Journal of Healthcare Management - July/August 2014 - (Page 274)

J o u r n al of H ealt H care M anage Ment 59:4 J uly /a ugust 2014 Department of Health and Human Services Health Resources and Services Administration's Area Resource File, and the CMS report of hospitals receiving incentive payments as of December 2012 (CMS, 2012). METHODS We linked each data source using AHA and CMS identification numbers and restricted our analysis to hospitals potentially eligible to receive MU payments (i.e., nonfederal acute care hospitals in the 50 U.S. states). Data on hospital characteristics came from the AHA Annual Survey and included hospital size (measured as staffed beds), ownership (for-profit or not-for-profit), region of the country (by census division), teaching status (whether or not the organization is a member of the Council of Teaching Hospitals and Health Systems), system membership (part of a system or independent), and Joint Commission accreditation status. In addition, we obtained information from the AHA Annual Survey on (1) whether the hospital is eligible for Medicaid incentive payments (measured as having 10% or larger share of Medicaid discharges) and (2) the proportion of hospital inpatient days billed to Medicare (Medicare caseload). Last, we calculated market concentration at the hospital system level using the Herfindahl-Hirschman Index. We calculated EHR adoption status in 2010 (prior to the start of the program) using the Annual Survey and EHR Adoption Database. We consider both data sources in our analyses because the latter source, as shown later, has a high nonresponse rate to this question. Using both data sources of EHR adoption serves as a sensitivity test to our analyses. Using the Annual Survey, we categorized EHR adoption into nonadopters, partial adopters, full adopters, and missing. We used the EHR Adoption Database to categorize EHR adoption into five categories: none, basic, basic with clinical notes, comprehensive, and missing (Jha et al., 2009). Moreover, given that previous research suggests the hospital health information technology (IT) management strategy (e.g., best of breed, single vendor) may influence MU attainment (Ford, Menachemi, Huerta, & Yu, 2010), we extracted a variable from the EHR Adoption Database that indicates whether the hospital has a single EHR vendor. Last, from the Area Resource File, we extracted measures of rural and urban location and census division. We conducted a bivariate analysis of these characteristics using chi-square tests of independence to compare the frequencies of each characteristic between hospitals that did and did not receive Medicare MU incentive payments and hospitals that did and did not respond to the EHR Adoption Database survey. Next, we conducted two separate logistic regressions to assess the relationship between these hospital characteristics and the receipt of Medicare MU incentive payments. One regression model used the Annual Survey EHR variable, and the other used the EHR Adoption Database EHR variable. The dependent variable for both logistic regressions is whether the hospital received Medicare MU incentive payments as of December 2012. We report both odds ratios and marginal 274

Table of Contents for the Digital Edition of Journal of Healthcare Management - July/August 2014

Journal of Healthcare Management - July/August 2014
Contents
Interview With Charles R. Evans, FACHE, President of the International Health Services Group and Senior Advisor at Jackson Healthcare
The Most Effective Leadership Style for the New Landscape of Healthcare
Exploring Obstacles to Success for Early Careerists in Healthcare Leadership
Decisions Through Data: Analytics in Healthcare
Sustainable Competitive Advantage for Accountable Care Organizations
Hospital Characteristics Associated With Achievement of Meaningful Use
The Effect of Professional Culture on Intrinsic Motivation Among Physicians in an Academic Medical Center
Abstract from the Academy of Management

Journal of Healthcare Management - July/August 2014