Need for Health Data Standardization in Nutrition Informatics

Nutrition informatics is the effective retrieval, organization, storage, and optimum use of information, data and knowledge for food-and-nutrition-related problem-solving and decision-making.Management and interpretation of data could help clarify the relationships and interrelationships of diet and disease in India on both national and regional levels. Individuals with expertise in food and nutrition may receive training in informatics to develop national informatics systems.

India is undergoing a nutrition transition, driven both by demographic and socioeconomic changes. Understanding the causes and consequences of these changes could be important in preventing diet-related diseases of both under- and over-nutrition. Assessment of food consumption patterns around the country found an overall increase in processed foods and snack foods, with increases in consumption of sweets varied by region.

The Digital India Initiative’s goal is to create infrastructure as a utility through which every citizen can access multiple public services through a single integrated window. Several cloud platforms using open Application Programming Interfaces (APIs), such as Seva, PayGov, eSangam, and MeghRaj established to provide software interoperability for all e-governance systems and applications. Geospatial information systems (GIS) enhance delivering government services through the cloud or mobile technology. 

-Multiple platforms currently exist or are under development to collect, tabulate and report nutrition information in India:-

-The PM’s Overarching Scheme for Holistic Nourishment (POSHAN) Abhiyan:-Integrated Child Development Services, Anemia Mukt Bharat, Jan Andolan

-The Food Safety and Standards Authority of India (FSSAI)

-The National Institute for Transforming India (NITI) Aayog State Nutrition

-Nutrition India is the Ministry of Health and Family Welfare’s

-Nutrify India Now is a mobile app developed by the NIN

Reference : 

//www.ncbi.nlm.nih.gov/books/NBK216088/

Data standardization is the critical process of bringing data into a common format that can provide the collaborative research, large-scale analytics, sharing of sophisticated tools and methodologies. It is so important especially for health data. That is because the health data can vary greatly from one organization to the next for different purposes like clinical research and direct patient care. 

Regarding the nutrition informatics, it is a field that involves the collection, analysis, application, storage and knowledge for food and nutrition related problem-solving and decision-making. For these kinds of purposes, it is necessary to be reliable in sharing the nutrition informatics from one organization to the next. Without standardization, the nutrition informatics cannot be reliable. Thus, I think standardization of the health data is necessary for nutrition informatics.

The essence of nutrition informatics is to manage nutrition data in combination with standards, processes, and technology to improve knowledge and practice that ultimately lead to improved quality of health care and work efficiency. Registered dietitian nutritionists and nutrition and dietetic technicians, registered, are already experts in using evidence to practice in all areas of nutrition and dietetics. To remain at the forefront of technological innovation, the profession must actively participate in the development of standards, processes, and technologies for providing nutrition care.

References:

//www.jandonline.org/article/S2212-2672(19)30517-9/fulltext

Nutrition Informatics is the information related to food and nutrition that need to be effectively retrieved, organize, stored, and gained knowledge for the purposes of solving the problem and decision. (Joshi A et al. 2021) India has more progress toward the digitalization of health care services in the name of Digital India Initiatives for accessibility of health services to the entire city through a single integrated window. (Vision and Vision Areas, 2020). Integrated Child Development Services—Common application software (CDS-CAS), Anemia Mukt Bharat Dashboard, Jan Andolan Dashboard, The National Institute for Transforming India (NITI) Aayog State Nutrition Dashboard, SUN movement, etc. are some examples of digital health program of India. (Joshi A et al. 2021) Despite lots of program lunches on digital health, there is a lack of infrastructure, and skills for the selection, utilization, and management of suitable technology. (Laurila, B. 2020)  Accurate, appropriate, and complete data without a dual report are keys to meeting sustainable development goals. That could be met through digitalization in health and Nutrition. To upgrade the healthcare worker in the field of digital health we need to conduct training and education in Nutrition Informatics and develop the curriculum to include content on standardized terminologies, systems design, standards and regulations related to technology, and applications, including analysis, management, and evaluation. In addition to that, updating and installing developing platforms and informatics infrastructure is also important. (Joshi A et al. 2021)

References

1. Joshi A, Gaba A, Thakur S, Grover A. Need and Importance of Nutrition Informatics in India: A Perspective. Nutrients. 2021 May 27;13(6):1836.
2. Vision and Vision Areas, Digital India Programme, Ministry of Electronics & Information Technology (MeitY) Government of India. Available online: //www.digitalindia.gov.in/content/vision-and-vision-areas (accessed on 10 December 2020).
3. Laurila, B. You Spelled “NIRD” Wrong. Food & Nutrition. 2016. Available online: //foodandnutrition.org/blogs/the-feed/ spelled-nird-wrong/ (accessed on 20 August 2020).

Nutrition informatics (NI) is the effective retrieval, organization, storage, and optimum use of information, data and knowledge for food-and-nutrition-related problem-solving and decision-making. There is a growing opportunity to facilitate technology-enabled behavioral change interventions to support NI research and practice.

Nutri-informatics suffers from a lack of standardization with a wide array of groups working on similar projects with no community-wide development principles to ensure interoperability and cohesion between nutri-informatics and other biomedical resources. While a large number of resources for nutri-informatics are available, much of nutrition is underrepresented. This may be due to how expansive and heterogeneous nutrition is as a field, increasing the difficulty of data modeling. Approaches to formalize nutrition research language and connect standardized terminologies across biomedical fields have been initiated through the use of biomedical ontologies and computational nutrition data resources. While a variety of nutrition-related ontologies have been initiated, they are still in development and require further attention from nutrition researchers and biomedical ontologists.

hence there is need for Health data standardization in Nutrition Informatics

Reference:

//www.ncbi.nlm.nih.gov/pmc/articles/PMC8230128/  

//www.ncbi.nlm.nih.gov/pmc/articles/PMC7833928/

The primary informatics component required for information flow through the national health information system is data standards. Clinical and patient safety systems can share an integrated information architecture where data is collected and repurposed for many purposes to meet the broad spectrum of data collection and reporting needs more efficiently with common standards. Common data standards also facilitate the successful incorporation of new knowledge into decision support tools, such as an alert of a new drug contraindication and care process modifications.

References: //www.ncbi.nlm.nih.gov/books/NBK216088/

References:

Standardization of data in nutrition informatics is crucial to ensure that accurate and consistent information is collected and analyzed. Standardized data makes it easier to compare data across different sources and helps to ensure that the data is accurate and reliable.

One example of the importance of standardization in nutrition informatics is the collection and analysis of dietary intake data. Without standardized methods for collecting and reporting dietary intake data, it can be difficult to compare data across different studies or populations. This can lead to inconsistencies in research findings and hinder the development of evidence-based nutrition recommendations.

To address this issue, several organizations have developed standardized methods for collecting and reporting dietary intake data, such as the 24-Hour Dietary Recall (24HR) method and the Food Frequency Questionnaire (FFQ) method. These methods help to ensure that the data collected is accurate and consistent, making it easier to compare data across different sources.

Next example of a widely used standard in nutrition informatics is the Food and Nutrient Database for Dietary Studies (FNDDS), which provides a standardized coding system for foods and their nutrient content. This allows researchers, policymakers, and healthcare providers to compare and combine data from different studies and sources, enabling more robust analysis and decision-making.

Another example is the Logical Observation Identifiers Names and Codes (LOINC), which provides a standard vocabulary for laboratory tests and results, including those related to nutrition biomarkers and metabolic indicators. This allows healthcare providers to share and compare laboratory data across different institutions and settings, enhancing patient care and research.

Overall, standardization of data in nutrition informatics is crucial for improving the quality, efficiency, and effectiveness of nutrition-related research, practice, and policy. It enables better communication, collaboration, and decision-making among stakeholders and promotes a more evidence-based approach to nutrition and health.

Reference link:

• //www.ncbi.nlm.nih.gov/pmc/articles/PMC6409677/
• //www.ncbi.nlm.nih.gov/pmc/articles/PMC4393466/
• National Institutes of Health. (2021). Food and Nutrient Database for Dietary Studies. Retrieved from //www.ars.usda.gov/northeast-area/beltsville-md-bhnrc/beltsville-human-nutrition-research-center/food-surveys-research-group/docs/fndds/ .

Nutrition informatics (NI) is the effective retrieval, organization, storage, and optimum use of information, data and knowledge for food-and-nutrition-related problem-solving and decision-making. There is a growing opportunity to facilitate technology-enabled behavioral change interventions to support NI research and practice.

A rising opportunity exists to promote NI research and practice by facilitating technology-enabled behavioral change interventions. This study focuses on how food and nutrition practices are evolving in India in order to help NI workers become better equipped to deal with the dual burden of nutrition. Data management and interpretation should make it clearer how nutrition and disease interact in India on both a national and regional level. To create national informatics systems, experts in food and nutrition may obtain informatics training. Professionals in NI create tools and methods, oversee numerous projects, and carry out informatics research.

India is going through a nutrition move brought on by socioeconomic and demographic developments. In order to prevent diet-related disorders of both undernutrition and overnutrition, it may be helpful to understand the reasons for and effects of these changes. Analyses of food consumption patterns across the nation revealed regional variations in increases in the intake of sweets, as well as an overall increase in processed meals and snack foods.

References:

Nutri-informatics suffers from a lack of standardization with a wide array of groups working on similar projects with no community-wide development principles to ensure interoperability and cohesion between nutri-informatics and other biomedical resources. While a large number of resources for nutri-informatics are available, much of nutrition is underrepresented. This may be due to how expansive and heterogeneous nutrition is as a field, increasing the difficulty of data modeling.

References: //zenodo.org/record/4147677#.ZEDEKXZBzIU

Nutrition informatics suffers from a lack of standardization, with numerous groups working on similar projects but with no community-wide development of guidelines to assure interoperability and cohesion between nutrition informatics and other biomedical resources. Although many nutrition informatics tools are accessible, much of nutrition is underrepresented and data modelling is difficult as nutrition is a vast and diverse field. Through the use of biomedical ontologies and computational nutrition data resources, approaches to formalizing nutrition research language and connecting standardized terminology across biomedical domains have been initiated. While several nutrition-related ontologies have been established, they are still in the early stages and require additional attention from nutrition researchers and biomedical ontologists.

If nutrition data is produced without any standardization of language, documentation specifications, or data reuse restrictions, nutrition informatics investigations will continue to struggle with incompatible data. In order to support nutrition informatics, the community must promote nutrition data generation, reuse, and publication standards. Academic publications, as well as members of the nutrition research and biomedical ontology communities, should advocate for language and data interoperability standardization.

The Academy of Nutrition and Dietetics, the largest professional organization of registered dietitian nutritionists in the United States, is working to build standards and processes that use nutrition informatics to promote effective nutrition care. This includes use of electronic health records as well as standardization of the electronic Nutrition Care Process and nomenclature (eNCPT), a systematic nomenclature that specifies nutrition patient care via Assessment, Diagnosis, Intervention, Monitoring, and Evaluation.

Another approach is to identify malnutrition in a hospital setting. Software-based screening methods that standardize malnutrition evaluations have improved the consistency and efficiency with which malnutrition is detected, hence accelerating the nutrition care response for patients and supporting staff malnutrition knowledge, attitudes, and practices.

In general, the lack of standardization and technical challenges in the field of nutrition informatics lead to a lot of issues within the community.  A systematic approach with community-wide support and adoption is required to solve technological issues in the nutrition informatics sector. Nutrition researchers and ontology developers must continue to educate and act to integrate nutrition research into biomedical ontologies so that nutrition informatics investigations can reach their full potential, supporting discovery from nutrition data beyond a single investigation and providing insights beyond the field of nutrition.

References:

//academic.oup.com/database/article/doi/10.1093/database/baab003/6119904

Nutrition informatics is the management of nutrition data in a standard process to improve knowledge and practice of professionals . It also ensures compliance with electronic health records.Health data standardization is essential in nutrition informatics to ensure the accuracy, reliability, and interoperability of data across different healthcare settings. Standardization facilitate the use of data, support clinical decision-making, and enhance patient outcomes. A Delphi study across all levels of nutrition and dietetics practice was conducted in 2012 to determine the competencies necessary for the practice of Nutrition informatics(NI).The study found that the competencies required for NI practice included knowledge and skills in areas such as computer and information technology, information systems, data analysis, data management, information security and privacy, and ethical and legal issues related to information management. The study emphasized on the importance of effective communication, collaboration, and leadership skills in the practice of Nutrition informatics.

Several surveys followed developing NI among Academy members. The Commission on Dietetic Registration (CDR) in 2016 included informatics as an essential practice competency in continuing education for Registered Dietitian Nutritionists. Nutrition informatics is essesntial to bring about change in food-and-nutrition-related problem-solving and decision-making. It can drive and  facilitate technology-enabled behavioral change interventions to support research and practice. 

India is undergoing a nutrition transition, driven both by demographic and socioeconomic changes.Assessment of food consumption patterns around the country found an overall increase in processed foods and snack foods, with increases in consumption of sweets varied by region.Changes from traditional dietary patterns have been associated with increasing the incidence of obesity and diabetes throughout the country, especially in urban areas.The variability in diet makes implementing nutrition interventions to prevent diseases more challenging. In this situation tool such as Nutrition informatics development makes standarization of data and prevention of diseases possible. 

Reference: 

Ashish Joshi, Ann Gaba, Shyamli Thakur, Ashoo Grover, (2021),Nutrients, Need and Importance of Nutrition Informatics in India: A perspective.

//www.ncbi.nlm.nih.gov/pmc/articles/PMC8230128/

Need for Health Data Standardization in Nutrition Informatics

           There have been very few attempts to use -omics data, nutrition and clinical survey data, and other heterogeneous data types collectively with one another in research 

            Nutrition informatics  is the effective retrieval, organization, storage, and optimum use of information, data and knowledge for food-and-nutrition-related problem-solving and decision-making. There is a growing opportunity to facilitate technology-enabled behavioral change interventions to support NI research and practice.

            Management and interpretation of data could help clarify the relationships and interrelationships of diet and disease in Country on both national and regional levels. 

             Individuals with expertise in food and nutrition may receive training in informatics to develop national informatics systems. Nutrition informatics professionals develop tools and techniques, manage various projects and conduct informatics research. These professionals should be well prepared to work in technological settings and communicate data and information effectively. Opportunities for training in Nutrition informatics are very limited in developing countries.

                To make documentation of clinical nutrition care more compatible with Nutrition informatics initiatives, the Academy of Nutrition and Dietetics formulated the International Dietetics and Nutrition Terminology (IDNT). The goals of having and using standardized language are to promote clear communication across facilities, and to identify in a consistent manner the nutrition problems observed, interventions employed, and outcomes. This facilitates the ultimate goal of NI, which is to improve health outcomes.

           Data collected through Nutrition informatics methods are anticipated to be a means to provide evidence-based nutrition guidance in various settings. These include clinical practice, coding and billing for nutrition care services, food service management, food composition research, and food and nutrition policy.

                Given the volume and complexity of the information and the urgency of developing solutions to the health problems encountered within a transitioning food environment, NI could provide some valuable tools . Management and interpretation of big data could help to clarify the relationships and interrelationships of diet and disease as these relate to the socioeconomic and agricultural changes occurring in India on both national and regional levels. Data mining could yield targeted, evidence-based recommendations and guide interventions.

//www.ncbi.nlm.nih.gov/pmc/articles/PMC8230128/

Need for Health Data Standardization in Nutrition Informatics

literature has been published on the methodological and statistical approaches to

improve the standardization of dietary measurements collected in large multicenter studies.

A major operational issue relates to the comparability of dietary measurements collected from populations of different countries. Between-country comparisons are particularly prone to error when different food  composition databases and software are used to estimate nutrient intake .

There have been ongoing efforts since 1984 to standardize food composition databases over the world  the lack of a homogeneous and complete Latin American database represents a handicap for nutritional epidemiology studies on the relationship between nutrition and health, and the comparison and evaluation of dietary intake within this world region, similar to the situation for international studies in other parts of the world.

The process of standardization at the food and nutrient assessments was performed to minimize systematic and random errors in nutrient intake estimations and to allow comparisons between Latin American countries involved in ELANS (Latin American Nutrition and Health Study).

No study has evaluated the food and nutrient intake, as well as nutritional status

and physical activity patterns of representative populations in Latin America using a standardized methodology across a consortium of several participating countries. The Latin American Study of Nutrition and Health/Estudio Latinoamericano de Nutrición y Salud (ELANS) is a randomized,

cross-sectional, multicenter investigation on nutrition and physical activity of adolescents and adults in eight Latin American countries.

The standardization of nutritional assessment in ELANS should prevent or minimize bias (systematic errors) which could affect the pooling of data collected in different centers and improve between-country comparisons.

REFERENCES :    Kovalskys I, Fisberg M, Gómez G, Rigotti A, Cortés LY, Yépez MC, Pareja RG, Herrera-Cuenca M, Zimberg IZ, Tucker KL, Koletzko B, Pratt M; ELANS Study Group. Standardization of the Food Composition Database Used in the Latin American Nutrition and Health Study (ELANS). Nutrients. 2015 Sep 16;7(9):7914-24. doi: 10.3390/nu7095373. PMID: 26389952; PMCID: PMC4586568.