Toward an all-inclusive trauma system in Central South Ontario: development of the Trauma-System Performance Improvement and Knowledge Exchange (T-SPIKE) project.

Background: There is currently no integrated data system to capture the true burden of injury and its management within Ontario's regional trauma networks (RTNs), largely owing to difficulties in identifying these patients across the multiple health care provider records. Our project represents an iterative effort to create the ability to chart the course of care for all injured patients within the Central South RTN. Methods: Through broad stakeholder engagement of major health care provider organizations within the Central South RTN, we obtained research ethics board approval and established data-sharing agreements with multiple agencies. We tested identification of trauma cases from Jan. 1 to Dec. 31, 2017, and methods to link patient records between the various echelons of care to identify barriers to linkage and opportunities for administrative solutions. Results: During 2017, potential trauma cases were identified within ground paramedic services (23 107 records), air medical transport services (196 records), referring hospitals (7194 records) and the lead trauma hospital trauma registry (1134 records). Linkage rates for medical records between services ranged from 49% to 92%. Conclusion: We successfully conceptualized and provided a preliminary demonstration of an initiative to collect, collate and accurately link primary data from acute trauma care providers for certain patients injured within the Central South RTN. Administration-level changes to the capture and management of trauma data represent the greatest opportunity for improvement.

Contexte: On ne dispose actuellement d'aucun système intégré de gestion des données pour évaluer le fardeau réel des traumatismes et de leur gestion dans les réseaux régionaux de traumatologie (RRT) en Ontario, en bonne partie en raison de la difficulté d'identifier les cas parmi la multiplicité des dossiers d'intervenants médicaux. Notre projet représente un effort itératif pour créer la capacité de cartographier le parcours de soin de tous les polytraumatisés du RRT de la région Centre-Sud. Méthodes: Grâce à l'engagement général des intervenants des grandes organisations de santé du RRT de la région Centre-Sud, nous avons obtenu l'approbation d'un comité d'éthique de la recherche et conclu des accords de partage des données avec plusieurs agences. Nous avons testé l'identification des cas de traumatologie du 1er janvier au 31 décembre 2017 et les méthodes de liaison des dossiers de patients entre les divers échelons de soin pour identifier les obstacles à la liaison et leurs solutions administratives possibles. Résultats: Au cours de 2017, les cas de traumatologie potentiels ont été identifiés auprès des services ambulanciers terrestres (23 107 dossiers), des services de transport médical aérien (196 dossiers), des hôpitaux référents (7194 dossiers) et du registre hospitalier principal de traumatologie (1134 dossiers). Les taux de liaison entre les différents services pour les dossiers médicaux variaient de 49 % à 92 %. Conclusion: Nous avons conceptualisé et présenté avec succès la démonstration préliminaire d'un projet visant à recueillir, colliger et relier avec justesse les données primaires des intervenants en traumatologie aiguë pour certains patients blessés du RRT du Centre-Sud. Des changements administratifs centrés sur la saisie et la gestion des données de traumatologie représentent la meilleure voie vers une amélioration.

The Development of Medical Markup Language Version 4 as a Clinical Document Exchange Format for Nationwide EHR Systems.

Medical Markup Language (MML) is a standard format for exchange of healthcare data among healthcare providers. Following the last major update (version 3), we developed new modules and discussed the requirements for the next major updates. Subsequently, in 2016 we released MML version 4 and used it to obtain clinical data from healthcare providers for a nationwide electronic health records (EHR) system. In this article we provide an overview of this major update of MML version 4 and discuss its interoperability for clinical data.

Measuring follow-up time in routinely-collected health datasets: Challenges and solutions.

A key requirement for longitudinal studies using routinely-collected health data is to be able to measure what individuals are present in the datasets used, and over what time period. Individuals can enter and leave the covered population of administrative datasets for a variety of reasons, including both life events and characteristics of the datasets themselves. An automated, customizable method of determining individuals' presence was developed for the primary care dataset in Swansea University's SAIL Databank. The primary care dataset covers only a portion of Wales, with 76% of practices participating. The start and end date of the data varies by practice. Additionally, individuals can change practices or leave Wales. To address these issues, a two step process was developed. First, the period for which each practice had data available was calculated by measuring changes in the rate of events recorded over time. Second, the registration records for each individual were simplified. Anomalies such as short gaps and overlaps were resolved by applying a set of rules. The result of these two analyses was a cleaned set of records indicating start and end dates of available primary care data for each individual. Analysis of GP records showed that 91.0% of events occurred within periods calculated as having available data by the algorithm. 98.4% of those events were observed at the same practice of registration as that computed by the algorithm. A standardized method for solving this common problem has enabled faster development of studies using this data set. Using a rigorous, tested, standardized method of verifying presence in the study population will also positively influence the quality of research.

Comparing record linkage software programs and algorithms using real-world data.

Linkage of medical databases, including insurer claims and electronic health records (EHRs), is increasingly common. However, few studies have investigated the behavior and output of linkage software. To determine how linkage quality is affected by different algorithms, blocking variables, methods for string matching and weight determination, and decision rules, we compared the performance of 4 nonproprietary linkage software packages linking patient identifiers from noninteroperable inpatient and outpatient EHRs. We linked datasets using first and last name, gender, and date of birth (DOB). We evaluated DOB and year of birth (YOB) as blocking variables and used exact and inexact matching methods. We compared the weights assigned to record pairs and evaluated how matching weights corresponded to a gold standard, medical record number. Deduplicated datasets contained 69,523 inpatient and 176,154 outpatient records, respectively. Linkage runs blocking on DOB produced weights ranging in number from 8 for exact matching to 64,273 for inexact matching. Linkage runs blocking on YOB produced 8 to 916,806 weights. Exact matching matched record pairs with identical test characteristics (sensitivity 90.48%, specificity 99.78%) for the highest ranked group, but algorithms differentially prioritized certain variables. Inexact matching behaved more variably, leading to dramatic differences in sensitivity (range 0.04-93.36%) and positive predictive value (PPV) (range 86.67-97.35%), even for the most highly ranked record pairs. Blocking on DOB led to higher PPV of highly ranked record pairs. An ensemble approach based on averaging scaled matching weights led to modestly improved accuracy. In summary, we found few differences in the rankings of record pairs with the highest matching weights across 4 linkage packages. Performance was more consistent for exact string matching than for inexact string matching. Most methods and software packages performed similarly when comparing matching accuracy with the gold standard. In some settings, an ensemble matching approach may outperform individual linkage algorithms.

Highly drug-resistant bacteria: Is intra- and inter-hospital communication optimal?

OBJECTIVES: Communication represents a key component of the control of highly drug-resistant bacteria (HDRB) in healthcare settings. This survey assessed communication strategies developed and adopted in a large hospital network. METHODS: An online survey was sent to 83 infection control specialists working in hospitals of the Pays de la Loire region, France, in June 2016. Internal and external systems of identification and communication of HDRB status (colonized and contact patients) were assessed at the following steps of the hospital pathway: patient admission, during the stay, at discharge, and at readmission. RESULTS: Sixty-one hospitals (73%) participated in the survey: 31 (51%) had recently managed colonized patients and 51 (93%) had recently managed contact patients. At patient admission, 28 (46%) hospitals had an identification system for repatriated patients. During hospital stay, the colonized or contact status was informed in computerized patient records for 47/57 (82%) and 43 (75%) hospitals, respectively. At patient discharge, 56/61 (92%) hospitals declared transmitting the HDRB status to the downstream ward. Twenty-six and 25/60 (43% and 42%) hospitals had an automated alert system at readmission of colonized or contact patients, respectively. This strategy met the expectations of 15/61 (26%) infection control specialists. CONCLUSION: Efforts are still required in terms of communication for HDRB control. Sharing experiences and tools developed by hospitals may be beneficial for the entire hospital network.

Linkage between Utah All Payers Claims Database and Central Cancer Registry.

OBJECTIVE: To evaluate the linkage of claims from the Utah All Payers Claims Database (APCD) and Utah Cancer Registry (UCR). DATA SOURCES: Secondary data from 2013 and 2014 Utah APCD and 2013 UCR cases. STUDY DESIGN: This is a descriptive analysis of the quality of linkage between APCD claims data and cancer registry cases. DATA COLLECTION/EXTRACTION METHODS: We used the LinkPlus software to link Utah APCD and UCR data. PRINCIPAL FINDINGS: We were able to link 82.4 percent (9441/11 453) of the UCR reportable cancer cases with APCD claims. Of those linked, 66 percent were perfect matches. CONCLUSIONS: The quality of identifiers is high, evidence that claims data can potentially supplement cancer registry data for use in research.

Internal deterministic record linkage using indirect identifiers for matching of same-patient hospital transfers and early readmissions after acute coronary syndrome in a nationwide hospital discharge database: a retrospective observational validation study.

OBJECTIVES: To assess validity of record linkage using multiple indirect personal identifiers to identify same-patient hospitalisations and definition of episode of care (EC) due to acute coronary syndrome (ACS). METHODS: Using national hospital discharge data to identify all admissions due to ACS, we used six different linkage rules using indirect identifiers with increasing level of detail and compared validity against a pseudonymised unique identifier used as gold standard (GS). Contiguous hospitalisations within each matched group of hospitalizations occurring within 28 days of each other were considered one EC. We classified hospitalisations according to time between the first pair of hospitalisations as hospital transfer (HT: ≤1 day), early readmission (ER: 2-28 days) or recurrent cases (>28 days). RESULTS: There were 146 671 hospitalisations (unlinked), 121 987 ACS 28-day EC (linked GS), with 18 398 HTs (≤1 day), and 6286 ERs (≤28 days). Linkage rules using demographic and residence code variables produced linkage rates with highest validity for rule using sex, date of birth and four-digit residence code with sensitivity of 98.4 (95% CI: 98.4 to 98.5); specificity of 97.8 (95% CI: 97.6 to 98.0) and Cohen's κ of 0.9 to detect ACS-EC, compared with GS linkage rule. Similarly, validity for HT and ER was high and of similar magnitude, with sensitivity ranging between 97.2% and 98.1%, and specificity between 98.8% and 99.9%, respectively. CONCLUSIONS: Our internal linkage validation study using indirect patient identifiers will allow calibration of incidence rates and performance indicators, accounting for the effect of HT and readmissions.

Impact of linkage quality on inferences drawn from analyses using data with high rates of linkage errors in rural Tanzania.

BACKGROUND: Studies based on high-quality linked data in developed countries show that even minor linkage errors, which occur when records of two different individuals are erroneously linked or when records belonging to the same individual are not linked, can impact bias and precision of subsequent analyses. We evaluated the impact of linkage quality on inferences drawn from analyses using data with substantial linkage errors in rural Tanzania. METHODS: Semi-automatic point-of-contact interactive record linkage was used to establish gold standard links between community-based HIV surveillance data and medical records at clinics serving the surveillance population. Automated probabilistic record linkage was used to create analytic datasets at minimum, low, medium, and high match score thresholds. Cox proportional hazards regression models were used to compare HIV care registration rates by testing modality (sero-survey vs. clinic) in each analytic dataset. We assessed linkage quality using three approaches: quantifying linkage errors, comparing characteristics between linked and unlinked data, and evaluating bias and precision of regression estimates. RESULTS: Between 2014 and 2017, 405 individuals with gold standard links were newly diagnosed with HIV in sero-surveys (n = 263) and clinics (n = 142). Automated probabilistic linkage correctly identified 233 individuals (positive predictive value [PPV] = 65%) at the low threshold and 95 individuals (PPV = 90%) at the high threshold. Significant differences were found between linked and unlinked records in primary exposure and outcome variables and for adjusting covariates at every threshold. As expected, differences attenuated with increasing threshold. Testing modality was significantly associated with time to registration in the gold standard data (adjusted hazard ratio [HR] 4.98 for clinic-based testing, 95% confidence interval [CI] 3.34, 7.42). Increasing false matches weakened the association (HR 2.76 at minimum match score threshold, 95% CI 1.73, 4.41). Increasing missed matches (i.e., increasing match score threshold and positive predictive value of the linkage algorithm) was strongly correlated with a reduction in the precision of coefficient estimate (R2 = 0.97; p = 0.03). CONCLUSIONS: Similar to studies with more negligible levels of linkage errors, false matches in this setting reduced the magnitude of the association; missed matches reduced precision. Adjusting for these biases could provide more robust results using data with considerable linkage errors.

Exchanging personal health data with electronic health records: A standardized information model for patient generated health data and observations of daily living.

OBJECTIVE: The development of a middleware information model to facilitate better interoperability between Personal and Electronic Health Record systems in order to allow exchange of Patient Generated Health Data and Observations of Daily Leaving between patients and providers in order to encourage patient self-management. MATERIALS AND METHODS: An information model based on HL7 standards for interoperability has been extended to support PGHD and ODL data types. The new information models uses HL7 CDA to represent data, is instantiated as a Protégé ontology and uses a set of mapping rules to transfer data between Personal and Electronic Health Record systems. RESULTS: The information model was evaluated by executing a set of use case scenarios containing data exported from three consumer health apps, transformed to CDA according to developed mapping rules and validated against a CDA schema. This allowed various challenges to emerge as well as revealed gaps in current standards in use and the information model has been refined accordingly. DISCUSSION AND CONCLUSION: Our proposed middleware solution offers a number of advantages. When modifications are made to either a Personal or Health Electronic Health Record system or any integrated consumer app, they can be incorporated by altering only the instantiation of the information model. Our proposition uses current standards in use such as CDA. The solution is applicable to any EHR system with HL7 CDA support.

Sociodemographic differences in linkage error: an examination of four large-scale datasets.

BACKGROUND: Record linkage is an important tool for epidemiologists and health planners. Record linkage studies will generally contain some level of residual record linkage error, where individual records are either incorrectly marked as belonging to the same individual, or incorrectly marked as belonging to separate individuals. A key question is whether errors in linkage quality are distributed evenly throughout the population, or whether certain subgroups will exhibit higher rates of error. Previous investigations of this issue have typically compared linked and un-linked records, which can conflate bias caused by record linkage error, with bias caused by missing records (data capture errors). METHODS: Four large administrative datasets were individually de-duplicated, with results compared to an available 'gold-standard' benchmark, allowing us to avoid methodological issues with comparing linked and un-linked records. Results were compared by gender, age, geographic remoteness (major cities, regional or remote) and socioeconomic status. RESULTS: Results varied between datasets, and by sociodemographic characteristic. The most consistent findings were worse linkage quality for younger individuals (seen in all four datasets) and worse linkage quality for those living in remote areas (seen in three of four datasets). The linkage quality within sociodemographic categories varied between datasets, with the associations with linkage error reversed across different datasets due to quirks of the specific data collection mechanisms and data sharing practices. CONCLUSIONS: These results suggest caution should be taken both when linking younger individuals and those in remote areas, and when analysing linked data from these subgroups. Further research is required to determine the ramifications of worse linkage quality in these subpopulations on research outcomes.

Linking HIV and Viral Hepatitis Surveillance Data: Evaluating a Standard, Deterministic Matching Algorithm Using Data From 6 US Health Jurisdictions.

Accurate interpretations and comparisons of record linkage results across jurisdictions require valid and reliable matching methods. We compared existing matching methods used by 6 US state and local health departments (Houston, Texas; Louisiana; Michigan; New York, New York; North Dakota; and Wisconsin) to link human immunodeficiency virus and viral hepatitis surveillance data with a 14-key automated, hierarchical deterministic matching method. Applicable years of study varied by disease and jurisdiction, ranging from 1979 to 2016. We calculated percentage agreement and Cohen's κ coefficient to compare the matching methods used within each jurisdiction. We calculated sensitivity, specificity, and positive predictive value for each matching method, as compared with a new standard that included manual review of discrepant cases. Agreement between the existing matching method and the deterministic matching method was 99.6% or higher in all jurisdictions; Cohen's κ values ranged from 0.87 to 0.98. The sensitivity of the deterministic matching method ranged from 97.4% to 100% in the 6 jurisdictions; specificity ranged from 99.7% to 100%; and positive predictive value ranged from 97.4% to 100%. Although no gold standard exists, prior assessments of existing methods and review of discrepant classifications suggest good accuracy and reliability of our deterministic matching method, with the advantage that our method reduces the need for manual review and allows for standard comparisons across jurisdictions when linking human immunodeficiency virus and viral hepatitis data.

Refer-to-pharmacy: a qualitative study exploring the implementation of an electronic transfer of care initiative to improve medicines optimisation following hospital discharge.

BACKGROUND: Transition between care settings is a time of high risk for preventable medication errors. Poor communication about medication changes on discharge from hospital can result in adverse drug events and medicines-related readmissions. Refer-to-Pharmacy is a novel electronic referral system that allows hospital pharmacy staff to refer patients from their bedside to their community pharmacist for post-hospital discharge medication support. The aim of this study was to examine factors that promoted or inhibited the implementation of Refer-to-Pharmacy in hospital and community settings. METHODS: Twenty six interviews with hospital pharmacists (n = 11), hospital technicians (n = 10), and community pharmacists (n = 5) using Normalisation Process Theory (NPT) as the underpinning conceptual framework for data collection and analysis. RESULTS: Using NPT to understand the implementation of the technology revealed that the participants unanimously agreed that the scheme was potentially beneficial for patients and was more efficient than previous systems (coherence). Leadership and initiation of the scheme was more achievable in the contained hospital environment, while initiation was slower to progress in the community pharmacy settings (cognitive participation). Hospital pharmacists and technicians worked flexibly together to deliver the scheme, and community pharmacists reported better communication with General Practitioners (GPs) about changes to patients' medication (collective action). However, participants reported being unaware of how the scheme impacted patients, meaning they were unable to evaluate the effectiveness of scheme (reflexive monitoring). CONCLUSION: The Refer-to-Pharmacy scheme was perceived by participants as having important benefits for patients, reduced the possibility for human error, and was more efficient than previous ways of working. However, initiation of the scheme was more achievable in the single site of the hospital in comparison to disparate community pharmacy organisations. Community and hospital pharmacists and organisational leaders will need to work individually and collectively if Refer-to-Pharmacy is to become more widely embedded across health settings.

Linkage of Maternity Hospital Episode Statistics data to birth registration and notification records for births in England 2005-2014: Quality assurance of linkage of routine data for singleton and multiple births.

OBJECTIVES: To quality assure a Trusted Third Party linked data set to prepare it for analysis. SETTING: Birth registration and notification records from the Office for National Statistics for all births in England 2005-2014 linked to Maternity Hospital Episode Statistics (HES) delivery records by NHS Digital using mothers' identifiers. PARTICIPANTS: All 6 676 912 births that occurred in England from 1 January 2005 to 31 December 2014. PRIMARY AND SECONDARY OUTCOME MEASURES: Every link between a registered birth and an HES delivery record for the study period was categorised as either the same baby or a different baby to the same mother, or as a wrong link, by comparing common baby data items and valid values in key fields with stepwise deterministic rules. Rates of preserved and discarded links were calculated and which features were more common in each group were assessed. RESULTS: Ninety-eight per cent of births originally linked to HES were left with one preserved link. The majority of discarded links were due to duplicate HES delivery records. Of the 4854 discarded links categorised as wrong links, clerical checks found 85% were false-positives links, 13% were quality assurance false negatives and 2% were undeterminable. Births linked using a less reliable stage of the linkage algorithm, births at home and in the London region, and with birth weight or gestational age values missing in HES were more likely to have all links discarded. CONCLUSIONS: Linkage error, data quality issues, and false negatives in the quality assurance procedure were uncovered. The procedure could be improved by allowing for transposition in date fields, and more discrimination between missing and differing values. The availability of identifiers in the datasets supported clerical checking. Other research using Trusted Third Party linkage should not assume the linked dataset is error-free or optimised for their analysis, and allow sufficient resources for this.

Database Quality and Access Issues Relevant to Research Using Anesthesia Information Management System Data.

For this special article, we reviewed the computer code, used to extract the data, and the text of all 47 studies published between January 2006 and August 2017 using anesthesia information management system (AIMS) data from Thomas Jefferson University Hospital (TJUH). Data from this institution were used in the largest number (P = .0007) of papers describing the use of AIMS published in this time frame. The AIMS was replaced in April 2017, making this finite sample finite. The objective of the current article was to identify factors that made TJUH successful in publishing anesthesia informatics studies. We examined the structured query language used for each study to examine the extent to which databases outside of the AIMS were used. We examined data quality from the perspectives of completeness, correctness, concordance, plausibility, and currency. Our results were that most could not have been completed without external database sources (36/47, 76.6%; P = .0003 compared with 50%). The operating room management system was linked to the AIMS and was used significantly more frequently (26/36, 72%) than other external sources. Access to these external data sources was provided, allowing exploration of data quality. The TJUH AIMS used high-resolution timestamps (to the nearest 3 milliseconds) and created audit tables to track changes to clinical documentation. Automatic data were recorded at 1-minute intervals and were not editable; data cleaning occurred during analysis. Few paired events with an expected order were out of sequence. Although most data elements were of high quality, there were notable exceptions, such as frequent missing values for estimated blood loss, height, and weight. Some values were duplicated with different units, and others were stored in varying locations. Our conclusions are that linking the TJUH AIMS to the operating room management system was a critical step in enabling publication of multiple studies using AIMS data. Access to this and other external databases by analysts with a high degree of anesthesia domain knowledge was necessary to be able to assess the quality of the AIMS data and ensure that the data pulled for studies were appropriate. For anesthesia departments seeking to increase their academic productivity using their AIMS as a data source, our experiences may provide helpful guidance.

[Assessment of the incompleteness of the maternal schooling variable in Live Birth Certificate databases in Brazilian state capitals, 1996-2013]. / Avaliação da incompletude da variável escolaridade materna nos registros das Declarações de Nascidos Vivos nas capitais brasileiras - 1996 a 2013.

The article assessed the quality of completion of the maternal school variable in Brazilian state capitals and its regional distribution, based on the Brazilian Information System on Live Births (SINASC) with processed data from live birth certificates. A descriptive study was conducted in the time series from 1996 to 2013, with a total de 12,062,064 births, of which 11,442,494 (94.86%) had valid information on the maternal schooling variable. The results were calculated as the number of incomplete results in the variable per 1,000 live births, and the trend was assessed with the Joinpoint software, version 4.3.1. According to regional analysis, the South of Brazil showed a downward trend in incompleteness of maternal schooling throughout the study in all the state capitals of that region. Most of the country's other state capitals also showed improvement in the variable's completeness. However, there were different trends in some state capitals, even with greater incompleteness at the end of the period when compared to the beginning. SINASC proved to be a valuable source of data on mothers and their newborns, besides information on conditions in labor, delivery, and birth in the country. Maternal schooling, considered an important factor for obstetric and neonatal outcomes, is particularly useful for elaborating and evaluating policies and measures in maternal and child health. Thus, to achieve maximum completeness in data on this variable requires joint effort by health professionals and administrators, thereby guaranteeing the data's trustworthiness.

O presente artigo avaliou a qualidade de preenchimento da variável escolaridade da mãe nas capitais brasileiras e sua distribuição regional, por intermédio do Sistema de Informações sobre Nascidos Vivos (SINASC), processado pela Declaração de Nascido Vivo (DNV). Foi realizado um estudo descritivo de uma série temporal no período de 1996 a 2013, com um total de 12.062.064 nascimentos, dos quais 11.442.494 (94,86%) possuíam informação válida para a variável escolaridade da mãe. Os resultados foram calculados por número de incompletude da variável para cada 1.000 nascidos vivos e foi avaliada a tendência por meio do software Jointpoint (versão 4.3.1). A análise regional demonstrou que a Região Sul apresentou uma tendência de redução da incompletude da escolaridade materna, mantida no período do estudo, em todas as suas capitais. Igualmente, de forma geral, a maior parte das outras capitais do país também evidenciou uma melhora na completude da variável. Entretanto, verificaram-se diferentes tendências, com algumas capitais, inclusive, apresentando uma maior incompletude ao final do período, quando comparado ao seu início. O SINASC demonstrou ser um instrumento valioso nas informações sobre as mães e seus recém-nascidos juntamente com as condições de parto e nascimento no país. Particularmente, a escolaridade materna, considerada um fator importante sobre os desfechos obstétricos e neonatais, é uma variável que permite a elaboração e avaliação das políticas e ações na área da saúde materno-infantil. Assim, alcançar a sua máxima completude requer um esforço conjunto, dos profissionais e gestores, garantindo a credibilidade dessas informações.

El presente artículo evaluó la calidad en la cumplimentación de la variable escolaridad de la madre en las capitales brasileñas y su distribución regional, mediante el Sistema de Información sobre Nacidos Vivos (SINASC), registrado vía la Declaración de Nacido Vivo (DNV). Se realizó un estudio descriptivo de una serie temporal, durante el período de 1996 a 2013, con un total de 12.062.064 nacimientos, de los cuales 11.442.494 (94,86%) contaban con información válida de la variable escolaridad de la madre. Los resultados se calcularon por número de registros con carácter incompleto de la variable por cada 1.000 nacidos vivos y se evaluó la tendencia mediante el programa Jointpoint (versión 4.3.1). El análisis regional demostró que la región sur presentó una tendencia en la reducción de la incompletitud de la escolaridad materna, sostenida durante el período del estudio, en todas sus capitales. Igualmente, de manera general, la mayor parte de las otras capitales del país también evidenció una mejora en la completitud de la variable. No obstante, se verificaron diferentes tendencias con algunas capitales, inclusive, algunas presentando una mayor incompletitud al final del período, cuando se compara con el principio del mismo. El SINASC demostró ser un instrumento valioso para la información sobre las madres y sus recién nacidos, junto a las condiciones de parto y nacimiento en el país. Particularmente, la escolaridad materna, considerada un factor importante sobre los desenlaces obstétricos y neonatales, es una variable que permite la elaboración y evaluación de las políticas y acciones en el área de la salud materno-infantil. De esta forma, alcanzar su máxima completitud requiere un esfuerzo conjunto, de profesionales y gestores, garantizando la credibilidad de esta información.

Linkage of Maternity Hospital Episode Statistics data to birth registration and notification records for births in England 2005-2014: methods. A population-based birth cohort study.

INTRODUCTION: Maternity Hospital Episode Statistics (HES) data for 2005-2014 were linked to birth registration and birth notification data (previously known as NHS Numbers for Babies or NN4B) to bring together some key demographic and clinical data items not otherwise available at a national level. The linkage algorithm that was previously used to link 2005-2007 data was revised to improve the linkage rate and reduce the number of duplicate HES records. METHODS: Birth registration and notification linked records from the Office for National Statistics ('ONS birth records') were further linked to Maternity HES delivery and birth records using the NHS Number and other direct identifiers if the NHS Number was missing. RESULTS: For the period 2005-2014, over 94% of birth registration and notification records were correctly linked to HES delivery records. Two per cent of the ONS birth records were incorrectly linked to the HES delivery record and 5% of ONS birth records were linked to more than one HES delivery record. Therefore, a considerable amount of time was spent in quality assuring these files. CONCLUSION: The linkage rate for birth registration and notification records to HES delivery records steadily improved from 2005 to 2014 due to improvement in the quality and completeness of patient identifiers in both HES and birth notification data.

[Transmission of death certificates to CepiDc-Inserm related to suspicious deaths, in France, since 2000]. / Transmission des certificats de décès au CépiDc-Inserm en cas de mort suspecte en France, depuis 2000.

BACKGROUND: The purpose of this study is to assess variability in death certificates' transmission related to suspicious deaths. METHODS: The medical part of death certificates of suspicious deaths (violent or sudden deaths, unknown or ill-defined causes of death) were examined. We studied the frequency of suspicious deaths, in France, for deaths aged under 65, from 2000 to 2013, searching for temporal (2000-2013) and spatial correlations between unknown causes of death and other suspicious causes, and report of an autopsy. These results were compared with external data. RESULTS: Standardized proportion of deaths by unknown cause more than doubled during the study period (from 3.4 to 7.5%). The spatial correlation was strongly negative between standardized proportions of unknown causes of death and violent deaths (ICC=-0.80). Report of autopsy varied with cause of suspicious death and estimated zone of the forensic institute. The distribution was consistently distributed with external data, except for homicides. CONCLUSION: Information transmission to CépiDc-Inserm needs to be improved in case of suspicious death, in particularly from forensic institutes. This study emphasizes the urgent need for a complementary form to the death certificate.