In this report, the authors evaluate the effectiveness of breast reduction in alleviating the symptoms of macromastia by comparing baseline and postoperative health status using a series of well-validated self-report instruments. The study had a prospective design with a surgical intervention group and two control groups: a hypertrophy control group with bra cup sizes D or larger and a normal control group with bra cup sizes less than D. The effectiveness of nonsurgical interventions in relieving the symptoms of macromastia was also evaluated, both in the operative subjects and in the control groups. Surgical candidates and controls completed a self-administered baseline survey that consisted of the following validated and standardized instruments commonly used to evaluate outcomes: SF-36, EuroQol, Multidimensional Body-Self Relations Questionnaire (MBSRQ), and the McGill Pain Questionnaire (MPQ). A specially designed and validated instrument, the Breast-Related Symptoms (BRS), was also used. There were also questions about prior nonsurgical treatments, comorbid conditions, bra size, and a physical assessment. Additional information obtained on the operative subjects included surgical procedure data, resection weight, and complications. Approximately 6 to 9 months postoperatively, surgical subjects completed the same questionnaire as described above, and a final physical assessment was performed. The cohort included 179 operative subjects with matched preoperative and postoperative data sets, 96 normal controls and 88 hypertrophy controls. The women were predominantly Caucasian, middle-aged, well educated, and employed. Fifty percent of the operative subjects reported breast-related pain all or most of the time in the upper back, shoulders, neck, and lower back preoperatively compared with less than 10 percent postoperatively. Operative subjects and hypertrophy controls tried a number of conservative treatments, including weight loss, but none provided adequate permanent relief. Compared with population norms, the preoperative subjects had significantly lower scores (p < 0.05) in all eight health domains of the SF-36, and in the mental and physical component summary scores. After surgery, the operative subjects had higher means (better health) than national norms in seven of the eight domains and improved significantly from presurgical means in all eight domains (p < 0.05). Before surgery, the operative subjects reported high levels of pain with a Pain Rating Index (PRI) score from the MPQ of 26.6. After surgery, pain was significantly lower with a mean PRI score of 11.7, similar to that of our controls (mean PRI score, 11.2). Regression analysis was used to control for covariate effects on the main study outcomes. Among the operative subjects, benefits from breast reduction were not associated with body weight, bra cup size, or weight of resection, with essentially all patients benefiting from surgery.Breast hypertrophy has a significant impact on women's health status and quality of life as measured by validate...

We examined evidence on whether mobile health (mHealth) tools, including Interactive Voice Response (IVR) calls, short message service (SMS) or text messaging, and smartphones, can improve lifestyle behaviors and management related to cardiovascular diseases throughout the world. We conducted a state-of-the-art review and literature synthesis of peer-reviewed and grey literature published since 2004. The review prioritized randomized trials and studies focused on cardiovascular diseases and risk factors, but included other reports when they represented the best available evidence. The search emphasized reports on the potential benefits of mHealth interventions implemented in low- and middle-income countries (LMICs). IVR and SMS interventions can improve cardiovascular preventive care in developed countries by addressing risk factors including weight, smoking, and physical activity. IVR and SMS-based interventions for cardiovascular disease management also have shown benefits with respect to hypertension management, hospital readmissions, and diabetic glycemic control. Multi-modal interventions including web-based communication with clinicians and mHealth-enabled clinical monitoring with feedback also have shown benefits. The evidence regarding the potential benefits of interventions using smartphones and social media is still developing. Studies of mHealth interventions have been conducted in more than 30 LMICs, and evidence to date suggests that programs are feasible and may improve medication adherence and disease outcomes. Emerging evidence suggests that mHealth interventions may improve cardiovascular-related lifestyle behaviors and disease management. Next generation mHealth programs developed worldwide should be based on evidence-based behavioral theories and incorporate advances in artificial intelligence for adapting systems automatically to patients’ unique and changing needs.

BackgroundMobile health (mHealth) interventions may improve heart failure (HF) self-care, but standard models do not address informal caregivers’ needs for information about the patient’s status or how the caregiver can help.ObjectiveWe evaluated mHealth support for caregivers of HF patients over and above the impact of a standard mHealth approach.MethodsWe identified 331 HF patients from Department of Veterans Affairs outpatient clinics. All patients identified a “CarePartner” outside their household. Patients randomized to “standard mHealth” (n=165) received 12 months of weekly interactive voice response (IVR) calls including questions about their health and self-management. Based on patients’ responses, they received tailored self-management advice, and their clinical team received structured fax alerts regarding serious health concerns. Patients randomized to “mHealth+CP” (n=166) received an identical intervention, but with automated emails sent to their CarePartner after each IVR call, including feedback about the patient’s status and suggestions for how the CarePartner could support disease care. Self-care and symptoms were measured via 6- and 12-month telephone surveys with a research associate. Self-care and symptom data also were collected through the weekly IVR assessments.ResultsParticipants were on average 67.8 years of age, 99% were male (329/331), 77% where white (255/331), and 59% were married (195/331). During 15,709 call-weeks of attempted IVR assessments, patients completed 90% of their calls with no difference in completion rates between arms. At both endpoints, composite quality of life scores were similar across arms. However, more mHealth+CP patients reported taking medications as prescribed at 6 months (8.8% more, 95% CI 1.2-16.5, P=.02) and 12 months (13.8% more, CI 3.7-23.8, P<.01), and 10.2% more mHealth+CP patients reported talking with their CarePartner at least twice per week at the 6-month follow-up (P=.048). mHealth+CP patients were less likely to report negative emotions during those interactions at both endpoints (both P<.05), were consistently more likely to report taking medications as prescribed during weekly IVR assessments, and also were less likely to report breathing problems or weight gains (all P<.05). Among patients with more depressive symptoms at enrollment, those randomized to mHealth+CP were more likely than standard mHealth patients to report excellent or very good general health during weekly IVR calls.ConclusionsCompared to a relatively intensive model of IVR monitoring, self-management assistance, and clinician alerts, a model including automated feedback to an informal caregiver outside the household improved HF patients’ medication adherence and caregiver communication. mHealth+CP may also decrease patients’ risk of HF exacerbations related to shortness of breath and sudden weight gains. mHealth+CP may improve quality of life among patients with greater depressive symptoms. Weekly health and self-care monitoring via mHealth tools may identify intervention effec...

Background Mobile health services may improve chronic illness care, but interventions rarely support informal caregivers’ efforts. Objectives To determine whether automated feedback to caregivers of chronic heart failure (HF) patients impacts caregiving burden and assistance with self-management. Research Design Randomized comparative effectiveness trial. Subjects 369 HF patients were recruited from a VA healthcare system. All patients participated with a “CarePartner” or informal caregiver outside their household. Intervention Patients randomized to “standard mHealth” received weekly automated self-care support calls for 12 months with notifications about problems sent to clinicians. “mHealth+CP” patients received identical services, plus email summaries and suggestions for self-care assistance automatically sent to their CarePartners. Measures At baseline, six- and twelve months, CarePartners completed assessments of caregiving strain, depressive symptoms, and participation in self-care support. Results mHealth+CP CarePartners reported less caregiving strain than controls at both 6- and 12-months (both p≤.03). That effect as well as improvements in depressive symptoms were seen primarily among CarePartners reporting greater burden at baseline (p ≤.03 for interactions between arm and baseline strain/depression at both endpoints). While most mHealth+CP CarePartners increased the amount of time spent in self-care support, those with the highest time commitment at baseline reported decreases at both follow-ups (all p<.05). mHealth+CP CarePartners reported more frequently attending patients’ medical visits at six months (p=.049) and greater involvement in medication adherence at both endpoints (both p≤.032). Conclusions When CarePartners experienced significant caregiving strain and depression, systematic feedback about their patient-partner decreased those symptoms. Feedback also increased most CarePartners’ engagement in self-care.

Women seeking consultation for the surgical relief of symptoms associated with breast hypertrophy have been the focus of many studies. In contrast, little is known about those women with breast hypertrophy who do not seek symptomatic relief. The purpose of this study was to describe the health burden of breast hypertrophy by using a set of validated questionnaires and to compare women with breast hypertrophy who seek surgical treatment with those who do not. In addition, this latter group was compared with a group of control women without breast hypertrophy. Women seeking consultation for surgery were recruited from 14 plastic-surgery practices. Control subjects were recruited by advertisements in primary-care offices and newspapers. Women were asked to complete a self-report questionnaire that included the European Quality of Life (EuroQol) questionnaire, McGill Pain Questionnaire, Multidimensional Body Self Relations Questionnaire (MBSRQ), the Short Form-36 (SF-36) questionnaire, and questions regarding breast-related symptoms, comorbidities, and bra size. Descriptive statistics were compiled for three groups of women: (1) hypertrophy patients seeking surgical care, (2) hypertrophy control subjects (those whose reported bra-cup size was a D or larger), and (3) normal control subjects (those whose reported bra-cup size was an A, B, or C). The multiple linear regression method was used to compare the health burdens across groups while adjusting for other variables. Two hundred ninety-one women seeking surgical care and 195 control subjects were enrolled in the study. The 184 control subjects with bra-cup information available were further separated into 88 hypertrophy control subjects and 96 normal control subjects. In the control group, bra-cup size was correlated with health-burden measures, whereas in the surgical candidates, it was not. When scores were compared across the three groups, significant differences were found in all health-burden measures. The surgical candidates scored more poorly on the EuroQol utility, McGill pain rating index, MBSRQ appearance evaluation, physical component scale of the SF-36, and on breast symptoms than did the two control groups. In addition, the hypertrophy control subjects scored more poorly than the normal control subjects. With multiple linear regression analysis incorporating important potential confounders, the poorer scores in the surgical candidates remained statistically significant. It was concluded that breast hypertrophy in those seeking surgical care and those not seeking surgery has a significant impact on women's quality of life as measured by validated and widely used self-report instruments including the EuroQol, MBSRQ, McGill Pain Questionnaire, and the SF-36. Likewise, a new assessment instrument for breast-related symptoms also demonstrated greater symptomatology in women with breast hypertrophy.

Background Patient self-care support via Interactive Voice Response (IVR) can improve disease management. However little is known about the factors affecting program engagement. Methods We compiled data on IVR program engagement for 1,173 patients with: heart failure, depression, diabetes, and cancer who were followed for 28,962 person-weeks. Patients in programs for diabetes or depression (N=727) had the option of participating along with an informal caregiver who received electronic feedback based on the patient’s IVR assessments. Analyses focused on factors associated with completing weekly IVR calls. Results Patients were on average 61 years old, 37% had at most a high school education, and 48% reported incomes < $30,000. Among patients given the option of participating with an informal caregiver, 65% chose to do so. Patients completed 83% of attempted IVR assessments, with rates higher for heart failure (90%) and cancer programs (90%) than for the diabetes (81%) or depression programs (71%) (p<0.001). Among patients in diabetes or depression programs, those opting to have feedback provided to an informal caregiver were more likely to complete assessments (adjusted odds ratio: 1.36; 95% CI: 1.06, 1.75). Older patients had higher call completion rates, even among patients > 75 years of age. Missed clinic appointments, prior hospitalizations, depression program participation, and poorer mental health were associated with lower completion rates. Conclusions Patients with a variety of chronic conditions will complete IVR self-care support calls regularly. Risk factors for missed IVR calls overlap with those for missed appointments. Involvement of informal caregivers may significantly increase engagement.

Hospitalized patients often are readmitted soon after discharge, with many hospitalizations being potentially preventable. The authors evaluated a mobile health intervention designed to improve post-hospitalization support for older adults with common chronic conditions. All participants enrolled with an informal caregiver or “CarePartner” (CP). Intervention patients received automated assessment and behavior change calls. CPs received automated, structured feedback following each assessment. Clinicians received alerts about serious problems identified during patient calls. Controls had a 65% greater risk of hospitalization within 90 days post discharge than intervention patients ( P = .041). For every 6.8 enrollees, the intervention prevented 1 rehospitalization or emergency department encounter. The intervention improved physical functioning at 90 days ( P = .012). The intervention also improved medication adherence and indicators of the quality of communication with CPs (all P < .01). Automated telephone patient monitoring and self-care advice with feedback to primary care teams and CPs reduces readmission rates over 90 days.

BackgroundCognitive behavioral therapy (CBT) is one of the most effective treatments for chronic low back pain. However, only half of Department of Veterans Affairs (VA) patients have access to trained CBT therapists, and program expansion is costly. CBT typically consists of 10 weekly hour-long sessions. However, some patients improve after the first few sessions while others need more extensive contact.ObjectiveWe are applying principles from “reinforcement learning” (a field of artificial intelligence or AI) to develop an evidence-based, personalized CBT pain management service that automatically adapts to each patient’s unique and changing needs (AI-CBT). AI-CBT uses feedback from patients about their progress in pain-related functioning measured daily via pedometer step counts to automatically personalize the intensity and type of patient support. The specific aims of the study are to (1) demonstrate that AI-CBT has pain-related outcomes equivalent to standard telephone CBT, (2) document that AI-CBT achieves these outcomes with more efficient use of clinician resources, and (3) demonstrate the intervention’s impact on proximal outcomes associated with treatment response, including program engagement, pain management skill acquisition, and patients’ likelihood of dropout.MethodsIn total, 320 patients with chronic low back pain will be recruited from 2 VA healthcare systems and randomized to a standard 10 sessions of telephone CBT versus AI-CBT. All patients will begin with weekly hour-long telephone counseling, but for patients in the AI-CBT group, those who demonstrate a significant treatment response will be stepped down through less resource-intensive alternatives including: (1) 15-minute contacts with a therapist, and (2) CBT clinician feedback provided via interactive voice response calls (IVR). The AI engine will learn what works best in terms of patients’ personally tailored treatment plans based on daily feedback via IVR about their pedometer-measured step counts, CBT skill practice, and physical functioning. Outcomes will be measured at 3 and 6 months post recruitment and will include pain-related interference, treatment satisfaction, and treatment dropout. Our primary hypothesis is that AI-CBT will result in pain-related functional outcomes that are at least as good as the standard approach, and that by scaling back the intensity of contact that is not associated with additional gains in pain control, the AI-CBT approach will be significantly less costly in terms of therapy time.ResultsThe trial is currently in the start-up phase. Patient enrollment will begin in the fall of 2016 and results of the trial will be available in the winter of 2019.ConclusionsThis study will evaluate an intervention that increases patients’ access to effective CBT pain management services while allowing health systems to maximize program expansion given constrained resources.