Incidental Pulmonary Nodules Reported on CT Abdominal Imaging: Frequency and Factors Affecting Inclusion in the Hospital Discharge Summary

Improving Resident Hospital Discharge Communication by Changing Electronic Health Record Templates to Enhance Primary Care Provider Satisfaction

BACKGROUND AND OBJECTIVES

Despite use of standardized electronic health record templates, the structure of discharge summaries may hinder communication from inpatient settings to primary care providers (PCPs). We developed an enhanced electronic discharge summary template to improve PCP satisfaction with written discharge summaries targeting diagnoses, medication reconciliation, laboratory test results, specialist follow-up, and recommendations.

METHODS

Resident template usage was measured using statistical process control charts. PCP reviewers' discharge summary satisfaction was surveyed using 5-point Likert scales analyzed using the Mann-Whitney U test. Residents were surveyed for satisfaction.

RESULTS

Resident template usage increased from 61% initially to 72% of discharge summaries at 6 months. The PCP reviewers reported increased satisfaction for summaries using the template compared with those without (4.3 vs 3.9, P = .003). Surveyed residents desired template inclusion in the default electronic discharge summary (93%).

CONCLUSIONS

This system-level resident-initiated quality improvement initiative created a novel discharge summary template that achieved widespread usage among residents and significantly increased outpatient PCP satisfaction.

Clinical Implementation of a Combined Artificial Intelligence and Natural Language Processing Quality Assurance Program for Pulmonary Nodule Detection in the Emergency Department Setting

OBJECTIVE

This quality assurance study assessed the implementation of a combined artificial intelligence (AI) and natural language processing (NLP) program for pulmonary nodule detection in the emergency department setting. The program was designed to function outside of normal reading workflows to minimize radiologist interruption.

MATERIALS AND METHODS

In all, 19,246 CT examinations including at least some portion of the lung anatomy performed in the emergent setting from October 1, 2021, to June 1, 2022, were processed by the combined AI-NLP program. The program used an AI algorithm trained on 6-mm to 30-mm pulmonary nodules to analyze CT images and an NLP to analyze radiological reports. Cases flagged as negative for pulmonary nodules by the NLP but positive by the AI algorithm were classified as suspected discrepancies. Discrepancies result in secondary review of examinations for possible addenda.

RESULTS

Out of 19,246 CT examinations, 50 examinations (0.26%) resulted in secondary review, and 34 of 50 (68%) reviews resulted in addenda. Of the 34 addenda, 20 patients received instruction for new follow-up imaging. Median time to addendum was 11 hours. The majority of reviews and addenda resulted from missed pulmonary nodules on CT examinations of the abdomen and pelvis.

CONCLUSION

A background quality assurance process using AI and NLP helped improve the detection of pulmonary nodules and resulted in increased numbers of patients receiving appropriate follow-up imaging recommendations. This was achieved without disrupting in-shift radiologist workflow or causing significant delays in patient follow for the diagnosed pulmonary nodule.

A Standardized Radiology Template Improves Incidental Adrenal Mass Follow-Up: A Prospective Effectiveness and Implementation Study

PURPOSE

Incidental adrenal masses (IAMs) are common but rarely evaluated. To improve this, we developed a standardized radiology report recommendation template and investigated its implementation and effectiveness.

METHODS

We prospectively studied implementation of a standardized IAM reporting template as part of an ongoing quality improvement initiative, which also included primary care provider (PCP) notifications and a straightforward clinical algorithm. Data were obtained via medical record review and a survey of radiologists. Outcomes included template adoption rates and acceptability (implementation measures), as well as the proportion of patients evaluated and time to follow-up (effectiveness outcomes).

RESULTS

Of 4,995 imaging studies, 200 (4.0%) detected a new IAM. The standardized template was used in 54 reports (27.0%). All radiologists surveyed were aware of the template, and 91% affirmed that standardized recommendations are useful. Patients whose reports included the template were more likely to have PCP follow-up after IAM discovery compared with those with no template (53.7% versus 36.3%, P = .03). After adjusting for sex, current or prior malignancy, and provider ordering the initial imaging (PCP, other outpatient provider, or emergency department or inpatient provider), odds of PCP follow-up remained 2.0 times higher (95% confidence interval 1.02-3.9). Patients whose reports included the template had a shorter time to PCP follow-up (log-rank P = .018). PCPs ultimately placed orders for biochemical testing (35.2% versus 18.5%, P = .01), follow-up imaging (40.7% versus 23.3%, P = .02), and specialist referral (22.2% versus 4.8%, P < .01) for a higher proportion of patients who received the template compared with those who did not.

CONCLUSIONS

Use of a standardized template to communicate IAM recommendations was associated with improved IAM evaluation. Our template demonstrated high acceptability, but additional strategies are necessary to optimize adoption.

Outcomes of Incidental Lung Nodules With Structured Recommendations and Electronic Tracking

OBJECTIVE

To evaluate the impact of structured recommendations on follow-up completion for incidental lung nodules (ILNs).

METHODS

Patients with ILNs before and after implementation of structured Fleischner recommendations and electronic tracking were sampled randomly. The cohorts were compared for imaging follow-up. Multivariable logistic regression was used to assess appropriate follow-up and loss to follow-up, with independent variables including use of structured recommendations or tracking, age, gender, race, ethnicity, setting of the index test (inpatient, outpatient, emergency department), smoking history, and nodule features.

RESULTS

In all, 1,301 patients met final inclusion criteria, including 255 patients before and 1,046 patients after structured recommendations or tracking. Baseline differences were found in the pre- and postintervention groups, with smaller ILNs and younger age after implementing structured recommendations. Comparing pre- versus postintervention outcomes, 40.0% (100 of 250) versus 29.5% (309 of 1,046) of patients had no follow-up despite Fleischner indications for imaging (P = .002), and among the remaining patients, 56.6% (82 of 145) versus 75.0% (553 of 737) followed up on time (P < .001). Delayed follow-up was more frequent before intervention. Differences postintervention were mostly accounted for by nodules ≤ 8 mm in the outpatient setting (P < .001). In multivariable analysis, younger age, White race, outpatient setting, and larger nodule size showed significant association with appropriate follow-up completion (P < .015), but structured recommendations did not. Similar results applied for loss to follow-up.

DISCUSSION

Consistent use of structured reporting is likely key to mitigate selection bias when benchmarking rates of appropriate follow-up of ILN. Emergency department patients and inpatients are at high risk of missed or delayed follow-up despite structured recommendations.

Creating an Incidental Pulmonary Nodule Safety-Net Program

Pulmonary nodules are a frequent, incidental finding on CT scans, ranging from up to 8.4% on abdominal scans and up to 48% on CT angiograms. Incidental findings are sometimes disregarded or overshadowed by critical situations and may not be disclosed or documented on discharge. The costs and risks associated with incidental findings are not insignificant, including the risk of a delayed diagnosis of lung cancer. A medical center commitment to prevent overlooked incidental pulmonary nodules led to the development of an incidental pulmonary nodule program. The program, led by an advanced practice nurse, established processes to identify patients with incidental lung nodules on CT scans and developed criteria for further follow-up with the primary care provider and the patient. Improvements with consistent use of Fleischner guidelines in scan reports by radiologists and increased ownership in informing patients of incidental nodules by ED and trauma providers have occurred. As the frequency of chest CT imaging is increasing, the number of incidental nodules identified will also increase. A lung nodule surveillance process would greatly benefit every lung nodule clinic or hospital system for management of pulmonary nodules.

Statistical modeling can determine what factors are predictive of appropriate follow-up in patients presenting with incidental pulmonary nodules on CT

PURPOSE

To assess the performance of statistical modeling in predicting follow-up adherence of incidentally detected pulmonary nodules (IPN) on CT, based on patient variables (PV), radiology report related variables (RRRV) and physician-patient communication variables (PPCV).

METHODS

200 patients with IPN on CT were retrospectively identified and randomly selected. PV (age, gender, smoking status, ethnicity), RRRV (nodule size, patient context, whether follow-up recommendations were provided) and PPCV (whether referring physician documented IPN and ordered follow-up on the electronic medical record) were recorded. Primary outcome was whether patients received appropriate follow-up within +/- 1 month of the recommended time frame. Statistical methods included logistic regression and machine learning (K-nearest neighbors and support vector machine).

RESULTS

Adherence was low, with or without recommendations provided in the radiology report (23.4 %-27.4 %). Whether the referring physician ordered follow-up was the dominant predictor of adherence in all models. The following variables were statistically significant predictors of whether referring physician ordered follow-up: recommendations provided in the radiology report, smoking status, patient context and nodule size (FDR logworth of respectively 21.18, 11.66, 2.35, 1.63, p < 0.05). Prediction accuracy varied from 72 % (PV) to 93 % (PPCV, all variables).

CONCLUSION

PPCV are the most important predictors of adherence. Amongst all variables, patient context, smoking status, nodule size, and whether the radiologist provided follow-up recommendations in the report were all statistically significant predictors of patient follow-up adherence, supporting the utility of statistical modeling for analytics, quality assurance and optimization of outcomes related to IPN.

Clinical Documentation for Intensivists: The Impact of Diagnosis Documentation

OBJECTIVES

The aim of this review is to describe the interaction of clinical documentation with patient care, measures of patient acuity, quality metrics, research database accuracy, and healthcare reimbursement in order to highlight potential areas of improvement for intensivists.

DATA SOURCES

An online search of PubMed was undertaken as well as review of resources published by the American Academy of Pediatrics, the Society of Critical Care Medicine, the American Medical Association, and the Association of Clinical Documentation Improvement Specialists.

STUDY SELECTION

Selected publications included those that described coding, medical record documentation, healthcare reimbursement, quality metrics, administrative databases, Clinical Documentation Improvement programs, medical scribe programs, and various payment models.

DATA EXTRACTION

Relevant information was extracted to highlight the impact of diagnosis documentation on patient care, perceived patient severity of illness, quality metrics, and healthcare reimbursement. Query data from our hospital's Clinical Documentation Improvement program were reviewed to highlight areas of improvement within our own Division of Critical Care Medicine. Additionally, interventions to improve clinical documentation were incorporated into this review.

DATA SYNTHESIS

Available data in the literature indicate that documentation of precise diagnoses in the medical record has a positive impact on quality metrics, accuracy of administrative databases, hospital reimbursement, and perceived patient complexity. However, there is insufficient data to make conclusions regarding documentation of specific diagnoses and effects on patient care. Administrative responsibilities associated with documentation have been increasing, especially with the introduction of electronic medical records.

CONCLUSIONS

Documentation of specific diagnoses in the medical record is important in the broad context of our existing medical system but there is an associated burden in doing so. Widespread implementation of electronic medical record systems has inadvertently led to clinician dissatisfaction and burnout. Research is needed to further evaluate the impact of documentation on patient care as well as steps to decrease the associated burden.

No stone unturned: Nodule Net, an intervention to reduce loss to follow-up of lung nodules

OBJECTIVE

Inadequate lung nodule surveillance leads to diagnostic delays. We implemented a retrospective intervention program, Nodule Net, to improve surveillance in our hospital.

METHODS

9,224 Chest computed tomography (CT) scans between January 1, 2015 and December 31, 2016 were manually reviewed for lung nodules. For patients without follow-up, charts were reviewed to assess follow-up. If follow-up appeared indicated, the clinician or patient was contacted, and follow-up was tracked.

RESULTS

Lung nodules were identified on 5,101 (55%) of 9,224 scans. Follow-up was potentially indicated and not completed in 1,385 (27%). 183 (13%) were excluded after imaging review. 1,202 received outreach. Of the 801 (66%) with a provider in our system, 225 (27%) returned for follow-up. Nodules were stable in 199 (88%), new or growing in 23 (11%), resolved in 3 (1%), and stage 1 lung cancer in 2 (1%). 90 (11%) had follow-up outside our system and 431 (51%) had no follow-up due to a clinical contraindication. 55 (7%) have imaging pending and 14 (2%) are awaiting pulmonary evaluation. Of the 302 (25%) patients with providers outside our system, 121 (40%) had followed-up elsewhere. 146 (48%) had no follow-up due to a clinical reason. 35 (12%) providers did not respond to outreach.

CONCLUSIONS

We identified 1,202 patients with lung nodules who needed follow-up over a two-year period. Compliance was more successful with providers within our hospital system. We recommend robust surveillance for patients to ensure follow-up is completed and clinical contraindications are well documented.