Presentation on theme: "Differences in Electronic Medical Record Implementation and Use according to Geographical Location and Organizational Characteristics of US Federally Qualified."— Presentation transcript:
Differences in Electronic Medical Record Implementation and Use according to Geographical Location and Organizational Characteristics of US Federally Qualified Health Centers Charles S. Beverley, Jr., M.S. Doctoral Candidate Arnold School of Public Health University of South Carolina October 30, 2012
Agenda I. Background and Significance What is a Federally Qualified Health Center (FQHC)? Electronic Medical Records (EMRs) and Barriers to Adoption Implications of the 2009 Recovery and Reinvestment Act Benefits of EMR Adoption II. Purpose of the Study III. Research Questions Overall Objectives and Research Hypotheses V. Methods and Procedures Dataset and Study Population Measures - Health Information Management Systems Society EMR Adoption Model Data Analysis Procedures Analytical Approach VI. Results VII. Discussion VIII. Benefits and Limitations
What is a Federally Qualified Health Center (FQHC)? A FQHC is a community health center designated by the federal government to provide comprehensive health care services (HRSA, 2012). These services include primary and preventive care, including health, oral, and mental health services that are provided to persons of all ages, regardless of their ability to pay or health insurance status. FQHCs charge for services on a sliding-fee scale that is based on patients' family income and size. FQHCs receive consideration from the Federal government in the form of a cash grant, cost-based reimbursement for their Medicaid patients, and free malpractice coverage (HRSA, 2012).
Electronic Medical Records (EMRs) and Barriers to EMR Adoption An EMR is a technology that allows physicians to improve clinical efficiency in health care settings (Miller and Sim, 2004). EMRs allow physicians to pursue more powerful quality improvement programs than is possible with paper-based records (Miller and Sim, 2004). Barriers to EMR adoption reported by health care organizations include high training costs, compliance issues related to reporting, insufficient technical support over the lifetime of an EMR system, and system interface issues (McAlearney et al., 2010).
Barriers to EMR Adoption (cont.) High startup costs are the primary barrier to full EMR adoption in healthcare organizations (Miller and West, 2007). The first national survey of federally funded community health centers reported 26% of CHCs have EMR capacity (Shields, Shin, Leu, Levy, Betancourt, Hawkins, and Proser, 2007). However, only 13% have implemented a full EMR system (Shields, Shin, Leu, Levy, Betancourt, Hawkins, and Proser, 2007). Data from a national survey in 2002 revealed that only 5-10% of physicians have adopted EMRs in their practices (Loomis, 2002). Low rates of full EMR adoption have been associated with a loss of productivity, lack of support in securing investments to support EMR adoption, and an undeveloped EMR software market (Ash and Bates, 2005).
Implications of the 2009 American Recovery and Reinvestment Act A primary objective of this statute is to modernize the nation’s infrastructure by requiring all health care organizations to adopt EMRs by the year 2014. $19 billion in funds set aside for health care organizations to incorporate EMRs into their practice. Each organization can receive up to $44,000 over a period of five years (Fishman, 2011). Health care organizations, such as FQHCs, are under pressure to either meet the 2014 deadline or face penalties in their Medicaid and Medicare reimbursements (Hutagalung, 2011). The proposed penalties will be in the form of a 1% reduction in Medicare and Medicaid reimbursements and up to 5% in the forthcoming years (Hutagalung, 2011).
Benefits of EMR Adoption EMR systems are faster to access and more updated than paper medical records. In a study that compared paper medical records and EMRs of 180 patients with schizophrenia, EMRs were 40% more updated and 20% faster to access than using paper medical records (Tsai and Bond, 2008). It is estimated that potential savings associated with adoption of fully functional EMR systems is more than $81 billion annually. It is estimated that EMR systems can produce efficiency and safety savings of $142-$371 billion. These savings could be doubled with the assistance of EMRs in the prevention and management of chronic diseases (Hillestad, Bigelow, Bower, Girosi, Meili, Scoville, and Taylor, 2005).
Purpose of the Study Few studies have evaluated the implementation and usage of EMR systems in FQHCs. Purpose: To assess EMR implementation and usage through a scale consisting of three levels (FQHCs without EMR, simple EMR, and full EMR) This scale was developed to match the Healthcare Information Management Systems Society (HIMSS) EMR Adoption Model to the 2009 Commonwealth Fund National Survey of Federally Qualified Health Centers.
Objectives & Hypotheses Objectives: Examine organizational characteristics of FQHCs and differences in their usage of EMR systems. Analyze associations between organizational characteristics, EMR implementation, and usage to determine where improvements are needed. Hypotheses: We hypothesize that more simple EMRs are implemented in FQHCs than full EMR systems because startup costs are lower. We hypothesize that simple EMR systems are underutilized in FQHCs due to an absence of clinician training in EMR functionality and workflow.
Methods This study used data from the 2009 Commonwealth Fund National Survey of Federally Qualified Health Centers. This national survey collected data from March 2, 2009 to May 27, 2009 using an eight-page questionnaire that took approximately 20-25 minutes to complete (Haran, 2009). The questionnaire consists of 31 questions used to measure the factors that assist and discourage initiatives for health care improvement in FQHCs. The survey measures these factors in five sections: (1) quality improvement, (2) patient information systems, (3) access to care and care coordination, (4) language services, and (5) respondent information. The survey was mailed to 1,007 FQHCs in the U.S. Of these 1,007 FQHCs, 795 responded (78.9% response rate). The survey data was validated and weighted by FQHC grantees according to number of patients, number of sites, region, and urbanity under the auspicious of the Bureau of Primary Health Care (Haran, 2009).
Measures The Healthcare Information Management Systems Society (HIMSS) EMR Adoption Model was used as a measure to examine EMR implementation and usage in FQHCs. This model identified seven stages of EMR capabilities at three levels of implementation: FQHCs without EMR, simple EMR, and full EMR (HIMSS, 2011). The model was matched with the 2009 Commonwealth Fund National Survey of Federally Qualified Health Centers to create commonly used categories for all three levels of EMR. Each level of implementation is based on answers reported to question 14 from the survey. Question 14: “Do you currently use any of the following technologies in your largest site – (a) electronic entry of clinical notes, (b) electronic ordering of laboratory tests, (c) electronic access to patients’ laboratory tests, (d) electronic prescribing of medication, (e) electronic list of all medications taken by patient, and (f) electronic alerts about a potential problem with drug dose or drug interaction?”
HIMSS EMR Adoption Model matched to the 2009 Commonwealth Fund Survey of FQHCs
Stages of EMR Implementation FQHCs that have not implemented an EMR system are in the HIMSS stage 0 and are not using any of the EMR capabilities in the seven stages. FQHCs that have implemented a simple EMR are using EMR capabilities in one of the HIMSS stages 1 through 5. FQHCs that have implemented a full EMR are using EMR capabilities in HIMSS stage 6 or 7.
Data Analysis Procedures SAS version 9.3 was used to analyze the 2009 Commonwealth Fund National Survey of Federally Qualified Health Centers. Chi-square analyses was used to assess the differences in EMR implementation and usage in FQHCs. P-values of less than 0.05 from the chi-square analyses determined the significance of the variables of interest. Logistic regression was used to obtain adjusted odds ratios and 95% confidence intervals. This information was used to understand the adjusted associations between EMR implementation and usage. All analyses for my study incorporated sampling weights in SAS version 9.3.
Analytical Approach: Dependent & Independent Variables Q. 11 was the dependent variable from the 2009 Commonwealth Fund National Survey of FQHCs that was critical to the study: - Q.11: “Do you currently use electronic medical records throughout your health center?” Q.14 was the independent variable from the 2009 Commonwealth Fund National Survey of FQHCs that was critical to the study: - Q.14: “Do you currently use any of the following technologies in your largest site – (a) electronic entry of clinical notes, (b) electronic ordering of laboratory tests, (c) electronic access to patients’ laboratory tests, (d) electronic prescribing of medication, (e) electronic list of all medications taken by patient, and (f) electronic alerts about a potential problem with drug dose or drug interaction?”
Analytical Approach: Covariates Several covariates from the 2009 Commonwealth Fund National Survey of FQHCs were critical to the study: - Region: (Northeast, Midwest, South, West) - Geographical Location: ( Urban or Rural) - Number of FQHC sites: (1 site, 2 sites, 3 sites, 4-9 sites, and 10 or more sites) - Physician shortage: (yes or no) - Percentage of patients with limited English proficiency: (0-10%, 11-24%, 25-50%, Greater than 50%) - Availability of bilingual clinical staff services: (75-100%, 50-74%, 25-49%, 1-24%, or 0% of the time) - Dental care availability: (yes or no) - Mental care availability: (yes or no) - Nutritional counseling availability: (yes or no) - Hospital support for IT adoption: (yes or no)
Results More than half (64%) of FQHCs in the United States have implemented simple EMR systems than full EMR systems. Simple EMRs were implemented in more than half of FQHCs in the Northeast, Southern, and Western regions of the United States. Simple EMRs in more than half of the FQHCs in the Southern and Western regions are underutilized (less than a 40% usage rate), compared to the Northeast that has a 50% usage rate. Based on the literature, EMR systems are underutilized because clinicians and health care providers have not learned how to use the systems (Ash and Bates, 2005). To address this problem, the literature has shown that proper clinician training in EMR functionality and workflow has significantly improved EMR usage in FQHCs (Santiago et al., 2006).
Discussion There is a need to improve simple EMR usage and full EMR implementation in FQHCs to meet the requirements of the American Recovery and Reinvestment Act by 2014. Otherwise, FQHCS will face a reduction in Medicare and Medicaid reimbursements. Improving full EMR implementation and usage in FQHCs cannot be completed overnight. Progress can be accelerated with the assistance of the federal government to uncover mechanisms that will improve full EMR implementation and simple EMR usage: - Further research - Stronger federal policies/guidelines - Additional federal funding specifically allocated to FQHCs for EMR training
Benefits and Limitations Benefits: A benefit of this study is the use of this large U.S. survey to examine patterns of EMR usage and the organizational characteristics associated with EMR implementation. Another benefit is the sample being validated and weighted to account for the distribution of all FQHCs. Other benefits of this study include the identification of key covariates, such as number of sites, region, and geographical location that may be associated with EMR usage and implementation. This study is beneficial because it promotes EMR adoption, which in turns assists in the creation of jobs in the health information technology sector during a time where unemployment rates are highest in the United States. Limitations: A strong limitation in this study is the removal of data from the sample because of incomplete or missing information. Another limitation in this study is that the American Recovery and Reinvestment Act was enacted in 2009 around the same time as the Commonwealth Fund National Survey of Federally Qualified Health Centers was completed. The survey may not take into account the financial penalties and benefits FQHCs gain from the American Recovery and Reinvestment Act that affect their decision to adopt EMRs.