scholarly journals Government plans in the 2016 and 2021 Peruvian presidential elections: A natural language processing analysis of the health chapters

2021 ◽  
Vol 6 ◽  
pp. 177
Author(s):  
Rodrigo M. Carrillo-Larco ◽  
Manuel Castillo-Cara ◽  
Jesús Lovón-Melgarejo
Keyword(s):  
Natural Language Processing ◽  
Natural Language ◽  
Language Processing ◽  
Universal Health Coverage ◽  
Presidential Elections ◽  
Clinical Medicine ◽  
Health Coverage ◽  
Keywords And Phrases ◽  
The Government ◽  
Universal Health

Background: While clinical medicine has exploded, electronic health records for Natural Language Processing (NLP) analyses, public health, and health policy research have not yet adopted these algorithms. We aimed to dissect the health chapters of the government plans of the 2016 and 2021 Peruvian presidential elections, and to compare different NLP algorithms. Methods: From the government plans (18 in 2016; 19 in 2021) we extracted each sentence from the health chapters. We used five NLP algorithms to extract keywords and phrases from each plan: Term Frequency–Inverse Document Frequency (TF-IDF), Latent Dirichlet Allocation (LDA), TextRank, Keywords Bidirectional Encoder Representations from Transformers (KeyBERT), and Rapid Automatic Keywords Extraction (Rake). Results: In 2016 we analysed 630 sentences, whereas in 2021 there were 1,685 sentences. The TF-IDF algorithm showed that in 2016, 22 terms appeared with a frequency of 0.05 or greater, while in 2021 27 terms met this criterion. The LDA algorithm defined two groups. The first included terms related to things the population would receive (e.g., ’insurance’), while the second included terms about the health system (e.g., ’capacity’). In 2021, most of the government plans belonged to the second group. The TextRank analysis provided keywords showing that ’universal health coverage’ appeared frequently in 2016, while in 2021 keywords about the COVID-19 pandemic were often found. The KeyBERT algorithm provided keywords based on the context of the text. These keywords identified some underlying characteristics of the political party (e.g., political spectrum such as left-wing). The Rake algorithm delivered phrases, in which we found ’universal health coverage’ in 2016 and 2021. Conclusion: The NLP analysis could be used to inform on the underlying priorities in each government plan. NLP analysis could also be included in research of health policies and politics during general elections and provide informative summaries for the general population.

scholarly journals Government plans in the 2016 and 2021 Peruvian presidential elections: A natural language processing analysis of the health chapters

2021 ◽  
Vol 6 ◽  
pp. 177
Author(s):  
Rodrigo M. Carrillo-Larco ◽  
Manuel Castillo-Cara ◽  
Jesús Lovón-Melgarejo
Keyword(s):  
Natural Language Processing ◽  
Natural Language ◽  
Language Processing ◽  
Universal Health Coverage ◽  
Presidential Elections ◽  
Clinical Medicine ◽  
Health Coverage ◽  
Keywords And Phrases ◽  
The Government ◽  
Universal Health

Background: While clinical medicine has exploded, electronic health records for Natural Language Processing (NLP) analyses, public health, and health policy research have not yet adopted these algorithms. We aimed to dissect the health chapters of the government plans of the 2016 and 2021 Peruvian presidential elections, and to compare different NLP algorithms. Methods: From the government plans (18 in 2016; 19 in 2021) we extracted each sentence from the health chapters. We used five NLP algorithms to extract keywords and phrases from each plan: Term Frequency–Inverse Document Frequency (TF-IDF), Latent Dirichlet Allocation (LDA), TextRank, Keywords Bidirectional Encoder Representations from Transformers (KeyBERT), and Rapid Automatic Keywords Extraction (Rake). Results: In 2016 we analysed 630 sentences, whereas in 2021 there were 1,685 sentences. The TF-IDF algorithm showed that in 2016, nine terms appeared with a frequency of 0.10 or greater, while in 2021 43 terms met this criterion. The LDA algorithm defined two groups. The first included terms related to things the population would receive (e.g., ’insurance’), while the second included terms about the health system (e.g., ’capacity’). In 2021, most of the government plans belonged to the second group. The TextRank analysis provided keywords showing that ’universal health coverage’ appeared frequently in 2016, while in 2021 keywords about the COVID-19 pandemic were often found. The KeyBERT algorithm provided keywords based on the context of the text. These keywords identified some underlying characteristics of the political party (e.g., political spectrum such as left-wing). The Rake algorithm delivered phrases, in which we found ’universal health coverage’ in 2016 and 2021. Conclusion: The NLP analysis could be used to inform on the underlying priorities in each government plan. NLP analysis could also be included in research of health policies and politics during general elections and provide informative summaries for the general population.

scholarly journals Government plans in the 2016 and 2021 Peruvian presidential elections: A natural language processing analysis of the health chapters

2021 ◽  
Vol 6 ◽  
pp. 177
Author(s):  
Rodrigo M. Carrillo-Larco ◽  
Manuel Castillo-Cara ◽  
Jesús Lovón-Melgarejo
Keyword(s):  
Natural Language Processing ◽  
Natural Language ◽  
Language Processing ◽  
Universal Health Coverage ◽  
Presidential Elections ◽  
Clinical Medicine ◽  
Health Coverage ◽  
Keywords And Phrases ◽  
The Government ◽  
Universal Health

Background: While clinical medicine has exploded, electronic health records for Natural Language Processing (NLP) analyses, public health, and health policy research have not yet adopted these algorithms. We aimed to dissect the health chapters of the government plans of the 2016 and 2021 Peruvian presidential elections, and to compare different NLP algorithms. Methods: From the government plans (18 in 2016; 19 in 2021) we extracted each sentence from the health chapters. We used five NLP algorithms to extract keywords and phrases from each plan: Term Frequency–Inverse Document Frequency (TF-IDF), Latent Dirichlet Allocation (LDA), TextRank, Keywords Bidirectional Encoder Representations from Transformers (KeyBERT), and Rapid Automatic Keywords Extraction (Rake). Results: In 2016 we analysed 630 sentences, whereas in 2021 there were 1,685 sentences. The TF-IDF algorithm showed that in 2016, nine terms appeared with a frequency of 0.10 or greater, while in 2021 43 terms met this criterion. The LDA algorithm defined two groups. The first included terms related to things the population would receive (e.g., ’insurance’), while the second included terms about the health system (e.g., ’capacity’). In 2021, most of the government plans belonged to the second group. The TextRank analysis provided keywords showing that ’universal health coverage’ appeared frequently in 2016, while in 2021 keywords about the COVID-19 pandemic were often found. The KeyBERT algorithm provided keywords based on the context of the text. These keywords identified some underlying characteristics of the political party (e.g., political spectrum such as left-wing). The Rake algorithm delivered phrases, in which we found ’universal health coverage’ in 2016 and 2021. Conclusion: The NLP analysis could be used to inform on the underlying priorities in each government plan. NLP analysis could also be included in research of health policies and politics during general elections and provide informative summaries for the general population.

Social bots detection in Brazilian presidential elections using natural language processing

2021 ◽  
Author(s):  
Gabriel Estavaringo Ferreira ◽  
Bianca Lima Santos ◽  
Marcelo Torres do Ó ◽  
Rafael Rodrigues Braz ◽  
Luciano Antonio Digiampietri
Keyword(s):  
Natural Language Processing ◽  
Natural Language ◽  
Language Processing ◽  
Presidential Elections

scholarly journals Unique health identifiers for universal health coverage

2019 ◽  
Vol 38 (S1) ◽  
Author(s):  
Samuel Mills ◽  
Jane Kim Lee ◽  
Bahie Mary Rassekh ◽  
Martina Zorko Kodelja ◽  
Green Bae ◽  
...  
Keyword(s):  
Universal Health Coverage ◽  
Identity Management ◽  
Health Coverage ◽  
Vital Event ◽  
Identification Number ◽  
Civil Registration ◽  
Advantages And Disadvantages ◽  
Number Systems ◽  
The Government ◽  
Universal Health

Abstract Identifying everyone residing in a country, especially the poor, is an indispensable part of pursuing universal health coverage (UHC). Having information on an individuals’ financial protection is also imperative for measuring the progress of UHC. This paper examines different ways of instituting a system of unique health identifiers that can lead toward achieving UHC, particularly in relation to utilizing universal civil registration and national unique identification number systems. Civil registration is a fundamental function of the government that establishes a legal identity for individuals and enables them to access essential public services. National unique identification numbers assigned at birth registration can further link their vital event information with data collected in different sectors, including in finance and health. Some countries use the national unique identification number as the unique health identifier, such as is done in South Korea and Thailand. In other countries, a unique health identifier is created in addition to the national unique identification number, but the two numbers are linked; Slovenia offers an example of this arrangement. The advantages and disadvantages of the system types are discussed in the paper. In either approach, linking the health system with the civil registration and national identity management systems contributed to advancing effective and efficient UHC programs in those countries.

scholarly journals Gambaran Out of Pocket pada Awal Era JKN di Indonesia

2018 ◽  
pp. 141-146
Author(s):  
Ingan Tarigan ◽  
Taty Suryati
Keyword(s):  
Health Insurance ◽  
Universal Health Coverage ◽  
Health Expenditures ◽  
Health Care Expenditures ◽  
Financial Protection ◽  
Health Coverage ◽  
Medical Expenses ◽  
The Poor ◽  
The Government ◽  
Universal Health

Abstrak Pogram Jaminan Kesehatan Nasional (JKN) salah satunya bertujuan memberikan perlindungan finansial khususnya biaya katastropik terhadap semua peserta. Penerima manfaat JKN berhak mendapatkan berbagai layanan sebagai bagian dari paket manfaat dasar tanpa mengeluarkan biaya pelayanan, dan diharapkan Out of Pocket (OOP) akan lebih rendah dibandingkan dengan mereka yang tidak memiliki asuransi kesehatan. Tujuan penulisan akan membandingkan total pengeluaran untuk kesehatan dari peserta jaminan kesehatan dengan yang tidak memiliki jaminan kesehatan pada awal era JKN. Dalam analisis ini, pengukuran pengeluaran perawatan kesehatan hanya mencakup biaya pengobatan langsung, seperti biaya konsultasi, pemakaian kamar di rumah sakit dan obat-obatan. Analisis dengan menggunakan data Susenas 2014 terdiri dari 274.673 individu dan 71.051 rumah tangga di 33 provinsi di Indonesia. Hasil penelitian menunjukkan bahwa pada awal era JKN ada sedikit perbedaan OOP pada penduduk miskin dibandingkan dengan penduduk dimana proteksi finansial terhadap penduduk miskin untuk pengeluaran kesehatan masih rendah.Kepemilikan jaminan kesehatan memberikan proteksi finansial akibat pengeluaran biaya kesehatan, khususnya pengeluaran biaya katastropik dibandingkan dengan yang tidak memiliki jaminan kesehatan. Kepesertaan penduduk miskin ditargetkan tahun 2019 sudah terpenuhi sehingga target pemerintah tentang Universal Health Coverage (UHC) perlindungan finansial pada penduduk miskin dan hampir miskin semakin tinggi atau OOP semakin mendekati nol. Kata kunci: OOP, Pembiayaan, Asuransi Kesehatan Abstract One of the main objectives of the JKN program is to provide financial protection, especially catastrophic costs to all members. JKN beneficiaries are entitled to various services as part of the basic benefit package without incurring service costs, and it is expected that Out of Pocket (OOP) will be lower than those who do not have health insurance. The purpose of writing will be to compare the total health expenditures of health insurance participants or beneficiaries and those without health insurance. In this analysis, the measurement of health care expenditures only includes direct medical expenses, such as consultation fees, hospital room usage and medication. Using Susenas data 2014 consists of 274,673 individuals and 71,051 households in 33 provinces in Indonesia. At the beginning of the JKN implementation, there was little difference of out of pocket in the poorest population compared to the richest population. This shows that financial protection to the poor for health expenditures are still low. The ownership of health insurance tends to provide financial protection due to health expenditures, especially catastrophic expenses compared to those without health insurance. In the Year of 2019 where the government targeted to Universal Health Coverage (UHC) expected protection financial on the poor and near poor is getting higher or out of pocket or getting closer up to zero. Keywords: OOP, Financial Protection, Health Insurance

Predicting Catastrophic Events Using Machine Learning Models for Natural Language Processing

2022 ◽  
pp. 223-243
Author(s):  
Muskaan Chopra ◽  
Sunil K. Singh ◽  
Kriti Aggarwal ◽  
Anshul Gupta
Keyword(s):  
Natural Language Processing ◽  
Natural Language ◽  
Language Processing ◽  
Communication Technologies ◽  
High Accuracy ◽  
Data Prediction ◽  
The Government ◽  
Media Applications ◽  
Disaster Prediction ◽  
Machine Learning Models

In recent years, there has been widespread improvement in communication technologies. Social media applications like Twitter have made it much easier for people to send and receive information. A direct application of this can be seen in the cases of disaster prediction and crisis. With people being able to share their observations, they can help spread the message of caution. However, the identification of warnings and analyzing the seriousness of text is not an easy task. Natural language processing (NLP) is one way that can be used to analyze various tweets for the same. Over the years, various NLP models have been developed that are capable of providing high accuracy when it comes to data prediction. In the chapter, the authors will analyze various NLP models like logistic regression, naive bayes, XGBoost, LSTM, and word embedding technologies like GloVe and transformer encoder like BERT for the purpose of predicting disaster warnings from the scrapped tweets. The authors focus on finding the best disaster prediction model that can help in warning people and the government.

scholarly journals In search of universal health coverage – highlighting the accessibility of health care to students with disabilities in Ghana: a qualitative study

2020 ◽  
Author(s):  
Eric Abodey ◽  
Irene Vanderpuye ◽  
Isaac Mensah ◽  
Eric Badu
Keyword(s):  
Health Care ◽  
Health Insurance ◽  
Students With Disabilities ◽  
Universal Health Coverage ◽  
Access To Health Care ◽  
Health Workers ◽  
Policy Formulation ◽  
Health Coverage ◽  
The Government ◽  
Universal Health

Abstract Background: Accessibility of health care to students with disabilities is a global concern. This is no less important in Ghana, however, to date, no study has been undertaken regarding access to health care to students with disabilities. This study, therefore, aims to explore the accessibility of health care to students with disabilities, in the quest of achieving universal health coverage in Ghana. Methods: Qualitative methods, involving in-depth interviews were employed to collect data from 54 participants (29 students with disabilities, 17 health workers and 8 school mothers), selected through purposive sampling. Thematic analysis was used to analyze the data. Results : The study identified three themes – accessibility, adequacy, and affordability. The study findings highlighted that universal health coverage for students with disabilities has not been achieved due to barriers in accessing health care. The barriers faced by students with disabilities were unfriendly physical environments, structures, equipment, limited support services and poor health insurance policy to finance health care. Conclusion : The study concludes that the government should prioritize disability-related issues in health policy formulation, implementation and monitoring. The current provisions and requirements in the disability act should be prioritized, enforced and monitored to ensure adequate inclusion of disability issues in health services. Further, the current exemption policy under the National Health Insurance Scheme should be revised to adequately address the needs of people with disabilities.

scholarly journals The role of occupational health services in the universal health coverage era in Indonesia

2019 ◽  
Vol 38 (1) ◽  
pp. 1
Author(s):  
Muchtaruddin Mansyur
Keyword(s):  
Social Security ◽  
Universal Health Coverage ◽  
Social Health Insurance ◽  
Pension Benefit ◽  
Occupational Health Services ◽  
Health Coverage ◽  
The Social ◽  
National Organizations ◽  
The Government ◽  
Universal Health

<p>In accordance to Act No 24 Year 2011 on The Social Security Administrating Body, the Indonesian National Social Security program is managed by  two national organizations, namely: Social Security Administering Body for Health (<em>Badan Penyelenggara Jaminan Sosial Kesehatan = BPJS Kesehatan</em>) and Social Security Administering Body for Labor (<em>Badan Penyelenggara Jaminan Sosial Ketenagakerjaan = BPJS Ketenagakerjaan</em>). The former is responsible for providing health coverage for all Indonesians through the National Social Health Insurance Scheme known as the Jaminan Kesehatan Nasional/JKN. The latter is  responsible for  providing the worker's social security consisting of Provident Fund Benefit, Accident Benefit, Pension Benefit, and Death Benefit.<sup>1</sup></p>The Indonesian government has been continuously improving the health service program towards better national universal health coverage and has set the 2019 functional achievement target of 95% of the population enrolled in the program. To ensure that this target of  the program will be achieved,  the government pays the premium of <em>BPJS Kesehatan</em> of the poor and near poor.<sup>2</sup>

scholarly journals In search of universal health coverage – highlighting the accessibility of health services for students with disabilities in Ghana: a qualitative study

2019 ◽  
Author(s):  
Eric Abodey ◽  
Irene Vanderpuye ◽  
Isaac Mensah ◽  
Eric Badu
Keyword(s):  
Health Services ◽  
Students With Disabilities ◽  
Universal Health Coverage ◽  
Health Workers ◽  
Policy Formulation ◽  
Health Coverage ◽  
Access To Health Services ◽  
Accessibility Of Health Services ◽  
The Government ◽  
Universal Health

Abstract Background: Accessibility to health services for students with disabilities is a global concern. This is no less important in Ghana, however, to date, no study has been undertaken regarding access to health services for students with disabilities. This study, therefore, aims to explore the accessibility of health services for students with disabilities, in the quest of achieving universal health coverage in Ghana. Methods: Qualitative methods, involving in-depth interviews were employed to collect data from 54 participants (29 students with disabilities, 17 health workers and 8 school mothers), selected through purposive sampling. Thematic analysis was used to analyze the data. Results : The study identified three themes – accessibility, adequacy, and affordability. The study findings highlighted that universal health coverage for students with disabilities has not been achieved due to barriers in accessing health services. The barriers faced by students with disabilities are unfriendly physical environments, structures, equipment, limited support services and poor health insurance policy to finance health services. Conclusion : The study concludes that the government should prioritize disability-related issues in health policy formulation, implementation and monitoring. The current provisions and requirements in the disability act should be prioritized, enforced and monitored to ensure adequate inclusion of disability issues in health services. Further, the current exemption policy under the NHIS scheme should be revised to adequately address the needs of people with disabilities.

Sign in / Sign up

Export Citation Format

Share Document