Assessing the Accuracy of International Classification of Diseases (ICD) Coding for Delirium

Abstract

Objective: We assessed the accuracy of the ICD-10 code for delirium (F05) and its relationship with delirium discharge summary documentation. Methods: We performed a retrospective chart review at three academic hospitals. The Chart-based Delirium Identification Instrument (CHART-DEL) was used to identify 108 hospitalized patients aged ≥65 years with delirium, and 758 patients without delirium as controls. We assessed the proportion of patients who received the F05 code and calculated the sensitivity and specificity. We compared the rates of F05 code received between patients with and without “delirium” documented in the discharge summary. Results: Among delirious patients, 46.3% received a F05 code, which has a sensitivity of 46.3% and specificity of 99.6% for delirium. Of charts with “delirium” in the discharge summary ( n = 67), 67.2% were appropriately coded. Conclusions: Current ICD-10 data inadequately capture delirium. Delirium documentation in the discharge summary is associated with improved delirium coding.

Identification and information management of cognitive impairment of patients in acute care hospitals: An integrative review

“…Twenty-two primary studies were included in the review, including fourteen quantitative [ 12 , [42] , [43] , [44] , [45] , [46] , [47] , [48] , [49] , [50] , [51] , [52] , [53] , [54] ], four qualitative [ 30 , [55] , [56] , [57] ], and four mixed methods studies [ 29 , [58] , [59] , [60] ] ( Table 3 ). The included studies were published between 2003 and 2023 and were conducted in the UK ( n = 7), the USA ( n = 4), Australia ( n = 4), Canada ( n = 3), New Zealand, Finland, Italy, and Germany.…”

“… Lack of interaction Concerns: inadequate information about the data Grealish et al., 2019 [ 56 ]Australia Ethnographic study Delirium Source: seek information initiatively from multiple sources (such as residential facilities, family); Screening tool: not reported Record: delirium screening was not included in the documentation; Report: seek or share information at handover The patients valued being included in care decisions but reported cases where this did not happen. Concerns: none Bakhru et al., 2023 [ 51 ] USA Cross-sectional survey Delirium Source: delirium assessment and management protocol (43% of the ICUs) Tools: CAM ICU (35%) Not reported Not reported Concerns: risk of bias due to 31% non-response rate and social desirability in responses and 18-month survey collection period Chuen et al., 2022 [ 42 ] Canada Case-control study Delirium Source: routine admission assessment; Screening tool: CAM Record and store: patient’s electronic charts; Refer: discharge summary Lack of interaction varied among physicians or medical teams Concerns: none FitzGerald et al., 2020 [ 43 ] UK Descriptive cross-sectional study Delirium superimposed on dementia Not reported Refer: delirium diagnosis disclosed to GP via discharge summary Patients and or families/carers were given information about delirium and its impact Concerns: inadequate information about the data Gilmore-Bykovskyi et al., 2021 [ 44 ]USA Cohort study Dementia Not reported Record and store: clinical notes Refer: written discharge summary (both have high rates of omission) Not reported Co...…”

“…Information about patient interaction in practice was obtained from nine studies ( n = 9/22). Patient interaction was valued but was lacking ( n = 6) [ 12 , 42 , 48 , 55 , 56 , 59 ]. Three papers reported the interaction with patients, families, and carers to provide education and support regarding the diagnosis, prognosis, and management [ 30 , 43 , 50 ].…”

Former smoking, but not active smoking, is associated with delirium in postoperative ICU patients: a matched case-control study

“…Exclusion criteria included (i) lack of data regarding smoking status, (ii) cessation of smoking less than 1 year prior, (iii) unknown delirium status, (iv) drug abuse, (v) current or former alcohol abuse. Delirium status during ICU stay was determined using a combination of ICD-10 diagnosis code (27) and ICDSC score. The ICDSC scoring system ranges from 0 to 8, with a score of 4 or higher serving as the threshold for delirium (28).…”

Clinical Prediction Models for Hospital-Induced Delirium Using Structured and Unstructured Electronic Health Record Data: Protocol for a Development and Validation Study

“…Automated identification of conditions from EHR or other health data is not straightforward, even when biomedical ontologies such as the World Health Organization's International Classification of Diseases (ICD) or the Systemized Nomenclature of Medicine-Clinical Terms are used [11,12]. Previous studies have shown that ICD code data captures a low percentage of delirium cases [13][14][15][16]. The notion of "computable phenotype" has been introduced to provide standardized, automated algorithms that make use of both structured and unstructured health data to identify conditions [11,12].…”