A web-based tumor registration system for a regional Canine Cancer Registry in Umbria, central Italy.

The Umbria Canine Cancer Registry (CCR) is a web-based platform for cancer registration set up in order to estimate the incidence of spontaneous tumors. It is an integral part of the regional canine demographic registry in which veterinary practitioners and pathologists interact. Veterinary pathologists perform double-blind comparisons and classify neoplasms in an automated classification process using the WHO criteria for canine neoplasms and the ICD-O tumor topographical and morphological keys. Here we describe the organization, on-line procedures and the methods used to assess canine demography, a pre-requisite for accurately estimating the incidence of cancer. In its first 4 years the CCR recruited 4857 cases of suspected tumors, as diagnosed by practitioners, clinics and a veterinary hospital. After the first year the number of enrolled cases increased by 63%, suggesting growing interest from the regional veterinary community.

[Epidemiology of postpartum hemorrhages in the Umbrian population in the years 2006-2017.] / Epidemiologia delle emorragie post partum nella popolazione umbra nel periodo 2006-2017.

INTRODUCTION: Postpartum haemorrhage (PPH) is one of the main causes of mortality and severe maternal morbidity and its incidence is increasing also in Western countries. Aim of this study is to estimate the incidence and the trend of PPH in the Umbrian population using the validated Umbrian health database and to identify possible determinants for the development of PPH. METHODS: The source of the data was the regional Healthcare Database of the Umbria Region. The population of interest was represented by women who gave birth in Umbria between 2006 and 2017. The PPH was identified from the hospital data using the ICD-9-CM 666.x codes. Demographic data, principal and secondary diagnoses and data on maternal morbidity and blood component transfusion were collected. The incidence of PPH was calculated taking into account cases of PPH over the total number of births. The determinants of PPH, the associated morbidity and the variation in the severity of the PPH over time have been identified by logistic regression models. RESULTS: In Umbria, between 2006 and 2017, 93,403 births were registered (69% by vaginal delivery and 31% by caesarean section) and the rate of caesarean sections decreased by about 4%. The incidence of PPH increased three-fold during this period with an increase (p<0.001) of women with PPH who received transfusions. Regarding the caesarean sections, the PPH trend increased by 53% (p=0.3), while in the vaginal deliveries the PPHs increased by 233% (p<0.001). Logistic regression analysis showed that possible risk factors for the occurrence of PPH are maternal morbidity (OR 22.8, 95% CI 18.5-30.0), twin birth (OR 2.0, 95% CI 1.3-3.2) and antepartum haemorrhage (OR 5.7, 95% CI 3.1-10.4). CONCLUSIONS: The incidence of PPH has increased in recent years, while the morbidity associated with PPH has remained substantially unchanged. The study identified several risk factors responsible for PPH that can be used in the monitoring of pregnant women and for planning prevention strategies such as Patient Blood Management.

[Postpartum haemorrhage in Umbria: accuracy of the regional health information system for the code ICD-9-CM 666.x.] / Emorragia post partum in Umbria: accuratezza del sistema informativo sanitario regionale per il codice ICD-9-CM 666.x.

INTRODUCTION: Postpartum haemorrhage (PPH) is the main cause of morbidity and mortality for pregnant women. Administrative databases are useful sources of information for the assessment of PPH and related outcomes, once the corresponding ICD-9-CM code is validated. The objective of the present study is to evaluate the accuracy of the ICD-9-CM code related to PPH. MATERIAL AND METHODS: Source of the data was the Regional Healthcare Database of the Umbria Region. The population of interest were women with at least 20 weeks of gestation that delivered in any hospital in the Umbria Region during 2012-2016. Cases of interest were identified using the ICD-9-CM 666.x code. For validation purposes, both cases (women who delivered and developed PPH) and non-cases (women who delivered without occurrence of PPH) were considered and algorithms proposed. The basic criterion used for the validity of ICD-9-CM codes was the presence of bleeding ≥500 ml. Additional criteria based on values of haemoglobin or transfusion of red blood cells were considered. Sensitivity, specificity and predictive values were calculated. RESULTS: Medical charts of 422 cases and 200 non-cases were examined. Accuracy results for code 666.x related to the presence of bleeding ≥500 ml were: sensitivity 97% (95% CI, 96-99%), specificity 70% (65-76%), positive predictive value (PPV) 79% (76-82%) and negative predictive value (NPV) 95% (91-97%). The best algorithm was the one that, in addition to the basic criterion, considered both the haemoglobin values and red blood cell transfusion: sensitivity 93% (90-95%), specificity 85% (80-90%), PPV 92% (89-94%) and NPV 86% (81-90%). ICD-9 subcodes showed a higher specificity and PPV for immediate bleeding (666.0, 666.1) than delayed or secondary haemorrhage (666.2). CONCLUSIONS: The accuracy data from the present study confirm that the Regional Healthcare Database of the Umbria Region can be used as a reliable source for the evaluation of epidemiological studies relating to PPHs, in order to improve the quality of maternity care.

Diagnostic, preventive and therapeutic evidence in obstetrics for the implementation of patient blood management: a systematic review protocol.

INTRODUCTION: Patientblood management (PBM) is defined as the application of evidence-based diagnostic, preventive and therapeutic approaches designed to maintain haemoglobin concentration, optimise haemostasis and minimise blood loss in an effort to improve patient outcome. We propose a protocol for the assessment of the evidence of diagnostic, preventive and therapeutic approaches for the management of relevant outcomes in obstetrics with the aim to create a framework for PBM implementation. METHODS AND ANALYSIS: Diagnostic, preventive and therapeutic tools will be considered in the gynaecological conditions and obstetrics setting (antenatal care, peripartum care and maternity care). For each condition, (1) clinical questions based on prioritised outcomes will be developed; (2) evidence will be retrieved systematically from electronic medical literature (MEDLINE, EMBASE, the Cochrane Library, Web of Science, and CINAHL); (3) quality of the reviews will be assessed using the AMSTAR (A Measurement Tool to Assess Systematic Reviews) checklist; quality of primary intervention studies will be assessed using the risk of bias tool (Cochrane method); quality of diagnostic primary studies will be assessed using QUADAS-2 (Quality Assessment of Diagnostic Accuracy Studies); (4) the Grading of Recommendations Assessment, Development and Evaluation method will be applied to rate the quality of the evidence and to develop recommendations. ETHICS AND DISSEMINATION: For each diagnostic, preventive or therapeutic intervention evaluated, a manuscript comprising the evidence retrieved and the recommendation produced will be provided and published in peer-reviewed journals. Ethical approval is not required.

Accuracy of colorectal cancer ICD-9-CM codes in Italian administrative healthcare databases: a cross-sectional diagnostic study.

Objectives To assess the accuracy of International Classification of Diseases, Ninth Revision - Clinical Modification (ICD-9-CM) codes in identifying subjects with colorectal cancer. DESIGN: A diagnostic accuracy study comparing ICD-9-CM codes (index test) for colorectal cancers with medical chart (as a reference standard). Case ascertainment based on neoplastic lesion(s) within the colon/rectum and histological documentation from a primary or metastatic site positive for colorectal cancer. SETTING: Administrative databases from the Umbria region, Azienda Sanitaria Locale (ASL) Napoli 3 Sud (NA) region and Friuli Venezia Giulia (FVG) region. PARTICIPANTS: We randomly selected 130 incident patients from each hospital discharge database, admitted between 2012 and 2014, having colorectal cancer ICD-9 codes located in primary position, and 94 non-cases, that is, patients having a diagnosis of cancer (ICD-9 140-239) other than colorectal cancer in primary position. OUTCOME MEASURES: Sensitivity, specificity and predictive values for 153.x code (colon cancer) and for 154.x code (rectal cancer). RESULTS: The positive predictive value (PPV) for colon cancer diagnoses was 80% for Umbria (95% CI 73% to 87%), 81% for NA (95% CI 73% to 88%) and 80% for FVG (95% CI 72% to 87%).The sensitivity ranged from 98% to 99%, while the specificity ranged from 78% to 80% in the three units.For rectal cancer, the PPV was 84% for Umbria (95% CI 77% to 90%), 80% for NA (95% CI 72% to 87%) and 81% for FVG (95% CI 73% to 87%). The sensitivities ranged from 98% to 100%, while the specificity estimates from 79% to 82%. CONCLUSIONS: Administrative databases in Italy can be a valuable tool for cancer surveillance as well as monitoring geographical and temporal variation of cancer practice.

Accuracy of administrative databases in detecting primary breast cancer diagnoses: a systematic review.

OBJECTIVE: To define the accuracy of administrative datasets to identify primary diagnoses of breast cancer based on the International Classification of Diseases (ICD) 9th or 10th revision codes. DESIGN: Systematic review. DATA SOURCES: MEDLINE, EMBASE, Web of Science and the Cochrane Library (April 2017). ELIGIBILITY CRITERIA: The inclusion criteria were: (a) the presence of a reference standard; (b) the presence of at least one accuracy test measure (eg, sensitivity) and (c) the use of an administrative database. DATA EXTRACTION: Eligible studies were selected and data extracted independently by two reviewers; quality was assessed using the Standards for Reporting of Diagnostic accuracy criteria. DATA ANALYSIS: Extracted data were synthesised using a narrative approach. RESULTS: From 2929 records screened 21 studies were included (data collection period between 1977 and 2011). Eighteen studies evaluated ICD-9 codes (11 of which assessed both invasive breast cancer (code 174.x) and carcinoma in situ (ICD-9 233.0)); three studies evaluated invasive breast cancer-related ICD-10 codes. All studies except one considered incident cases.The initial algorithm results were: sensitivity ≥80% in 11 of 17 studies (range 57%-99%); positive predictive value was ≥83% in 14 of 19 studies (range 15%-98%) and specificity ≥98% in 8 studies. The combination of the breast cancer diagnosis with surgical procedures, chemoradiation or radiation therapy, outpatient data or physician claim may enhance the accuracy of the algorithms in some but not all circumstances. Accuracy for breast cancer based on outpatient or physician's data only or breast cancer diagnosis in secondary position diagnosis resulted low. CONCLUSION: Based on the retrieved evidence, administrative databases can be employed to identify primary breast cancer. The best algorithm suggested is ICD-9 or ICD-10 codes located in primary position. TRIAL REGISTRATION NUMBER: CRD42015026881.

Sensitivity and specificity of breast cancer ICD-9-CM codes in three Italian administrative healthcare databases: a diagnostic accuracy study.

OBJECTIVES: To assess the accuracy of International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) codes in identifying patients diagnosed with incident carcinoma in situ and invasive breast cancer in three Italian administrative databases. DESIGN: A diagnostic accuracy study comparing ICD-9-CM codes for carcinoma in situ (233.0) and for invasive breast cancer (174.x) with medical chart (as a reference standard). Case definition: (1) presence of a primary nodular lesion in the breast and (2) cytological or histological documentation of cancer from a primary or metastatic site. SETTING: Administrative databases from Umbria Region, Azienda Sanitaria Locale (ASL) Napoli 3 Sud (NA) and Friuli VeneziaGiulia (FVG) Region. PARTICIPANTS: Women with breast carcinoma in situ (n=246) or invasive breast cancer (n=384) diagnosed (in primary position) between 2012 and 2014. OUTCOME MEASURES: Sensitivity and specificity for codes 233.0 and 174.x. RESULTS: For invasive breast cancer the sensitivities were 98% (95% CI 93% to 99%) for Umbria, 96% (95% CI 91% to 99%) for NA and 100% (95% CI 97% to 100%) for FVG. Specificities were 90% (95% CI 82% to 95%) for Umbria, 91% (95% CI 83% to 96%) for NA and 91% (95% CI 84% to 96%) for FVG.For carcinoma in situ the sensitivities were 100% (95% CI 93% to 100%) for Umbria, 100% (95% CI 95% to 100%) for NA and 100% (95% CI 96% to 100%) for FVG. Specificities were 98% (95% CI 93% to 100%) for Umbria, 86% (95% CI 78% to 92%) for NA and 90% (95% CI 82% to 95%) for FVG. CONCLUSIONS: Administrative healthcare databases from Umbria, NA and FVG are accurate in identifying hospitalised news cases of carcinoma of the breast. The proposed case definition is a powerful tool to perform research on large populations of newly diagnosed patients with breast cancer.

Accuracy of lung cancer ICD-9-CM codes in Umbria, Napoli 3 Sud and Friuli Venezia Giulia administrative healthcare databases: a diagnostic accuracy study.

OBJECTIVES: To assess the accuracy of International Classification of Diseases 9th Revision-Clinical Modification (ICD-9-CM) codes in identifying subjects with lung cancer. DESIGN: A cross-sectional diagnostic accuracy study comparing ICD-9-CM 162.x code (index test) in primary position with medical chart (reference standard). Case ascertainment was based on the presence of a primary nodular lesion in the lung and cytological or histological documentation of cancer from a primary or metastatic site. SETTING: Three operative units: administrative databases from Umbria Region (890 000 residents), ASL Napoli 3 Sud (NA) (1 170 000 residents) and Friuli Venezia Giulia (FVG) Region (1 227 000 residents). PARTICIPANTS: Incident subjects with lung cancer (n=386) diagnosed in primary position between 2012 and 2014 and a population of non-cases (n=280). OUTCOME MEASURES: Sensitivity, specificity and positive predictive value (PPV) for 162.x code. RESULTS: 130 cases and 94 non-cases were randomly selected from each database and the corresponding medical charts were reviewed. Most of the diagnoses for lung cancer were performed in medical departments.True positive rates were high for all the three units. Sensitivity was 99% (95% CI 95% to 100%) for Umbria, 97% (95% CI 91% to 100%) for NA, and 99% (95% CI 95% to 100%) for FVG. The false positive rates were 24%, 37% and 23% for Umbria, NA and FVG, respectively. PPVs were 79% (73% to 83%)%) for Umbria, 58% (53% to 63%)%) for NA and 79% (73% to 84%)%) for FVG. CONCLUSIONS: Case ascertainment for lung cancer based on imaging or endoscopy associated with histological examination yielded an excellent sensitivity in all the three administrative databases. PPV was moderate for Umbria and FVG but lower for NA.

Validating malignant melanoma ICD-9-CM codes in Umbria, ASL Napoli 3 Sud and Friuli Venezia Giulia administrative healthcare databases: a diagnostic accuracy study.

OBJECTIVES: To assess the accuracy of International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) codes in identifying subjects with melanoma. DESIGN: A diagnostic accuracy study comparing melanoma ICD-9-CM codes (index test) with medical chart (reference standard). Case ascertainment was based on neoplastic lesion of the skin and a histological diagnosis from a primary or metastatic site positive for melanoma. SETTING: Administrative databases from Umbria Region, Azienda Sanitaria Locale (ASL) Napoli 3 Sud (NA) and Friuli Venezia Giulia (FVG) Region. PARTICIPANTS: 112, 130 and 130 cases (subjects with melanoma) were randomly selected from Umbria, NA and FVG, respectively; 94 non-cases (subjects without melanoma) were randomly selected from each unit. OUTCOME MEASURES: Sensitivity and specificity for ICD-9-CM code 172.x located in primary position. RESULTS: The most common melanoma subtype was malignant melanoma of skin of trunk, except scrotum (ICD-9-CM code: 172.5), followed by malignant melanoma of skin of lower limb, including hip (ICD-9-CM code: 172.7). The mean age of the patients ranged from 60 to 61 years. Most of the diagnoses were performed in surgical departments.The sensitivities were 100% (95% CI 96% to 100%) for Umbria, 99% (95% CI 94% to 100%) for NA and 98% (95% CI 93% to 100%) for FVG. The specificities were 88% (95% CI 80% to 93%) for Umbria, 77% (95% CI 69% to 85%) for NA and 79% (95% CI 71% to 86%) for FVG. CONCLUSIONS: The case definition for melanoma based on clinical or instrumental diagnosis, confirmed by histological examination, showed excellent sensitivities and good specificities in the three operative units. Administrative databases from the three operative units can be used for epidemiological and outcome research of melanoma.

Validity of ICD-9-CM codes for breast, lung and colorectal cancers in three Italian administrative healthcare databases: a diagnostic accuracy study protocol.

INTRODUCTION: Administrative healthcare databases are useful tools to study healthcare outcomes and to monitor the health status of a population. Patients with cancer can be identified through disease-specific codes, prescriptions and physician claims, but prior validation is required to achieve an accurate case definition. The objective of this protocol is to assess the accuracy of International Classification of Diseases Ninth Revision-Clinical Modification (ICD-9-CM) codes for breast, lung and colorectal cancers in identifying patients diagnosed with the relative disease in three Italian administrative databases. METHODS AND ANALYSIS: Data from the administrative databases of Umbria Region (910,000 residents), Local Health Unit 3 of Napoli (1,170,000 residents) and Friuli--Venezia Giulia Region (1,227,000 residents) will be considered. In each administrative database, patients with the first occurrence of diagnosis of breast, lung or colorectal cancer between 2012 and 2014 will be identified using the following groups of ICD-9-CM codes in primary position: (1) 233.0 and (2) 174.x for breast cancer; (3) 162.x for lung cancer; (4) 153.x for colon cancer and (5) 154.0-154.1 and 154.8 for rectal cancer. Only incident cases will be considered, that is, excluding cases that have the same diagnosis in the 5 years (2007-2011) before the period of interest. A random sample of cases and non-cases will be selected from each administrative database and the corresponding medical charts will be assessed for validation by pairs of trained, independent reviewers. Case ascertainment within the medical charts will be based on (1) the presence of a primary nodular lesion in the breast, lung or colon-rectum, documented with imaging or endoscopy and (2) a cytological or histological documentation of cancer from a primary or metastatic site. Sensitivity and specificity with 95% CIs will be calculated. DISSEMINATION: Study results will be disseminated widely through peer-reviewed publications and presentations at national and international conferences.

Validity of breast, lung and colorectal cancer diagnoses in administrative databases: a systematic review protocol.

INTRODUCTION: Breast, lung and colorectal cancers constitute the most common cancers worldwide and their epidemiology, related health outcomes and quality indicators can be studied using administrative healthcare databases. To constitute a reliable source for research, administrative healthcare databases need to be validated. The aim of this protocol is to perform the first systematic review of studies reporting the validation of International Classification of Diseases 9th and 10th revision codes to identify breast, lung and colorectal cancer diagnoses in administrative healthcare databases. METHODS AND ANALYSIS: This review protocol has been developed according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Protocol (PRISMA-P) 2015 statement. We will search the following databases: MEDLINE, EMBASE, Web of Science and the Cochrane Library, using appropriate search strategies. We will include validation studies that used administrative data to identify breast, lung and colorectal cancer diagnoses or studies that evaluated the validity of breast, lung and colorectal cancer codes in administrative data. The following inclusion criteria will be used: (1) the presence of a reference standard case definition for the disease of interest; (2) the presence of at least one test measure (eg, sensitivity, positive predictive values, etc) and (3) the use of data source from an administrative database. Pairs of reviewers will independently abstract data using standardised forms and will assess quality using a checklist based on the Standards for Reporting of Diagnostic accuracy (STARD) criteria. ETHICS AND DISSEMINATION: Ethics approval is not required. We will submit results of this study to a peer-reviewed journal for publication. The results will serve as a guide to identify appropriate case definitions and algorithms of breast, lung and colorectal cancers for researchers involved in validating administrative healthcare databases as well as for outcome research on these conditions that used administrative healthcare databases. TRIAL REGISTRATION NUMBER: CRD42015026881.