most patients were treated. Access to cancer specialists and cancer centers was limited in many areas, particularly in rural and low-income areas.

Racial and Ethnic Disparities in Opioid Access and Urine Drug Screening Among Older Patients With Poor-Prognosis Cancer Near the End of Life

PURPOSE

To characterize racial and ethnic disparities and trends in opioid access and urine drug screening (UDS) among patients dying of cancer, and to explore potential mechanisms.

METHODS

Among 318,549 non-Hispanic White (White), Black, and Hispanic Medicare decedents older than 65 years with poor-prognosis cancers, we examined 2007-2019 trends in opioid prescription fills and potency (morphine milligram equivalents [MMEs] per day [MMEDs]) near the end of life (EOL), defined as 30 days before death or hospice enrollment. We estimated the effects of race and ethnicity on opioid access, controlling for demographic and clinical factors. Models were further adjusted for socioeconomic factors including dual-eligibility status, community-level deprivation, and rurality. We similarly explored disparities in UDS.

RESULTS

Between 2007 and 2019, White, Black, and Hispanic decedents experienced steady declines in EOL opioid access and rapid expansion of UDS. Compared with White patients, Black and Hispanic patients were less likely to receive any opioid (Black, -4.3 percentage points, 95% CI, -4.8 to -3.6; Hispanic, -3.6 percentage points, 95% CI, -4.4 to -2.9) and long-acting opioids (Black, -3.1 percentage points, 95% CI, -3.6 to -2.8; Hispanic, -2.2 percentage points, 95% CI, -2.7 to -1.7). They also received lower daily doses (Black, -10.5 MMED, 95% CI, -12.8 to -8.2; Hispanic, -9.1 MMED, 95% CI, -12.1 to -6.1) and lower total doses (Black, -210 MMEs, 95% CI, -293 to -207; Hispanic, -179 MMEs, 95% CI, -217 to -142); Black patients were also more likely to undergo UDS (0.5 percentage points; 95% CI, 0.3 to 0.8). Disparities in EOL opioid access and UDS disproportionately affected Black men. Adjustment for socioeconomic factors did not attenuate the EOL opioid access disparities.

CONCLUSION

There are substantial and persistent racial and ethnic inequities in opioid access among older patients dying of cancer, which are not mediated by socioeconomic variables.

Organization and Performance of US Health Systems

IMPORTANCE

Health systems play a central role in the delivery of health care, but relatively little is known about these organizations and their performance.

OBJECTIVE

To (1) identify and describe health systems in the United States; (2) assess differences between physicians and hospitals in and outside of health systems; and (3) compare quality and cost of care delivered by physicians and hospitals in and outside of health systems.

EVIDENCE REVIEW

Health systems were defined as groups of commonly owned or managed entities that included at least 1 general acute care hospital, 10 primary care physicians, and 50 total physicians located within a single hospital referral region. They were identified using Centers for Medicare & Medicaid Services administrative data, Internal Revenue Service filings, Medicare and commercial claims, and other data. Health systems were categorized as academic, public, large for-profit, large nonprofit, or other private systems. Quality of preventive care, chronic disease management, patient experience, low-value care, mortality, hospital readmissions, and spending were assessed for Medicare beneficiaries attributed to system and nonsystem physicians. Prices for physician and hospital services and total spending were assessed in 2018 commercial claims data. Outcomes were adjusted for patient characteristics and geographic area.

FINDINGS

A total of 580 health systems were identified and varied greatly in size. Systems accounted for 40% of physicians and 84% of general acute care hospital beds and delivered primary care to 41% of traditional Medicare beneficiaries. Academic and large nonprofit systems accounted for a majority of system physicians (80%) and system hospital beds (64%). System hospitals were larger than nonsystem hospitals (67% vs 23% with >100 beds), as were system physician practices (74% vs 12% with >100 physicians). Performance on measures of preventive care, clinical quality, and patient experience was modestly higher for health system physicians and hospitals than for nonsystem physicians and hospitals. Prices paid to health system physicians and hospitals were significantly higher than prices paid to nonsystem physicians and hospitals (12%-26% higher for physician services, 31% for hospital services). Adjusting for practice size attenuated health systems differences on quality measures, but price differences for small and medium practices remained large.

CONCLUSIONS AND RELEVANCE

In 2018, health system physicians and hospitals delivered a large portion of medical services. Performance on clinical quality and patient experience measures was marginally better in systems but spending and prices were substantially higher. This was especially true for small practices. Small quality differentials combined with large price differentials suggests that health systems have not, on average, realized their potential for better care at equal or lower cost.

Health Workforce Issues More Conspicuous After Onset of COVID-19

This JAMA Forum discusses the problems facing the health care workforce in the wake of the COVID-19 pandemic, including a shortage of workers and the challenge of increasing wages, and highlights issues that policy makers and leaders may consider to address these problems.

The impact of physician-hospital integration on spending and quality of oncology care

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Background: There has been increasing hospital and health system ownership of physician practices in recent years, particularly in oncology. However, relatively little is known about how this impacts care delivery for patients with cancer, who use many hospital-based services that may be impacted by integration. We evaluated the impact of physician-hospital integration in oncology on spending and quality of care for Medicare beneficiaries with cancer. Methods: We used Medicare Fee-for-Service claims from 2005-2019 linked with a unique Health System and Provider Database, developed by National Bureau of Economic Research and Harvard University researchers, to track practice ownership relationships over time. We used a stacked event study to assess outcomes for patients three years before and after oncologists move from independent practices to hospital- or system- owned practices. We compared outcomes to a control group with oncologists who shifted from independent to hospital- or system-owned practices in later years. We focused on two cohorts of patients. The first cohort included cancer patients with presumed incident or recurrent cancer based on ≥2 visits to an oncologist and no visit in the past year. For these patients, we evaluated the impact of physician-hospital integration on the likelihood of receiving chemotherapy following the visit. The second cohort included 6-month episodes for patients receiving chemotherapy. For these patients we evaluated the impact of physician-hospital integration on spending, utilization, and quality. Quality measures included receipt of timely chemotherapy (within 60 days) following surgery, inpatient readmissions, non-use of tamoxifen + strong CYPD26 inhibitors, and end-of-life intensity of care measures. Results: There was no change in the likelihood of receiving chemotherapy with an initial oncology consultation following an oncologist’s transition to hospital-based employment. Total spending during six-month chemotherapy episodes increased by $1391 (95%CI: $465, $2316). The primary contributors to this growth were increases in spending on inpatient care, chemotherapy administration, and office visits. Spending growth, where observed, was driven primarily by higher Medicare prices for care in hospital outpatient settings. We found no positive impact of physician-hospital integration on timeliness of chemotherapy initiation, readmissions, concurrent use of tamoxifen+strong CYPD26 inhibitors, or intensity of end-of-life care. Conclusions: Physician-hospital integration resulted in higher prices and thus higher spending, but had limited impact on utilization and no detectable impacts on measures of quality. These results suggest that claims of quality improvements and concerns regarding overuse associated with physician-hospital integration may be overstated. Our results also support continued movement towards site-neutral payments.

Increases in Inpatient Psychiatry Beds Operated by Systems, For-Profits, and Chains, 2010-2016

OBJECTIVE

This study explored trends in the quantity of inpatient psychiatry beds and in facility characteristics.

METHODS

Using the National Bureau of Economic Research's Health Systems and Provider Database, the authors examined changes in the number of psychiatric facilities and beds, focusing on system ownership, profit status, facility type (general acute care versus freestanding), and affiliation with psychiatric hospital chains from 2010 to 2016.

RESULTS

The number of psychiatric beds was relatively unchanged from 2010 (N=112,182 beds) to 2016 (N=111,184). However, the number of beds operated by systems increased by 39.8% (N=15,803); for-profits, by 56.9% (N=8,572); and chains, by 16.7% (N=6,256). Net increases in beds were primarily concentrated in for-profit freestanding psychiatric hospitals. In 2016, most for-profit beds were part of chains (70.2%) and systems (61.3%).

CONCLUSIONS

Inpatient psychiatry has shifted toward increased ownership by systems, for-profits, and chains. Payers and policy makers should safeguard against profiteering, and future research should investigate the implications of these trends on quality of care.

US Trends in Opioid Access Among Patients With Poor Prognosis Cancer Near the End-of-Life

PURPOSE

Heightened regulations have decreased opioid prescribing across the United States, yet little is known about trends in opioid access among patients dying of cancer.

METHODS

Among 270,632 Medicare fee-for-service decedents with poor prognosis cancers, we used part D data to examine trends from 2007 to 2017 in opioid prescription fills and opioid potency (morphine milligram equivalents per day [MMED]) near the end-of-life (EOL), defined as the 30 days before death or hospice enrollment. We used administrative claims to evaluate trends in pain-related emergency department (ED) visits near EOL.

RESULTS

Between 2007 and 2017, the proportion of decedents with poor prognosis cancers receiving ≥ 1 opioid prescription near EOL declined 15.5% (relative percent difference [RPD]), from 42.0% (95% CI, 41.4 to 42.7) to 35.5% (95% CI, 34.9 to 36.0) and the proportion receiving ≥ 1 long-acting opioid prescription declined 36.5% (RPD), from 18.1% (95% CI, 17.6 to 18.6) to 11.5% (95% CI, 11.1 to 11.9). Among decedents receiving opioids near EOL, the mean daily dose fell 24.5%, from 85.6 MMED (95% CI, 82.9 to 88.3) to 64.6 (95% CI, 62.7 to 66.6) MMED. Overall, the total amount of opioids prescribed per decedent near EOL (averaged across those who did and did not receive an opioid) fell 38.0%, from 1,075 morphine milligram equivalents per decedent (95% CI, 1,042 to 1,109) to 666 morphine milligram equivalents per decedent (95% CI, 646 to 686). Simultaneously, the proportion of patients with pain-related ED visits increased 50.8% (RPD), from 13.2% (95% CI, 12.7 to 13.6) to 19.9% (95% CI, 19.4 to 20.4). Sensitivity analyses demonstrated similar declines in opioid utilization in the 60 and 90 days before death or hospice, and suggested that trends in opioid access were not confounded by secular trends in hospice utilization.

CONCLUSION

Opioid use among patients dying of cancer has declined substantially from 2007 to 2017. Rising pain-related ED visits suggests that EOL cancer pain management may be worsening.

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.

An algorithmic approach to reducing unexplained pain disparities in underserved populations

Underserved populations experience higher levels of pain. These disparities persist even after controlling for the objective severity of diseases like osteoarthritis, as graded by human physicians using medical images, raising the possibility that underserved patients' pain stems from factors external to the knee, such as stress. Here we use a deep learning approach to measure the severity of osteoarthritis, by using knee X-rays to predict patients' experienced pain. We show that this approach dramatically reduces unexplained racial disparities in pain. Relative to standard measures of severity graded by radiologists, which accounted for only 9% (95% confidence interval (CI), 3-16%) of racial disparities in pain, algorithmic predictions accounted for 43% of disparities, or 4.7× more (95% CI, 3.2-11.8×), with similar results for lower-income and less-educated patients. This suggests that much of underserved patients' pain stems from factors within the knee not reflected in standard radiographic measures of severity. We show that the algorithm's ability to reduce unexplained disparities is rooted in the racial and socioeconomic diversity of the training set. Because algorithmic severity measures better capture underserved patients' pain, and severity measures influence treatment decisions, algorithmic predictions could potentially redress disparities in access to treatments like arthroplasty.

Explaining The Slowdown In Medical Spending Growth Among The Elderly, 1999-2012

We examined trends in per capita spending for Medicare beneficiaries ages sixty-five and older in the United States in the period 1999-2012 to determine why spending growth has been declining since around 2005. Decomposing spending by condition, we found that half of the spending slowdown was attributable to slower growth in spending for cardiovascular diseases. Spending growth also slowed for dementia, renal and genitourinary diseases, and aftercare for people with acute illnesses. Using estimates from the medical literature of the impact of pharmaceuticals on acute disease, we found that roughly half of the reduction in major cardiovascular events was attributable to medications controlling cardiovascular risk factors. Despite this substantial cost-saving improvement in cardiovascular health, additional opportunities remain to lower spending through disease prevention and control.

Contributions Of Public Health, Pharmaceuticals, And Other Medical Care To US Life Expectancy Changes, 1990-2015

Life expectancy in the US increased 3.3 years between 1990 and 2015, but the drivers of this increase are not well understood. We used vital statistics data and cause-deletion analysis to identify the conditions most responsible for changing life expectancy and quantified how public health, pharmaceuticals, other (nonpharmaceutical) medical care, and other/unknown factors contributed to the improvement. We found that twelve conditions most responsible for changing life expectancy explained 2.9 years of net improvement (85 percent of the total). Ischemic heart disease was the largest positive contributor to life expectancy, and accidental poisoning or drug overdose was the largest negative contributor. Forty-four percent of improved life expectancy was attributable to public health, 35 percent was attributable to pharmaceuticals, 13 percent was attributable to other medical care, and -7 percent was attributable to other/unknown factors. Our findings emphasize the crucial role of public health advances, as well as pharmaceutical innovation, in explaining improving life expectancy.

Attributing medical spending to conditions: A comparison of methods

To understand the cost burden of medical care it is essential to partition medical spending into conditions. Two broad strategies have been used to measure disease-specific spending. The first attributes each medical claim to the condition that physicians list as its cause. The second decomposes total spending for a person over a year to their cumulative set of health conditions. Traditionally, this has been done through regression analysis. This paper has two contributions. First, we develop a new cost attribution method to attribute spending to conditions using a more flexible attribution approach, based on propensity score analysis. Second, we compare the propensity score approach to the claims-based approach and the regression approach in a common set of beneficiaries age 65 and older in the 2009 Medicare Current Beneficiary Survey. Our estimates show that the three methods have important differences in spending allocation and that the propensity score model likely offers the best theoretical and empirical combination.

U.S. trends and racial/ethnic disparities in opioid access among patients with poor prognosis cancer at the end of life (EOL)

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Background: Heightened US opioid regulations may limit advanced cancer patients’ access to effective pain management, particularly for racial/ethnic minority and other vulnerable populations. We examined trends in opioid access, disparities in access, and pain-related emergency department (ED) visits among cancer patients near end of life (EOL). Methods: Using a 20% random sample of Medicare FFS beneficiaries, we identified 243,124 patients with poor prognosis cancers who died between 2007-2016. We examined trends in outpatient opioid prescription fills and pain-related ED visits near EOL (30 days prior to death or hospice enrollment), for the overall cohort and by race (white, black, other). Per-capita opioid supply by state was obtained from the federal Drug Enforcement Agency ARCOS database. Geographic fixed-effects models examined predictors of opioid use near EOL, opioid dose in morphine milligram equivalents (MMEs), and pain-related ED visits, adjusted for patient demographic and clinical characteristics, state, opioid supply, and year. Results: From 2007-2016 the proportion of patients with poor prognosis cancers filling an opioid prescription near EOL fell from 41.7% to 35.7%, with greater decrements among blacks (39.3% to 29.8%) than whites (42.2% to 36.5%) and other races (38.2% to 32.4%). The proportion of patients receiving long-acting opioids near EOL fell from 17% to 12% overall (15% to 9% among blacks). Among patients receiving EOL opioids, the median daily dose fell from 40MMEs (IQR 16.5-98.0) to 30MMEs (IQR 15.0–78.8). In adjusted analyses, blacks were less likely than whites to receive EOL opioids (AOR 0.85; 95% CI, 0.80 to 0.91) and on average received 10MMEs less per day (b -9.9; 95% CI -15.7 to -4.2). Patients of other race were also less likely to receive EOL opioids (AOR 0.92; 95% CI, 0.85-0.95), although their dose did not differ significantly from whites. Rates of pain-related ED visits near EOL increased from 13.2% to 18.8% over the study period. In adjusted analyses, blacks were more likely than whites to have pain-related ED visits (AOR 1.29, 95% CI, 1.16-1.37) near death, as were those of other races (AOR 1.30; 95% CI, 1.17-1.37). Conclusions: While lawmakers have sought to mitigate the impact of opioid regulations upon cancer patients, access to EOL opioids have decreased substantially over time with concomitant increases in pain-related ED visits. There are significant racial/ethnic disparities in opioid access, with blacks receiving fewer opioids at lower doses and having more ED-based care for pain near EOL.

Potential impact of Affordable Care Act-related insurance expansion on trauma care reimbursement

BACKGROUND

Nearly one quarter of trauma patients are uninsured and hospitals recoup less than 20% of inpatient costs for their care. This study examines changes to hospital reimbursement for inpatient trauma care if the full coverage expansion provisions of the Affordable Care Act (ACA) were in effect.

METHODS

We abstracted nonelderly adults (ages 18-64 years) admitted for trauma from the Nationwide Inpatient Sample during 2010-the last year before most major ACA coverage expansion policies. We calculated national and facility-level reimbursements and trauma-related contribution margins using Nationwide Inpatient Sample-supplied cost-to-charge ratios and published reimbursement rates for each payer type. Using US census data, we developed a probabilistic microsimulation model to determine the proportion of pre-ACA uninsured trauma patients that would be expected to gain private insurance, Medicaid, or remain uninsured after full implementation of the ACA. We then estimated the impact of these coverage changes on national and facility-level trauma reimbursement for this population.

RESULTS

There were 145,849 patients (representing 737,852 patients nationwide) included. National inpatient trauma costs for patients aged 18 years to 64 years totaled US $14.8 billion (95% confidence interval [CI], 12.5,17.1). Preexpansion reimbursements totaled US $13.7 billion (95% CI, 10.8-14.7), yielding a national margin of -7.9% (95% CI, -10.6 to -5.1). Postexpansion projected reimbursements totaled US $15.0 billion (95% CI, 12.7-17.3), increasing the margin by 9.3 absolute percentage points to +1.4% (95% CI, -0.3 to +3.2). Of the 263 eligible facilities, 90 (34.2%) had a positive trauma-related contribution margin in 2010, which increased to 171 (65.0%) using postexpansion projections. Those facilities with the highest proportion of uninsured and racial/ethnic minorities experienced the greatest gains.

CONCLUSION

Health insurance coverage expansion for uninsured trauma patients has the potential to increase national reimbursement for inpatient trauma care by over one billion dollars and nearly double the proportion of hospitals with a positive margin for trauma care. These data suggest that insurance coverage expansion has the potential to improve trauma centers' financial viability and their ability to provide care for their communities.

LEVEL OF EVIDENCE

Economic analysis, level II.

Early death after discharge from emergency departments: analysis of national US insurance claims data

OBJECTIVE

 To measure incidence of early death after discharge from emergency departments, and explore potential sources of variation in risk by measurable aspects of hospitals and patients.

DESIGN

 Retrospective cohort study.

SETTING

 Claims data from the US Medicare program, covering visits to an emergency department, 2007-12.

PARTICIPANTS

 Nationally representative 20% sample of Medicare fee for service beneficiaries. As the focus was on generally healthy people living in the community, patients in nursing facilities, aged ≥90, receiving palliative or hospice care, or with a diagnosis of a life limiting illnesses, either during emergency department visits (for example, myocardial infarction) or in the year before (for example, malignancy) were excluded.

MAIN OUTCOME MEASURE

 Death within seven days after discharge from the emergency department, excluding patients transferred or admitted as inpatients.

RESULTS

 Among discharged patients, 0.12% (12 375/10 093 678, in the 20% sample over 2007-12) died within seven days, or 10 093 per year nationally. Mean age at death was 69. Leading causes of death on death certificates were atherosclerotic heart disease (13.6%), myocardial infarction (10.3%), and chronic obstructive pulmonary disease (9.6%). Some 2.3% died of narcotic overdose, largely after visits for musculoskeletal problems. Hospitals in the lowest fifth of rates of inpatient admission from the emergency department had the highest rates of early death (0.27%)-3.4 times higher than hospitals in the highest fifth (0.08%)-despite the fact that hospitals with low admission rates served healthier populations, as measured by overall seven day mortality among all comers to the emergency department. Small increases in admission rate were linked to large decreases in risk. In multivariate analysis, emergency departments that saw higher volumes of patients (odds ratio 0.84, 95% confidence interval 0.81 to 0.86) and those with higher charges for visits (0.75, 0.74 to 0.77) had significantly fewer deaths. Certain diagnoses were more common among early deaths compared with other emergency department visits: altered mental status (risk ratio 4.4, 95% confidence interval 3.8 to 5.1), dyspnea (3.1, 2.9 to 3.4), and malaise/fatigue (3.0, 2.9 to 3.7).

CONCLUSIONS

 Every year, a substantial number of Medicare beneficiaries die soon after discharge from emergency departments, despite no diagnosis of a life limiting illnesses recorded in their claims. Further research is needed to explore whether these deaths were preventable.

Changes in Hospital-Physician Affiliations in U.S. Hospitals and Their Effect on Quality of Care

BACKGROUND

Growing evidence shows that hospitals are increasingly employing physicians.

OBJECTIVE

To examine changes in U.S. acute care hospitals that reported employment relationships with their physicians and to determine whether quality of care improved after the hospitals switched to this integration model.

DESIGN

Retrospective cohort study of U.S. acute care hospitals between 2003 and 2012.

SETTING

U.S. nonfederal acute care hospitals.

PARTICIPANTS

803 switching hospitals compared with 2085 nonswitching control hospitals matched for year and region.

INTERVENTION

Hospitals' conversion to an employment relationship with any of their privileged physicians.

MEASUREMENTS

Risk-adjusted hospital-level mortality rates, 30-day readmission rates, length of stay, and patient satisfaction scores for common medical conditions.

RESULTS

In 2003, approximately 29% of hospitals employed members of their physician workforce, a number that rose to 42% by 2012. Relative to regionally matched controls, switching hospitals were more likely to be large (11.6% vs. 7.1%) or major teaching hospitals (7.5% vs. 4.5%) and less likely to be for-profit institutions (8.8% vs. 19.9%) (all P values <0.001). Up to 2 years after conversion, no association was found between switching to an employment model and improvement in any of 4 primary composite quality metrics.

LIMITATIONS

The measure of integration used depends on responses to the American Hospital Association annual questionnaire, yet this measure has been used by others to examine effects of integration. The study examined performance up to 2 years after evidence of switching to an employment model; however, beneficial effects may have taken longer to appear.

CONCLUSION

During the past decade, hospitals have increasingly become employers of physicians. The study's findings suggest that physician employment alone probably is not a sufficient tool for improving hospital care.

PRIMARY FUNDING SOURCE

Agency for Healthcare Research and Quality and National Science Foundation Graduate Research Fellowship.

Physician Characteristics Strongly Predict Patient Enrollment In Hospice

Individual physicians are widely believed to play a large role in patients' decisions about end-of-life care, but little empirical evidence supports this view. We developed a novel method for measuring the relationship between physician characteristics and hospice enrollment, in a nationally representative sample of Medicare patients. We focused on patients who died with a diagnosis of poor-prognosis cancer in the period 2006-11, for whom palliative treatment and hospice would be considered the standard of care. We found that the proportion of a physician's patients who were enrolled in hospice was a strong predictor of whether or not that physician's other patients would enroll in hospice. The magnitude of this association was larger than that of other known predictors of hospice enrollment that we examined, including patients' medical comorbidity, age, race, and sex. Patients cared for by medical oncologists and those cared for in not-for-profit hospitals were significantly more likely than other patients to enroll in hospice. These findings suggest that physician characteristics are among the strongest predictors of whether a patient receives hospice care-which mounting evidence indicates can improve care quality and reduce costs. Interventions geared toward physicians, both by specialty and by previous history of patients' hospice enrollment, may help optimize appropriate hospice use.