Browsing by Subject "Nursing Home"

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    Adoption of Health Information Technology Among US Nursing Facilities
    (Elsevier, 2018-12-19) Vest, Joshua R.; Jung, Hye-Young; Wiley, Kevin; Kooreman, Harold; Pettit, Lorren; Unruh, Mark A.; Health Policy and Management, School of Public Health
    Objectives: Nursing facilities have lagged behind in the adoption interoperable health information technology (i.e. technologies that allow the sharing and use of electronic patient information between different information systems). The objective of this study was to estimate the nationwide prevalence of electronic health record (EHR) adoption among nursing facilities and to identify the factors associated with adoption. Design: Cross-sectional survey. Setting & participants: We surveyed members of the Society for Post-Acute & Long-Term Care Medicine (AMDA) about their organizations’ health information technology usage and characteristics. Measurements: Using questions adopted from existing instruments, the survey measured nursing home’s EHR adoption, the ability to send, receive, search and integrate electronic information, as well as barriers to usage. Additionally, we linked survey responses to public use secondary data sources to construct measurements for eight determinants known to be associated with organizational adoption: innovativeness, functional differentiation, role specialization, administrative intensity, professionalism, complexity, technical knowledge resources and slack resources. A series of regression models estimated the association between potential determinants and technology adoption. Results: 84% of nursing facilities reported using an EHR. After controlling for all other factors, respondents who characterized their organization as more innovative had more than 6 times the odds (adjusted odds ratio = 6.39; 95%CI = 2.69, 15.21) of adopting an EHR. Organization innovativeness was also associated with an increased odds of being able to send, integrate, and search for electronic information. The most commonly identified barrier to sharing clinical information among nursing facilities with an EHR was a reported absence of interoperability (57%). Conclusions/Implications: An organizational culture that fosters innovation and awareness campaigns by professional societies may facilitate further adoption and effective use of technology. This will be increasingly important as policymakers continue to emphasize the use of EHRs and interoperability to improve the quality of care in nursing facilities.
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    Identification, Quantification, and Characterization of Nursing Home Resident Pain Trajectories
    (2022-05) Cole, Connie Sue; Hickman, Susan; Blackburn, Justin; Carpenter, Janet S.; Chen, Chen X.
    Pain prevalence in nursing home (NH) residents is high. Studies report up to 85.0% of NH residents experience pain and up to 58.0% experience persistent pain. Pain in NH residents can lead to decreased happiness, quality of life, and life satisfaction. Traditionally, pain has been studied in relation to specific comorbid conditions or pain subtypes (nociceptive, neuropathic) with little consideration for the dynamic (temporal) nature of pain. Current pain subtypes are clinically linked to recommended pain treatments and provide insight into underlying mechanisms. However, current pain subtypes are limited by their focus on pain origin, do not include severity or duration of the pain experience, and do not illustrate how the course or trajectory of pain changes over time. Understanding the trajectory of pain experience can provide opportunities to alter the course of pain experience, improve residents’ quality of life and prevent adverse outcomes. This dissertation provides the first evidence of four distinct pain trajectories among NH residents including persistent pain which was associated with several resident characteristics and clinically relevant diagnosis. Using residents’ characteristics associated with persistent pain, such as a history of fracture or contracture, may improve care planning based on early identification or risk stratification and can improve mitigation of persistent pain. To identify and characterize pain trajectories in NH residents, the following activities were completed (1) systematic review of the literature related to prevalence of pain and associated factors in NH residents, (2) cross-sectional analysis of secondary data to examine prevalence of pain, persistent pain, and factors associated with pain in NH residents, and (3) a longitudinal retrospective analysis of secondary data using group-based trajectory modeling to identify, quantify, and characterize NH pain trajectories. The findings from this study highlight the prevalence and complexity of pain in NH residents.
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    Identifying risk factors for healthcare-associated infections from electronic medical record home address data
    (BMC, 2010-09-17) Wilson, Jeffrey S.; Shepherd, David C.; Rosenman, Marc B.; Kho, Abel N.; Geography, School of Liberal Arts
    Background Residential address is a common element in patient electronic medical records. Guidelines from the U.S. Centers for Disease Control and Prevention specify that residence in a nursing home, skilled nursing facility, or hospice within a year prior to a positive culture date is among the criteria for differentiating healthcare-acquired from community-acquired methicillin-resistant Staphylococcus aureus (MRSA) infections. Residential addresses may be useful for identifying patients residing in healthcare-associated settings, but methods for categorizing residence type based on electronic medical records have not been widely documented. The aim of this study was to develop a process to assist in differentiating healthcare-associated from community-associated MRSA infections by analyzing patient addresses to determine if residence reported at the time of positive culture was associated with a healthcare facility or other institutional location. Results We identified 1,232 of the patients (8.24% of the sample) with positive cultures as probable cases of healthcare-associated MRSA based on residential addresses contained in electronic medical records. Combining manual review with linking to institutional address databases improved geocoding rates from 11,870 records (79.37%) to 12,549 records (83.91%). Standardization of patient home address through geocoding increased the number of matches to institutional facilities from 545 (3.64%) to 1,379 (9.22%). Conclusions Linking patient home address data from electronic medical records to institutional residential databases provides useful information for epidemiologic researchers, infection control practitioners, and clinicians. This information, coupled with other clinical and laboratory data, can be used to inform differentiation of healthcare-acquired from community-acquired infections. The process presented should be extensible with little or no added data costs.