Facilitators and Barriers to Implementing a Digital Informed Decision Making Tool in Primary Care: A Qualitative Study

Evaluation of a Patient Decision Aid for Refractive Eye Surgery

BACKGROUND

We developed a prototype patient decision aid, EyeChoose, to assist college-aged students in selecting a refractive surgery. EyeChoose can educate patients on refractive errors and surgeries, generate evidence-based recommendations based on a user's medical history and personal preferences, and refer patients to local refractive surgeons.

OBJECTIVES

We conducted an evaluative study on EyeChoose to assess the alignment of surgical modality recommendations with a user's medical history and personal preferences, and to examine the tool's usefulness and usability.

METHODS

We designed a mixed methods study on EyeChoose through simulations of test cases to provide a quantitative measure of the customized recommendations, an online survey to evaluate the usefulness and usability, and a focus group interview to obtain an in-depth understanding of user experience and feedback.

RESULTS

We used stratified random sampling to generate 245 test cases. Simulated execution indicated EyeChoose's recommendations aligned with the reference standard in 243 (99%). A survey of 55 participants with 16 questions on usefulness, usability, and general impression showed that 14 questions recorded more than 80% positive responses. A follow-up focus group with 10 participants confirmed EyeChoose's useful features of patient education, decision assistance, surgeon referral, as well as good usability with multimedia resources, visual comparison among the surgical modalities, and the overall aesthetically pleasing design. Potential areas for improvement included offering nuances in soliciting user preferences, providing additional details on pricing, effectiveness, and reversibility of surgeries, expanding the function of surgeon referral, and fixing specific usability issues.

CONCLUSION

The initial evaluation of EyeChoose suggests that it could provide effective patient education, generate appropriate recommendations, connect to local refractive surgeons, and demonstrate good system usability in a test environment. Future research is required to enhance the system functions, fully implement and evaluate the tool in naturalistic settings, and examine the findings' generalizability to other populations.

Effectiveness and implementation of mPATH™-CRC: a mobile health system for colorectal cancer screening

BACKGROUND

Screening for colorectal cancer (CRC) is widely recommended but underused, even though CRC is the third most diagnosed cancer and the second leading cause of cancer death in the USA. The mPATH™ program is an iPad-based application designed to identify patients due for CRC screening, educate them on the commonly used screening tests, and help them select their best option, with the goal of increasing CRC screening rates.

METHODS

The mPATH™ program consists of questions asked of all adult patients at check-in (mPATH™-CheckIn), as well as a module specific for patients due for CRC screening (mPATH™-CRC). In this study, the mPATH™ program is evaluated through a Type III hybrid implementation-effectiveness design. Specifically, the study consists of three parts: (1) a cluster-randomized controlled trial of primary care clinics comparing a "high touch" evidence-based implementation strategy with a "low touch" implementation strategy; (2) a nested pragmatic study evaluating the effectiveness of mPATH-CRC™ on completion of CRC screening; and (3) a mixed-methods study evaluating factors that facilitate or impede the maintenance of interventions like mPATH-CRC™. The primary objective is to compare the proportion of patients aged 50-74 who are eligible for CRC screening who complete mPATH™-CRC in the 6th month following implementation between the "high touch" and "low touch" implementation strategies. Effectiveness of mPATH™-CRC is evaluated by comparing the proportion who complete CRC screening within 16 weeks of their visit to the clinic between a pre-implementation cohort (8 months before implementation) and a post-implementation cohort (8 months after implementation).

DISCUSSION

This study will provide data on both the implementation of the mPATH™ program and its effectiveness in improving screening rates for CRC. In addition, this work has the potential to have an even broader impact by identifying strategies to support the sustained use of other similar technology-based primary care interventions.

TRIAL REGISTRATION

ClinicalTrials.gov NCT03843957. Registered on 18 February 2019.

An Explainable Knowledge-Based System Using Subjective Preferences and Objective Data for Ranking Decision Alternatives

BACKGROUND

 Allergy is a hypersensitive reaction that occurs when the allergen reacts with the immune system. The prevalence and severity of the allergies are uprising in South Asian countries. Allergy often occurs in combinations which becomes difficult for physicians to diagnose.

OBJECTIVES

 This work aims to develop a decision-making model which aids physicians in diagnosing allergy comorbidities. The model intends to not only provide rational decisions, but also explainable knowledge about all alternatives.

METHODS

 The allergy data gathered from real-time sources contain a smaller number of samples for comorbidities. Decision-making model applies three sampling strategies, namely, ideal, single, and complete, to balance the data. Bayes theorem-based probabilistic approaches are used to extract knowledge from the balanced data. Preference weights for attributes with respect to alternatives are gathered from a group of domain-experts affiliated to different allergy testing centers. The weights are combined with objective knowledge to assign confidence values to alternatives. The system provides these values along with explanations to aid decision-makers in choosing an optimal decision.

RESULTS

 Metrics of explainability and user satisfaction are used to evaluate the effectiveness of the system in real-time diagnosis. Fleiss' Kappa statistic is 0.48, and hence the diagnosis of experts is said to be in moderate agreement. The decision-making model provides a maximum of 10 suitable and relevant pieces of evidence to explain a decision alternative. Clinicians have improved their diagnostic performance by 3% after using CDSS (77.93%) with a decrease in 20% of time taken.

CONCLUSION

 The performance of less-experienced clinicians has improved with the support of an explainable decision-making model. The code for the framework with all intermediate results is available at https://github.com/kavya6697/Allergy-PT.git.

Higher Electronic Health Record Functionality Is Associated with Lower Operating Costs in Urban—but Not Rural—Hospitals

Objectives  The aim of the study is to examine the relationship between electronic health record (EHR) use/functionality and hospital operating costs (divided into five subcategories), and to compare the results across rural and urban facilities.

Methods  We match hospital-level data on EHR use/functionality with operating costs and facility characteristics to perform linear regressions with hospital- and time-fixed effects on a panel of 1,596 U.S. hospitals observed annually from 2016 to 2019. Our dependent variables are the logs of the various hospital operating cost categories, and alternative metrics for EHR use/functionality serve as the primary independent variables of interest. Data on EHR use/functionality are retrieved from the American Hospital Association's (AHA) Annual Survey of Hospitals Information Technology (IT) Supplement, and hospital operating cost and characteristic data are retrieved from the American Hospital Directory. We include only hospitals classified as “general medical and surgical,” removing specialty hospitals.

Results  Our results suggest, first, that increasing levels of EHR functionality are associated with hospital operating cost reductions. Second, that these significant cost reductions are exclusively seen in urban hospitals, with the associated coefficient suggesting cost savings of 0.14% for each additional EHR function. Third, that urban EHR-related cost reductions are driven by general/ancillary and outpatient costs. Finally, that a wide variety of EHR functions are associated with cost reductions for urban facilities, while no EHR function is associated with significant cost reductions in rural locations.

Conclusion  Increasing EHR functionality is associated with significant hospital operating cost reductions in urban locations. These results do not hold across geographies, and policies to promote greater EHR functionality in rural hospitals will likely not lead to short-term cost reductions.