Patient injuries in pediatric otorhinolaryngology

Nokso-Koivisto, Johanna; Blomgren, Karin; Aaltonen, Leena‐Maija; Lehtonen, Lasse; Helmiö, Päivi

doi:10.1016/j.ijporl.2019.02.007

Cited by 4 publications

(3 citation statements)

References 15 publications

(32 reference statements)

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“…PIC administers an extensive patient injury data which has been widely used for medical research. Research has concentrated on surgical specialties like orthopaedics, 4 5 otorhinolaryngology, 6 and dental care. 7 8 An article 9 recently raised attention to psychiatric patient injuries which had not been investigated earlier.…”

Section: Introductionmentioning

confidence: 99%

Machine Learning Classification of Psychiatric Data Associated with Compensation Claims for Patient Injuries

Juhola,

Nikkanen,

Niemi

et al. 2023

Methods Inf Med

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Background Adverse events are common in health care. In psychiatric treatment, compensation claims for patient injuries appear to be less common than in other medical specialties. The most common types of patient injury claims in psychiatry include diagnostic flaws, unprevented suicide, or coercive treatment deemed as unnecessary or harmful. Objectives The objective was to study whether it is possible to form different categories of patient injury types associated with the psychiatric evaluations of compensation claims and to base machine learning classification on these categories. Further, the binary classification of positive and negative decisions for compensation claims was the other objective. Methods Finnish psychiatric specialist evaluations for the compensation claims of patient injuries were classified into six different categories called classes applying the machine learning methods of artificial intelligence. In addition, another classification of the same data into two classes was performed to test whether it was possible to classify data cases according to their known decisions, either accepted or declined compensation claim. Results The former classification task produced relatively good classification results subject to separating between different classes. Instead, the latter was more complex. However, classification accuracies of both tasks could be improved by using the generation of artificial data cases in the preprocessing phase before classifications. This preprocessing improved the classification accuracy of six classes up to 88% when the method of random forests was used for classification and that of the binary classification to 89%. Conclusion The results show that the objectives defined were possible to solve reasonably.

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Section: Introductionmentioning

confidence: 99%

Machine Learning Classification of Psychiatric Data Associated with Compensation Claims for Patient Injuries

Juhola,

Nikkanen,

Niemi

et al. 2023

Methods Inf Med

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“…Most of the errors and adverse events in the field of otorhinolaryngology (ORL) are related to surgical treatment 1 . Retrospective national studies in Finland show that ORL‐related patient injuries, in general, are strongly linked to routine operations in high‐volume centers 2–5 . In a recent study, 88% of ORL‐related patient injuries that affected children were related to operative care in Finland 3 …”

Section: Introductionmentioning

confidence: 99%

“… 2 , 3 , 4 , 5 In a recent study, 88% of ORL‐related patient injuries that affected children were related to operative care in Finland. 3 …”

Section: Introductionmentioning

confidence: 99%

Patient injuries from tonsil and adenoid surgery in Finland

Sjöblom

Timgren

Piitulainen

et al. 2022

Laryngoscope Investig Oto

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Objectives: The aims of this national register-based study were to examine patient injury claims related to tonsil and adenoid surgery injuries and to compare the frequency of claims between tonsillectomies and tonsillotomies in Finland. Methods:We analyzed the complaints related to tonsil and adenoid surgery received by the Finnish Patient Insurance Center (PIC) between the years 2000 and 2019.One hundred seventy-two cases were included in the analysis. The annual surgery rates between the years 2000 and 2018 were acquired from the Finnish Institute for Health and Welfare.Results: During the years 2000 to 2018, a total of 292,679 patients had tonsil and/or adenoid surgery nationwide. For tonsil or adenoid surgeries, the national average was 5.3 cases and 1.8 cases per 10,000, respectively, resulting in patient injury claims and compensations. A total of 33.1% of the claims regarding tonsil or adenoid surgery processed by the PIC were compensated. Most of the claims were made after a tonsillectomy (87.8%), and few were made after a tonsillotomy (1.7%). Seven deaths were recorded. Conclusion:Patient injuries from tonsil and adenoid surgeries were mostly related to traditional extracapsular tonsillectomies. Most surgeries, along with most complications, involved specialists, who performed routine operations in high-volume centers.Surgeries for acute or recurrent infections resulted in more claims. Severe complications arising from tonsil and adenoid surgeries were rare.

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