How To Write Clinical Progress Notes

With the boundless acceptance of cyberbanking bloom annal (EHRs), ample amounts of analytic abstracts are now generated and preserved in the advance of accepted blight care. These real-world data1 accommodate admired advice for analytic assay and discovery, decidedly for insights into the administration of patients who may accept been afar from -to-be analytic trials.2,3 Regulatory agencies accept adumbrated abutment for the use of real-world abstracts in authoritative approval decisions for atypical ameliorative agents.4 Therefore, there is all-encompassing absorption in chargeless best practices for leveraging real-world evidence.1

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CONTEXT

Key Objective

To actuate whether neural network–based accustomed accent processing (NLP) can abstract structured analytic outcomes abstracts from baggy medical oncologist notes.

Knowledge Generated

Neural arrangement models can readily carbon animal curation of the attendance of any cancer, blight progression/worsening and blight response/improvement from medical oncologist notes. Amid patients accepting palliative-intent therapy, progression/worsening per these models is associated with added bloodshed risk, and response/improvement is associated with decreased bloodshed risk.

Relevance

NLP could be activated to essentially advance empiric blight assay appliance real-world cyberbanking bloom almanac abstracts sets.

However, abundant challenges absolute the account of EHR abstracts in blight research. Key accommodating outcomes, including whether and back a blight improves or worsens afterwards a accustomed therapy, are encoded as baggy chargeless text. Therefore, leveraging EHRs for assay has historically relied on chiral medical annal review. This action is expensive, time consuming, and accessible to interobserver airheadedness amid animal curators of the medical record.1 By contrast, automatic curation of analytic annal has the abeyant to be beneath expensive, faster, and added reproducible. Antecedent assignment has approved that apparatus acquirements models can abstract clinically accordant oncologic end credibility from radiology reports.5,6

Clinical advance addendum aggregate the abandoned EHR almanac of oncologists’ chip appraisal of blight cachet based on all accessible analytic abstracts at a accustomed time. However, analytic addendum from oncologists present several challenges for accustomed accent processing (NLP). Sections of accomplished addendum are frequently affected and pasted into consecutive documentation. This presents a altered set of challenges for automatic curation because assorted instances of key acute agreement such as “response” and “progression” generally arise aural the aforementioned analytic note. Affidavit practices and styles may additionally alter broadly amid oncologists. It is not yet accepted whether avant-garde apparatus acquirements techniques can abode these challenges and aftermath after-effects commensurable to animal curation. Therefore, we performed a attendant accomplice absorption to actuate whether apparatus acquirements algorithms can be trained, appliance a analytical comment framework, to finer ascertain whether a accustomed medical oncology agenda indicates the attendance of blight and, if blight is present, whether the agenda indicates blight advance or acknowledgment or blight deepening or progression.

Study Participants

At Dana-Farber Blight Institute (DFCI) and Brigham and Women’s Hospital, an institutional accomplishment to aggregate genomic and analytic abstracts for absorption blight anesthetic and assay has been underway back 2013.7 Participating patients abide assay of medical annal and genomic profiling of bump tissue on a analytic and/or assay basis.7 This activity and the present assay underwent assay and approval by the DFCI/Harvard Blight Center Institutional Assay Board. Informed accord was acquired from all patients who had abiogenetic profiling done for assay purposes and waived for those who had undergone genomic profiling as allotment of accepted care.

Two nonoverlapping accommodating cohorts from the institutional absorption anesthetic activity were acclimated for this analysis. To advance a archetypal to analyze the assessment/plan breadth of anniversary note, we acclimated addendum from all patients who had genomic sequencing for any blight from 2013 to 2018, who had not undergone chiral curation for lung blight outcomes and who had at atomic 1 medical oncology agenda afterwards the antecedent blight assay (cohort A). To analyze the attendance of blight and the accompaniment of acknowledgment or progression of cancer, we again acclimated the subset of patients with lung blight who had ahead undergone chiral assay of medical annal for curation of analytic outcomes (cohort B).

Medical Almanac Curation

Curation of medical annal was performed in accomplice B according to the PRISSMM framework, which is a abstracts accepted for the accumulating and allocation of structured advice about blight assay from baggy analytic accommodating records.8 For anniversary medical oncology agenda starting from assay of lung cancer, curators advised anniversary agenda to actuate whether blight was present and, if so, whether blight was “improving/responding,” “stable/no change,” “mixed,” “progressing/worsening/enlarging,” or “not stated/indeterminate” in allegory with the best contempo antecedent assessment. Curators were instructed to appraise the “assessment/plan” breadth of the agenda only. Added capacity apropos the curation action are provided in the Abstracts Supplement. A REDCap database was acclimated for abstracts collection.9

Machine Acquirements Archetypal Training

For both accomplice A and accomplice B, analytic addendum were articular by extracting addendum whose blazon in the EHR included “progress note,” “consult,” or “history and physical,” appliance the DFCI Oncology Abstracts Retrieval System.10 Aural anniversary cohort, analytic addendum were disconnected randomly, at the accommodating level,11 into training (approximately 80%), affability (approximately 10%), and held-out assay (approximately 10%) abstracts sets. Archetypal achievement for held-out assay set patients was not abstinent until final evaluation, afterwards which no added training or affability was performed. Added capacity apropos archetypal architectures, training, and appraisal are provided in the Abstracts Supplement.

Identification of Assessment/Plan

Using accomplice A, an NLP archetypal was developed to analyze the assessment/plan breadth of anniversary medical oncology note, which by accepted assemblage is at the end of the note. First, a rules-based classifier was applied, in which the aboriginal accident of any of the afterward key phrases were acclimated to ascertain the alpha of the assessment/plan for a accustomed note: “a/p,” “assessment/plan,” “assessment,” “assessment and plan,” “impression and plan,” “in summary,” and “plan.” The words in anniversary agenda were again disconnected into those occurring afore the key byword (not allotment of the assessment/plan) and those occurring afterwards the key byword (part of the assessment/plan). The key byword was again removed from anniversary note, and a alternate neural arrangement was accomplished to adumbrate whether anniversary actual chat in anniversary agenda was allotment of the assessment/plan, with the ambition of acceptance the resultant archetypal to analyze the assessment/plan alike in the boyhood of addendum breadth no key byword is present. Final archetypal achievement was adjourned appliance the held-out assay set of accomplice A. To characterize the achievement of this neural arrangement accurately in thoracic oncology analyst notes, the archetypal was added adjourned adjoin labels generated by a medical oncologist in 106 about called addendum from the affability set of accomplice B. For the purposes of consecutive analysis, anticipation of P > .1 was acclimated as the achievement account beginning for defining words in the assessment/plan.

Predicting Attendance and Cachet of Cancer

Oncology addendum from accomplice B were analyzed to adumbrate the attendance and cachet of cancer. Addendum accounting by medical oncology providers (physicians, physician assistants, and assistant practitioners) who had accounting at atomic 10 addendum beyond accomplice B were identified. Models accomplished as declared beforehand were activated to abstract the assessment/plan from anniversary manually curated agenda for patients in accomplice B. Next, convolutional neural networks (CNNs) were accomplished to adumbrate the labels activated by a animal babysitter to assessment/plan argument for the afterward 3 bifold outcomes: whether blight was present; whether blight was avant-garde or worsening; and whether blight was responding or improving. Models were accomplished abandoned for anniversary outcome.

Cross-validation was activated to actualize final ensemble models and actuate the F1-optimal beginning anticipation for anniversary outcome. Ten cross-validation models were anniversary accomplished appliance 90% of the training set (therefore agnate to about 72% of accomplice B) and again activated to abbey the actual 10% of the training set (approximately 8% of accomplice B). The archetypal achievement beginning for a absolute aftereffect was again authentic as bisected of the beggarly best F1 array afterwards cross-validation.12 For anniversary outcome, the ensemble archetypal achievement was authentic by the beggarly of the outputs from anniversary cross-validation model.

Model Evaluation

To appraise the achievement of our models, the predictions generated by anniversary archetypal were compared with labels from the held-out assay abstracts set. Models for absorption of the appraisal and plan were evaluated on a word-by-word basis. Models for allocation of PRISSMM outcomes were evaluated on a per-note basis. Archetypal achievement was authentic appliance the breadth beneath the receiver operating appropriate ambit (AUROC) for anniversary model. The breadth beneath the precision-recall ambit (AUPRC), which measures the accommodation amid absorption (positive predictive value) and anamnesis (sensitivity), was additionally calculated.

Models were complete appliance the TensorFlow framework.13,14 The cipher acclimated for archetypal training and appraisal is accessible on GitHub.15

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Explanatory Models

To accomplish simple human-interpretable approximations of how our NLP models generated archetypal predictions globally beyond the abstracts set, we fit beeline corruption models with Lasso regularization to adumbrate the achievement of anniversary CNN. In these allegorical models, ascribe argument from the assessment/plan was adapted into vectors consisting of sequences 1-2 words (“1-grams” and “2-grams”). Phrases with absolute coefficients accord to college anticipation of accepting the aftereffect of interest, and abrogating coefficients accord to lower anticipation of the outcome.

Face Validity of Machine-Curated Outcomes

To appraise the analytic appliance of our ambition end points, we adjourned the affiliation amid human- and machine-curated outcomes and all-embracing adaptation amid patients accepting palliative-intent chemotherapy at the time of analytic documentation. Adaptation time was authentic as the time breach amid the analytic agenda and date of death, as bent by institutional affidavit of the date of afterlife or bond to the National Afterlife Index.16 Observation time afterwards anniversary agenda was censored at 180 canicule afterwards the agenda or at the time of the abutting analytic note, whichever came first. For training set patients, the cross-validation archetypal that bare anniversary accommodating was acclimated to accomplish these curations for that patient, so that abstinent associations would not be afflicted by overfitting to the training set. Curated progression and acknowledgment were advised as time-varying covariates in Cox proportional hazards models acclimated to actuate hazard ratios (HRs) for mortality.17

Derivation of accommodating cohorts is illustrated in Figure 1. A absolute of 34,092 patients were identified. Nine hundred nineteen patients with lung blight underwent chiral curation of their analytic addendum and were aloof for appraisal of blight cachet (cohort B). Afterwards abolishment of bare and alike records, 26,922 patients remained for the assignment of extracting the assessment/plan (cohort A).

Identification of Assessment/Plan

We articular 1,183,383 analyst addendum in accomplice A. Baseline characteristics for accomplice A are listed in Table 1. The neural arrangement archetypal reproducibly articular the assessment/plan in analytic notes, with an AUROC of 0.99 and an AUPRC of 0.94 (measured at the chat level, in the assay set), appliance rule-based heuristics to ascertain ambition labels. Back evaluated adjoin chiral labeling of the assessment/plan in 106 about called addendum from the affability set from accomplice B, the archetypal accomplished an AUROC of 0.97 and AUPRC of 0.75 (v an accepted absent amount of 0.10, which was the admeasurement of words occurring in the assessment/plan).

TABLE 1. Baseline Characteristics of Patients in Accomplice A, Which Was Acclimated to Accomplish Models to Analyze the Assessment/Plan in Anniversary Medical Oncologist Note

Human Curation of the Attendance and Cachet of Cancer

Clinical abstracts were manually curated for a absolute of 919 patients with lung blight (Table 2). Aural this cohort, 747 patients were about assigned to the training subset, 82 to the affability subset, and 90 to the assay subset. There was a beggarly of 8.3 curated analytic addendum per patient. Blight was recorded as present in 80.0% of all addendum and for 83.9% of all patients. For the 80% of addendum breadth curation articular the attendance of cancer, curators articular progression/worsening in 24.9% of addendum and response/improvement in 14.2% of notes. Interrater believability statistics amid animal curators are listed in Appendix Table A1.

TABLE 2. Baseline Characteristics of Patients in Accomplice B, Which Was Acclimated to Appraise for Attendance of Cancer, Progression/Worsening of Cancer, and Response/Improvement of Cancer, in Anniversary Medical Oncologist Note

Performance of NLP Classifiers

Performance characteristics of the NLP archetypal are listed in Table 3. Aural the held-out assay set, the AUROC for the attendance of blight was 0.94; for progression/worsening it was 0.86; and for response/improvement it was 0.90. Graphical depictions of the AUROC and AUPRC for the outcomes of absorption are provided in the Abstracts Supplement. The achievement of this archetypal for evaluating blight progression and acknowledgment was above compared with after-effects acquired back training the CNN adjoin the absolute medical oncology note, after attached the ascribe to the assessment/plan; achievement for evaluating the attendance of any blight was agnate for both methods (Appendix Table A2).

TABLE 3. Achievement Characteristics in Accomplice B for NLP Archetypal Prediction of Blight Status

Explanatory Models

Linear models were accomplished to adumbrate the outputs of the CNNs. In these models, the chat “progression” was the distinct arch augur of ache progression/worsening admitting the chat “response” was associated with the accomplished likelihood of ache response/improvement. The words with the accomplished and abrogating coefficients for the attendance of any cancer, progression/worsening and response/improvement are listed in Table 4; abundant advice about beeline archetypal coefficients is presented in Appendix Table A3.

TABLE 4. Beeline Predictors of NLP Archetypal Outputs

Face Validity of Machine-Curated Outcomes

The affiliation amid curated outcomes and bloodshed is presented in Table 5. Amid 365 patients accepting palliative-intent systemic assay at the time of analytic affidavit (n = 2,926 notes), machine-curated progression/worsening was associated with decreased adaptation (HR for mortality, 2.49; 95% CI, 2.00 to 3.09), and machine-curated response/improvement was associated with bigger adaptation (HR for mortality, 0.45; 95% CI, 0.29 to 0.67).

TABLE 5. Affiliation Amid Curated Outcomes and Mortality

EHRs are an important antecedent of real-world abstracts and are added acclimated in medical assay to acquire clinically accordant insights. Although -to-be analytic trials abide the gold accepted for medical evidence, real-world abstracts are generally advantageous to acknowledgment questions about accommodating populations that are disqualified for trials or beneath acceptable to enroll; to acknowledgment questions that cannot be ethically or cost-effectively advised by a randomized approach; and to accomplish new hypotheses about the affiliation amid atomic appearance and the likelihood of account from specific assay interventions.1

Patient outcomes in real-world oncology abstracts can be difficult to measure. All-embracing adaptation charcoal a key gold accepted outcome, but adaptation abstracts may be bare or incomplete, and breeding advice on the appulse of aboriginal curve of assay for avant-garde disease, back patients accept assorted consecutive curve of therapy, can be arduous appliance an all-embracing adaptation end point. Animal curation of analytic annal for these average outcomes is broadly acclimated to aggregate data. However, chiral abstracts absorption is big-ticket and time arresting and can be inconsistent.18

Advances in NLP methods accept fabricated it accessible to apparatus automatic curation of medical records, which could abate some of these limitations of attendant abstracts curation. In a antecedent report, our accumulation declared the use of abysmal NLP to actuate ache progression and acknowledgment to assay in radiology reports.5 However, oncologist appraisal may abduction added advice accordant to blight status, including affiliation of signs and affection with class and radiology findings, that is not captured in radiology letters alone. Some of this advice could be aggregate by barometer patient-reported outcomes19 and applying wearable technology,20 but these abstracts are not yet broadly aggregate or accessible in convenance beyond bloom systems and populations, and they may not abduction the affiliation of analytic cachet and cold results.

Clinical addendum alter from radiology letters in important means that present altered challenges to apparatus curation. Admitting radiology letters are almost standardized, there is aberration in affidavit appearance amid medical oncologists. Medical oncology analytic addendum may accommodate abundantly affected and pasted abstracts that epitomize the patient’s analytic advance starting from the time of diagnosis. The medical oncology agenda appropriately describes a time-varying ache aisle that generally includes assorted instances of response/improvement abiding disease, and progression/worsening. This botheration is mitigated but not necessarily alone back assay is belted to the assessment/plan breadth of the note. This presents a claiming to simple rules-based NLP approaches that await on key agreement such as “response” and “progression” to actuate the accepted cachet of a patient’s disease.

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Other board accept approved to abode these challenges by appliance human-supervised beginning approaches to architecture NLP models that use rules-based linguistic and semantic annotation.21,22 Although rules-based methods can accomplish acceptable performance,23 they crave all-encompassing animal abetment of the allocation rules and aftereffect in a archetypal that is awful customized to the specific abstracts set used. NLP techniques accept acquired from rules-based algorithms to computational and probabilistic linguistics and, added recently, to the boundless acceptance of apparatus learning.24 The use of abysmal acquirements methods to abstract blight outcomes from analytic addendum has been limited, although above-mentioned authors accept acclimated abysmal NLP to abstract cancer-related advice from anatomy reports,25-27 as able-bodied as Breast Imaging Reporting and Abstracts System comment from radiology reports.28

In this report, we authenticate that a neural network–based NLP archetypal can accomplish commensurable achievement to animal curation after the charge to absolutely archetypal linguistic rules. Rather than developing an overarching NLP algorithm to analyze “response” or “progression” anywhere in the EHR, we labeled annal and accomplished models to analyze these constructs from abstracts with acutely defined provenance. We additionally activated a agent beeline archetypal to almost the neural arrangement archetypal outputs, acquiescent after-effects advertence that our models were appliance automatic features, allowance to abode the atramentous box objection29 that is generally aloft to neural network–based approaches.

Limitations of this absorption accommodate its focus on patients with lung blight who were evaluated by medical oncologists at a distinct institution. Future studies are bare to actuate whether these methods can be cryptic to patients with added blight types and those accepting affliction at added institutions, decidedly those that use altered EHR systems. Furthermore, oncologists sometimes accept irreducible ambiguity about whether a patient’s blight is responding or avant-garde at the time that a analytic agenda is filed. Animal curators were instructed to assort cryptic addendum as indeterminate, and such addendum would again accept been categorized as apery the absence of an aftereffect of absorption for bifold archetypal training and evaluation. Although this access could abatement the acuteness of chiral curation for some bookish accurate aftereffect such as blight response, it ability additionally access the specificity, potentially apprehension animal and apparatus curations of absolute outcomes added acutely relevant. In addition, cases in which animal curators were borderline whether to announce an aftereffect as present or general ability accept yielded blatant ambition labels. This would present a claiming for archetypal training and appraisal that ability be accepted to bent after-effects against the null; in this case, archetypal metrics including AUROC, AUPRC, and F1 account could belittle the achievement accepted in the clean-label case.

In this report, we authenticate that the use of neural network–based NLP for curation of analytic addendum is achievable and carefully recapitulates animal curation. This represents a atypical adjustment for annotating EHR abstracts to facilitate biomarker assay and blight affliction delivery. Because ample accomplice sizes are all-important to analyze associations amid attenuate genomic markers and aberrant acknowledgment or attrition to treatment, NLP-based aftereffect assay may facilitate identification of important genomic-phenomic associations. Added assignment is bare to calibration this address to added blight types and to appraise its achievement on EHR annal from multicenter cohorts.

Supported by National Blight Institute Grants No. K05CA169384 (D.S.) and K99CA245899 (K.L.K.); the Claude Dauphin Philanthropic Assay Fund (B.E.J. and D.S.); and the Simeon J. Fortin Foundation (K.L.K.).

Conception and design: Kenneth L. Kehl, Wenxin Xu, Eva Lepisto, Deborah Schrag

Financial support: Kenneth L. Kehl, Deborah Schrag

Administrative support: Eva Lepisto, Bruce E. Johnson, Deborah Schrag

Provision of absorption abstracts or patients: Bruce E. Johnson, Deborah Schrag

Collection and accumulation of data: Kenneth L. Kehl, Wenxin Xu, Eva Lepisto, Bruce E. Johnson, Deborah Schrag

Data assay and interpretation: Kenneth L. Kehl, Wenxin Xu, Haitham Elmarakeby, Michael J. Hassett, Eliezer M. Van Allen, Bruce E. Johnson, Deborah Schrag

Manuscript writing: All authors

Final approval of manuscript: All authors

Accountable for all aspects of the work: All authors

AUTHORS’ DISCLOSURES OF POTENTIAL CONFLICTS OF INTEREST

The afterward represents acknowledgment advice provided by authors of this manuscript. All relationships are advised compensated unless contrarily noted. Relationships are self-held unless noted. I = Immediate Family Member, Inst = My Institution. Relationships may not chronicle to the accountable amount of this manuscript. For added advice about ASCO’s battle of absorption policy, amuse accredit to www.asco.org/rwc or ascopubs.org/cci/author-center.

Open Payments is a accessible database absolute advice appear by companies about payments fabricated to US-licensed physicians (Open Payments).

Kenneth L. Kehl

Consulting or Advisory Role: Aetion

Eva Lepisto

Employment: Kiniksa Pharmaceuticals (I)

Stock and Added Ownership Interests: Kiniksa Pharmaceuticals (I)

Michael J. Hassett

Research Funding: IBM

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Eliezer M. Van Allen

Stock and Added Ownership Interests: Syapse, Tango Therapeutics, Genome Medical, Microsoft, Ervaxx

Consulting or Advisory Role: Syapse, Roche, Third Rock Ventures, Takeda, Novartis, Genome Medical, InVitae, Illumina, Tango Therapeutics, Ervaxx, Janssen

Speakers’ Bureau: Illumina

Research Funding: Bristol Myers Squibb, Novartis

Patents, Royalties, Added Intellectual Property: Apparent on assay of retained intron as antecedent of blight neoantigens (Inst), apparent on assay of chromatin regulators as biomarkers of acknowledgment to blight immunotherapy (Inst), apparent on analytic estimation algorithms appliance blight atomic abstracts (Inst)

Travel, Accommodations, Expenses: Genentech

Bruce E. Johnson

Consulting or Advisory Role: Novartis, Foundation Medicine, Hengrui Therapeutics, Daiichi Sankyo, Chugai Pharmaceuticals, Eli Lilly

Research Funding: Novartis (Inst), Toshiba (Inst)

Patents, Royalties, Added Intellectual Property: Dana-Farber Blight Institute

Deborah Schrag

Stock and Added Ownership Interests: Merck (I)

Honoraria: Pfizer

Consulting or Advisory Role: Journal of the American Medical Association

Research Funding: American Affiliation for Blight Assay (Inst), GRAIL (Inst)

Patents, Royalties, Added Intellectual Property: PRISSMM archetypal is trademarked, and curation accoutrement are accessible to bookish medical centers and government beneath artistic aliment license.

Travel, Accommodations, Expenses: IMEDEX, Absorption Anesthetic World Conference

Other Relationship: Journal of the American Medical Association

No added abeyant conflicts of absorption were reported.

TABLE A1. Interrater Airheadedness Amid Animal Curators

TABLE A2. Archetypal Achievement Characteristics for Anniversary Label (any cancer, progression/worsening and response/improvement) Back Archetypal Was Accomplished Appliance the Absolute Medical Oncology Agenda Text

TABLE A3. Abundant Representation of Beeline Allegorical Archetypal Accomplished on Convolutional Neural Arrangement Outputs (top 10 absolute and abrogating appearance in anniversary archetypal are presented)

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