Network analysis of medical care services

Niyirora, Jerome; Aragones, Ossayne

doi:10.1177/1460458219887047

Cited by 14 publications

(11 citation statements)

References 43 publications

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“…An example of how such an analysis may be conducted is shown in Figure 4. To extract thematic descriptions of the outlier maps, network analysis techniques suggested in Niyirora and Aragones [21] were applied after removing stopwords [22] and residual words (e.g., other, unspecified, etc.). Communities of words in Sub-figures 4c and 4d (distinguished by different colors) were isolated using the modularity algorithm in Gephi [23].…”

Section: Resultsmentioning

confidence: 99%

Entropic Measures of Complexity in a New Medical Coding System

Niyirora

2021

Preprint

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BackgroundTransitioning from an old medical coding system to a new one can be challenging, especially when thetwo coding systems are signiﬁcantly diﬀerent. The US experienced such a transition in 2015.ObjectiveThis research aims to introduce entropic measures to help users prepare for the migration to a newmedical coding system by identifying and focusing preparation initiatives on clinical concepts with morelikelihood of adoption challenges.MethodsTwo entropic measures of coding complexity are introduced. The ﬁrst measure is a function of thevariation in the alphabets of new codes. The second measure is based on the possible number of validrepresentations of an old code.ResultsA demonstration of how to implement the proposed techniques is carried out using the 2015 mappingsbetween ICD-9-CM and ICD-10-CM/PCS. The signiﬁcance of the resulting entropic measures is discussed inthe context of clinical concepts that were likely to pose challenges regarding documentation, coding errors,and longitudinal data comparisons.ConclusionThe proposed entropic techniques are suitable to assess the complexity between any two medical coding systems where mappings or crosswalks exist. The more the entropy, the more likelihood of adoptionchallenges. Users can utilize the suggested techniques as a guide to prioritize training eﬀorts to improve documentation and increase the chances of accurate coding, code validity, and longitudinal data comparisons.

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Section: Resultsmentioning

confidence: 99%

Entropic Measures of Complexity in a New Medical Coding System

Niyirora

2021

Preprint

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“…4 . To extract thematic descriptions of the outlier maps, network analysis techniques suggested in Niyirora and Aragones [ 21 ] were applied after removing stopwords [ 22 ] and residual words (e.g., other, unspecified, etc.). Communities of words in Fig.…”

Section: Resultsmentioning

confidence: 99%

“…Many thematic analysis [ 24 ] and ontological learning methods [ 25 , 26 ] are applicable here. For demonstration purposes, a simple graph was constructed and patterns were examined using network algorithms [ 21 , 27 ] (see Fig. 4 ).…”

Section: Discussionmentioning

confidence: 99%

Entropic measures of complexity in a new medical coding system

Niyirora

2021

BMC Med Inform Decis Mak

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Background Transitioning from an old medical coding system to a new one can be challenging, especially when the two coding systems are significantly different. The US experienced such a transition in 2015. Objective This research aims to introduce entropic measures to help users prepare for the migration to a new medical coding system by identifying and focusing preparation initiatives on clinical concepts with more likelihood of adoption challenges. Methods Two entropic measures of coding complexity are introduced. The first measure is a function of the variation in the alphabets of new codes. The second measure is based on the possible number of valid representations of an old code. Results A demonstration of how to implement the proposed techniques is carried out using the 2015 mappings between ICD-9-CM and ICD-10-CM/PCS. The significance of the resulting entropic measures is discussed in the context of clinical concepts that were likely to pose challenges regarding documentation, coding errors, and longitudinal data comparisons. Conclusion The proposed entropic techniques are suitable to assess the complexity between any two medical coding systems where mappings or crosswalks exist. The more the entropy, the more likelihood of adoption challenges. Users can utilize the suggested techniques as a guide to prioritize training efforts to improve documentation and increase the chances of accurate coding, code validity, and longitudinal data comparisons.

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“…Big data and AI techniques are being applied to the care of people in specific settings, such as nursing homes (Hamann and Bezboruah, 2020). These data allow for a 'network' of care services to be constructed to improve overall service efficiency (Niyirora and Aragones, 2020). The article suggests that healthcare managers could employ such a network, and that similar methods could be developed to build a network of symptoms for various conditions (Niyirora and Aragones, 2020).…”

Section: Using His and Big Data To Learn Understand And Inform Decision-makingmentioning

confidence: 99%

Developments in healthcare information systems in Ireland and internationally

Walsh¹,

Domhnaill²,

Mohan³

2021

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The mission of the Economic and Social Research Institute is to advance evidencebased policymaking that supports economic sustainability and social progress in Ireland. ESRI researchers apply the highest standards of academic excellence to challenges facing policymakers, focusing on 12 areas of critical importance to 21st Century Ireland.The Institute was founded in 1960 by a group of senior civil servants led by Dr T.K. Whitaker, who identified the need for independent and in-depth research analysis to provide a robust evidence base for policymaking in Ireland.Since then, the Institute has remained committed to independent research and its work is free of any expressed ideology or political position. The Institute publishes all research reaching the appropriate academic standard, irrespective of its findings or who funds the research.The quality of its research output is guaranteed by a rigorous peer review process. ESRI researchers are experts in their fields and are committed to producing work that meets the highest academic standards and practices.The work of the Institute is disseminated widely in books, journal articles and reports. ESRI publications are available to download, free of charge, from its website. Additionally, ESRI staff communicate research findings at regular conferences and seminars.The ESRI is a company limited by guarantee, answerable to its members and governed by a Council, comprising 14 members who represent a cross-section of ESRI members from academia, civil services, state agencies, businesses and civil society. The Institute receives an annual grant-in-aid from the Department of Public Expenditure and Reform to support the scientific and public interest elements of the Institute's activities; the grant accounted for an average of 30 per cent of the Institute's income over the lifetime of the last Research Strategy. The remaining funding comes from research programmes supported by government departments and agencies, public bodies and competitive research programmes.

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Network analysis of medical care services

Cited by 14 publications

References 43 publications

Entropic Measures of Complexity in a New Medical Coding System

Entropic Measures of Complexity in a New Medical Coding System

Entropic measures of complexity in a new medical coding system

Developments in healthcare information systems in Ireland and internationally

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