Department of Health Policy and Management Works
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Item A decade post-HITECH: Critical access hospitals have electronic health records but struggle to keep up with other advanced functions(Oxford University Press, 2021) Apathy, Nate C.; Holmgren, A. Jay; Adler-Milstein, Julia; Health Policy and Management, Richard M. Fairbanks School of Public HealthObjective: Despite broad electronic health record (EHR) adoption in U.S. hospitals, there is concern that an "advanced use" digital divide exists between critical access hospitals (CAHs) and non-CAHs. We measured EHR adoption and advanced use over time to analyzed changes in the divide. Materials and methods: We used 2008 to 2018 American Hospital Association Information Technology survey data to update national EHR adoption statistics. We stratified EHR adoption by CAH status and measured advanced use for both patient engagement (PE) and clinical data analytics (CDA) domains. We used a linear probability regression for each domain with year-CAH interactions to measure temporal changes in the relationship between CAH status and advanced use. Results: In 2018, 98.3% of hospitals had adopted EHRs; there were no differences by CAH status. A total of 58.7% and 55.6% of hospitals adopted advanced PE and CDA functions, respectively. In both domains, CAHs were less likely to be advanced users: 46.6% demonstrated advanced use for PE and 32.0% for CDA. Since 2015, the advanced use divide has persisted for PE and widened for CDA. Discussion: EHR adoption among hospitals is essentially ubiquitous; however, CAHs still lag behind in advanced use functions critical to improving care quality. This may be rooted in different advanced use needs among CAH patients and lack of access to technical expertise. Conclusions: The advanced use divide prevents CAH patients from benefitting from a fully digitized healthcare system. To close the widening gap in CDA, policymakers should consider partnering with vendors to develop implementation guides and standards for functions like dashboards and high-risk patient identification algorithms to better support CAH adoption.Item A large language model for electronic health records(Springer Nature, 2022-12-26) Yang, Xi; Chen, Aokun; PourNejatian, Nima; Shin, Hoo Chang; Smith, Kaleb E.; Parisien, Christopher; Compas, Colin; Martin, Cheryl; Costa, Anthony B.; Flores, Mona G.; Zhang, Ying; Magoc, Tanja; Harle, Christopher A.; Lipori, Gloria; Mitchell, Duane A.; Hogan, William R.; Shenkman, Elizabeth A.; Bian, Jiang; Wu, Yonghui; Health Policy and Management, Richard M. Fairbanks School of Public HealthThere is an increasing interest in developing artificial intelligence (AI) systems to process and interpret electronic health records (EHRs). Natural language processing (NLP) powered by pretrained language models is the key technology for medical AI systems utilizing clinical narratives. However, there are few clinical language models, the largest of which trained in the clinical domain is comparatively small at 110 million parameters (compared with billions of parameters in the general domain). It is not clear how large clinical language models with billions of parameters can help medical AI systems utilize unstructured EHRs. In this study, we develop from scratch a large clinical language model—GatorTron—using >90 billion words of text (including >82 billion words of de-identified clinical text) and systematically evaluate it on five clinical NLP tasks including clinical concept extraction, medical relation extraction, semantic textual similarity, natural language inference (NLI), and medical question answering (MQA). We examine how (1) scaling up the number of parameters and (2) scaling up the size of the training data could benefit these NLP tasks. GatorTron models scale up the clinical language model from 110 million to 8.9 billion parameters and improve five clinical NLP tasks (e.g., 9.6% and 9.5% improvement in accuracy for NLI and MQA), which can be applied to medical AI systems to improve healthcare delivery. The GatorTron models are publicly available at: https://catalog.ngc.nvidia.com/orgs/nvidia/teams/clara/models/gatortron_ogItem A national overview of nonprofit hospital community benefit programs to address the social determinants of health(Oxford University Press, 2023-12-06) Franz, Berkeley; Burns, Ashlyn; Kueffner, Kristin; Bhardwaj, Meeta; Yeager, Valerie A.; Singh, Simone; Puro, Neeraj; Cronin, Cory E.; Health Policy and Management, Richard M. Fairbanks School of Public HealthDecades of research have solidified the crucial role that social determinants of health (SDOH) play in shaping health outcomes, yet strategies to address these upstream factors remain elusive. The aim of this study was to understand the extent to which US nonprofit hospitals invest in SDOH at either the community or individual patient level and to provide examples of programs in each area. We analyzed data from a national dataset of 613 hospital community health needs assessments and corresponding implementation strategies. Among sample hospitals, 69.3% (n = 373) identified SDOH as a top-5 health need in their community and 60.6% (n = 326) reported investments in SDOH. Of hospitals with investments in SDOH, 44% of programs addressed health-related social needs of individual patients, while the remaining 56% of programs addressed SDOH at the community level. Hospitals that were major teaching organizations, those in the Western region of the United States, and hospitals in counties with more severe housing problems had greater odds of investing in SDOH at the community level. Although many nonprofit hospitals have integrated SDOH-related activities into their community benefit work, stronger policies are necessary to encourage greater investments at the community-level that move beyond the needs of individual patients.Item A novel method for evaluating physician communication: A pilot study testing the feasibility of parent-assisted audio recordings via Zoom(Elsevier, 2022) Staras, Stephanie A. S.; Bylund, Carma L.; Desai, Shivani; Harle, Christopher A.; Richardson, Eric; Khalil, Georges E.; Thompson, Lindsay A.; Health Policy and Management, Richard M. Fairbanks School of Public HealthObjective: Quality of physician consultations are best assessed via direct observation, but require intensive in-clinic research staffing. To evaluate physician consultation quality remotely, we pilot tested the feasibility of parents using their personal mobile phones to facilitate audio recordings of pediatric visits. Methods: Across four academic pediatric primary care clinics, we invited all physicians with a patient panel (n=20). For participating physicians, we identified scheduled patients from medical records. We invited parents to participate via text message and phone calls. During their adolescent's appointment, parents used their mobile phone to connect to Zoom for remote research staff to audio record. Results: In Spring 2021, five of 20 (25%) physicians participated. During a nine-week period, we invited parents of all 54 patients seen by participating physicians of which 15 (28%) completed adult consent and adolescent assent and 10 (19%) participated. For 9 recordings, at least 45% of the conversation was audible. Conclusions: It was feasible and acceptable to directly observe physician consultations virtually with Zoom, although participation rates and potentially audio quality were lower. Innovation: Patients used their cellular phone calling features to connect to Zoom where research staff audio-recorded their physician consultation to evaluate communication quality.Item Acceptance of Automated Social Risk Scoring in the Emergency Department: Clinician, Staff, and Patient Perspectives(University of California, 2024) Mazurenko, Olena; Hirsh, Adam T.; Harle, Christopher A.; McNamee, Cassidy; Vest, Joshua R.; Health Policy and Management, Richard M. Fairbanks School of Public HealthIntroduction: Healthcare organizations are under increasing pressure from policymakers, payers, and advocates to screen for and address patients' health-related social needs (HRSN). The emergency department (ED) presents several challenges to HRSN screening, and patients are frequently not screened for HRSNs. Predictive modeling using machine learning and artificial intelligence, approaches may address some pragmatic HRSN screening challenges in the ED. Because predictive modeling represents a substantial change from current approaches, in this study we explored the acceptability of HRSN predictive modeling in the ED. Methods: Emergency clinicians, ED staff, and patient perspectives on the acceptability and usage of predictive modeling for HRSNs in the ED were obtained through in-depth semi-structured interviews (eight per group, total 24). All participants practiced at or had received care from an urban, Midwest, safety-net hospital system. We analyzed interview transcripts using a modified thematic analysis approach with consensus coding. Results: Emergency clinicians, ED staff, and patients agreed that HRSN predictive modeling must lead to actionable responses and positive patient outcomes. Opinions about using predictive modeling results to initiate automatic referrals to HRSN services were mixed. Emergency clinicians and staff wanted transparency on data inputs and usage, demanded high performance, and expressed concern for unforeseen consequences. While accepting, patients were concerned that prediction models can miss individuals who required services and might perpetuate biases. Conclusion: Emergency clinicians, ED staff, and patients expressed mostly positive views about using predictive modeling for HRSNs. Yet, clinicians, staff, and patients listed several contingent factors impacting the acceptance and implementation of HRSN prediction models in the ED.Item Access to Recovery and Recidivism Among Former Prison Inmates(Sage, 2015) Ray, Bradley; Grommon, Eric; Buchanan, Victoria; Brown, Brittany; Watson, Dennis P.; Department of Health Policy and Management, Richard M. Fairbanks School of Public HealthAccess to Recovery (ATR) is a SAMHSA-funded initiative that offers a mix of clinical and supportive services for substance abuse. ATR clients choose which services will help to overcome barriers in their road to recovery, and a recovery consultant provides vouchers and helps link the client to these community resources. One of ATR’s goals was to provide services to those involved in the criminal justice system in the hopes that addressing substance abuse issues could reduce subsequent criminal behaviors. This study examines this goal by looking at recidivism among a sample of clients in one state’s ATR program who returned to the community after incarceration. Results suggest there were few differential effects of service selections on subsequent recidivism. However, there are significant differences in recidivism rates among the agencies that provided ATR services. Agencies with more resources and a focus on prisoner reentry had better recidivism outcomes than those that focus only on substance abuse services.Item Achieving an Optimal Childhood Vaccine Policy(American Medical Association, 2017-09-01) Opel, Douglas J.; Schwartz, Jason L.; Omer, Saad B.; Silverman, Ross D.; Duchin, Jeff; Kodish, Eric; Diekema, Douglas S.; Marcuse, Edgar K.; Orenstein, Walt; Health Policy and Management, School of Public HealthPolicies to remove parents' ability to opt-out from school immunization requirements on the basis of religious or personal beliefs (ie, nonmedical exemptions) may be a useful strategy to increase immunization rates and prevent outbreaks of vaccine-preventable disease. However, there is uncertainty about the effectiveness of this strategy and the range of possible outcomes. We advocate for a more deliberative process through which a broad range of outcomes is scrutinized and the balance of values underlying the policy decision to eliminate nonmedical exemptions is clearly articulated. We identify 3 outcomes that require particular consideration before policies to eliminate nonmedical exemptions are implemented widely and outline a process for making the values underlying such policies more explicit.Item Adoption of Best Practices in Behavioral Health Crisis Care by Mental Health Treatment Facilities(APA, 2023-09-01) Burns, Ashlyn; Menachemi, Nir; Yeager, Valerie A.; Vest, Joshua R.; Mazurenko, Olena; Health Policy and Management, School of Public HealthObjective: The authors aimed to examine adoption of behavioral health crisis care (BHCC) services included in the Substance Abuse and Mental Health Services Administration’s (SAMHSA’s) best practices guidelines. Methods: Secondary data from SAMHSA’s Behavioral Health Treatment Services Locator in 2022 were used. BHCC best practices were measured on a summated scale capturing whether a mental health treatment facility (N=9,385) adopted BHCC best practices, including provision of these services to all age groups: emergency psychiatric walk-in services, crisis intervention teams, onsite stabilization, mobile or offsite crisis responses, suicide prevention, and peer support. Descriptive statistics were used to examine organizational characteristics (such as facility operation, type, geographic area, license, and payment methods) of mental health treatment facilities nationwide, and a map was created to show locations of best practices BHCC facilities. Logistic regressions were performed to identify facilities’ organizational characteristics associated with adopting BHCC best practices. Results: Only 6.0% (N=564) of mental health treatment facilities fully adopted BHCC best practices. Suicide prevention was the most common BHCC service, offered by 69.8% (N=6,554) of the facilities. A mobile or offsite crisis response service was the least common, adopted by 22.4% (N=2,101). Higher odds of adopting BHCC best practices were significantly associated with public ownership (adjusted OR [AOR]=1.95), accepting self-pay (AOR=3.18), accepting Medicare (AOR=2.68), and receiving any grant funding (AOR=2.45). Conclusions: Despite SAMHSA guidelines recommending comprehensive BHCC services, a fraction of facilities have fully adopted BHCC best practices. Efforts are needed to facilitate widespread uptake of BHCC best practices nationwide.Item 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 HealthObjectives: 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.Item Adverse Selection in the Children’s Health Insurance Program(Sage, 2015-01) Morrisey, Michael A.; Blackburn, Justin; Becker, David J.; Sen, Bisakha; Kilgore, Meredith L.; Caldwell, Cathy; Menachemi, Nir; Department of Nursing, IU School of NursingThis study investigates whether new enrollees in the Alabama Children’s Health Insurance Program have different claims experience from renewing enrollees who do not have a lapse in coverage and from continuing enrollees. The analysis compared health services utilization in the first month of enrollment for new enrollees (who had not been in the program for at least 12 months) with utilization among continuing enrollees. A second analysis compared first-month utilization of those who renew immediately with those who waited at least 2 months to renew. A 2-part model estimated the probability of usage and then the extent of usage conditional on any utilization. Claims data for 826 866 child-years over the period from 1999 to 2012 were used. New enrollees annually constituted a stable 40% share of participants. Among those enrolled in the program, 13.5% renewed on time and 86.5% of enrollees were late to renew their enrollment. In the multivariate 2-part models, controlling for age, gender, race, income eligibility category, and year, new enrollees had overall first-month claims experience that was nearly $29 less than continuing enrollees. This was driven by lower ambulatory use. Late renewals had overall first-month claims experience that was $10 less than immediate renewals. However, controlling for the presence of chronic health conditions, there was no statistically meaningful difference in the first-month claims experience of late and early renewals. Thus, differences in claims experience between new and continuing enrollees and between early and late renewals are small, with greater spending found among continuing and early renewing participants. Higher claims experience by early renewals is attributable to having chronic health conditions.