Empowering diversity: striving for inclusivity by leveraging the American Medical Informatics Association's "For Your Informatics" Podcast.

Importance: Starting in 2018, the 'Women in American Medical Informatics Association (AMIA) Podcast' was women-focused, in 2021 the podcast was rebranded and relaunched as the "For Your Informatics Podcast" (FYI) to expand the scope of the podcast to include other historically underrepresented groups. That expansion of the scope, together with a rebranding and marketing campaign, led to a larger audience and engagement of the AMIA community.

Objectives: The goals of this case report are to characterize our rebranding and expanding decisions, and to assess how they impacted our listenership and engagement to achieve the Podcast goals of increasing diversity among the Podcast team, guests, audience, and improve audience engagement.

Pediatric Consent on FHIR.

Background:  Standardizing and formalizing consent processes and forms can prevent ambiguities, convey a more precise meaning, and support machine interpretation of consent terms.

Objectives:  Our goal was to introduce a systematic approach to standardizing and digitizing pediatric consent forms, which are complex due to legal requirements for child and legal guardian involvement.

Methods:  First, we reviewed the consent requirements from the Arizona regulation, and we used 21 pediatric treatment consents from five Arizona health care organizations to propose and evaluate an implementation-agnostic Consent for Treatment Framework.

Perceptions and Concerns of SUD Treatment Organizations Regarding the CARES Act's Alterations to Patient Confidentiality Regulations.

Objectives: Learn how substance use disorder (SUD) treatment organizations view and respond to changes in confidentiality and disclosure law following adoption of CARES Act Sec. 3221 and prior to promulgation of revised implementing regulations.

Methods: Online survey followed by informal interviews.

Behavioral Health Professionals' Perceptions on Patient-Controlled Granular Information Sharing (Part 2): Focus Group Study.

Background: Patient-directed selection and sharing of health information "granules" is known as granular information sharing. In a previous study, patients with behavioral health conditions categorized their own health information into sensitive categories (eg, mental health) and chose the health professionals (eg, pharmacists) who should have access to those records. Little is known about behavioral health professionals' perspectives of patient-controlled granular information sharing (PC-GIS).

Behavioral Health Professionals' Perceptions on Patient-Controlled Granular Information Sharing (Part 1): Focus Group Study.

Background: Patient-controlled granular information sharing (PC-GIS) allows a patient to select specific health information "granules," such as diagnoses and medications; choose with whom the information is shared; and decide how the information can be used. Previous studies suggest that health professionals have mixed or concerned opinions about the process and impact of PC-GIS for care and research. Further understanding of behavioral health professionals' views on PC-GIS are needed for successful implementation and use of this technology.

A Data-Driven Iterative Approach for Semi-automatically Assessing the Correctness of Medication Value Sets: A Proof of Concept Based on Opioids.

Background: Value sets are lists of terms (e.g., opioid medication names) and their corresponding codes from standard clinical vocabularies (e.

Design and evaluation of a Women in American Medical Informatics Association (AMIA) leadership program.

The objective is to report on the design and evaluation of the inaugural Women in AMIA Leadership Program. A year-long leadership curriculum was developed. Survey responses were summarized with descriptive statistics and quotes selected.

EHR Conversion on the PreOp Care: A Pre-Post Workflow Comparison.

The impact of EHRs conversion on clinicians' daily work is crucial to evaluate the success of the intervention for Hospitals and to yield valuable insights into quality improvement. To assess the impact of different EHR systems on the preoperative nursing workflow, we used a structured framework combining quantitative time and motion study and qualitative cognitive analysis to characterize, visualize and explain the differences before and after an EHR conversion. The results showed that the EHR conversion brought a significant decrease in the patient case time and a reduced percentage of time using EHR.

We're Lost, But We are Making Good Time: Navigating Complex Pathways in a Patient-Order Management Task.

Patient order management (POM) is a mission-critical task for perioperative workflow. Interface complexity within different EHR systems result in poor usability, increasing documentation burden. POM interfaces were compared across two systems prior to (Cerner SurgiNet) and subsequent to an EHR conversion (Epic).

A pilot comparison of medical records sensitivity perspectives of patients with behavioral health conditions and healthcare providers.

This pilot study compares medical record data sensitivity (e.g., depression is sensitive) and categorization perspective (e.

Study of EHR-mediated workflows using ethnography and process mining methods.

Rapid ethnography and data mining approaches have been used individually to study clinical workflows, but have seldom been used together to overcome the limitations inherent in either type of method. For rapid ethnography, how reliable are the findings drawn from small samples? For data mining, how accurate are the discoveries drawn from automatic analysis of big data, when compared with observable data? This paper explores the combined use of rapid ethnography and process mining, aka ethno-mining, to study and compare metrics of a typical clinical documentation task, vital signs charting. The task was performed with different electronic health records (EHRs) used in three different hospital sites.

A micro-analytic approach to understanding electronic health record navigation paths.

Clinician task performance is significantly impacted by the navigational efficiency of the system interface. Here we propose and evaluate a navigational complexity framework useful for examining differences in electronic health record (EHR) interface systems and their impact on task performance. The methodological approach includes 1) expert-based methods-specifically, representational analysis (focused on interface elements), keystroke level modeling (KLM), and cognitive walkthrough; and 2) quantitative analysis of interactive behaviors based on video-captured observations.

Process Mining and Ethnography Study of Medication Reconciliation Tasks.

We studied the medication reconciliation (MedRec) task through analysis of computer logs and ethnographic data. Time spent by healthcare providers performing MedRec was compared between two different EHR systems used at four different regional perioperative settings. Only one of the EHRs used at two settings generated computer logs that supported automatic discovery of the MedRec task.

Pilot evaluation of sensitive data segmentation technology for privacy.

Background: Consent2Share (C2S) is an open source software created by the Office of the National Coordinator Data Segmentation for Privacy initiative to support electronic health record (EHR) granular segmentation. To date, there are no published formal evaluations of Consent2Share.

Method: Structured data (e.

A Task-Analytic Framework Comparing Preoperative Electronic Health Record-Mediated Nursing Workflow in Different Settings.

Preoperative care is a critical, yet complex, time-sensitive process. Optimization of workflow is challenging for many reasons, including a lack of standard workflow analysis methods. We sought to comprehensively characterize electronic health record-mediated preoperative nursing workflow.

Mental health professional perspectives on health data sharing: Mixed methods study.

This study explores behavioral health professionals' perceptions of granular data. Semi-structured in-person interviews of 20 health professionals were conducted at two different sites. Qualitative and quantitative analysis was performed.

Mental health professionals' perceptions on patients control of data sharing.

Integrated mental and physical care environments require data sharing, but little is known about health professionals' perceptions of patient-controlled health data sharing. We describe mental health professionals' views on patient-controlled data sharing using semi-structured interviews and a mixed-method analysis with thematic coding. Health information rights, specifically those of patients and health care professionals, emerged as a key theme.

Data-Driven Diabetes Education Guided by a Personalized Report for Patients on Insulin Pump Therapy.

Objective: It is difficult to assess self-management behaviors (SMBs) and incorporate them into a personalized self-care plan. We aimed to develop and apply SMB phenotyping algorithms from data collected by diabetes devices and a mobile health (mHealth) application to create patient-specific SMBs reports to guide individualized interventions. Follow-up interventions aimed to understand patient's reasoning behind discovered SMB choices.

State of the art and a mixed-method personalized approach to assess patient perceptions on medical record sharing and sensitivity.

Objective: Sensitive health information possesses risks, such as stigma and discrimination, when disclosed. Few studies have used a patient's own electronic health records (EHRs) to explore what types of information are considered sensitive andhow such perceptions affect data sharing preferences. After a systematic literature review, we designed and piloted a mixed-method approach that employs an individual's own records to assess content sensitivity and preferences for granular data sharing for care and research.

Mayo Clinic Registry of Operational Tasks (ROOT): A Paradigm Shift in Electronic Health Reco Implementation Evaluation.

Objective: To systematically examine clinical workflows before and after a major electronic health record (EHR) implementation, we performed this study. EHR implementation and/or conversion are associated with many challenges, which are barriers to optimal care. Clinical workflows may be significantly affected by EHR implementations and conversions, resulting in provider frustration and reduced efficiency.

Design and Pilot Testing of an English and Spanish Behavioral Health Patient Survey on Data Privacy.

We piloted a Spanish and English survey on data privacy. Thirty-one Latino behavioral health patients completed the survey in person with a preference for paper (78%) over electronic questionnaire. Dialect variations across Latino countries and the lack of tools to assess reading level in Spanish affected comprehension.

Perceptions and Preferences About Granular Data Sharing and Privacy of Behavioral Health Patients.

Little is known about data sharing preferences for care and research of behavioral health patients. Eighty-six behavioral health patients (n = 37 Latinos; n = 32 with serious mental illness) completed questionnaires, in either English or Spanish, with items assessing their views on privacy and sensitivity of health record information. Most patients (82.

Systematic Literature Review of Prescription Drug Monitoring Programs.

Prescription opioid abuse has become a serious national problem. To respond to the opioid epidemic, states have implemented prescription drug monitoring programs (PDMPs) to monitor and reduce opioid abuse. We conducted a systematic literature review to better understand the PDMP impact on reducing opioid abuse, improving prescriber practices, and how EHR integration has impacted PDMP usability.

Multi-Method Study of Electronic Health Records Workflows.

EHRs transform work practices in ways that enhance or impede the quality of care. There is a need for in-depth analysis of EHR workflows, particularly in complex clinical environments. We investigated EHR-basedpre-operative workflows by combining findings from 18 interviews, 7 days of observations, and process mining of EHR interactions from 31 personnel caring for 375 patients at one tertiary referral center.