Healthcare

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.

To help support implementation of aligning clinical redesign with payment reforms in practices and institutions throughout the country, we present two cases from Duke University Health System ("Duke") and University of Colorado Hospital ("Colorado"). The studies provide practical solutions for not only implementing clinical redesign, but also an understanding of how those clinical innovations can be aligned with alternative payment models. The cases will explore the following questions: What challenges or problems encouraged the organization to redesign CHF care? How did the organization select and then align care innovations with payment reforms, including bundled payments and shared savings? What did the organization identify as key success factors and/or challenges? How did these changes impact the organization׳s clinical outcomes or financial position? Finally, what lessons would the organization share with others attempting to implement similar strategies? Copyright © 2014 Elsevier Inc. All rights reserved.

Emerging digital technologies offer enormous potential to improve quality, reduce cost, and increase patient-centeredness in healthcare. Academic Medical Centers (AMCs) play a key role in advancing medical care through cutting-edge medical research, yet traditional models for invention, validation and commercialization at AMCs have been designed around biomedical initiatives, and are less well suited for new digital health technologies. Recently, two large bi-coastal Academic Medical Centers, the University of California, San Francisco (UCSF) through the Center for Digital Health Innovation (CDHI) and Partners Healthcare through the Center for Connected Health (CCH) have launched centers focused on digital health innovation. These centers show great promise but are also subject to significant financial, organizational, and visionary challenges. We explore these AMC initiatives, which share the following characteristics: a focus on academic research methodology; integration of digital technology in educational programming; evolving models to support "clinician innovators"; strategic academic-industry collaboration and emergence of novel revenue models. Copyright © 2014 Elsevier Inc. All rights reserved.

Policymakers, patients and clinicians are increasingly eager to foster patient involvement in health care innovation. Our objective was to use participatory action research with high-risk hospitalized patients to design a post-hospital transition intervention. We conducted qualitative interviews with sixty-five low-income, recently hospitalized patients exploring their perceptions of barriers to post-hospital recovery and ideas for improvement. We then used a modified grounded theory approach to design an intervention that would address each barrier using patients׳ suggestions. Five key themes were translated into design elements. First, patients wished to establish a relationship with healthcare personnel to whom they could relate. The intervention was provided by an empathic community health worker (CHW) who established rapport during hospitalization. Second, patients suggested tailoring support to their needs and goals. CHWs and patients designed individualized action plans for achieving their goals for recovery. Third, patient goals were misaligned with those of the inpatient team. CHW facilitated patient-provider discharge communication to align goals. Fourth, patients lacked post-discharge support for predominantly psychosocial or financial issues that undermined recovery. CHWs provided support tailored to patient needs. Finally, patients faced numerous barriers in obtaining post-hospital primary care. CHWs helped patients to obtain timely care with a suitable provider. Low-income hospitalized patients voiced needs and suggestions that were directly translated into the design of a scalable patient-centered CHW intervention. The approach of using participatory action research to tightly mapping patient input into intervention design is rapid and systematic strategy for operationalizing patient involvement in innovation. Copyright © 2014 Elsevier Inc. All rights reserved.

Wide variations exist in healthcare expenditures, though most prior studies have assessed aggregate utilization. We sought to examine healthcare utilization variation in New York State by assessing hospitals in peer groups of similar capabilities. Using charge data in New York State from the 2008 Statewide Planning and Research Cooperative System (SPARCS) and cost-to-charge ratios at the cost-center level drawn from Institutional Cost Reports, we calculated total, routine, and ancillary costs for patients discharged with an acute myocardial infarction (AMI) diagnosis in 2008. We assessed the correlation of these cost data to Hospital Referral Region (HRR) Medicare reimbursement data from the 2007 Dartmouth Atlas of Health Care. After describing hospital level cost variability, we examined characteristics associated with higher costs within peer groups of similar cardiac care capabilities. We found greater costs in hospitals providing the highest level of cardiovascular services, with cardiac surgery capable hospitals and non-invasive hospitals having total costs of $21,166 and $9268 per AMI discharge, and ancillary costs of $12,006 and $4167 per AMI discharge, respectively. Substantial variability in utilization existed in all levels of hospitals and across individual departmental cost centers. The two factors most frequently associated with higher total and ancillary costs across peer groups were patient case mix index and major or minor teaching status. Significant variation in cost per AMI discharge exists even within peer groups of hospitals with similar cardiac care capabilities. These findings support measurement and analysis at the hospital level to further understand the reasons for variation in utilization. Copyright © 2014 Elsevier Inc. All rights reserved.

Background 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. Methods 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. Results 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. Conclusions 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 impact of health information technology (HIT) in hospitals is dependent in large part on how it is used by nurses. This study examines the impact of HIT on the quality of care in hospitals in the Veterans Health Administration (VA), focusing on nurse-sensitive outcomes from 1995 to 2005. Data were obtained from VA databases and original data collection. Fixed-effects Poisson regression was used, with the dependent variables measured using the Agency for Healthcare Research and Quality Inpatient Quality Indicators and Patient Safety Indicators software. Dummy variables indicated when each facility began and completed implementation of each type of HIT. Other explanatory variables included hospital volume, patient characteristics, nurse characteristics, and a quadratic time trend. The start of computerized patient record implementation was associated with significantly lower mortality for two diagnoses but significantly higher pressure ulcer rates, and full implementation was associated with significantly more hospital-acquired infections. The start of bar-code medication administration implementation was linked to significantly lower mortality for one diagnosis, but full implementation was not linked to any change in patient outcomes. The commencement of HIT implementation had mixed effects on patient outcomes, and the completion of implementation had little or no effect on outcomes. This longitudinal study provides little support for the perception of VA staff and leaders that HIT has improved mortality rates or nurse-sensitive patient outcomes. Future research should examine patient outcomes associated with specific care processes affected by HIT. Copyright © 2014 Elsevier Inc. All rights reserved.

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.

The arterial blood gas (ABG) is a valuable and commonly used laboratory test. This prospective cohort study examined the variability of ABG ordering through the implementation of an evidence-based protocol. The study consisted of two 6-week periods. The protocol consisted of evidence-based and consensus opinion based indications for ABGs. In the first phase (initial 6 weeks), respiratory therapists recorded the indications for ABGs ordered by clinicians. In the second phase, all medical and surgical physicians were trained on the clinical rationale behind the protocol and were instructed to write the indication for each ABG with the order. Rates of ABGs/patient/day were measured in aggregate and per indication. Multivariate regression was used for adjusted comparisons between indications within the protocol. After protocol implementation, there was a significant decrease in ABGs from 2158 to 1674 (p=0.001), and after adjusting for daily census, there was a significant decrease from 35.3 ABGs/100 patients/day to 26.5 ABGs/100 patients/day (p<0.001), with no change in mortality or demographic characteristics between the populations. The percent of ABGs with normal range values for pH, PaCO2, and PaO2 decreased from 13.3% to 9.6% after implementation (p<0.001). Multivariate analysis revealed a 14% decrease in daily ABGs (p=0.001), a 15% decrease in weaning trial ABGs (p=0.039), and a 15% increase in ABGs ordered following a change in minute ventilation (p=0.004). Cost minimization analysis estimated annual institutional savings to be $87,565. Implementation of an evidence based protocol for ABG use resulted in fewer ABGs/patient/day largely from reduction of routine, daily ABGs. Ordering patterns for ABGs appeared to shift towards more clinically appropriate/relevant indications. 2b. © 2013 Elsevier Inc. All rights reserved.

Background 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. Methods 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. Results 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. Conclusions 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.

In 2009, the American Recovery and Reinvestment Act apportioned $643 million for a Health Information Technology Extension Program, which established Regional Extension Centers (RECs) to support the implementation and use of electronic health records (EHRs). Little is known, however, about how RECs should assist in EHR implementation and how they should structure ongoing support. The purpose of this paper is to describe physicians' experiences with the Primary Care Information Project (PCIP), an REC run by the New York City Department of Health and Mental Hygiene. We interviewed 17 physicians enrolled in PCIP to understand the role of the EHRon quality of care and their experience with technical assistance from PCIP. All physicians stated that they felt that the EHR improved the quality of care they delivered to their patients particularly because it helped them track patients. All the physicians found technical assistance helpful but most wanted ongoing assistance months or years after they adopted the EHR. © 2013 Published by Elsevier Inc.

Introduction 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. Methods 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. Results 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. Discussion 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.