{"id":12298,"date":"2018-08-08T10:01:37","date_gmt":"2018-08-08T14:01:37","guid":{"rendered":"http:\/\/www.iri.com\/blog\/?p=12298"},"modified":"2025-04-25T09:43:51","modified_gmt":"2025-04-25T13:43:51","slug":"pii-agedate-blurring-iri-fieldshield","status":"publish","type":"post","link":"https:\/\/www.iri.com\/blog\/data-protection\/pii-agedate-blurring-iri-fieldshield\/","title":{"rendered":"Blurring Ages and Dates to Anonymize PHI"},"content":{"rendered":"<p><span style=\"font-weight: 400;\">Random noise data masking, or blurring, is a common requirement for PII anonymization in healthcare data, particularly for researchers and marketers of protected health information (PHI) seeking to comply with the <\/span><a href=\"\/solutions\/data-masking\/hipaa\/overview\"><span style=\"font-weight: 400;\">HIPAA Expert Determination Method<\/span><\/a><span style=\"font-weight: 400;\"> security rule. Adding random noise to date, or other integer values is one of several PII data anonymization and de-identification techniques included in the <\/span><a href=\"http:\/\/www.iri.com\/products\/fieldshield\"><span style=\"font-weight: 400;\">IRI FieldShield<\/span><\/a><span style=\"font-weight: 400;\"> and <a href=\"https:\/\/www.iri.com\/products\/darkshield\">IRI DarkShield<\/a> HIPAA data masking tools, and the broader <\/span><a href=\"\/products\/voracity\"><span style=\"font-weight: 400;\">IRI Voracity<\/span><\/a><span style=\"font-weight: 400;\"> data management platform which includes them.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Moreover, blurring can be used along with other <\/span><a href=\"http:\/\/www.iri.com\/solutions\/data-masking\/static-data-masking\/blur\"><span style=\"font-weight: 400;\">data generalization<\/span><\/a><span style=\"font-weight: 400;\"> techniques like bucketing to improve re-ID risk scores by anonymizing direct (key) or demographic (quasi-) identifiers. Specifically, the goal is to change the values of like ages or dates (of birth, admission, treatment, etc.) that will make them less susceptible to re-identification, but still preserve their utility for research or marketing purposes.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">It is also possible to use &#8216;lesser&#8217; masking functions on dates, too, like a <a href=\"https:\/\/www.iri.com\/solutions\/data-transformation\/cross-calculate\">mathematical<\/a>\u00a0(e.g., add 10 to each age) or <a href=\"https:\/\/www.iri.com\/blog\/data-transformation2\/date-time-boost\/\">date calculation<\/a>. Either way however, you can also<em>\u00a0<\/em>preserve consistent date intervals in HIPAA and related data privacy scenarios like admit-discharge; <a href=\"mailto:fieldshield@iri.com\">ask us<\/a> how if this is a requirement.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">More specifically, the IRI <em>blur_age <\/em>and <em>blur_date<\/em> functions, along with <em>blur_int <\/em>and <em>blur_int_pct <\/em>are related data anonymization techniques designed to read input values and return similar but not identical values. The functions randomly blur a number or date within a certain range of the original number via a \u201cblur factor\u201d, but also keep the new number within a minimum and maximum value.<\/span><\/p>\n<p>&nbsp;<\/p>\n<h2>How the Functions Work<\/h2>\n<p><span style=\"font-weight: 400;\">Age blurring uses a function that can take either four or six arguments. The first set of arguments needs an original age, a minimum age, a maximum age, and a blur factor. The blur factor will determine the range that the function will change the original value. A blur factor of 10 will randomly pick a value between -10 and 10 years and then add it to the original value. The random blur will never pick zero unless the blur itself is set to zero. <\/span><\/p>\n<p><span style=\"font-weight: 400;\">The second set of arguments ask for two more inputs: a mode age and a second blur factor. The mode age is intended to be the mode of the data or another value that can be interpreted as the middle. Any age found within a certain distance of the mode is blurred by the second blur factor. The distance is the midpoint between the minimum and mode as well as the midpoint between the maximum and mode. This allows the function to adapt if the data distribution is skewed from the center.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">The blur library contains the function <\/span><b>blur_age<\/b><span style=\"font-weight: 400;\">. Its forms are:<\/span><\/p>\n<p><code>blur_age(AGE, MIN_AGE, MAX_AGE, BLUR_FACTOR)<br \/>\nblur_age(AGE, MIN_AGE, MAX_AGE, BLUR_FACTOR, MODE_AGE, MODE_BLUR_FACTOR)<br \/>\n<\/code><code><br \/>\n<\/code><\/p>\n<p><code><br \/>\n<\/code><a href=\"\/blog\/wp-content\/uploads\/2018\/08\/data-blurring-blurred-faces.png\"><img loading=\"lazy\" decoding=\"async\" class=\"aligncenter wp-image-12300\" src=\"\/blog\/wp-content\/uploads\/2018\/08\/data-blurring-blurred-faces.png\" alt=\"People with blurred faces\" width=\"600\" height=\"200\" srcset=\"https:\/\/www.iri.com\/blog\/wp-content\/uploads\/2018\/08\/data-blurring-blurred-faces.png 1100w, https:\/\/www.iri.com\/blog\/wp-content\/uploads\/2018\/08\/data-blurring-blurred-faces-300x100.png 300w, https:\/\/www.iri.com\/blog\/wp-content\/uploads\/2018\/08\/data-blurring-blurred-faces-768x256.png 768w, https:\/\/www.iri.com\/blog\/wp-content\/uploads\/2018\/08\/data-blurring-blurred-faces-1024x342.png 1024w\" sizes=\"(max-width: 600px) 100vw, 600px\" \/><\/a><\/p>\n<p><span style=\"font-weight: 400;\">Date blurring follows a format similar to age blurring but uses the a date as its input and output. The function supports ISO, American, and European date formats. Respectively, their forms are yyyy-mm-dd, mm\/dd\/yyyy, and dd.mm.yyyy. The random blur factors for these functions is in days and will change month and year if the new date is past the last day of the month or before the first.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">To blur dates for data privacy, use he <\/span><b>blur_date<\/b><span style=\"font-weight: 400;\"> function. This function is contained within the IRI\u00a0 dates library and exposed as one of four Blurring Functions in the Data Masking rule dialog in IRI Workbench (see below). Its forms are:<\/span><\/p>\n<p><code>blur_date (DATE, MIN_DATE, MAX_DATE, BLUR_FACTOR)<br \/>\nblur_date (DATE, MIN_DATE, MAX_DATE, BLUR_FACTOR, MODE_DATE, MODE_BLUR_FACTOR)<br \/>\n<\/code><\/p>\n<p><code><\/code><\/p>\n<p><span style=\"font-weight: 400;\">The <strong>blur_int<\/strong><\/span><span style=\"font-weight: 400;\"> function for standard integers with a relatively limited range between low (min) and high (max) values takes the form:<\/span><\/p>\n<p><code>blur_int(FIELD, MIN, MAX, BLUR, MODE, BLUR2)<br \/>\n<\/code><\/p>\n<p><span style=\"font-weight: 400;\">while the <strong>blur_int_pct<\/strong><\/span><span style=\"font-weight: 400;\"> function form only contemplates a percentage of blurring, which is better for values that may span a very large range:<\/span><\/p>\n<p><code>blur_int_pct(FIELD, PERCENT_AMOUNT)<\/code><\/p>\n<h3>Examples<\/h3>\n<p>Function Calls<\/p>\n<p><code>\/FIELD=(<em>EXPRESSION_AGE=blur_age(AGE, 18, 90, 10), TYPE=NUMERIC,\u00a0PRECISION=0<\/em>, POSITION=1, PRECISION=0, SEPARATOR=\"|\")<br \/>\n\/FIELD=(<em>EXPRESSION_DATE=blur_date(DATE, \"1982-12-31\", 30), TYPE=ISO_DATE<\/em> ...<\/code><\/p>\n\n<table id=\"tablepress-29\" class=\"tablepress tablepress-id-29\">\n<thead>\n<tr class=\"row-1 odd\">\n\t<th class=\"column-1\">Input<\/th><th class=\"column-2\">Ouput<\/th>\n<\/tr>\n<\/thead>\n<tbody class=\"row-hover\">\n<tr class=\"row-2 even\">\n\t<td class=\"column-1\">61|1982-01-12<\/td><td class=\"column-2\">62|1982-02-01<\/td>\n<\/tr>\n<tr class=\"row-3 odd\">\n\t<td class=\"column-1\">81|1982-12-16<\/td><td class=\"column-2\">72|1982-11-17<\/td>\n<\/tr>\n<tr class=\"row-4 even\">\n\t<td class=\"column-1\">58|1982-11-29<\/td><td class=\"column-2\">66|1982-11-24<\/td>\n<\/tr>\n<tr class=\"row-5 odd\">\n\t<td class=\"column-1\">23|1982-03-05<\/td><td class=\"column-2\">19|1982-02-13<\/td>\n<\/tr>\n<tr class=\"row-6 even\">\n\t<td class=\"column-1\">24|1982-11-18<\/td><td class=\"column-2\">21|1982-12-09<\/td>\n<\/tr>\n<tr class=\"row-7 odd\">\n\t<td class=\"column-1\">42|1982-05-26<\/td><td class=\"column-2\">43|1982-06-14<\/td>\n<\/tr>\n<tr class=\"row-8 even\">\n\t<td class=\"column-1\">28|1982-09-21<\/td><td class=\"column-2\">26|1982-09-10<\/td>\n<\/tr>\n<tr class=\"row-9 odd\">\n\t<td class=\"column-1\">63|1982-06-13<\/td><td class=\"column-2\">60|1982-07-07<\/td>\n<\/tr>\n<tr class=\"row-10 even\">\n\t<td class=\"column-1\">83|1982-03-08<\/td><td class=\"column-2\">87|1982-03-02<\/td>\n<\/tr>\n<tr class=\"row-11 odd\">\n\t<td class=\"column-1\">30|1982-05-27<\/td><td class=\"column-2\">33|1982-06-23<\/td>\n<\/tr>\n<tr class=\"row-12 even\">\n\t<td class=\"column-1\">37|1982-04-20<\/td><td class=\"column-2\">30|1982-03-21<\/td>\n<\/tr>\n<tr class=\"row-13 odd\">\n\t<td class=\"column-1\">90|1982-10-15<\/td><td class=\"column-2\">81|1982-10-23<\/td>\n<\/tr>\n<tr class=\"row-14 even\">\n\t<td class=\"column-1\">63|1982-06-21<\/td><td class=\"column-2\">66|1982-07-03<\/td>\n<\/tr>\n<tr class=\"row-15 odd\">\n\t<td class=\"column-1\">72|1982-04-19<\/td><td class=\"column-2\">76|1982-05-03<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<!-- #tablepress-29 from cache -->\n<p><span style=\"font-weight: 400;\">Graphical specification of blur function parameters into data masking jobs is available in <\/span><a href=\"\/products\/workbench\"><span style=\"font-weight: 400;\">IRI Workbench<\/span><\/a><span style=\"font-weight: 400;\">. The Blur Functions dialog described below is launched from the list of available protection rules that can apply in data classification or FieldShield job design:<\/span><\/p>\n<p><a href=\"\/blog\/wp-content\/uploads\/2018\/08\/data-blurring-new-field-rule-wizard.png\"><img loading=\"lazy\" decoding=\"async\" class=\"aligncenter wp-image-12301 size-full\" src=\"\/blog\/wp-content\/uploads\/2018\/08\/data-blurring-new-field-rule-wizard.png\" alt=\"New Field Rule Wizard\" width=\"526\" height=\"713\" srcset=\"https:\/\/www.iri.com\/blog\/wp-content\/uploads\/2018\/08\/data-blurring-new-field-rule-wizard.png 526w, https:\/\/www.iri.com\/blog\/wp-content\/uploads\/2018\/08\/data-blurring-new-field-rule-wizard-221x300.png 221w\" sizes=\"(max-width: 526px) 100vw, 526px\" \/><\/a><\/p>\n<p><span style=\"font-weight: 400;\">Additionally, the functions can be saved as rules so that they can be reused. <\/span><\/p>\n<p><span style=\"font-weight: 400;\">Choosing Blur Functions open this dialog:<\/span><\/p>\n<figure id=\"attachment_16440\" class=\"thumbnail wp-caption aligncenter style=\"width: 816px\"><a href=\"http:\/\/www.iri.com\/blog\/wp-content\/uploads\/2018\/08\/data-blurring-blur-functions.png\"><img loading=\"lazy\" decoding=\"async\" class=\"wp-image-16440 size-full\" src=\"http:\/\/www.iri.com\/blog\/wp-content\/uploads\/2018\/08\/VoracityBlurFunctions2023.png\" alt=\"Random noise anonymization\" width=\"806\" height=\"472\" srcset=\"https:\/\/www.iri.com\/blog\/wp-content\/uploads\/2018\/08\/VoracityBlurFunctions2023.png 806w, https:\/\/www.iri.com\/blog\/wp-content\/uploads\/2018\/08\/VoracityBlurFunctions2023-300x176.png 300w, https:\/\/www.iri.com\/blog\/wp-content\/uploads\/2018\/08\/VoracityBlurFunctions2023-768x450.png 768w\" sizes=\"(max-width: 806px) 100vw, 806px\" \/><\/a><figcaption class=\"caption wp-caption-text\"><em>Blur Functions &#8211; Another IRI data masking rule<\/em><\/figcaption><\/figure>\n<p>For numbers which may fall into a large range, the function <em>blur_int_pct <\/em>blurs an integer by a percentage of its value. This handles uses cases where blurring a number by up to 200, for example, is insignificant if the original value is 20,000, and inappropriate if the original value is 20. A 10 percent blur might blur 20 by up to plus or minus 2, while blurring 20,000 by 10% will vary the result up to plus or minus 2,000.<\/p>\n<p>For each and every field value passed to the function, the percentage is applied to the value, and that becomes the blurring factor. Assuming a specified blur percentage of 25. A value of 20 would be blurred by a random amount between -5 and +5, a value of 2,000 would be blurred by a random amount between -500 and +500.<\/p>\n<h2>Behaviors for Bad Data<\/h2>\n<p><span style=\"font-weight: 400;\">In case the value of the first argument is less than the minimum or greater than the maximum, the new value will default to the minimum or maximum value. This applies to all the blurring functions.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Blur factors that are larger than the actual distance between the minimum and maximum will be ignored. Instead, it will create a value between the minimum and maximum. A similar behavior will occur for the mode blur factor.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">The blur_age function will return a bad value error if the first argument read in is not an integer. This function will also accept negative values as long as they are integers.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">If blur_date encounters a value that is not an ISO_DATE, AMERICAN_DATE, EUROPEAN_DATE, it will return \u201cnot-a-date-time\u201d. This is the default value for the <\/span><a href=\"\/blog\/data-transformation2\/date-time-boost\/\"><span style=\"font-weight: 400;\">Boost library<\/span><\/a><span style=\"font-weight: 400;\"> variables IRI uses, and will return it if the variable is not set correctly or not set at all.<\/span><\/p>\n<p>If you are interested these functions or PII anonymization in healthcare data specifically, please contact info@iri.com.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Random noise data masking, or blurring, is a common requirement for PII anonymization in healthcare data, particularly for researchers and marketers of protected health information (PHI) seeking to comply with the HIPAA Expert Determination Method security rule. Adding random noise to date, or other integer values is one of several PII data anonymization and de-identification<\/p>\n<div><a class=\"btn-filled btn\" href=\"https:\/\/www.iri.com\/blog\/data-protection\/pii-agedate-blurring-iri-fieldshield\/\" title=\"Blurring Ages and Dates to Anonymize PHI\">Read More<\/a><\/div>\n","protected":false},"author":115,"featured_media":12300,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"_exactmetrics_skip_tracking":false,"_exactmetrics_sitenote_active":false,"_exactmetrics_sitenote_note":"","_exactmetrics_sitenote_category":0,"footnotes":""},"categories":[8,1,29],"tags":[1356,20,1340,1342,14,19,13,1357,1354,1341,520,789,2021,1349,1355,1377,1344,1343],"class_list":["post-12298","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-data-protection","category-data-transformation2","category-test-data","tag-age-blurring","tag-data-anonymization","tag-data-blurring","tag-data-generalization","tag-data-masking","tag-data-obfuscation","tag-data-protection-2","tag-dob-blur","tag-hipaa-expert-determination","tag-indirect-identifier-masking","tag-iri-fieldshield","tag-iri-voracity","tag-phi-anonymization","tag-protecting-quasi-identifiers","tag-random-noise","tag-re-id-risk-determination","tag-re-id-risk-score","tag-risk-score"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v23.4 (Yoast SEO v23.4) - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Blurring Ages and Dates to Anonymize PHI - IRI<\/title>\n<meta name=\"description\" content=\"Need to anonymize protected health information (PHI) in files or DBs? 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