Icd 10 Code for Family History of Pancreatic Cancer
Globe J Gastroenterol. 2019 Oct vii; 25(37): 5619–5629.
Accuracy of an administrative database for pancreatic cancer by international classification of disease 10th codes: A retrospective large-accomplice report
Young-Jae Hwang
Departments of Internal Medicine, Seoul National University Bundang Hospital, Seoungnam 13620, South Korea
Seon Mee Park
Section of Internal Medicine, Chungbuk National University College of Medicine and Medical Research Plant, Cheongju 28644, Republic of korea
Soomin Ahn
Departments of Pathology, Seoul National University Bundang Hospital, Seoungnam 13620, Republic of korea
Jong-Chan Lee
Departments of Internal Medicine, Seoul National University Bundang Infirmary, Seoungnam 13620, South Korea
Young Soo Park
Departments of Internal Medicine, Seoul National University Bundang Hospital, Seoungnam 13620, South Korea
Nayoung Kim
Departments of Internal Medicine, Seoul National University Bundang Infirmary, Seoungnam 13620, Republic of korea. rk.ca.uns@94mikan
Department of Internal Medicine and Institute of Liver Research and Tumor Microenvironment Global Core Research Centre, Seoul National Academy College of Medicine, Seoul 08826, Republic of korea
Received 2019 Jul 22; Revised 2019 Sep 3; Accepted 2019 Sep 11.
Abstract
Background
Korean National Health Insurance (NHI) claims database provides large-cohort. However, studies regarding accuracy of administrative database for pancreatic cancer (PC) have not been reported. We aimed to place accuracy of NHI database regarding PC classified by international classification of disease (ICD)-10 codes.
AIM
To identify the accurateness and usefulness of administrative database in PC and the accurate ICD codes for PC with location.
METHODS
Study and control groups were collected from 2003 to 2016 at Seoul National University Bundang Infirmary. Cases of PC were identified in NHI database past international classification of diseases, 10th revision edition (ICD-10 codes) supported with V codes. V code is issued by medical doctors for covering 95% of medical cost by Korean government. According to pathologic reports, definite or possible diagnoses were defined using medical records, images, and pathology.
RESULTS
A total of 1846 cases with PC and controls were collected. Among PC, simply 410 (22.2%) cases were identified as specific cancer sites including caput in 234 (12.seven%) cases, tail in 104 (5.6%) cases and body in 72 (3.9%) cases. Amongst PC, 910 (49.3%) cases were diagnosed past definite criteria. Most of these were adenocarcinoma (98.0%). The rates of definite diagnosis of PC were highest in caput (70.i%) followed by torso (47.2%) and tail (43.3%). Imitation-positive cases were pancreatic cystic neoplasm and metastasis to the pancreas. In terms of the overall diagnosis of PC, sensitivity, specificity, positive predictive value, and negative predictive value were 99.95%, 98.72%, 98.lxx%, and 99.95%, respectively. Diagnostic accuracy was similar both in terms of diagnostic criteria and tumor locations.
CONCLUSION
Korean NHI claims database collected according to ICD-10 code with V code for PC showed expert accuracy.
Keywords: Korean national health insurance, Accuracy, Pancreatic cancer, International classification of disease, Sensitivity, Specificity
Core tip: International classification of diseases, tenth revision edition (ICD-10 codes) of pancreatic cancer in an administrative database are acceptable for use for population-based large-cohort studies. To enhance the diagnostic accuracy, we recommend patient identification by the ICD-10 lawmaking with tumor location information.
INTRODUCTION
Pancreatic cancer (PC) has a very poor prognosis considering nearly are diagnosed at advanced stages, are inoperable state due to invasion of next arteries, or are intractable to chemotherapy[1-3]. Accurate diagnosis of PC remains challenging despite the widespread utilize of endoscopic ultrasound-guided fine needle aspiration (EUS-FNA) and biopsy. Therefore, pathological diagnosis of PC is non ever possible, and almost are diagnosed based on clinical features including image findings, clinical class, and laboratory data.
Location of primary PC is of import for prognosis[iv]. Patients with PC in head showed a 5% increased survival benefit every bit compared with PC in trunk or tail[4]. It may be associated with early symptom of PC in the head by obstruction of bile duct or pancreatic duct. Further inquiry is needed nigh epidemiology and risk factor of PC in body or tail for screening and early on diagnosis. If the primary location of PC is well described in database, information technology might be easier to practise research for PC.
Recently, an administrative database has been widely used for medical research[5-8]. The administrative database includes personal medical information of a large number of the population with long-term follow-upwards. In addition, administrative database can provide like shooting fish in a barrel access for study of PC location such as identification of information regarding this PC location. For proper estimation of the results derived from this database, the reliability on the database is critical. All the same, their accuracy in identifying cancer patients for the claims databases collect data for the purposes of reimbursement remains in doubtfulness[9]. Furthermore, there have been limited studies regarding accuracy and usefulness of the administrative database[9-eleven].
The Korea National Wellness Insurance System (NHIS) contains a complete set of health information pertaining to 50 million members[12]. The source of the NHIS is the Health Insurance Review and Assessment (HIRA) database, including all insurance claims information of approximately 97% of the Korean population. In this database, the proper name of the affliction is usually coded according to the international classification of diseases, 10th revision edition (ICD-10 lawmaking) published by the World Health Arrangement[13,xiv]. Straight validation for the accurateness betwixt the administrative dataset and NHIS data is impossible because of the Personal Information Protection Act in Korea. Therefore, validation for accuracy and usefulnessof diagnostic codes could only be performed at individual hospitals where the diagnosis of each disease was performed and reported to HIRA for insurance claims. Furthermore even though ICD-x code includes the information for location of PC sometimes information technology is difficult to define the location of PC. In this situation ICD-10 code without location of PC is used by medical doctors. If current situation is analyzed, it might be good information for approaching the patients with PC.
From this background nosotros aimed to evaluate the accuracy and usefulness of authoritative database in PC. To certify the accuracy of diagnosis, we calculated the sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) of PC by ICD-10 codes compared to controls[xv]. In addition, we aimed to identify the location of PC in particular using ICD-x codes and electronic medical records (EMR) to ascertain how much the doctors insert the authentic ICD codes for PC with location.
MATERISALS AND METHODS
Data source
From May 2003 to December 2016, cases of PC were retrospectively collected using the Seoul National Academy Bundang Infirmary (SNUBH) Clinical Data Warehouse (CDW)[16], which was its own database analysis program. The EMR system contains information on the visiting hospital departments, the main diagnoses and surgical and diagnostic procedures for each patient[17]. In addition, it includes pathologic results of specimens and imaging modalities, including computerized tomography (CT), endoscopic retrograde cholangiopancreatography (ERCP), EUS, magnetic resonance imaging (MRI), and positron emission tomography (PET)[three,18-21].
Written report population
Information regarding patients, including hospital visit dates, subject characteristics, diagnostic procedures, pathologic results, and surgeries was collected. These information was easily obtained from administrative database. Other hospital medical data were identified though the uploaded database in SNUBH EMR. After blessing of the study protocol by the Ideals Committee at SNUBH (IRB number B-1701/378-105), a listing of patients with PC according to the ICD-x code as chief diagnosis was caused: (1) C25.0-25.3 (malignant neoplasm of pancreas at caput, torso, tail, and duct, respectively); (2) C25.4 (Malignant neoplasm of endocrine pancreas); and (iii) C25.7-9 (malignant tumour of pancreas at other parts, overlapping lesion, and unspecified, respectively)[22]. Then, searched cases were checked as being registered as V codes in the NHIS to confirm diagnostic codes[23]. The Five code is a special code for patients with any ICD-x cancer codes in Republic of korea, established by the Korean Ministry of Wellness and Welfare in 2008. Cancer patients who are registered in the NHIS have issued a V code and are reimbursed at 95% of the medical cost by the Korean regime for 5 years. Control cases are defined every bit individuals without ICD-10 codes for PCs (C25.0-25.9) during the study periods, who experience work-up pathways similar to those of PC, including images (CT, MRI, ERCP, or EUS) and surgery.
Analyzing accuracy of PC diagnosis from administrative database
Medical records of the study and command groups were analyzed to identify definite and possible diagnostic criteria. Definite diagnoses were made co-ordinate to pathologic reports compatible with PC[24-26]. Possible diagnoses were made according to image findings, clinical courses, or increased CA 19-9 > 100 U/m compatible with PC[three,21,27-29]. Typical image finding of PC was defined as focal hypo-attenuated lesions, pancreatic ductal dilation, distal pancreatic parenchymal cloudburst, and interest of the surrounding vascular structures or other organs on radiologic examinations (Table 1 and Figure 1)[30-32].
Table 1
Diagnostic criteria of pancreatic cancer
| Diagnostic criteria | Methods | Positive finding |
| Definite criteria | ||
| Pathologic analysis | Endoscopy, ERCP, EUS-FNA, Surgery | Adenocarcinoma Mucinous carcinoma Adenosquamous carcinoma Other cancerous neoplasm |
| Possible criteria | ||
| Imaging finding | CT, MRI, ERCP, MRCP, EUS, endoscopy, PET | Focal hypo-adulterate lesion Pancreatic duct dilation Distal pancreatic parenchymal atrophy Interest of the surrounding vascular structures or other organs |
| Clinical features | Medical tape | Clinical courses compatible with PC |
| Tumor marking | CA19-9 | > 100 U/mL |
| αFP | To exclude other malignancies including hepatocellular carcinoma | |
Proposed study algorithm for the inclusion and nomenclature of subjects. ICD: International classification of diseases; PC: Pancreatic cancer; EUS: Endoscopic ultrasound; ERCP: Endoscopic retrograde cholangiopancreatography; CT: Computerized tomography; MRI: Magnetic resonance imaging; PET: Positron emission tomography.
In the definite diagnosis grouping, cancer prison cell types (adenocarcinoma, adenosquamous carcinoma, or neuroendocrine tumor) and methods of pathologic diagnosis through surgery, endoscopic biopsy or FNA were analyzed (Tables 1 and two)[25,33]. In the possible diagnosis grouping, we examined reports of images (CT, MRI, ERCP, EUS, endoscopy, and PET) by a radiologist or medical records of a physician's reading of the images. We used serum levels of CA 19-9 to differentiate PC from other cancers[21,29]. To heighten the study reliability, three reviewers carefully examined medical records and compared the final decisions for each case. For discordant cases, they discussed the cases and reached consensus. Afterward reviewing medical records and classifying each case, the sensitivity, specificity, PPV, and NPV with 95% confidence intervals (CI) were calculated. We besides compared diagnostic power according to cancer sites at the head (C25.0), body (C25.ane) and tail (C25.2). In addition, we analyzed patients with ICD 10-lawmaking of PC with chief location (C25.0, C25.one, and C25.2).
Table 2
Cancer cell type of pancreatic cancer
| Adenocarcinoma | Adeno-squamous carcinoma | Neuroendocrine tumor | Full | |
| C250 | 163 | 0 | ane | 164 |
| C251 | 33 | 0 | 0 | 33 |
| C252 | 45 | 0 | 0 | 45 |
| C253 | 2 | 0 | 0 | ii |
| C254 | 2 | 0 | 0 | 2 |
| C257 | one | 0 | 0 | ane |
| C259 | 640 | 3 | fourteen | 657 |
| 886 (98.0)1 | iii (0.3) | 15 (1.7) | 904 |
RESULTS
Characteristics of cases diagnosed every bit PC by the international nomenclature of diseases, 10th revision edition
A total of 1846 subjects were identified as registered with ICD-ten codes for PC at the SNUBH during the study menstruation (Tabular array 3). Among PC, 1428 (77.4%) cases were registered every bit unspecified PC, and only 410 (22.2%) cases could be identified with specific cancer sites. PC in the caput [234, (12.seven%)] was the most mutual, followed past the tail [104, (v.half-dozen%)] and body [72, (3.9%)]. Proportions of PC cases in the pancreatic duct, neuroendocrine tumor, or overlapping were very rare, with but 0.iii%, 0.i%, or 0.1%, respectively. Primary cancer location couldn't be identified in patients with C25.9 [1428, (77.4%)]. In these cases with C25.9, we carefully examined all medical records ane by one to place primary cancer location.
Table iii
Characteristics of patients with pancreatic cancer co-ordinate to the international classification of diseases, 10thursday revision edition
| Parameters | N (%) | C250 | C251 | C252 | C253 | C254 | C257 | C259 |
| Number of patients | 1846 | 234 (12.7)2 | 72 (iii.ix) | 104 (5.6) | 5 (0.3) | 2 (0.1) | 1 (0.one) | 1428 (77.4) |
| Age at diagnosis | 65.22 ± 11.971 | 64.72 ± x.14 | 63.39 ± x.48 | 65.43 ± xi.32 | 65.20 ± 11.08 | 70.l ± iv.95 | 45.00 ± 0.00 | 65.39 ± 12.35 |
| Gender (male: Female person) | 1116:730 | 150:84 | 45:27 | 52:52 | i:four | 2:0 | 1:0 | 865:563 |
| Diagnostic criteria | ||||||||
| Definite | 910 (49.3) | 164 (70.ane) | 34 (47.2) | 45 (43.three) | 2 (40.0) | two (100.0) | 1 (100.0) | 662 (46.4) |
| Possible | 936 (l.7) | 70 (29.nine) | 38 (52.8) | 59 (56.7) | 3 (threescore.0) | 0 (0.0) | 0 (0.0) | 766 (53.6) |
| Methods of pathologic diagnosis (northward = 910) | ||||||||
| ERCP or endoscopy | 163 (17.nine) | 34 (twenty.7) | 2 (5.nine) | viii (17.8) | 0 (0.0) | 0 (0.0) | 0 (0.0) | 119 (18.0) |
| EUS-FNA or percutaneous biopsy | thirty (3.3) | four (2.four) | 0 (0.0) | ii (4.four) | 0 (0.0) | 0 (0.0) | 0 (0.0) | 26 (3.ix) |
| Surgery | 717 (78.8) | 126 (76.eight) | 32 (94.1) | 35 (77.8) | ii (100.0) | ii (100.0) | i (100.0) | 517 (78.1) |
| CA19-ix > 100 U/L | ||||||||
| Yes | 684 (37.1) | 95 (40.6) | 29 (40.3) | 44 (42.iii) | 1 (20.0) | 0 (0.0) | 0 (0.0) | 515 (36.1) |
| No | 514 (27.8) | 63 (26.9) | 24 (33.3) | 23 (22.1) | one (xx.0) | 1 (50.0) | 0 (0.0) | 402 (28.2) |
| Missing | 648 (35.1) | 76 (32.five) | 19 (26.4) | 37 (35.half dozen) | 3 (60.0) | 1 (50.0) | 1 (100.0) | 511 (35.eight) |
Among PC, 910 (49.three%) cases had pancreatic pathologic results associated with the definite diagnostic criteria and classified as definite diagnosis grouping. Other 936 (50.vii%) cases were classified every bit possible diagnosis group. Pathologic diagnosis was accomplished by surgery in 717 (78.8%) cases, by ERCP or endoscopy in 163 (17.9%) cases, and by EUS-FNA or percutaneous biopsy in 30 (iii.5%) cases. Amidst 1198 cases with serum levels of CA19-nine, 684 (57.i%) cases had elevated levels (> 100 UL).
Diagnostic accuracy of PC by the international nomenclature of diseases, xth revision edition in the administrative database
Nosotros analyzed accurateness of ICD-10 codes of PC by definite or possible diagnostic criteria (Table 4). Among 910 cases with pathologic diagnosis, 904 cases satisfied definite diagnostic criteria of PC. Pathologic diagnoses were adenocarcinoma in 886 (98.0%) cases, adenosquamous carcinoma in three (0.3%), and neuroendocrine tumor in 15 (1.7%) cases. Six cases who were identified as faux-positives, were pancreatic cystic neoplasms, including serous cystic neoplasms, mucinous cystic neoplasms and intraductal pancreatic mucinous neoplasms (Table three). Among 938 cases with possible diagnoses, 924 subjects satisfied possible diagnostic criteria for PC. Xiv cases identified as false-positive were pancreatic metastasis from other main cancers in vi cases, pancreatic cystic neoplasms in 5 cases, pancreatitis in two cases, and accessory spleen in 1 instance.
Table four
Diagnostic accuracy of pancreatic cancer diagnosed past the international classification of diseases, 10th revision edition in the administrative database
| Condition of PC | Full | |||
| Positive | Negative | |||
| Definite diagnostic criteria | ||||
| ICD codes of PC | Issue positive | True positive | Simulated positive | 910 |
| 904 | half-dozen | |||
| Result negative | False negative | True negative | 1846 | |
| 1 | 1845 | |||
| Total | 905 | 1851 | 2756 | |
| Possible diagnostic criteria | ||||
| ICD codes of PC | Event positive | Truthful positive | False positive | 936 |
| 918 | 18 | |||
| Outcome negative | Imitation negative | True negative | 1846 | |
| 1 | 1845 | |||
| Total | 919 | 1863 | 2782 | |
| Overall diagnostic criteria | ||||
| ICD codes of PC | Outcome positive | True positive | Simulated positive | 1846 |
| 1822 | 24 | |||
| Outcome negative | Simulated negative | True negative | 1846 | |
| i | 1845 | |||
| Total | 1823 | 1869 | 3692 | |
Amidst 1846 cases of control, only 1 example of PC was identified (Table 4). This patient underwent distal pancreatectomy because of a pancreatic tail mass and pancreatic ductal dilatation on CT scan. Pathologic diagnosis was invasive carcinoma originating from an intraductal papillary mucinous tumour of the pancreas. This case should be coded equally PC; even so, information technology was registered as a beneficial neoplasm of the pancreas (D13.6)[34,35].
The diagnostic accuracy of PC differed according to tumor sites (Table v). The rate of definite diagnosis in the pancreas head was 70.0%, while those in pancreas tail and body were 46.2% and 43.1%, respectively. Incorrect diagnoses including false-positives and false–negatives were ane.4% for pancreatic body cancer, 1.0% for pancreatic tail cancer, and 0% for pancreatic head cancer.
Table five
Diagnostic accuracy of pancreatic cancer according to tumor sites by the international classification of diseases, 10th revision edition
| ICD codes | Overall diagnosis | Definite diagnosis | Possible diagnosis | ||||||
| True (+)ane | False (+)two | Total | True (+) | Simulated (+) | Total | Truthful (+) | False (+) | Total | |
| Cell types | 234 | 0 | 234 | 164 | 0 | 164 | 70 | 0 | lxx |
| C251 | 71 | i | 72 | 30 | 1 | 31 | 41 | 0 | 41 |
| C252 | 104 | 0 | 104 | 48 | 0 | 48 | 56 | 0 | 56 |
| C253 | 5 | 0 | v | ii | 0 | ii | 3 | 0 | 3 |
| C254 | 2 | 0 | 2 | ii | 0 | two | 0 | 0 | 0 |
| C257 | 1 | 0 | 1 | 1 | 0 | 1 | 0 | 0 | 0 |
| C259 | 1405 | 23 | 1428 | 657 | 5 | 662 | 748 | 18 | 766 |
| 1822 | 24 | 1846 | 904 | 6 | 910 | 918 | 18 | 936 | |
Accuracy of the international classification of diseases, 10th revision edition of PC in the authoritative database
Calculated statistical values are summarized in Table 6. For overall diagnostic criteria of PC, the sensitivity and specificity of ICD-10 codes for PC were 99.95% (95%CI: 99.94-99.95) and 98.72% (95%CI: 98.70-98.73), respectively. The PPV and NPV were 98.70% (95%CI: 98.68-98.72) and 99.95% (95%CI: 99.94-99.95), respectively. For definite diagnostic criteria of PC, the sensitivity and specificity of ICD-10 codes for PC were 99.89% (95%CI: 99.88-99.90) and 99.68% (95%CI: 99.67-99.68), respectively. The PPV and NPV were 99.34% (95%CI: 99.32-99.36) and 99.95% (95%CI: 99.94-99.95), respectively. For possible diagnostic criteria for PC, the sensitivity and specificity were 99.89% (95%CI, 99.88-99.ninety) and 99.03% (99.02-99.05), respectively. The PPV and NPV were 98.08% (98.05-98.11) and 99.95% (99.94-99.95), respectively.
Table 6
Diagnostic ability of international nomenclature of diseases, xth revision edition for pancreatic cancer
| Overall diagnosis | Definite diagnosis | Possible diagnosis | ||||
| Betoken guess (%) | 95%CI (%) | Point approximate (%) | 95%CI (%) | Signal estimate (%) | 95%CI (%) | |
| Sensitivity | 99.95 | 99.94-99.95 | 99.89 | 99.88-99.90 | 99.89 | 99.88-99.90 |
| Specificity | 98.72 | 98.70-98.73 | 99.68 | 99.67-99.68 | 99.03 | 99.02-99.05 |
| Positive predictive value | 98.70 | 98.68-98.72 | 99.34 | 99.32-99.36 | 98.08 | 98.05-98.11 |
| Negative predictive value | 99.95 | 99.94-99.95 | 99.95 | 99.94-99.95 | 99.95 | 99.94-99.95 |
Give-and-take
This study demonstrated that ICD-10 codes for PC in the authoritative database are valid for employ in population-based large-cohort studies. Although one-half of the cases were diagnosed by clinical and radiological features, they showed loftier diagnostic accuracy. Our results suggest the reliability of previous big-cohort studies using the administrative database in Republic of korea.
Administrative big databases from various disease registries have been used for population-based studies. Yet, the quality of a database may be suggested by the quotation of previous studies[36,37] or by demonstrating like trends in national estimates[38] instead of validation of their database. Jon et al[39] studied cancer trends in liver, gallbladder, bile duct, and pancreas in an elderly population in Kingdom of denmark. They identified cases by ICD-x codes using the NORDCAN database, widely used in a previous study[40], without validation.
Previous studies for accuracy of ICD-ix codes revealed that interpretation of administrative databases relying only on ICD-9 codes requires caution. Arous et al[8] identified a total of 1107 PC patients past ICD-9 codes from institutional health intendance information arrangement (HIS)-linked data sets and surgical databases. They reviewed all patients manually to validate the diagnoses. Analysis regarding pancreatic pathology revealed that 80.3% of patients had true pancreatic neoplasms and nineteen.7% had other pancreatic pathologies. When they used but the HIS-linked dataset, only 36.3% of patients were consistent with pancreatic neoplasms. Friedlin et al[9] compared the diagnostic accuracy of ICD-9 codes and natural linguistic communication processing (NLP) technology to identify PC in a cohort of pancreatic cysts. They reported that ICD-ix codes achieved lower specificity than did the NLP method (46% and 94%, respectively) in spite of the high sensitivity for identifying PC by both ICD-9 codes and NLP (95% and 84%, respectively).
Our study identified a study group of PC past ICD-10 codes past adding V lawmaking using two affliction registries, the SNUBH database and the NHIS. Previous population-based large-cohort studies identified cancer populations by both V code and ICD-ten codes[41,42]. They reported the usefulness of the NHIS database collected by Five code in Republic of korea[41,42]. Seo et al[42] compared the cancer incidence rates found in the NHIS against in the National Cancer Registry of Korea. The results showed similar overall cancer incidences as well equally age-, sex activity-, and disease-specific rates in both databases.
The reason why we tried to place the accurateness ofICD-10 code for PC registered in the NHIS in the present study was considering the disease entity of PC is difficult to diagnose. We used two disease registries, the SNUBH database and the NHIS, to identify PC cases and controls. We analyzed the diagnostic accuracy according to definite diagnostic criteria in the presence of pathologic reports. Although the rates of pathologic diagnosis were only 49.3%, they achieved a high sensitivity of 99.89%, specificity of 99.68%, PPV of 99.34%, and NPV of 99.95%. These results provide scientific evidence of the results of previous studies using the administrative database. The rates of definite diagnosis and identification of specific cancer sites were higher for pancreatic head cancer (n = 163) than for pancreatic body (n = 33) or tail (n = 45) cancers. These results suggest that pancreatic head cancer is detected earlier and specimens are obtained more easily than for other sites[28]. In addition, we suggest that it is rather difficult to diagnose pancreatic body or tail cancer, respectively, based on pathologic finding.
Half of the cases registered every bit PC by ICD-10 codes were validated by possible diagnostic criteria. Because obtaining pancreatic specimens by non-surgical methods is difficult and most would not be candidates for surgery. Only xv-xx pct of patients could be candidates for surgery[iv]. In our study, 717 (38.8%) patients got pancreatectomy. In patients who were not candidates of surgery or procedure because of advanced stages, PC was diagnosed only past clinical, radiologic or serologic features. For the diagnostic accuracy of PC we did non absolutely depend on the level of CA19-9. Instead we used tumor markers of CA19-nine and αFP to differentiate them from other cancer such every bit hepatocellular carcinoma when prototype findings and clinical symptoms were insufficient to diagnose PC. Cases registered as PC by ICD-10 codes without pathologic confirmation achieved a high sensitivity of 99.89%, specificity of 99.03%, PPV of 98.08%, and NPV of 99.95%.
We analyzed fake-positive and false-negative cases. Cases with incorrect diagnostic pathologic codes were pancreatic cystic neoplasm. Malignant transformation tin can occur in premalignant pancreatic cystic neoplasm. The differential diagnosis between them is very difficult[36]. Among cases with possible diagnoses, the wrong diagnosis was caused by pancreatic metastases, pancreatic cystic neoplasm, pancreatitis, or ectopic next organs. PC was difficult to differentiate from invasion, metastasis from adjacent organs or benign cystic lesion.
Nosotros found that diagnosis according to cancer sites was not authentic in spite of the loftier overall diagnostic accuracy for PC. Unspecified PC (C25.9) comprised 77.4% of all PC, and near of the false-positive cases (23 out of 24) were recorded as C25.9. Therefore PC by ICD-10 code adding a V-code in the NHIS data was not sufficient to report cancer sites. For the authentic study regarding primary PC location, nosotros excluded PC patients of C25.ix or examined these patients ane by 1. If patients with C25.9 are excluded, the advantages of large administrative database disappear. If patients with C25.9 need to exist checked primary cancer location individually, the advantage of easy access for medical information is eliminated. Both methods reduce the usefulness of administrative database. So we should endeavour to fill in the ICD-10 codes with primary location of PC. Another weak indicate of PC coded by ICD-10 in the NHIS data was that it was not acceptable for evaluation of neuroendocrine tumors. All neuroendocrine tumors were coded as C25.0 or C25.9, whereas they should be coded as C25.iv. Furthermore, two adenocarcinoma cases were coded as C24.4 and should take been coded every bit C25.4. For the study for accuracy of diagnostic codes in the authoritative database, institutions crave two conditions: A high burden of cancer patients and a well-established CDW system. SNUBH might exist an adequate hospital to perform this study because of its comprehensive EMR arrangement[8]. SNUBH developed an in-house comprehensive EMR in 2003. The warehouse system provides piece of cake access to diagnostic information for research[8,sixteen]. In add-on, SNUBH is a tertiary referral infirmary to which regional hospitals would refer patients; therefore, sufficient numbers of PC cases would be enrolled in this study to enhance the ability of the written report results. To satisfy statistical requirements (α = 0.05, 1-β = 0.95, and effect size 0.1), more one 1000 cases are needed. The size of our study group was sufficient to fulfill the statistical criteria. We provided a new written report model for evaluating the accuracy and usefulnessof large administrative databases. Many studies using large administrative databases of PC have been washed, and our study could support the reliability of these studies[10,37-twoscore,43]. To enhance the reliability of studies with large administrative databases, our study could be cited as a reference.
Our study has several limitations. One-half of cases were diagnosed by possible diagnostic criteria without pathologic confirmation. Pathologic diagnosis of PC is sometimes impossible because of poor patient weather and technical difficulty. Therefore, if we adopted simply definite diagnostic criteria of PC for accuracy of diagnosis, selection bias could occur. Another limitation was that the written report was done just in a single hospital, SNUBH. The diagnostic accuracy might exist increased in a third referral hospital rather than a multicenter study. Because well-nigh PC cases are treated in referral hospitals in S Korea, we believe that our data may correspond the entire PC data of the NHIS in Republic of korea. In spite of this limitation, our study demonstrated the excellent diagnostic accuracy of the PC data of the NHIS.
In conclusion, ICD-10 codes of PC in an administrative database are acceptable for use for population-based large-accomplice studies. To prove reliability of administrative database, we examined subjects dividing two groups, definite and possible diagnosis. In add-on, nosotros analyzed both disease registries, SNUBH and NHIS. This study as well compared with command group for calculating sensitivity, specificity, PPV and NPV.
To identify usefulness of database, we examined cancer location. If researchers could become information of PC site through only ICD-x code, they can perform the study more easily.
To enhance the diagnostic accuracy, nosotros recommend patient identification by the ICD-10 lawmaking with tumor location information and V-code system. From this, we preserved huge administrative database without exclusion. More researches with multiple institutions and various diseases should exist needed to practice researches with administrative database.
Commodity HIGHLIGHTS
Research background
Pancreatic cancer (PC) is usually diagnosed at avant-garde stages, resulting in the poor prognosis. Large-cohort studies should be performed to evaluate epidemiology and prognosis of PC. However, at that place are non enough researches about the accuracy of authoritative database to avoid coding discrepancies. This study identified accuracy of the authoritative large-cohort database of PC. This study is important to back up the validation of other large accomplice study for PC.
Research motivation
Administrative database was useful for research because of easy access and much information. So, authoritative database has been widely used for medical research. Nonetheless accurateness of the administrative database may be trouble. In addition, it was hard to perform written report to identify this. We tried to examine each case and bear witness accuracy of database of PC. Future study using authoritative database of PC should be supported by this study.
Enquiry objectives
We evaluated the accuracy and usefulness of administrative database in PC. In addition, we identified much the doctors insert the authentic ICD codes for PC with location.
Inquiry methods
We evaluated the diagnostic accuracy of PC co-ordinate to tumor sites from total of 1846 cases with PC and controls. To heighten the study reliability, three reviewers carefully examined medical records and compared the terminal decisions for each case. After reviewing, we calculated the sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV). In addition, nosotros analyzed patients with ICD x-code of PC with principal location.
Research results
Among PC, 1428 (77.4%) cases were registered as unspecified PC, and only 410 (22.2%) cases could be identified with specific cancer sites. For overall diagnostic criteria of PC, the sensitivity and specificity of ICD-10 codes for PC were 99.95% and 98.72%, respectively. The PPV and NPV were 98.70% and 99.95%, respectively.
Enquiry conclusions
We showed accuracy of administrative database of PC in seoul national academy Bundang infirmary. In addition, we identified the location of PC to usefulness of database. Authoritative database is useful and important for inquiry. However, validation of database is necessary. From this consequence, study based on authoritative database might be reliable. Time to come study with administrative database of PC could receive credibility from this result. In add-on, this written report presented a research method how to identify validation of administrative database.
Enquiry perspectives
We thought that future report involved multiple institute should be planned. In add-on, it is important to get together information in a unified way. Nosotros call up there is a demand for researches for accuracy of administrative database on other disease. These researches should be necessary for studies base on administrative database.
Footnotes
Institutional review board statement: This study was approved by the institutional review board of the Ethics Commission of Seoul National University Bundang Hospital.
Informed consent statement: Patients were not required to give informed consent to the study because our study was done retrospectively. Information for study were obtained after each patient agreed to treatment.
Conflict-of-interest statement: The authors have no conflicts of involvement to disclose.
Data sharing statement: To gain admission to data, information requestors will need to sign a information admission agreement. Proposals should be directed to the Ethics Committee of Seoul National University Bundang Infirmary.
STROBE statement: The guidelines of the STROBE statement take been adopted.
Peer-review started: July 22, 2019
Get-go decision: August 27, 2019
Commodity in press: September 11, 2019
Specialty type: Gastroenterology and hepatology
Country of origin: South Korea
Peer-review report nomenclature
Grade A (Excellent): 0
Form B (Very good): B
Form C (Good): C
Form D (Fair): 0
Grade Eastward (Poor): 0
P-Reviewer: Caputo D, Sunday SY S-Editor: Tang JZ L-Editor: A E-Editor: Ma YJ
Contributor Data
Young-Jae Hwang, Departments of Internal Medicine, Seoul National University Bundang Hospital, Seoungnam 13620, South Korea.
Seon Mee Park, Department of Internal Medicine, Chungbuk National University College of Medicine and Medical Research Establish, Cheongju 28644, South Korea.
Soomin Ahn, Departments of Pathology, Seoul National Academy Bundang Infirmary, Seoungnam 13620, Republic of korea.
Jong-Chan Lee, Departments of Internal Medicine, Seoul National University Bundang Hospital, Seoungnam 13620, S Korea.
Young Soo Park, Departments of Internal Medicine, Seoul National University Bundang Hospital, Seoungnam 13620, Due south Korea.
Nayoung Kim, Departments of Internal Medicine, Seoul National University Bundang Hospital, Seoungnam 13620, South Korea. rk.ca.uns@94mikan.. Section of Internal Medicine and Institute of Liver Research and Tumor Microenvironment Global Cadre Research Middle, Seoul National University Higher of Medicine, Seoul 08826, South korea.
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Source: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6785515/
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