BMC Med Inform Decis Mak - A study of diverse clinical decision support rule authoring environments and requirements for integration.

Tópicos

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{ data(1714) softwar(1251) tool(1186) }
{ ehr(2073) health(1662) electron(1139) }
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{ data(3963) clinic(1234) research(1004) }
{ state(1844) use(1261) util(961) }
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{ featur(3375) classif(2383) classifi(1994) }
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{ health(3367) inform(1360) care(1135) }
{ research(1218) medic(880) student(794) }
{ patient(2837) hospit(1953) medic(668) }
{ data(2317) use(1299) case(1017) }
{ age(1611) year(1155) adult(843) }
{ cost(1906) reduc(1198) effect(832) }
{ group(2977) signific(1463) compar(1072) }
{ sampl(1606) size(1419) use(1276) }
{ gene(2352) biolog(1181) express(1162) }
{ data(3008) multipl(1320) sourc(1022) }
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{ patient(1821) servic(1111) care(1106) }
{ health(1844) social(1437) communiti(874) }
{ structur(1116) can(940) graph(676) }
{ cancer(2502) breast(956) screen(824) }
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{ activ(1452) weight(1219) physic(1104) }
{ method(1969) cluster(1462) data(1082) }
{ method(2212) result(1239) propos(1039) }
{ detect(2391) sensit(1101) algorithm(908) }

Resumo

CKGROUND: Efficient rule authoring tools are critical to allow clinical Knowledge Engineers (KEs), Software Engineers (SEs), and Subject Matter Experts (SMEs) to convert medical knowledge into machine executable clinical decision support rules. The goal of this analysis was to identify the critical success factors and challenges of a fully functioning Rule Authoring Environment (RAE) in order to define requirements for a scalable, comprehensive tool to manage enterprise level rules.METHODS: The authors evaluated RAEs in active use across Partners Healthcare, including enterprise wide, ambulatory only, and system specific tools, with a focus on rule editors for reminder and medication rules. We conducted meetings with users of these RAEs to discuss their general experience and perceived advantages and limitations of these tools.RESULTS: While the overall rule authoring process is similar across the 10 separate RAEs, the system capabilities and architecture vary widely. Most current RAEs limit the ability of the clinical decision support (CDS) interventions to be standardized, sharable, interoperable, and extensible. No existing system meets all requirements defined by knowledge management users.CONCLUSIONS: A successful, scalable, integrated rule authoring environment will need to support a number of key requirements and functions in the areas of knowledge representation, metadata, terminology, authoring collaboration, user interface, integration with electronic health record (EHR) systems, testing, and reporting.

Resumo Limpo

ckground effici rule author tool critic allow clinic knowledg engin kes softwar engin ses subject matter expert smes convert medic knowledg machin execut clinic decis support rule goal analysi identifi critic success factor challeng fulli function rule author environ rae order defin requir scalabl comprehens tool manag enterpris level rulesmethod author evalu rae activ use across partner healthcar includ enterpris wide ambulatori system specif tool focus rule editor remind medic rule conduct meet user rae discuss general experi perceiv advantag limit toolsresult overal rule author process similar across separ rae system capabl architectur vari wide current rae limit abil clinic decis support cds intervent standard sharabl interoper extens exist system meet requir defin knowledg manag usersconclus success scalabl integr rule author environ will need support number key requir function area knowledg represent metadata terminolog author collabor user interfac integr electron health record ehr system test report

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