Laboratory Results Release to Patients under the 21st Century Cures Act: The Eight Stakeholders Who Should Care

Immediate Access to Radiology Reports: Perspectives on X Before and After the Cures Act Information Blocking Provision

OBJECTIVE

The 21st Century Cures Act's information blocking provision mandates that patients have immediate access to their electronic health information, including radiology reports. We evaluated public opinions surrounding this policy on X, a microblogging platform with over 400 million users.

METHODS

We retrieved 27,522 posts related to radiology reports from October 5, 2020, through October 4, 2021. One reviewer performed initial screening for relevant posts. Two reviewers categorized user type and post theme(s) using a predefined coding system. Posts were grouped as "pre-Cures" (6 months before information blocking) and "post-Cures" (6 months after). Descriptive statistics and χ2 tests were performed.

RESULTS

Among 1,155 final posts, 1,028 unique users were identified (64% patients, 11% non-radiologist physicians, 4% radiologists). X activity increased, with 40% (n = 462) pre-Cures and 60% (n = 693) post-Cures. Early result notification before referring providers was the only theme that significantly increased post-Cures (+3%, P = .001). Common negative themes were frustration (33%), anxiety (27%), and delay (20%). Common positive themes were gratitude for radiologists (52%) and autonomy (21%). Of posts expressing opinions on early access, 84% favored and 16% opposed it, with decreased preference between study periods (P = .006). More patients than physicians preferred early access (92% versus 40%, P < .0001).

DISCUSSION

X activity increased after the information blocking provision, partly due to conversation about early notification. Despite negative experiences with reports, most users preferred early access. Although the Cures Act is a positive step toward open access, work remains to improve patients' engagement with their radiology results.

Establishing priorities for implementation of large language models in pathology and laboratory medicine

Artificial intelligence and machine learning have numerous applications in pathology and laboratory medicine. The release of ChatGPT prompted speculation regarding the potentially transformative role of large-language models (LLMs) in academic pathology, laboratory medicine, and pathology education. Because of the potential to improve LLMs over the upcoming years, pathology and laboratory medicine clinicians are encouraged to embrace this technology, identify pathways by which LLMs may support our missions in education, clinical practice, and research, participate in the refinement of AI modalities, and design user-friendly interfaces that integrate these tools into our most important workflows. Challenges regarding the use of LLMs, which have already received considerable attention in a general sense, are also reviewed herein within the context of the pathology field and are important to consider as LLM applications are identified and operationalized.

Unsolicited Patient Complaints Following the 21st Century Cures Act Information-Blocking Rule

Importance

The 21st Century Cures Act includes an information-blocking rule (IBR) that requires health systems to provide patients with immediate access to their health information in the electronic medical record upon request. Patients accessing their health information before they receive an explanation from their health care team may experience confusion and may be more likely to share unsolicited patient complaints (UPCs) with their health care organization.

Objective

To evaluate the quantity of UPCs about physicians before and after IBR implementation and to identify themes in UPCs that may identify patient confusion, fear, or anger related to the release of information.

Design, Setting, and Participants

This retrospective cohort study was conducted with an interrupted time-series analysis of UPCs spanning January 1, 2020, to June 30, 2022. The data were obtained from a single academic medical center, Vanderbilt University Medical Center, at which the IBR was implemented on January 20, 2021. Data analysis was performed from January 11 to July 15, 2023.

Exposure

Implementation of the IBR on January 20, 2021.

Main Outcomes and Measures

The primary outcome was the monthly rate of UPCs before and after IBR implementation. A qualitative analysis was performed for UPCs received after IBR implementation. The Wilcoxon rank-sum test was used to compare monthly complaints between the pre- and post-IBR groups. The Pearson χ2 test was used to compare proportions of complaints by UPC category between time periods.

Results

The medical center received 8495 UPCs during the study period: 3022 over 12 months before and 5473 over 18 months after institutional IBR implementation. There was no difference in the monthly proportions of UPCs per 1000 patient encounters before (median, 0.81 [IQR, 0.75-0.88]) and after (median, 0.83 [IQR, 0.77-0.89]) IBR implementation (difference in medians, -0.02 [95% CI, -0.12 to 0.07]; P =.86). Segmented regression analysis revealed no difference in monthly UPCs (β [SE], 0.03 [0.09]; P =.72).

Conclusions and Relevance

In this cohort study, implementation of the Cures Act IBR was not associated with an increase in monthly rates of UPCs. These findings suggest that review of UPCs identified as IBR-specific complaints may allow clinicians and organizations to prepare patients that their test and procedure results may be available before clinicians are able to review them and respond.