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The American Journal of Managed Care December 2015
Interest in Mental Health Care Among Patients Making eVisits
Steven M. Albert, PhD; Yll Agimi, PhD; and G. Daniel Martich, MD
The Impact of Electronic Health Records and Teamwork on Diabetes Care Quality
Ilana Graetz, PhD; Jie Huang, PhD; Richard Brand, PhD; Stephen M. Shortell, PhD, MPH, MBA; Thomas G. Rundall, PhD; Jim Bellows, PhD; John Hsu, MD, MBA, MSCE; Marc Jaffe, MD; and Mary E. Reed, DrPH
Health IT-Assisted Population-Based Preventive Cancer Screening: A Cost Analysis
Douglas E. Levy, PhD; Vidit N. Munshi, MA; Jeffrey M. Ashburner, PhD, MPH; Adrian H. Zai, MD, PhD, MPH; Richard W. Grant, MD, MPH; and Steven J. Atlas, MD, MPH
A Health Systems Improvement Research Agenda for AJMC's Next Decade
Dennis P. Scanlon, PhD, Associate Editor, The American Journal of Managed Care
An Introduction to the Health IT Issue
Jeffrey S. McCullough, PhD, Assistant Professor, University of Minnesota School of Public Health; Guest Editor-in-Chief for the health IT issue of The American Journal of Managed Care
Preventing Patient Absenteeism: Validation of a Predictive Overbooking Model
Mark Reid, PhD; Samuel Cohen, MD; Hank Wang, MD, MSHS; Aung Kaung, MD; Anish Patel, MD; Vartan Tashjian, BS; Demetrius L. Williams, Jr, MPA; Bibiana Martinez, MPH; and Brennan M.R. Spiegel, MD, MSHS
EHR Adoption Among Ambulatory Care Teams
Philip Wesley Barker, MS; and Dawn Marie Heisey-Grove, MPH
Impact of a National Specialty E-Consultation Implementation Project on Access
Susan Kirsh, MD, MPH; Evan Carey, MS; David C. Aron, MD, MS; Omar Cardenas, BS; Glenn Graham, MD, PhD; Rajiv Jain, MD; David H. Au, MD; Chin-Lin Tseng, DrPH; Heather Franklin, MPH; and P. Michael Ho, MD, PhD
E-Consult Implementation: Lessons Learned Using Consolidated Framework for Implementation Research
Leah M. Haverhals, MA; George Sayre, PsyD; Christian D. Helfrich, PhD, MPH; Catherine Battaglia, PhD, RN; David Aron, MD, MS; Lauren D. Stevenson, PhD; Susan Kirsh, MD, MPH; P. Michael Ho, MD, MPH; and Julie Lowery, PhD
Patient-Initiated E-mails to Providers: Associations With Out-of-Pocket Visit Costs, and Impact on Care-Seeking and Health
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Innovations in Chronic Care Delivery Using Data-Driven Clinical Pathways
Yiye Zhang, MS; and Rema Padman, PhD
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Katherine K. Kim, PhD, MPH, MBA; Robert S. Rudin, PhD; and Machelle D. Wilson, PhD
Currently Reading
Characteristics of Residential Care Communities That Use Electronic Health Records
Eunice Park-Lee, PhD; Vincent Rome, MPH; and Christine Caffrey, PhD
Physician Attitudes on Ease of Use of EHR Functionalities Related to Meaningful Use
Michael F. Furukawa, PhD; Jennifer King, PhD; and Vaishali Patel, PhD, MPH

Characteristics of Residential Care Communities That Use Electronic Health Records

Eunice Park-Lee, PhD; Vincent Rome, MPH; and Christine Caffrey, PhD
Select organizational characteristics and geographic locations were independently associated with the use of any electronic health record system among residential care communities.

Objectives: Residential care communities’ (RCCs) use of electronic health records (EHRs) has the potential to improve communication and facilitate care coordination. This study describes the use of, and examines characteristics associated with, any type of EHR system among RCCs in the United States, nationally and by Census division.

Study Design: This study examined organizational and geographic characteristics, as well as resident case-mix in association with the use of EHRs among RCCs. 

Methods: Data from the 2012 National Study of Long-Term Care Providers were used for the analyses. Of 4694 sampled RCCs that completed the questionnaire, 3987 cases with complete data were included in the study.

Results: About 20.2% of RCCs used any type of EHR system and 3.1% used EHRs that had 6 selected computerized capabilities to meet this study’s definition for a basic EHR system. Compared with the national rate of 20.2%, a higher percentage of RCCs in the following Census divisions used some type of an EHR system: New England (23.2%), East North Central (26.3%), and West North Central (32.9%). Larger size, being chain affiliated, owned by other organizations or part of a continuing care retirement community, and geographic location were independently associated with the use of any EHRs among RCCs.

Conclusions: As RCCs serve increasingly less healthy and more disabled residents, improved communication and effective care coordination among RCC staff and across different care settings are critical. The estimates presented in this study can be used to establish a baseline for monitoring trends in EHR use among RCCs.

Am J Manag Care. 2015;21(12):e669-e676
Take-Away Points
  • In 2012, 20.2% of assisted living and similar residential care communities (RCCs) in the United States used some type of electronic heath record (EHR) system. 
  • RCCs that were larger, chain-affiliated, multi-level, and located in the Midwest region were more likely to use an EHR system. 
  • Estimates presented in this study can be used to establish a baseline for monitoring trends in EHR use among RCCs. 
  • With more hospitals and physicians advancing to Stage 2 “meaningful use,” it will become increasingly important to monitor RCCs’ use of EHR systems.
The Health Information Technology for Economic and Clinical Health (HITECH) Act was enacted in 2009 to improve the quality, safety, and efficiency of healthcare.1 Starting in 2011, the HITECH Act authorized financial incentives to eligible Medicare and Medicaid providers that demonstrate the adoption and meaningful use of certified electronic health record (EHR) systems.2 The incentive programs are phased in 3 stages, with increasing requirements at each stage; for example, one of the Stage 2 meaningful use requirements is that EHRs must have the capability to provide care summaries to other providers electronically during transitions of care or referral by 2014.3 Physicians and hospitals are among the core set of eligible providers that have been targeted by the incentive program since it was instituted in 2011.

Assisted living and similar residential care communities (RCCs), as well as other long-term and post acute care providers, are currently ineligible for incentive programs under the HITECH Act, despite the fact that RCCs serve increasingly less healthy and more disabled populations. In 2012, about 33.5% and 13.1% of RCC residents were discharged to a nursing home and a hospital, respectively.EHR systems could be one of the key mechanisms for limiting complications during care transitions, as these transitions are associated with medication errors, delayed or inadequate treatment, and other adverse events.5-7 Yet, little is known about the adoption and use of EHRs among RCCs. Most of what we know on the adoption and use of EHRs and other health information technology is based on the hospital and ambulatory care settings.8-14

Two recent studies examined the use of EHRs in RCCs using data from the 2010 National Survey of Residential Care Facilities (NSRCF). One study found that about 17% of RCCs used any EHR system in 201015; and a greater proportion of RCCs that used any EHR system were larger, nonprofit, chain-affiliated, co-located with another care setting, and located in a non-metropolitan statistical area (MSA) than those that did not use EHRs. Another study found that approximately 3% of RCCs reported having an EHR system that met the study’s definition of a basic system, which is defined as: having the capabilities to record resident demographics, resident, problem lists and clinical notes; to maintain the list of medications taken by the residents; to order prescriptions; and to view laboratory and imaging results.16 Due to the sampling design of the 2010 NSRCF data, neither of the studies examined geographic variations in relation to any EHR use. Geographic variations in the adoption and use of EHRs are observed in ambulatory care settings and hospitals despite financial incentives from the HITECH Act.12-14 Understanding whether similar geographic variations exist in the use of EHRs among RCCs would be important, as it may suggest the presence of disproportionate barriers to EHR adoption across healthcare settings in select geographic areas and disparities in access to benefits from EHRs. In addition, previous research on EHR use in RCCs examined resident case-mix limited to resident demographics.16 To build upon previous research and fill potential knowledge gaps in the literature, this study: 1) describes the use of any type of EHR system and basic system among RCCs in the United States, 2) describes the use of any type of EHR system among RCCs by Census division, and 3) examines the association between the use of any EHR system and the organizational and geographic characteristics, as well as resident case-mix of RCCs.


The CDC’s National Center for Health Statistics (NCHS) conducted the National Study of Long-Term Care Providers (NSLTCP). Data from the 2012 NSLTCP were used for the analyses.17 To be eligible for the study, an RCC: 1) had to be licensed, registered, listed, certified, or otherwise regulated by the state; 2) provided room and board with at least 2 meals a day, and around-the-clock on-site supervision; 3) helped with personal care or health-related services; 4) had 4 or more beds; 5) had at least 1 resident currently living in the community; and 6) served a predominantly adult population. Excluded, were RCCs that exclusively serve individuals with severe mental illness or intellectual or developmental disability; nursing homes were also excluded. The sampling frame was constructed based on these eligibility criteria, which are consistent with the definition and approach used to build the sampling frame for 2010 NSRCF. Based on the benchmarking results of the 2010 NSRCF sampling frame, the eligibility criteria identified a comprehensive and nationally representative list of RCCs that served older adults and individuals with physical disabilities.18

From 39,779 communities in the sampling frame, 11,690 RCCs were sampled, stratified by state and bed size. Data collection was conducted using a multi-mode survey protocol with mail, Web, and telephone follow-up for nonresponse. The questionnaire was completed for 4694 eligible communities, for a weighted response rate of 55.4%. (More detailed information on the study design and data collection is available elsewhere 17 and in other published reports.19,20) This study was exempt from NCHS’ Institutional Review Board because it met the definition of nonhuman subjects research.


Use of any and basic EHR systems. EHR systems are often categorized into any, basic, and fully functional systems. The criteria to define basic and fully functional EHR systems are based on the capabilities available in the system.21 A basic EHR system needs to have a subset of capabilities available in a fully functional system. In contrast, any type of EHR system refers to a wide range of systems that providers consider and report as an EHR system.

RCCs were coded as having any type of EHR system in use if the respondent reported “Yes” to the question, “An electronic health record is a computerized version of the resident’s health and personal information used in the management of the resident’s healthcare. Other than for accounting or billing purposes, does this residential care community use electronic health records?” RCCs were coded as having a basic system if they used any type of EHR system and reported having all 6 of the following selected computerized capabilities to collect or track: 1) resident demographics; 2) clinical notes, including medical history and daily progress notes; 3) resident problem lists; 4) lists of medications; 5) orders for prescriptions; and 6) viewing laboratory or imaging results. The definition of a basic system was adapted from other studies.10,12 

Organizational characteristics and resident case-mix. Informed by previous research on the use of EHRs in various healthcare settings,12-16,22-27 organizational and geographic characteristics and resident case-mix variables were selected as independent variables. Organizational characteristics included: ownership status; chain affiliation status, owned by other organization(s) or part of a continuing care retirement community (CCRC) (which can include RCCs), facility size, occupancy, status of having been in operation for 10 years or more, and staffing variables. The cutoff points for facility size and years in operation were pre-determined as they were collected as categorical variables. The staffing variables indicate hours per resident day (HPRDs) by registered nurse (RN) employees, licensed practical or vocational nurse (LPN/LVN) employees, and aide employees. HPRDs were computed by multiplying the number of full-time equivalent employees for each staff type by 35 hours, and then dividing the product by the number of residents, and by 7 days.

Geographic characteristics of RCCs included MSA status and Census division. The 9 Census divisions are groupings of the 50 states and the District of Columbia, and are subdivisions of the 4 regions; the lists of states by Census division and Census region are available elsewhere.28 Census divisions were used to describe whether there were differences in the rate of using any type of EHR system within each division compared with the national rate (Table 1). However, for descriptive (Table 2) and multivariate analyses (Table 3), Census divisions were grouped into 4 Census regions because of inadequate sample size within each division.

Variables indicating resident case-mix were the percentages of RCC residents that had the following characteristics: non-Hispanic white, female, 85 or older, with Medicaid paying for some or all of their long-term care services in the previous 30 days, diagnosed with Alzheimer’s disease or other dementias, needing any assistance with eating, percent of residents needing any assistance with bathing, percent of residents receiving assistance with medication management, treated in a hospital emergency department (ED) in the previous 90 days, and discharged from an overnight hospital stay in the previous 90 days. When counting the number of residents needing assistance with eating or bathing, respondents were instructed to include residents who needed any help or supervision from another person, or the use of special equipment to perform a given activity of daily living.

Data Analysis  

Descriptive analyses using χ2 and t tests were conducted to examine the variation in use of EHR systems among RCCs’ organizational and geographic characteristics and resident case-mix variables. Multivariate logistic regression analyses were used to examine factors associated with the use of any EHRs. All significance tests were 2-sided using P <.05 as the level of significance. Analyses were performed using the statistical package SAS-callable, SUDAAN version 11 (RTI International, Research Triangle Park, North Carolina) to account for complex sampling design used in NSLTCP.


Of the 4694 cases who completed the questionnaire, 3987 cases with complete data were included in the study; therefore, 9% of cases were excluded because of missing data on the use of any EHRs or any other variables in the analyses. Variables on the use of EHRs (9%) and the number of residents treated in a hospital ED (9%) had the highest percentage of missing data. Based on the comments provided by respondents, some respondents failed to answer these questions if the RCC was in the process of obtaining an EHR system, or the respondent was not sure if the RCC’s internal database could be considered an EHR system. In addition, respondents could not provide valid responses if the community did not track the number of residents treated in an ED. A higher proportion of cases excluded from the analyses were extra-large RCCs with over 100 beds, located in an MSA, and had higher RN employee HPRDs and aide employee HPRDs compared with cases with no missing data. Excluded cases had a higher percentage of residents diagnosed with dementia compared with those included in the analyses. No significant differences were observed relative to other characteristics (data on missing analysis are available upon request).

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