Even under optimal internal organizational conditions, implementation can be undermined by changes in organizations’ external environments, such as fluctuations in funding, adjustments in contracting practices, new technology, new legislation, changes in clinical practice guidelines and recommendations, or other environmental shifts. Internal organizational conditions are increasingly reflected in implementation frameworks, but nuanced explanations of how organizations’ external environments influence implementation success are lacking in implementation research. Organizational theories offer implementation researchers a host of existing, highly relevant, and heretofore largely untapped explanations of the complex interaction between organizations and their environment. In this paper, we demonstrate the utility of organizational theories for implementation research. We applied four well-known organizational theories (institutional theory, transaction cost economics, contingency theories, and resource dependency theory) to published descriptions of efforts to implement SafeCare, an evidence-based practice for preventing child abuse and neglect. Transaction cost economics theory explained how frequent, uncertain processes for contracting for SafeCare may have generated inefficiencies and thus compromised implementation among private child welfare organizations. Institutional theory explained how child welfare systems may have been motivated to implement SafeCare because doing so aligned with expectations of key stakeholders within child welfare systems’ professional communities. Contingency theories explained how efforts such as interagency collaborative teams promoted SafeCare implementation by facilitating adaptation to child welfare agencies’ internal and external contexts. Resource dependency theory (RDT) explained how interagency relationships, supported by contracts, memoranda of understanding, and negotiations, facilitated SafeCare implementation by balancing autonomy and dependence on funding agencies and SafeCare developers. In addition to the retrospective application of organizational theories demonstrated above, we advocate for the proactive use of organizational theories to design implementation research. For example, implementation strategies should be selected to minimize transaction costs, promote and maintain congruence between organizations’ dynamic internal and external contexts over time, and simultaneously attend to organizations’ financial needs while preserving their autonomy. We describe implications of applying organizational theory in implementation research for implementation strategies, the evaluation of implementation efforts, measurement, research design, theory, and practice. We also offer guidance to implementation researchers for applying organizational theory.

Background: Past studies examining barriers to patient portal adoption have been conducted with a small number of patients and health care settings, limiting generalizability. Objective: This study had the following two objectives: (1) to assess the prevalence of barriers to patient portal adoption among nonadopters and (2) to examine the association between nonadopter characteristics and reported barriers in a nationally representative sample. Methods: Data from this study were obtained from the 2019 Health Information National Trends Survey. We calculated descriptive statistics to determine the most prevalent barriers and conducted multiple variable logistic regression analysis to examine which characteristics were associated with the reported barriers. Results: The sample included 4815 individuals. Among these, 2828 individuals (58.73%) had not adopted a patient portal. Among the nonadopters (n=2828), the most prevalent barriers were patient preference for in-person communication (1810/2828, 64.00%), no perceived need for the patient portal (1385/2828, 48.97%), and lack of comfort and experience with computers (735/2828, 25.99%). Less commonly, individuals reported having no patient portal (650/2828, 22.98%), no internet access (650/2828, 22.98%), privacy concerns (594/2828, 21.00%), difficulty logging on (537/2828, 18.99%), and multiple patient portals (255/2828, 9.02%) as barriers. Men had significantly lower odds of indicating a preference for speaking directly to a provider compared with women (odds ratio [OR] 0.75, 95% CI 0.60-0.94; P=.01). Older age (OR 1.01, 95% CI 1.00-1.02; P<.001), having a chronic condition (OR 1.83, 95% CI 1.44-2.33; P<.001), and having an income lower than US $20,000 (OR 1.61, 95% CI 1.11-2.34; P=.01) were positively associated with indicating a preference for speaking directly to a provider. Hispanic individuals had significantly higher odds of indicating that they had no need for a patient portal (OR 1.59, 95% CI 1.24-2.05; P<.001) compared with non-Hispanic individuals. Older individuals (OR 1.05, 95% CI 1.04-1.06; P<.001), individuals with less than a high school diploma (OR 3.15, 95% CI 1.79-5.53; P<.001), and individuals with a household income of less than US $20,000 (OR 2.78, 95% CI 1.88-4.11; P<.001) had significantly higher odds of indicating that they were uncomfortable with a computer. Conclusions: The most common barriers to patient portal adoption are preference for in-person communication, not having a need for the patient portal, and feeling uncomfortable with computers, which are barriers that are modifiable and can be intervened upon. Patient characteristics can help predict which patients are most likely to experience certain barriers to patient portal adoption. Further research is needed to tailor implementation approaches based on patients’ needs and preferences.

Background: Electronic visits (e-visits) involve asynchronous communication between clinicians and patients through a secure web-based platform, such as a patient portal, to elicit symptoms and determine a diagnosis and treatment plan. E-visits are now reimbursable through Medicare due to the COVID-19 pandemic. The state of evidence regarding e-visits, such as the impact on clinical outcomes and health care delivery, is unclear. Objective: To address this gap, we examine how e-visits have impacted clinical outcomes and health care quality, access, utilization, and costs. Methods: We conducted a systematic review; MEDLINE, Embase, and Web of Science were searched from January 2000 through October 2020 for peer-reviewed studies that assessed e-visits’ impacts on clinical and health care delivery outcomes. Results: Out of 1859 papers, 19 met the inclusion criteria. E-visit usage was associated with improved or comparable clinical outcomes, especially for chronic disease management (eg, diabetes care, blood pressure management). The impact on quality of care varied across conditions. Quality of care was equivalent or better for chronic conditions, but variable quality was observed in infection management (eg, appropriate antibiotic prescribing). Similarly, the impact on health care utilization varied across conditions (eg, lower utilization for dermatology but mixed impact in primary care). Health care costs were lower for e-visits than those for in-person visits for a wide range of conditions (eg, dermatology and acute visits). No studies examined the impact of e-visits on health care access. It is difficult to draw firm conclusions about effectiveness or impact on care delivery from the studies that were included because many used observational designs. Conclusions: Overall, the evidence suggests e-visits may provide clinical outcomes that are comparable to those provided by in-person care and reduce health care costs for certain health care conditions. At the same time, there is mixed evidence on health care quality, especially regarding infection management (eg, sinusitis, urinary tract infections, conjunctivitis). Further studies are needed to test implementation strategies that might improve delivery (eg, clinical decision support for antibiotic prescribing) and to assess which conditions can be managed via e-visits.

Objective: Our study examines how consistently fall prevention practices and implementation strategies are used by U.S. hospitals. Methods: We conducted a cross-sectional, descriptive study of 60 general adult hospital units. We administered a survey measuring 5 domains of fall prevention practices: visibility and identification, bed modification, patient monitoring, patient safety, and education. We measured 4 domains of implementation strategies including quality management (e.g., providing data and support for quality improvement), planning (e.g., designating leadership), education (e.g., providing consultation and training), and restructuring (e.g., revising staff roles and modifying equipment). Results: Of 60 units, 43% were medical units and 57% were medical-surgical units. The hospital units varied in fall prevention practices, with practices such as keeping a patient’s bed in a locked position (73% strongly agree) being used more consistently than other practices, such as scheduled toileting (15% strongly agree). Our study observed variation in fall prevention implementation strategies. For example, publicly posting fall rates (60% strongly agree) was more consistently used than having a multidisciplinary huddle after a fall event (12% strongly agree). Conclusions: There is substantial variation in the implementation of fall prevention practices and implementation strategies across inpatient units. Our study found that resource-intensive practices (e.g., scheduled toileting) are less consistently used than less resource-intensive practices and that interdisciplinary approaches to fall prevention are limited. Future studies should examine how units tailor fall prevention practices based on patient risk factors and how units decide, based on their available resources, which implementation strategies should be used.

Background: Rapid implementation of telehealth for cancer care during COVID-19 required innovative and adaptive solutions among oncology health care providers and professionals (HPPs). Objective: The aim of this qualitative study was to explore oncology HPPs’ experiences with telehealth implementation during the COVID-19 pandemic. Methods: This study was conducted at Moffitt Cancer Center (Moffitt), an NCI (National Cancer Institute)-Designated Comprehensive Cancer Center. Prior to COVID-19, Moffitt piloted telehealth visits on a limited basis. After COVID-19, Moffitt rapidly expanded telehealth visits. Telehealth visits included real-time videoconferencing between HPPs and patients and virtual check-ins (ie, brief communication with an HPP by telephone only). We conducted semistructured interviews with 40 oncology HPPs who implemented telehealth during COVID-19. The interviews were recorded, transcribed verbatim, and analyzed for themes using Dedoose software (version 4.12). Results: Approximately half of the 40 participants were physicians (n=22, 55%), and one-quarter of the participants were advanced practice providers (n=10, 25%). Other participants included social workers (n=3, 8%), psychologists (n=2, 5%), dieticians (n=2, 5%), and a pharmacist (n=1, 3%). Five key themes were identified: (1) establishing and maintaining patient-HPP relationships, (2) coordinating care with other HPPs and informal caregivers, (3) adapting in-person assessments for telehealth, (4) developing workflows and allocating resources, and (5) future recommendations. Participants described innovative strategies for implementing telehealth, such as coordinating interdisciplinary visits with multiple HPPs and inviting informal caregivers (eg, spouse) to participate in telehealth visits. Health care workers discussed key challenges, such as workflow integration, lack of physical exam and biometric data, and overcoming the digital divide (eg, telehealth accessibility among patients with communication-related disabilities). Participants recommended policy advocacy to support telehealth (eg, medical licensure policies) and monitoring how telehealth affects patient outcomes and health care delivery. Conclusions: To support telehealth growth, implementation strategies are needed to ensure that HPPs and patients have the tools necessary to effectively engage in telehealth. At the same time, cancer care organizations will need to engage in advocacy to ensure that policies are supportive of oncology telehealth and develop systems to monitor the impact of telehealth on patient outcomes, health care quality, costs, and equity.

Our study estimates the prevalence and predictors of wearable device adoption and data sharing with healthcare providers in a nationally representative sample. Data were obtained from the 2019 Health Information National Trend Survey. We conducted multivariable logistic regression to examine predictors of device adoption and data sharing. The sample contained 4159 individuals, 29.9% of whom had adopted a wearable device in 2019. Among adopters, 46.3% had shared data with their provider. Individuals with diabetes (odds ratio [OR], 2.39; 95% CI, 1.66–3.45; P < .0001), hypertension (OR, 2.80; 95% CI, 2.12–3.70; P < .0001), and multiple chronic conditions (OR, 1.55; 95% CI, 1.03–2.32; P < .0001) had significantly higher odds of wearable device adoption. Individuals with a usual source of care (OR, 2.44; 95% CI, 1.95–3.04; P < .0001), diabetes (OR, 1.66; 95% CI, 1.32–2.08; P < .0001), and hypertension (OR, 1.78; 95% CI, 1.44–2.20; P < .0001) had significantly higher odds of sharing data with providers. A third of individuals adopted a wearable medical device and nearly 50% of individuals who owned a device shared data with a provider in 2019. Patients with certain conditions, such as diabetes and hypertension, were more likely to adopt devices and share data with providers. Social determinants of health, such as income and usual source of care, negatively affected wearable device adoption and data sharing, similarly to other consumer health technologies. Wearable device adoption and data sharing with providers may be more common than prior studies have reported; however, digital disparities were noted. Studies are needed that test implementation strategies to expand wearable device use and data sharing into care delivery.