BMC Med Inform Decis Mak - Pseudonymization of patient identifiers for translational research.

Tópicos

{ system(1050) medic(1026) inform(1018) }
{ data(3008) multipl(1320) sourc(1022) }
{ research(1085) discuss(1038) issu(1018) }
{ patient(2837) hospit(1953) medic(668) }
{ concept(1167) ontolog(924) domain(897) }
{ care(1570) inform(1187) nurs(1089) }
{ drug(1928) target(777) effect(648) }
{ estim(2440) model(1874) function(577) }
{ can(774) often(719) complex(702) }
{ framework(1458) process(801) describ(734) }
{ can(981) present(881) function(850) }
{ inform(2794) health(2639) internet(1427) }
{ patient(2315) diseas(1263) diabet(1191) }
{ sequenc(1873) structur(1644) protein(1328) }
{ studi(2440) review(1878) systemat(933) }
{ chang(1828) time(1643) increas(1301) }
{ record(1888) medic(1808) patient(1693) }
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{ take(945) account(800) differ(722) }
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{ perform(999) metric(946) measur(919) }
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{ decis(3086) make(1611) patient(1517) }
{ bind(1733) structur(1185) ligand(1036) }
{ method(1219) similar(1157) match(930) }
{ featur(3375) classif(2383) classifi(1994) }
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{ assess(1506) score(1403) qualiti(1306) }
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{ control(1307) perform(991) simul(935) }
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{ ehr(2073) health(1662) electron(1139) }
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{ age(1611) year(1155) adult(843) }
{ medic(1828) order(1363) alert(1069) }
{ signal(2180) analysi(812) frequenc(800) }
{ group(2977) signific(1463) compar(1072) }
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{ gene(2352) biolog(1181) express(1162) }
{ first(2504) two(1366) second(1323) }
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{ cancer(2502) breast(956) screen(824) }
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{ process(1125) use(805) approach(778) }
{ method(2212) result(1239) propos(1039) }
{ detect(2391) sensit(1101) algorithm(908) }

Resumo

CKGROUND: The usage of patient data for research poses risks concerning the patients' privacy and informational self-determination. Next-generation-sequencing technologies and various other methods gain data from biospecimen, both for translational research and personalized medicine. If these biospecimen are anonymized, individual research results from genomic research, which should be offered to patients in a clinically relevant timeframe, cannot be associated back to the individual. This raises an ethical concern and challenges the legitimacy of anonymized patient samples. In this paper we present a new approach which supports both data privacy and the possibility to give feedback to patients about their individual research results.METHODS: We examined previously published privacy concepts regarding a streamlined de-pseudonymization process and a patient-based pseudonym as applicable to research with genomic data and warehousing approaches. All concepts identified in the literature review were compared to each other and analyzed for their applicability to translational research projects. We evaluated how these concepts cope with challenges implicated by personalized medicine. Therefore, both person-centricity issues and a separation of pseudonymization and de-pseudonymization stood out as a central theme in our examination. This motivated us to enhance an existing pseudonymization method regarding a separation of duties.RESULTS: The existing concepts rely on external trusted third parties, making de-pseudonymization a multistage process involving additional interpersonal communication, which might cause critical delays in patient care. Therefore we propose an enhanced method with an asymmetric encryption scheme separating the duties of pseudonymization and de-pseudonymization. The pseudonymization service provider is unable to conclude the patient identifier from the pseudonym, but assigns this ability to an authorized third party (ombudsman) instead. To solve person-centricity issues, a collision-resistant function is incorporated into the method. These two facts combined enable us to address essential challenges in translational research. A productive software prototype was implemented to prove the functionality of the suggested translational, data privacy-preserving method. Eventually, we performed a threat analysis to evaluate potential hazards connected with this pseudonymization method.CONCLUSIONS: The proposed method offers sustainable organizational simplification regarding an ethically indicated, but secure and controlled process of de-pseudonymizing patients. A pseudonym is patient-centered to allow correlating separate datasets from one patient. Therefore, this method bridges the gap between bench and bedside in translational research while preserving patient privacy. Assigned ombudsmen are able to de-pseudonymize a patient, if an individual research result is clinically relevant.

Resumo Limpo

ckground usag patient data research pose risk concern patient privaci inform selfdetermin nextgenerationsequenc technolog various method gain data biospecimen translat research person medicin biospecimen anonym individu research result genom research offer patient clinic relev timefram associ back individu rais ethic concern challeng legitimaci anonym patient sampl paper present new approach support data privaci possibl give feedback patient individu research resultsmethod examin previous publish privaci concept regard streamlin depseudonym process patientbas pseudonym applic research genom data wareh approach concept identifi literatur review compar analyz applic translat research project evalu concept cope challeng implic person medicin therefor personcentr issu separ pseudonym depseudonym stood central theme examin motiv us enhanc exist pseudonym method regard separ dutiesresult exist concept reli extern trust third parti make depseudonym multistag process involv addit interperson communic might caus critic delay patient care therefor propos enhanc method asymmetr encrypt scheme separ duti pseudonym depseudonym pseudonym servic provid unabl conclud patient identifi pseudonym assign abil author third parti ombudsman instead solv personcentr issu collisionresist function incorpor method two fact combin enabl us address essenti challeng translat research product softwar prototyp implement prove function suggest translat data privacypreserv method eventu perform threat analysi evalu potenti hazard connect pseudonym methodconclus propos method offer sustain organiz simplif regard ethic indic secur control process depseudonym patient pseudonym patientcent allow correl separ dataset one patient therefor method bridg gap bench bedsid translat research preserv patient privaci assign ombudsmen abl depseudonym patient individu research result clinic relev

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