Patient-generated Digital Images after Pediatric Ambulatory Surgery

Digital photography in the evaluation and management of female patients with congenital adrenal hyperplasia: A standardized protocol for quality improvement

INTRODUCTION

Digital photography can be securely stored in the medical record and enhance documentation of physical exam findings and monitor wound healing. A standardized protocol that respects the dignity of the patient and maintains the fidelity of objective documentation is needed for patients with differences in sexual development (DSD) and congenital adrenal hyperplasia (CAH).

OBJECTIVE

The purpose of this study was to evaluate the feasibility, acceptability, and applications of a HIPAA-compliant digital photography protocol in the care of female patients with CAH.

STUDY DESIGN

A protocol for standardized digital imaging including consent, permission, data capture, and storage in the electronic medical record (EMR) was implemented. Patients undergoing physical examination during multidisciplinary CAH clinic visits, preoperative evaluation, and postoperative follow-up from October 2020 through May 2021 were included. Male patients with CAH, patients with clitoromegaly or urogenital sinus not from CAH, and patients seen through telehealth were excluded. Consent was obtained from caregivers and permission from patients. Images of the exam were taken during clinic visits or at the time of surgery with no identifying features included. Images were directly uploaded into the patient's chart in the HIPAA-protected EMR separate from other clinical documentation and not stored on personal devices.

RESULTS

There were 17 patients with CAH seen with median age 6 years (range 2 weeks-18 years). There was a median of 3 photos per patient during the study period with cooperation from both the patient and their caregiver. Amongst the patients seen, 6 patients underwent reconstruction with a median of 10 photos per patient. Images were available and used for preoperative planning and counseling. Patients with previous images did not require repeat examinations and were subjected to fewer genital examinations. Fewer providers were present during exams. Images taken by providers and caregivers during the postoperative period were used to monitor wound healing and surgical outcomes.

DISCUSSION

Protocol implementation improved patient care by reducing the number of exams and number of providers present, enhancing clinical documentation, and providing a means of tracking the physical exam over time. This was in concordance with guidelines for limiting exams for patients with DSD and CAH. Implementation of best practices for medical photography was important in respecting patient dignity and confidentiality.

CONCLUSION

Implementation of standardized digital photography was feasible and acceptable to patients and caregivers. Digital images reduced the need for repeat physical examination and provided a visual means of enhancing clinical documentation.

Patient-Generated Health Photos and Videos Across Health and Well-being Contexts: Scoping Review

Background

Patient-generated health data are increasingly used to record health and well-being concerns and engage patients in clinical care. Patient-generated photographs and videos are accessible and meaningful to patients, making them especially relevant during the current COVID-19 pandemic. However, a systematic review of photos and videos used by patients across different areas of health and well-being is lacking.

Objective

This review aims to synthesize the existing literature on the health and well-being contexts in which patient-generated photos and videos are used, the value gained by patients and health professionals, and the challenges experienced.

Methods

Guided by a framework for scoping reviews, we searched eight health databases (CINAHL, Cochrane Library, Embase, PsycINFO, PubMed, MEDLINE, Scopus, and Web of Science) and one computing database (ACM), returning a total of 28,567 studies. After removing duplicates and screening based on the predefined inclusion criteria, we identified 110 relevant articles. Data were charted and articles were analyzed following an iterative thematic approach with the assistance of NVivo software (version 12; QSR International).

Results

Patient-generated photos and videos are used across a wide range of health care services (39/110, 35.5% articles), for example, to diagnose skin lesions, assess dietary intake, and reflect on personal experiences during therapy. In addition, patients use them to self-manage health and well-being concerns (33/110, 30%) and to share personal health experiences via social media (36/110, 32.7%). Photos and videos create significant value for health care (59/110, 53.6%), where images support diagnosis, explanation, and treatment (functional value). They also provide value directly to patients through enhanced self-determination (39/110, 35.4%), social (33/110, 30%), and emotional support (21/110, 19.1%). However, several challenges emerge when patients create, share, and examine photos and videos, such as limited accessibility (16/110, 14.5%), incomplete image sets (23/110, 20.9%), and misinformation through photos and videos shared on social media (17/110, 15.5%).

Conclusions

This review shows that photos and videos engage patients in meaningful ways across different health care activities (eg, diagnosis, treatment, and self-care) for various health conditions. Although photos and videos require effort to capture and involve challenges when patients want to use them in health care, they also engage and empower patients, generating unique value. This review highlights areas for future research and strategies for addressing these challenges.

Patient generated health data: Benefits and challenges

Patient Generated Health Data (PGHD) is defined as data generated by and from patients.¹ The use of PGHD has rapidly increased with the widespread availability of smart phone mobile health applications (mHealth apps) and wearable devices. Currently, the vast majority of PGHD is generated via the use of mHealth apps and wearables like "Fitbit" or medical devices such as a continuous glucose monitoring device. There are many benefits of PGHD including increased monitoring of children's chronic health conditions outside clinical care to supplement ambulatory clinic visits, improved health outcomes, increased patient awareness and engagement and improved patient-provider communication. When leveraged properly, PGHD can be a powerful tool in delivering safe, effective, patient centered, efficient and equitable care as outlined by the Institute of Medicine (IOM).² The challenges that limit collection, use and acceptance of PGHD include limited access to the internet, inability to incorporate PGHD into clinical workflows, data privacy and security concerns and apprehension about accuracy and safety of mHealth apps. These issues can lead to a lack of use or compliance with devices or apps associated with PGHD. To ensure optimal health benefits, agreement to leverage PGHD should be a joint decision between the clinician and the patient/caregiver. Future steps to ensure safety and clinical relevance of PGHD include involving regulatory authorities, device manufacturers and professional bodies to develop standards for mHealth apps and wearables to promote uncomplicated PGHD integration into workflows, easy and secure sharing of PGHD. Wearable technology, medical devices and smart phone apps become more advanced and widespread among the population, there will be an increasing potential for PGHD to facilitate personalized, efficient, and collaborative care resulting in improved health outcomes for children and adolescent and young adult. More research and innovation is needed to facilitate this transition.

A natural language processing pipeline to synthesize patient-generated notes toward improving remote care and chronic disease management: a cystic fibrosis case study

Objectives

Patient-generated health data (PGHD) are important for tracking and monitoring out of clinic health events and supporting shared clinical decisions. Unstructured text as PGHD (eg, medical diary notes and transcriptions) may encapsulate rich information through narratives which can be critical to better understand a patient’s condition. We propose a natural language processing (NLP) supported data synthesis pipeline for unstructured PGHD, focusing on children with special healthcare needs (CSHCN), and demonstrate it with a case study on cystic fibrosis (CF).

Materials and Methods

The proposed unstructured data synthesis and information extraction pipeline extract a broad range of health information by combining rule-based approaches with pretrained deep-learning models. Particularly, we build upon the scispaCy biomedical model suite, leveraging its named entity recognition capabilities to identify and link clinically relevant entities to established ontologies such as Systematized Nomenclature of Medicine (SNOMED) and RXNORM. We then use scispaCy’s syntax (grammar) parsing tools to retrieve phrases associated with the entities in medication, dose, therapies, symptoms, bowel movements, and nutrition ontological categories. The pipeline is illustrated and tested with simulated CF patient notes.

Results

The proposed hybrid deep-learning rule-based approach can operate over a variety of natural language note types and allow customization for a given patient or cohort. Viable information was successfully extracted from simulated CF notes. This hybrid pipeline is robust to misspellings and varied word representations and can be tailored to accommodate the needs of a specific patient, cohort, or clinician.

Discussion

The NLP pipeline can extract predefined or ontology-based entities from free-text PGHD, aiming to facilitate remote care and improve chronic disease management. Our implementation makes use of open source models, allowing for this solution to be easily replicated and integrated in different health systems. Outside of the clinic, the use of the NLP pipeline may increase the amount of clinical data recorded by families of CSHCN and ease the process to identify health events from the notes. Similarly, care coordinators, nurses and clinicians would be able to track adherence with medications, identify symptoms, and effectively intervene to improve clinical care. Furthermore, visualization tools can be applied to digest the structured data produced by the pipeline in support of the decision-making process for a patient, caregiver, or provider.

Conclusion

Our study demonstrated that an NLP pipeline can be used to create an automated analysis and reporting mechanism for unstructured PGHD. Further studies are suggested with real-world data to assess pipeline performance and further implications.

Experiences of Health Care Providers Using a Mobile Medical Photography Application

OBJECTIVE

To understand the ways in which providers use a mobile photography application integrated with the electronic health record (EHR) to facilitate clinical care, and the process outcomes that result from the application's use.

METHODS

An e-mail survey was sent on November 13, 2017, to 1,463 health care providers at Mayo Clinic who had used an internally developed, EHR-integrated medical photography application.

RESULTS

The survey was completed by 712 (49%) providers. Providers reported using the application on approximately 1 in 7 days spent in clinical practice. Median provider satisfaction with the use of the application (0-100 scale; higher numbers indicate favorable response) was 94 (interquartile range [IQR]: 74-100). Although the use for store-and-forward telemedicine was reported (22% often or frequently used the application to send photographs to a specialist for advice), the most common use was for clinical documentation (65% often or frequently used the application to supplement text-based notes with photographs, and 71% often or frequently used the application to take photographs for reference by a colleague who may see the patient in the future). Of the health care providers, 36% indicated that the application's use often or frequently expedited treatment.

DISCUSSION

Health care providers reported using a mobile point-of-care medical photography application regularly in clinical practice and were generally satisfied with the application.

CONCLUSION

Point-of-care medical photography using a secure mobile, EHR-integrated application has potential to become a new standard of care for clinical documentation and may facilitate continuity across the continuum of care with multiple providers who see a patient.

Use of an EHR-Integrated Point-of-Care Mobile Medical Photography Application in a Pediatric Emergency Department

BACKGROUND

Mobile applications allow health care providers to capture point-of-care medical photographs and transfer them to the electronic health record (EHR). It is unclear how providers use these photographs or how they affect clinical care.

OBJECTIVES

We aimed to understand the content, purpose, and outcomes of point-of-care medical photography performed in the pediatric emergency department (ED) at large academic medical center.

METHODS

A retrospective chart review was conducted of patients <21 years of age who were seen in the ED and photographed between March 29, 2015 and July 1, 2017 using a secure smartphone application integrated with the EHR. Inter-rater agreement and reliability between the two reviewers was assessed for the first 50 charts, and any discrepancies in interpretation were resolved before proceeding with the remaining data abstraction. The documented rationale for photography, content of photographs, and outcomes were recorded.

RESULTS

We identified 619 clinical encounters involving photographs of 605 patients who were eligible for inclusion. Skin was photographed in 499 (81%). The most common finding was rash (N = 177; 29%). Photos were of acceptable quality, with 569 (94%) achieving a score between 4 and 5 out of 5. The primary use of photography was documentation (N = 334; 54%), though teleconsultation was noted in 38 (6%). Nearly one-third (N = 187; 30%) of patients were seen in the ED or outpatient clinic for any reason within 2 weeks, and in 25 (13%), clinical notes explicitly referenced the initial photograph(s). In 53 (9%) cases, patients were photographed at a clinical visit in the subsequent 2 weeks, suggesting that photography was used to track changes over time.

CONCLUSION

Documentation of findings using mobile point-of-care photography allows for high-fidelity documentation and facilitates continuity of care.

Patient generated health data use in clinical practice: A systematic review

BACKGROUND

Precision health calls for collecting and analyzing large amounts of data to capture an individual's unique behavior, lifestyle, genetics, and environmental context. The diffusion of digital tools has led to a significant growth of patient generated health data (PGHD), defined as health-related data created, gathered or inferred by or from patients and for which the patient controls data collection and data sharing.

PURPOSE

We assessed the current evidence of the impact of PGHD use in clinical practice and provide recommendations for the formal integration of PGHD in clinical care.

METHODS

We searched PubMed, Ovid, Embase, CINAHL, Web of Science, and Scopus up to May 2018. Inclusion criteria were applied and four reviewers screened titles and abstracts and consequently full articles.

FINDINGS

Our systematic literature review identified 21 studies that examined the use of PGHD in clinical settings. Integration of PGHD into electronic records was extremely limited, and decision support capabilities were for the most part basic.

DISCUSSION

PGHD and other types of patient-reported data will be part of the health care system narrative and we must continue efforts to understand its impact on health outcomes, costs, and patient satisfaction. Nursing scientists need to lead the process of defining the role of PGHD in the era of precision health.

A Picture is Worth 1,000 Words. The Use of Clinical Images in Electronic Medical Records

OBJECTIVE

To understand how clinicians utilize image uploading tools in a home grown electronic health records (EHR) system.

METHODS

A content analysis of patient notes containing non-radiological images from the EHR was conducted. Images from 4,000 random notes from July 1, 2009 - June 30, 2010 were reviewed and manually coded. Codes were assigned to four properties of the image: (1) image type, (2) role of image uploader (e.g. MD, NP, PA, RN), (3) practice type (e.g. internal medicine, dermatology, ophthalmology), and (4) image subject.

RESULTS

3,815 images from image-containing notes stored in the EHR were reviewed and manually coded. Of those images, 32.8% were clinical and 66.2% were non-clinical. The most common types of the clinical images were photographs (38.0%), diagrams (19.1%), and scanned documents (14.4%). MDs uploaded 67.9% of clinical images, followed by RNs with 10.2%, and genetic counselors with 6.8%. Dermatology (34.9%), ophthalmology (16.1%), and general surgery (10.8%) uploaded the most clinical images. The content of clinical images referencing body parts varied, with 49.8% of those images focusing on the head and neck region, 15.3% focusing on the thorax, and 13.8% focusing on the lower extremities.

CONCLUSION

The diversity of image types, content, and uploaders within a home grown EHR system reflected the versatility and importance of the image uploading tool. Understanding how users utilize image uploading tools in a clinical setting highlights important considerations for designing better EHR tools and the importance of interoperability between EHR systems and other health technology.