File Name: applying human factors and usability engineering to optimize medical device design .zip
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The patient interface was tested in six formative HF studies followed by a validation study. All tasks critical to safety or necessary for effective use were included.
Formative studies identified use-related risks and the causes of use problems to guide design modification. Results: During the patient formative studies, design improvements were made to address problems and mitigate risks thought to be associated with a suboptimal system design or patient understanding of the system. One close call, 15 failures, and 6 difficulties occurred on these user tasks; only 3 of these were on a critical task.
Residual risks resistant to mitigation were found to be of low severity based on the US Food and Drug Administration guidance. Conclusion: The final design of the DMS reflects input by the intended user populations through a comprehensive development methodology.
In alignment with the US Food and Drug Administration goals for HF studies, the system was found to be safe and effective for the intended users, uses, and use environments. Keywords: digital medicine system, drug—device combination, schizophrenia, bipolar disorder, major depressive disorder, aripiprazole, serious mental illness, usability. A new digital medicine system provides objective medication adherence information based on whether a patient takes a pill that is embedded with a sensor.
Adherence information is then available to the patient and his or her health care provider. In order to assess and improve the ability of the system to be used properly while minimizing medication- or device-associated risks, iterative human factors studies were performed with progressively updated versions of the system until the remaining risks were considered of low severity.
These studies showed that the system modifications reduced risks to the lowest level possible and improved the ability of the intended user population — patients with schizophrenia, bipolar disorder, or major depressive disorder — to safely use the system.
Poor adherence to medication is a common problem in patients with serious mental illness SMI such as schizophrenia, bipolar I disorder, and major depressive disorder MDD 1 — 3 and has been consistently associated with suboptimal treatment response, including relapse, rehospitalization, and poor health outcomes.
Directly observed medication ingestion is the gold standard but can be used only in a limited number of settings such as hospitals or nursing homes.
Currently available and more broadly applicable options include pill counts, pharmacy refill records, technology-assisted monitoring of pill containers such as Medication Event Monitoring System bottle caps, and biological assays from bodily fluids. Capsule photographs taken with cellular phones have been reported as a simple tool to assess adherence but, similar to the other modalities, cannot confirm medication ingestion.
However, the potential benefits of LAIs are limited only to patients who accept the LAI antipsychotic as a therapeutic option. The digital medicine system DMS is an innovative drug—device combination developed for patients with SMI, which integrates adherence measurement capabilities as part of the drug formulation via an embedded ingestible sensor.
It objectively measures medication ingestion and reports adherence to oral aripiprazole, an atypical antipsychotic indicated as monotherapy for the treatment of schizophrenia, acute treatment of manic and mixed episodes associated with bipolar I disorder, and for the treatment of MDD adjunctive to antidepressants. Self-management systems based on mobile device applications developed for patients with schizophrenia have been reported, 18 , 19 but no currently marketed product offers a combination of functions comparable with that of the DMS.
Figure 1 Information components and data communication. Developing a digital medicine system in psychiatry: ingestion detection rate and latency period. The Journal of Clinical Psychiatry. Volume 77 9. Pages e—e Copyright Reprinted with permission. The absence of directly applicable user experience from a comparable existing product highlights the importance of a comprehensive development program that includes an analysis of use-related risks and device optimization through human factors HF studies.
HF is defined as the application of knowledge about human capabilities physical, sensory, emotional, and intellectual and limitations to the design and development of tools, devices, systems, environments, and organizations. Digital health applications created for users with SMI require specific product design characteristics that allow effective use of the product by the target population. This article describes two stages of HF studies: formative studies that help optimize design of the product and validation studies that evaluate the final product.
Formative and validation studies are also called iterative and summative studies, respectively. To the best of our knowledge, the DMS represents the first integrative digital health product developed in psychiatry that has undergone a comprehensive HF assessment to support the FDA regulatory submission.
Validation studies conclude the HF study process and aim to demonstrate that the final product has been optimized for safe and effective use by the intended users in the expected use environments.
Figure 2 Steps in A human factors studies overall and B in risk analysis. Notes: Six formative human factors studies were conducted on the patient interface and one on the HCP and caregiver interface. One validation study was conducted on the patient interface and one on the HCP and caregiver interface.
The risk analysis was conducted in accordance with FDA recommendations and FDA-recognized standards on human factors and usability engineering of medical devices. Draft guidance for industry and Food and Drug Administration staff: applying human factors and usability engineering to medical devices to optimize safety and effectiveness in design.
Accessed July 11, The patient interface of the DMS was tested in six formative user-centered HF studies followed by a validation study.
The studies were approved by an institutional review board Core Human Factors, Inc. All participants provided written informed consent. The primary objectives of the formative studies on the patient interface were to assess the effectiveness of mitigations from previous DMS usability studies, identify steps in the use process that may result in new unforeseen risks, and understand the root cause of performance failures or difficulties to help optimize the design of the product Figure 2A.
A use-risk analysis was performed before and after each study to identify remaining potential use-related risks associated with the system and inform product design iterations. The risk analysis, schematically shown in Figure 2B , 20 , 21 included task analysis, hazard analysis, and use failure mode and effect analysis uFMEA. The task analysis identified all reasonably foreseeable user steps during use of the DMS. The hazard analysis determined potential use-related hazards resulting from unsuccessful completion of use-related tasks and assessed probability and severity of the hazards.
A uFMEA provided a risk-analysis code RAC for each potential failure mode representing the acceptability of the harm not acceptable, as low as reasonably practical, or tolerable ; the RAC was used to prioritize efforts to mitigate risks during the redesign process.
The risk analysis identified critical and necessary tasks for safe and effective use of the DMS, which were tested in validation studies. Critical tasks are required for safe and effective use of the product, and when performed either incorrectly or not at all can cause serious harm to the user, whereas necessary tasks are required to achieve the medical benefit but do not constitute a serious safety risk if omitted or performed incorrectly.
The patient interface was tested in six formative studies Table 1. Prior to validation, patients were chosen based on their conformity with the intended users of the system as per FDA guidance on sampling methodology. Patients with schizophrenia, bipolar I disorder, and MDD were eligible.
The first two studies consisted of single minute individual sessions. The remaining four studies included a minute individual onboarding session on day 1 that simulated a first day with the system and a minute individual session on day 2 that simulated regular use. The day 1 activities comprised initial steps required for the system setup installing the application on a mobile device, logging into the software, creating an account, inputting user settings, and sending an invitation to share information with an HCP , applying the first wearable sensor, and pairing it with the mobile application.
The day 2 regular-use activities included weekly maintenance steps, such as replacing the wearable sensor and pairing the new sensor to the patient mobile application. The participants in the third and fourth studies of the patient interface were randomly assigned to one of two arms, either HCP-assisted or HCP-unassisted onboarding that balanced diagnoses schizophrenia, bipolar I disorder, MDD between the two groups.
Some of the critical tasks assessed during formative studies are listed in Table 2. For formative study 5, the definitions of critical and necessary tasks were aligned with the updated regulatory guidelines on HF studies, 21 and all tasks on which failures or difficulties were observed in the previous formative study were tested.
This study was conducted in three waves or sprints, allowing design changes in the interim to mitigate any observed usability issues. At the conclusion of formative study 5, only three issues remained that could potentially be mitigated through design. A final formative study, study 6, assessed these remaining failures and difficulties related to the interface design and concluded that minor design changes could address these issues.
Table 2 Examples of formative study findings and corresponding design modifications to the patient interface Abbreviations: HCP, health care provider; IFU, instructions for use. Critical and necessary tasks are typically the focus of validation studies as these constitute the tasks that are required for the safe and effective use of a system. A representative sample of the intended user population was randomly assigned to each onboarding arm.
Participants completed tasks in a simulated environment designed to mimic the real-world setting to the degree necessary for effective testing. The tasks were set up to simulate 7 days of system use. The smartphone application was controlled by an HF software tool designed specifically to allow the moderator to trigger notifications and application functions similar to those experienced in actual use, consistent with a simulated use methodology.
For example, because no pill was ingested during the study, this was one of the key system feedbacks that had to be simulated via this software tool. Skin placement of the wearable sensor was simulated by the participant placing the sensor on a flexible wrap worn on the abdomen.
The participants were evenly divided into assisted and unassisted onboarding groups. Both participant groups viewed within-app video segments during onboarding, and participants in the assisted group received HCP-provided assistance as necessary. Both groups subsequently completed the same independent-use assessments. Study participants were selected from the patient database of a clinic in California and were representative of the intended population of DMS users, ie, male and female patients aged 18—65 years with a confirmed diagnosis of schizophrenia, bipolar I disorder, or MDD.
The participants only needed to be potential users of the system and did not have to be stable on oral aripiprazole in order to take part in the study. In addition, all participants were required to own and use a smartphone. Candidates were excluded if they had any personal or commercial interest in a pharmaceutical or medical device company or did not understand and speak English. Participants were transported to an independent research facility with individual testing rooms set up to simulate a simple home or office environment.
As in the formative studies, day 1 onboarding included tasks performed during first-day use of the product, whereas day 2 regular use included tasks experienced with the use of the product over time.
Each interview was conducted by a team of HF professionals, including a moderator and a notetaker. This approach was intended to capture unanticipated use errors observed by the moderator or articulated by the participant.
Targeted discussions with participants investigated the causes of performance failures, close calls, and difficulties. The primary objectives of the study on the HCP and caregiver interface were to identify steps in the use process that resulted in risks or confusion and to understand the root cause of performance failures or difficulties to help redesign the product.
HCP and caregiver use of the system comprised initial setup steps and periodic viewing of patient data. A use-risk analysis was performed before and after the study as previously described for formative studies on the patient interface. In the validation study on the HCP and caregiver interface, the participants completed all critical and necessary tasks identified in the risk analysis. The participants completed the study tasks in an office-like environment simulating conditions found during treatment and routine care for patients with SMI; the simulated environment was controlled by the research team.
Both HCPs and caregivers were identified and contacted by professional recruiters using databases of potential respondents and specified recruitment criteria. All participants were also required to have an email address and to use a computer, tablet, or smartphone.
As noted in the Forward:. The Forward further explains the difference between -1 and -2 by stating:. I first learned about the standard being divided into two parts from a presentation. Below are several resources that are relevant for individuals interested in learning about medical device human factors, companies looking to incorporate a comprehensive human factors program in their organization, and seasoned professionals that need a repository of readily accessible information. This post will be updated as additional, relevant resources are identified. Medical Technology Innovator. Human factors engineering — Design of medical device.
Applying Human Factors and Usability Engineering to Medical Devices to maximize the likelihood that new medical devices will be safe and are intended to support manufacturers in improving the design of devices to.
Document issued on: June 22, You should submit comments and suggestions regarding this draft document within 90 days of publication in the Federal Register of the notice announcing the availability of the draft guidance. Identify all comments with the docket number listed in the notice of availability that publishes in the Federal Register. For questions regarding this document, contact Ron Kaye at ron. Preface Additional Copies Additional copies are available from the Internet. You may also send an e-mail request to dsmica fda.
Be sure to leave feedback using the 'Feedback' button on the bottom right of each page! The Public Inspection page on FederalRegister. The Public Inspection page may also include documents scheduled for later issues, at the request of the issuing agency.
Human factors and ergonomics commonly referred to as human factors is the application of psychological and physiological principles to the engineering and design of products, processes, and systems.
You have a medical device you wish to market. Function is critical, but no more so than usability. How will people use it? What kind of user failures need to be considered in documentation and testing? Are you confident your interface is intuitive and clear? After all, the effectiveness of your device relies on consistently error-free use. Device manufacturers are responding by actively initiating human factors and usability engineering to many high priority devices.
This research aimed to find main users, frequent utilized tasks, major usability problems, and the context of use of a neonatal incubator NI present in a neonatal intensive care unit from a Brazilian hospital and to find out the problems faced by a new user. The chosen methods were the heuristics analysis, contextual investigation, and usability test UT.
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