Mapping 2 Decades of Research in Health Services Research, Health Policy, and Health Economics Journals.

OBJECTIVE: To identify major research topics and exhibit trends in these topics in 15 health services research, health policy, and health economics journals over 2 decades. DATA SOURCES: The study sample of 35,159 abstracts (1999-2020) were collected from PubMed for 15 journals. STUDY DESIGN: The study used a 3-phase approach for text analyses: (1) developing the corpus of 40,618 references from PubMed (excluding 5459 of those without abstract or author information); (2) preprocessing and generating the term list using natural language processing to eliminate irrelevant textual data and identify important terms and phrases; (3) analyzing the preprocessed text data using latent semantic analysis, topic analyses, and multiple correspondence analysis. PRINCIPAL FINDINGS: Application of analyses generated 16 major research topics: (1) implementation/intervention science; (2) HIV and women's health; (3) outcomes research and quality; (4) veterans/military studies; (5) provider/primary-care interventions; (6) geriatrics and formal/informal care; (7) policies and health outcomes; (8) medication treatment/therapy; (9) patient interventions; (10) health insurance legislation and policies; (11) public health policies; (12) literature reviews; (13) cost-effectiveness and economic evaluation; (14) cancer care; (15) workforce issues; and (16) socioeconomic status and disparities. The 2-dimensional map revealed that some journals have stronger associations with specific topics. Findings were not consistent with previous studies based on user perceptions. CONCLUSION: Findings of this study can be used by the stakeholders of health services research, policy, and economics to develop future research agendas, target journal submissions, and generate interdisciplinary solutions by examining overlapping journals for particular topics.

A critical analysis of COVID-19 research literature: Text mining approach.

OBJECTIVE: Among the stakeholders of COVID-19 research, clinicians particularly experience difficulty keeping up with the deluge of SARS-CoV-2 literature while performing their much needed clinical duties. By revealing major topics, this study proposes a text-mining approach as an alternative to navigating large volumes of COVID-19 literature. MATERIALS AND METHODS: We obtained 85,268 references from the NIH COVID-19 Portfolio as of November 21. After the exclusion based on inadequate abstracts, 65,262 articles remained in the final corpus. We utilized natural language processing to curate and generate the term list. We applied topic modeling analyses and multiple correspondence analyses to reveal the major topics and the associations among topics, journal countries, and publication sources. RESULTS: In our text mining analyses of NIH's COVID-19 Portfolio, we discovered two sets of eleven major research topics by analyzing abstracts and titles of the articles separately. The eleven major areas of COVID-19 research based on abstracts included the following topics: 1) Public Health, 2) Patient Care & Outcomes, 3) Epidemiologic Modeling, 4) Diagnosis and Complications, 5) Mechanism of Disease, 6) Health System Response, 7) Pandemic Control, 8) Protection/Prevention, 9) Mental/Behavioral Health, 10) Detection/Testing, 11) Treatment Options. Further analyses revealed that five (2,3,4,5, and 9) of the eleven abstract-based topics showed a significant correlation (ranked from moderate to weak) with title-based topics. CONCLUSION: By offering up the more dynamic, scalable, and responsive categorization of published literature, our study provides valuable insights to the stakeholders of COVID-19 research, particularly clinicians.

Identifying research themes and trends in the top 20 cancer journals through textual analysis.

BACKGROUND: The rapid growth in cancer research continues expanding the literature. Text mining approaches help make sense of large bodies of scientific literature and integrate the mounting data into the health care delivery system. Our objective is to generate a comprehensive understanding of the themes and trends in cancer research. METHODS: We employed a three-step text mining process of corpus generation and term-list creation and analysis, including latent semantic analysis for dimension reduction and factor analysis for topic identification to analyze 93,423 abstracts from the top 20 cancer/oncology journals for the period between 1999 and 2020. RESULTS: We identified 14 distinct topics in cancer literature. The results revealed the uptrend topics - including cell signaling (T-2), immunotherapy (T-3), clinical trials (T-5), disparities and epidemiology (T-7), cancer practice and policy (T-8), outcome research (T-9), and molecular therapeutics (T-10). - and downtrend topics such as cell death (T-1), early phase clinical trials (T-4), angiogenesis (T-6), cancer screening (T-12), and transplant (T-13). The topics of biomarkers(T-11) and cancer genetics(T-16) remained relatively stable. While the topics of angiogenesis (n = 10,490) and cell death (n = 10,258) included the highest number of abstracts, biomarkers (n = 3203), and cancer genetic (n = 4322) themes included the least number of articles. These findings suggest that despite having the lowest numbers of publications, certain topics such as cancer genetic (T-16) and biomarkers (T-11) have been exhibiting a stable trend and drawing a steady amount of attention from cancer researchers over the past 20 years. CONCLUSION: Findings of this study contribute explanatory insight about themes and trends in cancer research, which can help researchers and stakeholders to identify areas for future studies. POLICY SUMMARY STATEMENT: The findings indicate the increasing efforts to improve cancer practice and cancer care through policy efforts. Therefore, policymakers and other stakeholders may use the findings in prioritization and funding of specific topics.

Analyzing Workers' Compensation Claims and Payments Made Using Data from a Large Insurance Provider.

BACKGROUND: All states in the USA have established Workers' Compensation (WC) insurance systems/programs. WC systems address key occupational safety and health concerns. This effort uses data from a large insurance provider for the years 2011-2018 to provide estimates for WC payments, stratified by the claim severity, i.e., medical only, and indemnity. METHODS: Besides providing descriptive statistics, we used generalized estimating equations to analyze the association between the key injury characteristics (nature, source, and body part injured) and total WC payments made. We also provide the overall cost burden for the former. RESULTS: Out of the total 151,959 closed claims, 83% were medical only. The mean overall WC payment per claim for the claims that resulted in a payment was $1477 (SD: $7221). Adjusted models showed that mean payments vary by claim severity. For example, among medical only claims, the mean payment was the highest for amputations ($3849; CI: $1396, $10,608), and among disability and death related claims, ruptures cost the most ($14,285; $7772, $26,255). With frequencies taken into account, the overall cost burden was however the highest for strains. CONCLUSIONS: Workplace interventions should prioritize both the costs of claims on average and the frequency.

Healthcare Research and Analytics Data Infrastructure Solution: A Data Warehouse for Health Services Research.

BACKGROUND: Health services researchers spend a substantial amount of time performing integration, cleansing, interpretation, and aggregation of raw data from multiple public or private data sources. Often, each researcher (or someone in their team) duplicates this effort for their own project, facing the same challenges and experiencing the same pitfalls discovered by those before them. OBJECTIVE: This paper described a design process for creating a data warehouse that includes the most frequently used databases in health services research. METHODS: The design is based on a conceptual iterative process model framework that utilizes the sociotechnical systems theory approach and includes the capacity for subsequent updates of the existing data sources and the addition of new ones. We introduce the theory and the framework and then explain how they are used to inform the methodology of this study. RESULTS: The application of the iterative process model to the design research process of problem identification and solution design for the Healthcare Research and Analytics Data Infrastructure Solution (HRADIS) is described. Each phase of the iterative model produced end products to inform the implementation of HRADIS. The analysis phase produced the problem statement and requirements documents. The projection phase produced a list of tasks and goals for the ideal system. Finally, the synthesis phase provided the process for a plan to implement HRADIS. HRADIS structures and integrates data dictionaries provided by the data sources, allowing the creation of dimensions and measures for a multidimensional business intelligence system. We discuss how HRADIS is complemented with a set of data mining, analytics, and visualization tools to enable researchers to more efficiently apply multiple methods to a given research project. HRADIS also includes a built-in security and account management framework for data governance purposes to ensure customized authorization depending on user roles and parts of the data the roles are authorized to access. CONCLUSIONS: To address existing inefficiencies during the obtaining, extracting, preprocessing, cleansing, and filtering stages of data processing in health services research, we envision HRADIS as a full-service data warehouse integrating frequently used data sources, processes, and methods along with a variety of data analytics and visualization tools. This paper presents the application of the iterative process model to build such a solution. It also includes a discussion on several prominent issues, lessons learned, reflections and recommendations, and future considerations, as this model was applied.

Introduction to "health informatics, healthcare quality and safety, and healthcare simulation: the new triad to advance healthcare operations".

This special themed international issue explores the multiple facets of health informatics, healthcare quality and safety, and healthcare simulation from different parts of the world. The papers in this issue fall into two broad themes. The first theme uses the intersection to address better management of care including physical design layout. The second theme examines innovative uses of the triad to prevent critical and non-critical safety events. The collection of papers culminates with a position paper reporting on the interdependence that is emerging as an important triad for research and practice within medical education, system development and testing, and teamwork and communication and concludes with reducing imprecision and factual errors in handoffs. Findings from the special collection of papers can inform managers and leaders on advancing operations in healthcare settings.

The emerging literature for the triad of health informatics, healthcare quality and safety, and healthcare simulation.

The areas of health informatics, healthcare quality and safety, and healthcare simulation are often thought of as separate domains. The purpose of this position paper is to report on the interdependence that is emerging as an important triad across the healthcare/health system continuum. A qualitative review of 24 studies suggests the interdependence of health informatics, healthcare quality and safety, and healthcare simulation reaches much broader than traditional utilisation of simulation. We suggest ways that organisations can take advantage of the interdependence of this triad across a broader variety of healthcare environments, including teamwork, communication, and complex system relationships. In conclusion, the reviewed 24 studies suggest that the research in the triad focuses on simulation education and computerised simulation, and when coupled with health informatics, bears greater strength on quality improvement or patient safety.

Inclusiveness and ethical considerations for observational, translational, and clinical cancer health disparity research.

BACKGROUND: Although general trends in cancer outcomes are improving, racial/ethnic disparities in patient outcomes continue to widen, suggesting disparity-related shortcomings in cancer research designs. METHODS: Using convenience sampling, a total of 24 data sources, representing several research designs and 5 high-burden tumor types, were included for analyses. The percentages of races/ethnicities across each design/tumor type were compared with those of the 2017 US Census data. The authors used a framework based on the Belmont principles to evaluate the ethical strengths and/or weaknesses of each design. RESULTS: In all designs, white individuals were found to be overrepresented. African American and Asian individuals were underrepresented, and Native Americans had consistently poor or no representation. In general, ethical concerns varied according to the study design. Clinical trials were high with regard to respect for persons and beneficence but low for equitable subject selection related to the inclusion of race/ethnicity. Observational study designs were more inclusive for race/ethnicity compared with clinical and translational studies, but their clinical usefulness was less. CONCLUSIONS: The authors proposed that ethical concerns should vary according to the study design. Because observational designs have strengths in inclusiveness for race/ethnicity, their clinical usefulness can be improved by extending the Learning Health System in hospital catchment populations, the use of health records linked to biospecimens, and minority oversampling. Likewise, minority enrollment into clinical trials can be improved through Learning Health System linking and by using National Cancer Institute-mandated Community Outreach and Engagement Cores. This will allow precision medicine for otherwise overlooked minority subgroups.

Longitudinal analysis of high-technology medical services and hospital financial performance.

BACKGROUND: U.S. hospitals have been investing in high-technology medical services as a strategy to improve financial performance. Despite the interest in high-tech medical services, there is not much information available about the impact of high-tech services on financial performance. PURPOSE: The aim of this study was to examine the impact of high-tech medical services on financial performance of U.S. hospitals by using the resource-based view of the firm as a conceptual framework. METHODOLOGY/APPROACH: Fixed-effects regressions with 2 years lagged independent variables using a longitudinal panel sample of 3,268 hospitals (2005-2010). It was hypothesized that hospitals with rare or large numbers (breadth) of high-tech medical services will experience better financial performance. FINDINGS: Fixed effects regression results supported the link between a larger breadth of high-tech services and total margin, but only among not-for-profit hospitals. Both breadth and rareness of high-tech services were associated with high total margin among not-for-profit hospitals. Neither breadth nor rareness of high-tech services was associated with operating margin. Although breadth and rareness of high-tech services resulted in lower expenses per inpatient day among not-for-profit hospitals, these lower costs were offset by lower revenues per inpatient day. PRACTICE IMPLICATIONS: Enhancing the breadth of high-tech services may be a legitimate organizational strategy to improve financial performance, especially among not-for-profit hospitals. Hospitals may experience increased productivity and efficiency, and therefore lower inpatient operating costs, as a result of newer technologies. However, the negative impact on operating revenue should caution hospital administrators about revenue reducing features of these technologies, which may be related to the payer mix that these technologies may attract. Therefore, managers should consider both the cost and revenue implications of these technologies.

Three-Dimensional Anthropometric Evaluation of Facial Morphology.

OBJECTIVES: The objectives of this study were to evaluate sexual dimorphism for facial features within Colombian and Mexican-American populations and to compare the facial morphology by sex between these 2 populations. MATERIALS AND METHODS: Three-dimensional facial images were acquired by using the portable 3dMDface system, which captured 223 subjects from 2 population groups of Colombians (n = 131) and Mexican-Americans (n = 92). Each population was categorized into male and female groups for evaluation. All subjects in the groups were aged between 18 and 30 years and had no apparent facial anomalies. A total of 21 anthropometric landmarks were identified on the 3-dimensional faces of each subject. The independent t test was used to analyze each data set obtained within each subgroup. RESULTS: The Colombian males showed significantly greater width of the outercanthal width, eye fissure length, and orbitale than the Colombian females. The Colombian females had significantly smaller lip and mouth measurements for all distances except upper vermillion height than Colombian males. The Mexican-American females had significantly smaller measurements with regard to the nose than Mexican-American males. Meanwhile, the heights of the face, the upper face, the lower face, and the mandible were all significantly less in the Mexican-American females. The intercanthal and outercanthal widths were significantly greater in the Mexican-American males and females. Meanwhile, the orbitale distance of Mexican-American sexes was significantly smaller than those of the Colombian males and females. The Mexican-American group had significantly larger nose width and length of alare than the Colombian group regarding both sexes. With respect to the nasal tip protrusion and nose height, they were significantly smaller in the Colombian females than in the Mexican-American females. The face width was significantly greater in the Colombian males and females. CONCLUSIONS: Sexual dimorphism for facial features was presented in both the Colombian and Mexican-American populations. In addition, there were significant differences in facial morphology between these 2 populations.

Text-mining analysis of mHealth research.

In recent years, because of the advancements in communication and networking technologies, mobile technologies have been developing at an unprecedented rate. mHealth, the use of mobile technologies in medicine, and the related research has also surged parallel to these technological advancements. Although there have been several attempts to review mHealth research through manual processes such as systematic reviews, the sheer magnitude of the number of studies published in recent years makes this task very challenging. The most recent developments in machine learning and text mining offer some potential solutions to address this challenge by allowing analyses of large volumes of texts through semi-automated processes. The objective of this study is to analyze the evolution of mHealth research by utilizing text-mining and natural language processing (NLP) analyses. The study sample included abstracts of 5,644 mHealth research articles, which were gathered from five academic search engines by using search terms such as mobile health, and mHealth. The analysis used the Text Explorer module of JMP Pro 13 and an iterative semi-automated process involving tokenizing, phrasing, and terming. After developing the document term matrix (DTM) analyses such as single value decomposition (SVD), topic, and hierarchical document clustering were performed, along with the topic-informed document clustering approach. The results were presented in the form of word-clouds and trend analyses. There were several major findings regarding research clusters and trends. First, our results confirmed time-dependent nature of terminology use in mHealth research. For example, in earlier versus recent years the use of terminology changed from "mobile phone" to "smartphone" and from "applications" to "apps". Second, ten clusters for mHealth research were identified including (I) Clinical Research on Lifestyle Management, (II) Community Health, (III) Literature Review, (IV) Medical Interventions, (V) Research Design, (VI) Infrastructure, (VII) Applications, (VIII) Research and Innovation in Health Technologies, (IX) Sensor-based Devices and Measurement Algorithms, (X) Survey-based Research. Third, the trend analyses indicated the infrastructure cluster as the highest percentage researched area until 2014. The Research and Innovation in Health Technologies cluster experienced the largest increase in numbers of publications in recent years, especially after 2014. This study is unique because it is the only known study utilizing text-mining analyses to reveal the streams and trends for mHealth research. The fast growth in mobile technologies is expected to lead to higher numbers of studies focusing on mHealth and its implications for various healthcare outcomes. Findings of this study can be utilized by researchers in identifying areas for future studies.

Vitamin E modulates lung oxidative stress, serum copper, zinc, and iron levels in rats with pulmonary contusion.

BACKGROUND/AIM: To evaluate the effects of oxidant/antioxidant mechanisms and levels of trace elements on trauma-stimulated moderate pulmonary contusions after vitamin E administration. MATERIALS AND METHODS: Sixty-three male Sprague Dawley rats were used. Animals were studied in 4 groups. Vitamin E (150 mg/kg) was injected intraperitoneally 30 min after trauma and on the first and second days. Blood samples were obtained for nitric oxide (NO) levels and superoxide dismutase (SOD) and glutathione peroxidase (GSH-Px) activities. Zinc (Zn+2), copper (Cu+2), and iron (Fe+3) were measured in serum. RESULTS: Lung contusion increased serum and tissue NO levels and SOD activities and decreased GSH-Px activities (P < 0.05). Vitamin E significantly (P < 0.05) decreased NO levels and SOD activities and increased GSH-Px. Serum Zn+2, Cu+2, and Fe+3 levels were statistically significantly influenced by the administration of vitamin E (P < 0.05). Group 4 had lower scores compared to Group 3 (P < 0.05) and no difference compared to Group 1 (P > 0.05). CONCLUSION: These results suggest that treatment with vitamin E reduces lung oxidative stress and related mechanisms in isolated lung contusion as demonstrated by an experimental rat model.

Association between retinal thickness measured by spectral-domain optical coherence tomography (OCT) and rod-mediated dark adaptation in non-exudative age-related maculopathy.

AIM: To examine associations between retinal thickness and rod-mediated dark adaptation in older adults with non-exudative age-related maculopathy (ARM) or normal macular health. METHODS: A cross-sectional study was conducted with 74 adults ≥ 50 years old from the comprehensive ophthalmology and retina services of an academic eye centre. ARM presence and disease severity in the enrolment eye was defined by the masked grading of stereofundus photos using the Clinical Age-Related Maculopathy grading system. High-definition, spectral-domain optical coherence tomography was used to estimate retinal thickness in a grid of regions in the macula. Rod-mediated dark adaptation, recovery of light sensitivity after a photo-bleach, was measured over a 20-min period for a 500 nm target presented at 5° on the inferior vertical meridian. Main outcomes of interest were retinal thickness in the macula (µm) and parameters of rod-mediated dark adaptation (second slope, third slope, average sensitivity, final sensitivity). RESULTS: In non-exudative disease retinal thickness was decreased in greater disease severity; thinner retina was associated with reductions in average and final rod-mediated sensitivity even after adjustment for age and visual acuity. CONCLUSIONS: Impairment in rod-mediated dark adaptation in non-exudative ARM is associated with macular thinning.