scholarly journals Disagreement of ICD-10 Codes Between a Local Hospital Information System and a Cancer Registry

2015 ◽  
Vol 16 (1) ◽  
pp. 259-263 ◽  
Author(s):  
Hutcha Sriplung ◽  
Tirada Kantipundee ◽  
Cheamjit Tassanapitak
Keyword(s):  
Information System ◽  
Cancer Registry ◽  
Hospital Information System ◽  
Local Hospital ◽  
Icd 10

Automatisierte Berechnung und Visualisierung von Komorbiditätsindizes für den Tumorboard-Entscheid

2020 ◽  
Vol 41 (08) ◽  
pp. 536-541
Author(s):  
Theresa Wald ◽  
Klemens Birnbaum ◽  
Susanne Wiegand ◽  
Andreas Dietz ◽  
Veit Zebralla ◽  
...  
Keyword(s):  
Information System ◽  
Record Linkage ◽  
Hospital Information System ◽  
Icd 10 ◽  
Kurative Therapie

Zusammenfassung Einleitung Komorbidität beeinflusst die für die kurative Therapie von Kopf-Hals-Karzinomen (HNC) verfügbaren Optionen. Das manuelle Zusammentragen der Nebenerkrankungen vor der Anmeldung im interdisziplinären Tumorboard (TB) ist zeitintensiv und oft unvollständig. Eine automatisierte Erfassung von nach ICD-10 kodierten Komorbiditätsdaten und deren Darstellung könnte die therapeutische Entscheidungsfindung im TB verbessern sowie bestehenden Informationsbedarf aufzeigen. Material und Methoden Die ICD-10-Codes unserer Patienten wurden aus 4 Datenbanken (hospital-information-system (HIS*-MED), der klinikinternen Tumordatenbank, OncoFlow® und OncoFunction®) extrahiert. Nach der Datensatzverknüpfung mittels der Python-Programmbibliotheken Pandas und Record Linkage wurden die ICD-10-Codes bezüglich des Charlson-Scores gewichtet und für die Implementierung in OncoFlow visualisiert. Die Kodierqualität wurde am Beispiel Diabetes an einer 1:1 gematchten Stichprobe von 240 Patienten überprüft. Ergebnisse 29 073 ICD-10-Codes von 2087 Patienten mit HNC wurden extrahiert. Die Anmeldung eines Patienten im TB triggert die sofortige automatische Erfassung und Visualisierung der Daten als Piktogramm in OncoFlow. Dies ermöglicht die schnelle Erfassung und Bewertung der Komorbidität sowie erforderlicher Diagnostik zur Komplettierung der Daten. Die klinikinterne Validationsstudie ergab eine Präzision der durch Datenimport verfügbaren Information zu Diabetes von 95,0 %. Diskussion Patienten mit HNC weisen häufig für die Therapieentscheidung relevante Nebenerkrankungen auf. Die automatisierte Erfassung der Komorbidität aus administrativen Daten und deren intuitive Darstellung ist ressourcen- und kostengünstig möglich. Voraussetzung ist eine präzise, vollständige Verschlüsselung der Krankheitsdiagnosen.

scholarly journals Recovering records on cancer of the larynx from anonymous health information databases

2021 ◽  
Vol 24 ◽  
Author(s):  
Fernando Timoteo Fernandes ◽  
Diego Rodrigues Mendonça e Silva ◽  
Felipe Campos ◽  
Vilma Sousa Santana ◽  
Lucas Cuani ◽  
...  
Keyword(s):  
Information System ◽  
Health Information ◽  
Hospital Information System ◽  
Causes Of Death ◽  
National Health System ◽  
Hospital Records ◽  
Cancer Statistics ◽  
Linkage Algorithm ◽  
Sociodemographic Data ◽  
Icd 10

ABSTRACT: Objective: To develop a linkage algorithm to match anonymous death records of cancer of the larynx (ICD-10 C32X), retrieved from the Mortality Information System (SIM) and the Hospital Information System of the Brazilian Unified National Health System (SIH-SUS) in Brazil. Methodology: Death records containing ICD-10 C32X codes were retrieved from SIM and SIH-SUS, limited to individuals aged 30 years and over, between 2002 and 2012, in the state of São Paulo. The databases were linked using a unique key identifier developed with sociodemographic data shared by both systems. Linkage performance was ascertained by applying the same procedure to similar non-anonymous databases. True pairs were those having the same identification variables. Results: A total of 14,311 eligible death records were found. Most records, 10,674 (74.6%), were exclusive to SIM. Only 1,853 (12.9%) deaths were registered in both systems, representing true pairs. A total of 1,784 (12.5%) cases of laryngeal cancer in the SIH-SUS database were tracked in SIM with different causes of death. The linkage failed to match 167 (9.4%) records due to inconsistencies in the key identifier. Conclusion: The authors found that linking anonymous data from mortality and hospital records is a feasible measure to track missing records and may improve cancer statistics.

Automatisierte Berechnung und Visualisierung von Komorbiditätsindizes für den Tumorboard-Entscheid

2019 ◽  
Vol 99 (01) ◽  
pp. 31-36
Author(s):  
Theresa Wald ◽  
Klemens Birnbaum ◽  
Susanne Wiegand ◽  
Andreas Dietz ◽  
Veit Zebralla ◽  
...  
Keyword(s):  
Information System ◽  
Record Linkage ◽  
Hospital Information System ◽  
Icd 10 ◽  
Kurative Therapie

Zusammenfassung Einleitung Komorbidität beeinflusst die für die kurative Therapie von Kopf-Hals-Karzinomen (HNC) verfügbaren Optionen. Das manuelle Zusammentragen der Nebenerkrankungen vor der Anmeldung im interdisziplinären Tumorboard (TB) ist zeitintensiv und oft unvollständig. Eine automatisierte Erfassung von nach ICD-10 kodierten Komorbiditätsdaten und deren Darstellung könnte die therapeutische Entscheidungsfindung im TB verbessern sowie bestehenden Informationsbedarf aufzeigen. Material und Methoden Die ICD-10-Codes unserer Patienten wurden aus 4 Datenbanken (hospital-information-system (HIS*-MED), der klinikinternen Tumordatenbank, OncoFlow® und OncoFunction®) extrahiert. Nach der Datensatzverknüpfung mittels der Python-Programmbibliotheken Pandas und Record Linkage wurden die ICD-10-Codes bezüglich des Charlson-Scores gewichtet und für die Implementierung in OncoFlow visualisiert. Die Kodierqualität wurde am Beispiel Diabetes an einer 1:1 gematchten Stichprobe von 240 Patienten überprüft. Ergebnisse 29 073 ICD-10-Codes von 2087 Patienten mit HNC wurden extrahiert. Die Anmeldung eines Patienten im TB triggert die sofortige automatische Erfassung und Visualisierung der Daten als Piktogramm in OncoFlow. Dies ermöglicht die schnelle Erfassung und Bewertung der Komorbidität sowie erforderlicher Diagnostik zur Komplettierung der Daten. Die klinikinterne Validationsstudie ergab eine Präzision der durch Datenimport verfügbaren Information zu Diabetes von 95,0 %. Diskussion Patienten mit HNC weisen häufig für die Therapieentscheidung relevante Nebenerkrankungen auf. Die automatisierte Erfassung der Komorbidität aus administrativen Daten und deren intuitive Darstellung ist ressourcen- und kostengünstig möglich. Voraussetzung ist eine präzise, vollständige Verschlüsselung der Krankheitsdiagnosen.

scholarly journals Health Care Workers’ Use Of Electronic Hospital Information System And Their Computer Literacy At The Outpatient Department In District General Hospital Trincomalee In Sri Lanka

2016 ◽  
Vol 2 (1) ◽  
pp. 20-29
Author(s):  
Ayanthi Saranga Jayawardena ◽  
S.C. Wickramasinghe ◽  
S.R.U. Wimalaratne
Keyword(s):  
Health Care ◽  
Information System ◽  
Health Care Workers ◽  
Hospital Information System ◽  
Computer Literacy ◽  
District General Hospital ◽  
Staff Members ◽  
Care Workers ◽  
Icd 10 ◽  
Electronic Hospital

AbstractObjectives:To describe the use of Electronic Hospital Information System(EHIS) by the staff, to assess the competency of them to handle the EHIS and to assess the computer literacy among health care workers at the Out Patient’s Department(OPD) in District General Hospital(DGH) Trincomalee.Study design:A cross sectional descriptive study. A competency assessment test and a self administered questionnaire were used. Participants: All the staff members operating the EHIS at the OPD in DGH Trincomalee. Results: Regarding the general use of the EHIS medical officers (100%) used the EHIS to write prescriptions,(>70%)to get the patient’s socio-demographic details, enter patient’s history to retrieve previous medical records, to obtain what drugs available and what drugs out of stock at the outdoor pharmacy, for notification of diseases and used less frequently to get the laboratory reports (50-70%). The system was used for 17 tasks out of 20 tasks and most unused tasks were write the diagnosis according to the ICD-10. Nurses and attendents used the system less than half of the tasks for which the system was functional. The pharmacists use of the system was optimal. Overall respondents’ competency of using the system were high (>80%). Conclusions: Majority of staff members had low level of computer literacy. Majority of them used the system successfully. Recommendations: To strengthen the training program,combat several constraints and upgrade the system, provide digital X-ray imaging and download them to CDs and improved to write the diagnosis according to the ICD-10.Key words: Electronic Hospital Information System, Multi Disease Surveillance, Computer Literacy. 

The Karolinska Hospital Information System

1974 ◽  
Vol 13 (03) ◽  
pp. 125-140 ◽  
Author(s):  
Ch. Mellner ◽  
H. Selajstder ◽  
J. Wolodakski
Keyword(s):  
Information System ◽  
Data Processing ◽  
Data Base ◽  
Hospital Information System ◽  
Care Delivery ◽  
Traditional Approach ◽  
Processing System ◽  
Systems Design ◽  
Data Processing System ◽  
Karolinska Hospital

The paper gives a report on the Karolinska Hospital Information System in three parts.In part I, the information problems in health care delivery are discussed and the approach to systems design at the Karolinska Hospital is reported, contrasted, with the traditional approach.In part II, the data base and the data processing system, named T1—J 5, are described.In part III, the applications of the data base and the data processing system are illustrated by a broad description of the contents and rise of the patient data base at the Karolinska Hospital.

A Computer-based Clinical Information System

1987 ◽  
Vol 26 (04) ◽  
pp. 189-194
Author(s):  
S. S. El-Gamal
Keyword(s):  
Information System ◽  
Hospital Information System ◽  
Clinical Information System ◽  
Research Work ◽  
Clinical Information ◽  
Hospital Staff ◽  
Vital Role ◽  
Daily Routine ◽  
Specialized Hospital ◽  
Computer Based

SummaryModern information technology offers new opportunities for the storage and manipulation of hospital information. A computer-based hospital information system, dedicated to urology and nephrology, was designed and developed in our center. It involves in principle the employment of a program that allows the analysis of non-restricted, non-codified texts for the retrieval and processing of clinical data and its operation by non-computer-specialized hospital staff.This Hospital Information System now plays a vital role in the efficient provision of a good quality service and is used in daily routine and research work in this hospital. This paper describes this specialized Hospital Information System.

scholarly journals Variable clinical characteristics and laboratory results in five patients with Chinese Good's syndrome (thymoma and hypogammaglobulinemia): an 8-year retrospective analysis in a university hospital in China

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Jinyao Ni ◽  
Junwu Zhang ◽  
Yanxia Chen ◽  
Weizhong Wang ◽  
Jinlin Liu
Keyword(s):  
Information System ◽  
Lichen Planus ◽  
Hospital Information System ◽  
Clinical Characteristics ◽  
Opportunistic Infections ◽  
Clinical Symptoms ◽  
University Hospital ◽  
Ivig Treatment ◽  
Good’S Syndrome ◽  
Laboratory Results

Abstract Background Good's syndrome (GS) is a rare secondary immunodeficiency disease presenting as thymoma and hypogammaglobulinemia. Due to its rarity, the diagnosis of GS is often missed. Methods We used the hospital information system to retrospectively screen thymoma and hypogammaglobulinemia patients at the First Affiliated Hospital of Wenzhou Medical University from Apr 2012 to Apr 2020. The clinical, laboratory, treatment, and outcome data for these patients were collected and analyzed. Results Among the 181 screened thymoma patients, 5 thymoma patients with hypogammaglobulinemia were identified; 3 patients had confirmed diagnoses of GS, and the other 2 did not have a diagnosis of GS recorded in the hospital information system. A retrospective review of the clinical characteristics, laboratory results, and follow-up data for these 2 undiagnosed patients confirmed the diagnosis of GS. All 5 GS patients presented with pneumonia, 2 patients presented with recurrent skin abscesses, 2 patients presented with recurrent cough and expectoration, 1 patient presented with recurrent oral lichen planus and diarrhea, and 1 patient presented with tuberculosis and granulomatous epididymitis. In the years after the diagnosis of hypogammaglobulinemia with mild symptoms, all 5 patients had received irregular intravenous immunoglobulin (IVIG) treatment. As the course of the disease progressed, the clinical symptoms of all patients worsened, but the symptoms were partly resolved with IVIG in these patients. However, 4 patients died due to comorbidities. Conclusion GS should be investigated as a possible diagnosis in thymoma patients who present with hypogammaglobulinemia, especially those with recurrent opportunistic infections, recurrent skin abscesses, chronic diarrhea, or recurrent lichen planus.

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