Big data in healthcare: are we close to it?

Naidus, Elliot; Celi, Leo Anthony

doi:10.5935/0103-507x.20160008

Cited by 8 publications

(6 citation statements)

References 13 publications

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“…The use of database helps studies that intend to analyse the manifestation of the disease over time. Studies of this nature can predict the probability of events based on continuous data streams [9]. In addition, the use of geoprocessing techniques with geographic information systems (GIS) combined with spatial statistics allows for the incorporation of distinct variables, especially demographic and social variables, in health studies [10, 11], making it possible to generate hypotheses regarding the transmission of diseases in different populations [12, 13].…”

Section: Introductionmentioning

confidence: 99%

Spatial and temporal analysis of tuberculosis in an area of social inequality in Northeast Brazil

et al. 2019

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Background Tuberculosis is an infectious disease caused by Mycobacterium tuberculosis . It is a disease known worldwide for its vulnerability factors, magnitude and mortality. The objective of the study was to analyze the spatial and temporal dynamics of TB in the area of social inequality in northeast Brazil between the years 2001 and 2016. Methods An ecological time series study with the use of spatial analysis techniques was carried out from 2001 to 2016. The units of analysis were the 75 municipalities in the state of Sergipe. Data from the Notification of Injury Information System were used. For the construction of the maps, the cartographic base of the state of Sergipe, obtained at the Instituto Brasileiro de Geografia e Estatística, was used. Georeferenced data were analysed using TerraView 4.2.2 software (Instituto Nacional de Pesquisas Espaciais) and QGis 2.18.2 (Open Source Geospatial Foundation). Spatial analyses included the empirical Bayesian model and the global and local Moran indices. The time trend analyses were performed by the software Joinpoint Regression, Version 4.5.0.1, with the variables of sex, age, cure and abandonment . Results There was an increasing trend of tuberculosis cases in patients under 20 years old and 20–39 years old, especially in males. Cured cases showed a decreasing trend, and cases of treatment withdrawal were stationary. A spatial dependence was observed in almost all analysed territories but with different concentrations. Significant spatial correlations with the formation of clusters in the southeast and northeast of the state were observed. The probability of illness among municipalities was determined not to occur in a random way. Conclusion The identification of risk areas and priority groups can help health planning by refining the focus of attention to tuberculosis control. Understanding the epidemiological, spatial and temporal dynamics of tuberculosis can allow for improved targeting of strategies for disease prevention and control.

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Section: Introductionmentioning

confidence: 99%

Spatial and temporal analysis of tuberculosis in an area of social inequality in Northeast Brazil

et al. 2019

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“…As the epidemiology of MDRB is continuously evolving, close monitoring of local resistance patterns may help to rationalize the empirical use of broad-spectrum antibiotics in this setting. With the expanding utilization of electronic medical records and applications specifically developed for the ICU, streaming analytics can provide dashboards containing real-time and easily accessible data for intensivists [162,163]. Such dashboards should capture data from medical records and microbiology systems, display an intuitive and userfriendly interface, and be available on both ICU computers and mobile devices to allow easy access to actionable data at the bedside.…”

Section: The Appropriate Dashboard In the Icumentioning

confidence: 99%

Rationalizing antimicrobial therapy in the ICU: a narrative review

et al. 2019

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The massive consumption of antibiotics in the ICU is responsible for substantial ecological side effects that promote the dissemination of multidrug-resistant bacteria (MDRB) in this environment. Strikingly, up to half of ICU patients receiving empirical antibiotic therapy have no definitively confirmed infection, while de-escalation and shortened treatment duration are insufficiently considered in those with documented sepsis, highlighting the potential benefit of implementing antibiotic stewardship programs (ASP) and other quality improvement initiatives. The objective of this narrative review is to summarize the available evidence, emerging options, and unsolved controversies for the optimization of antibiotic therapy in the ICU. Published data notably support the need for better identification of patients at risk of MDRB infection, more accurate diagnostic tools enabling a rule-in/rule-out approach for bacterial sepsis, an individualized reasoning for the selection of single-drug or combination empirical regimen, the use of adequate dosing and administration schemes to ensure the attainment of pharmacokinetics/pharmacodynamics targets, concomitant source control when appropriate, and a systematic reappraisal of initial therapy in an attempt to minimize collateral damage on commensal ecosystems through de-escalation and treatment-shortening whenever conceivable. This narrative review also aims at compiling arguments for the elaboration of actionable ASP in the ICU, including improved patient outcomes and a reduction in antibiotic-related selection pressure that may help to control the dissemination of MDRB in this healthcare setting.

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“…[12,18] Naidus and Celi offer the concept of big data leading to "big noise" when not applied and analyzed properly. [19] With the vast amount of data being collected today, the risk of discovering unintended and ultimately unrelated correlations can increase and can potentially lead to inappropriate changes in practice patterns if the data comprising these studies is not properly interpreted. [20] The CMS claims database and National Inpatient Sample database (NIS) represent two of the most utilized sources in orthopedic research.…”

Section: Identify the Role Of Big Data In Healthcare Deliverymentioning

confidence: 99%

Let’s not blame the patient: Understanding the benefits and shortcomings of population health in orthopaedic surgery

Amato

Sayeed²,

Lane

et al. 2018

JHA

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Population health is a concept that emerged from the desire of providers to care for patients in a manner that produces the best possible outcomes while minimizing cost. It may be defined as the study of medical data of large groups of people in order to recognize and investigate patterns. This information is then used to create disease management guidelines that streamline care and regulate practice patterns. Whereas population health looks to recognize commonalities in data, the concept of patient-centered care focuses on embracing individualization and increasing the involvement of each patient within their treatment planning. Combining both perspectives creates a challenge for providers and patients to strike the proper balance between adhering to standardized guidelines based on the treatment methods and outcomes recognized in populations and applying it clinically to individual patients. A significant contribution of population health studies is the identification of risk factors associated with increased rates of complications following total joint arthroplasty as well as preventative measures for conditions such as osteoarthritis. However, to employ these findings in a patient-centered manner orthopaedic surgeons must take this a step further and also evaluate a patient's ability to adhere to the recommendations by exploring factors such as home environment and socioeconomic factors, thus proactively addressing issues that could hinder patient compliance. With focused collection methods of acquiring data, these two practices of care will hopefully begin to see less divergence when it comes to applying data derived from population health initiatives to individual patients in a patient-centered manner.

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Big data in healthcare: are we close to it?

Cited by 8 publications

References 13 publications

Spatial and temporal analysis of tuberculosis in an area of social inequality in Northeast Brazil

Spatial and temporal analysis of tuberculosis in an area of social inequality in Northeast Brazil

Rationalizing antimicrobial therapy in the ICU: a narrative review

Let’s not blame the patient: Understanding the benefits and shortcomings of population health in orthopaedic surgery

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