Developing a standardised approach to the aggregation of inpatient episodes into person-based spells in all specialties and psychiatric specialties

Abstract

BackgroundElectronic health record (EHR) data are available for research in all UK nations and cross-nation comparative studies are becoming more common. All UK inpatient EHRs are based around episodes, but episode-based analysis may not sufficiently capture the patient journey. There is no UK-wide method for aggregating episodes into standardised person-based spells. This study identifies two data quality issues affecting the creation of person-based spells, and tests four methods to create these spells, for implementation across all UK nations.MethodsWelsh inpatient EHRs from 2013 to 2017 were analysed. Phase one described two data quality issues; transfers of care and episode sequencing. Phase two compared four methods for creating person spells. Measures were mean length of stay (LOS, expressed in days) and number of episodes per person spell for each method.Results3.5% of total admissions were transfers-in and 3.1% of total discharges were transfers-out. 68.7% of total transfers-in and 48.7% of psychiatric transfers-in had an identifiable preceding transfer-out, and 78.2% of total transfers-out and 59.0% of psychiatric transfers-out had an identifiable subsequent transfer-in. 0.2% of total episodes and 4.0% of psychiatric episodes overlapped with at least one other episode of any specialty.Method one (no evidence of transfer required; overlapping episodes grouped together) resulted in the longest mean LOS (4.0 days for all specialties; 48.5 days for psychiatric specialties) and the fewest single episode person spells (82.4% of all specialties; 69.7% for psychiatric specialties). Method three (evidence of transfer required; overlapping episodes separated) resulted in the shortest mean LOS (3.7 days for all specialties; 45.8 days for psychiatric specialties) and the most single episode person spells; (86.9% for all specialties; 86.3% for psychiatric specialties).ConclusionsTransfers-in appear better recorded than transfers-out. Transfer coding is incomplete, particularly for psychiatric specialties. The proportion of episodes that overlap is small but psychiatric episodes are disproportionately affected.The most successful method for grouping episodes into person spells aggregated overlapping episodes and required no evidence of transfer from admission source/method or discharge destination codes. The least successful method treated overlapping episodes as distinct and required transfer coding. The impact of all four methods was greater for psychiatric specialties.

Visualisation and optimisation of alcohol-related hospital admissions ICD-10 codes in Welsh e-cohort data

“…In PEDW records for an individual can be aggregated regardless of provider, where there is evidence that they are connected; these aggregated records are known as (person) spells. Spells involve at least one provider and one episode [ 27 ] and show continuous periods of inpatient care for a single patient which could take place under any number of different providers. Each record of an admission contains fields including, among others, date of admission; admission method (e.g.…”

Pharmacogenomics: A road ahead for precision medicine in psychiatry

“…This would not, however, avoid the presence of confounders and biases, which could stem from patient, clinician or even healthcare system factors (Dueñas et al, 2020). Addressing these difficulties should take advantage of both the population-wide scale of clinical databases and the multidisciplinary nature of eHR-based research (Figure 3), as both open up opportunities for identifying these problems rapidly and early, as well as exploring solutions in which data curation and quality control algorithms are informed by clinical expertise (Rees et al, 2019).…”