Public Health, Population Health, and Epidemiology Informatics: Recent Research and Trends in the United States

Digital surveillance: The interest in mouthwash-related information

BACKGROUND

The comprehension of the interests of Internet users regarding their health-related searches may reveal the community's demands about oral health. The study aimed to characterize the interests of Google users related to mouthwash in Australia, Brazil, Chile, Japan, Mexico, Russia, the United Kingdom, the United States, Saudi Arabia and South Africa applying the Google Trends.

METHODS

This longitudinal retrospective study analysed the mouthwash-related interest of Google users from January 2004 to December 2020. The monthly variation of relative search volume (RSV) and the main queries related were determined using Google Trends. Autoregressive integrated moving average (ARIMA) forecasting models were built to establish the predictive RSV values for mouthwash for additional 12 months. Auto-correlation plots and a general additive model (GAM) were used to diagnose trends and seasonality in RSV curves. In addition, the influence of social isolation related to the outbreak of COVID-19 were analysed.

RESULTS

The RSVs curves showed a considerable increase in searches related to mouthwash to AUS, BRA, JAP, MEX, GBR and USA (RSV > 25), while the growth was slight to CHI, KSA, RSA and RUS (RSV < 25) over the years, without influence of monthly seasonality. All countries showed a significant increase in mouthwash interest after the outbreak of COVID-19, except for KSA and RUS. The mouthwash-related searches were associated to specific brands or chemical compositions, treatments, whitening agents, homemade mouthwash and indications for the 'best mouthwash'.

CONCLUSIONS

In general, there was an increasing interest of Google users in mouthwash-related topics between 2004 and 2020. In addition, in most countries, there was an expansion in searches during the social isolation of the COVID-19 pandemics.

Collaborative clinical reasoning learning using an integrated care pathway in undergraduate interprofessional education: An explorative study

Collaborative clinical reasoning (CCR) is part of interprofessional collaborative practice and aims to negotiate and manage patient problems. An integrated care pathway (ICP) can be used as a framework for developing comprehensive patient care, typically in a clinical setting. This study aims to explore the CCR process in undergraduate interprofessional teams and the use of ICP as guidance in discussing a patient's problem and its comprehensive management. This is a qualitative study following phenomenology and was performed in an interprofessional education (IPE) program held by Health Science Cluster Universitas Indonesia. A total of four observations involving 40 students and four focus-group discussions involving 18 students from different health professions backgrounds were conducted to explore the CCR process using the ICP framework. In-depth interviews with four tutors from different health professions backgrounds and document analysis were also conducted as triangulation processes. This study shows that CCR was held in two stages - individual and group. The ICP framework could be used as a guiding tool in the CCR process to discuss the patient's management and discharge plan. This study also demonstrates that there are several challenges in this learning process, including the clinical case used in the discussion, the need for prior knowledge and previous exposure to IPE and the ICP framework, and health professions' dominance during the discussion. This study provides evidence on learning of CCR using the ICP framework as a guiding tool in a pre-licensure IPE program. This approach is useful for preparing students to develop an interprofessional, comprehensive, and holistic health care plan and to help them understand the roles of each profession.

Establishment of primary health information in the COVID-19 outbreak: A cross-sectional study of population awareness of self-testing

The global pandemic of the Corona Virus Disease 2019 is a severe threat to human health. This paper aims to investigate the status of mass health self-examination awareness and its influencing factors during the COVID-19 epidemic and establish complete health information to intervene in the prevention and control of the COVID-19 epidemic. The study used a simple random sampling method to survey permanent residents (9761 people) aged 15–70 years in a region of Jiangsu Province, China. The survey collected data using a questionnaire with acceptable reliability and validity. The data were entered into SPSS 26, and the data were analyzed using the chi-square test, ANOVA, and logistic regression. The differences in the status of mass health self-examination during COVID-19 were statistically significant (P < 0.05) in terms of the literacy level of the grassroots population, ease of access to medical care, primary medical and health conditions, the situation of medical examination programs, and the construction of primary health information technology. The establishment of comprehensive and systematic primary health information can effectively assist in raising people's awareness of health self-examination and promoting health behaviors, which is essential for enhancing COVID-19 prevention and intervention.

Barriers to Dissemination of Local Health Data Faced by US State Agencies: Survey Study of Behavioral Risk Factor Surveillance System Coordinators

Background

Advances in information technology have paved the way to facilitate accessibility to population-level health data through web-based data query systems (WDQSs). Despite these advances in technology, US state agencies face many challenges related to the dissemination of their local health data. It is essential for the public to have access to high-quality data that are easy to interpret, reliable, and trusted. These challenges have been at the forefront throughout the COVID-19 pandemic.

Objective

The purpose of this study is to identify the most significant challenges faced by state agencies, from the perspective of the Behavioral Risk Factor Surveillance System (BRFSS) coordinator from each state, and to assess if the coordinators from states with a WDQS perceive these challenges differently.

Methods

We surveyed BRFSS coordinators (N=43) across all 50 US states and the District of Columbia. We surveyed the participants about contextual factors and asked them to rate system aspects and challenges they faced with their health data system on a Likert scale. We used two-sample t tests to compare the means of the ratings by participants from states with and without a WDQS.

Results

Overall, 41/43 states (95%) make health data available over the internet, while 65% (28/43) employ a WDQS. States with a WDQS reported greater challenges (P=.01) related to the cost of hardware and software (mean score 3.44/4, 95% CI 3.09-3.78) than states without a WDQS (mean score 2.63/4, 95% CI 2.25-3.00). The system aspect of standardization of vocabulary scored more favorably (P=.01) in states with a WDQS (mean score 3.32/5, 95% CI 2.94-3.69) than in states without a WDQS (mean score 2.85/5, 95% CI 2.47-3.22).

Conclusions

Securing of adequate resources and commitment to standardization are vital in the dissemination of local-level health data. Factors such as receiving data in a timely manner, privacy, and political opposition are less significant barriers than anticipated.

Local Health Departments' Engagement in Activities to Address Opioid Use and Abuse: The Influence of Surveillance Systems' Use

AIMS

To examine the extent to which local health departments (LHDs) conduct activities to address opioid use and abuse. To test the hypothesis that (i) LHDs' access to data from an electronic syndromic surveillance system is associated with conducting activities to address opioid use and abuse, and (ii) among those LHDs with access to syndromic surveillance data, the use of syndromic and other surveillance data on opioid-related events is associated with LHDs' report of conducting activities to address opioid use and abuse.

METHODS

Logistic regression was used to analyze data from the 2018 Forces of Change Survey of a statistically representative sample of 966 LHDs, of which 591 participated in the survey.

RESULTS

The LHDs' access to a syndromic surveillance system was significantly associated with their report of conducting activities to address opioid use and abuse. Compared with LHDs that had no surveillance systems, odds of participating in activities to address the opioid use or abuse were higher for LHDs that managed their own surveillance systems (adjusted odds ratio, AOR = 3.022, P = .03) and those who had but did not manage their own surveillance systems (AOR = 1.920, P < .01). The LHDs' use of syndromic surveillance systems (AOR = 2.98, P = .01) or other surveillance systems (AOR = 2.21, P = .03) was also associated with higher odds to participate in activities to address the opioid use or abuse (vs no such use).

CONCLUSION

The LHDs are strategically well positioned to play their role in addressing this multifaceted epidemic. Access to data or information from electronic syndromic surveillance systems that use hospital emergency department data might significantly improve LHDs' engagement in conducting activities to address opioid use and abuse within their communities while building their capacity to face the next epidemic.

Place and health infrastructure in the Gulf Cooperation Council: A systematic scoping review of GIS applications in health

The rising burden of non-communicable diseases is taxing health systems globally. Using data science and information systems is necessary to support public health practices. Geographic Information Systems (GIS) are key to inform and help guide public health policies related to place (i.e. location or where one lives) and how it affects health. Despite the increasing use of GIS for public health globally, its applications to health in the Gulf Cooperation Council (GCC) states remains largely unknown. This systematic scoping review aimed to uncover how GIS has been used in the GCC states to understand "place" and "health". A comprehensive search of the literature was performed in PubMed, Scopus, Science Citation Index Expanded, ScienceDirect, Embase, IEEE Xplore, and ACM Digital Library during June 2020. All journal articles involving the use of GIS for human health applications in the GCC states published in English in peerreviewed scientific journals were considered. After removing duplicates and applying eligibility criteria, qualitative content analysis was performed for 24 of 630 studies. GIS uses in the GCC states were categorized as health access and planning (n=9), health risk analysis (n=8), disease surveillance (n=6) and community health profiling (n=1). The majority of the uncovered evidence in this study focused on the Kingdom of Saudi Arabia. The results of this study indicate a deficiency of published evidence regarding the use of GIS in support of public health in other GCC states. This stands to compromise planning and strategic decision making in health risk analysis, disease surveillance, community health profiling, health services provision and health interventions.

Potential value of electronic health records in capturing data on geriatric frailty for population health

OBJECTIVES

Despite the availability of many frailty measures to identify older adults at risk, frailty instruments are not routinely used for risk assessment in population health management. Here, we assessed the potential value of electronic health records (EHRs) and administrative claims in providing the necessary data for variables used across various frailty instruments.

SETTING AND PARTICIPANTS

The review focused on studies conducted worldwide. Participants included older people aged 50 and older.

DESIGN

We identified frailty instruments published between 2011 and 2018. Frailty variables used in each of the frailty instruments were extracted, grouped, and categorized across health determinants and various clinical factors.

MEASURES

The availability of the extracted frailty variables across various data sources (e.g., EHRs, administrative claims, and surveys) was evaluated by experts.

RESULTS

We identified 135 frailty instruments, which contained 593 unique variables. Clinical determinants of health were the best represented variables across frailty instruments (n = 516; 87 %), unlike social and health services factors (n = 33; ∼5% and n = 32; ∼5%). Most frailty instruments require at least one variable that is not routinely available in EHRs or claims (n = 113; ∼83 %). Only 22 frailty instruments have the potential to completely rely on EHR (structured or free-text data) and/or claims data, and possibly be operationalized on a population-level.

CONCLUSIONS AND IMPLICATIONS

Frailty instruments continue to be highly survey-based. More research is therefore needed to develop EHR-based frailty instruments for population health management. This will permit organizations and societies to stratify risk and better allocate resources among different older adult populations.

Current Approaches and Trends in Graduate Public Health Informatics Education in the United States: Four Case Studies from the Field

Background:Public Health Informatics (PHI) has taken on new importance in recent years as health and well-being face a number of challenges, including environmental disasters, emerging infectious diseases, such as Zika, Ebola and SARS-CoV-2, the growing impact of the Influenza virus, the opioid epidemic, and social determinants of health. Understanding the relationship between climate change and the health of populations adds further complexity to global health issues. Objectives: To describe four examples of curricula that exist in U.S. based graduate-level public and population health informatics training programs. Methods: Biomedical informatics educators are challenged to provide learners with relevant, interesting, and meaningful educational experiences in working with and learning from the many data sources that comprise the domain of PHI. Programs at four institutions were reviewed to examine common teaching practices that stimulate learners to explore the field of public health informatics. Results: Four case studies represent a range of pedagogical approaches to meeting the requirements of three established accreditation/certification agencies relevant to PHI education. Despite their differences, each program achieved the established learning objectives along with a substantive record of student learning achievements. Conclusion: The overarching goal of empowering learners to serve an active and dynamic role in enhancing preventive measures, informing policy, improving personal health behaviors, and clarifying issues such as quality, cost of care, and the social determinants of health, are essential components of PHI education and training, and must receive additional consideration now and in the future by educators, policy makers, administrators, and government officials.

Developing a Public Health Monitoring System in a War-torn Region: A Field Report From Iraqi Kurdistan

Wars, terrorism, and embargos destroyed facilities and shattered the public health system of Iraq. Today, there is limited documented knowledge about the health situation of the Iraqi population, particularly because health data are not systematically collected. Therefore, the capacity of the health system to address the major health problems of the population is considerably reduced. This report describes the implementation, started in 2015, of an electronic system for epidemiological monitoring and health surveillance, designed to collect and manage health care data in Iraqi Kurdistan. The aim of the program is to network all of the main health centers and hospitals of the region, then of the whole country, and to train medical and administrative staff in the management and analysis of health data. In countries recovering from war, a functioning health monitoring system is essential in guiding the development of appropriate public health interventions, a key instrument to prepare the health system to respond to future emergencies.

Explainable statistical learning in public health for policy development: the case of real-world suicide data

BACKGROUND

In recent years, the availability of publicly available data related to public health has significantly increased. These data have substantial potential to develop public health policy; however, this requires meaningful and insightful analysis. Our aim is to demonstrate how data analysis techniques can be used to address the issues of data reduction, prediction and explanation using online available public health data, in order to provide a sound basis for informing public health policy.

METHODS

Observational suicide prevention data were analysed from an existing online United Kingdom national public health database. Multi-collinearity analysis and principal-component analysis were used to reduce correlated data, followed by regression analyses for prediction and explanation of suicide.

RESULTS

Multi-collinearity analysis was effective in reducing the indicator set of predictors by 30% and principal component analysis further reduced the set by 86%. Regression for prediction identified four significant indicator predictors of suicide behaviour (emergency hospital admissions for intentional self-harm, children leaving care, statutory homelessness and self-reported well-being/low happiness) and two main component predictors (relatedness dysfunction, and behavioural problems and mental illness). Regression for explanation identified significant moderation of a well-being predictor (low happiness) of suicide behaviour by a social factor (living alone), thereby supporting existing theory and providing insight beyond the results of regression for prediction. Two independent predictors capturing relatedness needs in social care service delivery were also identified.

CONCLUSIONS

We demonstrate the effectiveness of regression techniques in the analysis of online public health data. Regression analysis for prediction and explanation can both be appropriate for public health data analysis for a better understanding of public health outcomes. It is therefore essential to clarify the aim of the analysis (prediction accuracy or theory development) as a basis for choosing the most appropriate model. We apply these techniques to the analysis of suicide data; however, we argue that the analysis presented in this study should be applied to datasets across public health in order to improve the quality of health policy recommendations.

Evaluating the outcomes of medical informatics development as a discipline in China: A publication perspective

BACKGROUND

As the world's second largest economy, China makes unique contributions to the world in many fields, including sociology, the economy, technology and defense. Medical informatics (MI) is an important cross-disciplinary field that, along with its applications, has received massive funding from the Chinese government. However, the question of how to evaluate China's input and output in MI remains important and complex issue of great significance for China and the rest of the world.

OBJECTIVE

This paper analyzed, for the first time, the quality and quantity of research by Chinese academics in MI based on their articles published in international specialty journals in recent years and examined MI research hotspots in China. Our purpose is to summarize the experiences and lessons learned by China and the rest of the world as they develop MI.

METHOD

We targeted 18 MI journals listed in the JCR 2016 report and searched for papers published by Chinese academics in these 18 journals in the WOS and PUBMED databases and on journal sites. We also performed data cleansing and categorized the obtained information. We used Excel, SPSS, Ucinet and NetDraw to conduct quantitative analyses on the research papers.

RESULTS

A total of 1340 articles satisfied the inclusion criteria of this study. We observed a significant upward trend in the number of articles published over time, particularly after 2011. Lei Jianbo, Huang Zhengxing and Li Jin-song are active Chinese authors in the MI discipline who have written many high-quality publications. Meanwhile, universities remain the primary breeding grounds for scientific research: 93.36% of the articles came from universities. Zhejiang University published the most first-author articles, whereas Zhejiang University, Shanghai Jiao Tong University and Tsinghua University produced 17.76% of the total articles. According to the lists of authors, 24% of the papers were co-authored with foreign researchers. This rate of cooperation is increasing each year, from 5.88% to the current rate of 39.04%. An analysis of keywords showed that "EMR", "SVM", "Authentication", "Telecare medical information system", "EEG", "ECG" and "RFID" were the most frequently searched terms in popular technological fields, including artificial intelligence and image processing. In recent years, there has been a significant increase in the number of high-frequency keywords and a broadening range of research fields, which has led to the emergence of several research hotspots, including MI systems, mobile health care, telecare, data mining and machine learning.

CONCLUSIONS

Through the quantitative analysis of publications, we discovered the emergence of three stages - infancy, slow growth and rapid growth - in China's MI research in recent years as academics make achievements in their research works. The global influence of Chinese academics is growing, and they are making increasingly conscious efforts to enter into research collaborations with foreign researchers. The findings of Chinese academics' publications are gaining international recognition.

Public and Population Health Informatics: The Bridging of Big Data to Benefit Communities

Objective:  To summarize the recent public and population health informatics literature with a focus on the synergistic “bridging” of electronic data to benefit communities and other populations.

Methods:  The review was primarily driven by a search of the literature from July 1, 2016 to September 30, 2017. The search included articles indexed in PubMed using subject headings with (MeSH) keywords “public health informatics” and “social determinants of health”. The “social determinants of health” search was refined to include articles that contained the keywords “public health”, “population health” or “surveillance”.

Results:  Several categories were observed in the review focusing on public health's socio-technical infrastructure: evaluation of surveillance practices, surveillance methods, interoperable health information infrastructure, mobile health, social media, and population health. Common trends discussing socio-technical infrastructure included big data platforms, social determinants of health, geographical information systems, novel data sources, and new visualization techniques. A common thread connected these categories of workforce, governance, and sustainability: using clinical resources and data to bridge public and population health.

Conclusions:  Both medical care providers and public health agencies are increasingly using informatics and big data tools to create and share digital information. The intent of this “bridging” is to proactively identify, monitor, and improve a range of medical, environmental, and social factors relevant to the health of communities. These efforts show a significant growth in a range of population health-centric information exchange and analytics activities.