scholarly journals Vault, cloud and agent: choosing strategies for quality improvement and research based on routinely collected health data

2010 ◽  
Vol 18 (1) ◽  
pp. 1-4
Author(s):  
Simon De Lusignan ◽  
Frank Sullivan ◽  
Paul Krause
2022 ◽  
Vol 11 (1) ◽  
pp. e001491
Author(s):  
Taylor McGuckin ◽  
Katelynn Crick ◽  
Tyler W Myroniuk ◽  
Brock Setchell ◽  
Roseanne O Yeung ◽  
...  

High-quality data are fundamental to healthcare research, future applications of artificial intelligence and advancing healthcare delivery and outcomes through a learning health system. Although routinely collected administrative health and electronic medical record data are rich sources of information, they have significant limitations. Through four example projects from the Physician Learning Program in Edmonton, Alberta, Canada, we illustrate barriers to using routinely collected health data to conduct research and engage in clinical quality improvement. These include challenges with data availability for variables of clinical interest, data completeness within a clinical visit, missing and duplicate visits, and variability of data capture systems. We make four recommendations that highlight the need for increased clinical engagement to improve the collection and coding of routinely collected data. Advancing the quality and usability of health systems data will support the continuous quality improvement needed to achieve the quintuple aim.


Author(s):  
Joia S. Mukherjee

Quality data are necessary to make good decisions in health delivery for both individuals and populations. Data can be used to improve care and achieve equity. However, systems for health data management were historically weak in most impoverished countries. Health data are not uncommonly compiled in stacks of poorly organized paper records. Efforts to streamline and improve health information discussed in this chapter include patient-held booklets, demographic health surveys, and the use of common indicators. This chapter also focuses on the evolution of medical records, including electronic systems. The use of data for monitoring, evaluation, and quality improvement is explained. Finally, this chapter reviews the use of frameworks—such as logic models and log frames—for program planning, evaluation, and improvement.


2016 ◽  
Vol Volume 8 ◽  
pp. 389-392 ◽  
Author(s):  
Stuart Nicholls ◽  
Sinead Langan ◽  
Henrik Toft Sørensen ◽  
Irene Petersen ◽  
Eric Benchimol

2020 ◽  
Vol 41 (Supplement_2) ◽  
Author(s):  
L.A Barnes ◽  
A Eng ◽  
M Corbin ◽  
H.J Denison ◽  
A t'Mannetje ◽  
...  

Abstract Background/Introduction Occupation is a poorly characterised risk factor for cardiovascular disease (CVD), with females and minority populations particularly under-represented in research. There is also a lack of longitudinal studies using detailed health data that does not rely on self-reports. Purpose This study aimed to address these gaps by assessing the association between a range of occupational groups and ischaemic heart disease (IHD) in New Zealand (NZ), through linkage of population-based occupational surveys to routinely collected health data. Half of the study population were females and 40% were indigenous Māori (who comprise 15% of the total 4.8 million NZ population), which enabled sex and ethnicity-specific aspects of the relationship between occupation and IHD to be assessed. Methods Two probability-based sample surveys of the NZ adult population (New Zealand Workforce Survey (NZWS); 2004–2006; n=3003) and of the Māori population (NZWS Māori; 2009–2010; n=2107), for which detailed occupational histories and lifestyle factors were collected, were linked with routinely collected health data available through Statistics NZ. Cox regression was used to calculate hazard ratios (HR) for “ever-worked” in any one of nine major occupational groups, with “never worked” in that occupational group defined as the reference group. Analyses were controlled for age, deprivation and smoking, and stratified by sex and ethnicity. Results The strongest associations were found for “plant/machine operators and assemblers” and “elementary workers”, particularly among female Māori (HR 2.19, 95% CI 1.16–4.13 and HR 2.03, 1.07–3.82 respectively). In contrast, inverse associations with IHD across all groups were observed for “technicians and associate professionals”, which was significant for NZWS males (HR 0.52, 0.32–0.84). There were some sex and ethnic differences, particularly for “clerks”, where a positive association was found for NZWS males (HR 1.81, 1.19–2.74), whilst an inverse association was observed for Māori females (HR 0.42, 0.22–0.82). Duration analyses (≤2 years, 2–10 years and 10+ years) showed significant dose-response trends for “clerks” in NZWS males, and “plant/machine operators and assemblers” and “elementary workers” in Māori females. Further adjustments for other potential confounders such diabetes mellitus, hypertension and high cholesterol did not affect the results. Conclusion Associations between occupation and IHD differed significantly across occupational groups and between sexes and ethnicities, even within the same occupational groups. This suggests that results may not be generalised across these groups and occupational interventions to reduce IHD risk may therefore need different approaches depending on the population and specific groups of interest. Funding Acknowledgement Type of funding source: Other. Main funding source(s): Health Research Council (HRC) of New Zealand


2017 ◽  
Vol 137 (5) ◽  
pp. S29 ◽  
Author(s):  
M.P. Dizon ◽  
A.M. Yu ◽  
R.K. Singh ◽  
J. Wan ◽  
D.J. Margolis ◽  
...  

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