RxFill Heading link
Upwards of 50% of patients do not take their medications as prescribed or are non-adherent. Medication non-adherence and its associated negative health outcomes, such as hospitalizations and death, result in over $100 billion of avoidable healthcare costs in the United States annually. Medication non-adherence is a complex problem enabled by numerous patient, medication, provider, and system-wide factors. System factors may include healthcare costs, availability of medical appointments, or access to a community pharmacy, such as CVS or Walgreens.
Prescribers can address non-adherence and promote correct medication use by developing trusting patient-prescriber relationships and engaging patients and their caregivers in discussions about their medication therapies.
Current methods for prescribers to identify medication non-adherence are suboptimal. Patient self-reported adherence may be inaccurate due to misremembering or intentionally overreporting to please their provider. Patients’ medication insurance plans (also known as pharmacy benefit managers [PBMs]) may send providers letters or faxes when patients’ prescriptions are not picked up, but this information is often delayed months after the missed fills. PBM claims and adherence calculations that are based on dates the pharmacy fills the prescription (i.e., fill dates) are also limited because they assume once patients have the medicine in their possession, they will always take it correctly.
Health information technology (IT) has made great strides in facilitating communication between prescribers and pharmacies, including electronic prescriptions. Novel health IT functionalities incorporate prescription fill dates and adherence data into the electronic health record (EHR). Two of these functionalities are RxFill and Electronic Pharmacy Claims Data. RxFill integrates prescription fill dates from the patients’ community pharmacy into their clinic EHR record. Electronic Pharmacy Claims Data (EPCD) incorporates prescription fill dates from the patient’s PBM into the EHR.
Although medication adherence measures may be limited individually, combining prescription fill dates with patient self-reported adherence at the time of an appointment may enhance prescribers’ ability to make decisions regarding medications and clinical care. Prescribers may use prescription fill dates to quickly assess for non-adherence and engage patients in collaborative conversations. Health IT that incorporates prescription fill dates and adherence into the EHR must be useful, easy to use, and fit into the prescriber’s daily work.
Health IT aimed at incorporating prescription fill dates and medication adherence data into the EHR, such as RxFill and EPCD, have great potential to improve patient safety and promote quality outcomes, but only if the prescribers have access and use them regularly.
Therefore, our research aims to examine healthcare professionals’ acceptance and current use of RxFill and EPCD, as well as provide best practice recommendations for other health systems, clinics, and providers that will maximize RxFill and EPCD use and adoption.
NCPDP Foundation RxFill Overview Video Heading link
This project was funded by the NCPDP Foundation. This video shares a brief overview of RxFill and some preliminary findings.
17th Annual Conference on the Science of Dissemination and Implementation in Health - 2024 Heading link
Did you find your way here from the 2024 D&I Conference?
Feel free to review our conference abstracts and e-posters below!
RxFill Aim 2
Authors: Taylor L. Watterson, PharmD, PhD; Emily L. Hoffins, MS; Aaron M. Gilson, MS, MSSW, PhD; Peter C. Kleinschmidt, MD; Jamie A. Stone. MS
Background:
Accurate medication dispensing information, such as prescription fill dates, allows healthcare professionals to quickly assess for non-adherence. Health information technology (HIT) has attempted to make this information accessible by integrating Electronic Pharmacy Claims Data (EPCD) into the Electronic Health Record (EHR). However, for widespread innovation adoption, HIT must be easy to use and fit into daily work. The goal of this study was to examine the usability of EPCD.
Methods:
This study utilized the Unified Theory of Acceptance and Use of Technology to examine EPCD usability—including the HIT’s effort expectancy and facilitating conditions. Primary care prescribers and pharmacists were recruited from a midwestern academic health system. Near-live usability testing included a simulated EHR profile with EPCD data embedded in two locations: 1) hover-to-discover functionalities on the main page and 2) detailed information pages available by clicking on medication hyperlinks. Participants were provided navigational training, asked to review the profile as normal, then conduct a medication review encounter with a standardized patient. During the session, participants wore eye-tracking glasses (Tobii Pro Glasses 3) to capture gaze patterns. Data analysis used schematic mapping to obtain the number and duration of EPCD fixations (i.e., gaze maintained on a single location).
Findings:
Three primary care prescribers and two primary care pharmacists participated in the study. During the EHR profile review, participants spent the most time looking at the EPCD hover-to-discover information (total of 782 fixations, 7 minutes). No participants looked at the EPCD detailed information pages. During the encounter, participants spent the most time looking at the standardized patient (3371 fixations, 22 minutes), but also referred to EPCD information available via the hover-to-discover functionality (229 fixations, 1.9 minutes) and the EPCD detailed information pages (25 fixations, 12 seconds).
Implications for D&I Research:
It is essential for organizations to consider HIT ease of use and integration amidst work system contexts. Primary care professionals are experiencing excessive workload, contributed in part by EHR use and documentation burden. Therefore, HIT must be designed and implemented considering the end-users. Near-live usability testing, including eye-tracking and standardized patients, is helpful in determining best practices for information location, workflow integration, and sustained adoption.
Case Studies
Leveraging eye-tracking to support implementation decision making: Exploring use through three case studies
Authors: Emily L. Hoffins, Taylor L. Watterson, Maria E. Berbakov, Jamie A. Stone, Aaron M. Gilson, Jason S. Chladek, Stephanie M. Resendiz, Shiying Mai, Katherine G. Moore, Michelle A. Chui
Background:
Healthcare systems are complex; therefore, many interventions are designed with numerous components targeting different behaviors. While effective, these strategies can be expensive and difficult to implement and sustain. It is critical to identify which components are most effective and why for intervention sustainability. Eye-tracking is a novel methodology that can illuminate how each intervention component influences user behavior by serving as a proxy for participant cognition and real-time decision-making. This presentation shares three case studies applying eye-tracking technology to evaluate multi-component interventions.
Methods:
Following the Exploration, Preparation, Implementation, and Sustainment (EPIS) framework, identifying the most effective intervention components requires a researcher to detangle use of the multiple strategies from the participant’s context. Eye-tracking captures eye behaviors that reflect neural mechanisms of attention and cognitive function. Gaze data from wearable eye-tracking glasses can be categorized into areas and/or times of interests; allowing researchers to assess how often and for how long participants look at intervention components.
Findings:
Case one used eye-tracking to examine how older adults interacted with Senior SafeTM, a community pharmacy redesign promoting safer over-the-counter medication selection. Analysis examined how participants navigated the pharmacy and engaged with intervention components. Findings identified which intervention factors should be prioritized in adaptation and sustainability iterations.
Case two used eye-tracking for near-live usability testing and examined how healthcare professionals used a novel electronic health record functionality, RxFill. Data collection required participants to prepare for and conduct a simulated medication review with a standardized patient. Analysis included schematic mapping to identify RxFill usability and implementation best practices.
Case three used eye-tracking to examine which components of a direct-to-consumer television advertisement (DTCA) were most relevant to older adults. Methods employed dynamic areas of interest that move with each video frame to capture participant gaze throughout the DTCA. Findings identified which components of the DTCA were most salient and provided insights on how to best leverage visual cues in DTCAs to support patient engagement.
Implications for D&I Research:
Eye-tracking provides rigorous methods for assessing how innovation components align with user needs and helps researchers curate interventions to maximize outcomes while minimizing required resources for sustainment.