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Paragangliomas are extremely rare neuroendocrine tumors. We report a case of a 44-year-old man with hypertension who presented a tumoral mass located retroperitoneally at the aortic bifurcation which included both the common iliac arteries and the posterior left iliac vein, who experienced an unpredictable intraoperative cardiac arrest with electromechanical dissociation at 5 min after laparotomy. After successful resuscitation and hemodynamic stability, the lesion was fully excised. In the course of tumor manipulation, the patient developed a major hypertensive crisis with peak systolic blood pressure over 280 mmHg. Pathologic examination revealed the presence of diffuse proliferation of large and medium-sized mature adipocytes consistent with paraganglioma diagnosis. The patient was discharged at home on the seventh postoperative day. He did not present evidence of recurrence at the one-year follow-up. In conclusion, paragangliomas can require particular management due to their location but also due to their capacity to discharge substances which might induce life-threatening intraoperative complications.

OBJECTIVE To examine the impact of the Medicare Physician Group Practice (PGP) demonstration on expenditure, utilization, and quality outcomes. DATA SOURCE Secondary data analysis of 2001-2010 Medicare claims for 1,776,387 person years assigned to the ten participating provider organizations and 1,579,080 person years in the corresponding local comparison groups. STUDY DESIGN We used a pre-post comparison group observational design consisting of four pre-demonstration years (1/01-12/04) and five demonstration years (4/05-3/10). We employed a propensity-weighted difference-in-differences regression model to estimate demonstration effects, adjusting for demographics, health status, geographic area, and secular trends. PRINCIPAL FINDINGS The ten demonstration sites combined saved $171 (2.0%) per assigned beneficiary person year (p

An understanding of variations in the delivery and outcomes of clinical care by physician specialty can be used to target education and interventions to the most relevant professional societies and training programs. The assessment of these variations, however, depends on the quality of the data used to measure physician specialty. The Surveillance, Epidemiology, and End Results (SEER)-Medicare dataset, which consists of cancer registry data linked to Medicare enrollment and claims files, contains physician specialty on the claims and is commonly used by health services researchers to examine specialty-related variations in care of people with cancer (Earle et al. 2002, 2006; Keating et al. 2003; National Cancer Institute 2007). Information about physician specialty available on Medicare claims can be supplemented by linking to sources such as the Unique Physician Identification Number (UPIN) Registry or the American Medical Association (AMA) Physician Masterfile (AMA 2004; NHIC 2006). Baldwin et al. (2002) reviewed the availability and quality of data on physician characteristics in Medicare claims and found that while these data are useful, investigators must understand the limitations of data on physician specialty so that they might decide the best approach to a particular research question and how these limitations may affect findings. For example, Rosenblatt and colleagues found that the AMA Masterfile identified 97 hematologist/oncologists in Washington state in addition to the 58 hematologist/oncologists found in that state's Medicare claims, a 167 percent increase (Rosenblatt et al. 1998; Baldwin et al. 2002). Thus, researchers investigating the role of hematologist/oncologists potentially would underestimate the number of physicians with this specialty if using Medicare claims alone. The extent to which there is agreement on cancer-specific physician specialty variables between Medicare claims, the UPIN Registry, and the AMA Masterfile for the entire SEER-Medicare dataset is unknown. Given the additional time and financial investment that is required to obtain and link the UPIN Registry and/or the AMA Masterfile to SEER-Medicare data, we believe a more complete understanding of the agreement on cancer-specific physician specialty between these data sources would be useful. Such information could be used by future investigators to determine whether seeking additional data on specialty will enhance the quality of their cancer-related research. The purpose of this paper is to compare the agreement and identification of physicians by cancer specialty between SEER-Medicare claims, the UPIN Registry, and the AMA Masterfile. We also demonstrate an approach to refine the determination of physicians as cancer specialists when using all three data sources, and we provide an overview of Medicare claims-based information on physician specialty, including the process of obtaining the data.

BACKGROUND: Studies have shown that follow-up care for cancer patients differs by physician specialty, and that coordination between specialists and generalists results in better care. Little is known, however, regarding which specialties of physicians provide care to long-term cancer survivors. METHODS: The authors used Surveillance, Epidemiology, and End Results data from 1992 through 1997 that were linked to 1997-2003 Medicare data to identify persons diagnosed >5 years earlier with bladder, female breast, colorectal, prostate, or uterine cancer. Physician specialties were assigned by combining Medicare data with the American Medical Association Masterfile and the Unique Physician Identification Number Registry. The percentage of long-term survivors who visited physicians of interest was determined by analyzing Medicare outpatient claims submitted 6 to 12 years after initial diagnosis. RESULTS: Over the entire study period, 46% of female breast cancer survivors, 26% of colorectal cancer survivors, and 14% of prostate cancer survivors saw hematologists/oncologists. Radiation oncologists were seen by 11%, 2%, and 14% of breast, colorectal, and prostate cancer survivors, respectively. Survivors also sought care from specialists related to their cancer: 19% of breast cancer survivors had a cancer-coded visit with a surgeon, 26% of colorectal cancer survivors visited a gastroenterologist, and 68% of prostate cancer survivors visited a urologist. The percentage of survivors who visited cancer and cancer-related physicians declined each year. In contrast, nearly 75% of female breast, colorectal, and prostate cancer survivors saw primary care providers, and these percentages did not decrease annually. CONCLUSIONS: The findings of the current study underscore the need to include both primary care providers and cancer-related specialists in education and guidelines regarding cancer survivorship. Cancer 2009. © 2009 American Cancer Society.

Background. Increasingly, investigators are using administrative databases to answer research questions requiring physician characteristics information. This article provides a roadmap for investigators who use Medicare data to answer such questions, focusing on use of the Surveillance, Epidemiology, and End Results (SEER)-Medicare files. Methods. Three data sources that can be linked to identify physician characteristics—Medicare claims, the Unique Physician Identification Number (UPIN) Registry, and the American Medical Association (AMA) Masterfile—were examined for data availability, linkage rates, and quality. These databases also were used to explore measurement issues regarding physician specialty and practice volume. Results. Over 98 percent of UPINs identified from the Medicare claims could be linked with both the AMA Masterfile and the UPIN Registry. The AMA Masterfile is the best source of sociodemographic and medical training information; the Medicare claims are the best source of practice ZIP code; and the UPIN Registry is the best source of practice organization data. The operationalization of variables such as physician specialty and practice volume is dependent on the specific research question that is being addressed. Conclusion. Administrative databases, such as SEER-Medicare data linked to AMA Masterfile or UPIN Registry data, are an important resource for investigators interested in assessing the relationship between physicians’ personal and practice characteristics and the content or outcomes of clinical care.

This paper examines changes in the use of selected diagnostic technologies for Medicare patients in 1985 and 1990. The analysis compares patients across five common, medical tracer conditions: acute myocardial infarction (AMI), congestive heart failure (CHF), stroke, pneumonia, and gastrointestinal (GI) hemorrhage. The relationship of hospital characteristics to patterns of technology use was assessed by grouping hospitals by a composite measure of "costliness." The overall use of 21 diagnostic tests rose by 27% over the 5-year period. Increases were most marked among the three cardiovascular tracers and for related technologies, such as cardiac angiography and cardiac ultrasound. There was evidence that newer technologies partially replaced older diagnostic tests that were used for similar indications: rates of noninvasive cerebrovascular imaging rose while rates of cerebral angiography declined. However, for several common, long-established tests, such as electrocardiogram and chest radiograph, there were consistent increases that are unexplained. High-cost hospitals performed diagnostic tests at much higher rates than lower-cost hospitals in both 1985 and 1990, but the rate of increase in test use across the two study years was generally greater for the lower-cost hospitals.

The adjusted average per capita cost (AAPCC) payment system for Medicare risk-based plans uses a county level geographic adjustment factor to account for differences in beneficiary costs across areas. The implications of abandoning the county unit as the basis of the geographic area are examined and the merging of counties to match the geographic definition used in the prospective payment system are considered. Year-to-year variation in a county AAPCC is inversely associated with county population size and, based on year-to-year AAPCC variation, 86 percent of all counties are too small to be used for the geographic adjustment.

The Federal government's Medicare program currently pays on a risk basis to health maintenance organizations (HMOs) and competitive medical plans (CMPs) using an adjusted average per capita cost (AAPCC) method. This article proposes using a blended sector rate adjustment to blunt the impact of biased selection. The blended sector rate adjustment calculates payments to risk-based plans for next year based on the weighted sum of the average payment of the risk-based sector in the current year plus an estimate of the average Medicare payment in the fee-for-service sector. The weights for the sum are proportional to the risk-based market penetration in the area.

This study investigates the effects of tax, regulatory, and reimbursement policies and other factors exogenous to the health insurance market on the relative price (to commercial insurers) paid by Blue Cross plans for hospital care, their administrative expense and accounting profits, premiums, and ultimately Blue Cross market share. We specify and estimate a simultaneous equation model to assess interrelationships among these variables. We conclude that premium tax advantages enjoyed by the Blues have virtually no effect on the Blues' premiums or their market shares. A Blue Cross plan's market share has a positive effect on the discount it obtains from hospitals as does coverage of Blue Shield charges by a state-mandated rate-setting plan. An upper bound on the effect on the Blue Cross market share of covering Blue Cross under rate-setting but excluding the commercials from such coverage is seven percentage points. Tests for administrative slack in the operation of Blue Cross plans yield mixed results.

An expectation-maximum (EM) likelihood algorithm is used to estimate two seemingly unrelated Tobit regressions in which the dependent variables are truncated normal. An illustrative example on the determination of the life-health insurance and pension benefits is also given.

Fringe benefits constitute a sizable proportion of total pay. Simulations show effects (1) of tax policy on the level of employer contributions to fringe benefit programs—both in the aggregate and ...

The Tax Equity and Fiscal Responsibility Act of 1982, under rules implemented in April 1985, creates incentives for HMOs and other competitive medical plans to significantly expand their participation in Medicare on an at-risk basis. In an attempt to gauge the likely response of HMOs to the new incentives, we examined data on a census of HMOs operating in 1982 to look for differences between HMOs that entered the Medicare program at risk under the earlier National Medicare Competition demonstration and those that did not. The most consistent difference we found was that HMOs in areas with a high adjusted average per capita cost were more likely to enter the Medicare market. HMOs with prior experience serving Medicare beneficiaries were also more likely to join the demonstration, as were HMOs that were federally qualified. No other HMO characteristics appeared to significantly affect the likelihood of entry.

The Health Care Financing Administration (HCFA) initiated the Medicare Competition Demonstration in 1982 in anticipation of congressional intent to establish a national program. Interim results on the 1984 service use and cost experience of the health maintenance organizations (HMOs) and competitive medical plans (CMPs) participating in the demonstrations indicate that Medicare enrollees in the demonstration experienced a median of 1,951 hospital days per 1,000 person years, 57 per cent of the median of 3,432 days per 1,000 in the local markets from which the plans drew enrollment. Independent practice association (IPA) HMOs experienced higher hospital use rates than staff and group model HMOs. These comparisons are not adjusted for various risk factors, the absence of which were likely to favor the demonstration plans. Plans with lower hospital service use were federally qualified and had been operating for more than five years. The median total annual revenue per enrollee across all plans was $2,312, compared to median annual expenses per enrollee of $2,250. The distribution of median annual expenses per enrollee by major category of expense was: institutional expenses ($1,038/enrollee), medical expenses ($720/enrollee), supplemental services expenses ($154/enrollee), and administrative and other expenses ($295/enrollee). Future analysis, using beneficiary-level data, will examine the impact of the demonstration and the nature and extent of evident biased selection and will compare the quality of care in the demonstrations to that in the fee-for-service sector.

This study examines the impact of unions on worker compensation and total costs in hospitals, both in specific departments and in the hospital as a whole. An analysis of data for 367 hospitals for the years 1974 and 1977 shows that unions raised the mean compensation of hospital workers by 8.8 percent without producing offsetting increases in worker productivity. Thus, unions do increase hospital costs, although far less than health insurance and other factors do.