Dataset Information

Identifying Possible False Matches in Anonymized Hospital Administrative Data without Patient Identifiers.

ABSTRACT:

Objective

To identify data linkage errors in the form of possible false matches, where two patients appear to share the same unique identification number.

Data source

Hospital Episode Statistics (HES) in England, United Kingdom.

Study design

Data on births and re-admissions for infants (April 1, 2011 to March 31, 2012; age 0-1 year) and adolescents (April 1, 2004 to March 31, 2011; age 10-19 years).

Data collection/extraction methods

Hospital records pseudo-anonymized using an algorithm designed to link multiple records belonging to the same person. Six implausible clinical scenarios were considered possible false matches: multiple births sharing HESID, re-admission after death, two birth episodes sharing HESID, simultaneous admission at different hospitals, infant episodes coded as deliveries, and adolescent episodes coded as births.

Principal findings

Among 507,778 infants, possible false matches were relatively rare (n = 433, 0.1 percent). The most common scenario (simultaneous admission at two hospitals, n = 324) was more likely for infants with missing data, those born preterm, and for Asian infants. Among adolescents, this scenario (n = 320) was more common for males, younger patients, the Mixed ethnic group, and those re-admitted more frequently.

Conclusions

Researchers can identify clinically implausible scenarios and patients affected, at the data cleaning stage, to mitigate the impact of possible linkage errors.

SUBMITTER: Hagger-Johnson G

PROVIDER: S-EPMC4545352 | biostudies-literature | 2015 Aug

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Identifying Possible False Matches in Anonymized Hospital Administrative Data without Patient Identifiers.

Hagger-Johnson Gareth G Harron Katie K Gonzalez-Izquierdo Arturo A Cortina-Borja Mario M Dattani Nirupa N Muller-Pebody Berit B Parslow Roger R Gilbert Ruth R Goldstein Harvey H

Health services research 20141218 4

<h4>Objective</h4>To identify data linkage errors in the form of possible false matches, where two patients appear to share the same unique identification number.<h4>Data source</h4>Hospital Episode Statistics (HES) in England, United Kingdom.<h4>Study design</h4>Data on births and re-admissions for infants (April 1, 2011 to March 31, 2012; age 0-1 year) and adolescents (April 1, 2004 to March 31, 2011; age 10-19 years).<h4>Data collection/extraction methods</h4>Hospital records pseudo-anonymize ...[more]

PMID: 25523215

Similar Datasets

Project description:BackgroundThe goal of regionalized perinatal care, specifically levels of maternal care, is to improve maternal outcomes through risk-appropriate obstetric care. Studies of levels of maternal care are limited by current approaches to identify a hospital's level of care, often relying on hospital self-reported data, which is expensive and challenging to collect and validate. The study objective was to develop an empiric approach to determine a hospital's level of maternal care using administrative data reflective of the patient care provided and apply this approach to describe the levels of maternal care available over time.MethodsRetrospective cohort study of mother-infant dyads who delivered in California, Missouri, and Pennsylvania hospitals from 2000 to 2009. Linked mother-infant administrative records with an infant born at 24-44 weeks' gestation and a birth weight of 400-8000 g were included. Using the American College of Obstetricians and Gynecologists and the Society for Maternal Fetal Medicine descriptions of levels of maternal care, four levels were classified based on the appropriate location of care for patients with specific medical or pregnancy conditions. Individual hospitals were assigned a level of maternal care annually based on the volume of patients who delivered reflective of the four classified levels as determined by International Classification of Diseases and Current Procedural Terminology.ResultsBased on the included 6,895,000 mother-infant dyads, the obstetric hospital levels of maternal care I, II, III and IV were identified. High-risk patients more frequently delivered in hospitals with higher level maternal care, accounting for 8.9, 10.9, 13.8, and 16.9% of deliveries in level I, II, III and IV hospitals, respectively. The total number of obstetric hospitals decreased over the study period, while the proportion of hospitals with high-level (level III or IV) maternal care increased. High-level hospitals were located in more densely populated areas.ConclusionIdentification of the level of maternal care, independent of hospital self-reported variables, is feasible using administrative data. This empiric approach, which accounts for changes in hospitals over time, is a valuable framework for perinatal researchers and other stakeholders to inexpensively identify measurable benefits of levels of maternal care and characterize where specific patient populations receive care.

Project description:OBJECTIVE:To use hospital-level data from the US to determine whether private patient rooms (PPRs) are associated with fewer in hospital-acquired methicillin-resistant Staphylococcus aureus (HA-MRSA) infections. METHODS:We retrospectively analyzed Texas Inpatient Public Use Data with discharges between September 2015 and August 2016 merged with American Hospital Association annual survey data. We used negative binomial regression to estimate the association between the proportion of PPRs within a hospital and the count of discharges with HA-MRSA infections, adjusting for potentially confounding variables. RESULTS:We analyzed data for 340 hospitals and 2,670,855 discharges. HA-MRSA incidence within these hospitals was 386 per 100,000 discharges (95% CI: 379, 393) and, on average, 62.73% (95% CI: 58.99, 66.46) of rooms in these hospitals were PPRs. PPRs were significantly associated with fewer HA-MRSA infections (unadjusted IRR = 0.973, 95% CI: 0.968, 0.979; adjusted IRR = 0.992, 95% CI: 0.991, 0.994; p<0.001 for both); at the hospital level, as the percentage of PPRs increased, HA-MRSA infection rates decreased. This association was non-linear; in hospitals with few PPRs there was a stronger association between PPRs and HA-MRSA infection rate relative to hospitals with many PPRs. CONCLUSION:We identified 0.8% fewer HA-MRSA infections for each 1% increase in PPRs as a proportion of all rooms, suggesting that private rooms provide substantial protection from HA-MRSA. Small changes may not induce significant improvements in HA-MRSA incidence, and hospitals seeking tangible benefits in HAI reduction likely need to markedly increase the proportion of PPRs through large-scale renovations. The effect of private rooms is disproportionate across hospitals. Hospitals with proportionately fewer PPRs stand to gain the most from adding additional PPRs, while those with an already high proportion of PPRs are unlikely to see large benefits. Our findings enable hospital administrators to consider potential patient safety benefits as they make decisions about facility design and renovation.

Project description:BackgroundCongenital anomalies are a major cause of co-morbidity in children. Diagnostic code lists are increasingly used to identify congenital anomalies in administrative health records. Evidence is lacking on comparability of these code lists.ObjectivesTo compare prevalence of congenital anomalies and prognostic outcomes for children with congenital anomalies identified in administrative health records using three different code lists.MethodsWe developed national cohorts of singleton livebirths in England (n = 7 354 363, 2003-2014) and Scotland (n = 493 556, 2003-2011). Children with congenital anomalies were identified if congenital anomaly diagnosis was recorded at birth, during subsequent hospital admission or as cause of death before 2 years old. We used three code lists: the EUROCAT list for congenital anomaly surveillance in Europe; the Hardelid list developed to identify children with chronic conditions (including congenital anomalies) admitted to hospital in England; and the Feudtner list developed to indicate children with complex chronic conditions (including congenital anomalies) admitted to hospitals in the United States. We compared prevalence, and risks of postnatal hospital readmission and death according to each code list in England and Scotland.ResultsPrevalence of congenital anomalies was highest using the EUROCAT list (4.1% of livebirths in England, 3.7% in Scotland), followed by Hardelid (3.1% and 3.0% of livebirths, respectively) and Feudtner (1.8% and 1.5% of livebirths, respectively). 67.2%-73.3% of children with congenital anomalies in England and 65.2%-77.0% in Scotland had at least one postnatal hospital admission across the three code lists; mortality ranged between 42.6-75.4 and 41.5-88.7 deaths per 1000 births in England Scotland, respectively. The risk of these adverse outcomes was highest using Feudtner and lowest using EUROCAT code lists.ConclusionsThe prevalence of congenital anomalies varied by congenital anomaly code list, over time and between countries, reflecting in part differences in hospital coding practices and admission thresholds. As a minimum, researchers using administrative health data to study congenital anomalies should report sensitivity analyses using different code lists.

Dataset Information

Identifying Possible False Matches in Anonymized Hospital Administrative Data without Patient Identifiers.

Objective

Data source

Study design

Data collection/extraction methods

Principal findings

Conclusions

Publications

Identifying Possible False Matches in Anonymized Hospital Administrative Data without Patient Identifiers.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets