Nonspecific Codes Research Articles

Validity of hospital ICD-10-GM codes to identify acute liver injury in Germany.

Acute liver injury (ALI) is an important adverse drug reaction. We estimated the positive predictive values (PPVs) of ICD-10-GM codes of ALI used in an international postauthorisation safety study (PASS). Analyses used routine data (2007 to 2016, adults) from a German academic hospital in a cross-sectional design. Two algorithms from the PASS were applied to extract potential cases from the hospital information system: specific end point (A) (discharge diagnosis of liver disease-specific codes) and less specific end point (B) (discharge and outpatient-specific and nonspecific codes suggestive of liver injury). ALI cases were confirmed on the basis of plasma liver enzyme activity elevation. Secondary analysis was performed following exclusion of cases with known cancer, chronic liver, biliary and pancreatic disease, heart failure, and alcohol-related disorders, as applied in the PASS. On the basis of ICD codes: outcome A, 154 cases (143 with case notes and lab data for case verification); outcome B, 485 cases (357 with case notes and lab data). ALI was confirmed in 71 outcome A cases, PPV of 49.7% (95% confidence interval [CI], 41.2%-58.1%), and 100 outcome B cases, PPV of 28.0% (95% CI, 23.4%-33.0%). Applying exclusion criteria increased PPV (95% CI) to 62.7% (50.0%-74.2%) for outcome A and 45.7% (37.2%-54.3%) for outcome B. In safety studies on hepatotoxicity based on routine data using ICD-10-GM discharge codes and when validation of potential cases is not feasible, only the more specific codes should be used to describe ALI, and competing diagnoses for liver injury should be excluded to avoid substantial misclassification.

Validity of ICD-9 and ICD-10 codes used to identify acute liver injury: A study in three European data sources.

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.

Time to cancer diagnosis in young women presenting to surgeons with breast-related symptoms: A population-based cohort study.

e13099 Background: Reports on delay to diagnosis of cancer in young women are based on retrospective studies and conflicting. The purpose of this study was to investigate time to cancer diagnosis in women presenting to a surgeon with breast-related complaints; and particularly, the role of age. Methods: A population-based cohort study including all women aged 18 to 44 presenting to a surgeon with a breast-related complaint between 2005 and 2015 in a large Israeli healthcare plan (N = 157,264). We collected data including demographics, diagnosis codes, breast imaging and biopsies. Breast cancer diagnosis within one year of the visit was ascertained from the national cancer registry. Time to breast imaging and biopsy was compared between the different age groups. Logistic regression analysis was used to determine the association between age and delay to biopsy while adjusting for possible confounders. Results: During the first year after the visit, 45,434 (29%) women had a breast imaging study; 5,767 (3.7%) women had a breast biopsy; and 676 (0.43%) were diagnosed with breast cancer. Overall, time to first breast imaging (mean, 53 days) and biopsy (mean, 68 days) did not differ significantly between the age groups. Non-specific visit codes (other than breast mass) were associated with delays to imaging and biopsy. This was more pronounced in the women ultimately diagnosed with breast cancer. Among women diagnosed with breast cancer, age under 40 (OR 2.3, 95% CI 1.4; 3.9), being post-partum (OR 2.6, 95% CI 1.1; 5.9) and a non-specific visit code (OR-8.3, 95% CI 4.9; 14.2) were associated with delay to biopsy. Conclusions: Symptomatic women with lower a-priori likelihood of breast malignancy (younger age, post-partum, or non-specific visit code) are at a significantly greater risk of delayed diagnosis of cancer. Physicians should be aware of the challenging diagnosis in young women with non-specific symptoms.

Accuracy of a composite event definition for hypoglycemia.

To evaluate the accuracy of a composite definition for the identification of hypoglycemia events that used both administrative claims and laboratory data in a cohort of patients. We reviewed medical records in a sample of presumed hypoglycemia events among patients who received care at the Veterans Health Administration Tennessee Valley Healthcare System in 2001 to 2012. A hypoglycemia event was defined as a hospitalization or emergency department visit judged by the treating clinician to be due to hypoglycemia, or an outpatient laboratory or point-of-care blood glucose measurement <60mg/dL. Based on medical record review, each event was classified as true positive (severe, documented symptomatic, documented asymptomatic) or false positive (probable symptomatic, not hypoglycemia). The positive predictive values (PPV) of the individual event types (hospitalization, emergency department, and outpatient) were estimated. Of 2250 events identified through the composite definition, 321 events (15 hospitalizations, 103 emergency department visits, and 203 outpatient events) were reviewed. The PPVs were 80% for hospitalization events, 48% for emergency department events, and 96% for outpatient events. The emergency department definition included a nonspecific diagnosis code for diabetic complications which captured many false positive events. Excluding this code from the definition improved the PPV for emergency department events to 70% and missed one true event. Our composite definition for hypoglycemia performed moderately well in a cohort of Veterans. Further evaluation of the emergency department events may be needed.

Drug overdose in the ED: a record linkage study examining emergency department ICD-10 coding practices in a cohort of people who inject drugs

BackgroundDrug overdose is a leading cause of mortality and morbidity amongst people who inject drugs (PWID). Drug overdose surveillance typically relies on the International Classification of Diseases (ICD-10) coding system, however its real world utilisation and the implications for surveillance have not been well characterised. This study examines the patterns of ICD-10 coding pertaining to drug overdoses within emergency departments for a cohort of known PWID.MethodsCohort data from 688 PWID was linked to statewide emergency department administrative data between January 2008 and June 2013. ICD-10 diagnostic codes pertaining to poisonings by drugs, medicaments and biological substances (T-codes T36-T50) as well as mental and behavioural disorders due to psychoactive substance use (F-codes F10-F19) were examined.ResultsThere were 449 unique ED presentations with T or F code mentions contributed by 168 individuals. Nearly half of the T and F codes used were non-specific and did not identify either a drug class (n = 160, 36%) or clinical reaction (n = 46, 10%) and 8% represented withdrawal states. T and F codes could therefore be used to reasonably infer an illicit drug overdose in only 42% (n = 188) of cases. Majority of presentations with T or F overdose codes recorded only one diagnostic code per encounter (83%) and representing multiple-drug overdose (F19.- = 18%) or unidentified substances (T50.9 = 17%) using a single, broad diagnostic code was common.ConclusionsReliance on diagnoses alone when examining ED data will likely significantly underestimate incidence of specific drug overdose due to frequent use of non-specific ICD-10 codes and the use of single diagnostic codes to represent polysubstance overdose. Measures to improve coding specificity should be considered and further work is needed to determine the best way to use ED data in overdose surveillance.

The Epidemiology, Cost, and Occupational Context of Spinal Injuries Sustained While 'Working for Income' in NSW: A Record-Linkage Study.

This study aimed to describe the epidemiological characteristics, the occupational context, and the cost of hospitalised work-related traumatic spinal injuries, across New South Wales, Australia. A record-linkage study of hospitalised cases of work-related spinal injury (ICD10-AM code U73.0 or workers compensation) was conducted. Study period 2013–2016. Eight hundred and twenty-four individuals sustained work-related spinal injuries; 86.2% of whom were males and had a mean age of 46.6 years. Falls led to 50% of the injuries; predominantly falls from building/structures, ladders or between levels. Falls occurred predominantly in the construction industry (78%). Transport crashes caused 31% of injuries and 24% in heavy vehicles. Half of all the transport injuries occurred ‘off road’. The external cause was coded as ‘non-specific work activity’ in 44.5% of cases; missing in 11.5%. Acute care bed days numbered at 13,302; total cost $19,500,000. High numbers of work-related spinal injuries occurred in the construction industry; particularly falling from a height. Off-road transport-related injuries were significant and likely unaddressed by ‘on-road’ prevention policies. Medical record documentation was insufficient in injury mechanism and context specificity. Workers in the construction industry or those using vehicles off-road were at high risk of spinal injury, suggesting inefficient systems approaches or ineffective prevention policies. Reducing the use of non-specific external cause codes in patients’ medical records would improve the measurement of policy effectiveness.

Acute general hospital admissions in people with serious mental illness.

Serious mental illness (SMI, including schizophrenia, schizoaffective disorder, and bipolar disorder) is associated with worse general health. However, admissions to general hospitals have received little investigation. We sought to delineate frequencies of and causes for non-psychiatric hospital admissions in SMI and compare with the general population in the same area. Records of 18 380 individuals with SMI aged ⩾20 years in southeast London were linked to hospitalisation data. Age- and gender-standardised admission ratios (SARs) were calculated by primary discharge diagnoses in the 10th edition of the World Health Organization International Classification of Diseases (ICD-10) codes, referencing geographic catchment data. Commonest discharge diagnosis categories in the SMI cohort were urinary conditions, digestive conditions, unclassified symptoms, neoplasms, and respiratory conditions. SARs were raised for most major categories, except neoplasms for a significantly lower risk. Hospitalisation risks were specifically higher for poisoning and external causes, injury, endocrine/metabolic conditions, haematological, neurological, dermatological, infectious and non-specific ('Z-code') causes. The five commonest specific ICD-10 diagnoses at discharge were 'chronic renal failure' (N18), a non-specific code (Z04), 'dental caries' (K02), 'other disorders of the urinary system' (N39), and 'pain in throat and chest' (R07), all of which were higher than expected (SARs ranging 1.57-6.66). A range of reasons for non-psychiatric hospitalisation in SMI is apparent, with self-harm, self-neglect and/or reduced healthcare access, and medically unexplained symptoms as potential underlying explanations.

Validation of asthma recording in the Clinical Practice Research Datalink (CPRD)

ObjectivesThe optimal method of identifying people with asthma from electronic health records in primary care is not known. The aim of this study is to determine the positive predictive value...

Road traffic accidents: Global Burden of Disease study, Brazil and federated units, 1990 and 2015.

To describe the global burden of disease due to road traffic accidents in Brazil and federated units in 1990 and 2015. This is an analysis of secondary data from the 2015 Global Burden of Disease study estimates. The following estimates were used: standardized mortality rates and years of life lost by death or disability, potential years of life lost due to premature death, and years of unhealthy living conditions. The Mortality Information System was the main source of death data. Underreporting and redistribution of ill-defined causes and nonspecific codes were corrected. Around 52,326 deaths due to road traffic accidents were estimated in Brazil in 2015. From 1990 to 2015, mortality rates decreased from 36.9 to 24.8/100 thousand people, a reduction of 32.8%. Tocantins and Piauí have the highest mortality risks among the federated units (FU), with 41.7/100 and 33.1/100 thousand people, respectively. They both present the highest rates of potential years of life lost due to premature deaths. Road traffic accidents are a public health problem. Using death- or disability-adjusted life years in studies of these causes is important because there are still no sources to know the magnitude of sequelae, as well as the weight of early deaths. Since its data are updated every year, the Global Burden of Disease study may provide evidence to formulate traffic security and health attention policies, which are guided to the needs of the federated units and of different groups of traffic users.

Validation of a Case Definition for Pediatric Brain Injury Using Administrative Data.

Health administrative data are a common population-based data source for traumatic brain injury (TBI) surveillance and research; however, before using these data for surveillance, it is important to develop a validated case definition. The objective of this study was to identify the optimal International Classification of Disease , edition 10 (ICD-10), case definition to ascertain children with TBI in emergency room (ER) or hospital administrative data. We tested multiple case definitions. Children who visited the ER were identified from the Regional Emergency Department Information System at Alberta Children's Hospital. Secondary data were collected for children with trauma, musculoskeletal, or central nervous system complaints who visited the ER between October 5, 2005, and June 6, 2007. TBI status was determined based on chart review. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated for each case definition. Of 6639 patients, 1343 had a TBI. The best case definition was, "1 hospital or 1 ER encounter coded with an ICD-10 code for TBI in 1 year" (sensitivity 69.8% [95% confidence interval (CI), 67.3-72.2], specificity 96.7% [95% CI, 96.2-97.2], PPV 84.2% [95% CI 82.0-86.3], NPV 92.7% [95% CI, 92.0-93.3]). The nonspecific code S09.9 identified >80% of TBI cases in our study. The optimal ICD-10-based case definition for pediatric TBI in this study is valid and should be considered for future pediatric TBI surveillance studies. However, external validation is recommended before use in other jurisdictions, particularly because it is plausible that a larger proportion of patients in our cohort had milder injuries.

Genomic Variability in Multiple Myeloma (MM) Patients By Race: An Analysis of the Publically Available Mmrf Commpass Study Database

Genomic Variability in Multiple Myeloma (MM) Patients By Race: An Analysis of the Publically Available Mmrf Commpass Study Database

Review of deaths correction methods and quality dimensions of the underlying cause for accidents and violence in Brazil.

This review article aims to perform analysis and critical discussion about the literature on methods correcting mortality from accidents and violence reported to the Brazilian Mortality Information System. We consulted Medline and SciELO databases, as well as the Global Burden of Disease site, using time filter for the 1996-2015 interval. Of the 77 studies identified, we selected 29, and 14 met the corrections production criteria for cases of underreporting: underreporting of deaths in the Mortality Information System, deaths declared as ill-defined causes or deaths from external causes declared with nonspecific codes. We found that the underreporting of external causes was not significantly different from what occurs in total deaths and sometimes was higher in small and medium-sized municipalities. The reclassification of ill-defined causes of death corrected external causes to non-negligible values. The selected studies differ on proposals for correction of unspecified external causes. Evidence supports interventions to improve the quality of data, and the availability of correction procedure of external causes that bring together application conditions.

Opportunities and Challenges in Developing a Cohort of Patients with Type 2 Diabetes Mellitus Using Electronic Primary Care Data.

PurposeTo develop a cohort of patients with T2DM treated with insulin using CPRD to obtain an accurate diagnosis date. This was used to analyse time from T2DM diagnosis to first ever insulin prescription between 01/01/2000 and 30/06/2012, for patients in England and Wales.MethodsPatients aged 18 years and over at diagnosis, were included if prescribed an anti-diabetic drug and were excluded if first diagnosis-specific code was inconsistent with a T2DM diagnosis. Diagnosis codes were split into 8 categories based on whether they related to specific T2DM or non-specific diabetes codes. Patients were excluded if they had non-specific diagnosis codes and were prescribed insulin as their first-ever treatment for diabetes. Descriptive statistics for time from T2DM diagnosis to insulin initiation were calculated.ResultsTwo hundred and fifty-six codes were identified which were consistent with a first-ever diagnosis of T2DM. 7 codes were considered to clearly define a diagnosis of T2DM, which were reported for 64% of patients. The final cohort comprised 11,917 patients and the median time to first insulin prescription from the date of diagnosis was 4.4 years.ConclusionsA clear definition of cohort development is required to compare and interpret results from studies. Use of diagnosis and product codes is essential when examining use of drugs such as insulin, where competing diagnoses need to be considered separately.

Validity of the coding for herpes simplex encephalitis in the Danish National Patient Registry.

BackgroundLarge health care databases are a valuable source of infectious disease epidemiology if diagnoses are valid. The aim of this study was to investigate the accuracy of the recorded diagnosis coding of herpes simplex encephalitis (HSE) in the Danish National Patient Registry (DNPR).MethodsThe DNPR was used to identify all hospitalized patients, aged ≥15 years, with a first-time diagnosis of HSE according to the International Classification of Diseases, tenth revision (ICD-10), from 2004 to 2014. To validate the coding of HSE, we collected data from the Danish Microbiology Database, from departments of clinical microbiology, and from patient medical records. Cases were classified as confirmed, probable, or no evidence of HSE. We estimated the positive predictive value (PPV) of the HSE diagnosis coding stratified by diagnosis type, study period, and department type. Furthermore, we estimated the proportion of HSE cases coded with nonspecific ICD-10 codes of viral encephalitis and also the sensitivity of the HSE diagnosis coding.ResultsWe were able to validate 398 (94.3%) of the 422 HSE diagnoses identified via the DNPR. Hereof, 202 (50.8%) were classified as confirmed cases and 29 (7.3%) as probable cases providing an overall PPV of 58.0% (95% confidence interval [CI]: 53.0–62.9). For “Encephalitis due to herpes simplex virus” (ICD-10 code B00.4), the PPV was 56.6% (95% CI: 51.1–62.0). Similarly, the PPV for “Meningoencephalitis due to herpes simplex virus” (ICD-10 code B00.4A) was 56.8% (95% CI: 39.5–72.9). “Herpes viral encephalitis” (ICD-10 code G05.1E) had a PPV of 75.9% (95% CI: 56.5–89.7), thereby representing the highest PPV. The estimated sensitivity was 95.5%.ConclusionThe PPVs of the ICD-10 diagnosis coding for adult HSE in the DNPR were relatively low. Hence, the DNPR should be used with caution when studying patients with encephalitis caused by herpes simplex virus.

Reimbursement Policies for Carotid Duplex Ultrasound that are Based on International Classification of Diseases Codes May Discourage Testing in High-Yield Groups

To curb increasing volumes of diagnostic imaging and costs, reimbursement for carotid duplex ultrasound (CDU) is dependent on "appropriate" indications as documented by International Classification of Diseases (ICD) codes entered by ordering physicians. Historically, asymptomatic indications for CDU yield lower rates of abnormal results than symptomatic indications, and consensus documents agree that most asymptomatic indications for CDU are inappropriate. In our vascular laboratory, we perceived an increased rate of incorrect or inappropriate ICD codes. We therefore sought to determine if ICD codes were useful in predicting the frequency of abnormal CDU. We hypothesized that asymptomatic or nonspecific ICD codes would yield a lower rate of abnormal CDU than symptomatic codes, validating efforts to limit reimbursement in asymptomatic, low-yield groups. We reviewed all outpatient CDU done in 2011 at our institution. ICD codes were recorded, and each medical record was then reviewed by a vascular surgeon to determine if the assigned ICD code appropriately reflected the clinical scenario. CDU findings categorized as abnormal (>50% stenosis) or normal (<50% stenosis) were recorded. Each individual ICD code and group 1 (asymptomatic), group 2 (nonhemispheric symptoms), group 3 (hemispheric symptoms), group 4 (preoperative cardiovascular examination), and group 5 (nonspecific) ICD codes were analyzed for correlation with CDU results. Nine hundred ninety-four patients had 74 primary ICD codes listed as indications for CDU. Of assigned ICD codes, 17.4% were deemed inaccurate. Overall, 14.8% of CDU were abnormal. Of the 13 highest frequency ICD codes, only 433.10, an asymptomatic code, was associated with abnormal CDU. Four symptomatic codes were associated with normal CDU; none of the other high frequency codes were associated with CDU result. Patients in group 1 (asymptomatic) were significantly more likely to have an abnormal CDU compared to each of the other groups (P<0.001, P<0.001, P=0.020, P=0.002) and to all other groups combined (P<0.001). Asymptomatic indications by ICD codes yielded higher rates of abnormal CDU than symptomatic indications. This finding is inconsistent with clinical experience and historical data, and we suggest that inaccurate coding may play a role. Limiting reimbursement for CDU in low-yield groups is reasonable. However, reimbursement policies based on ICD coding, for example, limiting payment for asymptomatic ICD codes, may impede use of CDU in high-yield patient groups.

Traffic accidents in Belo Horizonte: the view from three different sources, 2008 to 2010.

To analyze the contribution of three data sources in the description of traffic accidents in the city of Belo Horizonte, Brazil. Exploratory study of databases: BHTRANS (metropolitan traffic and transportation authority), Hospital Admissions and Mortality Information Systems, with estimation of proportions, coefficients and odds ratios. Incomplete data was observed in the three sources, especially regarding alcohol consumption by drivers and use of safety equipment. The victim profile among the sources was consistent: young adults, males, motorcycle riders and pedestrians. In addition to the high mortality rate (19.4 per 100.000 inhabitants), an increase in the number of non-fatal accidents was observed. An increase of 34% in hospital admissions and of 53% in hospital costs was evidenced. The motorcycle accident rate is higher than expected given the fleet composition. Male drivers have the highest risk of injury or death; relative to drivers, passengers or pedestrians have a 1,8 times higher risk of death. There was a 12% increase in the number of deaths at the site of the accident, 55% of which showed positive evidence of alcohol use and 50% higher risk of fatal accidents on weekends. Despite some incomplete record keeping and non-specific death registry codes, it was possible to characterize the main factors associated with accidents: elderly pedestrians, motorcycle riders, alcohol consumption and speeding. The study demonstrated the complementarity of the three data sources, with their different goals, and revealed important features of the traffic accident event-chain and victim profile, providing key data for the development of mitigation strategies.

Challenges in Surveillance for Chikungunya Virus (CHIKV) Infection

We describe challenges and lessons learned using biosurveillance methods for identifying Chikungunya (CHIKV) infections. Surveillance was performed using VA ESSENCE, electronic laboratory data and facility reports. As of Aug. 14, 2014, 21 confirmed/probable cases were identified at 10 hospitals. The principal challenges were lack of a specific ICD-9 code for CHIKV, use of non-specific symptom codes at initial and subsequent encounters, lack of CHIKV testing, long turn-around times for results, poor uniformity in test names, and infection control not being notified of suspected/confirmed CHIKV cases. Based on our experience, a combination surveillance strategy using multiple data sources is essential for CHIKV detection.

Pneumocystis Jirovecii Pneumonia (PCP) in Children with Cancer: A Retrospective Cohort Analysis from the Pediatric Health Information System (PHIS) Database, 2004-2009

Background: Pneumocystis jirovecii pneumonia (PCP) is an opportunistic fungal infection that can develop in the setting of deficient cell-mediated immunity. Children with hematologic malignancies and children undergoing immunosuppressive treatment for other types of cancer are at risk of developing PCP. However, the epidemiology of PCP in children with cancer is not well described. We sought to determine the prevalence of PCP in hospitalized children with cancer in the U.S. and to identify risk factors for PCP in this population.Methods: This retrospective cohort study included pediatric patients with newly diagnosed cancer at 45 children’s hospitals in the U.S. between January 1, 2004, and December 31, 2009. Data was obtained from the Pediatric Health Information System (PHIS). Patients were included if they were 0 to 20 years of age and had an index hospitalization with an ICD-9 diagnosis code for a malignant condition (140 to 239.39). Patients who had a benign tumor, >1 cancer type, or non-specific cancer codes, and those who received a hematopoietic stem cell transplant were excluded. Groups were defined for cancer types by ICD-9 codes: acute lymphoblastic leukemia (ALL), acute myeloid leukemia (AML), Non-Hodgkin lymphoma (NHL), Hodgkin disease (HD), central nervous system (CNS), and solid non-CNS tumors. Patients within the cohort who had a diagnosis of PCP (ICD-9 code 136.3) within 3 years of their cancer diagnosis were considered PCP cases. The relative risk for PCP was calculated according to demographics and cancer types. The data were analyzed for trends in the incidence of PCP cases by year, the time to PCP diagnosis following cancer diagnosis, and the regional distribution of PCP in the U.S.Results: A total of 33,067 pediatric cancer patients met the criteria for inclusion in the study. Of these patients, 169 (0.5%) were classified as PCP cases (Table 1). Patients with ALL and AML had the highest relative risks of PCP, when compared with other cancer types. Patients of Asian race had the highest relative risk of PCP, when compared with patients of other races. [Display omitted] Figure 1 depicts that the time to the development of PCP was relatively short in patients with NHL (median 33 days, IQR: 0-253 days) and AML (median 70 days, IQR: 0-149 days). In contrast, PCP was diagnosed later in patients with ALL, (median 347 days, IQR; 168-675 days). The number of new PCP cases did not significantly vary by year of diagnosis. Regional differences in the diagnosis of PCP by the locations of PHIS institutions were not identified. [Display omitted] Conclusions: This study represents the largest cohort analysis of PCP in children with cancer. Among children with cancer who were hospitalized at major U.S. children’s hospitals during the study period, the prevalence of PCP was 0.5%. The relative risk of PCP was increased in patients with leukemia when compared with other cancer types. However, PCP was identified in all cancer types. The variation in time to diagnosis of PCP is hypothesized to be due to differences in the intensity and duration of immunosuppressive therapy by cancer type. DisclosuresNo relevant conflicts of interest to declare.

66 Comparison of Ultrasound and Plain Radiography for the Detection of Long Bone Fractures

2013 were included in this study. Clinical and demographic data was collected and analyzed. Chi squared analysis was used. Results: There were 1,937 patients during the study period who were discharged with a non-specific GI diagnostic code. Of these patients, 49 (2.5%) returned within 72 hours of treatment. There was no difference in the frequency of imaging in the group of patients that returned versus those that did not return (42.8% versus 37%; OR 1.27, 95% CI .72-2.26). Return rate was not affected by the specific use of CT scanning (OR 0.68, 95% CI 0.36 -1.3) or US (OR 1.16, 0.56-2.42) during their first visit. Conclusion: Despite the common provider belief that knowledge of a negative study will reassure patients and ultimately prevent a return visit, to the contrary, this study shows that imaging patients with non-specific abdominal pain does not prevent return. Imaging should be reserved for answering specific clinical questions, and should not be considered a means to preventing a return visit in patients with non-specific abdominal pain.

Use of multiple imputation to correct for bias in lung cancer incidence trends by histologic subtype.

Over the past several decades, advances in lung cancer research and practice have led to refinements of histologic diagnosis of lung cancer. The differential use and subsequent alterations of nonspecific morphology codes, however, may have caused artifactual fluctuations in the incidence rates for histologic subtypes, thus biasing temporal trends. We developed a multiple imputation (MI) method to correct lung cancer incidence for nonspecific histology using data from the Surveillance, Epidemiology, and End Results Program during 1975 to 2010. For adenocarcinoma in men and squamous in both genders, the change to an increasing trend around 2005, after more than 10 years of decreasing incidence, is apparently an artifact of the changes in histopathology practice and coding system. After imputation, the rates remained decreasing for adenocarcinoma and squamous in men, and became constant for squamous in women. As molecular features of distinct histologies are increasingly identified by new technologies, accurate histologic distinctions are becoming increasingly relevant to more effective "targeted" therapies, and therefore, are important to track in patients. However, without incorporating the coding changes, the incidence trends estimated for histologic subtypes could be misleading. The MI approach provides a valuable tool for bridging the different histology definitions, thus permitting meaningful inferences about the long-term trends of lung cancer by histologic subtype.