Introduction

Healthcare providers deal with enormous amounts of sensitive patient health data important in making significant care decisions. Patient registration details & demographics, Appointment/scheduling details, Billing and reimbursement information, Diagnostic codes (ICD -10), Patient Medical details: Allergy information/vital signs, Medication administration records, Patient laboratory, and radiology reports, Patient operative notes and Discharge Summary are just an among many other administrative and clinical data that are dealt with.

The above patient information is collected mainly to make informed clinical decisions for better patient care. Apart from this, the information can be used to communicate with the patient during each encounter or can be used for billing and reimbursement documentation as proof to the insurance companies, besides the data can be used in various clinical research purposes with the consent of the patient.

EHRs (Electronic Health Records) and medical apps such as mobile prescription apps that have this complex and sensitive patient health information ideally should be intuitive enough for the healthcare professional to enter, archive, and interpret the relevant information promptly to make the right patient care decision. However, with the implementation of such technologies within healthcare facilities, the problem of accessibility of data at the right time and in the right manner (with consideration to patient privacy and security) remains unresolved most of the time, though there has been some improvement in the quality of patient care.

Usability and its importance in digital health technologies

We have seen the various forms of complex health data that have to be managed appropriately within a health technology to make informed clinical decisions about patient care.   there is humongous data available on medicine and personal healthcare on the web. Personal healthcare care information that deals with either Diabetes self-management or post-operative care at home after chemotherapy or treating hypertension safely at home and others.  Be it a hospital information system that is relevant to a healthcare professional or health awareness information relevant to an individual or a patient, the questions that arise are:

1. Does a hospital information product like EHR (Electronic Health Records), EMR (Electronic Medical Records), PHR (Personal Health Records) medical apps, or a health website display information in an intuitive manner to the user?
2. Upon accessing the information is the user able to interpret the relevant message with the screens displayed? Especially in the case of hospital information systems are the relevant alerts and messages prompted to the user?
3. Is the user able to browse for the desired information promptly?
4. Is the user able to navigate smoothly from one information to another in a meaningful flow?
5. Is the user alerted about important information and are there options available for the user to rectify their errors?

When it comes to accessing any digital health solution or product, understanding the presentation of information is crucial to negate the associated clinical risks, here is when usability plays a pivotal role.

What is Usability?

Usability is defined by various standard Health IT regulatory bodies in multiple ways but all imply the same, ultimately emphasizing ‘Effectiveness’, ‘Efficiency’, and ‘Satisfaction’.

The International Organization for Standardization (ISO) defines Usability as: ‘’the effectiveness, efficiency, and satisfaction with which the intended users can achieve their tasks in the intended context of product use.’’

Here ‘Effectiveness’ is defined as the degree to which the interface facilitates the user to accomplish the tasks. ‘Efficiency’ is the time frame taken to complete the task and ‘Satisfaction’ is subjective based on the user’s perception of usability and sense of satisfaction with respect to the ease of use.

The ‘Preece J, et al. Human-Computer Interaction. Addison-Wesley; Workingham, England: 1994’(Preece, 2002), defines Usability as the measure of the ease with which a system can be learned and used, including its safety, effectiveness, and efficiency.

The National Centre for Cognitive Informatics and Decision Making in Healthcare (NCCD) defines usability based on its TURF (Task, User, Representation, and Function) framework as “how useful, usable, and satisfying a system is for the intended users to accomplish goals in the work domain by performing certain sequences of tasks (Zhang and Walji, 2011)

The TURF framework consists of:

1. Useful: How well the EHR supports the users to accomplish their tasks with the relevant and sufficient domain content. This factor determines whether the relevant domain workflow is in place to ensure proper functionality for the intended purpose.
2. Usable: This refers to how easy the system is to use, how easy is it to learn, and whether it is error-tolerant. Usability may be measured by learnability, efficiency, and error tolerance.
3. Learnability: how quickly a novice user learns the interface to perform his routine tasks. Learnability is dependent on the consistency of the interface. It can be measured by the time it takes to learn a new task.
4. Efficiency is the length of time required to complete a task.
5. Error tolerance refers to the ability of the system to help users avoid and recover from errors.
6. Satisfying: Subjective to the user’s perception of satisfaction with respect to the ease of use.

To sum it up Usability is not just the look and feel of a system but the way systems function in a way that is easy to use.

Hypothetical Case Studies-Usability Nightmares and Health information Technologies

Case study 1

User story 1:

Mrs. Kerry Smith 36 yrs., was rushed to the emergency of a healthcare facility, because of a sudden sharp and stabbing chest pain along with shortness of breath.  The duty physician of the healthcare facility performed an ECG (Electrocardiograph) to rule out the possibility of cardiovascular disease. Simultaneously the blood pressure was measured and readings were in the range of 110/80 which was considered normal for her age.

The ECG reports were also found to be normal. The duty doctor entered the medical records of Mrs Smith and referred Mrs Smith to Dr. Ray the Cardiologist, to reconfirm the absence of any cardiovascular disease. Dr. Ray examined Mrs. Smith thoroughly and asked her to get a Chest X-ray. Dr. Ray entered his observations too about Mrs Smith into the system. Now the observations of the duty doctor and Dr. Ray were synchronized and were available as a single report of two different encounters.

Mrs. Smith gets her Chest x-ray from the radiology department in the basement of the facility. The radiologist Ms. Parsons uploads the chest x-ray image to the records of Mrs Smith by identifying her unique patient registration number. Now this chest X-ray image is available for view to the duty doctor as well as Dr. Ray.

Dr Ray uses his Patient record app to view emergency records while he is away from the clinic. As soon as Ms. Parsons uploaded the X-ray image to Mrs. Smith’s records, Dr. Ray gets an alert on his Android device that he uses for accessing the patient records. In here Dr Ray tried to download and open the chest X-ray image of Mrs. Smith. The screen was too small for him to interpret the result and draw any conclusion. Also, the display property of the device or the low contrast ratio of the device was a hindrance to getting a clear picture of the image. Looking at the overall image he suspected it to be cardiovascular disease. He in turn asks Mrs Smith to get an ECHO stress test, to repeat the ECG, and also asks her to get a blood test for the CBC and Cardiac enzymes.

These blood reports, ECHO stress data, and the ECG images were uploaded by the lab assistant and the radiologist respectively to Mrs. Smith’s records. Dr. Ray accessed them while he was away from the clinic. Though the font size was small still he managed to read the numerical values of the blood tests and the ECHO stress test, due to the small screen and low resolution he was again unable to interpret the results of these using his patient records app. In the blood reports the cardiac enzyme values were found to be normal and the ECHO stress data confirmed the absence of cardiovascular disease. However, the CBC (Complete Blood count) test has displayed an increase in the WBC (White Blood Cell) count. Dr. Ray realised that it must be due to some infection since Mrs. Smith stabbing chest pain did not subside either. He immediately asked Mrs. Smith to come over for a consultation in person with the Chest X-ray film. The X-ray indicated inflammation of the Pleural cavity and Dr. Ray then diagnosed Mrs Smith for the condition of mild Pleurisy. He then put her on antibiotics for 5 days.

The above case study shows that though the app was useful to the physician for referring the results while he was not in the clinic, the small screen size, font size, and low contrast ratio of the app were not usable to interpret the result. This made the Cardiologist repeat certain tests and the patient had to undergo certain unnecessary tests despite having a clear x-ray film, indicating the condition. If a usability test had been done before this would have optimized the app design and the small problems above, could have been resolved.

User story 2:

Consider a Paediatrician using a medication prescribing app to prescribe the right dosage of the medicine based on the weight of a 3-year-old kid. This medication-prescribing app has an in-built calculator. The fields for data entry are the first four fields while dosage and frequency are to be automatically calculated by the app, the name of the patient is displayed by default by the app.

Child Age:  DD/MM/YYYY (The app would then calculate the exact age of the child as of that date)

Body weight:

Diagnosis:

Medicine:

Brand/Generic:

• Dosage: mg/kg or mg/dl
• Frequency: BID, TID ( Two times in a day for 5 days or Three times a day for 5 days and so on)

Assume if the ‘Age’ and ‘Weight’ fields were not marked mandatory in the app, just upon entering the diagnosis and the medicine the app would have calculated a default dosage as per the in-built calculator. This could be very fatal. For example, a child of 4 years could weigh anywhere between 28-44 pounds (normal to obese child). Hence the dose would differ and depending on the dose the medicine would react to the body’s condition. If a child of 4 years weighing only 22 pounds is given a dose of painkiller or an antibiotic with a frequency that is equivalent to that of a child weighing 44 pounds, it would pose a risk to the liver.

Thus while designing usable medical apps, it is of utmost importance to pay heed to this aspect of ‘mandatory’ fields to be highlighted, without which sometimes it could be clinically risky.

Again, assume that in case of Paediatric emergencies, this app takes 2 minutes to display the exact dosage required to be administered to the child on the emergency bed. It would be a highly sensitive condition if the physician had to rely only on this app for calculating the dose. Hence usability-wise it is essential that the interaction time between the user and the device is synchronized or optimal so that the user receives the output faster and clinical risks associated with UI design are reduced or nullified.

Reflecting on the consequences of bad usability

In the above paragraph, we’ve seen a few blunders major or minor in healthcare applications that can be fatal due to their bad usability. Not only that, but a few functionalities of a clinical workflow can have a profound effect on patient care due to the lack of usability of Health IT systems.

Consider a Medication Administration module and a Laboratory Information module within a Hospital Information System. The Medication Administration module with the functionality of administrating the scheduled drugs. The Laboratory information module to enter Pathology tests, Biochemistry as well as Microbiology tests.

We all know the basic thumb rule that ‘The right medicine, with the right dose, to the right patient through the right route at the right time must be administered’.

In the Biochemistry panel, one of the tests was that of Blood glucose level. Assume that the system has a provision to display the test value and the normal or reference value. The patient’s blood glucose level however does not fall within the normal range but is quite higher than the normal range such that he would require immediate medical attention. However, if the system due to its improperly designed screens fails to highlight any one of the above pieces of information (say dose) clearly to the healthcare professional, the care provider may end up administrating an incorrect dose to the patient and not consider pursuing this case as a serious one. The immediate medical attention that the patient should have been provided with would delay and this in turn may result in fatal consequences.

Applying the PERMA Model to Enhance Healthcare Technology Usability and Professional Well-being

To integrate Positive Psychology(Zhang and Walji, 2011) and the PERMA model into healthcare technology systems, the following actions can be implemented:

1. Positive Emotion:
   • Design for emotional satisfaction through user-centered design, aesthetic appeal (calming colors, clear layouts), and gamification elements (rewards, achievement badges).
   • Outcome: Reduced frustration and greater emotional satisfaction for healthcare professionals.
2. Engagement:
   • Promote flow by streamlining workflows, minimizing distractions, and prioritizing relevant tasks.
   • Outcome: Enhanced engagement and cognitive ease, leading to improved focus and task enjoyment.
3. Relationships:
   • Foster collaboration through team-based tools (shared notes, messaging) and social connectivity (community features).
   • Outcome: Increased sense of teamwork, reduced isolation, and improved job satisfaction.
4. Meaning:
   • Align work with purpose by highlighting the impact of individual work on patient outcomes, offering personalized dashboards, and recognizing achievements.
   • Outcome: Strengthened connection to work, reduced burnout, and enhanced job satisfaction.
5. Accomplishment:
   • Provide achievable goals with task breakdowns, progress indicators, and performance feedback.
   • Outcome: Increased motivation, personal growth, and efficiency.

Implementation Strategy

• Iterative Design: Continuously involve healthcare professionals in the development process.
• Cross-functional Collaboration: Integrate input from behavioural scientists, designers, and healthcare professionals.
• Ongoing Evaluation: Regularly assess the system’s impact on well-being and usability.

Integrating the PERMA model improves both the usability of healthcare technology and the well-being of professionals, leading to better patient care outcomes.

References

1. Preece, J. (Ed.), 2002. Human-computer interaction, Nachdr. ed. Addison-Wesley, Harlow.
2. Zhang, J., Walji, M.F., 2011. TURF: Toward a unified framework of EHR usability. J. Biomed. Inform. 44, 1056–1067. https://doi.org/10.1016/j.jbi.2011.08.005