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Letteratura scientifica selezionata sul tema "ICD-10"

Autore: Grafiati

Pubblicato: 4 giugno 2021

Ultima modifica: 20 febbraio 2023

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Articoli di riviste sul tema "ICD-10"

1

Gonzalez, Tyler, e Christopher Chiodo. "ICD 10". Foot & Ankle International 36, n. 9 (13 agosto 2015): 1110–16. http://dx.doi.org/10.1177/1071100715600286.

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2

Harrington, Linda. "ICD-10". AACN Advanced Critical Care 25, n. 4 (2014): 319–21. http://dx.doi.org/10.1097/nci.0000000000000040.

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3

Henley, M. Bradford. "ICD 10". Sports Medicine and Arthroscopy Review 21, n. 3 (settembre 2013): 142–47. http://dx.doi.org/10.1097/jsa.0b013e3182991370.

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4

Drimmelen-krabbe, Jenny J. Van. "The neurological adaptation of ICD-10 (ICD-10 NA)". Arquivos de Neuro-Psiquiatria 53, n. 2 (giugno 1995): 342–43. http://dx.doi.org/10.1590/s0004-282x1995000200029.

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5

Stephens, James H., Gerald R. Ledlow e Thomas V. Fockler. "Converting ICD-9 to ICD-10". Hospital Topics 94, n. 1 (2 gennaio 2016): 1–7. http://dx.doi.org/10.1080/00185868.2015.1119549.

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6

Rydelius, P. "From ICD-10 to ICD-11". Neuropsychiatrie de l'Enfance et de l'Adolescence 60, n. 5 (luglio 2012): S8. http://dx.doi.org/10.1016/j.neurenf.2012.04.039.

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7

Feinstein, Anthony. "Editorial : ICD-10". International Journal of Social Psychiatry 39, n. 3 (settembre 1993): 157–58. http://dx.doi.org/10.1177/002076409303900301.

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8

van Drimmelen-Krabbe, J. J. "WHO ICD-10 Evaluation and evolution: ICD-10 Training courses". European Psychiatry 11 (gennaio 1996): 200s. http://dx.doi.org/10.1016/0924-9338(96)88574-9.

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9

Buckholtz, Rhonda. "ICD-9 Transition to ICD-10 Diagnostic Coding". Otolaryngology–Head and Neck Surgery 143, n. 5 (novembre 2010): 716. http://dx.doi.org/10.1016/s0194-5998(10)02292-8.

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10

Waguespack, Richard W., e Rhonda Buckholtz. "ICD-9-CM to ICD-10-CM Transition". Otolaryngology–Head and Neck Surgery 145, n. 2_suppl (agosto 2011): P10—P11. http://dx.doi.org/10.1177/0194599811415818a8.

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Tesi sul tema "ICD-10"

1

Butz, Jennifer Anne. "The Transition to ICD-10-CM/PCS: A Comparison of Physician and Coder Perceptions". The Ohio State University, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=osu1428911324.

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2

Jacobs, Felix Daniel. "Entwicklung eines neuen Instruments zur Diagnostik psychischer Störungen nach ICD-10 /". Regensburg, 2007. http://opac.nebis.ch/cgi-bin/showAbstract.pl?sys=000253229.

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3

Hentschel, Katrin. "Semantische, psychopathologische und syntaktische Beurteilung der Kriteriensätze für Persönlichkeitsstörungen nach ICD-10". Berlin Logos-Verl, 2005. http://deposit.d-nb.de/cgi-bin/dokserv?id=2875260&prov=M&dok_var=1&dok_ext=htm.

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4

Monestime, Judith. "ICD-10-CM Implementation Strategies: An Application of the Technology Acceptance Model". ScholarWorks, 2015. https://scholarworks.waldenu.edu/dissertations/1909.

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The United States is one of the last countries to transition to the 10th edition of the International Classification of Diseases (ICD-10) coding system. The move from the 35-year-old system, ICD-9, to ICD-10, represents a milestone in the transformation of the 21st century healthcare industry. All covered healthcare entities were mandated to use the ICD-10 system on October 1, 2015, to justify medical necessity, an essential component in determining whether a service is payable or not. Despite the promising outcomes of this shift, more than 70% of healthcare organizations identified concerns related to education efforts, including lack of best practices for the ICD-10 transition. Lack of preparation for the implementation of ICD-10 undermines the clinical, technological, operational, and financial processes of healthcare organizations. This study was an exploration of implementation strategies used to overcome barriers to transition to ICD-10. A single case study was conducted, grounded by the conceptual framework of the technology acceptance model, to learn about ways to mitigate the barriers of this new coding system. Data were gathered from the review of documents, observations, and semistructured interviews with 9 participants of a public healthcare organization in Florida. Data were coded to identify themes. Key themes that emerged from the study included (a) in-depth ICD-10 training, (b) the prevalence of ICD-10 cheat sheets, (c) lack of system readiness, and (d) perception of usefulness of job performance. The results of the study may contribute to social change by identifying successful implementation strategies to mitigate operational disruptions that will allow providers to capture more detailed health information about the severity of patients' conditions.

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Johansson, Anders, e Robin Wassbjer. "Windows 10 för inbyggda system : En undersökning av Windows 10 IoT Enterprise". Thesis, Linnéuniversitetet, Institutionen för datavetenskap (DV), 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-55599.

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Microsoft lanserade Windows 10 i mitten av 2015. Windows 10 är en serie operativ-system med flera versioner anpassade för många olika användningsområden. Windows 10 IoT Enterprise är en av versionerna inriktade på olika typer av inbyggda system. Vid anpassning utefter miljö kan delar av operativsystemet därför låsas ned och begränsas. För konfiguration av Windows 10 finns både gamla och nya verktyg tillgängliga. I detta projekt görs en undersökning av nedlåsnings- och anpassningsmöjligheter, samt konfigurationsverktyg med fokus på Windows 10 IoT Enterprise. De verktyg som har använts är Microsofts helt nya Windows Imaging and Configuration Designer, men även det lite äldre Windows System Image Manager. Med och utan hjälp av dessa verktyg har flera konfigurationsmöjligheter undersökts. Detta inkluderar bl.a. användar- och applikationsbegränsningar, branding (mjukvarumässig produktmärk-ning), och utseendeanpassningar. Utöver detta behandlas även framtagandet av färdig-konfigurerade Windows-avbildningar ytligt. Projektet har bestått av åtskilliga tester, främst baserade på Microsofts egna dokumentation. Majoriteten av de möjligheter och konfigurationer som har undersökts har visat sig fungerande och någorlunda lättanvända. En fungerande funktion har endast bedömts som sådan om denna uppfyller de beskrivningar Microsoft själva har givit ut. Detta utan att för den sakens skull förstöra andra delar av systemet. I slutändan beskriver resultaten till stor del funktioner som finns och fungerar, men inte i vilka praktiska scenarier dessa lämpar sig för användning. Vid konfiguration av större nedlåsningsfunktioner uppvisar Windows ICD problem. Ytterligare problem som också har noterats berör bl.a. möjligheterna för profilkopiering och generalisering i Windows 10.
Microsoft released Windows 10 in the middle of 2015. Windows 10 is a series of operating systems with multiple versions adapted for many different fields of work. Windows 10 IoT Enterprise is one of the versions aimed at various types of embedded systems. During adaptation into certain environments, parts of the operating system may therefore be locked down or limited. For configuration of Windows 10, both old and new tools are available. In this project, an examination of lockdown and adaptation possibilities, as well as configuration tools, focusing on Windows 10 IoT Enterprise is made. The tools used are Microsoft’s brand new Windows Imaging and Configuration Designer, but also their older Windows System Image Manager. Multiple configurations have been examined both with, and without the help of these tools. This includes user and application limitations, branding, and appearance. In addition to this, the creation of fully configured Windows images is superficially addressed. The project has consisted of several tests, mainly based on documentation from Microsoft. A majority of the examined possibilities and configurations have proven functional and quite easy to make use of. A working functionality has only been evaluated as such if it satisfies descriptions released by Microsoft themselves. This, as well as not breaking other parts of the system. In the end, the result mainly describes existing and working functionalities, not in what practical scenarios they fit. During configuration of major lockdown features, Windows ICD displays problems. Other problems has also been noted, among other things related to profile copying and generalization in Windows 10.

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Slade, Tim Psychiatry Faculty of Medicine UNSW. "Using epidemiology to inform classification in psychiatry". Awarded by:University of New South Wales. Psychiatry, 2002. http://handle.unsw.edu.au/1959.4/19059.

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Classification systems in psychiatry are a work in progress. Therefore, continued efforts to improve their validity are necessary. Epidemiology provides a scientific method to assess the extent of psychiatric morbidity in community populations. However, data from epidemiological surveys have also contributed, either directly or indirectly, to many changes in the classification systems. Recent reviews of the current state of psychiatric classification indicate four unresolved issues: 1) the presence of two differing classification systems, 2) the role of the clinical significance criterion in differentiating psychopathology from normality, 3) the relationship of the exclusion criteria to the co-occurrence of psychiatric disorder pairs, and 4) the relative validity of categorical versus dimensional conceptualizations of psychiatric disorders. The current thesis examines these four unresolved issues, using data from a large-scale epidemiological survey of psychiatric disorders. With regard to GAD, differences in diagnostic criteria between DSM-IV and ICD-10 resulted in different types of cases identified, despite similarities in prevalence. The DSM-IV diagnostic criterion for clinical significance impacted, albeit to different degrees, on the prevalence, health service use and impairment of five disorders. The exclusion criteria in both DSM-IV and ICD-10 were significantly related to the patterns of co-occurrence found in the data. Using the example of depression, symptoms were more consistent with a dimensional rather than a categorical structure. A specific research agenda is proposed, the aim of which is to provide possible avenues of research that may benefit revisions to classification systems and the conduct of epidemiological surveys. This research agenda contains a number of suggestions. Future revisions will benefit from an explicit understanding of the differences between the classification systems. Better definitions of the concepts of clinical significance and psychiatric disorder are required. The co-occurrence of disorder pairs in epidemiological data informs understanding of the exclusion criteria, but the validity of these criteria relies on different data. Dimensional models of classification may yield more information than categorical models, and methods for incorporating them in large-scale surveys are proposed. It is concluded that epidemiological data should continue to play a significant part in the refinement of psychiatric classification.

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Akkerman, Cindy A. "Intraoperative Neurophysiological Monitoring Reimbursement Post International Classification of Diseases-10". ScholarWorks, 2019. https://scholarworks.waldenu.edu/dissertations/6297.

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International Classification of Diseases the 10th Revision (ICD-10) was implemented October 1, 2015, and there was little knowledge how the transition to ICD-10 would impact the revenue cycle for intraoperative neurophysiological monitoring medical practices in Oklahoma. This correlational quantitative study examined the changes in dependent variables of reimbursements due to the change from ICD-9 to ICD-10 for independent variables of intraoperative neurophysiological monitoring procedure codes. The reimbursements from 2014 were compared to reimbursements from 2016. Prices were adjusted for inflation to 2016 dollar values. Annual reimbursements decreased for all intraoperative neurophysiological monitoring procedures examined except the remote monitoring code. The intraoperative neurophysiological monitoring procedure with the greatest mean annual decreases in reimbursement was the lower somatosensory evoked potentials. The intraoperative neurophysiological monitoring procedures with the least annual reimbursement decreases were transcranial electrical motor potential monitoring and electromyography. The findings of the budget-impact analysis and cost-effectiveness analysis indicated that reimbursement for procedures has steadily decreased from 2014 to 2016, causing a negative effect on practices' revenue cycle management. The findings of this study could benefit intraoperative neurophysiological monitoring companies in Oklahoma by supporting adjustments essential for healthcare leaders to maintain a financially sustainable intraoperative neurophysiological monitoring medical practice.

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8

Probst, Thomas. "Monitoring und Feedback in der stationären Psychosomatik mit dem OQ-Analyst und dem ICD-10-Symptom-Rating". Doctoral thesis, Humboldt-Universität zu Berlin, Lebenswissenschaftliche Fakultät, 2015. http://dx.doi.org/10.18452/17159.

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Diese publikationsgestützte Dissertation umfasst Arbeiten zum Thema Monitoring und Feedback in der stationären Psychosomatik. In zwei Arbeiten wurde untersucht, ob die Effektivität von psychosomatischen Behandlungen gesteigert werden kann, wenn Therapeuten regelmäßig Feedbackberichte der Monitoring- und Feedbacksoftware OQ-Analyst erhalten Hier zeigte sich, dass Feedback den Outcome von Patienten mit erhöhtem Risiko einer Verschlechterung verbessern kann. Bei den restlichen Patienten dagegen konnte Feedback den Therapieprozess nur schwach und nur kurzfristig für eine Behandlungswoche verbessern. In einer weiteren Arbeit wurde untersucht, ob sich unterschiedliche Belastungsgrade im wöchentlichen Monitoring differenziell verändern. Hierfür wurde das ICD-10-Symptomrating herangezogen. Die Ergebnisse lieferten Hinweise darauf, dass sich depressive Beschwerden und Angstbeschwerden schon in der ersten Behandlungswoche verbessern, somatoforme Beschwerden jedoch erst im späteren Behandlungsverlauf. Die vierte Arbeit setze sich mit der Fragestellung auseinander, ob Therapiebeziehung, soziale Unterstützung, Motivation, und Lebensereignisse mit bedeutsamen Verbesserungen und bedeutsamen Verschlechterungen assoziiert sind. Während alle vier Bereiche mit bedeutsamen Verbesserungen verknüpft waren, waren nur soziale Unterstützung und Lebensereignisse mit bedeutsamen Verschlechterungen assoziiert.
This dissertation is based on four publications on monitoring and feedback in psychosomatic in-patient therapy. In two publication it was investigated whether the effectiveness of psychosomatic in-patient therapy can be increased when therapists routinely receive the feedback reports of the monitoring and feedback software OQ-Analyst. Feedback could improve the outcome of patients at risk of treatment failure. For the remaining patients, feedback could optimize the therapy process only slightly for one treatment week. In another publication, the ICD-10-Symptom-Rating was used to explore how different symptoms change on a weekly basis. While depressive symptoms and symptoms of anxiety disorders improved already in the first treatment week, more treatment weeks were required to improve somatoform symptoms. In a fourth publication, associations between considerable positive as well as considerable negative change and the therapeutic alliance, social support, motivation, and life events were investigated. While all four factors were associated with considerable improvements, only social support and life events correlated with considerable deteriorations.

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9

Januel, Jean-Marie. "Les données de routine des séjours d’hospitalisation pour évaluer la sécurité des patients : études de la qualité des données et perspectives de validation d’indicateurs de la sécurité des patients". Thesis, Lyon 1, 2011. http://www.theses.fr/2011LYO10355/document.

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Évaluer la sécurité des patients hospitalisés constitue un enjeu majeur de la gestion des risques pour les services de santé. Le développement d’indicateurs destinés à mesurer les événements indésirables liés aux soins (EIS) est une étape cruciale dont le défi principal repose sur la performance des données utilisées. Le développement d’indicateurs de la sécurité des patients – les Patient Safety Indicators (PSIs) – par l’Agency for Healthcare Research and Quality (AHRQ) aux Etats Unis, utilisant des codes de la 9ème révision (cliniquement modifiée) de la Classification Internationale des Maladies (CIM) présente des perspectives intéressantes. Nos travaux ont abordé cinq questions fondamentales liées au développement de ces indicateurs : la définition du cadre nosologique, la faisabilité de calcul des algorithmes et leur validité, la qualité des données pour coder les diagnostics médicaux à partir de la CIM et leur performance pour comparer plusieurs pays, et la possibilité d’établir une valeur de référence pour comparer ces indicateurs. Certaines questions demeurent cependant et nous proposons des pistes de recherche pour améliorer les PSIs : une meilleure définition des algorithmes et l’utilisation d’autres sources de données pour les valider (i.e., données de registre), ainsi que l’utilisation de modèles d’ajustement utilisant l’index de Charlson, le nombre moyen de diagnostics codés et une variable de la valeur prédictive positive, afin de contrôler les variations du case-mix et les différences de qualité du codage entre hôpitaux et pays
Assessing safety among hospitalized patients is a major issue for health services. The development of indicators to measure adverse events related to health care (HAE) is a crucial step, for which the main challenge lies on the performance of the data used for this approach. Based on the limitations of the measurement in terms of reproducibility and on the high cost of studies conducted using medical records audit, the development of Patient Safety Indicators (PSI) by the Agency for Healthcare Research and Quality (AHRQ) in the United States, using codes from the clinically modified 9th revision of the International Classification of Diseases (ICD) shows interesting prospects. Our work addressed five key issues related to the development of these indicators: nosological definition; feasibility and validity of codes based algorithms; quality of medical diagnoses coding using ICD codes, comparability across countries; and possibility of establishing a benchmark to compare these indicators. Some questions remain, and we suggest several research pathways regarding possible improvements of PSI based on a better definition of PSI algorithms and the use of other data sources to validate PSI (i.e., registry data). Thus, the use of adjustment models including the Charlson index, the average number of diagnoses coded and a variable of the positive predictive value should be considered to control the case-mix variations and differences of quality of coding for comparisons between hospitals or countries

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Höjvall, Jessica. "A Cost-of-illness Study : of skin, soft tissue, bone and lung infections caused by Staphylococci". Thesis, Uppsala University, Department of Economics, 2006. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-7051.

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The essay investigates the economic burden of skin, soft tissue, bone and lung infections in Sweden 2003. The cost-of-illness method, based on the human capital theory, is used in the estimation. A prevalence approach and a top-down method were chosen for direct as well as indirect costs. Also there is a discussion concerning health economic aspects of antibiotic resistance and evidence of the increasing costs because of it. The lack of data leads to a result within a large interval of uncertainty; the direct costs are estimated to 1 072 million SEK and indirect costs are estimated to 4 655 million SEK.

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Libri sul tema "ICD-10"

1

Hazelwood, Anita C. ICD-10-CM and ICD-10-PCS preview. 2^a ed. Chicago, Ill: AHIMA, 2009.

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Hazelwood, Anita C. ICD-10-CM and ICD-10-PCS preview. Chicago, Ill: AHIMA, 2004.

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A, Venable Carol, e American Health Information Management Association., a cura di. ICD-10-CM and ICD-10-PCS preview. 2^a ed. Chicago, Ill: AHIMA, 2009.

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Hazelwood, Anita C. ICD-10-CM and ICD-10-PCS preview. 2^a ed. Chicago, Ill: AHIMA, 2009.

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5

Köpf, Gerhard, a cura di. ICD-10 literarisch. Wiesbaden: VS Verlag für Sozialwissenschaften, 2006. http://dx.doi.org/10.1007/978-3-8350-9667-7.

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6

Grebner, Leah A. Medical coding: Understanding ICD-10-CM and ICD-10-PCS. New York, NY: McGraw-Hill, 2013.

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E, Bowman Sue, American Health Information Management Association e American Medical Association, a cura di. Pocket guide of ICD-10-CM and ICD-10-PCS. Chicago, Ill: AHIMA, 2010.

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8

Scherer, Josef, e Karin Kuhn. Angststörungen nach ICD-10. Heidelberg: Steinkopff, 2002. http://dx.doi.org/10.1007/978-3-642-57530-3.

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9

ICD-10 diagnostic coding. 5^a ed. [St. Louis, Mo.]: Saunders, 2015.

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10

ICD-10-CM mappings. [Place of publication not identified]: Ingenix, 2010.

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Capitoli di libri sul tema "ICD-10"

1

Morisy, Lee R. "ICD-10". In Principles of Coding and Reimbursement for Surgeons, 13–34. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-43595-4_2.

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Nahler, Gerhard. "ICD-10 cade". In Dictionary of Pharmaceutical Medicine, 88. Vienna: Springer Vienna, 2009. http://dx.doi.org/10.1007/978-3-211-89836-9_659.

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von Goethe, Johann Wolfgang. "Die Leiden des jungen Werthers". In ICD-10 literarisch, 159–70. Wiesbaden: VS Verlag für Sozialwissenschaften, 1991. http://dx.doi.org/10.1007/978-3-8350-9667-7_10.

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von Hofmannsthal, Hugo. "Ein Brief". In ICD-10 literarisch, 185–97. Wiesbaden: VS Verlag für Sozialwissenschaften, 2000. http://dx.doi.org/10.1007/978-3-8350-9667-7_12.

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Scheinert, Hanns-Dierk, Christoph Straub, Theo Riegel, Holger Strehlau-Schwoll, Klaus Schmolling, Frank Tschubar e Harald Schmitz. "Überführung ICD-9 auf ICD-10". In Krankenhausabrechnung für Ärzte, 115–19. Berlin, Heidelberg: Springer Berlin Heidelberg, 2000. http://dx.doi.org/10.1007/978-3-662-08207-2_6.

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Sartorius, Norman. "ICD-10 and Depression". In Clinical Psychopathology Nomenclature and Classification, 661–63. Boston, MA: Springer US, 1985. http://dx.doi.org/10.1007/978-1-4899-5049-9_113.

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Nicolai, T., e F. Hoffmann. "Häufige ICD-10 Diagnosen". In Kindernotfall-ABC, 303–7. Berlin, Heidelberg: Springer Berlin Heidelberg, 2019. http://dx.doi.org/10.1007/978-3-662-49797-5_23.

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Hinterhuber, Hartmann. "Schlafstörungen (ICD-10 F51)". In Lehrbuch Psychiatrie, 405–29. Vienna: Springer Vienna, 2012. http://dx.doi.org/10.1007/978-3-211-89865-9_12.

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Kapfhammer, Hans-Peter. "Persönlichkeitsstörungen (ICD-10 F6)". In Lehrbuch Psychiatrie, 293–321. Vienna: Springer Vienna, 2012. http://dx.doi.org/10.1007/978-3-211-89865-9_8.

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Stöver, Imke, e Petra Feyer. "ICD-10-GM-Klassifikation". In Praxismanual Strahlentherapie, 445–69. Berlin, Heidelberg: Springer Berlin Heidelberg, 2018. http://dx.doi.org/10.1007/978-3-662-56577-3_39.

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Atti di convegni sul tema "ICD-10"

1

Shafruddin, Hafiz, e Jeewani A. Ginige. "An Algorithmic Approach to Create Bi-directional Mapping Files Between ICD-10 and ICD-10-AM". In ACSW '20: Australasian Computer Science Week 2020. New York, NY, USA: ACM, 2020. http://dx.doi.org/10.1145/3373017.3373044.

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Siangchin, Noppon, e Taweesak Samanchuen. "Chatbot Implementation for ICD-10 Recommendation System". In 2019 International Conference on Engineering, Science, and Industrial Applications (ICESI). IEEE, 2019. http://dx.doi.org/10.1109/icesi.2019.8863009.

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Kharadkar, Ronak, e S. Justus. "Designing knowledge representation framework for ICD-10". In 2015 International Conference on Futuristic Trends on Computational Analysis and Knowledge Management (ABLAZE). IEEE, 2015. http://dx.doi.org/10.1109/ablaze.2015.7154927.

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"ICD-10 Auto-coding System Using Deep Learning". In 2020 the 10th International Workshop on Computer Science and Engineering. WCSE, 2020. http://dx.doi.org/10.18178/wcse.2020.02.008.

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Dilling, Horst, Y. Nakane, Harald J. Freyberger e Werner Mombour. "ENSURING EQUIVALENCE OF ICD-10 VERSIONS IN DIFFERENT LANGUAGES". In IX World Congress of Psychiatry. WORLD SCIENTIFIC, 1994. http://dx.doi.org/10.1142/9789814440912_0031.

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Doi, Shunsuke, Takashi Kimura, Takahiro Suzuki e Katsuhiko Takabayashi. "Development of Doctors Search Engine based on ICD-10". In 2012 Joint 6th Intl. Conference on Soft Computing and Intelligent Systems (SCIS) and 13th Intl. Symposium on Advanced Intelligent Systems (ISIS). IEEE, 2012. http://dx.doi.org/10.1109/scis-isis.2012.6505365.

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Velichkov, Boris, Simeon Gerginov, Panayot Panayotov, Sylvia Vassileva, Gerasim Velchev, Ivan Koychev e Svetla Boytcheva. "Automatic ICD-10 codes association to diagnosis: Bulgarian case". In CSBio2020: The 11th International Conference on Computational Systems-Biology and Bioinformatics. New York, NY, USA: ACM, 2020. http://dx.doi.org/10.1145/3429210.3429224.

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8

Zweigenbaum, Pierre, e Thomas Lavergne. "Hybrid methods for ICD-10 coding of death certificates". In Proceedings of the Seventh International Workshop on Health Text Mining and Information Analysis. Stroudsburg, PA, USA: Association for Computational Linguistics, 2016. http://dx.doi.org/10.18653/v1/w16-6113.

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9

LOPEZ-IBOR, JUAN J., NORMAN SARTORIUS, A. JANCA, M. KASTRUP, H. KATSCHNIG e J. MEZZICH. "THE ICD-10 MULTIAXIAL SYSTEM: PRELIMINARY RESULTS OF FIELD TRIALS". In IX World Congress of Psychiatry. WORLD SCIENTIFIC, 1994. http://dx.doi.org/10.1142/9789814440912_0037.

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10

Bagheri, Ayoub, Arjan Sammani, Peter Van Der Heijden, Folkert Asselbergs e Daniel Oberski. "Automatic ICD-10 Classification of Diseases from Dutch Discharge Letters". In Workshop on COMP2CLINIC: Biomedical Researchers & Clinicians Closing The Gap Between Translational Research And Healthcare Practice. SCITEPRESS - Science and Technology Publications, 2020. http://dx.doi.org/10.5220/0009372602810289.

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Rapporti di organizzazioni sul tema "ICD-10"

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Hedegaard, Holly, Matthew Garnett, Renee Johnson e Karen Thomas. A Revised ICD–10–CM Surveillance Case Definition for Injury-related Emergency Department Visits. National Center for Health Statistics (U.S.), settembre 2021. http://dx.doi.org/10.15620/cdc:108998.

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Hedegaard, Holly, Matthew Garnett, Renee Johnson e Karen Thomas. A Revised ICD–10–CM Surveillance Case Definition for Injury-related Emergency Department Visits. National Center for Health Statistics (U.S.), settembre 2021. http://dx.doi.org/10.15620/cdc:109050.

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Dai, Ning, Fangfang Zhao, Min Fang, Lingyao Kong, Fenglan Pu e Jianping Liu. Gynostemma Pentaphyllum for Dyslipidemia: A protocol of Systematic Review of Randomized Controlled Trials. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, gennaio 2022. http://dx.doi.org/10.37766/inplasy2022.1.0135.

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Abstract (sommario):

Review question / Objective: The aim of this systematic review is to compare Chinese herb Gynostemma pentaphyllum with no treatment, placebo, lipid-lowering agents, or other Chinese herbal products that containing red yeast rice extracts to evaluate effectiveness, safety and cost-effectiveness in people with dyslipidemia to inform clinical practice. To this end, the proposed systematic review will address the following question: Is Chinese herb Gynostemma pentaphyllum effective for dyslipidemia? Information sources: The PubMed, the Cochrane Library, EMBASE, Web of Science, China National Knowledge Infrastructure (CNKI), Chinese Scientific Journal Database (VIP), SinoMed, and Wanfang Data will be searched in January 2022. We also explored the World Health Organization International Clinical Trials Registry Platform (https://www.who.int/clinical-trials-registry-platform), ClinicalTrials.gov (www.clinicaltrials.gov/), and the Chinese Clinical Trial Registry (http://www.chictr.org.cn/index.aspx) for ongoing or unpublished trials to January 2022. Subject words or text words are determined based on published systematic reviews, clinical practice guidelines, ICD-10, ICD-11, MeSH terms, and Emtree. In addition, the reference lists of all identified studies will also be searched to find any relevant trials for inclusion.

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Margraf, Jürgen, Jan Christopher Cwik, Ruth von Brachel, Andrea Suppiger e Silvia Schneider. DIPS Open Access 1.2: Diagnostisches Interview bei psychischen Störungen. Ruhr-Universität Bochum (RUB), 2021. http://dx.doi.org/10.46586/rub.172.149.

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Das DIPS Open Access: Diagnostisches Interview bei psychischen Störungen 1.2 stellt die überarbeitete Version des DIPS Open Access dar. Es wurde für eine schnellere Durchführung gekürzt. Damit liegt das etablierte diagnostische Interview in seiner sechsten Auflage vor und steht für Praxis und Forschung weiterhin frei zur Verfügung. Mithilfe des DIPS Open Access 1.2 können Diagnosen psychischer Störungen nach DSM-5 und ICD-10 zuverlässig gestellt werden. Zudem können wichtige Informationen für die Planung und Durchführung psychotherapeutischer Interventionen strukturiert ermittelt werden. Der Interviewleitfaden des DIPS Open Access 1.2. leitet Interviewerinnen und Interviewer durch das diagnostische Gespräch. Im Anschluss an den Interviewleitfaden bietet das DIPS Open Access 1.2 die Möglichkeit einer umfassenden Dokumentation der allgemeinen Anamnese sowie der sozialen Beurteilung. Der ebenfalls enthaltene Protokollbogen ermöglicht schließlich die übersichtliche Dokumentation der erhobenen Symptomatik sowie eine detaillierte Zuordnung zu DSM-5-Kriterien.

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Brown, Yolanda, Twonia Goyer e Maragaret Harvey. Heart Failure 30-Day Readmission Frequency, Rates, and HF Classification. University of Tennessee Health Science Center, dicembre 2020. http://dx.doi.org/10.21007/con.dnp.2020.0002.

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30 Day Hospital Readmission Rates, Frequencies, and Heart Failure Classification for Patients with Heart Failure Background Congestive heart failure (CHF) is the leading cause of mortality, morbidity, and disability worldwide among patients. Both the incidence and the prevalence of heart failure are age dependent and are relatively common in individuals 40 years of age and older. CHF is one of the leading causes of inpatient hospitalization readmission in the United States, with readmission rates remaining above the 20% goal within 30 days. The Center for Medicare and Medicaid Services imposes a 3% reimbursement penalty for excessive readmissions including those who are readmitted within 30 days from prior hospitalization for heart failure. Hospitals risk losing millions of dollars due to poor performance. A reduction in CHF readmission rates not only improves healthcare system expenditures, but also patients’ mortality, morbidity, and quality of life. Purpose The purpose of this DNP project is to determine the 30-day hospital readmission rates, frequencies, and heart failure classification for patients with heart failure. Specific aims include comparing computed annual re-admission rates with national average, determine the number of multiple 30-day re-admissions, provide descriptive data for demographic variables, and correlate age and heart failure classification with the number of multiple re-admissions. Methods A retrospective chart review was used to collect hospital admission and study data. The setting occurred in an urban hospital in Memphis, TN. The study was reviewed by the UTHSC Internal Review Board and deemed exempt. The electronic medical records were queried from July 1, 2019 through December 31, 2019 for heart failure ICD-10 codes beginning with the prefix 150 and a report was generated. Data was cleaned such that each patient admitted had only one heart failure ICD-10 code. The total number of heart failure admissions was computed and compared to national average. Using age ranges 40-80, the number of patients re-admitted withing 30 days was computed and descriptive and inferential statistics were computed using Microsoft Excel and R. Results A total of 3524 patients were admitted for heart failure within the six-month time frame. Of those, 297 were re-admitted within 30 days for heart failure exacerbation (8.39%). An annual estimate was computed (16.86%), well below the national average (21%). Of those re-admitted within 30 days, 50 were re-admitted on multiple occasions sequentially, ranging from 2-8 re-admissions. The median age was 60 and 60% male. Due to the skewed distribution (most re-admitted twice), nonparametric statistics were used for correlation. While graphic display of charts suggested a trend for most multiple re-admissions due to diastolic dysfunction and least number due to systolic heart failure, there was no statistically significant correlation between age and number or multiple re-admissions (Spearman rank, p = 0.6208) or number of multiple re-admissions and heart failure classification (Kruskal Wallis, p =0.2553).

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ICD-10 versus ICD-11: the effects of PTSD diagnoses. ACAMH, luglio 2020. http://dx.doi.org/10.13056/acamh.12651.

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2018 saw PTSD symptoms being changed by the International Classification of Diseases. Now, data from a study recently published in the Journal of Child Psychology and Psychiatry have shed light on the clinical utility of these revisions in the ICD-11.

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Transitioning to ICD-10 (Updated). Project HOPE, aprile 2014. http://dx.doi.org/10.1377/hpb20140403.830190.

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Transitioning to ICD-10 (Updated). Project HOPE, giugno 2014. http://dx.doi.org/10.1377/hpb20140612.499016.

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9

How do the ICD-11, ICD-10 and DSM-5 diagnostic classifications of youth irritability and oppositionality compare? ACAMH, agosto 2020. http://dx.doi.org/10.13056/acamh.12681.

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Earlier this month, Spencer Evans and colleagues published data from their field study comparing the ICD-11 with ICD-10 and DSM-5 in terms of their classifications of irritability and oppositionality in youth.

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