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Information Management and Technology
Published in James Sherifi, General Practice Under the NHS, 2023
Safe healthcare provision is dependent on many factors, not the least being good medical records. Over the past 70 years, the infrastructure and quality of record-keeping have evolved, expanded, and improved. Clarity, accessibility, and transfer of information are all light-years better than they were in 1948. GP IT systems contain a wealth of material that not only provides for targeted and safe care for the individual but also elevates the quality of care for patient populations. Aggregated data mining allows improved diagnosis, treatment, productivity, research, and best practice in primary care. Checks and balances are in place, especially with prescribing software that should reduce the potential for iatrogenic misadventures.
Practical knowledge (1) - people, communities and health workers
Published in Nigel Crisp, Turning the World Upside Down Again, 2022
These four points may all seem to be very much common sense and as if they should apply to every health system in every country. In reality, they ate not how most health systems operate. Individual clinicians may well try to take account of all of these factors; however, the health systems within which they work in western countries will typically focus on the disease or condition, use aggregated data that applies to the whole population - falling into the averages and aggregates trap mentioned in Chapter 2 - and pay little or no attention to the rest of a patient's life or to the barriers to good health which they face.
Dose Evaluation of Treatment Plans
Published in W. P. M. Mayles, A. E. Nahum, J.-C. Rosenwald, Handbook of Radiotherapy Physics, 2021
Margaret Bidmead, J.-C. Rosenwald
Such tools are normally part of any modern treatment planning system. However, it is also useful to be able to aggregate data from various categories of patients and various institutions. Therefore, specific stand-alone computer platforms have been developed, some of them including features for TCP and NTCP calculation (Sanchez-Nieto and Nahum 2000; Deasy et al. 2003; Tsougos et al. 2009; Pyakuryal et al. 2010; Ebert et al. 2010; Oinam et al. 2011; Uzan and Nahum 2012). Commercial versions of such software have also been developed (e.g. Artiview® from Aquilab). Data exchanges between various platforms are made easier with the use of the DICOM standard (see Chapter 49) and the widely accepted AAPM-RTOG format* (Deasy et al. 2003).
Chronic stroke survivors with upper limb spasticity: linking experience to the ICF
Published in Disability and Rehabilitation, 2022
Shannon Pike, Natasha A. Lannin, Lisa Cameron, Mithu Palit, Anne Cusick
Demographic and clinical data were presented for each participant and aggregated to characterise the sample. To understand the impact of spasticity on functioning disability and health, participant experience data were mapped to the ICF, initially using the refined ICF Comprehensive Core Set for stroke [9] and for data that could not be mapped to categories within the core set, other categories in the ICF were linked as required. The Brief Core Set for stroke was mapped by extracting relevant items from the Comprehensive Core Set so that gaps and overlaps between the two could be identified. Different levels of the ICF are presented (with codes) in this paper using different font-styles to help readers navigate the classification hierarchy as follows: Domains, Chapters, second-level and third-level categories.
Decomposition of Economic Inequality in Cataract Surgery Using Oaxaca Blinder Decomposition: Tehran Geriatric Eye Study (TGES)
Published in Ophthalmic Epidemiology, 2022
Hassan Hashemi, Reza Pakzad, Mehdi Khabazkhoob
Although there are several studies on the use of Oaxaca-Blinder decomposition,20–22 an extensive search showed that only one study investigated economic inequality and decomposed it using individual data for cataract surgery.23 To the best of our knowledge, most of the studies have investigated economic data using aggregate data. Alinia et al. found an inequality in cataract surgery in Iran such that the cataract surgery rate was higher in provinces with a better economic status.10 Hashemi et al. also reported a concentration index of 0.1964 between cataract surgery rate and economic status indicating a pro-rich inequality at the province level.11 In line with Alinia et al.10 and Hashemi et al.,11 Ono et al.9 and Yan et al.8 showed a positive relationship between cataract surgery rate and economic status such that the cataract surgery rate increased with improvement in the economic status. Although the findings of these studies were in contrast to our results, it should be noted that the occurrence of ecologic fallacy is a possibility in these studies due to their ecologic design.8 In other words, it is possible that in rich provinces where cataract surgery services are available, poor people more undergo more cataract surgery because they are more at risk of cataract.24 Studies have shown that in nutritionally deprived communities, the risk of developing cataracts increases due to antioxidant deficiencies and protein deficiency.25
Acceptance and forgiveness therapy for veterans with moral injury: spiritual and psychological collaboration in group treatment
Published in Journal of Health Care Chaplaincy, 2022
Patricia U. Pernicano, Jennifer Wortmann, Kerry Haynes
AFT groups for MI launched in 2018, and Pre- and Post-measures were collected in session to track clinical outcomes, consistent with the VA emphasis on data-driven care. The bowls described in this paper were a clinical task during and between sessions and photographed/used with veteran permission, and veterans keep their original drawings. Aggregate data was compiled for this paper to illustrate our program’s overall effectiveness. The Research Compliance Coordinator of the Institutional Review Board (IRB) determined that this project is not regulated research and does not require IRB approval, due to the purpose of data collection. Patient data is stored in Mental Health Assistant, a secure medical records system, and de-identified scores on Pre- and Post-measures are saved in password protected Excel files.