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• Administrative Data Linkage in Brazil: Potentials for Health Technology Assessment

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Date descending Date ascending. Select job type. Select experience levels. Login Sign up. Add to collection. Save to PDF. Bud Lampshade by Etienne Esmenjaud for Desinature by retail design blog. Privacy Overview This website uses cookies so that we can provide you with the best user experience possible. There are two main types of linkage algorithms: deterministic and probabilistic. Probabilistic linkage methods, on the other hand, takes advantage of differences in the discriminatory power of each attribute and apply calculation of similarity scores, as well as decision rules, to classify record pairs as linked, potentially linked treated as dubious records in most linkage tools and non-linked Newcombe et al.

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It can also deal with some inconsistencies between records with missing data, i. Since its introduction by Newcombe Newcombe et al. Many of these tools have a general purpose, allowing a combination of existing configurations and methodologies Camargo and Coeli, ; Elfeky et al. In general, a successful linkage processing involves several main steps: pre-processing, blocking and indexing, field comparison, weight vector classification, and accuracy assessment Christen, as depicted in Figure 1. Common flowchart of a data linkage tool: Raw data are pre-processed 1 and split into smaller blocks 2.

Pairwise comparison is performed among records within similar blocks using functions that produce a similarity measure for each attribute. A weighted vector is then used to average each individual similarity measure into a single score S 3.

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Manual review the dataset generated after the pairwise comparison is optionally performed 4. The pre-processing step involves data cleansing and standardization whereby incomplete and incorrectly formatted data is converted into well-defined, consistent form Christen et al. Specific approaches to deal with missing data can be applied at this step to i remove missing fields or entire records or ii impute missing values based on standard or calculated values.

Pre-processing may also involve anonymization using different privacy-preserving techniques, such as Bloom filters Inan et al. In a big data context, these numbers make pairwise comparisons impractical and lead to a number of infrastructure, data processing, and data analysis challenges Peek et al. Other initiatives have also proposed the use of cluster-based platforms, multi-processors or graphics processing units GPUs Boratto et al. Blocking and indexing step generates pairs of candidate records pertaining to the same comparison blocks Christen, These methods drastically decrease the number of candidate record pairs to a feasible number thereby speeding up the linkage performance over big data sets while still maintaining linkage accuracy.

Several indexing techniques used in linkage solutions are well described in the literature Christen, The field comparison step involves using several functions to measure the similarity of attributes for each record pair.

The choice of the functions is dependent on the content of the field: string comparison functions are used for names and addresses whereas numerical comparison functions are used for fields, such as date, age, and numerical values Christen, Once a vector of numerical similarity values is calculated for each record pair, the candidate record pairs are classified as linked i.

Example of a frequency analysis of a data set produced by the linkage pipeline. Three cut-off points can be chosen according to specific needs. Any pair in between sensitivity and specificity cutoffs is considered a dubious match and thus passed for manual review. When manual review is not possible, a common approach is to choose a cut-off point that averages sensitivity and specificity, maximizing accuracy.

During the final step—accuracy assessment—evaluates the linkage algorithm and the quality of the linkage i. Linkage accuracy is often assessed using a gold standard dataset where the true match status of each pair of records is known. Comparing the probabilistically linked dataset to the gold-standard dataset will identify true matches, true non-matches, false matches, and missed matches.

Hence, measures of linkage quality such as sensitivity, positive predictive value, and F-measure can be easily derived. When gold standard dataset is not available,alternative approaches such as sensitivity analysis, comparison of characteristics of linked and non-linked data, and identification of implausible matches could be used to quantify the rate of linkage errors Christen, In the last decade, the use of big data for research in Brazil has increased substantially due to several factors: data access, creation of research groups and data centers, development of efficient record linkage tools, and international research collaborations, among others.

In this section, we describe three data centers specialized in the use of big data as well as development of record linkage tools:. It houses the Million Brazilian Cohort Pita et al. The center operates with a strong governance; an advanced data platform comprising the computational infrastructure needed for receipt, storage, curation, and integration of large databases, and extraction of data sets for specific analysis; and a physical structure carefully designed to give full physical protection for the data when handling non-anonymized data sets as well as to manage access and analysis of de-identified or anonymized data sets.

All standard operation procedures SOPs for data manipulation, cleaning, linkage, and for meta-data production are being defined according to international standards. The research group at the Federal University of Minas Gerais had also made significant achievement in record linkage. It will allow researchers to generate real-world evidence using clinical, pharmacological, and pharmacoeconomic studies. This initiative has enabled several scientific investigations, such as the study of a criminal network by identifying distinct offenders on a graph-based police event database dos Santos Fraga, The research group at the State University of Rio de Janeiro has made substantial contribution on data science and record linkage in Brazil, including the largely used probabilistic record linkage tool based on Fellegi-Sunter model, RecLink Camargo and Coeli, ; Camargo and Coeli, Reclink has been used in many epidemiological studies by academic institutions and the MoH which were mostly published in Reports in Public Health , 1 a scientific repository maintained by the Oswaldo Cruz Foundation.

They have also employed record linkage on administrative databases to study mortality rate on patients submitted to high complex cardiology procedures Migowski et al. Main contributions of this group, beyond the reported linked databases, comprise the use of the Expectation Maximization EM algorithm to predict the best settings for model tuning Junger, , the use of phonetic code in blocking step Coeli and Camargo, , and the rule-based matching. Recent work on the development of an open source version, the OpenRecLink de Camargo and Coeli, has provided a multi-platform solution suitable to international users.

Additional efforts have been made to define a cut-off point on probabilistic record linkage results Verzinhasse Peres et al. In the past decade, the use of secondary data for research in Brazil has grown substantially. This is due to several factors: availability of large data sources, development of efficient linkage tools, legislation in Brazil favoring the used of secondary data for Brazil, the need to evaluate several public policies, and international collaborations, among others.

The interface is also used to define the behavior of the tool, such as the pre-processing steps, blocking and matching parameters Camargo and Coeli, RecLink uses a custom format for input, which means the original data sets first have to be converted to standard formats to be linked. It has functions related to the standardization of common fields, including manipulation of names case sensitive conversions, preposition and accent removal in names, and removal of commas and punctuation marks , standardization of date formats, and correct classification of missing values.

Standardization of character attributes, such as date of birth and sex, is performed using the dBASE database manager, whereas a Soundex code developed for this purpose is used for strings, such as names and municipality Camargo and Coeli, ; Camargo and Coeli, RecLink performs record linkage in two steps: 1 blocking step, which separates the two data sets to be linked into smaller data sets according to the configuration provided by the user and 2 matching weight calculation and pairwise comparison of records that belong to the same block Camargo and Coeli, The blocking stage can be conducted in one-step procedure using a single attribute, such as municipality Paixao et al.

The Levenshtein string comparator is used to compare names; it is defined as the minimum number of insertions, deletions, or substitutions necessary to change one string into another the values varying between 1, perfect similarity and 0, total disagreement. RecLink uses three different weight systems that can be selected by the user: 1 the pure and simple comparison, which only classifies records as matches if their attributes are strictly identical; 2 the character sequence comparison, which evaluates each pair of attributes from both records and returns how many different characters they have; and 3 the fuzzy comparison, which returns a normalized score consisting of the size of the longest common sequence of characters divided by the size of the longest attribute.

The default m-probabilities and u-probabilities of 0.

RecLink is the most popular linkage tool in Brazil that has been used in several population linkage-based studies Oliveira et al. It also has several functions for other applications, such as de-duplication, standard query language SQL exporting, and frequency tables calculation. The tool aims to maximize accuracy and to minimize the need for clerical manual review in data linkage Pacheco et al. The Rio de Janeiro cohort database was originally designed to validate the WHO-HIV staging system in a developing country, whereas the THRio cohort was designed to assess the impact of implementing isoniazid prophylactic therapy among HIV-positive patients with indications for prophylaxis in Rio de Janeiro Pacheco et al.

The algorithm has a hierarchical structure and correlates records using exact comparisons.