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Background: Practice tools such as health information technology (HIT) have the potential to support care processes, such as communication between health care providers, and influence care for “ambulatory care–sensitive conditions” (ACSCs). ACSCs are conditions for which good outpatient care can potentially prevent the need for hospitalization. To date, associations between such primary care practice capabilities and hospitalizations for ambulatory care–sensitive conditions have been primarily limited to smaller, local studies or unique delivery systems rather than nationally representative studies of primary care physicians in the United States. Methods: We analyzed a nationally representative sample of 1,819 primary care physicians who responded to the Center for Studying Health System Change9s Physician Survey. We linked 3 years of Medicare claims (2007 to 2009) with these primary care physician survey respondents. This linkage resulted in the identification of 123,760 beneficiaries with one or more of 4 ambulatory care–sensitive chronic conditions (diabetes, chronic obstructive pulmonary disease, asthma, and congestive heart failure) for whom these physicians served as the usual provider. Key independent variables of interest were physicians9 practice capabilities, including communication with specialists, use of care managers, participation in quality and performance measurement, use of patient registries, and HIT use. The dependent variable was a summary measure of ambulatory care–sensitive hospitalizations for one or more of these 4 conditions. Results: Higher provider-reported levels of communication between primary care and specialist physicians were associated with lower rates of potentially avoidable hospitalizations. While there was no significant main effect between HIT use and ACSC hospitalizations, the associations between interspecialty communication and ACSC hospitalizations were magnified in the presence of higher HIT use. For example, patients in practices with both the highest level of interspecialty communication and the highest level of HIT use had lower odds of ambulatory care–sensitive hospitalizations than did those in practices with lower interspecialty communication and high HIT use (adjusted odds ratio, 0.70; 95% confidence limits, 0.59, 0.82). Conclusions: Greater primary care and specialist communication is associated with reduced hospitalizations for ambulatory care–sensitive conditions. This effect was magnified in the presence of higher provider-reported HIT use, suggesting that coordination of care with support from HIT is important in the treatment of ambulatory care–sensitive conditions.

Objective To estimate the cost of defensive medicine among elderly Medicare patients. Data Sources We use a 2008 national physician survey linked to respondents’ elderly Medicare patients’ claims data. Study Design Using a sample of survey respondent/beneficiary dyads stratified by physician specialty, we estimated cross-sectional regressions of annual costs on patient covariates and a medical malpractice fear index formed from five validated physician survey questions. Defensive medicine costs were calculated as the difference between observed patient costs and those under hypothetical alternative levels of malpractice concern, and then aggregated to estimate average defensive medicine costs per beneficiary. Data Collection Methods The physician survey was conducted by mail. Patient claims were linked to survey respondents and reweighted to approximate the elderly Medicare beneficiary population. Principal Findings Higher levels of the malpractice fear index were associated with higher patient spending. Based on the measured associations, we estimated that defensive medicine accounted for 8 to 20 percent of total costs under alternative scenarios. The highest estimate is associated with a counterfactual of no malpractice concerns, which is unlikely to be socially optimal as some extrinsic incentives to avoid medical errors are desirable. Among specialty groups, primary care physicians contributed the most to defensive medicine spending. Higher costs resulted mostly from more hospital admissions and greater postacute care. Conclusions Although results are based on measured associations between malpractice fears and spending, and may not reflect the true causal effects, they suggest defensive medicine likely contributes substantial additional costs to Medicare.

Objective. To identify factors associated with the cost of treating high-cost Medicare beneficiaries. Data Sources. A national sample of 1.6 million elderly, Medicare beneficiaries linked to 2004–2005 Community Tracking Study Physician Survey respondents and local market data from secondary sources. Study Design. Using 12 months of claims data from 2005 to 2006, the sample was divided into predicted high-cost (top quartile) and lower cost beneficiaries using a risk-adjustment model. For each group, total annual standardized costs of care were regressed on beneficiary, usual source of care physician, practice, and market characteristics. Principal Findings. Among high-cost beneficiaries, health was the predominant predictor of costs, with most physician and practice and many market factors (including provider supply) insignificant or weakly related to cost. Beneficiaries whose usual physician was a medical specialist or reported inadequate office visit time, medical specialist supply, provider for-profit status, care fragmentation, and Medicare fees were associated with higher costs. Conclusions. Health reform policies currently envisioned to improve care and lower costs may have small effects on high-cost patients who consume most resources. Instead, developing interventions tailored to improve care and lowering cost for specific types of complex and costly patients may hold greater potential for “bending the cost curve.”

Primary care physicians are expected to coordinate care for their patients.To assess the number of physician peers providing care to the Medicare patients of a primary care physician.Cross-sectional analysis of claims data.Fee-for-service Medicare in 2005.2284 primary care physicians who responded to the 2004 to 2005 Community Tracking Study Physician Survey.Primary patients for each physician were defined as beneficiaries for whom the physician billed for more evaluation and management visits than any other physician in 2005. The number of physician peers for each physician was the sum of other unique physicians that the index physician's primary patients visited plus other unique physicians who served as the primary physician for each of the index physician's nonprimary patients during 2005.The typical primary care physician has 229 (interquartile range, 125 to 340) other physicians working in 117 (interquartile range, 66 to 175) practices with which care must be coordinated, equivalent to an additional 99 physicians and 53 practices for every 100 Medicare beneficiaries managed by the primary care physician. When only the 31% of a primary care physician's primary patients who had 4 or more chronic conditions was considered, the median number of peers involved was still substantial (86 physicians in 36 practices). The number of peers varied with geographic region, practice type, and reliance on Medicaid revenues.Estimates are based only on fee-for-service Medicare patients and physician peers, and the number of peers is therefore probably an underestimate. The modest response rate of the Community Tracking Study Physician Survey may bias results in unpredictable directions.In caring for his or her own primary and nonprimary patients during a single year, each primary care physician potentially must coordinate with a large number of individual physician colleagues who also provide care to these patients.National Institute on Aging, American Medical Group Association, and the Robert Wood Johnson Foundation.