Importance of Standardization of Data in Policymaking
Data standardization is critical in aiding decision-making (Grannis et al., 2019). There are several ways that this can be enabled. First, data standardization helps foster consistency, meaning the information is collected and reported consistently across different sources over time. At the same time, consistency helps policymakers in comparing and analyzing data effectively. Secondly, standardized data is critical in ensuring interoperability. Thus, it is easy for data integration from different sources, which is needed in healthcare where data is from different sources. Thirdly, accuracy is maintained and enhanced when data is standardized. Errors and inaccuracies are eliminated, and the data obtained is reliable to aid in policymaking. Fourthly, with data standardization, efficiency is enhanced, which means the process is efficient, and the time spent obtaining resources and gathering information is minimized. When the data is standardized, policymakers can effectively compare data obtained from different sources and periods. Mainly, this could help them make policies central to identifying trends and areas in need of attention.
Role of Data Collection in Advanced Practice
Data collection helps in enabling advanced practice. This could be through evidence-based sources. The use of evidence-based sources helps lead to more effective outcomes for patients. At the same time, quality improvement is enabled through data collection. Through regular data collection, practitioners can identify situations where the services need improvement. In this case, this yields better outcomes. Aside from that, data collection enhances the research process, subsequently leading to creativity. The data can be subjected to further research and evaluation in healthcare. In the sequel, this could lead to a situation where there are insights acquired into emerging trends and opportunities.
Examples of Primary and Secondary Data
Surveys, clinical trials, patient medical records, health assessments, and health behavior interventions are examples of primary data sources. Surveys are collected directly from people through interviews and questionnaires (Schneider et al., 2023). Clinical trials involve obtaining data on the safety and efficacy of medical interventions and treatment. Patient health records contain critical information regarding a patient. They are usually obtained during a health visit and could form a part of primary data as they are obtained directly from a source. Health evaluation is another example of primary data acquired through physical assessments that a health professional often does. Lastly, observing individual behaviors could be a source of primary data as just like in other cases, the information is obtained from the source.
Secondary data can be acquired from different sources, such as claims from a health insurer. Information gathered from the insurance providers can be used to analyze health utilization and costs. The data on disease patterns, outbreaks, and public health trends is critical in providing a secondary source of information. Aside from that, databases from the government are often obtained by government agencies such as the World Health Organization (WHO). Hospital records could be another source of secondary information. In hospital records, a physician, nurse, or pharmacist informs health policy decisions. Healthcare policymakers can leverage information to inform their decisions and subsequently improve health practice through the primary and secondary data sources discussed. The data is useful and necessary in ensuring that awareness is created of the areas needing reforms and that relevant agencies work on implementing them effectively.
References
Grannis, S. J., Xu, H., Vest, J. R., Kasthurirathne, S., Bo, N., Moscovitch, B., Torkzadeh, R., & Rising, J. (2019). Evaluating the effect of data standardization and validation on patient matching accuracy. Journal of the American Medical Informatics Association, 26(5), 447-456. https://doi.org/10.1093/jamia/ocy191
Paradis, E., O’Brien, B., Nimmon, L., Bandiera, G., & Martimianakis, M. A. (2016). Design: Selection of data collection methods. Journal of Graduate Medical Education, 8(2), 263-264. https://doi.org/10.4300/jgme-d-16-00098.1
Schneider, A., Wagenknecht, A., Sydow, H., Riedlinger, D., Holzinger, F., Figura, A., Deutschbein, J., Reinhold, T., Pigorsch, M., Stasun, U., Schenk, L., & Möckel, M. (2023). Primary and secondary data in emergency medicine health services research – a comparative analysis in a regional research network on multimorbid patients. BMC Medical Research Methodology, 23(1). https://doi.org/10.1186/s12874-023-01855-2
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