Therapeutic Duplication in Taiwan Hospitals for Patients With High Blood Pressure, Sugar, and Lipids: Evaluation With a Mobile Health Mapping Tool

Visualizing burst spots on research for four authors in MDPI journals named to be Citation Laureates 2021 using temporal bar graph

BACKGROUND

The appearance of a topic in a document stream is signaled by a burst of activity, with certain features rising sharply in frequency as the topic emerges. Although temporal bar graph (TBG) is frequently applied to present the burst spot in the bibliographical study, none of the research has combined the inflection point (IP) to interpret the burst spot feature. The aims of this study are to improve the traditional TBG and apply the TBG to understand better the evolution of a topic (e.g., publications and citations for a given author).

METHODS

The EISTL model, including entity, indicator, selection of a few vital ones (named attributes) with higher values in quantity (e.g., the citation data of the top 10 entities), TBG and line-chart plots to verify the trend of interest, was proposed to demonstrate the TBG as a whole. The IP locations compared to the median point in data along with the heap map and line-chart trend were identified. The burst strength was computed. A dashboard on Google Maps was designed and launched for bibliometric analysis. Four authors in MDPI (Multidisciplinary Digital Publishing Institute) journals named to be Citation Laureates 2021 were recruited to compare their research achievements shown on the TBG, particularly displaying the burst spots and the recent developments and stages (e.g., increasing, ready to increase, slowdown, or decreasing).

RESULTS

We observed that the highest burst strengths in publication and citations are earned by Barry Halliwell (8.99) and Jean-Pierre Changeux (18.01). The breakthrough of TBG using the EISTL model to display the influence of authors in academics was made with 2 parts of the primary IP point and the trend feature in the data.

CONCLUSION

The dashboard-type TBG shown on Google Maps is unique and innovative and able to provide deeper insights to readers, not merely limited to the publications and citations for a given author as we did in this study.

Orenstein E, Umontuen U, McNeill D, Kandaswamy S. Reducing Therapeutic Duplication in Inpatient Medication Orders

BACKGROUND

Therapeutic duplication, the presence of multiple agents prescribed for the same indication without clarification for when each should be used, can contribute to serious medical errors. Joint Commission standards require that orders contain clarifying information about when each order should be given. In our system, as needed (PRN) acetaminophen and ibuprofen orders are major contributors to therapeutic duplication.

OBJECTIVE

The objective of this study is to design and evaluate effectiveness of clinical decision support (CDS) to reduce therapeutic duplication with acetaminophen and ibuprofen orders.

METHODS

This study was done in a pediatric health system with three freestanding hospitals. We iteratively designed and implemented two CDS strategies aimed at reducing the therapeutic duplication with these agents: (1) interruptive alert prompting clinicians for clarifying PRN comments at order entry and (2) addition of discrete "first-line" and "second-line" PRN reasons to orders. Therapeutic duplications were measured by manual review of orders for 30-day periods before and after each intervention and 6 months later.

RESULTS

Therapeutic duplications decreased from 1,485 in the 30 days prior to the first alert implementation to 818 in the 30 days after but rose back to 1,208 in the 30 days prior to the second intervention. After discrete reasons were added to the order, therapeutic duplication decreased to 336 in the immediate 30 days and 6 months later remained at 277. Alerts firing rates decreased from 76.0 per 1,000 PRN acetaminophen or ibuprofen orders to 42.9 after the second intervention.

CONCLUSION

Interruptive alerts may reduce therapeutic duplication but are associated with high rates of user frustration and alert fatigue. Leveraging discrete PRN reasons for "first line" and "second line" produced a greater reduction in therapeutic duplication as well as fewer interruptive alerts and less manual entry for providers.

The ascendancy of research in acronyms related to COVID-19 displayed on a growth-share matrix (GSM): Bibliometric analysis

BACKGROUND

The acronym COVID, which stands for coronavirus disease, has become one of the most infamous acronyms in the world since 2020. An analysis of acronyms in health and medical journals has previously found that acronyms have become more common in titles and abstracts over time (e.g., DNA and human immunodeficiency virus are the most common acronyms). However, the trends in acronyms related to COVID remain unclear. It is necessary to verify whether the dramatic rise in COVID-related research can be observed by visualizations. The purpose of this study was to display the acronym trends in comparison through the use of temporal graphs and to verify that the COVID acronym has a significant edge over the other 2 in terms of research dominance.

METHODS

An analysis of the 30 most frequently used acronyms related to COVID in PubMed since 1950 was carried out using 4 graphs to conduct this bibliometric analysis, including line charts, temporal bar graphs (TBGs), temporal heatmaps (THM), and growth-share matrices (GSM). The absolute advantage coefficient (AAC) was used to measure the dominance strength for COVID acronym since 2020. COVID's AAC trend was expected to decline over time.

RESULTS

This study found that COVID, DNA, and human immunodeficiency virus have been the most frequently observed research acronyms since 2020, followed by computed tomography and World Health Organization; although there is no ideal method for displaying acronym trends over time, researchers can utilize the GSM to complement traditional line charts, TBGs, and THMs, as shown in this study; and COVID has a significant edge over the other 2 in terms of research dominance by ACC (≥0.67), but COVID's AAC trend has declined (e.g., AACs 0.83, 0.80, and 0.69) since 2020.

CONCLUSIONS

It is recommended that the GSM complement traditional line charts, TBGs, and THMs in trend analysis, rather than being restricted to acronyms in future research. This research provides readers with the AAC to understand how research dominates its counterparts, which will be useful for future bibliometric analyses.

A leading author of meta-analysis does not have a dominant contribution to research based on the CJAL score: Bibliometric analysis

BACKGROUND

There have been nearly 200 thousand meta-analysis articles indexed by web of science (WoS) since 2013. To date, a bibliometric analysis of leading authors of meta-analyses that contribute to the field has not been conducted. Analyzing trend patterns in article citations and comparing individual research achievements (IRAs) are required following the extraction of meta-analysis articles. Using trend analysis, this study aims to verify the hypotheses that; The leading author has a dominant research achievement and; Recent articles that deserve worth reading can be identified.

METHODS

In the WoS collection, we identified the top 20 authors with the most articles related to meta-analysis. Using coword analysis, 2882 articles were collected to cluster author collaborations and identify the top 3 authors with the highest weighted centrality degrees. Based on the CJAL (category, journal raking by impact factor, authorship, and L-index on article citation) score and absolute advantage coefficient (AAC), we compared the IRAs and identified the author who dominated the field significantly beyond the next 2 authors. In WoS collection, coword analysis was used to highlight the characteristics of research domains for the top authors contributing to meta-analyses. The selection of articles that deserve reading is based on a temporal heatmap.

RESULTS

The top 2 authors were Young-Ho Lee (South Korea), Patompong Ungprasert (U.S.), and Brendon Stubbs (US) with CJAL scores of 240.71, 230.99, and 240.71, respectively. Based on the weak dominance coefficient (AAC = 0.49 < 0.50), it is evident that the leading meta-analysis author does not possess a significant dominant position over the next 2 leading authors in IRAs. Coword analysis was used to illustrate the characteristics of the 3 authors research domains. The 3 articles worth reading were selected based on a trend analysis of the last 4 years using the temporal heatmap.

CONCLUSION

A coword analysis of meta-analysis studies identified 3 leading authors. There was no evidence that 1 author possessed a dominant position due to the lower AAC (=0.49 < 0.50) for the leading author. As we have demonstrated in this study, the CJAL score and the AAC can be applied to many bibliographical studies in the future.

Sedatives and analgesics are major contributors to potentially inappropriate duplicate prescriptions in geriatric psychiatry

BACKGROUND

This study sought to investigate the frequency and characteristics of duplicate prescriptions (DPs) in elderly psychiatric inpatients using a novel categorisation of DPs that differentiates between appropriate duplicate prescriptions (ADPs) and potentially inappropriate duplicate prescriptions (PIDPs).

METHODS

The study was conducted as a monocentric retrospective cross-sectional pilot study on the gerontopsychiatric ward of the Department of Psychiatry, Social Psychiatry and Psychotherapy of Hannover Medical School, a large university hospital in northern Germany. The outcome measures were the nature and frequency of PIDPs compared with the frequency of ADPs.

RESULTS

For 92 individual patients a total of 339 medication chart reviews were conducted between April 2021 and February 2022. The median age of the study population was 73 years (interquartile range (IQR) 68-82 years); 64.6% were female. Patients' medications comprised a median of eight drugs (IQR 6-11 drugs) and 43.1% of the study population were exposed to at least one PIDP (at least one grade-1 PIDP: 39.5%; at least one grade-2 PIDP: 5.0%; at least one grade-3 PIDP: 1.5%). Sedatives were most frequently responsible for grade-1 and grade-2 PIDPs, while grade-3 PIDPs were elicited exclusively by analgesics. Nearly half of the study population (49.0%) displayed at least one ADP.

CONCLUSION

Even though the clinical implications of PIDPs are not fully established to date, we recommend that physicians who treat elderly psychiatric patients pay special attention to PIDPs, especially PIDPs elicited by sedatives. Termination of PIDPs may prevent adverse drug reactions and save healthcare expenditures.

A leading bibliometric author does not have a dominant contribution to research based on the CJAL score: Bibliometric analysis

BACKGROUND

A total of 22,367 bibliometric articles have been indexed by Web of Science (WoS). The most significant contribution to the field has not yet been identified through bibliometric analysis. A comparison of individual research achievements (IRAs) and trend analysis of article citations are required after extracting bibliometric articles. The study aimed to confirm whether the leading author has a dominant RA and which articles are worth reading for readers using trend analysis.

METHODS

We identified authors with at least 100 articles related to bibliometrics in the WoS core collection. A total of 399 articles were collected to cluster author collaborations. Co-word analysis and chord diagrams were used to match chief authors in clusters with Keywords Plus in WoS core collection. The category, journal impact factor, authorship, and L-index (CJAL) score and the absolute advantage coefficient (AAC) were used to compare IRAs and identify the leading author who dominated the field significantly beyond the next 2 authors. In addition to network charts and chord diagrams, 4 visualizations were used to report study results, including a Sankey diagram, a dot plot, a temporal trend graph, and a radar plot. The temporal bubble graph was used to select articles that deserve to be read.

RESULTS

The top 3 authors were Lutz Bornmann, Yuh-Shan Ho, and Giovanni Abramo, with CJAL scores of 176.22, 176.02, and 112.06, respectively, from Germany, Italy, and Taiwan. Based on the weak dominance coefficient (AAC = 0.20 < 0.70), it is evident that the leading bibliometric author has no such significant power beyond the next 2 leading authors in IRAs. A trend analysis of the last 4 years was used to illustrate the 2 articles that deserve to be read.

CONCLUSION

Three leading authors were identified through a co-word analysis of bibliometrics. There was no evidence of an author who possessed a dominant position due to a lower AAC on the leading author. The CJAL score and the AAC can be applied to many bibliographical studies in the future rather than being limited to bibliometric studies that evaluate the leading authors in a field, as we did in this study.

Citation trends in ophthalmology articles and keywords in mainland China, Hong Kong, and Taiwan since 2013 using temporal bar graphs (TBGs): Bibliometric analysis

BACKGROUND

We selected authors from mainland China, Hong Kong, and Taiwan (CHT) to examine citation trends on articles and keywords. The existence of suitable temporal bar graphs (TBGs) for displaying citation trends is unknown. It is necessary to enhance the traditional TBGs to provide readers with more information about the citation trend. The purpose of this study was to propose an advanced TBG that can be applied to understand the most worth-reading articles by ophthalmology authors in the CHT.

METHODS

Using the search engine of the Web of Science core collection, we conducted bibliometric analyses to examine the article citation trends of ophthalmology authors in CHT since 2013. A total of 6695 metadata was collected from articles and review articles. Using radar plots, the Y-index, and the combining the Y-index with the CJAL scores (CJAL) scores, we could determine the dominance of publications by year, region, institute, journal, department, and author. A choropleth map, a dot plot, and a 4-quadrant radar plot were used to visualize the results. A TBG was designed and provided for readers to display citation trends on articles and keywords.

RESULTS

We found that the majority of publications were published in 2017 (2275), Shanghai city (935), Sun Yat-Sen University (China) (689), the international journal Ophthalmology (1399), the Department of Ophthalmology (3035), and the author Peizeng Yang (Chongqing) (65); the highest CAJL scores were also from Guangdong (2767.22), Sun Yat-Sen University (China) (2147.35), and the Ophthalmology Department (7130.96); the author Peizeng Yang (Chongqing) (170.16) had the highest CAJL; and the enhanced TBG features maximum counts and recent growth trends that are not included in traditional TBGs.

CONCLUSION

Using the Y-index and the CJAL score compared with research achievements of ophthalmology authors in CHT, a 4-quadrant radar plot was provided. The enhanced TBGs and the CJAL scores are recommended for future bibliographical studies.

Trend and prediction of citations on the topic of neuromuscular junctions in 100 top-cited articles since 2001 using a temporal bar graph: A bibliometric analysis

BACKGROUND

A neuromuscular junction (NMJ) (or myoneural junction) is a chemical synapse between a motor neuron (MN) and a muscle fiber. Although numerous articles have been published, no such analyses on trend or prediction of citations in NMJ were characterized using the temporal bar graph (TBG). This study is to identify the most dominant entities in the 100 top-cited articles in NMJ (T100MNJ for short) since 2001; to verify the improved TBG that is viable for trend analysis; and to investigate whether medical subject headings (MeSH terms) can be used to predict article citations.

METHODS

We downloaded T100MNJ from the PubMed database by searching the string ("NMJ" [MeSH Major Topic] AND ("2001" [Date - Modification]: "2021" [Date - Modification])) and matching citations to each article. Cluster analysis of citations was performed to select the most cited entities (e.g., authors, research institutes, affiliated countries, journals, and MeSH terms) in T100MNJ using social network analysis. The trend analysis was displayed using TBG with two major features of burst spot and trend development. Next, we examined the MeSH prediction effect on article citations using its correlation coefficients (CC) when the mean citations in MeSH terms were collected in 100 top-cited articles related to NMJ (T100NMJs).

RESULTS

The most dominant entities (i.e., country, journal, MesH term, and article in T100NMJ) in citations were the US (with impact factor [IF] = 142.2 = 10237/72), neuron (with IF = 151.3 = 3630/24), metabolism (with IF = 133.02), and article authored by Wagh et al from Germany in 2006 (with 342 citing articles). The improved TBG was demonstrated to highlight the citation evolution using burst spots, trend development, and line-chart plots. MeSH terms were evident in the prediction power on the number of article citations (CC = 0.40, t = 4.34).

CONCLUSION

Two major breakthroughs were made by developing the improved TBG applied to bibliographical studies and the prediction of article citations using the impact factor of MeSH terms in T100NMJ. These visualizations of improved TBG and scatter plots in trend, and prediction analyses are recommended for future academic pursuits and applications in other disciplines.

Using Sankey diagrams to explore the trend of article citations in the field of bladder cancer: Research achievements in China higher than those in the United States

BACKGROUND

Urology authors are required to evaluate research achievements (RAs) in the field of bladder cancer (BC). However, no such bibliometric indices were appropriately applied to quantify the contributions to BC in research. In this study, we examined 3 questions: whether RAs in China are higher than those in the United States, how the Sankey-based temporal bar graph (STBG) may be applied to the analysis of the trend of article citations in the BC field, and what subthemes were reflected in China's and the United States' proportional counts in BC articles.

METHODS

Using the PubMed search engine to download data, we conducted citation analyses of BC articles authored by urology scholars since 2012. A total of 9885 articles were collected and analyzed using the relative citations ratios (RCRs) and the STBG. The 3 research goals were verified using the RCRs, the STBG, and medical subject headings (MesH terms). The choropleth map and the forest plot were used to 1 highlight the geographical distributions of publications and RCRs for countries/regions and 2 compare the differences in themes (denoted by major MeSH terms on proportional counts using social network analysis to cluster topics) between China and the United States.

RESULTS

There was a significant rise over the years in RCRs within the 9885 BC articles. We found that the RCRs in China were substantially higher than those in the United States since 2017, the STBG successfully explored the RCR trend of BC articles and was easier and simpler than the traditional line charts, area plots, and TBGs, and the subtheme of genetics in China has a significantly higher proportion of articles than the United States. The most productive and influential countries/regions (denoted by RCRs) were {Japan, Germany, and Italy} and {Japan, Germany, New York}, respectively, when the US states and provinces/metropolitan cities/areas in China were separately compared to other countries/regions.

CONCLUSIONS

With an overall increase in publications and RCRs on BC articles, research contributions assessed by the RCRs and visualized by the STBGs are suggested for use in future bibliographical studies.

Visualizing the features of inflection point shown on a temporal bar graph using the data of COVID-19 pandemic

BACKGROUND

Exponential-like infection growth leading to peaks (denoted by inflection points [IP] or turning points) is usually the hallmark of infectious disease outbreaks, including coronaviruses. To determine the IPs of the novel coronavirus (COVID-19), we applied the item response theory model to detect phase transitions for each country/region and characterize the IP feature on the temporal bar graph (TBG).

METHODS

The IP (using the item difficulty parameter to locate) was verified by the differential equation in calculus and interpreted by the TBG with 2 virtual and real empirical data (i.e., from Collatz conjecture and COVID-19 pandemic in 2020). Comparisons of IPs, R2, and burst strength [BS = ln() denoted by the infection number at IP(Nip) and the item slope parameter(a) in item response theory were made for countries/regions and continents on the choropleth map and the forest plot.

RESULTS

We found that the evolution of COVID-19 on the TBG makes the data clear and easy to understand, the shorter IP (=53.9) was in China and the longest (=247.3) was in Europe, and the highest R2 (as the variance explained by the model) was in the US, with a mean R2 of 0.98. We successfully estimated the IPs for countries/regions on COVID-19 in 2020 and presented them on the TBG.

CONCLUSION

Temporal visualization is recommended for researchers in future relevant studies (e.g., the evolution of keywords in a specific discipline) and is not merely limited to the IP search in COVID-19 pandemics as we did in this study.

An application for classifying perceptions on my health bank in Taiwan using convolutional neural networks and web-based computerized adaptive testing: A development and usability study

BACKGROUND

The classification of a respondent's opinions online into positive and negative classes using a minimal number of questions is gradually changing and helps turn techniques into practices. A survey incorporating convolutional neural networks (CNNs) into web-based computerized adaptive testing (CAT) was used to collect perceptions on My Health Bank (MHB) from users in Taiwan. This study designed an online module to accurately and efficiently turn a respondent's perceptions into positive and negative classes using CNNs and web-based CAT.

METHODS

In all, 640 patients, family members, and caregivers with ages ranging from 20 to 70 years who were registered MHB users were invited to complete a 3-domain, 26-item, 5-category questionnaire asking about their perceptions on MHB (PMHB26) in 2019. The CNN algorithm and k-means clustering were used for dividing respondents into 2 classes of unsatisfied and satisfied classes and building a PMHB26 predictive model to estimate parameters. Exploratory factor analysis, the Rasch model, and descriptive statistics were used to examine the demographic characteristics and PMHB26 factors that were suitable for use in CNNs and Rasch multidimensional CAT (MCAT). An application was then designed to classify MHB perceptions.

RESULTS

We found that 3 construct factors were extracted from PMHB26. The reliability of PMHB26 for each subscale beyond 0.94 was evident based on internal consistency and stability in the data. We further found the following: the accuracy of PMHB26 with CNN yields a higher accuracy rate (0.98) with an area under the curve of 0.98 (95% confidence interval, 0.97-0.99) based on the 391 returned questionnaires; and for the efficiency, approximately one-third of the items were not necessary to answer in reducing the respondents' burdens using Rasch MCAT.

CONCLUSIONS

The PMHB26 CNN model, combined with the Rasch online MCAT, is recommended for improving the accuracy and efficiency of classifying patients' perceptions of MHB utility. An application developed for helping respondents self-assess the MHB cocreation of value can be applied to other surveys in the future.

Using the absolute advantage coefficient (AAC) to measure the strength of damage hit by COVID-19 in India on a growth-share matrix

BACKGROUND

The COVID-19 pandemic occurred and rapidly spread around the world. Some online dashboards have included essential features on a world map. However, only transforming data into visualizations for countries/regions is insufficient for the public need. This study aims to (1) develop an algorithm for classifying countries/regions into four quadrants inn GSM and (2) design an app for a better understanding of the COVID-19 situation.

METHODS

We downloaded COVID-19 outbreak numbers daily from the Github website, including 189 countries/regions. A four-quadrant diagram was applied to present the classification of each country/region using Google Maps run on dashboards. A novel presentation scheme was used to identify the most struck entities by observing (1) the multiply infection rate (MIR) and (2) the growth trend in the recent 7 days. Four clusters of the COVID-19 outbreak were dynamically classified. An app based on a dashboard aimed at public understanding of the outbreak types and visualizing of the COVID-19 pandemic with Google Maps run on dashboards. The absolute advantage coefficient (AAC) was used to measure the damage hit by COVID-19 referred to the next two countries severely hit by COVID-19.

RESULTS

We found that the two hypotheses were supported: India (i) is in the increasing status as of April 28, 2021; (ii) has a substantially higher ACC(= 0.81 > 0.70), and (iii) has a substantially higher ACC(= 0.66 < 0.70) as of May 17, 2021.

CONCLUSION

Four clusters of the COVID-19 outbreak were dynamically classified online on an app making the public understand the outbreak types of COVID-19 pandemic shown on dashboards. The app with GSM and AAC is recommended for researchers in other disease outbreaks, not just limited to COVID-19.

Therapeutic Duplication in Taiwan Hospitals for Patients With High Blood Pressure, Sugar, and Lipids: Evaluation With a Mobile Health Mapping Tool

BACKGROUND

Cardiovascular disease causes approximately half of all deaths in patients with type 2 diabetes. Duplicative prescriptions of medication in patients with high blood pressure (hypertension), high blood sugar (hyperglycemia), and high blood lipids (hyperlipidemia) have attracted substantial attention regarding the abuse of health care resources and to implement preventive measures for such abuse. Duplicative prescriptions may occur by patients receiving redundant medications for the same condition from two or more sources such as doctors, hospitals, and multiple providers, or as a result of the patient's wandering among hospitals.

OBJECTIVE

We evaluated the degree of duplicative prescriptions in Taiwanese hospitals for outpatients with three types of medications (antihypertension, antihyperglycemia, and antihyperlipidemia), and then used an online dashboard based on mobile health (mHealth) on a map to determine whether the situation has improved in the recent 25 fiscal quarters.

METHODS

Data on duplicate prescription rates of drugs for the three conditions were downloaded from the website of Taiwan's National Health Insurance Administration (TNHIA) from the third quarter of 2010 to the third quarter of 2016. Complete data on antihypertension, antihyperglycemia, and antihyperlipidemia prescriptions were obtained from 408, 414, and 359 hospitals, respectively. We used scale quality indicators to assess the attributes of the study data, created a dashboard that can be traced using mHealth, and selected the hospital type with the best performance regarding improvement on duplicate prescriptions for the three types of drugs using the weighted scores on an online dashboard. Kendall coefficient of concordance (W) was used to evaluate whether the performance rankings were unanimous.

RESULTS

The data quality was found to be acceptable and showed good reliability and construct validity. The online dashboard using mHealth on Google Maps allowed for easy and clear interpretation of duplicative prescriptions regarding hospital performance using multidisciplinary functionalities, and showed significant improvement in the reduction of duplicative prescriptions among all types of hospitals. Medical centers and regional hospitals showed better performance with improvement in the three types of duplicative prescriptions compared with the district hospitals. Kendall W was 0.78, indicating that the performance rankings were not unanimous (Chi square₂=4.67, P=.10).

CONCLUSIONS

This demonstration of a dashboard using mHealth on a map can inspire using the 42 other quality indicators of the TNHIA by hospitals in the future.