Additional research is necessary to assess patient and physician perceptions of reviewing immediately released test results, which warrants future research.
Objective: This study aimed to develop and assess the performance of fine-tuned large language models for generating responses to patient messages sent via an electronic health record patient portal. Methods: Utilizing a dataset of messages and responses extracted from the patient portal at a large academic medical center, we developed a model (CLAIR-Short) based on a pre-trained large language model (LLaMA-65B). In addition, we used the OpenAI API to update physician responses from an open-source dataset into a format with informative paragraphs that offered patient education while emphasizing empathy and professionalism. By combining with this dataset, we further fine-tuned our model (CLAIR-Long). To evaluate the fine-tuned models, we used ten representative patient portal questions in primary care to generate responses. We asked primary care physicians to review generated responses from our models and ChatGPT and rated them for empathy, responsiveness, accuracy, and usefulness. Results: The dataset consisted of a total of 499,794 pairs of patient messages and corresponding responses from the patient portal, with 5,000 patient messages and ChatGPT-updated responses from an online platform. Four primary care physicians participated in the survey. CLAIR-Short exhibited the ability to generate concise responses similar to provider responses. CLAIR-Long responses provided increased patient educational content compared to CLAIR-Short and were rated similarly to ChatGPT responses, receiving positive evaluations for responsiveness, empathy, and accuracy, while receiving a neutral rating for usefulness. Conclusion: Leveraging large language models to generate responses to patient messages demonstrates significant potential in facilitating communication between patients and primary care providers.
Background and Objective Patient portal use has increased over the last two decades in response to consumer demand and government regulation. Despite growing adoption, few guidelines exist to direct successful implementation and governance. We describe the policies and procedures that have governed over a decade of continuous My Health at Vanderbilt (MHAV) patient portal use. Methods We examined MHAV usage data between May 2007 and November 2017. We classified patient portal activity into eight functional categories: Appointment, Billing, Document Access, Genetics, Health Result, Immunization, Medication, and Messaging. We describe our operating policies and measure portal uptake, patient account activity, and function use over time. Results By the end of the study period, there were 375 517 registered accounts. Policies made MHAV available to competent adults and adolescents 13 and over. Patients signed up for a limited access account online, which could be upgraded to a full-access account after identity verification. Patients could assign proxy accounts to family and caregivers, which permitted nonpatient access to select MHAV functions. Laboratory and radiology results were accessible via MHAV. Results were classified into three groups based on sensitivity, which govern the length of delay before results appeared in MHAV. Discussion and Conclusion Patient portals offer significant opportunity to engage patients in their healthcare. However, there remains a need to understand how policies can promote uptake and use. We anticipate that other institutions can apply concepts from our policies to support meaningful patient portal engagement.
Pediatric patients and caregivers have avidly used messaging, test result, and appointment functions. The majority of access was done by surrogates. Adolescent portal usage increased with age. Most accounts for pediatric patients were only used actively for a few years, with peak usage for patients in early childhood and late adolescence.
ImportanceThe 21st Century Cures Act Final Rule mandates the immediate electronic availability of test results to patients, likely empowering them to better manage their health. Concerns remain about unintended effects of releasing abnormal test results to patients.ObjectiveTo assess patient and caregiver attitudes and preferences related to receiving immediately released test results through an online patient portal.Design, Setting, and ParticipantsThis large, multisite survey study was conducted at 4 geographically distributed academic medical centers in the US using an instrument adapted from validated surveys. The survey was delivered in May 2022 to adult patients and care partners who had accessed test results via an online patient portal account between April 5, 2021, and April 4, 2022.ExposuresAccess to test results via a patient portal between April 5, 2021, and April 4, 2022.Main Outcomes and MeasuresResponses to questions related to demographics, test type and result, reaction to result, notification experience and future preferences, and effect on health and well-being were aggregated. To evaluate characteristics associated with patient worry, logistic regression and pooled random-effects models were used to assess level of worry as a function of whether test results were perceived by patients as normal or not normal and whether patients were precounseled.ResultsOf 43 380 surveys delivered, there were 8139 respondents (18.8%). Most respondents were female (5129 [63.0%]) and spoke English as their primary language (7690 [94.5%]). The median age was 64 years (IQR, 50-72 years). Most respondents (7520 of 7859 [95.7%]), including 2337 of 2453 individuals (95.3%) who received nonnormal results, preferred to immediately receive test results through the portal. Few respondents (411 of 5473 [7.5%]) reported that reviewing results before they were contacted by a health care practitioner increased worry, though increased worry was more common among respondents who received abnormal results (403 of 2442 [16.5%]) than those whose results were normal (294 of 5918 [5.0%]). The result of the pooled model for worry as a function of test result normality was statistically significant (odds ratio [OR], 2.71; 99% CI, 1.96-3.74), suggesting an association between worry and nonnormal results. The result of the pooled model evaluating the association between worry and precounseling was not significant (OR, 0.70; 99% CI, 0.31-1.59).Conclusions and RelevanceIn this multisite survey study of patient attitudes and preferences toward receiving immediately released test results via a patient portal, most respondents preferred to receive test results via the patient portal despite viewing results prior to discussion with a health care professional. This preference persisted among patients with nonnormal results.
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