Leveraging Clinical Informatics Tools to Extract Cumulative Anthracycline Exposure, Measure Cardiovascular Outcomes, and Assess Guideline Adherence for Children With Cancer

PURPOSE Cardiovascular disease is a significant cause of late morbidity and mortality in survivors of childhood cancer. Clinical informatics tools could enhance provider adherence to echocardiogram guidelines for early detection of late-onset cardiomyopathy. METHODS Cancer registry data were linked to electronic health record data. Structured query language facilitated the construction of anthracycline-exposed cohorts at a single institution. Primary outcomes included the data quality from automatic anthracycline extraction, sensitivity of International Classification of Disease coding for heart failure, and adherence to echocardiogram guideline recommendations. RESULTS The final analytic cohort included 385 pediatric oncology patients diagnosed between July 1, 2013, and December 31, 2018, among whom 194 were classified as no anthracycline exposure, 143 had low anthracycline exposure (< 250 mg/m2), and 48 had high anthracycline exposure (≥ 250 mg/m2). Manual review of anthracycline exposure was highly concordant (95%) with the automatic extraction. Among the unexposed group, 15% had an anthracycline administered at an outside institution not captured by standard query language coding. Manual review of echocardiogram parameters and clinic notes yielded a sensitivity of 75%, specificity of 98%, and positive predictive value of 68% for International Classification of Disease coding of heart failure. For patients with anthracycline exposure, 78.5% (n = 62) were adherent to guideline recommendations for echocardiogram surveillance. There were significant association with provider adherence and race and ethnicity ( P = .047), and 50% of patients with Spanish as their primary language were adherent compared with 90% of patients with English as their primary language ( P = .003). CONCLUSION Extraction of treatment exposures from the electronic health record through clinical informatics and integration with cancer registry data represents a feasible approach to assess cardiovascular disease outcomes and adherence to guideline recommendations for survivors.

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Surveillance for Healthcare-Associated Influenza-Like Illness in Pediatric Clinics: Validity of Diagnosis Codes for Case Identification

Infection Control and Hospital Epidemiology ◽

10.1017/ice.2016.147 ◽

2016 ◽

Vol 37 (10) ◽

pp. 1247-1250 ◽

Cited By ~ 3

Author(s):

Kristen A. Feemster ◽

Folasade M. Odeniyi ◽

Russell Localio ◽

Robert W. Grundmeier ◽

Susan E. Coffin ◽

...

Keyword(s):

Chart Review ◽

Health Record ◽

Diagnosis Code ◽

Predictive Values ◽

Influenza Like Illness ◽

Case Identification ◽

International Classification Of Disease ◽

Diagnosis Codes ◽

Healthcare Associated

Compared to chart review, a definition based on the International Classification of Disease, Ninth Revision, Clinical Modification (ICD-9-CM) diagnosis code for healthcare-associated influenza-like illness (HA-ILI) among young children in a large pediatric network demonstrated high positive and negative predictive values. This finding suggests that electronic health record–based definitions for surveillance can accurately identify medically attended outpatient HA-ILI cases for research and surveillance.Infect Control Hosp Epidemiol 2016;1–4

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Future Directions

The Oxford Handbook of Digital Technologies and Mental Health ◽

10.1093/oxfordhb/9780190218058.013.40 ◽

2020 ◽

pp. 476-479

Author(s):

Marc N. Potenza ◽

Kyle A. Faust ◽

David Faust

Keyword(s):

Technology Development ◽

Digital Technologies ◽

World Health ◽

International Classification Of Disease ◽

Levels Of Use ◽

Pornography Use ◽

Negative Impacts ◽

Mental Health Treatments ◽

The Many

As digital technology development continues to expand, both its positive and negative applications have also grown. As such, it is essential to continue gathering data on the many types of digital technologies, their overall effects, and their impact on public health. The World Health Organization’s inclusion of Gaming Disorder in the eleventh edition of the International Classification of Disease (ICD-11) indicates that some of the problematic effects of gaming are similar to those of substance-use disorders and gambling. Certain behaviors easily engaged in via the internet may also lead to compulsive levels of use in certain users, such as shopping or pornography use. In contrast, digital technologies can also lead to improvements in and wider accessibility to mental health treatments. Furthermore, various types of digital technologies can also lead to benefits such as increased productivity or social functioning. By more effectively understanding the impacts of all types of digital technologies, we can aim to maximize their benefits while minimizing or preventing their negative impacts.

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Neue Terminologie für Sprachentwicklungsstörungen?

Monatsschrift Kinderheilkunde ◽

10.1007/s00112-021-01148-2 ◽

2021 ◽

Author(s):

K. Neumann ◽

B. Arnold ◽

A. Baumann ◽

C. Bohr ◽

H. A. Euler ◽

...

Keyword(s):

International Classification Of Diseases ◽

International Classification ◽

International Classification Of Disease ◽

Diagnostik Und Therapie ◽

Classification Of Diseases ◽

Icd 10

Zusammenfassung Hintergrund Sprachtherapeutisch-linguistische Fachkreise empfehlen die Anpassung einer von einem internationalen Konsortium empfohlenen Änderung der Nomenklatur für Sprachstörungen im Kindesalter, insbesondere für Sprachentwicklungsstörungen (SES), auch für den deutschsprachigen Raum. Fragestellung Ist eine solche Änderung in der Terminologie aus ärztlicher und psychologischer Sicht sinnvoll? Material und Methode Kritische Abwägung der Argumente für und gegen eine Nomenklaturänderung aus medizinischer und psychologischer Sicht eines Fachgesellschaften- und Leitliniengremiums. Ergebnisse Die ICD-10-GM (Internationale statistische Klassifikation der Krankheiten und verwandter Gesundheitsprobleme, 10. Revision, German Modification) und eine S2k-Leitlinie unterteilen SES in umschriebene SES (USES) und SES assoziiert mit anderen Erkrankungen (Komorbiditäten). Die USES- wie auch die künftige SES-Definition der ICD-11 (International Classification of Diseases 11th Revision) fordern den Ausschluss von Sinnesbehinderungen, neurologischen Erkrankungen und einer bedeutsamen intellektuellen Einschränkung. Diese Definition erscheint weit genug, um leichtere nonverbale Einschränkungen einzuschließen, birgt nicht die Gefahr, Kindern Sprach- und weitere Therapien vorzuenthalten und erkennt das ICD(International Classification of Disease)-Kriterium, nach dem der Sprachentwicklungsstand eines Kindes bedeutsam unter der Altersnorm und unterhalb des seinem Intelligenzalter angemessenen Niveaus liegen soll, an. Die intendierte Ersetzung des Komorbiditäten-Begriffs durch verursachende Faktoren, Risikofaktoren und Begleiterscheinungen könnte die Unterlassung einer dezidierten medizinischen Differenzialdiagnostik bedeuten. Schlussfolgerungen Die vorgeschlagene Terminologie birgt die Gefahr, ätiologisch bedeutsame Klassifikationen und differenzialdiagnostische Grenzen zu verwischen und auf wertvolles ärztliches und psychologisches Fachwissen in Diagnostik und Therapie sprachlicher Störungen im Kindesalter zu verzichten.

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Lack of accuracy of the international classification of disease, ninth (ICD-9) codes in identifying patients with encephalitis

Journal of Neurology ◽

10.1007/s00415-019-09229-9 ◽

2019 ◽

Vol 266 (4) ◽

pp. 1034-1035 ◽

Cited By ~ 2

Author(s):

Mohammed Samannodi ◽

Michael Hansen ◽

Rodrigo Hasbun

Keyword(s):

International Classification ◽

International Classification Of Disease

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The International Classification of Disease Critical Care Severity Score Demonstrates that Pediatric Burden of Injury is Similar to that of Adults: Validation Using the National Trauma Databank

Journal of Pediatric Surgery ◽

10.1016/j.jpedsurg.2021.05.013 ◽

2021 ◽

Author(s):

Christopher W. Snyder ◽

Tara M. Barry ◽

David J. Ciesla ◽

Keith Thatch ◽

Nicholas Poulos ◽

...

Keyword(s):

Critical Care ◽

Severity Score ◽

International Classification ◽

International Classification Of Disease ◽

National Trauma

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Is Cauda Equina Syndrome Being Treated Within the Recommended Time Frame?

Neurosurgery ◽

10.1227/neu.0b013e31820cd426 ◽

2011 ◽

Vol 68 (6) ◽

pp. 1520-1526 ◽

Cited By ~ 19

Author(s):

Robert T. Arrigo ◽

Paul Kalanithi ◽

Maxwell Boakye

Keyword(s):

Cauda Equina Syndrome ◽

Medical Condition ◽

Cauda Equina ◽

Time Frame ◽

Current Guideline ◽

International Classification Of Disease ◽

Lumbar Disk ◽

Urgent Surgery ◽

Spine Surgeon

Abstract BACKGROUND: Cauda equina syndrome (CES) is a rare but devastating medical condition requiring urgent surgery to halt or reverse neurological compromise. Controversy exists as to how soon surgery must be performed after diagnosis, and clinical and medicolegal factors make this question highly relevant to the spine surgeon. It is unclear from the literature how often CES patients are treated within the recommended time frame. OBJECTIVE: To determine whether CES patients are being treated in compliance with the current guideline of surgery within 48 hours and to assess incidence, demography, comorbidities, and outcome measures of CES patients. METHODS: We searched the 2003 to 2006 California State Inpatient Databases to identify degenerative lumbar disk disorder patients surgically treated for CES. An International Classification of Disease, ninth revision, clinical modification, diagnosis code was used to identify CES patients with advanced disease. RESULTS: The majority (88.74%) of California's CES patients received surgery within the recommended 48-hour window after diagnosis. The incidence of CES in surgically treated degenerative lumbar disk patients was 1.51% with an average of 397 cases per year in California. CES patients had worse outcomes and used more healthcare resources than other surgically treated degenerative lumbar disk patients; this disparity was more pronounced for patients with advanced CES. CES patients treated after 48 hours had 3 times the odds of a nonroutine discharge as patients treated within 48 hours (odds ratio = 3.082; P < .001). CONCLUSION: In California, patients are being treated within the recommended 48-hour time frame.

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Risk Adjustment in Outcome Assessment: the Charlson Comorbidity Index

Methods of Information in Medicine ◽

10.1055/s-0038-1634956 ◽

1993 ◽

Vol 32 (05) ◽

pp. 382-387 ◽

Cited By ~ 324

Author(s):

C. Sicotte ◽

C. Tilquin ◽

W. D’Hoore

Keyword(s):

Risk Adjustment ◽

Predictive Accuracy ◽

Charlson Index ◽

Administrative Databases ◽

Receiver Operating Curve ◽

Multiple Logistic Regression ◽

Principal Diagnosis ◽

International Classification Of Disease ◽

Comorbidity Index

AbstractTo measure the burden of comorbid diseases using the MED-ECHO database (Quebec), the so-called Charlson index was adapted to International Classification of Disease (ICD-9) codes. The resulting comorbidity index was applied to the study of inpatient death in a group of 62,456 patients having one of the following conditions: ischemic heart disease, congestive heart failure, stroke, or bacterial pneumonia. Multiple logistic regression was used to relate inpatient death to its predictors, including gender, principal diagnosis, age, and the comorbidity index. Various transformations of the comorbidity score were performed, and their effect on predictive accuracy was assessed. The comorbidity index was constantly and strongly associated with death. When gender, age, comorbidity and the principal diagnoses were taken into account, the area under the receiver-operating curve was 0.83. Therefore, the Charlson Index is a useful approach to risk adjustment in outcomes research from administrative databases.

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Algorithm to detect pediatric provider attention to high BMI and associated medical risk

Journal of the American Medical Informatics Association ◽

10.1093/jamia/ocy126 ◽

2018 ◽

Vol 26 (1) ◽

pp. 55-60 ◽

Cited By ~ 2

Author(s):

Christy B Turer ◽

Celette S Skinner ◽

Sarah E Barlow

Keyword(s):

Body Mass Index ◽

Electronic Health Record ◽

Chart Review ◽

Health Record ◽

Medical Risk ◽

Practice Behaviors ◽

Diagnosis Codes ◽

Manual Review ◽

Clinician Practice ◽

High Bmi

Abstract We developed and validated an algorithm that uses combinations of extractable electronic-health-record (EHR) indicators (diagnosis codes, orders for laboratories, medications, and referrals) that denote widely-recommended clinician practice behaviors: attention to overweight/obesity/body mass index alone (BMI Alone), with attention to hypertension/other comorbidities (BMI/Medical Risk), or neither (No Attention). Data inputs used for each EHR indicator were refined through iterative chart review to identify and resolve modifiable coding errors. Validation was performed through manual review of randomly selected visit encounters (n = 308) coded by the refined algorithm. Of 104 encounters coded as No Attention, 89.4% lacked any evidence (specificity) of attention to BMI/Medical Risk. Corresponding evidence (sensitivity) of attention to BMI Alone was identified in 96.0% (of 101 encounters coded as BMI Alone) and BMI/Medical Risk in 96.1% (of 103 encounters coded as BMI/Medical Risk). Our EHR data algorithm can validly determine provider attention to BMI alone, with Medical Risk, or neither.

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