Association rule mining of real-world data: Uncovering links between race, glycemic control, lipid profiles, and suicide attempts in individuals with diabetes.

Aims: The increased risk of suicide among individuals with diabetes is a significant public health concern. However, few studies have focused on understanding the relationship between suicide attempts and diabetes. Association rule mining (ARM) is a data mining technique to discover a set of high-risk factors of a given disease. Therefore, this study aimed to utilize ARM to identify a high-risk group of suicide attempts among patients with diabetes using Cerner Real-World Data™ (CRWD). Methods: The study analyzed a large multicenter electronic health records data of 3,265,041 patients with diabetes from 2010 to 2020. The Least Absolute Shrinkage and Selection Operator regression with ten-fold cross-validation and the Apriori algorithm with ARM were used to uncover groups of high-risk suicide attempts. Results: Of the 52,217,517 unique patients in the CRWD, 3,266,856 were diagnosed with diabetes. There were 7764 (0.2%) patients with diabetes who had a history of suicide attempts. The study revealed that patients with diabetes who were never married and had average blood glucose levels below 150 mg/dl were more likely to attempt suicide. In contrast, patients with diabetes aged 60 and older who had diabetes for less than five years and A1C levels between 6.5 and 8.9% were less likely to attempt suicide. Risk factors were strongly associated with suicide attempts, including never married, White, blood glucose levels below 150 mg/dl, and LDL levels below 100 mg/dl. Conclusions: This is the first study utilizing ARM to discover the risk patterns for suicide attempts in individuals with diabetes. ARM showed the potential for knowledge discovery in large multi-center electronic health records data. The results are explainable and could be practically used by providers during outpatient clinic visits. Further studies are needed to validate the results and investigate the cause-and-effect relationship of suicide attempts among individuals with diabetes.

Predicting suicide attempts among people with diabetes using a large multicenter electronic health records dataset.

OBJECTIVE: People with diabetes have a higher risk of suicidal behaviors than the general population. However, few studies have focused on understanding this relationship. We investigated risk factors and predicted suicide attempts in people with diabetes using Least Absolute Shrinkage and Selection Operator (LASSO) regression. METHOD: Data was retrieved from Cerner Real-World Data and included over 3 million diabetes patients in the study. LASSO regression was applied to identify associated factors. Gender, diabetes-type, and depression-specific LASSO regression models were analyzed. RESULTS: There were 7764 subjects diagnosed with suicide attempts with an average age of 45. Risk factors for suicide attempts in diabetes patients were American Indian or Alaska Native race (ß = 0.637), receiving atypical antipsychotic agents (ß = 0.704), benzodiazepines (ß = 0.784), or antihistamines (ß = 0.528). Amyotrophy was negatively associated with suicide attempts in males (ß = 2.025); in contrast, amyotrophy significantly increased the risk in females (ß = 3.339). Using a MAOI was negatively related to suicide attempts in T1DM patients (ß = 7.304). Age less than 20 was positively associated with suicide attempts in depressed (ß = 2.093) and non-depressed patients (ß = 1.497). The LASSO model achieved a 94.4% AUC and 87.4% F1 score. CONCLUSIONS: To our knowledge, this is the first study to use LASSO regression to identify risk factors for suicide attempts in patients with diabetes. The shrinkage technique successfully reduced the number of variables in the model to improve the fit. Further research is needed to determine cause-and-effect relationships. The results may help providers to identify high-risk groups for suicide attempt among diabetic patients.

Analysis of Healthy Coping Feedback Messages from Diabetes Mobile Apps: Validation Against an Evidence-Based Framework.

BACKGROUND: In this study, we focused on Healthy Coping, a key principle of ADCES7 Self-Care Behaviors® (ADCES7®) that enables people with diabetes to achieve health goals for self-care. We aimed to validate Healthy Coping-related feedback messages from diabetes mobile apps against the framework based on behavioral change theories. METHODS: We searched apps using the search terms: "diabetes," "blood sugar," "glucose," and "mood" from iTunes and Google Play stores. We entered a range of values on 3 Healthy Coping domains: (1) diabetes-related measures including blood glucose, blood pressure, HbA1c, weight, (2) physical exercise/activity, and (3) mood to generate feedback messages. We used a framework by adopting validated behavioral change theory-based models to evaluate the feedback messages against 3 dimensions of timing, intention, and content (feedback purpose and feedback response). The feedback purposes in this study were categorized into 7 purposes; warning, suggestion, self-monitoring, acknowledging, reinforcement, goal setting, and behavior contract. RESULTS: We identified 1,749 apps from which 156 diabetes mobile apps were eligible and generated 473 feedback messages. The majority of generated feedback messages were related to blood sugar measurement. Only feedback messages on blood sugar under diabetes-related measures and mood domains encompassed all 7 feedback purposes under the content dimension. CONCLUSIONS: Many feedback messages neither supported Healthy Coping domains nor followed the behavioral theory-based framework. It is important that feedback messages be structured around the dimensions of the behavioral theory-based framework to promote behavior change. Furthermore, our framework had the generalizability that can be used in other clinical areas.

SEE-diabetes, a patient-centered diabetes self-management education and support for older adults: Findings and information needs from providers' perspectives.

BACKGROUND AND AIMS: Diabetes self-management education and support (DSMES) can improve clinical and health outcomes of people with diabetes. However, DSMES has been underutilized because of many barriers. We aimed to develop a patient-centered educational aid, SEE-Diabetes (Support-Engage-Empower-Diabetes), that facilitates shared decision-making about DSMES between patient and provider during the follow-up visit. We investigated the information needs to inform the design of the SEE-Diabetes from the providers' perspective. METHODS: We conducted an online survey (N = 42) and three focus groups (N = 13) involving providers who have experience managing diabetes in older patients. Survey collected demographics and assessed knowledge of DSMES. During the subsequent focus groups, participants evaluated the Assessment and Plan section of three clinic notes of older people with diabetes. We also demonstrated the potential workflow of DSMES documentation using SEE-Diabetes during clinical practice. RESULTS: The survey showed 60% of providers were familiar with DSMES. Focus group findings showed clinic notes should convey concise information at an appropriate reading level, numbered problems, and less medical jargon to improve the readability of clinic notes. Application of SMART (Specific, Measurable, Attainable, Relevant, Time-bound) goals was suggested to deliver effective diabetes self-care information. CONCLUSIONS: Providers should consider adopting validated DSMES guidelines along with goal-setting strategies to provide patient-centered care. The research team will integrate the provider recommendations when we develop SEE-Diabetes.

SEE-Diabetes, a patient-centered diabetes self-management education and support for older adults: Findings and information needs from patients' perspectives.

AIMS: This study identified the information needs of people with diabetes aged 65 and older through surveys and focus groups to inform the development of a patient-centered educational decision aid for diabetes care, SEE-Diabetes (Support-Engage-Empower-Diabetes). METHODS: We conducted survey (N = 37) and three focus groups (N = 9). The survey collected demographics, diabetes duration, insulin usage, and clinic notes accessibility through a patient portal. In focus groups, participants evaluated the Assessment and Plan section of three selected deidentified clinic notes to assess readability and helpfulness for diabetes care. RESULTS: The mean age of participants was 66 (24-82, SD = 12), and 22 were female (60%). The mean diabetes duration was 20.9 years (1-63, SD=15). Most participants (80%) read their clinical notes via patient portal. In the focus groups, the readability of clinic notes was noted as a primary concern because of medical abbreviations and poor formatting. Participants found the helpfulness of clinic notes was negatively impacted by vague or insufficient self-care information. CONCLUSIONS: We found the high use of patient portal for reading clinic notes, which offers a use case opportunity for the proposed SEE-Diabetes educational aid. Feedback about the readability and helpfulness of clinic notes will be considered during the design process.

Transforming AADE7 for Use in an Evaluation Framework for Health Information Technology in Diabetes Mellitus.

There is no validated framework to evaluate health information technology (HIT) for diabetes self-management education and support (DSMES). AADE7 Self-Care Behaviors is a patient-centered DSMES designed by the American Association of Diabetes Educators (AADE). We developed a codebook based on the AADE7 Self-Care Behaviors principles as an evaluation framework. In this commentary, we demonstrate the real-life applications of this codebook through three diabetes research studies. The first study analyzed features of mobile diabetes applications. The second study evaluated provider documentation patterns in electronic health records (EHRs) to deliver ongoing patient-centered DSMES. The third study analyzed feedback messages from diabetes apps. We found that this codebook, based on AADE7, can be instrumental as a framework for research, as well as real-life use in HIT for DSMES principles.

Evaluation of provider documentation patterns as a tool to deliver ongoing patient-centred diabetes education and support.

BACKGROUND: Diabetes mellitus (DM) is one of the most common chronic diseases in the world. As a disease with long-term complications requiring changes in management, DM requires not only education at the time of diagnosis, but ongoing diabetes self-management education and support (DSME/S). In the United States, however, only a small proportion of people with DM receive DSME/S, although evidence supports benefits of ongoing DSME/S. The diabetes education that providers deliver during follow-up visits may be an important source for DSME/S for many people with DM. METHODS: We collected 200 clinic notes of follow-up visits for 100 adults with DM and studied the History of Present Illness (HPI) and Impression and Plan (I&P) sections. Using a codebook based on the seven principles of American Association of Diabetes Educators Self-Care Behaviors (AADE7), we conducted a multi-step deductive thematic analysis to determine the patterns of DSME/S information occurrence in clinic notes. Additionally, we used the generalised linear mixed models for investigating whether providers delivered DSME/S to people with DM based on patient characteristics. RESULTS: During follow-up visits, Monitoring was the most common self-care behaviour mentioned in both HPI and I&P sections. Being Active was the least common self-care behaviour mentioned in the HPI section and Healthy Coping was the least common self-care behaviour mentioned in the I&P section. We found providers delivered more information on Healthy Eating to men compared to women in I&P section. Generally, providers delivered DSME/S to people with DM regardless of patient characteristics. CONCLUSIONS: This study focused on the frequency distribution of information providers delivered to the people with DM during follow-up clinic visits based on the AADE7. The results may indicate a lack of patient-centred education when people with DM visit providers for ongoing management. Further studies are needed to identify the underlying reasons why providers have difficulty delivering patient-centred education.

An Analysis of Diabetes Mobile Applications Features Compared to AADE7™: Addressing Self-Management Behaviors in People With Diabetes.

BACKGROUND: Diabetes self-management (DSM) applications (apps) have been designed to improve knowledge of diabetes and self-management behaviors. However, few studies have systematically examined if diabetes apps followed the American Association of Diabetes Educators (AADE) Self-Care Behaviors™ guidelines. The purpose of this study was to compare the features of current DSM apps to the AADE7™ guidelines. METHODS: In two major app stores (iTunes and Google Play), we used three search terms "diabetes," "blood sugar," and "glucose" to capture a wide range of diabetes apps. Apps were excluded based on five exclusion criteria. A multidisciplinary team analyzed and classified the features of each app based on the AADE7™. We conducted interviews with six diabetes physicians and educators for their opinions on the distribution of the features of DSM apps. RESULTS: Out of 1050 apps retrieved, 173 apps were identified as eligible during November 2015 and 137 apps during December 2017. We found an unbalanced DSM app development trend based on AADE7™ guidelines. Many apps were designed to support the behaviors of Healthy Eating (77%), Monitoring (76%), Taking Medication (58%), and Being Active (45%). On the other hand, few apps explored the behaviors of Problem Solving (31%), Healthy Coping (10%), and Reducing Risks (5%). From interviews, we identified the main reasons why only a few apps support the features related to Problem Solving, Healthy Coping, and Reducing Risks. CONCLUSIONS: Future diabetes apps should attempt to incorporate features under evidence-based guidelines such as AADE7™ to better support the self-management behavior changes of people with diabetes.

Usability Evaluation of a Clinical Decision Support System for Geriatric ED Pain Treatment.

BACKGROUND: Older adults are at risk for inadequate emergency department (ED) pain care. Unrelieved acute pain is associated with poor outcomes. Clinical decision support systems (CDSS) hold promise to improve patient care, but CDSS quality varies widely, particularly when usability evaluation is not employed. OBJECTIVE: To conduct an iterative usability and redesign process of a novel geriatric abdominal pain care CDSS. We hypothesized this process would result in the creation of more usable and favorable pain care interventions. METHODS: Thirteen emergency physicians familiar with the Electronic Health Record (EHR) in use at the study site were recruited. Over a 10-week period, 17 1-hour usability test sessions were conducted across 3 rounds of testing. Participants were given 3 patient scenarios and provided simulated clinical care using the EHR, while interacting with the CDSS interventions. Quantitative System Usability Scores (SUS), favorability scores and qualitative narrative feedback were collected for each session. Using a multi-step review process by an interdisciplinary team, positive and negative usability issues in effectiveness, efficiency, and satisfaction were considered, prioritized and incorporated in the iterative redesign process of the CDSS. Video analysis was used to determine the appropriateness of the CDS appearances during simulated clinical care. RESULTS: Over the 3 rounds of usability evaluations and subsequent redesign processes, mean SUS progressively improved from 74.8 to 81.2 to 88.9; mean favorability scores improved from 3.23 to 4.29 (1 worst, 5 best). Video analysis revealed that, in the course of the iterative redesign processes, rates of physicians' acknowledgment of CDS interventions increased, however most rates of desired actions by physicians (such as more frequent pain score updates) decreased. CONCLUSION: The iterative usability redesign process was instrumental in improving the usability of the CDSS; if implemented in practice, it could improve geriatric pain care. The usability evaluation process led to improved acknowledgement and favorability. Incorporating usability testing when designing CDSS interventions for studies may be effective to enhance clinician use.

How Does Learnability of Primary Care Resident Physicians Increase After Seven Months of Using an Electronic Health Record? A Longitudinal Study.

BACKGROUND: Electronic health records (EHRs) with poor usability present steep learning curves for new resident physicians, who are already overwhelmed in learning a new specialty. This may lead to error-prone use of EHRs in medical practice by new resident physicians. OBJECTIVE: The study goal was to determine learnability gaps between expert and novice primary care resident physician groups by comparing performance measures when using EHRs. METHODS: We compared performance measures after two rounds of learnability tests (November 12, 2013 to December 19, 2013; February 12, 2014 to April 22, 2014). In Rounds 1 and 2, 10 novice and 6 expert physicians, and 8 novice and 4 expert physicians participated, respectively. Laboratory-based learnability tests using video analyses were conducted to analyze learnability gaps between novice and expert physicians. Physicians completed 19 tasks, using a think-aloud strategy, based on an artificial but typical patient visit note. We used quantitative performance measures (percent task success, time-on-task, mouse activities), a system usability scale (SUS), and qualitative narrative feedback during the participant debriefing session. RESULTS: There was a 6-percentage-point increase in novice physicians' task success rate (Round 1: 92%, 95% CI 87-99; Round 2: 98%, 95% CI 95-100) and a 7-percentage-point increase in expert physicians' task success rate (Round 1: 90%, 95% CI 83-97; Round 2: 97%, 95% CI 93-100); a 10% decrease in novice physicians' time-on-task (Round 1: 44s, 95% CI 32-62; Round 2: 40s, 95% CI 27-59) and 21% decrease in expert physicians' time-on-task (Round 1: 39s, 95% CI 29-51; Round 2: 31s, 95% CI 22-42); a 20% decrease in novice physicians mouse clicks (Round 1: 8 clicks, 95% CI 6-13; Round 2: 7 clicks, 95% CI 4-12) and 39% decrease in expert physicians' mouse clicks (Round 1: 8 clicks, 95% CI 5-11; Round 2: 3 clicks, 95% CI 1-10); a 14% increase in novice mouse movements (Round 1: 9247 pixels, 95% CI 6404-13,353; Round 2: 7991 pixels, 95% CI 5350-11,936) and 14% decrease in expert physicians' mouse movements (Round 1: 7325 pixels, 95% CI 5237-10,247; Round 2: 6329 pixels, 95% CI 4299-9317). The SUS measure of overall usability demonstrated only minimal change in the novice group (Round 1: 69, high marginal; Round 2: 68, high marginal) and no change in the expert group (74; high marginal for both rounds). CONCLUSIONS: This study found differences in novice and expert physicians' performance, demonstrating that physicians' proficiency increased with EHR experience. Our study may serve as a guideline to improve current EHR training programs. Future directions include identifying usability issues faced by physicians when using EHRs, through a more granular task analysis to recognize subtle usability issues that would otherwise be overlooked.

UT Biomedical Informatics Lab (BMIL) Probability Wheel.

A probability wheel app is intended to facilitate communication between two people, an "investigator" and a "participant," about uncertainties inherent in decision-making. Traditionally, a probability wheel is a mechanical prop with two colored slices. A user adjusts the sizes of the slices to indicate the relative value of the probabilities assigned to them. A probability wheel can improve the adjustment process and attenuate the effect of anchoring bias when it is used to estimate or communicate probabilities of outcomes. The goal of this work was to develop a mobile application of the probability wheel that is portable, easily available, and more versatile. We provide a motivating example from medical decision-making, but the tool is widely applicable for researchers in the decision sciences.

Health information needs, sources, and barriers of primary care patients to achieve patient-centered care: A literature review.

To synthesize findings from previous studies assessing information needs of primary care patients on the Internet and other information sources in a primary care setting. A systematic review of studies was conducted with a comprehensive search in multiple databases including OVID MEDLINE, CINAHL, and Scopus. The most common information needs among patients were information about an illness or medical condition and treatment methods, while the most common information sources were the Internet and patients' physicians. Overall, patients tend to prefer the Internet for the ease of access to information, while they trust their physicians more for their clinical expertise and experience. Barriers to information access via the Internet include the following: socio-demographic variables such as age, ethnicity, income, education, and occupation; information search skills; and reliability of health information. CONCLUSION: Further research is warranted to assess how to create accurate and reliable health information sources for both Internet and non-Internet users.

Exploring the Usability of Mobile Apps Supporting Radiologists' Training in Diagnostic Decision Making.

PURPOSE: The objective of this study was to conduct a usability evaluation of mobile apps for supporting education and training in radiologic diagnostic decision-making processes. METHODS: Of 381 mobile apps available at two major stores (Google Play and iTunes), eight iOS apps were selected for laboratory-based usability tests. Six staff radiologists completed eight app-specific task sets, using a think-aloud strategy. The triangular methods approach included quantitative performance measures, System Usability Scale (SUS), and qualitative thematic analysis using heuristic usability principles of usability issues. RESULTS: Overall, radiologists achieved higher than 70% success, with favorable SUS scores, in completing the tasks for seven of the eight apps. However, task success rate and SUS score had a weak relation (r = 0.23), indicating that the perceived usability may not reflect the holistic usability of the app. Task analysis and self-report revealed 108 usability issues, which were condensed to 55 unique issues and categorized by nine usability themes and mapped to ten usability heuristics. Nonintuitive functionality (eg, nonintuitive or misleading labels) was the most frequent theme observed, leading to inefficient navigation. These usability findings were consistent with the 13 improvements the radiologists suggested. CONCLUSIONS: This study demonstrates the feasibility of usability evaluation of radiology mobile apps and suggests potential improvements in the development of radiology mobile apps. This study also suggests that proficiency with mobile devices may not be equivalent to being an expert user, proficient in using the apps.

Toward Successful Implementation of Speech Recognition Technology: A Survey of SRT Utilization Issues in Healthcare Settings.

PURPOSE: To evaluate physician utilization of speech recognition technology (SRT) for medical documentation in two hospitals. METHODS: A quantitative survey was used to collect data in the areas of practice, electronic equipment used for documentation, documentation created after providing care, and overall thoughts about and satisfaction with the SRT. The survey sample was from one rural and one urban facility in central Missouri. In addition, qualitative interviews were conducted with a chief medical officer and a physician champion regarding implementation issues, training, choice of SRT, and outcomes from their perspective. RESULTS: Seventy-one (60%) of the anticipated 125 surveys were returned. A total of 16 (23%) participants were practicing in internal medicine and 9 (13%) were practicing in family medicine. Fifty-six (79%) participants used a desktop and 14 (20%) used a laptop (2%) computer. SRT products from Nuance were the dominant SRT used by 59 participants (83%). Windows operating systems (Microsoft, Redmond, WA) was used by more than 58 (82%) of the survey respondents. With regard to user experience, 42 (59%) participants experienced spelling and grammatical errors, 15 (21%) encountered clinical inaccuracy, 9 (13%) experienced word substitution, and 4 (6%) experienced misleading medical information. CONCLUSIONS: This study shows critical issues of inconsistency, unreliability, and dissatisfaction in the functionality and usability of SRT. This merits further attention to improve the functionality and usability of SRT for better adoption within varying healthcare settings.

Determining differences in user performance between expert and novice primary care doctors when using an electronic health record (EHR).

RATIONALE, AIMS AND OBJECTIVES: The goal of this study is to determine usability gaps between expert and novice primary care doctors when using an electronic health record (EHR). METHODS: Usability tests using video analyses with triangular method approach were conducted to analyse usability gaps between 10 novice and seven expert doctors. Doctors completed 19 tasks, using think-aloud strategy, based on an artificial but typical patient visit note. The usability session lasted approximately 20 minutes. The testing room consisted of the participant and the facilitator. Mixed methods approach including four sets of performance measures, system usability scale (SUS), and debriefing session with participants was used. RESULTS: While most expert doctors completed tasks more efficiently, and provided a higher SUS score than novice doctors (novice 68, expert 70 out of 100 being perfect score), the result of 'percent task success rate' were comparable (74% for expert group, 78% for novice group, P = 0.98) on all 19 tasks. CONCLUSION: This study found a lack of expertise among doctors with more experience using the system demonstrating that although expert doctors have been using the system longer, their proficiency did not increase with EHR experience. These results may potentially improve the EHR training programme, which may increase doctors' performance when using an EHR. These results may also assist EHR vendors in improving the user interface, which may aid in reducing errors caused from poor usability of the system.

Quantifying the aesthetic outcomes of breast cancer treatment: assessment of surgical scars from clinical photographs.

RATIONALE: Accurate assessment of the degree of scaring that results from surgical intervention for breast cancer would enable more effective pre-operative counselling. The resultant scar that accompanies an open surgical intervention may be characterized by variance in thickness, colour and contour. These factors significantly impact the overall appearance of the breast. A number of studies have addressed the mechanical and pathologic aspects of scarring. The majority of these investigations have focused on the physiologic process of scar formation and means to improve the qualities of a scar. Few studies have focused on quantifying the visual impact of scars. METHODS: This manuscript critically reviews current methods used to assess scars in terms of overall satisfaction after surgery. We introduce objective, quantitative measures for assessing linear breast surgical scars using digital photography. These new measurements of breast surgical scars are based on calculations of contrast and area. RESULTS AND CONCLUSIONS: We demonstrate, using the intra-class correlation coefficient, that the new measures are robust to observer variability in annotating the scar region on clinical photographs. As an example of the utility of the new measures, we use them to quantify the aesthetic differences of reconstruction following skin-sparing mastectomy vs. conventional mastectomy.

A pilot study on using eye tracking to understand assessment of surgical outcomes from clinical photography.

Appearance changes resulting from breast cancer treatment impact the quality of life of breast cancer survivors, but current approaches to evaluating breast characteristics are very limited. It is challenging, even for experienced plastic surgeons, to describe how different aspects of breast morphology impact overall assessment of esthetics. Moreover, it is difficult to describe what they are looking for in a manner that facilitates quantification. The goal of this study is to assess the potential of using eye-tracking technology to understand how plastic surgeons assess breast morphology by recording their gaze path while they rate physical characteristics of the breasts, e.g., symmetry, based on clinical photographs. In this study, dwell time, transition frequency, dwell sequence conditional probabilities, and dwell sequence joint probabilities were analyzed across photographic poses and three observers. Dwell-time analysis showed that all three surgeons spent the majority of their time on the anterior-posterior (AP) views. Similarly, transition frequency analysis between regions showed that there were substantially more transitions between the breast regions in the AP view, relative to the number of transitions between other views. The results of both the conditional and joint probability analyses between the breast regions showed that the highest probabilities of transitions were observed between the breast regions in the AP view (APRB, APLB) followed by the oblique views and the lateral views to complete evaluation of breast surgical outcomes.

Towards quantifying the aesthetic outcomes of breast cancer treatment: comparison of clinical photography and colorimetry.

RATIONALE, AIMS AND OBJECTIVES: Scarring is a significant cause of dissatisfaction for women who undergo breast surgery. Scar tissue may be clinically distinguished from normal skin by aberrant colour, rough surface texture, increased thickness (hypertrophy) and firmness. Colorimeters or spectrophotometers can be used to quantitatively assess scar colour, but they require direct patient interaction and can cost thousands of dollars. By comparison, digital photography is already in widespread use to document clinical outcomes and requires less patient interaction. Thus, assessment of scar coloration by digital photography is an attractive alternative. The goal of this study was to compare colour measurements obtained by digital photography and colorimetry. METHODS: Agreements between photographic and colorimetric measurements of colour were evaluated. Experimental conditions were controlled by performing measurements on artificial scars created by a make-up artist. The colorimetric measurements of the artificial scars were compared with those reported in the literature for real scars in order to confirm the validity of this approach. We assessed the agreement between the colorimetric and photographic measurements of colour using a hypothesis test for equivalence, the intraclass correlation coefficient and the Bland-Altman method. RESULTS: Overall, good agreement was obtained for three parameters (L*a*b*) measured by colorimetry and photography from the results of three statistical analyses. CONCLUSION: Colour measurements obtained by digital photography were equivalent to those obtained using colorimetry. Thus, digital photography is a reliable, cost-effective measurement method of skin colour and should be further investigated for quantitative analysis of surgical outcomes.

Toward decision support for breast reconstruction: automated calculation of symmetry measure on clinical photographs.

The quality of life of breast cancer survivors is maintained by minimizing adverse effects on their physical appearance. In this study, we present an automated method for computing a common measure of breast symmetry, the normalized Breast Retraction Assessment (pBRA), from routine clinical photographs taken to document breast reconstruction procedures.

Assessment of breast aesthetics.

A good aesthetic outcome is an important endpoint of breast cancer treatment. Subjective ratings, direct physical measurements, measurements on photographs, and assessment by three-dimensional imaging are reviewed and future directions in aesthetic outcome measurements are discussed. Qualitative, subjective scales have frequently been used to assess aesthetic outcomes following breast cancer treatment. However, none of these scales has achieved widespread use because they are typically vague and have low intraobserver and interobserver agreement. Anthropometry is not routinely performed because conducting the large studies needed to validate anthropometric measures (i.e., studies in which several observers measure the same subjects multiple times) is impractical. Quantitative measures based on digital/digitized photographs have yielded acceptable results but have some limitations. Three-dimensional imaging has the potential to enable consistent, objective assessment of breast appearance, including properties (e.g., volume) that are not available from two-dimensional images. However, further work is needed to define three-dimensional measures of aesthetic properties and how they should be interpreted.