Examining Training Motivations Among Public Health Workers

CONTEXT: As public health needs and priorities evolve, maintaining a trained public health workforce is critical to the success of public health efforts. Researchers have examined training needs in various contexts and subpopulations, but a nationally representative study of what motivates public health workers to seek out training has yet to be conducted. By understanding these motivations, public health agencies and policy makers can appeal to worker motivations in both training programs and organizational incentives. OBJECTIVE: The purpose of this article was to describe overall training motivations and identify patterns of training motivations among public health workers. This study also explored whether or not training needs differ across prevalent motivational patterns. DESIGN AND PARTICIPANTS: Using data from the 2017 Public Health Workforce Interests and Needs Survey (PH WINS), the study used latent class analysis (LCA) to identify motivational patterns and logistic regression to analyze associations with training needs. RESULTS: The most prominent motivation to seek training was personal growth (82.7% of respondents). LCA identified 4 motivational classes of public health workers: those motivated by organizational pressure and requirements (31.8%), those motivated indiscriminately by all factors (28.4%), those motivated primarily by personal growth (21.7%), and those motivated by organizational accommodations and supports (18.2%). Motivational class was not associated with indicating training needs in any of 8 training domains, nor was it associated with indicating any training need in any domain. CONCLUSIONS: Public health agencies should consider the different motivational classes present in the public health workforce. In particular, motivational classes that represent organizational choices suggest that public health agencies should both motivate workers with organizational requirements and pressure from managers and offer institutional support via paid travel and covered time for training

Health Information Technology and Accountable Care Organizations: A Systematic Review and Future Directions

Background: Since the inception of Accountable Care Organizations (ACOs), many have acknowledged the potential synergy between ACOs and health information technology (IT) in meeting quality and cost goals. Objective: We conducted a systematic review of the literature in order to describe what research has been conducted at the intersection of health IT and ACOs and identify directions for future research. Methods: We identified empirical studies discussing the use of health IT via PubMed search with subsequent snowball reference review. The type of health IT, how health IT was included in the study, use of theory, population, and findings were extracted from each study. Results: Our search resulted in 32 studies describing the intersection of health IT and ACOs, mainly in the form of electronic health records and health information exchange. Studies were divided into three streams by purpose; those that considered health IT as a factor for ACO participation, health IT use by current ACOs, and ACO performance as a function of health IT capabilities. Although most studies found a positive association between health IT and ACO participation, studies that address the performance of ACOs in terms of their health IT capabilities show more mixed results. Conclusions: In order to better understand this emerging relationship between health IT and ACO performance, we propose future research should consider more quasi-experimental studies, the use of theory, and merging health, quality, cost, and health IT use data across ACO member organizations

Opt-in consent policies: potential barriers to hospital health information exchange

Objectives: First, to assess whether hospitals in states requiring explicit patient consent (“opt-in”) for health information exchange (HIE) are more likely to report regulatory barriers to HIE. Second, to analyze whether these policies correlate with hospital volume of HIE. Study Design: Cross-sectional analysis of US non-federal acute care hospitals in 2016. Methods: We combined legal scholarship surveying HIE-relevant state laws with the AHA Annual IT Supplement for regulatory barriers and hospital characteristics. Data from CMS reports for hospitals attesting to Meaningful Use Stage 2 in 2016 (MU2, renamed “Promoting Interoperability” in 2018) captured hospital HIE volume. We used multivariate logistic regression and linear regression to estimate the association between opt-in state consent policies and reported regulatory barriers and HIE volume, respectively. Results: Hospitals in states with opt-in consent policies were 7.8 percentage points more likely than hospitals in opt-out states to report regulatory barriers to HIE (p=0.03). In subgroup analyses, this finding held among hospitals that did not attest to MU2 (7.7pp, p=0.02). Among hospitals attesting, we did not find a relationship between opt-in policies and regulatory barriers (8.0pp, p=0.13), nor evidence of a relationship between opt-in policies and HIE volume (ß=0.56, p=0.76). Conclusions: Our findings suggest that opt-in consent laws may carry greater administrative burdens compared to opt-out policies. However, less technologically advanced hospitals may bear more of this burden. Furthermore, opt-in policies may not impact HIE volume for hospitals that have already achieved a degree of technological sophistication. Policymakers should carefully consider the incidence of administrative burdens when crafting laws pertaining to HIE

Barriers to Hospital Electronic Public Health Reporting and Implications for the COVID-19 Pandemic

We sought to identify barriers to hospital reporting of electronic surveillance data to local, state, and federal public health agencies and the impact on areas projected to be overwhelmed by the COVID-19 pandemic. Using 2018 American Hospital Association data, we identified barriers to surveillance data reporting and combined this with data on the projected impact of the COVID-19 pandemic on hospital capacity at the hospital referral region level. Our results find the most common barrier was public health agencies lacked the capacity to electronically receive data, with 41.2% of all hospitals reporting it. We also identified 31 hospital referral regions in the top quartile of projected bed capacity needed for COVID-19 patients in which over half of hospitals in the area reported that the relevant public health agency was unable to receive electronic data. Public health agencies’ inability to receive electronic data is the most prominent hospital-reported barrier to effective syndromic surveillance. This reflects the policy commitment of investing in information technology for hospitals without a concomitant investment in IT infrastructure for state and local public health agencies

Information Needs and Requirements for Decision Support in Primary Care: An Analysis of Chronic Pain Care

Decision support system designs often do not align with the information environments in which clinicians work. These work environments may increase Clinicians’ cognitive workload and harm their decision making. The objective of this study was to identify information needs and decision support requirements for assessing, diagnosing, and treating chronic noncancer pain in primary care. We conducted a qualitative study involving 30 interviews with 10 primary care clinicians and a subsequent multidisciplinary systems design workshop. Our analysis identified four key decision requirements, eight clinical information needs, and four decision support design seeds. Our findings indicate that clinicians caring for chronic pain need decision support that aggregates many disparate information elements and helps them navigate and contextualize that information. By attending to the needs identified in this study, decision support designers may improve Clinicians’ efficiency, reduce mental workload, and positively affect patient care quality and outcomes

Are They Aligned? An Analysis of Social Media-Based Nurse Well-Being Concerns and Well-Being Programs

# Background Nurse burnout and distress pose patient safety risks due to impaired nurse attention, increased likelihood of medical error, and increased nurse turnover leading to a reduction in the number of nurses available to deliver care. Some healthcare facilities have launched well-being programs in response to increasing rates of burnout. Many of these programs are based on survey data which may be incomplete, resulting in programs that are not as comprehensive as they should be. We sought to identify nurse concerns related to burnout and well-being through analysis of social media data. We aligned these concerns with well-being program leader perceptions of factors contributing to burnout and well-being program initiatives. # Methods We conducted a qualitative study composed of two parts: social media analysis and semistructured interviews with well-being leaders. The social media analysis focused on 120 nurse comments on Reddit that were retrieved based on a keyword search using the terms "burnout," "stress," and "wellbeing." The interviews were conducted with nine well-being leaders from seven different healthcare systems. Well-being program leaders were asked about factors contributing to burnout and lack of well-being, initiatives to address these factors, and metrics used to evaluate their programs. The social media comments and interview data were reviewed by two experts to identify topics, themes, and subthemes grounded in wellness models. # Results Of the 120 social media comments analyzed, the most frequent topic was Lack of Meaningful Recognition, Compensation, and Influence (n=46 of 120, 38.3%), followed by Work Environment (n=43, 35.8%) and Uninformed or Misinformed Public (n=31, 25.8%). Several themes emerged and the most prevalent was Constrained Professional Agency with the most prevalent subtheme of health system or macrosystem policies or regulations that limit nurses' ability to respond effectively to patient care needs. Of the seven healthcare systems interviewed, the most common topics that emerged from asking about the factors contributing to the lack of nurse well-being were the Work Environment (n=6 of 7, 85.7%), followed by Lack of Meaningful Recognition, Compensation, and Influence (n=4, 57.1%), and Inadequate or Inaccessible Well-Being Resources (n=3, 42.9%). Several novel initiatives were identified, and most healthcare systems relied on surveys as their key metric. # Conclusions The social media analysis revealed nurse concerns that may not be identified as factors contributing to lack of well-being by well-being program leaders. There is an opportunity to optimize our understanding of nurse concerns around well-being through social media, and an opportunity to better align nurse concerns with the focus of well-being programs