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Among a group of primary care accountable care organizations, patients with hypertension were 50% less likely to have a blood pressure recorded in April compared with February.

Importance Efforts to track the severity and public health impact of coronavirus disease 2019 (COVID-19) in the United States have been hampered by state-level differences in diagnostic test availability, differing strategies for prioritization of individuals for testing, and delays between testing and reporting. Evaluating unexplained increases in deaths due to all causes or attributed to nonspecific outcomes, such as pneumonia and influenza, can provide a more complete picture of the burden of COVID-19. Objective To estimate the burden of all deaths related to COVID-19 in the United States from March to May 2020. Design, Setting, and Population This observational study evaluated the numbers of US deaths from any cause and deaths from pneumonia, influenza, and/or COVID-19 from March 1 through May 30, 2020, using public data of the entire US population from the National Center for Health Statistics (NCHS). These numbers were compared with those from the same period of previous years. All data analyzed were accessed on June 12, 2020. Main Outcomes and Measures Increases in weekly deaths due to any cause or deaths due to pneumonia/influenza/COVID-19 above a baseline, which was adjusted for time of year, influenza activity, and reporting delays. These estimates were compared with reported deaths attributed to COVID-19 and with testing data. Results There were approximately 781 000 total deaths in the United States from March 1 to May 30, 2020, representing 122 300 (95% prediction interval, 116 800-127 000) more deaths than would typically be expected at that time of year. There were 95 235 reported deaths officially attributed to COVID-19 from March 1 to May 30, 2020. The number of excess all-cause deaths was 28% higher than the official tally of COVID-19–reported deaths during that period. In several states, these deaths occurred before increases in the availability of COVID-19 diagnostic tests and were not counted in official COVID-19 death records. There was substantial variability between states in the difference between official COVID-19 deaths and the estimated burden of excess deaths. Conclusions and Relevance Excess deaths provide an estimate of the full COVID-19 burden and indicate that official tallies likely undercount deaths due to the virus. The mortality burden and the completeness of the tallies vary markedly between states.

This mathematical modeling study examines the potential for contract tracing to reduce the spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in the context of reduced physical distancing under different assumptions for case detection, tracing, and quarantine efficacy.

Contact tracing has been recommended as a critical component of containment strategies for COVID-19. We used a simple epidemic model to evaluate how contact tracing might enable modification of current physical distancing restrictions. Testing and tracing coverage need to exceed 50% to see substantial gains; if both are below 50%, contact tracing does not reduce transmission by more than 10%. With 90% testing and tracing as well as high isolation and quarantine efficacy, contact tracing could reduce overall transmission by >45%, which would allow for partial loosening of physical distancing measures. Benefits of contact tracing could be enhanced by testing all contacts rather than only those with symptoms and by policies to support high adherence to voluntary isolation and quarantine.

BackgroundEfforts to track the severity and public health impact of the novel coronavirus, COVID-19, in the US have been hampered by testing issues, reporting lags, and inconsistency between states.Evaluating unexplained increases in deaths attributed to broad outcomes, such as pneumonia and influenza (P&I) or all causes, can provide a more complete and consistent picture of the burden caused by COVID-19.MethodsWe evaluated increases in the occurrence of deaths due to P&I above a seasonal baseline (adjusted for influenza activity) or due to any cause across the United States in February and March 2020. These estimates are compared with reported deaths due to COVID-19 and with testing data.ResultsThere were notable increases in the rate of death due to P&I in February and March 2020. In a number of states, these deaths pre-dated increases in COVID-19 testing rates and were not counted in official records as related to COVID-19. There was substantial variability between states in the discrepancy between reported rates of death due to COVID-19 and the estimated burden of excess deaths due to P&I. The increase in all-cause deaths in New York and New Jersey is 1.5-3 times higher than the official tally of COVID-19 confirmed deaths or the estimated excess death due to P&I.ConclusionsExcess P&I deaths provide a conservative estimate of COVID-19 burden and indicate that COVID-19-related deaths are missed in locations with inadequate testing or intense pandemic activity.RESEARCH IN CONTEXTEvidence before this studyDeaths due to the novel coronavirus, COVID-19, have been increasing sharply in the United States since mid-March. However, efforts to track the severity and public health impact of COIVD-19 in the US have been hampered by testing issues, reporting lags, and inconsistency between states. As a result, the reported number of deaths likely represents an underestimate of the true burden.Added Value of this studyWe evaluate increases in deaths due to pneumonia across the United States and relate these increases to the number of reported deaths due to COVID-19 in different states and evaluate the trajectories of these increases in relation to the volume of testing and to indicators of COVID-19 morbidity. This provides a more complete picture of mortality due to COVID-19 in the US and demonstrates how delays in testing led to many coronavirus deaths not being counted in certain states.Implications of all the available evidenceThe number of deaths reported to be due to COVID-19 represents just a fraction of the deaths linked to the pandemic. Monitoring trends in deaths due to pneumonia and all-causes provides a more complete picture of the tool of the disease.

Although use of the Medicare Annual Wellness Visit (AWV) is increasing nationally, it remains unclear whether it can help contain healthcare costs and improve quality. In the context of 2 primary care physician-led accountable care organizations (ACOs), we tested the hypothesis that AWVs can improve healthcare costs and clinical quality.A retrospective cohort study using propensity score matching and quasi-experimental difference-in-differences regression models comparing the differential changes in cost, emergency department (ED) visits, and hospitalizations for those who received an AWV versus those who did not from before until after the AWV. Logistic regressions were used for quality measures.Between 2014 and 2016, we examined the association of an AWV with healthcare costs, ED visits, hospitalizations, and clinical quality measures. The sample included Medicare beneficiaries attributed to providers across 44 primary care clinics participating in 2 ACOs.Among 8917 Medicare beneficiaries, an AWV was associated with significantly reduced spending on hospital acute care and outpatient services. Patients who received an AWV in the index month experienced a 5.7% reduction in adjusted total healthcare costs over the ensuing 11 months, with the greatest effect seen for patients in the highest hierarchical condition category risk quartile. AWVs were not associated with ED visits or hospitalizations. Beneficiaries who had an AWV were also more likely to receive recommended preventive clinical services.In a setting that prioritizes care coordination and utilization management, AWVs have the potential to improve healthcare quality and reduce cost.

Eight years ago, the HITECH Act launched an ambitious effort to modernize the U.S. health IT infrastructure. But the culture surrounding access to and sharing of information still needs to change to promote the seamless and secure flow of electronic information.

Background: Adoption and implementation of electronic health records (EHRs) has not been without challenges as it infuses technology into what has been a historically manual process of recording patient information. In an effort to identify these challenges, the Office of the National Coordinator for Health Information Technology leveraged the Regional Extension Center population of over 140,000 providers to develop a structured way to track challenges to EHR adoption and Meaningful Use (MU). Objectives: This report summarizes challenges to EHR adoption and MU based on nationwide data supplied by 55 Regional Extension Centers reporting over 19,000 issues representing over 43,000 unique health care providers. Practices were grouped on the basis of their place in the lifecycle of EHR adoption and MU achievement. Results: Provider engagement and administrative issues were among the more common issues reported across all cohorts. The most challenging MU measure was the clinical summaries measure, but MU Measure challenges varied by practice setting. Conclusions: EHR adoption and MU challenges are unique to practice setting and stage of the adoption process.

As Liaw et al report in this month’s issue of Annals of Family Medicine , solo and small practices are under pressure from market forces propelling practice consolidation.[1][1] However, more than one-half of all family medicine physicians—and one-half of recent graduates—are still caring for

Expanding the use of interoperable electronic health record (EHR) systems to improve health care delivery is a national policy priority. We used the 2010-12 National Ambulatory Medical Care Survey--Electronic Health Records Survey to examine which physicians in what types of practices are implementing the systems, and how they are using them. We found that 72 percent of physicians had adopted some type of system and that 40 percent had adopted capabilities required for a basic EHR system. The highest relative increases in adoption were among physicians with historically low adoption levels, including older physicians and those working in solo practices or community health centers. As of 2012, physicians in rural areas had higher rates of adoption than those in large urban areas, and physicians in counties with high rates of poverty had rates of adoption comparable to those in areas with less poverty. However, small practices continued to lag behind larger practices. Finally, the majority of physicians who adopted the EHR capabilities required to obtain federal financial incentives used the capabilities routinely, with few differences across physician groups.

The US health care system is in the midst of an enormous change in the way health care providers and hospitals document, monitor, and share information about health and care delivery. Part of this transition involves a wholesale, but currently uneven, shift from paper-based records to electronic health record (EHR) systems. We used the most recent longitudinal survey of US hospitals to track how they are adopting and using EHR systems. Only 44 percent of hospitals report having and using what we define as at least a basic EHR system. And although 42.2 percent meet all of the federal stage 1 "meaningful-use" criteria, only 5.1 percent could meet the broader set of stage 2 criteria. Large urban hospitals continue to outpace rural and nonteaching hospitals in adopting EHR systems. The increase in adoption overall suggests that the positive and negative financial incentives currently in place across the US health care system are working as intended. However, achieving a nationwide health information technology infrastructure may require efforts targeted at smaller and rural hospitals.

Patient-centered care is considered one pillar of a high-performing, high-quality health care system. It is a key component of many efforts to transform care and achieve better population health. Expansion of health information technology and consumer e-health tools--electronic tools and services such as secure e-mail messaging between patients and providers, or mobile health apps--have created new opportunities for individuals to participate actively in monitoring and directing their health and health care. The Office of the National Coordinator for Health Information Technology in the Department of Health and Human Services leads the strategy to increase electronic access to health information, support the development of tools that enable people to take action with that information, and shift attitudes related to the traditional roles of patients and providers. In this article we review recent evidence in support of consumer e-health and present the federal strategy to promote advances in consumer e-health to increase patient engagement, improve individual health, and achieve broader health care system improvements.

The U.S. health care system does not work as well as it could, or should. Prices are high and vary in seemingly incoherent ways, yet quality of care is uneven, and the system lacks the innovation and dynamism that characterizes much of the rest of our economy. The dearth of competition in our health care markets is a key reason for this dysfunction. There is a growing understanding that comprehensive efforts to control health care costs and improve the quality of care must address the functioning of the markets that undergird the health care system and the prices paid to providers. Ensuring that markets function efficiently is central to an effective health system that provides high quality, accessible, and affordable care. A large body of evidence shows that patients, employers, and private insurers pay more for health care in highly consolidated provider markets — for instance, where only one or two hospital systems exist. Higher health care costs lead to higher premiums, making insurance more expensive and less affordable. Even in public programs, such as Medicare, a lack of competition among providers is associated with lower quality care. The same is true of health insurance — it has been extensively documented that less competition leads to higher premiums. Each of us has been concerned about competition for quite some time. Earlier this fall, we convened a meeting supported by the Robert Wood Johnson Foundation, and co-sponsored by the American Enterprise Institute, the Brookings Institution, and Carnegie Mellon’s Heinz College, to formulate ideas for actionable policies that public and private stakeholders can implement to improve the functioning of health care markets. Approximately 40 academics, industry stakeholders, and federal and state government officials participated in the meeting, which produced focused, practical proposals. This white paper reflects the authors’ recommendations, taking the discussion at the meeting into account, without any attempt either to summarize the meeting or to associate the participants with these views. We propose a new “competition policy” for health care that involves multiple actors at the federal and the state level: the White House and state governors, federal and state executive agencies, and federal and state legislatures, as well as the federal and state antitrust enforcement agencies traditionally focused on competition. Inattention to the impact of policies on consolidation may have unwittingly put the U.S. on a path to less competition in health care markets; addressing it will require broader action and attention beyond antitrust enforcement as well. Pursuing this agenda will allow health care markets to function more efficiently, leading to higher quality, more accessible, and lower-cost care. We focus on policies to enable and support competition by health care organizations. We propose specific, actionable policies to maintain and enhance the competitiveness of health care markets, promote entry by new competitors and remove barriers to entry, and prevent anticompetitive practices. We think these policies can have an immediate and meaningful impact. We note that these are non-partisan policies that can elicit support from across the political spectrum.

In this article, we seek to provide the first detailed description of a Medicare Shared Savings Program (MSSP) accountable care organization (ACO)'s actions and results to help increase understanding of the challenges and opportunities facing ACOs, and in particular, those comprised of a network of independent practices. Whether ACOs have been successful in delivering value has been the subject of much debate and speculation. What has been missing from this discussion is a look at the program from the frontlines and those who are launching and running MSSP ACOs. We hope to fill that gap.

Electronic health information exchange addresses a critical need in the US health care system to have information follow patients to support patient care. Today little information is shared electronically, leaving doctors without the information they need to provide the best care. With payment reforms providing a strong business driver, the demand for health information exchange is poised to grow. The Office of the National Coordinator for Health Information Technology, Department of Health and Human Services, has led the process of establishing the essential building blocks that will support health information exchange. Over the coming year, this office will develop additional policies and standards that will make information exchange easier and cheaper and facilitate its use on a broader scale.

Objective: To assess the performance of electronic health record data for syndromic surveillance and to assess the feasibility of broadly distributed surveillance. Design: Two systems were developed to identify influenza-like illness and gastrointestinal infectious disease in ambulatory electronic health record data from a network of community health centers. The first system used queries on structured data and was designed for this specific electronic health record. The second used natural language processing of narrative data, but its queries were developed independently from this health record. Both were compared to influenza isolates and to a verified emergency department chief complaint surveillance system. Measurements: Lagged cross-correlation and graphs of the three time series. Results: For influenza-like illness, both the structured and narrative data correlated well with the influenza isolates and with the emergency department data, achieving cross-correlations of 0.89 (structured) and 0.84 (narrative) for isolates and 0.93 and 0.89 for emergency department data, and having similar peaks during influenza season. For gastrointestinal infectious disease, the structured data correlated fairly well with the emergency department data (0.81) with a similar peak, but the narrative data correlated less well (0.47). Conclusions: It is feasible to use electronic health records for syndromic surveillance. The structured data performed best but required knowledge engineering to match the health record data to the queries. The narrative data illustrated the potential performance of a broadly disseminated system and achieved mixed results.

The Massachusetts eHealth Collaborative and the New York City Primary Care Information Project have provided financial subsidies and extensive support to help hundreds of independent medical practices successfully adopt electronic health records. Their efforts address overcoming key barriers such as the amount of start-up funds needed, productivity lost during implementation, and the difficulty of choosing the right system. Their approaches differ: the Massachusetts project emphasizes continuity of care within selected communities; New York emphasizes improvements in preventive care and chronic disease management across a population. Both, however, offer valuable insights that can be applied elsewhere.

In disease surveillance, there are often many different data sets or data groupings for which we wish to do surveillance. If each data set is analysed separately rather than combined, the statistical power to detect an outbreak that is present in all data sets may suffer due to low numbers in each. On the other hand, if the data sets are added by taking the sum of the counts, then a signal that is primarily present in one data set may be hidden due to random noise in the other data sets. In this paper, we present an extension of the spatial and space-time scan statistic that simultaneously incorporates multiple data sets into a single likelihood function, so that a signal is generated whether it occurs in only one or in multiple data sets. This is done by defining the combined log likelihood as the sum of the individual log likelihoods for those data sets for which the observed case count is more than the expected. We also present another extension, where the concept of combining likelihoods from different data sets is used to adjust for covariates. Using data from the National Bioterrorism Syndromic Surveillance Demonstration Project, we illustrate the new method using physician telephone calls, regular physician visits and urgent care visits by Harvard Pilgrim Health Care members cared for by Harvard Vanguard Medical Associates, a large multi-specialty group practice in Massachusetts. For upper and lower gastrointestinal (GI) illness, there were on average 20 telephone calls, nine urgent care visits and 22 regular physician visits per day. The strongest signal was generated by a single data set and due to a familial outbreak of pinworm disease. The second and third strongest signals were generated by the combined strength of two of the three data sets.

Past research has shown that women who either have sex with women or who identify as lesbian access less preventive health care than other women. However, previous studies have generally relied on convenience samples and have not examined the multiple associations of sexual identity, behavior and health care access/utilization. Unlike other studies, we used a multi-lingual population-based survey in New York City to examine the use of Pap tests and mammograms, as well as health care coverage and the use of primary care providers, among women who have sex with women and by sexual identity status. We found that women who had sex with women (WSW) were less likely to have had a Pap test in the past 3 years (66 vs. 80%, p

Objectives. We investigated increases in diarrheal illness detected through syndromic surveillance after a power outage in New York City on August 14, 2003.Methods. The New York City Department of Health and Mental Hygiene uses emergency department, pharmacy, and absentee data to conduct syndromic surveillance for diarrhea. We conducted a case–control investigation among patients presenting during August 16 to 18, 2003, to emergency departments that participated in syndromic surveillance. We compared risk factors for diarrheal illness ascertained through structured telephone interviews for case patients presenting with diarrheal symptoms and control patients selected from a stratified random sample of nondiarrheal patients.Results. Increases in diarrhea were detected in all data streams. Of 758 patients selected for the investigation, 301 (40%) received the full interview. Among patients 13 years and older, consumption of meat (odds ratio [OR]=2.7, 95% confidence interval [CI]=1.2, 6.1) and seafood (OR=4.8; 95% CI=1.6, 14) between the power outage and symptom onset was associated with diarrheal illness.Conclusions. Diarrhea may have resulted from consumption of meat or seafood that spoiled after the power outage. Syndromic surveillance enabled prompt detection and systematic investigation of citywide illness that would otherwise have gone undetected.

Objectives. We sought to determine the impact of comprehensive tobacco control measures in New York City. Methods. In 2002, New York City implemented a tobacco control strategy of (1) increased cigarette excise taxes; (2) legal action that made virtually all work-places, including bars and restaurants, smoke free; (3) increased cessation services, including a large-scale free nicotine-patch program; (4) education; and (5) evaluation. The health department also began annual surveys on a broad array of health measures, including smoking. Results. From 2002 to 2003, smoking prevalence among New York City adults decreased by 11% (from 21.6% to 19.2%, approximately 140000 fewer smokers). Smoking declined among all age groups, race/ethnicities, and education levels; in both genders; among both US-born and foreign-born persons; and in all 5 boroughs. Increased taxation appeared to account for the largest proportion of the decrease; however, between 2002 and 2003 the proportion of cigarettes purchased outside New York City doubled, reducing the effective price increase by a third. Conclusions. Concerted local action can sharply reduce smoking prevalence. However, further progress will require national action, particularly to increase cigarette taxes, reduce cigarette tax evasion, expand education and cessation services, and limit tobacco marketing.

To inform New York City's (NYC's) tobacco control program, we identified the neighborhoods with the highest smoking rates, estimated the burden of second-hand smoke exposure, assessed the early response to state taxation, and examined cessation practices. We used a stratified random design to conduct a digit-dialed telephone survey in 2002 among 9,674 New York City adults. Our main outcome measures included prevalence of cigarette smoking, exposure to second-hand smoke, the response of smokers to state tax increases, and cessation practices. Even after controlling for sociodemographic factors (age, race/ethnicity, income, education, marital status, employment status, and foreign-born status) smoking rates were highest in Central Harlem and in the South Bronx. Sixteen percent of nonsmokers reported frequent exposure to second-hand smoke at home or in a workplace. Among smokers with a child with asthma, only 33% reported having a no-smoking policy in their homes. More than one fifth of smokers reported reducing the number of cigarettes they smoked in response to the state tax increase. Of current smokers who tried to quit, 65% used no cessation aid. These data were used to inform New York City's smoke-free legislation, taxation, public education, and a free nicotine patch give-away program. In conclusion, large, local surveys can provide essential data to effectively advocate for, plan, implement, and evaluate a comprehensive tobacco control program.

Background Despite the provisions of a Smoke-Free Air Act (SFAA) enacted in 1995, more than 415,000 non-smoking New York City workers reported exposure to second-hand smoke in the workplace all or most of the time in 2002. Continued exposure to second-hand smoke in New York City prompted a renewed debate about a broader smoke-free air law. Methods The approach taken by the New York City Department of Health and Mental Hygiene to make the case for workplace protection from second-hand smoke, counter the opposition's arguments, and ultimately win the support of policymakers and the public for comprehensive smoke-free workplace legislation is described. Results On December 30, 2002, New York City's Mayor signed the SFAA of 2002 into law, making virtually all workplaces, including restaurants and bars, smoke-free. Conclusions Proponents for a stronger law prevailed by defining greater protection from second-hand smoke as a matter of worker health and safety. Efforts to enact smoke-free workplace laws will inevitably encounter strong opposition, with the most common argument being that smoke-free measures will harm businesses. These challenges, however, can be effectively countered and public support for these measures is likely to increase over time by focusing the debate on worker protection from second-hand smoke exposure on the job. Am. J. Ind. Med. 46:188–195, 2004. © 2004 Wiley-Liss, Inc.

Syndromic surveillance refers to methods relying on detection of individual and population health indicators that are discernible before confirmed diagnoses are made. In particular, prior to the laboratory confirmation of an infectious disease, ill persons may exhibit behavioral patterns, symptoms, signs, or laboratory findings that can be tracked through a variety of data sources. Syndromic surveillance systems are being developed locally, regionally, and nationally. The efforts have been largely directed at facilitating the early detection of a covert bioterrorist attack, but the technology may also be useful for general public health, clinical medicine, quality improvement, patient safety, and research. This report, authored by developers and methodologists involved in the design and deployment of the first wave of syndromic surveillance systems, is intended to serve as a guide for informaticians, public health managers, and practitioners who are currently planning deployment of such systems in their regions.

A system designed to rapidly identify an infectious disease outbreak or bioterrorism attack and provide important demographic and geographic information is lacking in most health departments nationwide. The Department of Defense Global Emerging Infections System sponsored a meeting and workshop in May 2000 in which participants discussed prototype systems and developed recommendations for new surveillance systems. The authors provide a summary of the group’s findings, including expectations and recommendations for new surveillance systems. The consensus of the group was that a nationally led effort in developing health indicator surveillance methods is needed to promote effective, innovative systems.

An early warning system for West Nile virus (WNV) outbreaks could provide a basis for targeted public education and surveillance activities as well as more timely larval and adult mosquito control. We adapted the spatial scan statistic for prospective detection of infectious disease outbreaks, applied the results to data on dead birds reported from New York City in 2000, and reviewed its utility in providing an early warning of WNV activity in 2001. Prospective geographic cluster analysis of dead bird reports may provide early warning of increasing viral activity in birds and mosquitoes, allowing jurisdictions to triage limited mosquito-collection and laboratory resources and more effectively prevent human disease caused by the virus. This adaptation of the scan statistic could also be useful in other infectious disease surveillance systems, including those for bioterrorism.

After the 2001 World Trade Center disaster, the New York City Department of Health was under heightened alert for bioterrorist attacks in the city. An emergency department (ED) syndromic surveillance system was implemented with the assistance of the Centers for Disease Control and Prevention to ensure early recognition of an increase or clustering of disease syndromes that might represent a disease outbreak, whether natural or intentional. The surveillance system was based on data collected 7 days a week at area EDs. Data collected were translated into syndromes, entered into an electronic database, and analyzed for aberrations in space and time within 24 hours. From September 14-27, personnel were stationed at 15 EDs on a 24-hour basis (first staffing period); from September 29-October 12, due to resource limitations, personnel were stationed at 12 EDs on an 18-hour basis (second staffing period). A standardized form was used to obtain demographic information and classify each patient visit into 12 syndrome categories. Seven of these represented early manifestations of bioterrorist agents. Data transfer and analysis for time and space clustering (alarms) by syndrome and age occurred daily. Retrospective analyses examined syndrome trends, differences in reporting between staffing periods, and the staff's experience during the project. A total of 67,536 reports were received. The system captured 83.9% of patient visits during the first staffing period, and 60.8% during the second staffing period (P0.01). Five syndromes each accounted for more than 1% of visits: trauma, asthma, gastrointestinal illness, upper/lower respiratory infection with fever, and anxiety. Citywide temporal alarms occurred eight times for three of the major bioterrorism-related syndromes. Spatial clustering alarms occurred 16 times by hospital location and 9 times by ZIP code for the same three syndromes. No outbreaks were detected. On-site staffing to facilitate data collection and entry, supported by daily analysis of ED visits, is a feasible short-term approach to syndromic surveillance during high-profile events. The resources required to operate such a system, however, cannot be sustained for the long term. This system was changed to an electronic-based ED syndromic system using triage log data that remains in operation.

The distribution of human risk for West Nile virus was determined by spatial analysis of the initial case distribution for the New York City area in 1999 using remote sensing and geographic information system technologies. Cluster analysis revealed the presence of a statistically significant grouping of cases, which also indicates the area of probable virus introduction. Within the cluster, habitat suitability for potentially infective adult mosquitoes was measured by the amount of vegetation cover using satellite imagery. Logistic regression analysis revealed satellite-derived vegetation abundance to be significantly and positively associated with the presence of human cases. The logistic model was used to estimate the spatial distribution of human risk for West Nile virus throughout New York City. Accuracy of the resulting risk map was cross-validated using virus-positive mosquito sample sites. These new epidemiological methods aid in rapid entry point identification and spatial prediction of human risk of infection for introduced vector-borne pathogens.

Many studies have examined trends toward increasing consolidation of physician practices and hospitals in the US health care system and the negative effects of decreased competition on the quality of patient care and health care costs.1 Since 2010, there have been 561 hospital mergers,2 and nearly half of hospital markets are highly concentrated.3 Independent physician practice has declined; 33% of 929 419 active physicians in 2013 were employed by hospitals4 and many more are in affiliate relationships. A recent article acknowledged that there is little evidence of the promised benefits of such consolidation to patients or society, and it called on the presidential administration to “ensure that we have a dynamic health care marketplace.”5

Evidence supports the potential for e-prescribing to reduce the incidence of adverse drug events (ADEs) in hospital-based studies, but studies in the ambulatory setting have not used occurrence of ADE as their outcome. Using the “prescription origin code” in 2011 Medicare Part D prescription drug events files, the authors investigate whether physicians who meet the meaningful use stage 2 threshold for e-prescribing (≥50% of prescriptions e-prescribed) have lower rates of ADEs among their diabetic patients. Risk of any patient with diabetes in the provider’s panel having an ADE from anti-diabetic medications was modeled adjusted for prescriber and patient panel characteristics. Physician e-prescribing to Medicare beneficiaries was associated with reduced risk of ADEs among their diabetes patients (Odds Ratio: 0.95; 95% CI, 0.94-0.96), as were several prescriber and panel characteristics. However, these physicians treated fewer patients from disadvantaged populations.