Validity of Death Certificate and Hospital Discharge ICD Codes for Dementia Diagnosis: The Multi-Ethnic Study of Atherosclerosis.
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ABSTRACT:
SUBMITTER: Fujiyoshi A
PROVIDER: S-EPMC5418097 | biostudies-literature | 2017 Apr-Jun
REPOSITORIES: biostudies-literature
Publications
Validity of Death Certificate and Hospital Discharge ICD Codes for Dementia Diagnosis: The Multi-Ethnic Study of Atherosclerosis.
Fujiyoshi Akira A Jacobs David R DR Alonso Alvaro A Luchsinger José A JA Rapp Stephen R SR Duprez Daniel A DA
Alzheimer disease and associated disorders 20170401 2
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Project description:Background and purposeCharacterizing International Classification of Disease 9th Revision, Clinical Modification (ICD-9-CM) code validity is essential given widespread use of hospital discharge databases in research. Using the Atherosclerosis Risk in Communities (ARIC) Study, we estimated the accuracy of ICD-9-CM stroke codes.MethodsHospitalizations with ICD-9-CM codes 430 to 438 or stroke keywords in the discharge summary were abstracted for ARIC cohort members (1987-2010). A computer algorithm and physician reviewer classified definite and probable ischemic stroke, intracerebral hemorrhage, and subarachnoid hemorrhage. Using ARIC classification as a gold standard, we calculated the positive predictive value (PPV) and sensitivity of ICD-9-CM codes grouped according to the American Heart Association/American Stroke Association (AHA/ASA) 2013 categories and an alternative code grouping for comparison.ResultsThirty-three percent of 4260 hospitalizations were validated as strokes (1251 ischemic, 120 intracerebral hemorrhage, 46 subarachnoid hemorrhage). The AHA/ASA code groups had PPV 76% and 68% sensitivity compared with PPV 72% and 83% sensitivity for the alternative code groups. The PPV of the AHA/ASA code group for ischemic stroke was slightly higher among blacks, individuals <65 years, and at teaching hospitals. Sensitivity was higher among older individuals and increased over time. The PPV of the AHA/ASA code group for intracerebral hemorrhage was higher among blacks, women, and younger individuals. PPV and sensitivity varied across study sites.ConclusionsA new AHA/ASA discharge code grouping to identify stroke had similar PPV and lower sensitivity compared with an alternative code grouping. Accuracy varied by patient characteristics and study sites.
| S-EPMC4290877 | biostudies-literature
Project description:BACKGROUND: Administrative data are widely used to study health systems and make important health policy decisions. Yet little is known about the influence of coder characteristics on administrative data validity in these studies. Our goal was to describe the relationship between several measures of validity in coded hospital discharge data and 1) coders' volume of coding (> or = 13,000 vs. <13,000 records), 2) coders' employment status (full- vs. part-time), and 3) hospital type. METHODS: This descriptive study examined 6 indicators of face validity in ICD-10 coded discharge records from 4 hospitals in Calgary, Canada between April 2002 and March 2007. Specifically, mean number of coded diagnoses, procedures, complications, Z-codes, and codes ending in 8 or 9 were compared by coding volume and employment status, as well as hospital type. The mean number of diagnoses was also compared across coder characteristics for 6 major conditions of varying complexity. Next, kappa statistics were computed to assess agreement between discharge data and linked chart data reabstracted by nursing chart reviewers. Kappas were compared across coder characteristics. RESULTS: 422,618 discharge records were coded by 59 coders during the study period. The mean number of diagnoses per record decreased from 5.2 in 2002/2003 to 3.9 in 2006/2007, while the number of records coded annually increased from 69,613 to 102,842. Coders at the tertiary hospital coded the most diagnoses (5.0 compared with 3.9 and 3.8 at other sites). There was no variation by coder or site characteristics for any other face validity indicator. The mean number of diagnoses increased from 1.5 to 7.9 with increasing complexity of the major diagnosis, but did not vary with coder characteristics. Agreement (kappa) between coded data and chart review did not show any consistent pattern with respect to coder characteristics. CONCLUSIONS: This large study suggests that coder characteristics do not influence the validity of hospital discharge data. Other jurisdictions might benefit from implementing similar employment programs to ours, e.g.: a requirement for a 2-year college training program, a single management structure across sites, and rotation of coders between sites. Limitations include few coder characteristics available for study due to privacy concerns.
| S-EPMC2868845 | biostudies-other
Project description:ObjectiveTo assess if the Agency for Healthcare Research and Quality patient safety indictors (PSIs) could be used for case findings in the International Classification of Disease 10th revision (ICD-10) hospital discharge abstract data.DesignWe identified and randomly selected 490 patients with a foreign body left during a procedure (PSI 5-foreign body), selected infections (IV site) due to medical care (PSI 7-infection), postoperative pulmonary embolism (PE) or deep vein thrombosis (DVT; PSI 12-PE/DVT), postoperative sepsis (PSI 13-sepsis)and accidental puncture or laceration (PSI 15-laceration) among patients discharged from three adult acute care hospitals in Calgary, Canada in 2007 and 2008. Their charts were reviewed for determining the presence of PSIs and used as the reference standard, positive predictive value (PPV) statistics were calculated to determine the proportion of positives in the administrative data representing 'true positives'.ResultsThe PPV for PSI 5-foreign body was 62.5% (95% CI 35.4% to 84.8%), PSI 7-infection was 79.1% (67.4% to 88.1%), PSI 12-PE/DVT was 89.5% (66.9% to 98.7%), PSI 13-sepsis was 12.5% (1.6% to 38.4%) and PSI 15-laceration was 86.4% (75.0% to 94.0%) after excluding those who presented to the hospital with the condition.ConclusionsSeveral PSIs had high PPV in the ICD administrative data and are thus powerful tools for true positive case finding. The tools could be used to identify potential cases from the large volume of admissions for verification through chart reviews. In contrast, their sensitivity has not been well characterised and users of PSIs should be cautious if using them for 'quality of care reporting' presenting the rate of PSIs because under-coded data would generate falsely low PSI rates.
| S-EPMC3796280 | biostudies-literature
Project description:BackgroundHospitalization due to dengue illness is an important measure of dengue morbidity. However, limited studies are based on administrative database because the validity of the diagnosis codes is unknown. We validated the International Classification of Diseases, 10th revision (ICD) diagnosis coding for dengue infections in the Malaysian Ministry of Health's (MOH) hospital discharge database.MethodsThis validation study involves retrospective review of available hospital discharge records and hand-search medical records for years 2010 and 2013. We randomly selected 3219 hospital discharge records coded with dengue and non-dengue infections as their discharge diagnoses from the national hospital discharge database. We then randomly sampled 216 and 144 records for patients with and without codes for dengue respectively, in keeping with their relative frequency in the MOH database, for chart review. The ICD codes for dengue were validated against lab-based diagnostic standard (NS1 or IgM).ResultsThe ICD-10-CM codes for dengue had a sensitivity of 94%, modest specificity of 83%, positive predictive value of 87% and negative predictive value 92%. These results were stable between 2010 and 2013. However, its specificity decreased substantially when patients manifested with bleeding or low platelet count.ConclusionThe diagnostic performance of the ICD codes for dengue in the MOH's hospital discharge database is adequate for use in health services research on dengue.
| S-EPMC5910617 | biostudies-literature
Project description:BackgroundDischarge diagnoses are used to track national trends and patterns of maternal morbidity. There are few data regarding the validity of the International Classification of Diseases (ICD) codes used for this purpose. The goal of our study was to try to better understand the validity of administrative data being used to monitor and assess trends in morbidity.MethodsHospital stay billing records were queried to identify all delivery admissions at the Massachusetts General Hospital for the time period 2001 to 2011 and the University of Michigan Health System for the time period 2005 to 2011. From this, we identified patients with ICD-9-Clinical Modification (CM) diagnosis and procedure codes indicative of severe maternal morbidity. Each patient was classified with 1 of 18 different medical/obstetric categories (conditions or procedures) based on the ICD-9-CM code that was recorded. Within each category, 20 patients from each institution were selected at random, and the corresponding medical charts were reviewed to determine whether the ICD-9-CM code was assigned correctly. The percentage of correct codes for each of 18 preselected clinical categories was calculated yielding a positive predictive value (PPV) and 99% confidence interval (CI).ResultsThe overall number of correctly assigned ICD-9-CM codes, or PPV, was 218 of 255 (86%; CI, 79%-90%) and 154 of 188 (82%; CI, 74%-88%) at Massachusetts General Hospital and University of Michigan Health System, respectively (combined PPV, 372/443 [84%; CI, 79-88%]). Codes within 4 categories (Hysterectomy, Pulmonary edema, Disorders of fluid, electrolyte and acid-base balance, and Sepsis) had a 99% lower confidence limit ≥75%. Codes within 8 additional categories demonstrated a 99% lower confidence limit between 74% and 50% (Acute respiratory distress, Ventilation, Other complications of obstetric surgery, Disorders of coagulation, Cardiomonitoring, Acute renal failure, Thromboembolism, and Shock). Codes within 6 clinical categories demonstrated a 99% lower confidence limit <50% (Puerperal cerebrovascular disorders, Conversion of cardiac rhythm, Acute heart failure [includes arrest and fibrillation], Eclampsia, Neurotrauma, and Severe anesthesia complications).ConclusionsICD-9-CM codes capturing severe maternal morbidity during delivery hospitalization demonstrate a range of PPVs. The PPV was high when objective supportive evidence, such as laboratory values or procedure documentation supported the ICD-9-CM code. The PPV was low when greater judgment, interpretation, and synthesis of the clinical data (signs and symptoms) was required to support a code, such as with the category Severe anesthesia complications. As a result, these codes should be used for administrative research with more caution compared with codes primarily defined by objective data.
| S-EPMC7481827 | biostudies-literature
Project description:PurposeThis study validated incident and recurrent ischemic stroke identified by International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10) hospital discharge diagnosis codes.MethodsUsing electronic health records (EHR) of adults (≥18 years) receiving care from Kaiser Permanente Southern California with ICD-10 hospital discharge diagnosis codes of ischemic stroke (I63.x, G46.3, and G46.4) between October 2015 and September 2020, we identified 75 patients with both incident and recurrent stroke events (total 150 cases). Two neurologists independently evaluated validity of ICD-10 codes through chart reviews.ResultsThe positive predictive value (PPV, 95% CI) for incident stroke was 93% (95% CI: 88%, 99%) and the PPV for recurrent stroke was 72% (95% CI: 62%, 82%). The PPV for recurrent stroke improved after applying a gap of 20 days (PPV of 75%; 95% CI: 63%, 87%) or removing hospital admissions related to stroke-related procedures (PPV of 78%; 95% CI: 68%, 88%).ConclusionThe ICD-10 hospital discharge diagnosis codes for ischemic stroke showed a high PPV for incident cases, while the PPV for recurrent cases were less optimal. Algorithms to improve the accuracy of ICD-10 codes for recurrent ischemic stroke may be necessary.
| S-EPMC10830879 | biostudies-literature
Project description:ObjectiveTo evaluate the validity of COVID-19 International Classification of Diseases, 10th Revision (ICD-10) codes and their combinations.DesignRetrospective cohort study.SettingAcute care hospitals and emergency departments (EDs) in Alberta, Canada.ParticipantsPatients who were admitted to hospital or presented to an ED in Alberta, as captured by local administrative databases between 1 March 2020 and 28 February 2021, who had a positive COVID-19 test and/or a COVID-19-related ICD-10 code.Main outcome measuresThe sensitivity, positive predictive value (PPV) and 95% CIs for ICD-10 codes were computed. Stratified analysis on age group, sex, symptomatic status, mechanical ventilation, hospital type, patient intensive care unit (ICU) admission, discharge status and season of pandemic were conducted.ResultsTwo overlapping subsets of the study population were considered: those who had a positive COVID-19 test (cohort A, for estimating sensitivity) and those who had a COVID-19-related ICD-10 code (cohort B, for estimating PPV). Cohort A included 17 979 ED patients and 6477 inpatients while cohort B included 33 675 ED patients and 18 746 inpatients. Of inpatients, 9.5% in cohort A and 8.1% in cohort B received mechanical ventilation. Over 13% of inpatients were admitted to ICU. The length of hospital stay was 6 days (IQR: 3-14) for cohort A and 8 days (IQR: 3-19) for cohort B. In-hospital mortality was 15.9% and 38.8% for cohort A and B, respectively. The sensitivity for ICD-10 code U07.1 (COVID-19, virus identified) was 82.5% (81.8%-83.2%) with a PPV of 93.1% (92.6%-93.6%). The combination of U07.1 and U07.3 (multisystem inflammatory syndrome associated with COVID-19) had a sensitivity of 82.5% (81.9%-83.2%) and PPV of 92.9% (92.4%-93.4%).ConclusionsIn Alberta, ICD-10 COVID-19 codes (U07.1 and U07.3) were coded well with high validity. This indicates administrative data can be used for COVID-19 research and pandemic management purposes.
| S-EPMC8787827 | biostudies-literature
Project description:BackgroundUsing ICD-9 codes underestimates the prevalence of obesity in adults; however, the validity of these codes in studies of pregnancy-related outcomes is not known.ObjectivesTo compare classification of maternal obesity based on ICD-9 codes in hospital discharge records versus data from birth certificates in the same women, examine predictors of agreement, and assess how associations between obesity and two birth outcomes differ by source of weight data.MethodsThis population-based study included 2 329 145 California births between 2007 and 2012. We compared data on obesity from childbirth hospital discharge records (ICD-9 codes for obesity) and birth certificates (pre-pregnancy body mass index (BMI) calculated from weight and height) and identified predictors of agreement between the two sources. Logistic regression models assessed whether the two definitions of obesity resulted in different estimates of the associations of obesity with caesarean birth and large-for-gestational age.ResultsOverall, 464 754 women (20.0%) had obesity based on their pre-pregnancy BMI while only 100 002 (4.3%) had an obesity-related ICD-9 code. The sensitivity of ICD-9-based obesity was low at 16.2%; however, obesity codes were highly specific at 98.7%, with a negative predictive value of 82.5% and a positive predictive value of 75.2%. Among women with obesity identified by the birth certificate, those with pre-pregnancy and pregnancy-related complications (eg diabetes and hypertension) were more likely to have an obesity-related diagnosis in their delivery hospital discharge record. Using ICD-9 codes overestimated the association of obesity with caesarean birth and newborn large-for-gestational age.ConclusionsICD-9 codes in childbirth discharge records captured only one in five women with pre-pregnancy obesity. Sensitivity varied by maternal characteristics and conditions. This misclassification resulted in bias when examining the association of obesity and pregnancy-related outcomes.
| S-EPMC7483732 | biostudies-literature
Project description:PurposeValidating cases of acute liver injury (ALI) in health care data sources is challenging. Previous validation studies reported low positive predictive values (PPVs).MethodsCase validation was undertaken in a study conducted from 2009 to 2014 assessing the risk of ALI in antidepressants users in databases in Spain (EpiChron and SIDIAP) and the Danish National Health Registers. Three ALI definitions were evaluated: primary (specific hospital discharge codes), secondary (specific and nonspecific hospital discharge codes), and tertiary (specific and nonspecific hospital and outpatient codes). The validation included review of patient profiles (EpiChron and SIDIAP) and of clinical data from medical records (EpiChron and Denmark). ALI cases were confirmed when liver enzyme values met a definition by an international working group.ResultsOverall PPVs (95% CIs) for the study ALI definitions were, for the primary ALI definition, 84% (60%-97%) (EpiChron), 60% (26%-88%) (SIDIAP), and 74% (60%-85%) (Denmark); for the secondary ALI definition, 65% (45%-81%) (EpiChron), 40% (19%-64%) (SIDIAP), and 70% (64%-77%) (Denmark); and for the tertiary ALI definition, 25% (18%-34%) (EpiChron), 8% (7%-9%) (SIDIAP), and 47% (42%-52%) (Denmark). The overall PPVs were higher for specific than for nonspecific codes and for hospital discharge than for outpatient codes. The nonspecific code "unspecified jaundice" had high PPVs in Denmark.ConclusionsPPVs obtained apply to patients using antidepressants without preexisting liver disease or ALI risk factors. To maximize validity, studies on ALI should prioritize hospital specific discharge codes and should include hospital codes for unspecified jaundice. Case validation is required when ALI outpatient cases are considered.
| S-EPMC6618105 | biostudies-literature
Project description:BackgroundHospital discharge codes are relied upon for research, accounting/invoicing and health systems planning. Congenital heart disease (CHD), however, is uniquely difficult for non-cardiologists to code due to the rarity, variety and complexity of lesions. It is therefore important that the accuracy of hospital discharge codes is regularly checked to ensure that the prevalence and burden of CHD is being correctly estimated and recorded.Methods and resultsWe identified all inpatient admissions of adults with CHD to Royal Prince Alfred Hospital in Sydney, Australia from January 2018 to March 2021 (257 admissions, 106 unique patients). The associated discharge coding summaries were extracted and compared to the codes in the separately collected and audited Adult CHD database. Only a quarter of discharge coding summaries contained any diagnosis of CHD, and just one-tenth accurately recorded all appropriate CHD diagnoses. Patients with simple lesions were most likely to have a coded diagnosis of CHD, while those with moderate and complex lesions were much less likely. Moreover, patients admitted under a cardiovascular specialty were twice as likely to have a coded diagnosis of CHD, compared with those admitted under non-cardiovascular specialties (p = 0.006). Overall, less than half of patients had any hospital-coded diagnosis of CHD in any admission over the three-year study period.ConclusionsHospital discharge coding dramatically underreports CHD, especially for patients with moderate and severe CHD lesions and for admissions under non-cardiovascular specialties. This suggests that discharge coding-based estimates of the burden of CHD on hospitals and health systems may be substantially underestimated.
| S-EPMC11658532 | biostudies-literature