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Published in Demissie Alemayehu, Birol Emir, Michael Gaffney, Interface between Regulation and Statistics in Drug Development, 2020
Demissie Alemayehu, Birol Emir, Michael Gaffney
In addition to the methodological issues discussed above, effective use of data from observational studies requires addressing important operational challenges. Since healthcare data may come from different sources, including electronic health records (EHRs) and claims databases, they typically require special provisions for data storage, computing environment, data standards, and protection of privacy and confidentiality (Alemayehu and Mardekian 2011). Depending on the sources, different nomenclatures, coding conventions, and units are often used for medical terms. Since data collection is not performed for the purpose of research, data entry errors are common, often leading to such issues as miss-classification, missing values, and outliers. In addition, most of the available data may be unstructured. As a result, concerted efforts are required by various stakeholders to establish a framework for the harmonization of healthcare data. Recent activities in this regard include increased use of the International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) to code and classify diagnoses from inpatient and outpatient records. The National Drug Code (NDC) scheme, which is maintained by the US Food and Drug Administration (FDA), is another tool for coding prescription drugs and insulin products. In addition, some initiatives are underway in the US to harmonize data collection across states (Porter et al. 2015).
Evaluation of Status and Progression of HIV Disease: Use of a Computerized Medical Module
Published in G. J. Huba, Lisa A. Melchior, Vivian B. Brown, Trudy A. Larson, A. T. Panter, Evaluating HIV/AIDS Treatment Programs: Innovative Methods and Findings, 2020
Robert L. Brunner, Trudy A. Larson, G. J. Huba, Lisa A. Melchior, Barbara J. Scott
Many diseases or conditions not specifically offered as options in the data entry software were reported in clinical notes during visits. These were entered using ICD-9 codes and are shown in Table 3. The most frequently reported of these medical problems was numbness (which also included peripheral neuropathy when specified), stiff neck, diarrhea < 1 month, chills and shortness of breath. Reported conditions mix both non-specific complaints with more HIV-related issues and other chronic conditions. The presence of neuropathy (if defined as numbness) in 50% of patients contrasts with diagnosis of peripheral neuropathy (10.5%) as a stand alone diagnosis (Table 1) and more accurately reflects the morbidity experienced by the patient. In another comparison, chronic pain per se was identified in the clinic note and was therefore entered as a specific common condition (using the multiple choice option) for four patients. In contrast, limb and abdominal pain, not specifically identified as chronic in the clinic note but perhaps experienced as episodic, was reported by a total of 11 patients and was entered using the ICD-9 codes. This example highlights the usefulness of using specific ICD-9 coding in identifying issues that need to be addressed with patients on a more frequent basis.
The Disillusioned Physician and the Electronic Medical Record
Published in George Mayzell, The Resilient Healthcare Organization, 2020
The ICD 10 code set (International Classification of Diseases) which was recently adopted, has nearly 68,000 codes.15 It was meant to capture detailed patient specific diagnoses. Unfortunately, there are so many codes that the only way to deal with it is through electronic means. There are two major technical problems. The first is that there are so many codes that are superfluous and don’t really add any value. These include codes such as:16T Z63.1 – Problems in relationship with in-laws.W61.43 – Pecked by a turkey.W22.02 – Walked into lamppost.W97.33 – Sucked into a jet engine.
Hypertension burden, treatment, and control among people with HIV at a clinical care center in the Southeastern US, 2014–2019
Published in AIDS Care, 2023
Molly Remch, Nora Franceschini, Thibaut Davy-Mendez, Michelle Floris-Moore, Sonia Napravnik
Prevalent hypertension was defined as meeting the study definition of clinical hypertension or elevated blood pressure prior to or within 90 days of baseline (1 April 2014 or initiation of HIV care at UNC, whichever occurred later). Clinical hypertension was defined using the International Classification of Diseases (ICD)−9 codes 401.0-401.9 or ICD-10 code I10. Elevated blood pressure was defined as three consecutive ambulatory (i.e., non-hospitalized) blood pressure measurements ≥140/90 mmHg. This threshold is consistent with the Joint National Commission on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure (JNC) 7 definition of hypertension and the threshold at which medication treatment initiation is recommended in the JNC 8 (Chobanian et al., 2003; James et al., 2015). Incident hypertension was defined as having a new clinical diagnosis or having three consecutive ambulatory elevated blood pressure measurements (≥140/90 mmHg) at least 90 days after baseline. For patients with three elevated blood pressure measurements, we used the date of the third measurement as the event date to reflect clinical practice. We examined antihypertensive medications by class: angiotensin converting enzyme inhibitors (ACEIs) or angiotensin receptor blockers (ARBs), diuretics, calcium channel blockers, β-blocker, alpha blockers, central alpha agonists, or vasodilators.
The most common comorbidities in patients with Ehlers-Danlos syndrome: a 15-year nationwide population-based cohort study
Published in Disability and Rehabilitation, 2022
Julie Leganger, Siv Fonnes, M. L. Kulas Søborg, Jacob Rosenberg, Jakob Burcharth
We defined comorbidity as any disease or disorder coexisting with a diagnosis of EDS. Since EDS is genetically inherited, we defined that it was irrelevant whether the comorbidity occurred before or after the time of the EDS diagnosis. Hospital admissions, emergency department, and outpatient contacts were used to identify the most frequently occurring primary or secondary ICD-10 codes in the patients with EDS during the study period. The patients with EDS were excluded from contributing to a unique ICD-10 code more than once. We included the ICD-10 codes that more than 25 patients had been assigned during the study period. This resulted in a list of 211 unique ICD-10 codes. 69 of these codes were excluded from further analysis because the ICD-codes were unspecific and did not correspond to a disease or a disorder (e.g., codes for observation, examination, and screening or codes for a normal state of health e.g., normal birth or normal pregnancy), see Supplemental Material 1. Of the included 142 ICD-10 codes, the most frequent were used to form disease categories. These categories were expanded beyond the unique ICD-10 code. The disease categories were based on validated ICD-10 code algorithms [18,19] or meaningful ICD-10 code algorithms [17,20], see Supplemental Material 2. The most frequent remaining ICD-10 codes, that did not fit into a meaningful disease category, were listed according to involved the organ system.
Risk of developing major depressive disorder in polycystic ovary syndrome: a retrospective cohort study
Published in Journal of Obstetrics and Gynaecology, 2021
In Ok Lee, Jung Chul Kim, Jong Wook Seo, Hae Yong Pak, Jae Eun Chung
Instituted in 2005, the Korean National Health Insurance Claims Database contains comprehensive data regarding patients’ diagnostic codes in International Classification of Diseases (ICD-10 code), procedures undertaken (including major and minor operations), prescribed medications, and reimbursed medical costs in both outpatient and hospital admission settings. The ICD-10 codes were registered by the clinician who treated the patient through the electronic medical record system. The Korean National Health Information Database comprises a patient’s body mass index (BMI), blood pressure, cholesterol, fasting blood sugar, haemoglobin, triglycerides, smoking habits, socio-economic status, and residential area at the time of his or her biennial health check-up. These data sets are managed and publicly released by the National Health Insurance Corporation for research purposes, and the patient’s confidentiality is maintained accordingly. No patient healthcare records are duplicated because all Korean residents receive a unique identification number (Seong et al. 2017; Seong et al. 2017).