In 2009-2010, Blue Cross Blue Shield of Massachusetts entered into global payment contracts (the Alternative Quality contract, AQC) with 11 provider organizations. We evaluated the impact of the AQC on spending and utilization of several categories of medical technologies, including one considered high value (colonoscopies) and three that include services that may be overused in some situations (cardiovascular, imaging, and orthopedic services).
Approximately 420,000 unique enrollees in 2009 and 180,000 in 2010 were linked to primary care physicians whose organizations joined the AQC. Using three years of pre-intervention data and a large control group, we analyzed changes in utilization and spending associated with the AQC with a propensity-weighted difference-in-differences approach adjusting for enrollee demographics, health status, secular trends, and cost-sharing.
In the 2009 AQC cohort, total volume of colonoscopies increased 5.2 percent (p=0.04) in the first two years of the contract relative to control. The contract was associated with varied changes in volume for cardiovascular and imaging services, but total spending on cardiovascular services in the first two years decreased by 7.4% (p=0.02) while total spending on imaging services decreased by 6.1% (p<0.001) relative to control. In addition to lower utilization of higher-priced services, these decreases were also attributable to shifting care to lower-priced providers. No effect was found in orthopedics.
As one example of a large-scale global payment initiative, the AQC was associated with higher use of colonoscopies. Among several categories of services whose value may be controversial, the contract generally shifted volume to lower-priced facilities or services.
Under new bundled payment models, hospitals are financially responsible for post-acute care delivered by providers such as skilled nursing facilities (SNFs) and home health agencies (HHAs). The hope is that hospitals will use post-acute care more prudently and better coordinate care with post-acute providers. However, little is known about existing patterns in hospitals׳ referrals to post-acute providers.
Post-acute provider referrals were identified using SNF and HHA claims within 14 days following hospital discharge. Hospital post-acute care network size and concentration were estimated across hospital types and regions. The 2008 Medicare Provider Analysis and Review claims for acute hospitals and SNFs, and the 100% HHA Standard Analytic Files were used.
The mean post-acute care network size for U.S. hospitals included 57.9 providers with 37.5 SNFs and 23.4 HHAs. The majority of these providers (65.7% of SNFs, 60.9% of HHAs) accounted for 1 percent or less of a hospital׳s referrals and classified as “low-volume”. Other post-acute providers we classified as routine. The mean network size for routine providers was greater for larger hospitals, teaching hospitals and in regions with higher per capita post-acute care spending.
The average hospital works with over 50 different post-acute providers. Moreover, the size of post-acute care networks varies considerably geographically and by hospital characteristics. These results provide context on the complex task hospitals will face in coordinating care with post-acute providers and cutting costs under new bundled payment models.
Implementation of a patient centered medical home challenges primary care providers to change their scheduling practices to enhance patient access to care as well as to learn how to use performance metrics as part of a self-reflective practice redesign culture. As medical homes become more commonplace, health care administrators and primary care providers alike are eager to identify barriers to implementation. The objective of this study was to identify non-technological barriers to medical home implementation from the perspective of primary care providers. We conducted qualitative interviews with providers implementing the medical home model in Department of Veterans Affairs clinics-the most comprehensive rollout to date. Primary care providers reported favorable attitudes towards the model but discussed the importance of data infrastructure for practice redesign and panel management. Respondents emphasized the need for administrative leadership to support practice redesign by facilitating time for panel management and recognizing providers who utilize non-face-to-face ways of delivering clinical care. Health care systems considering adoption of the medical home model should ensure that they support both technological capacities and vertically aligned expectations for provider performance.
Published by Elsevier Inc.
The Triple Aim of better health, better care, and lower costs has become a fundamental framework for understanding the need for broad health care reform and describing health care value. While the framework is not specific to any clinical setting, this article focuses on the alignment between the framework and Emergency Department (ED) care. The paper explores where emergency care is naturally aligned with each Aim, as well as current barriers which must be addressed to meet the full vision of the Triple Aim. We propose a vision of EDs serving as a nexus for care coordination optimally consistent with the Triple Aim and the requirements for such a role. These requirements include: (1) substantial integration in coordinated care models; (2) development of reliable and actionable data on ED quality, population health, and cost outcomes; (3) specific initiatives to control and optimize ED utilization; and (4) payment models which preserve surge and disaster response capacity.
Published by Elsevier Inc.
Existing national health-related surveys take several months or years to become available. The Affordable Care Act will bring rapid changes to the health care system in 2014. We analyzed the Gallup-Healthways׳ Well-Being Index (WBI) in order to assess its ability to provide real-time estimates of the impact of the ACA on key health-related outcomes.
We compared the Gallup-Healthways WBI to established surveys on demographics, health insurance, access to care, and health. Data sources were the Gallup-Healthways WBI, the Current Population Survey, the American Community Survey, the Medical Expenditure Panel Survey, the National Health Interview Survey, and the Behavioral Risk Factor Surveillance System. Demographic measures included age, race/ethnicity, education, and income. Insurance outcomes were coverage rates by type, state, and year. Access measures included having a usual source of care and experiencing cost-related delays in care. Health measures were self-reported health and history of specific diagnoses.
Most differences across surveys were statistically significant (p<0.05) due to large sample sizes, so our analysis focused on the absolute magnitude of differences. The Gallup-Healthways WBI post-weighted sample was similar in age, race/ethnicity, and education to other surveys, though the Gallup-Healthways WBI sample is slightly older, has fewer minorities, and is more highly educated than in other national surveys. In addition, income was more frequently missing. The Gallup-Healthways WBI produced similar national, state, and time-trend estimates on uninsured rates, but far lower rates of public coverage. Access to care and health status were similar in the Gallup-Healthways WBI and other surveys.
The Gallup-Healthways WBI is a valuable complement to existing data sources for health services research. The Gallup-Healthways WBI estimates for uninsured rates and access to care were similar to established national surveys and may allow for rapid estimates of the ACA׳s impact on the uninsured in 2014. Estimates of insurance type are less comparable, particularly for public coverage, which likely limits the utility of the Gallup-Healthways WBI for analyzing changes in particular types of coverage.
Prior research has shown that provider positive attitudes about EHRs are associated with their successful adoption. There is no evidence on whether comfort with technology and more positive attitudes about EHRs affect use of EHR functions once they are adopted.
We used data from a survey of providers in the Primary Care Information Project, a bureau of the New York City Department of Health and Mental Hygiene and measures of use from their EHRs. The main predictor variables were scores on three indices: comfort with computers, positive attitudes about EHRs, and negative attitudes about EHRs. The main outcome measures were four measures of use of EHR functions. We used linear regression models to test the association between the three indices and measures of EHR use.
The mean comfort with computers score was 2.37 (SD 0.53) on a scale of 1–3 with 3 being the most comfortable. The mean positive attitude score was 2.74 (SD 0.40) on a scale of 1–3 with 3 being more positive. The mean negative attitude score was 1.81 (SD 0.54) on a scale of 1–3 with 3 being more negative. Within the first twelve months of having the EHR, 59.5% of visits had allergy information entered into a structured field, 64.8% had medications reviewed, and 74.3% had blood pressured entered. Among visits with a prescription generated, 24.5% had prescriptions electronically prescribed. In multivariate regression analysis, we found no significant correlations between comfort with computers, positive attitudes about EHRs, or negative attitudes about EHRs and any of the measures of use.
Comfort with computers and attitudes about EHRs did not predict future use of the EHR functions. Our findings suggest that meaningful use of the EHR may not be affected by providers׳ prior attitudes about EHRs.
The purpose of this study was to evaluate dentists׳ attitudes and perceptions toward dental therapists, a new licensed dental provider in Minnesota. This study employed mixed modes to administer a survey using a stratified random sample of 1000 dentists in Minnesota. The response rate was 55% (AAPOR RR1: n=551/999). Results showed a majority of dentists were opposed to dental therapists performing irreversible procedures. In addition, results identified perceived barriers to hiring a dental therapist and found dentists do not believe dental therapists will alleviate oral health disparity in the State.
Published by Elsevier Inc.
In 1999, the Institute of Medicine (IOM) published Ensuring Quality Cancer Care, an influential report that described an ideal cancer care system and issued ten recommendations to address pervasive gaps in the understanding and delivery of quality cancer care. Despite generating much fervor, the report's recommendations-including two recommendations related to quality measurement-remain largely unfulfilled. Amidst continuing concerns regarding increasing costs and questionable quality of care, the IOM charged a new committee with revisiting the 1999 report and with reassessing national cancer care, with a focus on the aging US population. The committee identified high-quality patient-clinician relationships and interactions as central drivers of quality and attributed existing quality gaps, in part, to the nation's inability to measure and improve cancer care delivery in a systematic way. In 2013, the committee published its findings in Delivering High-Quality Cancer Care: Charting a New Course for a System in Crisis, which included two recommendations that emphasize coordinated, patient-centered quality measurement and information technology enhancements: Develop a national quality reporting program for cancer care as part of a learning health care system; and,Develop an ethically sound learning health care information technology system for cancer that enables real-time analysis of data from cancer patients in a variety of care settings. These recommendations underscore the need for independent national oversight, public-private collaboration, and substantial funding to create robust, patient-centered quality measurement and learning enterprises to improve the quality, accessibility, and affordability of cancer care in America.
To assist practices and institutions throughout the country in implementing clinical redesign supported by - and aligned with - payment reform, we present a case study of the New Mexico Cancer Center (NMCC) based on numerous stakeholder interviews, literature reviews, and a comprehensive site visit. This study explores the complex barriers oncologists face in improving the quality and outcomes of cancer care and reducing overall costs in a sustainable way. This case will explore the following questions: How did the NMCC redesign care to improve quality, enhance patient experience and results, and reduce costs? How can an organization demonstrate they are improving quality to enable new payment contracts that enable sustainability? Are alternative payment models sustainable for an independent, community oncology practice?
•It is hypothesized that this delivery model can decrease wait times for diagnosis and treatment of cancer, increase awareness and knowledge of cancer prevention and treatment, and foster trust with providers and patients from vulnerable communities.•Involving oncologists in clinical diagnosis at community health centers can link specialty care more closely to vulnerable communities.•Funding for this type of clinical innovation is currently limited to institutional and philanthropic sources. A shift in the academic and public sector funding paradigms may be required to enable implementation on a broader level.
In 2011, federal incentive payments for meaningful use of electronic health records (EHRs) began. This study evaluates the impact of the program on hospitals and EHR vendors, identifying how it affects EHR planning and development. Specifically, it assesses whether vendors and Chief Information Officers (CIOs) are viewing the meaningful use requirements as a floor – the minimally acceptable level of implementation, upon which development continues – or as a ceiling – the upper-bound on EHR development and implementation.
The study combines interviews with EHR vendors and hospital CIOs with EHR adoption data from American Hospital Association surveys. Results from interviews with 17 hospital and system CIOs (representing 144 individual acute-care hospitals) and 8 EHR development executives (representing two-thirds of installations) are detailed. Furthermore, it compares adoption of two key EHR functions, BCMA and CPOE, which are treated differently under stage 1 of the incentive program.
Three key findings emerge from the study. First, meaningful use requirements can serve as either a floor or a ceiling, depending on the abilities of institutions implementing EHRs. Second, the increasing focus on achieving meaningful use across both hospitals and vendors risks missing the forest of health care system change through the trees of meeting discrete requirements. Third, while the meaningful use incentive program has accelerated the development and implementation of some key functions, it has also slowed development of others.
Policy makers should craft subsequent stages of the incentive program to ensure smaller facilities and additional features necessary for health care system change are not left behind.
While employer-sponsored financial incentives for healthy behaviors have demonstrated the potential to promote short-term employee behavior change, the effectiveness of such incentives in promoting long-term health behavior change has often been disappointing. This paucity of sustained change could be explained by the many factors that shape employees' health behaviors, only some of which may be influenced by incentives. We discuss how employer-sponsored incentives for healthy behaviors could become more patient-centered, and thus perhaps more effective, by integrating insights from self-determination theory and health behavior theories, targeting employees' capacity for change, and using tailoring.
Published by Elsevier Inc.
Unintended consequences of health care interventions are unavoidable. For example, computerized order entry systems, implemented to reduce prescription errors, catalyze novel errors of their own, with providers unexpectedly relying on these systems to provide default dosing information rather than locating appropriate treatment guidelines. We argue that unintended behavioral responses by patients and physicians to health care interventions may explain why certain health care interventions that seem logical and foolproof fail to demonstrate real-world benefits. We argue that compensatory markers which measure behavioral responses in clinical trials should be implemented to better understand why real-world benefits fail to materialize.