Journal of Healthcare Management最新文献

Goal: Provider buy-in to leadership priorities, patient experience measurement, and quality improvement (QI) is necessary for sustained improvements in care. However, little is documented about provider perceptions of patient experience measurement and QI in primary care. We examined provider perceptions of the work environment, patient care issues, measurement of and improvement in care quality, as well as their knowledge and perceived usefulness of the Consumer Assessment of Healthcare Providers and Systems (CAHPS) Clinician and Group (CG-CAHPS) Survey measures for QI.

Methods: We surveyed and interviewed providers about their use of CG-CAHPS for QI. Of the 143 providers at a large urban Federally Qualified Health Center (FQHC), 74 (52% response) completed a web-based survey; 19 were also interviewed. We asked questions about the clinic environment, use of the CG-CAHPS survey, patient interactions, burnout, job satisfaction, and compensation. We replicated measures from six relevant surveys.

Principal findings: Providers reported working in supportive environments that encouraged QI efforts, having leadership and colleagues who facilitated improvements that enabled them to do their job better (M = 3.8 on a 5-point scale), and serious efforts to solve problems (M = 3.7). Providers also reported significant barriers to patient care (e.g., time pressure and patient complexity). Interviews highlighted providers' difficulty in managing visit duration and ensuring effective patient-provider communication. Participants expressed mixed views on the usefulness of CG-CAHPS scores for QI (M = 2.5), suggesting a need for leadership to discuss and engage with CG-CAHPS performance more regularly. QI in primary care is often guided by patient experience outcomes. The time pressures faced by FQHC providers to care for patients with complex needs heighten the need for targeted interventions that enhance provider support. Providers also identified several areas that needed improvement, some of which are measured by CAHPS items: tools to communicate laboratory or other test results to patients, tools to elicit information on patient concerns, improved access to interpreter services, training for other care team staff, and more discussion of best practices.

Practical applications: To improve the patient experience, primary care organizations should foster environments that support QI and invest more in QI that better incorporates patient feedback and experience measures in ways that are relevant to providers and actionable by organizations to improve care experiences. Addressing these issues has the potential to improve both patient care outcomes and provider satisfaction. This is both practical and important given that CAHPS measures or other standardized patient experience measures, although not mandated, are increasingly in use.

Goal: Diversity, equity, and inclusion (DEI) policies have become central to corporate practices, particularly in the healthcare sector. This study employs signaling theory to explore how healthcare organizations communicate their commitment to DEI through their websites to external stakeholders. Signaling theory posits that organizations use signals to communicate information to stakeholders, and in healthcare, this information is important to prospective employees and patients. As a primary communication channel, the corporate website serves as a vital tool for conveying the organization's values, including DEI commitments.

Methods: This study analyzed a representative sample of 78 US hospitals and healthcare organizations, examining their websites for signals related to DEI. The signaling theory framework helped to evaluate the extent of signaling while considering variables such as gender and ethnic diversity in leadership; explicit diversity language in mission, vision, and values; and the presence of diversity statements. A composite measure scale quantified the magnitude of diversity signaling.

Principal findings: Our quantitative analysis found that while 89.74% of organizations exhibited observable C-suite diversity (i.e., gender or ethnicity), explicit diversity language in core statements was less common (10.26%). Most organizations (67.95%) lacked explicit diversity language in strategic statements, with value statements being the primary location for such language in organizations with diversity language. The composite score revealed a varied commitment to diversity signaling. Most organizations scored low (48.72%, with a score of 1 out 6).

Practical applications: The potential implications of the absence of signals suggest a possible unintended projection of a lack of commitment to DEI. This study's findings emphasize the impact on potential employees and patients, as the absence of diversity signals may dissuade those seeking inclusive environments. This examination of C-suite diversity also underscores the role of diversity in shaping organizational culture and its potential influence on health equity efforts. Organizations that actively communicate their commitment to DEI through explicit language and diverse leadership are better positioned to attract talent and create inclusive healing environments for staff and patients.

Goal: Prior to the COVID-19 pandemic, numerous studies had described gaps in hospital preparedness for natural and man-made disasters and public health emergencies. These gaps were especially evident during the COVID-19 pandemic and recent catastrophes, such as hurricanes, earthquakes, wildfires, and cyberattacks, highlighting the lack of organizational preparedness and response. This study aims to understand the training that healthcare executives should receive in order to prepare for future disasters and health emergencies.

Methods: We developed a survey based on existing literature and insights from healthcare executives and disaster medicine experts, all of whom had gained expertise while responding to prior disasters. Our exploratory study also targeted individuals with executive positions in hospitals. Respondents had varying levels of executive responsibility, including C-suite positions, operations directors, clinicians, and those in other strategic analytic roles.

Principal findings: Our survey found that scenario planning, using either a tabletop exercise or active role-playing-a simulation-based training method in which participants assume specific roles to act out realistic or hypothetical disaster scenarios-was found to be the most relevant type of training, while setting up an emergency operations center was the least relevant. Healthcare executives perceive that they are better prepared for disasters when the training they receive is relevant to them. This signifies that believing in oneself as being prepared leads healthcare executives to perceive that their organizations can implement more comprehensive emergency response activities, and that those activities are deemed to be more effective.

Practical applications: Assessing how healthcare executives perceive their personal preparedness for public health emergencies, such as pandemics and natural disasters, is crucial for enhancing leadership and overall organizational effectiveness in future crises. Organizations and leaders need to be proactive to ensure they effectively respond to increasingly unpredictable crises.

Goal: Consultations via commercial telemedicine platforms have enabled patients to access a larger network of providers whose secondary treatment recommendations may differ from those obtained by primary care providers. Subsequent changes in treatment recommendations may have meaningful implications for cost value and quality of care. However, despite the increased use of telemedicine, the frequency and type of treatment changes that occur are not well understood. This study evaluates the association between digital expert medical opinions (EMOs), treatment strategy changes, and cost implications, using data derived from a specialized musculoskeletal telemedicine platform.

Methods: Musculoskeletal EMOs from a large commercial digital health organization were retrospectively reviewed between 2020 and 2024. Treatment metrics, including surgical diversion (i.e., declining a surgical procedure), as well as the frequency of diagnosis and treatment plan changes, were calculated using existing client records and reports. Subsequently, an economic analysis was done to extrapolate potential cost savings based on treatment changes. Projections were constructed using average consultation cost savings based on Current Procedural Terminology (CPT) billing data and annual capture rates for a real-world enterprise client. Projections were also extrapolated to clients of various carrier sizes.

Principal findings: Among the 544 musculoskeletal EMOs reviewed, 40.1% of consultations resulted in surgical diversion. More than half (53.0%) of treatment plans changed as a result of obtaining EMOs, while the diagnosis change rate was 22.5%. An average cost savings of $8,146.89 per EMO was estimated based on data from a current enterprise client. Extrapolation of this analysis to a medium-sized carrier (10,000 annual claims) and a large-sized carrier (30,000 annual claims) based on data from this enterprise client was estimated to be $754,558.44 and $2,263,675.33, respectively.

Practical applications: Among secondary digital EMOs obtained through a telemedicine platform, more than half of treatment strategies were changed, with surgical diversion observed for 40% of patient cases. Resultant treatment and diagnosis strategy changes may result in increased value for patients, payers, and participating healthcare entities as demonstrated through the economic projections established using real-world data. Further extrapolation of savings based on claim volume, capture rate, and various client sizes may provide additional insights into the utility of telemedicine in other spaces as it pertains to defining appropriate treatment pathways and adjusting optimized costs.

Goal: The role of artificial intelligence (AI) continues to grow in healthcare. It is important to gain a deeper understanding of how patients and care providers perceive its use in patient care and whether they are satisfied with the AI experience. This study performed a scoping review of the published research on patient and physician satisfaction with AI used in healthcare delivery.

Methods: The Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) approach guided the identification, filtering, and analysis of research published from 2003 to 2023 on patient and care provider satisfaction with AI. A standardized data abstraction form created in Microsoft Excel was used to record relevant information in the 45 articles that were selected for review.

Principal findings: Most of the 45 empirical studies included in this study focused on patient satisfaction with AI. Almost half considered AI for treatment exclusively, mostly in hospital or remote settings. Moderate to high degrees of AI satisfaction were identified in 16 of 28 (57%) studies that contained a general AI satisfaction finding of some type. In the other 12 studies, satisfaction levels expressed were lower. Overall, higher satisfaction was seen with AI in diagnostic situations compared to treatment situations. Ninety percent of studies where AI was identified as effective in patient care also found high levels of AI satisfaction.

Practical applications: Both physicians and patients appear receptive to the integration of AI into patient care, regardless of the type of AI used. This receptivity may encourage healthcare organizations to support AI in patient care. Healthcare organizations should identify the full range of drivers of patient and physician satisfaction with AI beyond whether the technology or tool improves clinical outcomes. Future research could analyze contextual factors that may impact AI satisfaction; effects related to age, type of patient care setting, and clinical situation; and an expansion of the types of AI examined.