Associations Between Practice Characteristics and Demonstration of Stage 1 Meaningful Use for the Electronic Health Record Incentive Program.

BACKGROUND: The Medicare and Medicaid meaningful use (MU) incentive programs promote adoption and "meaningful use" of certified electronic health records among hospitals and eligible providers in outpatient settings, with a goal of improving the quality of patient care. Despite the potential importance of MU for providers and patients, little is currently known about the practice characteristics that facilitate providers' demonstration of MU. This study examined whether selected practice characteristics were associated with providers' meeting Stage 1 MU objectives at the end of 1 year in a single large North Carolina integrated delivery system. METHODS: Our retrospective database analysis included all 702 eligible providers from 54 ambulatory care practices on the main campus of the University of North Carolina Health Care System. We assessed associations between providers' ability to meet Stage 1 MU objectives as of December 2012 and the following practice characteristics: practice specialty, size, and mix of Medicare- and Medicaid-eligible providers. RESULTS: The following practice characteristics were associated with providers' ability to meet MU objectives: primary care practices as compared to specialty practices (odds ratio [OR] = 2.49; 95% CI, 1.11-5.62), small practices as compared to medium-sized practices (OR = 0.29; 95% CI, 0.09-0.89), and the presence of only Medicare-eligible providers in the practice as compared to the presence of only Medicaid-eligible providers (OR = 6.48; 95% Cl, 1.08-38.97). LIMITATIONS: Because our sample was drawn from a single integrated delivery system, results may not be generalizable to all ambulatory practice settings. CONCLUSIONS: This study suggests that larger practices, primary care practices, and practices comprised of Medicare-eligible providers may be better able to meet MU objectives. Further research is needed to evaluate strategies that account for practice characteristics and other contextual factors in the MU implementation process.

Stage 1 of the meaningful use incentive program for electronic health records: a study of readiness for change in ambulatory practice settings in one integrated delivery system.

BACKGROUND: Meaningful Use (MU) provides financial incentives for electronic health record (EHR) implementation. EHR implementation holds promise for improving healthcare delivery, but also requires substantial changes for providers and staff. Establishing readiness for these changes may be important for realizing potential EHR benefits. Our study assesses whether provider/staff perceptions about the appropriateness of MU and their departments' ability to support MU-related changes are associated with their reported readiness for MU-related changes. METHODS: We surveyed providers and staff representing 47 ambulatory practices within an integrated delivery system. We assessed whether respondent's role and practice-setting type (primary versus specialty care) were associated with reported readiness for MU (i.e., willingness to change practice behavior and ability to document actions for MU) and hypothesized predictors of readiness (i.e., perceived appropriateness of MU and department support for MU). We then assessed associations between reported readiness and the hypothesized predictors of readiness. RESULTS: In total, 400 providers/staff responded (response rate approximately 25%). Individuals working in specialty settings were more likely to report that MU will divert attention from other patient-care priorities (12.6% vs. 4.4%, p = 0.019), as compared to those in primary-care settings. As compared to advanced-practice providers and nursing staff, physicians were less likely to have strong confidence in their department's ability to solve MU implementation problems (28.4% vs. 47.1% vs. 42.6%, p = 0.023) and to report strong willingness to change their work practices for MU (57.9% vs. 83.3% vs. 82.0%, p < 0.001). Finally, provider/staff perceptions about whether MU aligns with departmental goals (OR = 3.99, 95% confidence interval (CI) = 2.13 to 7.48); MU will divert attention from other patient-care priorities (OR = 2.26, 95% CI = 1.26 to 4.06); their department will support MU-related change efforts (OR = 3.99, 95% CI = 2.13 to 7.48); and their department will be able to solve MU implementation problems (OR = 2.26, 95% CI = 1.26 to 4.06) were associated with their willingness to change practice behavior for MU. CONCLUSIONS: Organizational leaders should gauge provider/staff perceptions about appropriateness and management support of MU-related change, as these perceptions might be related to subsequent implementation.

Assessing organizational capacity for achieving meaningful use of electronic health records.

BACKGROUND: Health care institutions are scrambling to manage the complex organizational change required for achieving meaningful use (MU) of electronic health records (EHR). Assessing baseline organizational capacity for the change can be a useful step toward effective planning and resource allocation. PURPOSE: The aim of this article is to describe an adaptable method and tool for assessing organizational capacity for achieving MU of EHR. Data on organizational capacity (people, processes, and technology resources) and barriers are presented from outpatient clinics within one integrated health care delivery system; thus, the focus is on MU requirements for eligible professionals, not eligible hospitals. METHODS: We conducted 109 interviews with representatives from 46 outpatient clinics. FINDINGS: Most clinics had core elements of the people domain of capacity in place. However, the process domain was problematic for many clinics, specifically, capturing problem lists as structured data and having standard processes for maintaining the problem list in the EHR. Also, nearly half of all clinics did not have methods for tracking compliance with their existing processes. Finally, most clinics maintained clinical information in multiple systems, not just the EHR. The most common perceived barriers to MU for eligible professionals included EHR functionality, changes to workflows, increased workload, and resistance to change. PRACTICE IMPLICATIONS: Organizational capacity assessments provide a broad institutional perspective and an in-depth clinic-level perspective useful for making resource decisions and tailoring strategies to support the MU change effort for eligible professionals.

Implementation of SARS-CoV-2 Monoclonal Antibody Infusion Sites at Three Medical Centers in the United States: Strengths and Challenges Assessment to Inform COVID-19 Pandemic and Future Public Health Emergency Use.

Monoclonal antibody therapeutics to treat coronavirus disease (COVID-19) have been authorized by the US Food and Drug Administration under Emergency Use Authorization (EUA). Many barriers exist when deploying a novel therapeutic during an ongoing pandemic, and it is critical to assess the needs of incorporating monoclonal antibody infusions into pandemic response activities. We examined the monoclonal antibody infusion site process during the COVID-19 pandemic and conducted a descriptive analysis using data from 3 sites at medical centers in the United States supported by the National Disaster Medical System. Monoclonal antibody implementation success factors included engagement with local medical providers, therapy batch preparation, placing the infusion center in proximity to emergency services, and creating procedures resilient to EUA changes. Infusion process challenges included confirming patient severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) positivity, strained staff, scheduling, and pharmacy coordination. Infusion sites are effective when integrated into pre-existing pandemic response ecosystems and can be implemented with limited staff and physical resources.

Staffing and Capacity Planning for SARS-CoV-2 Monoclonal Antibody Infusion Facilities: A Performance Estimation Calculator Based on Discrete-Event Simulations.

Background: The COVID-19 pandemic has significantly stressed healthcare systems. The addition of monoclonal antibody (mAb) infusions, which prevent severe disease and reduce hospitalizations, to the repertoire of COVID-19 countermeasures offers the opportunity to reduce system stress but requires strategic planning and use of novel approaches. Our objective was to develop a web-based decision-support tool to help existing and future mAb infusion facilities make better and more informed staffing and capacity decisions. Materials and Methods: Using real-world observations from three medical centers operating with federal field team support, we developed a discrete-event simulation model and performed simulation experiments to assess performance of mAb infusion sites under different conditions. Results: 162,000 scenarios were evaluated by simulations. Our analyses revealed that it was more effective to add check-in staff than to add additional nurses for middle-to-large size sites with ≥2 infusion nurses; that scheduled appointments performed better than walk-ins when patient load was not high; and that reducing infusion time was particularly impactful when load on resources was only slightly above manageable levels. Discussion: Physical capacity, check-in staff, and infusion time were as important as nurses for mAb sites. Health systems can effectively operate an infusion center under different conditions to provide mAb therapeutics even with relatively low investments in physical resources and staff. Conclusion: Simulations of mAb infusion sites were used to create a capacity planning tool to optimize resource utility and allocation in constrained pandemic conditions, and more efficiently treat COVID-19 patients at existing and future mAb infusion sites.

Real-world Effect of Monoclonal Antibody Treatment in COVID-19 Patients in a Diverse Population in the United States.

BACKGROUND: Monoclonal antibodies (mAbs) against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are a promising treatment for limiting the progression of coronavirus disease 2019 (COVID-19) and decreasing strain on hospitals. Their use, however, remains limited, particularly in disadvantaged populations. METHODS: Electronic health records were reviewed from SARS-CoV-2 patients at a single medical center in the United States that initiated mAb infusions in January 2021 with the support of the US Department of Health and Human Services' National Disaster Medical System. Patients who received mAbs were compared with untreated patients from the time period before mAb availability who met eligibility criteria for mAb treatment. We used logistic regression to measure the effect of mAb treatment on the risk of hospitalization or emergency department (ED) visit within 30 days of laboratory-confirmed COVID-19. RESULTS: Of 598 COVID-19 patients, 270 (45%) received bamlanivimab and 328 (55%) were untreated. Two hundred thirty-one patients (39%) were Hispanic. Among treated patients, 5/270 (1.9%) presented to the ED or required hospitalization within 30 days of a positive SARS-CoV-2 test, compared with 39/328 (12%) untreated patients (P < .001). After adjusting for age, gender, and comorbidities, the risk of ED visit or hospitalization was 82% lower in mAb-treated patients compared with untreated patients (95% CI, 56%-94%). CONCLUSIONS: In this diverse, real-world COVID-19 patient population, mAb treatment significantly decreased the risk of subsequent ED visit or hospitalization. Broader treatment with mAbs, including in disadvantaged patient populations, can decrease the burden on hospitals and should be facilitated in all populations in the United States to ensure health equity.

Patient Portals: Who uses them? What features do they use? And do they reduce hospital readmissions?

BACKGROUND: Patient portals have demonstrated numerous benefits including improved patient-provider communication, patient satisfaction with care, and patient engagement. Recent literature has begun to illustrate how patients use selected portal features and an association between portal usage and improved clinical outcomes. OBJECTIVES: This study sought to: (1) identify patient characteristics associated with the use of a patient portal; (2) determine the frequency with which common patient portal features are used; and (3) examine whether the level of patient portal use (non-users, light users, active users) is associated with 30-day hospital readmission. METHODS: My UNC Chart is the patient portal for the UNC Health Care System. We identified adults discharged from three UNC Health Care hospitals with acute myocardial infarction, congestive heart failure, or pneumonia and classified them as active, light, or non-users of My UNC Chart. Multivariable analyses were conducted to compare across user groups; logistic regression was used to predict whether patient portal use was associated with 30-day readmission. RESULTS: Of 2,975 eligible patients, 83.4% were non-users; 8.6% were light users; and 8.0% were active users of My UNC Chart. The messaging feature was used most often. For patients who were active users, the odds of being readmitted within 30 days was 66% greater than patients who were non-users (p<0.05). There was no difference in 30-day readmission between non-users and light users. CONCLUSIONS: The vast majority of patients who were given an access code for My UNC Chart did not use it within 30 days of discharge. Of those who used the portal, active users had a higher odds of being readmitted within 30 days. Health care systems should consider strategies to: (1) increase overall use of patient portals and (2) target patients with the highest comorbidity scores to reduce hospital readmissions.