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 text mining study of topics and trends in health care management journals: 1998-2018.

BACKGROUND: Advances in natural language processing and text mining provide a powerful approach to understanding trending themes in the health care management literature. PURPOSE: The aim of this study was to introduce machine learning, particularly text mining and natural language processing, as a viable approach to summarizing a subset of health care management research. The secondary aim of the study was to display the major foci of health care management research and to summarize the literature's evolution trends over a 20-year period. METHODOLOGY/APPROACH: Article abstracts (N = 2,813), from six health care management journals published from 1998 through 2018 were evaluated through latent semantic analysis, topic analysis, and multiple correspondence analysis. RESULTS: Using latent semantic analysis and topic analysis on 2,813 abstracts revealed eight distinct topics. Of the eight, three leadership and transformation, workforce well-being, and delivery of care issues were up-trending, whereas organizational performance, patient-centeredness, technology and innovation, and managerial issues and gender concerns exhibited downward trending. Finance exhibited peaks and troughs throughout the study period. Four journals, Frontiers of Health Services Management, Journal of Healthcare Management, Health Care Management Review, and Advances in Health Care Management, exhibited strong associations with finance, organizational performance, technology and innovation, managerial issues and gender concerns, and workforce well-being. The Journal of Health Management and the Journal of Health Organization and Management were more distant from the other journals and topics, except for delivery of care, and leadership and transformation. CONCLUSION: There was a close association of journals and research topics, and research topics evolved with changes in the health care environment. PRACTICE IMPLICATIONS: As scholars develop research agendas, focus should be on topics important to health care management practitioners for better informed decision-making.

Do Medicare and Medicaid Payer-Mix Change After the Privatization of Public Hospitals?

This study assessed the impact of public hospitals' privatization on payer-mix. We used a national sample of nonfederal, acute care, public hospitals in 1997 and followed them through 2013, resulting in a cohort of 492 hospitals (8,335 hospital-year observations). Privatization to for-profit (FP) status was associated with a greater increase in Medicare payer-mix (ß = 0.13; p ≤ .001), compared with a smaller increase for privatization to not-for-profit (NFP) status (ß = 0.02; p ≤ .05). FP privatization was associated with a greater decrease in Medicaid payer-mix (ß = -0.09; p ≤ .001), compared with NFP privatization (nonsignificant). There is a larger change in payer-mix after FP privatization than after NFP privatization.

Patient Engagement Functionalities in U.S. Hospitals: Is Early Adoption Associated With Financial Performance?

EXECUTIVE SUMMARY: U.S. hospitals are in various stages in their adoption of health information technology (HIT) with patient engagement functionalities. The Health Information Technology for Economic and Clinical Health Act of 2009 allocated $30 billion to incentivize the adoption and use of HIT. This study aims to identify hospital characteristics of early patient engagement functionality adoption and compare the financial performance of groups of hospitals that offer these functionalities according to Rogers' adopter categories. The combined data from the American Hospital Association Annual Survey and Information Technology Supplement, Centers for Medicare & Medicaid cost reports, and Health Resources & Services Administration Area Health Resource Files from 2008 to 2013 yielded a sample of 696 unique acute care hospitals. Three adopter categories-early adopters, early majority, and late majority-were created. Generalized estimating equations were used to examine the financial performance (operating margin, return on assets, total margin, operating expenses, revenue per inpatient day) across the adopter types. Compared to early adopter hospitals, operating margins were lower for early majority hospitals (ß = -.407, p < .05) and late majority hospitals (ß = -.608, p < .05). Moreover, compared to early adopter hospitals, late majority hospitals exhibited significantly lower operating revenue (ß = -.087, p < .01) and operating expenses (ß = -.064, p < .01) per inpatient day. No significant relationships were observed when comparing these groups based on total margin and return on assets. Hospital administrators should consider the positive financial outcomes associated with early adoption of patient engagement functionalities in the decision-making process.

Reduction in Hospitals' Readmission Rates: Role of Hospital-Based Skilled Nursing Facilities.

Hospital readmission within 30 days of discharge is an important quality measure given that it represents a potentially preventable adverse outcome. Approximately, 20% of Medicare beneficiaries are readmitted within 30 days of discharge. Many strategies such as the hospital readmission reduction program have been proposed and implemented to reduce readmission rates. Prior research has shown that coordination of care could play a significant role in lowering readmissions. Although having a hospital-based skilled nursing facility (HBSNF) in a hospital could help in improving care for patients needing short-term skilled nursing or rehabilitation services, little is known about HBSNFs' association with hospitals' readmission rates. This study seeks to examine the association between HBSNFs and hospitals' readmission rates. Data sources included 2007-2012 American Hospital Association Annual Survey, Area Health Resources Files, the Centers for Medicare and Medicaid Services (CMS) Medicare cost reports, and CMS Hospital Compare. The dependent variables were 30-day risk-adjusted readmission rates for acute myocardial infarction (AMI), congestive heart failure, and pneumonia. The independent variable was the presence of HBSNF in a hospital (1 = yes, 0 = no). Control variables included organizational and market factors that could affect hospitals' readmission rates. Data were analyzed using generalized estimating equation (GEE) models with state and year fixed effects and standard errors corrected for clustering of hospitals over time. Propensity score weights were used to control for potential selection bias of hospitals having a skilled nursing facility (SNF). GEE models showed that the presence of HBSNFs was associated with lower readmission rates for AMI and pneumonia. Moreover, higher SNFs to hospitals ratio in the county were associated with lower readmission rates. These findings can inform policy makers and hospital administrators in evaluating HBSNFs as a potential strategy to lower hospitals' readmission rates.

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.