Access to Expert Stroke Care with Telemedicine: REACH MUSC

Stroke is a leading cause of death and disability, and recombinant tissue plasminogen activator (rtPA) can significantly reduce the long-term impact of acute ischemic stroke (AIS) if given within 3 h of symptom onset. South Carolina is located in the “stroke belt” and has a high rate of stroke and stroke mortality. Many small rural SC hospitals do not maintain the expertise needed to treat AIS patients with rtPA. MUSC is an academic medical center using REACH MUSC telemedicine to deliver stroke care to 15 hospitals in the state, increasing the likelihood of timely treatment with rtPA. The purpose of this study is to determine the increase in access to rtPA through the use of telemedicine for AIS in the general population and in specific segments of the population based on age, gender, race, ethnicity, education, urban/rural residence, poverty, and stroke mortality. We used a retrospective cross-sectional design examining Census data from 2000 and geographic information systems analysis to identify South Carolina residents that live within 30 or 60 min of a primary stroke center (PSC) or a REACH MUSC site. We include all South Carolina citizens in our analysis and specifically examine the population’s age, gender, race, ethnicity, education, urban/rural residence, poverty, and stroke mortality. Our sample includes 4,012,012 South Carolinians. The main measure is access to expert stroke care at a PSC or a REACH MUSC hospital within 30 or 60 min. We find that without REACH MUSC, only 38% of the population has potential access to expert stroke care in SC within 60 min given that most PSCs will maintain expert stroke coverage. REACH MUSC allows 76% of the population to be within 60 min of expert stroke care, and 43% of the population to be within 30 min drive time of expert stroke care. These increases in access are especially significant for groups that have faced disparities in care and high rates of AIS. The use of telemedicine can greatly increase access to care for residents throughout South Carolina

Electronic medical record use and efficiency: A DEA and windows analysis of hospitals

We use data envelopment analysis (DEA) to examine the relationship between hospital electronic medical record (EMR) use and efficiency in a national sample of acute care hospitals. Data sources include the American Hospital Association (AHA), Health Information Management Systems Society (HIMSS), and Case Mix Index. Using two research approaches including a retrospective, cross-sectional design and a first differencing repeated measures design, we find limited evidence that EMRs can improve hospital efficiency. Small hospitals may benefit in the area of efficiency through EMR use, but medium and large hospitals generally do not demonstrate such a difference. Likewise, there does not appear to be a significant increase in efficiency over time associated with EMRs when compared to the efficiency of hospitals without such documentation.DEA Hospitals EMR use Health information technology

Association of hospital and market characteristics with 30-day readmission rates from 2009 to 2015

Objectives: The US government implemented the Hospital Readmission Reduction Program on 1 October 2012 to reduce readmission rates through financial penalties to hospitals with excessive readmissions. We conducted a pooled cross-sectional analysis of US hospitals from 2009 to 2015 to determine the association of the Hospital Readmission Reduction Program with 30-day readmissions. Methods: We utilized multivariable linear regression with year and state fixed effects. The model was adjusted for hospital and market characteristics lagged by 1 year. Interaction effects of hospital and market characteristics with the Hospital Readmission Reduction Program indicator variable was also included to assess whether associations of Hospital Readmission Reduction Program with 30-day readmissions differed by these characteristics. Results: In multivariable adjusted analysis, the main effect of the Hospital Readmission Reduction Program was a 3.80 percentage point ( p  < 0.001) decrease in readmission rates in 2013–2015 relative to 2009–2012. Hospitals with lower readmission rates overall included not-for-profit and government hospitals, medium and large hospitals, those in markets with a larger percentage of Hispanic residents, and population 65 years and older. Higher hospital readmission rates were observed among those with higher licensed practical nurse staffing ratio, larger Medicare and Medicaid share, and less competition. Statistically significant interaction effects between hospital/market characteristics and the Hospital Readmission Reduction Program on the outcome of 30-day readmission rates were present. Teaching hospitals, rural hospitals, and hospitals in markets with a higher percentage of residents who were Black experienced larger decreases in readmission rates. Hospitals with larger registered nurse staffing ratios and in markets with higher uninsured rate and percentage of residents with a high school education or greater experienced smaller decreases in readmission rates. Conclusion: Findings of the current study support the effectiveness of the Hospital Readmission Reduction Program but also point to the need to consider the ability of hospitals to respond to penalties and incentives based on their characteristics during policy development

Market Factors and Electronic Medical Record Adoption in Medical Practices

BACKGROUND: Previous studies identified individual or practice factors that influence practice-based physicians\u27 electronic medical record (EMR) adoption. Less is known about the market factors that influence physicians\u27 EMR adoption. PURPOSE: The aim of this study was to explore the relationship between environmental market characteristics and physicians\u27 EMR adoption. METHODS: The Health Tracking Physician Survey 2008 and Area Resource File (2008) were combined and analyzed. Binary logistic regression was used to examine the relationship between three dimensions of the market environment (munificence, dynamism, and complexity) and EMR adoption controlling for several physician and practice characteristics. RESULTS: In a nationally representative sample of 4,720 physicians, measures of market dynamism including increases in unemployment, odds ratio (OR) = 0.95, 95% confidence interval (CI) [0.91, 0.99], or poverty rates, OR = 0.93, 95% CI [0.89, 0.96], were negatively associated with EMR adoption. Health maintenance organization penetration, OR = 3.01, 95% CI [1.49, 6.05], another measure of dynamism, was positively associated with EMR adoption. Physicians practicing in areas with a malpractice crisis, OR = 0.82, 95% CI [0.71, 0.94], representing environmental complexity, had lower EMR adoption rates. PRACTICE IMPLICATIONS: Understanding how market factors relate to practice-based physicians\u27 EMR adoption can assist policymakers to better target limited resources as they work to realize the national goal of universal EMR adoption and meaningful use

sj-docx-1-smo-10.1177_20503121231220815 – Supplemental material for Association of hospital and market characteristics with 30-day readmission rates from 2009 to 2015

Supplemental material, sj-docx-1-smo-10.1177_20503121231220815 for Association of hospital and market characteristics with 30-day readmission rates from 2009 to 2015 by Gabriel S Tajeu, Ganisher Davlyatov, David Becker, Robert Weech-Maldonado and Abby Swanson Kazley in SAGE Open Medicine</p