Search
- Filter Results
- Location
- Classification
- Include attachments
- https://med.libretexts.org/Bookshelves/Medicine/Value-based_Healthcare_(Khalil)/05%3A_Data_analytics_and_its_role_in_managing_patients/5.09%3A_ConclusionThe availability of a large amount of data in the healthcare arena from various platforms and its ease of analysis thanks to modern software offer numerous benefits to patients in remedial and prevent...The availability of a large amount of data in the healthcare arena from various platforms and its ease of analysis thanks to modern software offer numerous benefits to patients in remedial and preventive medicine. How do you see healthcare delivery evolving with the widespread adoption of data analytics in your area of clinical practice, particularly in the context of value-based healthcare?
- https://med.libretexts.org/Bookshelves/Medicine/Value-based_Healthcare_(Khalil)/05%3A_Data_analytics_and_its_role_in_managing_patients/5.04%3A_Data_analytics_applicationsAccording to the World Health Organization, data analytics applications in healthcare offer the opportunity to improve decision-making clinical skills, enact a patient-centred care approach, produce a...According to the World Health Organization, data analytics applications in healthcare offer the opportunity to improve decision-making clinical skills, enact a patient-centred care approach, produce a higher quality of care, improve disease monitoring, early diagnosis and detection of health threats and risk stratification of certain medical conditions, as well as optimise health resources (WHO, 2021).
- https://med.libretexts.org/Bookshelves/Medicine/Value-based_Healthcare_(Khalil)/05%3A_Data_analytics_and_its_role_in_managing_patientsThis chapter will explore the importance of data analytics in healthcare, the theories available to describe data analytics characteristics and modelling, and showcase three practical examples using t...This chapter will explore the importance of data analytics in healthcare, the theories available to describe data analytics characteristics and modelling, and showcase three practical examples using three models for using data analytics to improve patient outcomes.
- https://med.libretexts.org/Bookshelves/Medicine/Value-based_Healthcare_(Khalil)/05%3A_Data_analytics_and_its_role_in_managing_patients/5.02%3A_Data_characteristicsThe expansion in characterising data among data analytics researchers is mainly due to the breadth of available data and the continuous novel sources from which to retrieve it. Data volume is growing ...The expansion in characterising data among data analytics researchers is mainly due to the breadth of available data and the continuous novel sources from which to retrieve it. Data volume is growing considerably, and it is anticipated that the larger the data, the better the prediction models that will be created from them and the more reliable they will be.
- https://med.libretexts.org/Bookshelves/Medicine/Value-based_Healthcare_(Khalil)/05%3A_Data_analytics_and_its_role_in_managing_patients/5.03%3A_Data_modelling_categoriesThese methods allow health organisations to use raw patient and related data to support improvement in the quality of care of their patients, provide predictive modelling of progression of disease sta...These methods allow health organisations to use raw patient and related data to support improvement in the quality of care of their patients, provide predictive modelling of progression of disease states as well as improve allocation of available resources in a proactive approach, conducting gap analysis to address organisations goals (Wills, 2014).
- https://med.libretexts.org/Bookshelves/Medicine/Value-based_Healthcare_(Khalil)/05%3A_Data_analytics_and_its_role_in_managing_patients/5.01%3A_Data_analytics_in_healthcareWith the increase of electronic medical records (EMRs) in health organisations and integration with various platforms and healthcare systems in primary and secondary healthcare settings, it is likely ...With the increase of electronic medical records (EMRs) in health organisations and integration with various platforms and healthcare systems in primary and secondary healthcare settings, it is likely that healthcare organisations will transition to a proactive approach for managing patients given the ease of availability of real-time patient information and hence the potential to change the model of care (Guo & Chen, 2023).
- https://med.libretexts.org/Bookshelves/Medicine/Value-based_Healthcare_(Khalil)/05%3A_Data_analytics_and_its_role_in_managing_patients/5.10%3A_ReferencesImpact of big data analytics on people’s health: overview of systematic reviews and recommendations for future studies. Big data and predictive analytics and manufacturing performance: integrating ins...Impact of big data analytics on people’s health: overview of systematic reviews and recommendations for future studies. Big data and predictive analytics and manufacturing performance: integrating institutional theory, resource-based view and big data culture. Benefits and challenges of big data in healthcare: an overview of the European initiatives. Strategic issues of big data analytics applications for managing health-care sector: a systematic literature review and future research agenda.
- https://med.libretexts.org/Bookshelves/Medicine/Value-based_Healthcare_(Khalil)/05%3A_Data_analytics_and_its_role_in_managing_patients/5.08%3A_Implications_for_practiceData analytics will become integral to patient health management as more data platforms integrate to provide real-time information for decision-making to improve patient and resource management. While...Data analytics will become integral to patient health management as more data platforms integrate to provide real-time information for decision-making to improve patient and resource management. While there are restricted levels to patient information based on privacy laws in many countries, some data sources may yet miss key aspects of relevant information and may not provide the full dataset required to make informed decisions.
- https://med.libretexts.org/Bookshelves/Medicine/Value-based_Healthcare_(Khalil)/05%3A_Data_analytics_and_its_role_in_managing_patients/5.07%3A_Enablers_of_data_analytics_in_healthcare_Predictive_data_analyticsTo overcome unstructured clean data entered into various software programs sometimes by unskilled staff, predictive medical taxonomy can be used to improve data entry quality and standardise medical t...To overcome unstructured clean data entered into various software programs sometimes by unskilled staff, predictive medical taxonomy can be used to improve data entry quality and standardise medical terminology across various data platforms (Dubey et al., 2019). To improve efficiency and reduce data analysis cost, organisations in the same jurisdictions could streamline their data governance principles to enhance data quality and standardise formats (Reddy et al., 2022).
- https://med.libretexts.org/Bookshelves/Medicine/Value-based_Healthcare_(Khalil)/05%3A_Data_analytics_and_its_role_in_managing_patients/5.06%3A_Barriers_to_data_analytics_in_healthcareFactors affecting the cost of data analytics include the type, amount and quality of data, the objectives of data analytics, vendor pricing, time taken by content experts to analyse data and customise...Factors affecting the cost of data analytics include the type, amount and quality of data, the objectives of data analytics, vendor pricing, time taken by content experts to analyse data and customise it to meet the objectives, and organisational adaptability and readiness for change (Pastorino et al., 2019).
- https://med.libretexts.org/Bookshelves/Medicine/Value-based_Healthcare_(Khalil)/05%3A_Data_analytics_and_its_role_in_managing_patients/5.05%3A_Case_studiesSalvi et al. (2020) presented a patient integration model that used advanced data analytics modelling and processing from various devices to analyse patient pathology data and couple it with their phy...Salvi et al. (2020) presented a patient integration model that used advanced data analytics modelling and processing from various devices to analyse patient pathology data and couple it with their physical activities and daily eating habits to map a pattern of blood glucose fluctuations over time (see Figure 5.4).
