Natural Language Processing
advertisement
Applying Natural Language Processing in the Clinical Setting Peter Haug, MD Homer Warner Center for Informatics Research Intermountain Healthcare, Salt Lake City, Utah Applied NLP Research • • Goals: – Affect Care Delivery • Extract Clinical Data from Medical Documents • Use Extracted Data to Alter Care – Improve Documentation Examples: – Support for Diagnostic Systems • Screening for Disease • Assess Risk • Triggering Orders • Activating Clinical Protocols • Identify Necessary Data – Encode Admit Diagnoses • Identify Eligible Patients – Identify Patients for Trauma Registry – Support Clinical Research • Data Extraction • Phenotype Recognition – Complete Problem List – Identify Patients for Research Recruitment • Research Alerting – Improve Administrative Data • Improve Data for Business Planning • Improve Data for Billing 2 Process Begins with a Document Document Parsing Process •Find Document Structure •Extract MetaData •Plan Further Parsing •Find Sentence Structure •Determine Meaning (Concepts) •Store/Process Concepts Chest Xray Report History: Cough and fever. Previous history of right-sided pneumonia. Exam: PA and Lateral Chest Film. Observations: Prior films showed confluent opacification of the RLL. This finding remains in today’s exam. These opacities, seen in multiple previous films, have spread to the right and left upper lobes. Interpretation: Extension of previously diagnosed pneumonia to right and left upper lobes. A Sequence of Processing • Find Document Structure • Find Section Structure • Find Sentence Structure • Determine Meaning (Semantics) – Map to Concepts – Build Data Structures Document Document Sections Find Internal Structure Structured Document Planner Output Output Document Parsing Process Find Document Sections •Find Document XML Based Output XML Based <Body>Prior films showed confluent opacification ofOutput the RLL. Structure <Doc>Chest Xray Report</Doc> Xray Report</Doc> This finding remains in today’s exam. These<Doc>Chest opacities, seen in <Sec>History</Sec> <Body>Cough and fever. Previous history of right-sided pneumonia.</Body> <Sec>Exam</Sec> <Body>PA and Lateral Chest Film. </ Body> <Sec>Observations</Sec> <Body>Prior films showed confluent opacification of the RLL. This finding remains in today’s exam. These opacities, seen in multiple previous films, have spread to the right and left upper lobes. </Body> <Sec>Interpretation</Sec> …………………….. </Doc> <Sec>History</Sec> <Body> <Sen>Cough and fever.</Sen> <Sen>Previous history of right-sided pneumonia.</Sen> </Body> <Sec>Exam</Sec> <Body> <Sen>PA and Lateral Chest Film.</Sen> </Body> <Sec>Observations</Sec> <Body> <Sen>Prior films showed confluent opacification of the RLL.</Sen> <Sen>This finding remains in today’s exam.</Sen> <Sen>These opacities, seen in multiple previous films, have spread to the right and left upper lobes.</Sen> </Body> ………….. </Doc> multiple •Extract Meta- previous films, have spread to the right and left Data upper lobes.</Body> •Plan Further Parsing •Find Sentence Structure <Sen>These opacities, seen in multiple previous films, have spread to the right and left upper lobes.</Sen> •Determine Meaning (Concepts) •Store/Process Concepts Build Structures for: 1) Document Type 2) Sections 3) Paragraphs 4) Sentences 5) Tables 6) Internal Markup 7) Images 8) Lists 9) Images?? Choose Models to Parse Against: 1) Rules to determine which group of concepts to find based on Document Type and Sections Present Sentences Structured Document Planner MetaData Determine Sentence Structure Linked Phrasal Components Determine Semantics Output Document Parsing Process Includes Document Type and Section Information. XML Based Output •Find Structures <Doc>Chest Xray Report</Doc> ………….. <Sec>Observations</Sec> <Body> <Sen><Coded Index=”1">Prior films showed confluent opacification of the RLL.</Coded></Sen> <Sen><Coded Index=”2">This finding remains in today’s exam.</Coded></Sen> <Sen><Coded Index=”3">These opacities, seen in multiple previous films, have spread to the right and left upper lobes.</Coded></Sen> </Body> ………….. <Codes> <code ref=”1 Term=”Snomed”>2345</code> <code ref=”2 Term=”Snomed”>3456</code> <code ref=”3a Term=”Snomed”>1234</code> <code ref=”3b Term=”Snomed”>1235</code> ………….. </Doc> •Extract MetaData •Plan Further Parsing Sen><Coded Index=”3">These opacities, seen in multiple previous films, have spread to the right and left upper lobes.</Coded></Sen> •Find Sentence Structure •Determine Meaning (Concepts) •Store/Process Concepts <code ref=”3a” Terminology=”TermX?”>1234</code> <code ref=”3b” Terminology=”TermX?”>1235</code> Choose Models to Parse Against: 1) Rules to determine which group of concepts to find based on Document Type and Sections Present Coded Findings: Localized Infiltrate-RUL Localized Infiltrate-LUL Data Base Storage Structured Data Storage These opacities, seen in multiple views, have spread to the right and left upper lobes. Semantic Lexicon: Derived Sentence Parsing Process •Categorize Words •Extract Concepts Etc. Phrasal Grammar Compositional Grammar Output •Test for Semantic Congruence Output •Find Relationships Among Phrases Output •Identify Phrasal Boundaries Restrictions from SpecialistAdj. these=>POS: Phrasal Grammar (ME&E Restrictions, Lexicon?? And Semantic Rep: N/A Conjunctive semantic KB Restrictions) opacities=>POS: Noun Num; Pleural Semantic Rep: RadFind.finding.opacities ID: 1 Identify Identify verbSentence/Word Properties Phrasal Info Sentence seen=>POS: Word Candidate Num; N/A Properties Phrases Semantic Rep: N/A ………………………... right=>POS: adj. POS: Noun these=>POS: Adj. P1: these opacities: pntr- ID:1 Num; Singular Semantic Rep: N/A P2: in multiple Semantic Rep: RadFind.side.right opacities=>POS: Noun P3: previous flims Num; Pleural P4: In multiple previous films ID: 2 Semantic Rep: RadFind.finding.opacities P5: to the right: pntr- ID:2 ID: 1 left=>POS: adj. P6: to the left pntr- ID:3 seen=>POS: verb P7: upper lobes pntr- ID:4,5 POS: Noun Num; N/A P8: to the right upper lobes pntrSemantic Rep: N/A Num; Singular ID:2,4,5 ………………………... P9: to the left upper lobes pntrright=>POS: adj. Semantic Rep: RadFind.side.left ID:3,4,5 POS: Noun ID: 3 Num; Singular Etc. Semantic Rep: RadFind.side.right upper=>POS: adj. ID: 2 Num; N/A left=>POS: adj. POS: Noun Semantic Rep: RadFind.sup_inf.upper Num; Singular Semantic Rep: RadFind.side.left ID: 4 ID: 3 Etc. lobes=>POS: noun upper=>POS: adj. Num; N/A Num; pleural Semantic Rep: RadFind.sup_inf.upper ID: 4 Semantic Rep: RadFind.anat_loc.lobes lobes=>POS: noun ID: 5 Num; pleural Semantic Rep: RadFind.anat_loc.lobes Etc. ID: 5 these opacities these opacities to the right these opacities to the left tothese the left upper opacities these opacities lobes to the right upper lobes these opacities upper lobes to the left upper lobes These opacities, seen in multiple views, have spread to the right and left upper lobes. Phrasal Grammar Document Parsing Process From Words to Coded Findings: Localized Infiltrate-RUL Localized Infiltrate-LUL Structured Data Storage Compositional these opacities Grammar •Categorize Words Output •Identify Phrasal Boundaries these opacities •Find Relationships Among Phrases s_o bservatio ns these opacities to the left upper lobes to the right to the left c pneumothorax c enlargement of the heart c abnormality c ambiguity c lclzd prnchyml bnrmlty ns c generalized infiltrate c localized infiltrate c bilateral pleural effusion c nlrgmnt f th plmnry vssls c generalized volume reducti... c parenchymal abnormality no c pulmonary nodular lesion c mediastinal widening c pleural thickening c generic infiltrate nos c pleural effusion ns c bony abnormality c consolidation nos c localized volume reduction c vlm rfrnc t prvs rcrd other- s_to pic_co ncept c enlargement 12.7 c air density 11.5 c parenchymal abnormality ns 10.6 c prly mrgntd pcty nfltrt 9.17 c abnormality 8.73 c fluid density 7.94 c volume reduction 4.78 c see previous event 4.19 c consolidation 3.99 c smll wll mrgntd pcty ndl 3.56 other22.8 to pic_mo difier null nodular adj accumulation n increased focal adj hazy adj patchy adj active adj degenerative adj linear adj other- 79.3 1.98 1.66 1.58 1.30 0.67 0.59 0.51 0.51 0.51 11.4 9.76 9.48 5.97 5.37 5.18 4.98 4.35 3.87 3.24 2.77 2.73 2.73 2.69 2.61 2.33 2.21 2.13 2.09 1.94 1.86 21.7 s_anato mic_co ncept c bilateral lung c heart c interpleural space ns c see previous event c bilateral interpleural space c null c mediastinum c left lower lobe c pulmonary vessels c pleura c left upper lobe c right lung c left interpleural space c right lower lobe c all thoracic locations c left lung c bilateral lower lobes c right upper lobe c right interpleural space c aorta other- 16.0 9.56 8.93 5.49 4.74 4.50 4.46 4.35 3.00 2.84 2.73 2.57 2.57 2.49 2.25 2.21 1.90 1.78 1.62 1.58 14.4 anato mic_lo catio n_mo difier null otherwise adv structures n generalized adj remainder adj other- 22.3 10.3 6.32 5.85 4.03 3.64 3.32 2.65 2.25 1.94 37.4 93.0 0.71 0.40 0.36 0.28 5.22 s_o bservatio ns 16.2 15.7 8.95 8.31 7.12 5.77 5.42 4.03 3.08 2.46 23.0 s_to pic_co ncept c enlargement 12.7 c air density 11.5 c parenchymal abnormality ns 10.6 c prly mrgntd pcty nfltrt 9.17 c abnormality 8.73 c fluid density 7.94 c volume reduction 4.78 c see previous event 4.19 c consolidation 3.99 c smll wll mrgntd pcty ndl 3.56 other22.8 s_anato mic_link_co ncept c involving c null c throughout c adjacent to c projecting on other- null in of at throughout other- 73.3 11.7 8.02 1.26 1.22 4.51 s_supero r_inferio r s_side 86.5 8.34 4.07 0.75 0.12 0.20 c null 81.5 c upper 7.35 c middle 1.86 c lower 9.25 c null 61.4 c left 13.8 c right 10.6 c bilateral 11.3 c either 2.77 to pic_mo difier null left right bilateral both other- null nodular adj accumulation n increased focal adj hazy adj patchy adj active adj degenerative adj linear adj other- anato mic_mo difier_sup_inf_ anato mic_mo difier_side_ null lower upper base apical other- 61.4 13.6 10.5 7.82 2.81 3.83 c pneumothorax c enlargement of the heart c abnormality c ambiguity c lclzd prnchyml bnrmlty ns c generalized infiltrate c localized infiltrate c bilateral pleural effusion c nlrgmnt f th plmnry vssls c generalized volume reducti... c parenchymal abnormality no c pulmonary nodular lesion c mediastinal widening c pleural thickening c generic infiltrate nos c pleural effusion ns c bony abnormality c consolidation nos c localized volume reduction c vlm rfrnc t prvs rcrd other- anato mic_lo catio n_term null lung n lobe n pleural adj interpleural adj heart n lungs n cardiac adj mediastinal adj chest n other- to pic_term null air n opacities n opacity n consolidation n fluid n infiltrate n infiltrates n effusion n changes n other- anato mic_link_term 81.5 6.48 5.22 1.66 1.19 3.91 79.3 1.98 1.66 1.58 1.30 0.67 0.59 0.51 0.51 0.51 11.4 9.76 9.48 5.97 5.37 5.18 4.98 4.35 3.87 3.24 2.77 2.73 2.73 2.69 2.61 2.33 2.21 2.13 2.09 1.94 1.86 21.7 s_anato mic_co ncept c bilateral lung c heart c interpleural space ns c see previous event c bilateral interpleural space c null c mediastinum c left lower lobe c pulmonary vessels c pleura c left upper lobe c right lung c left interpleural space c right lower lobe c all thoracic locations c left lung c bilateral lower lobes c right upper lobe c right interpleural space c aorta other- •Test for Semantic Congruence 16.0 9.56 8.93 5.49 4.74 4.50 4.46 4.35 3.00 2.84 2.73 2.57 2.57 2.49 2.25 2.21 1.90 1.78 1.62 1.58 14.4 anato mic_lo catio n_mo difier null otherwise adv structures n generalized adj remainder adj other- 22.3 10.3 6.32 5.85 4.03 3.64 3.32 2.65 2.25 1.94 37.4 93.0 0.71 0.40 0.36 0.28 5.22 anato mic_lo catio n_term null lung n lobe n pleural adj interpleural adj heart n lungs n cardiac adj mediastinal adj chest n other- to pic_term null air n opacities n opacity n consolidation n fluid n infiltrate n infiltrates n effusion n changes n other- 16.2 15.7 8.95 8.31 7.12 5.77 5.42 4.03 3.08 2.46 23.0 s_anato mic_link_co ncept c involving c null c throughout c adjacent to c projecting on other- 86.5 8.34 4.07 0.75 0.12 0.20 anato mic_link_term these opacities •Extract Concepts Concept Extraction Linked Phrasal Components null in of at throughout other- 73.3 11.7 8.02 1.26 1.22 4.51 s_supero r_inferio r s_side c null 81.5 c upper 7.35 c middle 1.86 c lower 9.25 c null 61.4 c left 13.8 c right 10.6 c bilateral 11.3 c either 2.77 anato mic_mo difier_sup_inf_ anato mic_mo difier_side_ null left right bilateral both other- null lower upper base apical other- 61.4 13.6 10.5 7.82 2.81 3.83 81.5 6.48 5.22 1.66 1.19 3.91 these opacities s_o bservatio ns c pneumothorax c enlargement of the heart c abnormality c ambiguity c lclzd prnchyml bnrmlty ns c generalized infiltrate c localized infiltrate c bilateral pleural effusion c nlrgmnt f th plmnry vssls c generalized volume reducti... c parenchymal abnormality no c pulmonary nodular lesion c mediastinal widening c pleural thickening c generic infiltrate nos c pleural effusion ns c bony abnormality c consolidation nos c localized volume reduction c vlm rfrnc t prvs rcrd other- s_to pic_co ncept to the right upper lobes c enlargement 12.7 c air density 11.5 c parenchymal abnormality ns 10.6 c prly mrgntd pcty nfltrt 9.17 c abnormality 8.73 c fluid density 7.94 c volume reduction 4.78 c see previous event 4.19 c consolidation 3.99 c smll wll mrgntd pcty ndl 3.56 other22.8 to the left upper lobes to pic_mo difier null nodular adj accumulation n increased focal adj hazy adj patchy adj active adj degenerative adj linear adj other- 79.3 1.98 1.66 1.58 1.30 0.67 0.59 0.51 0.51 0.51 11.4 9.76 9.48 5.97 5.37 5.18 4.98 4.35 3.87 3.24 2.77 2.73 2.73 2.69 2.61 2.33 2.21 2.13 2.09 1.94 1.86 21.7 16.0 9.56 8.93 5.49 4.74 4.50 4.46 4.35 3.00 2.84 2.73 2.57 2.57 2.49 2.25 2.21 1.90 1.78 1.62 1.58 14.4 22.3 10.3 6.32 5.85 4.03 3.64 3.32 2.65 2.25 1.94 37.4 s_o bservatio ns anato mic_lo catio n_mo difier null otherwise adv structures n generalized adj remainder adj other- 16.2 15.7 8.95 8.31 7.12 5.77 5.42 4.03 3.08 2.46 23.0 s_to pic_co ncept c enlargement 12.7 c air density 11.5 c parenchymal abnormality ns 10.6 c prly mrgntd pcty nfltrt 9.17 c abnormality 8.73 c fluid density 7.94 c volume reduction 4.78 c see previous event 4.19 c consolidation 3.99 c smll wll mrgntd pcty ndl 3.56 other22.8 s_anato mic_link_co ncept c involving c null c throughout c adjacent to c projecting on other- 86.5 8.34 4.07 0.75 0.12 0.20 anato mic_link_term 73.3 11.7 8.02 1.26 1.22 4.51 s_side c null 61.4 c left 13.8 c right 10.6 c bilateral 11.3 c either 2.77 anato mic_mo difier_side_ null left right bilateral both other- 61.4 13.6 10.5 7.82 2.81 3.83 c pneumothorax c enlargement of the heart c abnormality c ambiguity c lclzd prnchyml bnrmlty ns c generalized infiltrate c localized infiltrate c bilateral pleural effusion c nlrgmnt f th plmnry vssls c generalized volume reducti... c parenchymal abnormality no c pulmonary nodular lesion c mediastinal widening c pleural thickening c generic infiltrate nos c pleural effusion ns c bony abnormality c consolidation nos c localized volume reduction c vlm rfrnc t prvs rcrd other- 93.0 0.71 0.40 0.36 0.28 5.22 anato mic_lo catio n_term null lung n lobe n pleural adj interpleural adj heart n lungs n cardiac adj mediastinal adj chest n other- to pic_term null air n opacities n opacity n consolidation n fluid n infiltrate n infiltrates n effusion n changes n other- null in of at throughout other- these opacities s_anato mic_co ncept c bilateral lung c heart c interpleural space ns c see previous event c bilateral interpleural space c null c mediastinum c left lower lobe c pulmonary vessels c pleura c left upper lobe c right lung c left interpleural space c right lower lobe c all thoracic locations c left lung c bilateral lower lobes c right upper lobe c right interpleural space c aorta other- s_supero r_inferio r 9.76 9.48 5.97 5.37 5.18 4.98 4.35 3.87 3.24 2.77 2.73 2.73 2.69 2.61 2.33 2.21 2.13 2.09 1.94 1.86 21.7 s_anato mic_co ncept c bilateral lung c heart c interpleural space ns c see previous event c bilateral interpleural space c null c mediastinum c left lower lobe c pulmonary vessels c pleura c left upper lobe c right lung c left interpleural space c right lower lobe c all thoracic locations c left lung c bilateral lower lobes c right upper lobe c right interpleural space c aorta other- 16.0 9.56 8.93 5.49 4.74 4.50 4.46 4.35 3.00 2.84 2.73 2.57 2.57 2.49 2.25 2.21 1.90 1.78 1.62 1.58 14.4 anato mic_lo catio n_mo difier null otherwise adv structures n generalized adj remainder adj other- anato mic_lo catio n_term null lung n lobe n pleural adj interpleural adj heart n lungs n cardiac adj mediastinal adj chest n other- c null 81.5 c upper 7.35 c middle 1.86 c lower 9.25 to pic_mo difier anato mic_mo difier_sup_inf_ null lower upper base apical other- 81.5 6.48 5.22 1.66 1.19 3.91 null nodular adj accumulation n increased focal adj hazy adj patchy adj active adj degenerative adj linear adj other- 79.3 1.98 1.66 1.58 1.30 0.67 0.59 0.51 0.51 0.51 11.4 to pic_term null air n opacities n opacity n consolidation n fluid n infiltrate n infiltrates n effusion n changes n other- 22.3 10.3 6.32 5.85 4.03 3.64 3.32 2.65 2.25 1.94 37.4 Data Base Storage 93.0 0.71 0.40 0.36 0.28 5.22 16.2 15.7 8.95 8.31 7.12 5.77 5.42 4.03 3.08 2.46 23.0 s_anato mic_link_co ncept c involving c null c throughout c adjacent to c projecting on other- 86.5 8.34 4.07 0.75 0.12 0.20 anato mic_link_term null in of at throughout other- 73.3 11.7 8.02 1.26 1.22 4.51 s_side c null 61.4 c left 13.8 c right 10.6 c bilateral 11.3 c either 2.77 anato mic_mo difier_side_ null left right bilateral both other- 61.4 13.6 10.5 7.82 2.81 3.83 s_supero r_inferio r c null 81.5 c upper 7.35 c middle 1.86 c lower 9.25 anato mic_mo difier_sup_inf_ null lower upper base apical other- 81.5 6.48 5.22 1.66 1.19 3.91 Etc. Etc. upper lobes Semantic Tests 1) Model determines Semantic consistency of phrasal combinations. 2) “Best” combinations trigger concept extraction and storage. Output of a Semantic Parse PARSE: A hazy opacity is seen in the right upper lobe. • Instantiated Event: • 1001 *Overall Concept : *localized infiltrate (0.998669) • 1002 *State Concept : *present (0.780993) • • • • • • • • • • • • • • • • • 1003 1004 1005 1006 1008 1009 1010 1011 1012 1013 1014 1015 1016 1017 1018 1019 1020 Presence Term : null (0.779583) *Topic Concept : *poorly-marginated opacity (infiltrate) (1.0) Topic Term : opacity~n (1.0) Topic Modifier Term: hazy~adj. (1.0) Topographic Location Term : null (0.588844) *Severity Concept : *null (0.969009) Severity Term : null (0.962739) *Link Concept : involving (0.686011) Topic Location Link Term : in (1.0) *Anatomic Concept : *right upper lobe (1.0) Anatomic Location Mod : null (0.9375) Anatomic Location : lobe~n (1.0) Anatomic Location Mod1 : right (1.0) Anatomic Location Mod2 : upper (1.0) Anatomic Location Mod3 : null (1.0) Anatomic Location Mod4 : null (1.0) Anatomic Location Mod5 : null (1.0) Probabilistic Semantics GlobalObservation abnormality 0+ localized infiltrate 58.4 alveolar infiltrate nos 14.8 generic infiltrate nos 26.8 State absent 28.8 present 64.2 possible 6.62 otherwise absent 0.39 state_term null 62.3 no 18.7 no evidence 4.67 with no 4.28 or 2.33 particularly 1.56 without 0.78 possibly 0.78 and or 0.78 most likely 0.78 other3.12 topic_term abcess .002 abnormalities .002 consolidation 31.1 infiltrates 18.3 opacity 10.5 visualization 0.39 infiltrate 30.7 opacification 0.39 opacities 2.73 densities 0.39 consolidated 0.39 air bronchogram 0.39 kerley lines 0.39 septal lines 0.39 changes 1.17 lesion 0.39 null 0.39 air 0.39 change 0.39 density 1.17 Observation localized infiltrate 53.3 infiltrate nos 43.2 generalized infiltrate 1.95 interstitial infiltrate 0.78 inflammatory lesion 0.39 other0.39 topic_modifier null 69.6 focal 6.61 superimposed 0.39 hazy 3.50 mildly coarse pattern 0.39 confluent 0.78 infiltrative 3.11 mixed pattern 0.39 dense 1.56 patchy 1.95 areas of 0.78 area 0.39 reticular 0.39 nodular 0.78 inflammatory 0.38 ill defined 0.78 indistinct 1.17 poorly marginated 1.17 slightly coarse 0.39 bronchogram 0.39 underlying 0.39 fluffy 1.95 ill defined 1.95 poorly defined 0.39 vague 0.39 Location bilateral lung 26.5 left lower lobe 14.0 null 10.1 bilateral lower lobes 8.17 left upper lobe 7.39 other33.9 anatomic_location_term pulmonary 3.51 null 37.7 lung 15.5 lungs 3.89 hemithorax 0.78 lobes 3.89 perivascular 0.40 lobe 28.4 lung fields 0.40 chest 0.40 location 0.40 infrahilar 0.39 side 0.40 heart 1.17 retrocardiac 0.78 lingula 1.95 Modifier_Side null 52.9 left 21.8 right 16.3 bilateral 8.57 either 0.40 anatomic_modifier_side_ null 52.5 either 0.40 right 16.3 bilaterally 0.78 left 22.2 bilateral 3.50 both 4.28 Modifier_Sup_Inf null 58.7 ascending .007 descending .007 superior 11.7 middle 2.73 inferior 26.8 anatomic_modifier_sup_inf_ null 58.7 lower 22.6 upper 10.9 base 1.95 apex 0.39 cranial 0.39 bases 1.56 mid 1.17 basilar 0.78 middle 1.56 Modifier_Cntrl_Prph_ null 97.3 central 1.95 peripheral 0.79 anatomic_mdfr_cntrl_prph_ null 97.3 peripheral 0.39 central 1.95 peripherally 0.39 Example: NLP in Pneumonia (a computer-based intervention) • Goal: – Identify Pneumonia Patients in the ED Rapidly – Assess Risk – Suggest Intervention • Approach: – Use Probabilistic System to Identify Patients – Suggest Enrollment in Pneumonia Protocol – Provide Therapeutic Suggestions • Requires Data Extracted from the X-ray Report Care Delivery Framework Example: Community-Acquired Pneumonia Computable Medical Knowledge Reposotory Chest Xray Reports Chest Xray Report Processing (Structured Data Extraction) Data Supporting Pneumonia Assessment Pneumonia Screening Tool Clinical Data Repository Pneumonia Guideline Enrollment Pneumonia Treatment Protocol Care Delivery Framework Example: Community-Acquired Pneumonia Computable Medical Knowledge Reposotory Chest Xray Reports Chest Xray Report Processing (Structured Data Extraction) Data Supporting Pneumonia Assessment Does the patient have pneumonia? Pneumonia Screening Tool Clinical Data Repository Pneumonia Guideline Enrollment Pneumonia Treatment Protocol Care Delivery Framework Example: Community-Acquired Pneumonia Computable Medical Knowledge Reposotory Chest Xray Reports Chest Xray Report Processing (Structured Data Extraction) Data Supporting Pneumonia Assessment Does the patient have pneumonia? Pneumonia Screening Tool Clinical Data Repository Should we used the guideline? Pneumonia Guideline Enrollment Pneumonia Treatment Protocol Care Delivery Framework Example: Community-Acquired Pneumonia Computable Medical Knowledge Reposotory Chest Xray Reports Chest Xray Report Processing (Structured Data Extraction) Data Supporting Pneumonia Assessment Does the patient have pneumonia? Pneumonia Screening Tool Should we used the guideline? Pneumonia Guideline Enrollment Pneumonia Treatment Protocol Apply Pneumonia Care Protocol. Clinical Data Repository ChiefComplaint RESPIRATORY COMPLAINT 32.4 FEVER 6.96 ABD PAIN 6.05 ORTHO INJURY 4.26 CHEST PAIN 4.12 NEURO COMPLAINT 3.69 FALL 3.62 TRAFFIC INJURY 3.50 ABD PROBLEMS 3.45 CHEST PRESSURE 3.10 BACK PAIN 2.82 WEAKNESS 2.79 SYNCOPE 2.28 ENT PROBLEM 2.19 BODY ACHES 1.88 CV COMPLAINTS 1.88 HEADACHE 1.83 DIZZY 1.77 FLANK PAIN 1.43 CV PROBLEMS 0.92 ASSAULT RAPE 0.87 PSYCHIATRIC 0.86 CHEST HEAVINESS 0.82 SKIN COMPLAINT 0.78 SPECIFIC DIAGNOSIS 0.51 DIABETIC 0.44 PAIN CHEST 0.37 HEART RACE 0.33 TRAUMA 0.31 GENITOURINARY PROBLEM 0.31 PALPITATIONS 0.31 HEART IRR 0.30 ALLERGIES 0.29 HIGH BP 0.28 FLUID NUTRITION 0.27 CONVULSIONS 0.25 INFECTION 0.20 RAPID HR 0.19 IRR HEARTBEAT 0.16 LACERATION 0.16 INGESTION 0.16 BP HIGH 0.13 UNCONSCIOUSNESS 0.11 VAGINAL BLEEDING .098 MED REFILL .091 UNKNOWN .087 LOW BP .064 CARDIAC ARREST .059 EYE PROBLEM .055 BP LOW .054 other0.18 BPSystolic < 121.5 29.4 121.5 to 148.5 44.6 >= 148.5 26.0 134 ± 22 HeartRate < 85.5 44.5 85.5 to 99.5 24.7 99.5 to 110.5 13.0 >= 110.5 17.8 92.1 ± 15 BPDiastolic < 69.5 28.3 69.5 to 82.5 36.2 >= 82.5 35.5 76.9 ± 11 RespRate < 19.5 52.3 19.5 to 21.5 24.9 21.5 to 27.5 16.1 >= 27.5 6.72 20.8 ± 3.5 MeanBP < 85.5 23.0 85.5 to 99.5 35.4 >= 99.5 41.7 95.1 ± 12 TempC < 36.75 62.7 36.75 to 37.45 23.8 37.45 to 38.05 6.04 >= 38.05 7.46 36.79 ± 0.63 Implimented Using: NLP_FINDING Positive 25.9 Negative 74.1 Age < 15.5 8.06 15.5 to 45.5 45.6 >= 45.5 46.4 42 ± 21 • Web Services Infrastructure Sodium < 137.5 25.7 137.5 to 140.5 41.8 >= 140.5 32.6 139.2 ± 2.4 • A Bayesian Network < 13.5 >= 13.5 Chloride < 103.5 42.1 103.5 to 105.5 25.1 >= 105.5 32.9 104.3 ± 1.8 Creatinine < 0.405 3.90 >= 0.405 96.1 PNEUMONIA • Supported by a Production Rules System Absent 94.9 Present WBC < 11.85 86.1 11.85 to 18.75 12.4 >= 18.75 1.45 9.46 ± 3.4 5.09 (DROOLS) • Using an NLP System Yes No BS_CLEAR 44.0 56.0 BS_STRIDOR Yes .083 No 99.9 BS_CRACKLES Yes 0.72 No 99.3 Yes No BS_RALES 0.11 99.9 Yes No BS_ABSENT .030 100 – Sentence Isolation BS_NO_COUGH Yes 0+ No 100 BS_WHEEZES Yes 2.84 No 97.2 BS_INSPIRATION Yes 0.79 No 99.2 BS_CONGESTION Yes 0.53 No 99.5 BS_RHONCHI Yes 0.43 No 99.6 BS_ABNORMAL Yes 3.87 No 96.1 BS_DECREASED Yes 2.29 No 97.7 BS_CLEARING_SECREA... Yes 0.45 No 99.6 BS_FINE_CRACK... Yes 0.31 No 99.7 BS_MODERATE Yes 1.36 No 98.6 BS_NON_PRODUCTIVE_CO... Yes 1.74 No 98.3 – Random Forests-Based Semantics BS_EXPIRATION Yes 0.90 No 99.1 BS_NOT_CLEARING_SECREA... Yes 0.10 No 99.9 BS_FREQUENT Yes 1.19 No 98.8 SpO2 < 92.1 10.2 92.1 to 95.3 23.6 95.3 to 98.4 44.9 >= 98.4 21.3 96.1 ± 3 BS_TUBULAR Yes .024 No 100 BS_COURSE Yes 0.90 No 99.1 Yes No BS_WEAK 0.16 99.8 BUN 45.1 54.9 BS_PRODUCTIVE_CO... Yes 1.81 No 98.2 BS_INFREQUENT Yes 0.62 No 99.4 BS_STRONG Yes 0.76 No 99.2 Patient Tracking Board Patient Tracking Board Conclusion • Natural Language Processing Does Play A Role In Patient Care • Useful Applications Will Blend NLP-Derived Data With Structured Data From The EHR • Radiology Reports Are A Data-rich Target For NLP Questions??? 23
