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

2021 ◽  
Vol 6 (1) ◽  
Author(s):  
Laszlo Trefan ◽  
Ashley Akbari ◽  
Jennifer Siân Morgan ◽  
Daniel Mark Farewell ◽  
David Fone ◽  
...  
Keyword(s):  
Hospital Admission ◽  
Hospital Admissions ◽  
Accurate Determination ◽  
Rate Sensitivity ◽  
Misclassification Rate ◽  
Care Utilization ◽  
Diagnostic Codes ◽  
Cohort Data ◽  
Icd 10 ◽  
Excessive Consumption

IntroductionThe excessive consumption of alcohol is detrimental to long term health and increases the likelihood of hospital admission. However, definitions of alcohol-related hospital admission vary, giving rise to uncertainty in the effect of alcohol on alcohol-related health care utilization. ObjectivesTo compare diagnostic codes on hospital admission and discharge and to determine the ideal combination of codes necessary for an accurate determination of alcohol-related hospital admission. MethodsRoutine population-linked e-cohort data were extracted from the Secure Anonymised Information Linkage (SAIL) Databank containing all alcohol-related hospital admissions (n,= 92,553) from 2006 to 2011 in Wales, United Kingdom. The distributions of the diagnostic codes recorded at admission and discharge were compared. By calculating a misclassification rate (sensitivity-like measure) the appropriate number of coding fields to examine for alcohol-codes was established. ResultsThere was agreement between admission and discharge codes. When more than ten coding fields were used the misclassification rate was less than 1%. ConclusionWith the data at present and alcohol-related codes used, codes recorded at admission and discharge can be used equivalently to identify alcohol-related admissions. The appropriate number of coding fields to examine was established: fewer than ten is likely to lead to under-reporting of alcohol-related admissions. The methods developed here can be applied to other medical conditions that can be described using a certain set of diagnostic codes, each of which can be a known sole cause of the condition and recorded in multiple positions in e-cohort data.

scholarly journals Using ICD-10-based Social Determinants of Health Categories to Assess Patients Risk for Acute Care Utilization

2021 ◽  
Author(s):  
Peter H. Nguyen ◽  
James Wang ◽  
Pamela Garcia-Filion ◽  
Deborah Dominick ◽  
Hamed Abbaszadegan ◽  
...  
Keyword(s):  
Social Determinants Of Health ◽  
Social Services ◽  
Acute Care ◽  
Social Determinants ◽  
Hospital Admissions ◽  
Medical Center ◽  
Determinants Of Health ◽  
Care Utilization ◽  
Icd 10 ◽  
Acute Care Utilization

ABSTRACTObjectiveSocial determinants of health (SDoH) play a pivotal role in health care utilization and adverse health outcomes. However, the optimal method to identify SDoH remains debatable. We ascertained SDoH based on International Classification of Disease 10 (ICD-10) codes in patient electronic health records (EHR) to assess the correlation with acute care utilization, and determine if social services interventions reduced care utilization.MethodsWe analyzed retrospective data for active patients at a Department of Veterans Affairs Medical Center (VAMC) from 2015-2017. Eleven categories of SDoH were developed based on existing literature of the social determinants; the relevant ICD-10 codes were divided among these categories. Emergency Room (ER) visits, hospital admissions, and social work visits were determined for each patient in the cohort.ResultsIn a cohort of 44,401 patients, the presence of ICD-10 codes within the EHR in the 11 SDoH categories was positively correlated with increased acute care utilization. Veterans with at least one SDoH risk factor were 71% (95%CI: 68% - 75%) more likely to use the ED and 71% (95%CI: 65%-77%) more likely to be admitted to the hospital. Utilization decreased with social service interventions.ConclusionThis project demonstrates a potentially meaningful method to capture patient social risk profiles through existing EHR data in the form of ICD-10 codes, which can be used to identify the highest risk patients for intervention with the understanding that not all SDoH codes are uniformly used and some SDoHs may not be captured.

scholarly journals The Safety of Non-Transport Decisions Made by Ambulance Personnel: A Retrospective Study of Subsequent Hospital Admission and 30-Day Mortality

2021 ◽  
Author(s):  
Kjersti Amundsen ◽  
Marie Svanes Elden ◽  
Lars Myrmel ◽  
Jörg Assmus ◽  
Audun Lange ◽  
...  
Keyword(s):  
Retrospective Study ◽  
Hospital Admission ◽  
Hospital Admissions ◽  
Information Age ◽  
Time Of Day ◽  
Ambulance Personnel ◽  
Icd 10 ◽  
Health Trust ◽  
Reason For Admission ◽  
Mental And Behavioral Disorders

Abstract BackgroundAmbulance missions do not always result in the patient being transported to a doctor or hospital after evaluation at the scene by ambulance personnel. Sometimes a patient is discharged at the scene but should have been transported for further examination and treatment. In this study, we aimed to identify and describe this group, and to investigate subsequent hospital admission within 72 hours and 30-day mortality, which may indicate the safety of leaving a patient at the scene after examination. MethodThis retrospective study was carried out in the Bergen health trust in western Norway and included ambulance missions from 2018. For each mission, we recorded the patient’s demographic information (age, gender, time of day), initial reason for contacting the emergency medical service (EMS), hospital admissions after non-transport, and time of death if within 30 days, in addition to some other variables. ResultsAmong 33,183 included acute and urgent ambulance missions, 7.3% of the patients were discharged at the scene after evaluation by ambulance personnel. The median age in this group was 47 years (IQR 28–70 years), compared to 64 years (IQR 39–80 years) for all included missions. Following a non-transport decision, 4.8% of the patients were admitted to a public hospital within 72 hours (median age, 59 years; IQR 35–76 years), with mental and behavioral disorders (ICD-10 chapter V) being the most common reason for admission (24.8%). The 30-day mortality rate following non-transport mission was 2.4%. In this group, the median age was 83 years (IQR 73–90 years), and the most common reasons for contacting EMS were breathing difficulties or lung diseases (25.4%), and injuries or fractures (18.6%). ConclusionOur present analysis revealed low rates of hospital admission within 72 hours, and 30-day mortality, among patients left at the scene following evaluation by ambulance personnel. These findings do not suggest an unsafe rate of non-transport in the Bergen EMS. There remains a need for further evaluation of the factors involved in the decision not to transport a patient, and the safety of these decisions.

RCVS: Symptoms, Incidence, and Resource Utilization in a Population-Based US Cohort

Neurology ◽  
2021 ◽  
pp. 10.1212/WNL.0000000000012223
Author(s):  
Jessica Magid-Bernstein ◽  
Setareh Salehi Omran ◽  
Neal S. Parikh ◽  
Alexander E. Merkler ◽  
Babak Navi ◽  
...  
Keyword(s):  
Hospital Admission ◽  
Administrative Data ◽  
Census Data ◽  
Hospital Admissions ◽  
Population Based ◽  
Cerebrovascular Diseases ◽  
Cerebral Vasoconstriction ◽  
Icd 10 ◽  
Incidence Of Hospitalization ◽  
Age And Sex

Objective:To estimate the incidence of hospitalization for reversible cerebral vasoconstriction syndrome (RCVS), we identified RCVS-related hospital admissions across 11 U.S. states in 2016.Methods:We tested the validity of ICD-10 code I67.841 in 79 patients with hospital admissions for RCVS or other cerebrovascular diseases at one academic and one community hospital. After determining that this code had a sensitivity of 100% (95% CI, 82-100%) and a specificity of 90% (95% CI, 79-96%), we applied it to administrative data from the Healthcare Cost and Utilization Project on all ED visits and hospital admissions. Age- and sex-standardized RCVS incidence was calculated using census data. Descriptive statistics were used to analyze associated diagnoses.Results:Across 5,067,250 hospital admissions in our administrative data, we identified 222 patients with a discharge diagnosis of RCVS in 2016. The estimated annual age- and sex-standardized incidence of RCVS hospitalization was 2.7 (95% CI, 2.4-3.1) cases per million adults. Many patients had concomitant neurologic diagnoses, including subarachnoid hemorrhage (37%), ischemic stroke (16%), and intracerebral hemorrhage (10%). In the 90 days before the index admission, 97 patients had an ED visit and 34 patients a hospital admission, most commonly for neurologic, psychiatric, and pregnancy-related diagnoses. Following discharge from the RCVS hospital admission, 58 patients had an ED visit and 31 had a hospital admission, most commonly for neurologic diagnoses.Conclusions:Using population-wide data, we estimated the age- and sex-standardized incidence of hospitalization for RCVS in U.S. adults as approximately 3 per million per year.

408 Validation of claim based algorithms for sleep apnea using ICD codes

SLEEP ◽  
2021 ◽  
Vol 44 (Supplement_2) ◽  
pp. A162-A162
Author(s):  
Rizwana Sultana ◽  
Elizabeth Lam ◽  
Enshuo Hsu ◽  
Erin Gurski ◽  
Gulshan Sharma
Keyword(s):  
Obstructive Sleep Apnea ◽  
Sleep Apnea ◽  
Individual Performance ◽  
Care Utilization ◽  
Office Visits ◽  
Sleep Study ◽  
Diagnostic Codes ◽  
Obstructive Sleep ◽  
Icd 10 ◽  
Icd Codes

Abstract Introduction Obstructive sleep apnea (OSA) is a common condition characterized by repeated episodes of partial or complete obstruction of the respiratory passages during sleep. According to recent studies prevalence of obstructive sleep apnea ranges between 9–38%. OSA is associated with increased all-cause mortality particularly associated with cardiac diseases. In order to provide representation of larger population estimates, administrative data using ICD codes have been utilized. Accurate identification of sleep apnea is important for research related to health care utilization and health outcomes. Our aim is to validate an algorithm for identification of patients with obstructive sleep apnea using ICD 10 codes seen at UTMB. Methods Patient medical records were collected from University of Texas Medical Branch EHR system. We included patients who visited from 6/1/2015 to 5/31/2018 in pulmonary or primary care clinics who had any sleep disorder diagnostic codes (ICD-10: G47.30, G47.31, G47.33, G47.34, G47.36, G47.20, G47.10, G47.39, G47.8, G47.9, F51.13, F51.09, R06.89, J96.90, R40.0, F51.9, R06.83, R06.3, G47.63, G47.39, Z86.69). Two algorithms were created. First algorithm included patient with sleep diagnostic codes used at 2 separate office visits. Second algorithm included patients with sleep diagnostic codes and evidence of sleep study. The performance of most used codes was calculated individually. Results 1200 patients were identified with ICD codes used during two office visits. According to the first algorithm with only ICD codes 75% of patients had sleep apnea. Upon addition of evidence of sleep apnea with ICD codes the % of patients with sleep apnea increased to 95.44. Among most used ICD codes, G47.30 had 86.47% patients with sleep apnea according to first algorithm and 96.01% with second algorithm. The percentages for G47.33 was 80.86% and 96.4%, for G47.10, 78.05% and 87.67%, for R40.0 78.91% and 90.63% respectively. Conclusion In conclusion, claim based algorithms for sleep apnea diagnostic codes showed good test positive percentages overall, but algorithm with ICD 10 codes with sleep study performed better in identifying patients with sleep apnea than ICD-9-CM codes alone. Similarly, the individual performance of most used ICD codes was highly improved when evidence of sleep study was present. Support (if any):

P0783PREVALENCE AND PROGNOSIS OF HYPERKALAEMIA IN PEOPLE HOSPITALISED WITH AND WITHOUT AKI

2020 ◽  
Vol 35 (Supplement_3) ◽  
Author(s):  
Andrew McLean ◽  
Corri Black ◽  
Angharad Marks ◽  
Simon Sawhney
Keyword(s):  
Hospital Admission ◽  
Hospital Admissions ◽  
Kidney Diseases ◽  
Close Observation ◽  
Icd 10 ◽  
Initial Hospital ◽  
Serial Serum ◽  
Definition Of ◽  
The Relationship ◽  
Clinical Emergency

Abstract Background and Aims Hyperkalemia is a clinical emergency associated with kidney diseases and hospital mortality. It may be apparent on initial hospital presentation, or develop during the course of admission, and can occur in the context of AKI. The prevalence of hyperkalemia across these different presentations and contexts is not well described. No work has previously described whether the prognosis of hyperkalemia varies depending on timing of presentation, or on AKI status defined by KDIGO creatinine change biochemical criteria. Method We constructed a cohort of all adult residents in Grampian (North Scotland) admitted to hospital in 2012 (n=28462). We used a validated and replicated KDIGO based definition of AKI to identify AKI using serial serum creatinine values. We determined the presence of hyperkalemia (serum potassium >= 6 mEq/L) both on first blood test on presentation to hospital, and also during the course of hospital admission. We explored the outcome of 30 day mortality within subgroups of AKI status and timing of hyperkalemia. Covariates of interest included age, CKD, medications prescribed in the preceding 90 days and comorbidities (ICD-10 hospital episode codes). The relationship between hyperkalemia and 30 day mortality was determined using multivariable logistic regression. Results Of 28462 hospital admissions, 247 (0.9%) presented with hyperkalemia, whereas 560 (2.0%) had hyperkalemia during the course of hospital admission. Hyperkalemia was common in the presence of AKI (4.2% at hospital presentation, 9.3% during hospital admission and rising to 24.5% during AKI stage 3). Hyperkalemia was uncommon in the absence of AKI (0.3% and 0.7% respectively) (OR AKI vs no AKI 13.9, 11.6-16.6). Other factors associated with hyperkalemia were male gender (OR 1.5, 1.3-1.8), age >70 years (OR 2.4, 2.0-2.9), CKD based on eGFR or proteinuria (5.5, 4.6-6.5), diabetes (OR 3.4, 2.8-4.0), heart failure (OR 3.0, 2.4-3.7), RAAS blockers (OR 2.4, 2.0-2.9), trimethoprim containing antibiotics (OR 2.2, 1.7-2.8)), non-RAAS antihypertensives (OR 1.7, 1.4-2.0), but not NSAIDs (OR 0.9, 0.7-1.1). Hyperkalemia mortality (AKI vs no AKI) was 31% vs 29% when presenting at admission, or 34.3% vs 27.8% when occurring during hospital admission. Although absolute risks were similar irrespective of AKI, the excess relative mortality risk associated with hyperkalemia was lower for those with AKI (OR 2.7, 2.1-3.4) than those without AKI (OR 9.5, 6.8-13.2), which may be explained by a higher mortality for those with AKI even without hyperkalemia. Conclusion Hyperkalemia is associated with a high mortality even in the absence of AKI and irrespective of the timing of presentation. Management protocols should draw attention to this poor prognosis across all clinical contexts. As hyperkalemia usually occurs within the context of AKI, it should prompt clinicians to consider ongoing close observation for emerging AKI even when AKI is not yet evident on blood tests.

scholarly journals Has the incidence of empyema in Scottish children continued to increase beyond 2005?

2014 ◽  
Vol 100 (3) ◽  
pp. 255-258 ◽  
Author(s):  
Stuart Nath ◽  
Matt Thomas ◽  
David Spencer ◽  
Steve Turner
Keyword(s):  
Hospital Admissions ◽  
Incidence Rate Ratio ◽  
Pneumococcal Vaccination ◽  
International Classification Of Diseases ◽  
Diagnostic Codes ◽  
Classification Of Diseases ◽  
Icd 10 ◽  
The Relationship ◽  
Insight Into

BackgroundThe incidence of empyema increased dramatically in children during the 1990s and early 2000s. We investigated the relationship between changes in the incidence of childhood empyema in Scotland following the 2006 introduction of routine heptavalent conjugate pneumococcal vaccination (PCv-7) and the 2010 introduction of the 13-valent (PCV-13) vaccine.MethodsThis was a whole-population study of Scottish hospital admissions between 1981 and 2013 using ICD (International Classification of Diseases)-9 and ICD-10 diagnostic codes for empyema. The number of admissions for pneumonia and croup was also captured to give insight into secular trends in admissions with other related and unrelated respiratory presentations.ResultsThere were 217 admissions with empyema between 1981 and 2005 (mean incidence 9 cases/million/year) and 323 between 2006 and 2013 (mean incidence 47 cases/million/year), p<0.001. The introduction of conjugate vaccines in 2006 was associated with an overall increase in admissions for empyema of 2.0 (95% CI 1.4 to 2.8) per 100 000 children, however, the incidence rate ratio for empyema admission between 2010 and 2013 was lower relative to 2006–2009 (0.78 (95% CI 0.63 to 0.98)). Secular changes in pneumonia, but not croup, were comparable with those for empyema.ConclusionsThe incidence of empyema in Scottish children initially rose in children aged 1 to 9 years after the introduction of routine conjugate pneumococcal vaccination, however, empyema incidence has fallen since 2010 when the PCV-13 was introduced.

scholarly journals Many people admitted to hospital with a provisional diagnosis of nonserious back pain are subsequently found to have serious pathology as the underlying cause

2022 ◽  
Author(s):  
Alla Melman ◽  
Chris G. Maher ◽  
Chris Needs ◽  
Gustavo C. Machado
Keyword(s):  
Back Pain ◽  
Lumbar Spine ◽  
Hospital Admissions ◽  
Spinal Fractures ◽  
Final Diagnosis ◽  
Snomed Ct ◽  
Provisional Diagnosis ◽  
Diagnostic Codes ◽  
Virtual Care ◽  
Icd 10

AbstractTo determine the proportion of patients admitted to the hospital for back pain who have nonserious back pain, serious spinal, or serious other pathology as their final diagnosis. The proportion of nonserious back pain admissions will be used to plan for future ‘virtual hospital’ admissions. Electronic medical record data between January 2016 and September 2020 from three emergency departments (ED) in Sydney, Australia were used to identify inpatient admissions. SNOMED-CT-AU diagnostic codes were used to select ED patients aged 18 and older with an admitting diagnosis related to nonserious back pain. The inpatient discharge diagnosis was determined from the primary ICD-10-AM codes by two independent clinician-researchers. Inpatient admissions were then analysed by sociodemographic and hospital admission variables. A total of 38.1% of patients admitted with a provisional diagnosis of nonserious back pain were subsequently diagnosed with a specific pathology likely unsuitable for virtual care; 14.2% with a serious spinal pathology (e.g., fracture and infection) and 23.9% a serious pathology beyond the lumbar spine (e.g., pathological fracture and neoplasm). A total of 57% of admissions were identified as nonserious back pain, likely suitable for virtual care. A challenge for implementing virtual care in this setting is screening for patients with serious pathology. Protocols need to be developed to reduce the risk of patients being admitted to virtual hospitals with serious pathology as the cause of their back pain. Key Points• Among admitted patients provisionally diagnosed in ED with non-serious back pain, 38.1% were found to have ‘serious spinal pathologies’ or ‘serious pathologies beyond the lumbar spine’ at discharge.• Spinal fractures were the most common serious spinal pathology, accounting for 9% of all provisional ‘non-serious back pain’ admissions from ED.• 57% of back pain admissions were confirmed to be non-serious back pain and may be suitable to virtual hospital care; the challenge is discriminating these patients from those with serious pathology.

scholarly journals Rural and Indigenous Health Disparity in Medical Service Use for Dementia and Diabetes Mellitus in Minnesota

2020 ◽  
Vol 4 (Supplement_1) ◽  
pp. 258-258
Author(s):  
Sung Han Rhew ◽  
Patrick Bright ◽  
Andrine Lemieux ◽  
Wayne Warry ◽  
Kristen Jacklin
Keyword(s):  
Diabetes Mellitus ◽  
Hospital Admission ◽  
Rural Areas ◽  
Service Use ◽  
Hospital Admissions ◽  
Indigenous Health ◽  
Metropolitan Region ◽  
Care Utilization ◽  
Urban Regions ◽  
Ed Visits

Abstract Minnesota has shown relatively high growth of mortality from diabetes mellitus (DM) and dementia in recent years, especially in rural areas. Analysis of medical care utilization patterns may reveal the reasons for this trend. The goal of the present study was to characterize the Minnesota dementia and diabetes care landscape by rurality and geographic region. Specifically, we compared the Metro region to five other rural-urban regions. Disease-specific 2017 hospital admission and emergency department (ED) visit data was obtained from the State Center for Health Statistics and the Healthcare Cost and Utilization Project. We used the logistic regression analysis adjusted by multiple covariates to evaluate rural-urban differences in hospital admissions and ED visits. Age-adjusted rates of ED visits for both DM and dementia were significantly higher in rural zip code areas, especially in northeast regions. Rural areas had elevated odds for dementia hospital admissions (OR=1.05, p&lt;0.0001) and ED visits (OR=1.24, p&lt;0.0001), but decreased odds for DM hospital admission (OR=0.96, p&lt;0.0001) and ED visits (OR=0.96, p&lt;0.0001). This was particularly true in the northeast region (relative to Metro regions) where ED visits were less likely due to DM (OR=0.89, p&lt;0.0001) but more likely related to dementia (ORs=1.42, p&lt;0.0001). Geographic differences for ED visits due to DM were greater than those for dementia, with higher rates for rural as compared to urban regions (northeast MN compared to a large metropolitan region). This geographical mismatch between mortality rates and ED visit rates may illustrate the relative lack of access to health services in rural MN.

scholarly journals Changing patterns of hospital admission for asthma, 1981–97

Thorax ◽  
2001 ◽  
Vol 56 (9) ◽  
pp. 687-690
Author(s):  
D S Morrison ◽  
P McLoone
Keyword(s):  
Hospital Admission ◽  
Hospital Admissions ◽  
Admission Rate ◽  
Hospital Admission Rate ◽  
Admission Rates ◽  
Lengths Of Stay ◽  
Icd 10 ◽  
Changing Patterns ◽  
Bed Days ◽  
Age And Sex

BACKGROUNDHospital admission rates for asthma have stopped rising in several countries. The aim of this study was to use linked hospital admission data to explore recent trends in asthma admissions in Scotland.METHODSLinked Scottish Morbidity Records (SMR1) for asthma (ICD-9 493 and ICD-10 J45–6) from 1981 to 1997 were used to describe rates of first admissions and readmissions by age and sex. As a measure of resource use, annual trends in bed days used were also explored by age and sex.RESULTSThere were 160 039 hospital admissions for asthma by 82 421 individuals in Scotland during the study period. The overall hospital admission rate increased by 122% (from 106.7 to 236.7 per 100 000 population) but this varied by sex, age, and admission type. First admissions rose by 70% from 73.2 per 100 000 in 1986 to 124.8 per 100 000 in 1997 while readmissions fell. Children (<15 years) experienced a decline in overall admissions after 1992 due to falls in both new admissions and readmissions. By 1997 the ratio of female to male admissions was 0.57 in children, but 1.50 above 14 years of age. Mean lengths of stay fell from 10.7 days to 3.7 days between 1981 and 1997 and bed days used showed little change except for a decline after 1992 in children.CONCLUSIONSAfter a period of increasing hospitalisation for asthma in Scotland, rates of admission among children have begun to fall but among adults admissions continue to rise.

scholarly journals Validating coding for a chronic condition (Cerebral Palsy) in routinely collected hospital admissions data

2018 ◽  
Vol 3 (4) ◽  
Author(s):  
Bethan Carter ◽  
Hywel Jones ◽  
Jackie Bethell ◽  
Alison Kemp ◽  
Ting Wang
Keyword(s):  
Cerebral Palsy ◽  
Hospital Admission ◽  
Hospital Admissions ◽  
Healthcare Utilisation ◽  
Hospital Data ◽  
Case Identification ◽  
Healthcare Data ◽  
Routinely Collected Data ◽  
Admission Data ◽  
Icd 10

IntroductionData-linkage provides an opportunity to evaluate healthcare utilisation of patients with chronic health conditions. However the consistency and accuracy of recording chronic conditions in routinely collected healthcare data is unclear and we aim to explore this in children and young people (CYP) with a cerebral palsy (CP). Objectives and ApproachThe study aims to validate CP case identification in routinely collected data by data-linking cases from The Northern Ireland Cerebral Palsy Register (NICPR) born 1981-2011 with routinely collected hospital admission data and cross-referencing cases between the two datasets. CP cases were identified in the administrative data using ICD-10 codes G80 (cerebral palsy), G81 (hemiplegia), G82 (paraplegia and tetraplegia) and G83.0-83.3 (diplegia and monoplegias). ResultsThere were 1,693 cases in the NICPR cohort and 1,733 cases of CP identified in the hospital admissions data, 915 of which were on the NICPR giving a positive predictive value for identifying a CP case within routinely collected data of 52.8%. Specificity was high (99.8%) however sensitivity was low (54.1%). 1,157 (68.3%) patients on the NICPR had at least one hospital admission. 914 (79.0 %) cases were coded at some time point with G80-83.3 (829 (71.7%) G80, 328 (28.3%)  G81-83.3). NICPR cases had a total 11,844 hospital admissions and a CP code was recorded during 6,397 (54.0%). The type of CP was recorded in NICPR for 1,673 (98.8%) cases whereas in the hospital admissions, data the majority (70.6%) were coded as other/unspecified CP (G80.8-9). Conclusion/ImplicationsThis study adds to understanding of CP coding practices within routinely collected hospital data, further supporting claims that coding of CP within such datasets is poor. Coding must be accurate and consistent if data are to be meaningful, comparable and useful to inform health outcome reviews and patient care.

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