scholarly journals Challenges to Using Big Data in Health Services Research

2019 ◽  
Vol 87 (2) ◽  
pp. 18-20
Author(s):  
Hosung Kang ◽  
Shannon Sibbald
Keyword(s):  
Big Data ◽  
Health Services ◽  
Clinical Results ◽  
Database Security ◽  
Administrative Databases ◽  
Sensitive Information ◽  
Significant Finding ◽  
Services Research ◽  
Accurate Representation ◽  
Healthcare Trends

Given the shift in current healthcare trends toward digitization of storing information, there has been an increase in the number of studies using administrative databases. These databases provide a powerful tool to conduct research on outcomes, health services, and epidemiology. However, these databases have limitations and biases that should be considered. Given the sensitive information regarding patients’ health in the database, security clearances must be granted before data is accessed. Furthermore, algorithms to link the different variables to create a cohort of people with specific disease are imperfect and may not yield an accurate representation. Due to a large volume of records, a statistically significant finding may be observed, but may provide insignificant clinical results. Despite the current limitations, administrative databases provide powerful data that researchers can use to identify gaps in performance to improve the healthcare system.

scholarly journals Secondary Use and Analysis of Big Data Collected for Patient Care

2017 ◽  
Vol 26 (01) ◽  
pp. 28-37
Author(s):  
F. J. Martin-Sanchez ◽  
V. Aguiar-Pulido ◽  
G. H. Lopez-Campos ◽  
N. Peek ◽  
L. Sacchi
Keyword(s):  
Big Data ◽  
Environmental Factors ◽  
Health Services Research ◽  
Health Services ◽  
Clinical Research ◽  
Economic Benefits ◽  
Patient Data ◽  
Genomic Research ◽  
Services Research ◽  
Secondary Use

Summary Objectives: To identify common methodological challenges and review relevant initiatives related to the re-use of patient data collected in routine clinical care, as well as to analyze the economic benefits derived from the secondary use of this data. Through the use of several examples, this article aims to provide a glimpse into the different areas of application, namely clinical research, genomic research, study of environmental factors, and population and health services research. This paper describes some of the informatics methods and Big Data resources developed in this context, such as electronic phenotyping, clinical research networks, biorepositories, screening data banks, and wide association studies. Lastly, some of the potential limitations of these approaches are discussed, focusing on confounding factors and data quality. Methods: A series of literature searches in main bibliographic databases have been conducted in order to assess the extent to which existing patient data has been repurposed for research. This contribution from the IMIA working group on “Data mining and Big Data analytics” focuses on the literature published during the last two years, covering the timeframe since the working group’s last survey. Results and Conclusions: Although most of the examples of secondary use of patient data lie in the arena of clinical and health services research, we have started to witness other important applications, particularly in the area of genomic research and the study of health effects of environmental factors. Further research is needed to characterize the economic impact of secondary use across the broad spectrum of translational research.

Dementia in Ontario: Prevalence and Health Services Utilization

2003 ◽  
Vol 22 (4) ◽  
pp. 369-379 ◽  
Author(s):  
J.E. Tranmer ◽  
R. Croxford ◽  
P.C. Coyte
Keyword(s):  
Health Services ◽  
Health Services Utilization ◽  
Elderly Women ◽  
Home Care Services ◽  
Dementia Care ◽  
Administrative Databases ◽  
Services Research ◽  
Services Utilization ◽  
Study Results ◽  
The Impact

ABSTRACTTo understand the impact of ongoing reform of mental health and dementia care in Ontario, an examination of prevalence and health services utilization rates is needed. However, there exists a gap in current prevalence and health services research specific to dementia care in Ontario. The objective of this study was to address these concerns using linked administrative databases to determine the incremental use of health services by elderly Ontarians with dementia. Overall, study results demonstrated that individuals with dementia used services in a pattern similar to non-demented persons, albeit at a higher level. Exceptions were women's use of hospital and home care services, where the most elderly women received significantly fewer services. Thus, the study provided important insight regarding the relative levels of health services used by demented Ontarians. Research in this area will become increasingly important as the population ages and the settings integral to dementia care and management shift and evolve.

scholarly journals Opportunities for diversifying and enriching our article mix

2020 ◽  
Vol 9 (1) ◽  
Author(s):  
Bruce Rosen ◽  
Stephen C. Schoenbaum ◽  
Avi Israeli
Keyword(s):  
Health Policy ◽  
Health Services Research ◽  
Health Services ◽  
Large Scale ◽  
Policy Research ◽  
National Policy ◽  
Administrative Databases ◽  
Services Research ◽  
Health Policy Analysis ◽  
Access To Data

AbstractAs 2020 comes to a close, the Israel Journal of Health Policy Research (IJHPR) will soon be starting its tenth year of publication. This editorial compares data from 2012 (the journal’s first year of publication) and 2019 (the journal’s most recent full year of publication), regarding the journal’s mix of article types, topics, data sources and methods, with further drill-downs regarding 2019.The analysis revealed several encouraging findings, including a broad and changing mix of topics covered. However, the analysis also revealed several findings that are less encouraging, including the limited number of articles which assessed national policy changes, examined changes over time, and/or made secondary use of large-scale survey data. These findings apparently reflect, to some extent, the mix of studies being carried out by Israeli health services researchers.As the senior editors of the IJHPR we are interested in working with funders, academic institutions, the owners and principal users of relevant administrative databases, and individual scholars to further understand the factors influencing the mix of research being carried out, and subsequently published, by Israel’s health services research community. This deeper understanding could then be used to develop a joint plan to diversify and enrich health services research and health policy analysis in Israel. The plan should include a policy of ensuring improved access to data, to properly support information-based research.

Identification in Administrative Databases of Women Dying of Breast Cancer

2006 ◽  
Vol 24 (6) ◽  
pp. 856-862 ◽  
Author(s):  
Bruno Gagnon ◽  
Nancy E. Mayo ◽  
Carroll Laurin ◽  
James A. Hanley ◽  
Neil McDonald
Keyword(s):  
Breast Cancer ◽  
Health Services ◽  
Predictive Value ◽  
Chronic Care ◽  
Chart Review ◽  
Population Based ◽  
Place Of Death ◽  
Administrative Databases ◽  
Services Research

Purpose Palliative care is an essential component of cancer care, and population-based research is needed to monitor its impact. Administrative databases are the cornerstone of health services research. Their limitation is that cause of death is not sufficient to readily classify decedents as terminally ill for the study of the health services they received at the end of life. The study purpose is to develop and test the validity of an algorithm allowing the classification of the decedents as dying of breast cancer (BC), using administrative data. Methods Validation was carried out through a chart review of 119 BC decedents extracted from hospital-based databases. This algorithm was applied to 3,384 deceased women with BC representative of the whole population. The effect of the classification by the algorithm was illustrated by the shift in the distributions of age and place of death. Results The validation showed a sensitivity of 95%, a specificity of 89%, a positive predictive value of 98%, and negative predictive value of 77% for the classification of women dying of BC. Of the 3,384 decedents, 2,293 were classified as dying of, and 1,091 as not dying of BC. Women dying of BC were younger, died less often at home (6.9% v 17.9%), and in chronic care institutions (4.1% v 14.8%), and more often in acute-care beds (69.9% v 57.1%). Conclusion This novel way to classify decedents is conceptually based and empirically validated through chart review and impact on distribution of age and place of death.

scholarly journals Comparative health services research across populations: the unused opportunities in big data

2015 ◽  
Vol 87 (6) ◽  
pp. 1094-1096 ◽  
Author(s):  
Benjamin A. Goldstein ◽  
Wolfgang C. Winkelmayer
Keyword(s):  
Big Data ◽  
Health Services Research ◽  
Health Services ◽  
Services Research

scholarly journals Secondary Use and Analysis of Big Data Collected for Patient Care

2017 ◽  
Vol 26 (01) ◽  
pp. 28-37 ◽  
Author(s):  
F. J. Martin-Sanchez ◽  
V. Aguiar-Pulido ◽  
G. H. Lopez-Campos ◽  
N. Peek ◽  
L. Sacchi
Keyword(s):  
Big Data ◽  
Environmental Factors ◽  
Health Services Research ◽  
Health Services ◽  
Clinical Research ◽  
Economic Benefits ◽  
Patient Data ◽  
Genomic Research ◽  
Services Research ◽  
Secondary Use

Summary Objectives: To identify common methodological challenges and review relevant initiatives related to the re-use of patient data collected in routine clinical care, as well as to analyze the economic benefits derived from the secondary use of this data. Through the use of several examples, this article aims to provide a glimpse into the different areas of application, namely clinical research, genomic research, study of environmental factors, and population and health services research. This paper describes some of the informatics methods and Big Data resources developed in this context, such as electronic phenotyping, clinical research networks, biorepositories, screening data banks, and wide association studies. Lastly, some of the potential limitations of these approaches are discussed, focusing on confounding factors and data quality. Methods: A series of literature searches in main bibliographic databases have been conducted in order to assess the extent to which existing patient data has been repurposed for research. This contribution from the IMIA working group on “Data mining and Big Data analytics” focuses on the literature published during the last two years, covering the timeframe since the working group’s last survey. Results and Conclusions: Although most of the examples of secondary use of patient data lie in the arena of clinical and health services research, we have started to witness other important applications, particularly in the area of genomic research and the study of health effects of environmental factors. Further research is needed to characterize the economic impact of secondary use across the broad spectrum of translational research.

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