The Political Economy of Digital Health Equity: Structural Analysis.

Digital technologies have produced many innovations in care delivery and enabled continuity of care for many people when in-person care was impossible. However, a growing body of research suggests that digital health can also exacerbate health inequities for those excluded from its benefits for reasons of cost, digital literacy, and structural discrimination related to characteristics such as age, race, ethnicity, and socioeconomic status. In this paper, we draw on a political economy perspective to examine structural barriers to progress in advancing digital health equity at the policy level. Considering the incentive structures and investments of powerful actors in the field, we outline how characteristics of neoliberal capitalism in Western contexts produce and sustain digital health inequities by describing 6 structural challenges to the effort to promote health equity through digital health, as follows: (1) the revenue-first incentives of technology corporations, (2) the influence of venture capital, (3) inequitable access to the internet and digital devices, (4) underinvestment in digital health literacy, (5) uncertainty about future reimbursement of digital health, and (6) justified mistrust of digital health. Building on these important challenges, we propose future immediate and long-term directions for work to support meaningful change for digital health equity.

Identifying patterns in administrative tasks through structural topic modeling: A study of task definitions, prevalence, and shifts in a mental health practice's operations during the COVID-19 pandemic.

OBJECTIVE: This case study illustrates the use of natural language processing for identifying administrative task categories, prevalence, and shifts necessitated by a major event (the COVID-19 [coronavirus disease 2019] pandemic) from user-generated data stored as free text in a task management system for a multisite mental health practice with 40 clinicians and 13 administrative staff members. MATERIALS AND METHODS: Structural topic modeling was applied on 7079 task sequences from 13 administrative users of a Health Insurance Portability and Accountability Act-compliant task management platform. Context was obtained through interviews with an expert panel. RESULTS: Ten task definitions spanning 3 major categories were identified, and their prevalence estimated. Significant shifts in task prevalence due to the pandemic were detected for tasks like billing inquiries to insurers, appointment cancellations, patient balances, and new patient follow-up. CONCLUSIONS: Structural topic modeling effectively detects task categories, prevalence, and shifts, providing opportunities for healthcare providers to reconsider staff roles and to optimize workflows and resource allocation.

Examining innovation in hospital units: a complex adaptive systems approach.

BACKGROUND: We are in an innovation age for healthcare delivery. Some note that the complexity of healthcare delivery may make innovation in this setting more difficult and may require more adaptive solutions. The aim of this study is to examine the relationship between unit complexity and innovation, using a complex adaptive systems approach in a hospital setting. METHODS: We conducted a quantitative study of 31 hospital units within one hospital and use complex adaptive systems (CAS) theory to examine how two CAS factors, autonomy and performance orientation, moderate the relationship between unit complexity and innovation. RESULTS: We find that unit complexity is associated with higher innovation performance when autonomy is low rather than high. We also find that unit complexity is associated with higher innovation performance when performance orientation is high rather than low. Our findings make three distinct contributions: we quantify the influence of complexity on innovation success in the health care sector, we examine the impact of autonomy on innovation in health care, and we are the first to examine performance orientation on innovation in health care. CONCLUSIONS: This study tackles the long debate about the influence of complexity on healthcare delivery, particularly innovation. Instead of being subject to the influence of complexity with no means of making progress or gaining control, hospitals looking to implement innovation programs should provide guidance to teams and departments regarding the type of innovation sought and provide support in terms of time and management commitment. Hospitals should also find ways to promote and make successful pilot implementations of such innovations visible in the organization. A close connection between the targeted innovation and the overall success and performance of the hospital unit is ideal.

Patient navigation to improve diabetes outpatient care at a safety-net hospital: a retrospective cohort study.

BACKGROUND: Recent emphasis on value based care and population management, such as Accountable Care Organizations in the United States, promote patient navigation to improve the quality of care and reduce costs. Evidence supporting the efficacy of patient navigation for chronic disease care is limited. The objective of this study was to evaluate the effect of a patient navigation program on medical and administrative outcomes among patients with diabetes in an urban, safety-net hospital clinic setting. METHODS: A retrospective cohort study with pre- and post-intervention periods was conducted. Eligible patients were those with A1C ≥ 8.5% and at least one appointment no-show in the previous 12 months. The intervention and reference groups were balanced on observed characteristics and baseline outcome levels using propensity score matching. The effect of patient navigation was isolated using the difference-in-differences approach. Primary outcomes were A1C, low-density lipoprotein cholesterol, triglycerides, random urine microalbumin, the number of scheduled appointments, clinic visits, emergency visits, and inpatient stays, and the percentage of arrivals, cancellations, and no-shows to scheduled appointments. RESULTS: Of 797 eligible patients, 328 entered the navigation program. Matching reduced the sample size to 392 individuals (196 in each group). Patient navigation resulted in improved A1C (-1.1 percentage points; p < .001), more scheduled appointments (+ 5.3 per year; p < .001), more clinic visits (+6.4 per year; p < .001), more arrivals to scheduled appointments (+7.4 percentage points; p = .009) and fewer no-shows (-9.8 percentage points; p < .001). CONCLUSIONS: Navigation was associated with improved glycemic control and better clinic engagement among patients with diabetes. Further research is important to identify what features of navigation in diabetes care are critical to achieving success and to understand navigators' role in other settings.

How do integrative practices influence patient-centered care?: An exploratory study comparing diabetes and mental health care.

BACKGROUND: Integration between organizational units to achieve common goals has been of interest to health systems because of the potential to improve patient-centered care. However, the means by which integrative practices actually influence patient-centered care remain unclear. Whereas many studies claim a positive association between implementation of integrative practices and patient-centered care, others raise concerns that integrative practices may not necessarily improve patient-centered care. PURPOSE: The aim of this study was to explore the mechanism by which integrative practices influence patient-centered care and to suggest a systematic approach for effective integration. APPROACH: We conducted a qualitative study comparing diabetes and mental health services through focus groups with 60 staff members from one health maintenance organization. We developed quantitative indicators to support the suggested model. FINDINGS: We identified a five-category framework of integrative practices that each directly and distinctively influences patient-centered care. Moreover, our findings suggest that integrative practices influence patient-centered care indirectly through creation of interdependent treatment competence, which enables providers to repeatedly deliver interdependent treatment in a flexible and adaptive way. PRACTICAL IMPLICATIONS: Providers should carefully implement integrative practices considering patient and disease characteristics, as our findings suggest that more implementation of integrative practices is not necessarily better for patient-centered care. Specifically, optimal implementation refers to the collective implementation of different integrative practices and thus encompasses both the extent (i.e., the amount of currently implemented practices out of those considered important to implement) and the extensiveness (i.e., the amount relative to the implementation of other practices) that may lead to interdependent treatment competence and higher patient-centered care. We suggest a creative measurement method of comparing the relative implementation of integrative practices that may assist managers and policy makers in developing interdependent treatment competence.

Architecting the Future U.S. Military Psychological Health Enterprise via Policy and Procedure Analysis.

Although researchers suggest that a systems approach is required to make meaningful advances in the U.S. psychological health care system for service members, limited research has considered such an approach. This research uses an enterprise architecting framework to identify the system's strengths and areas for opportunity as they relate to the Ecosystem, Stakeholders, Strategy, Process, Organization, Knowledge, Information, and Infrastructure. Codifying qualitative data from publicly available U.S. Defense Health Agency and U.S. Service Branch doctrine, policy guidance, and concepts of operations, our findings indicate that the psychological health care system is strongly process-oriented and mentions a variety of key stakeholders and their roles and responsibilities in the enterprise. Potential opportunities of improvement for the system include a stronger emphasis on the development and transfer of knowledge capabilities, and a stronger information-based infrastructure.

A conceptual model of the psychological health system for U.S. active duty service members: an approach to inform leadership and policy decision making.

The influence of individual-level factors such as pretraumatic risk and protective factors and the availability of unit-level and enterprise-level factors on psychological health outcomes have been previously considered individually, but have not been considered in tandem across the U.S. Military psychological health system. We use the existing literature on military psychological health to build a conceptual system dynamics model of the U.S. Military psychological health system "service-cycle" from accession and deployment to future psychological health screening and treatment. The model highlights a few key observations, challenges, and opportunities for improvement for the system that relate to several topics including the importance of modeling operational demand combined with the population's psychological health as opposed to only physical health; the role of resilience and post-traumatic growth on the mitigation of stress; the positive and negative effects of pretraumatic risk factors, unit support, and unit leadership on the service-cycle; and the opportunity to improve the system more rapidly by including more feedback mechanisms regarding the usefulness of pre- and post-traumatic innovations to medical leaders, funding authorities, and policy makers.