Mental health comorbidities and cost/utilization outcomes in head and neck cancer patients.

PURPOSE: Examine the relationship between mental health comorbidities and health services outcomes in non-elderly adults with head and neck cancer (HNC). DESIGN: Retrospective, cross-sectional. SAMPLE: Non-elderly adults with a primary diagnosis of HNC in U.S. Department of Defense (TRICARE) administrative claims data for fiscal years (FY) 2007-2014. METHODS: Linear regression and generalized linear models were used to examine predictors of reimbursed cost and healthcare utilization, respectively. FINDINGS: On average, there were 2944 HNC patients each year, the majority age 55-64, male, military retirees or family members of retirees, cared for in civilian facilities, and residing in the U.S. southern region. Between FY2007 and FY2014, there were slight increases in prevalence rates for diagnosed depression (12.4%-13.1%), anxiety (8.2%-11.9%), adjustment disorders (3.7%-5.8%), and drug use disorders (10.3%-19.4%), and a slight decrease in alcohol use disorders (12.3%-11.4%). In the cost regression model, depression and anxiety were the seventh and eighth strongest predictors (p < .001), behind hospice use, treatment modalities, chronic physical conditions, and tobacco use. In the utilization regression models, depression, adjustment disorder, and anxiety ranked seventh, ninth, and eleventh as the strongest predictors for the number of ambulatory visits; anxiety, depression and substance use disorder ranked fifth, sixth, and eighth in the model examining predictors of the number of annual hospitalizations; and anxiety and depression ranked fifth and sixth in the model examining predictors of the annual number of bed days. CONCLUSIONS: We found strong evidence that mental health comorbidities impact cost and utilization among HNC patients, independent of other factors. Implications for Psychosocial Providers or Policy: Addressing mental health comorbidities among HNC patients may reduce cost and improve resource efficiency.

Improving the safety and quality of cancer care.

The cancer community is increasingly interested in improving its safety and quality. Improvement will be driven by the expansion of safety and quality research and by a commitment to publish studies that advance high-quality, safe cancer care. Cancer 2017;123:549-550. © 2016 American Cancer Society.

Assessing the usability by clinicians of VISION: A hierarchical display of patient-collected physiological information to clinicians.

BACKGROUND: The inability of patients to accurately and completely recount their clinical status between clinic visits reduces the clinician's ability to properly manage their patients. One way to improve this situation is to collect objective patient information while the patients are at home and display the collected multi-day clinical information in parallel on a single screen, highlighting threshold violations for each channel, and allowing the viewer to drill down to any analog signal on the same screen, while maintaining the overall physiological context of the patient. All this would be accomplished in a way that was easy for the clinician to view and use. METHODS: Patients used five mobile devices to collect six heart failure-related clinical variables: body weight, systolic and diastolic blood pressure, pulse rate, blood oxygen saturation, physical activity, and subjective input. Fourteen clinicians practicing in a heart failure clinic rated the display using the System Usability Scale that, for acceptability, had an expected mean of 68 (SD, 12.5). In addition, we calculated the Intraclass Correlation Coefficient of the clinician responses using a two-way, mixed effects model, ICC (3,1). RESULTS: We developed a single-screen temporal hierarchical display (VISION) that summarizes the patient's home monitoring activities between clinic visits. The overall System Usability Scale score was 92 (95% CI, 87-97), p < 0.0001; the ICC was 0.89 (CI, 0.79-0.97), p < 0.0001. CONCLUSION: Clinicians consistently found VISION to be highly usable. To our knowledge, this is the first single-screen, parallel variable, temporal hierarchical display of both continuous and discrete information acquired by patients at home between clinic visits that presents clinically significant information at the point of care in a manner that is usable by clinicians.

Survey of Current Simulation Based Training in the US Military Health System.

INTRODUCTION: Simulation-based medical training has been shown to be effective and is widely used in civilian hospitals; however, it is unclear how widely and how effectively simulation is utilized in the U.S. Military Health System (MHS). The current operational state of medical simulation in the MHS is unknown, and there remains a need for a system-wide assessment of whether and how the advances in simulation-based medical training are employed to meet the evolving needs of the present-day warfighter. Understanding the types of skills and methods used within simulation programs across the enterprise is important data for leaders as they plan for the future in terms of curriculum development and the investment of resources. The aim of the present study is to survey MHS simulation programs in order to determine the prevalence of skills taught, the types of learners served, and the most common methodologies employed in this worldwide health care system. MATERIALS AND METHODS: A cross-sectional survey of simulation activities was distributed to the medical directors of all 93 simulation programs in the MHS. The survey was developed by the authors based on lists of critical wartime skills published by the medical departments of the US Army, Navy, and Air Force. Respondents were asked to indicate the types of learners trained at their program, which of the 82 unique skills included in the survey are trained at their site, and for each skill the modalities of simulation used, i.e., mannequin, standardized patients, part task trainers, augmented/virtual reality tools, or cadaver/live tissue. RESULTS: Complete survey responses were obtained from 75 of the 93 (80%) MHS medical simulation training programs. Across all skills included in the survey, those most commonly taught belonged predominantly to the categories of medic skills and nursing skills. Across all sites, the most common category of learner was the medic/corpsman (95% of sites), followed by nurses (87%), physicians (83%), non-medical combat lifesavers (59%), and others (28%) that included on-base first responders, law enforcement, fire fighters, and civilians. The skills training offered by programs included most commonly the tasks associated with medics/corpsmen (97%) followed by nursing (81%), advanced provider (77%), and General Medical Officer (GMO) skills (47%). CONCLUSION: The survey demonstrated that the most common skills taught were all related to point of injury combat casualty care and addressed the most common causes of death on the battlefield. The availability of training in medic skills, nursing skills, and advanced provider skills were similar in small, medium, and large programs. However, medium and small programs were less likely to deliver training for advanced providers and GMOs compared to larger programs. Overall, this study found that simulation-based medical training in the MHS is focused on medic and nursing skills, and that large programs are more likely to offer training for advanced providers and GMOs. Potential gaps in the availability of existing training are identified as over 50% of skills included in the nursing, advanced provider, and GMO skill categories are not covered by at least 80% of sites serving those learners.

Assessing the Ability of a Large Language Model to Score Free-Text Medical Student Clinical Notes: Quantitative Study.

Background: Teaching medical students the skills required to acquire, interpret, apply, and communicate clinical information is an integral part of medical education. A crucial aspect of this process involves providing students with feedback regarding the quality of their free-text clinical notes. Objective: The goal of this study was to assess the ability of ChatGPT 3.5, a large language model, to score medical students' free-text history and physical notes. Methods: This is a single-institution, retrospective study. Standardized patients learned a prespecified clinical case and, acting as the patient, interacted with medical students. Each student wrote a free-text history and physical note of their interaction. The students' notes were scored independently by the standardized patients and ChatGPT using a prespecified scoring rubric that consisted of 85 case elements. The measure of accuracy was percent correct. Results: The study population consisted of 168 first-year medical students. There was a total of 14,280 scores. The ChatGPT incorrect scoring rate was 1.0%, and the standardized patient incorrect scoring rate was 7.2%. The ChatGPT error rate was 86%, lower than the standardized patient error rate. The ChatGPT mean incorrect scoring rate of 12 (SD 11) was significantly lower than the standardized patient mean incorrect scoring rate of 85 (SD 74; P=.002). Conclusions: ChatGPT demonstrated a significantly lower error rate compared to standardized patients. This is the first study to assess the ability of a generative pretrained transformer (GPT) program to score medical students' standardized patient-based free-text clinical notes. It is expected that, in the near future, large language models will provide real-time feedback to practicing physicians regarding their free-text notes. GPT artificial intelligence programs represent an important advance in medical education and medical practice.

Radiation exposure and cost influence physician medical image decision making: a randomized controlled trial.

BACKGROUND: It is estimated that 20%-40% of advanced medical imaging in the United States is unnecessary, resulting in patient overexposure to radiation and increasing the cost of care. Previous imaging utilization studies have focused on clinical appropriateness. An important contributor to excessive use of advanced imaging may be a physician "knowledge gap" regarding the safety and cost of the tests. OBJECTIVES: To determine whether safety and cost information will change physician medical image decision making. RESEARCH DESIGN: Double-blinded, randomized controlled trial. Following standardized case presentation, physicians made an initial imaging choice. This was followed by the presentation of guidelines, radiation exposure and health risk, and cost information. RESULTS: Approximately half (57 of 112, 50.9%) of participants initially selected computed tomography (CT). When presented with guideline recommendations, participants did not modify their initial imaging choice (P=0.197). A significant reduction (56.3%, P<0.001) in CT ordering occurred after presentation of radiation exposure/health risk information; ordering changed to magnetic resonance imaging or ultrasound (US). A significant reduction (48.3%, P<0.001) in CT and magnetic resonance imaging ordering occurred after presentation of Medicare reimbursement information; ordering changed to US. The majority of physicians (31 of 40, 77.5%) selecting US never modified their ordering. No significant relationship between physician demographics and decision making was observed. CONCLUSIONS: This study suggests that physician decision making can be influenced by safety and cost information and the order in which information is provided to physicians can affect their decisions.

Responses of physicians to an objective safety and quality knowledge test: a cross-sectional study.

OBJECTIVE: For physicians to practice safe high quality medicine they must have sufficient safety and quality knowledge. Although a great deal is known about the safety and quality perceptions, attitudes and beliefs of physicians, little is known about their safety and quality knowledge. This study tested the objective safety and quality knowledge of practicing US primary care physicians. DESIGN: Cross-sectional objective test of safety and quality knowledge. SETTING: Primary care physicians practicing in the USA. PARTICIPANTS: Study consisted of 518 US practicing primary care physicians who answered an email invitation. Fifty-four percent were family medicine and 46% were internal medicine physicians.The response rate was 66%. INTERVENTION: The physicians took a 24-question multiple-choice test over the internet. OUTCOME: The outcome was the percent correct. RESULTS: The average number of correct answers was 11.4 (SD, 2.69), 48% correct. Three common clinical vignettes questions were answered correctly by 45% of the physicians. Five common radiation exposures questions were answered correctly by 40% of the physicians. Seven common healthcare quality and safety questions were answered correctly by 43% of the physicians. Seven Donabedian's model of structure, process and outcome measure questions were answered correctly by 67% of the physicians. Two Institute of Medicine's definitions of quality and safety questions were answered correctly by 19.5% of the physicians. CONCLUSION: Forty-eight per cent of the physicians' answers to the objective safety and quality questions were correct. To our knowledge, this is the first assessment of the objective safety and quality knowledge of practicing US primary care physicians.

Cost and Healthcare Utilization Among Non-Elderly Head and Neck Cancer Patients in the Military Health System, a Single-Payer Universal Health Care Model.

INTRODUCTION: Examining costs and utilization in a single-payer universal health care system provides information on fiscal and resource burdens associated with head and neck cancer (HNC). Here, we examine trends in the Department of Defense (DoD) HNC population with respect to: (1) reimbursed annual costs and (2) patterns and predictors of health care utilization in military only, civilian only, and both systems of care (mixed model). MATERIALS AND METHODS: A retrospective, cross-sectional study was conducted using TRICARE claims data from fiscal years 2007 through 2014 for reimbursement of ambulatory, inpatient, and pharmacy charges. The study was approved by the Defense Health Agency Office of Privacy and Civil Liberties as exempt from institutional review board full review. The population was all beneficiaries, age 18-64, with a primary ICD-9 diagnosis of HNC, on average, 2,944 HNC cases per year. The outcomes of regression models were total reimbursed health care cost, and counts of ambulatory visits, hospitalizations, and bed days. The predictors were fiscal year, demographic variables, hospice use, type and geographic region of TRICARE enrollment, use of military or civilian care or mixed use, cancer treatment modalities, the number of physical and mental health comorbid conditions, and tobacco use. A priori, null hypotheses were assumed. RESULTS: Per annual average, 61% of the HNC population was age 55-64, and 69% were males. About 6% accessed military facilities only for all health care, 60% accessed civilian only, and 34% accessed both military and civilian facilities. Patients who only accessed military care had earlier stage disease as indicated by rates of single modality treatment and hospice use; military care only and mixed use had similar rates of combination treatment and hospice use. The average cost per patient per year was $14,050 for civilian care only, $13,036 for military care only, and $29,338 for mixed use of both systems. The strongest predictors of higher cost were chemotherapy, radiation therapy, head and neck surgery, hospice care, and mixed-use care. The strongest predictors of health care utilization were chemotherapy, use of hospice, the number of physical and mental health comorbidities, radiation therapy, head and neck surgery, and system of care. CONCLUSIONS: To a single payer, the use of a single system of care exclusively among HNC patients is more cost-effective than use of a mixed-use system. The results suggest an over-utilization of ambulatory care services when both military and civilian care are accessed. Further investigation is needed to assess coordination between systems of care and improved efficiencies with respect to the cost and apparent over-utilization of health care services.

Predicting Clinical Outcomes Using Molecular Biomarkers.

Over the past 20 years, there has been an exponential increase in the number of biomarkers. At the last count, there were 768,259 papers indexed in PubMed.gov directly related to biomarkers. Although many of these papers claim to report clinically useful molecular biomarkers, embarrassingly few are currently in clinical use. It is suggested that a failure to properly understand, clinically assess, and utilize molecular biomarkers has prevented their widespread adoption in treatment, in comparative benefit analyses, and their integration into individualized patient outcome predictions for clinical decision-making and therapy. A straightforward, general approach to understanding how to predict clinical outcomes using risk, diagnostic, and prognostic molecular biomarkers is presented. In the future, molecular biomarkers will drive advances in risk, diagnosis, and prognosis, they will be the targets of powerful molecular therapies, and they will individualize and optimize therapy. Furthermore, clinical predictions based on molecular biomarkers will be displayed on the clinician's screen during the physician-patient interaction, they will be an integral part of physician-patient-shared decision-making, and they will improve clinical care and patient outcomes.

The adoption of an electronic health record did not improve A1c values in Type 2 diabetes.

BACKGROUND: A major justification for the clinical adoption of electronic health records (EHRs) was the expectation that it would improve the quality of medical care. No longitudinal study has tested this assumption. OBJECTIVE: We used hemoglobin A1c, a recognized clinical quality measure directly related to diabetes outcomes, to assess the effect of EHR use on clinical quality. METHODS: We performed a five-and-one-half-year multicentre longitudinal retrospective study of the A1c values of 537 type 2 diabetic patients. The same patients had to have been seen on at least three occasions: once approximately six months prior to EHR adoption (before-EHR), once approximately six monthsafter EHR adoption (after-EHR) and once approximately five years after EHR adoption (five-years), for a total of 1,611 notes. RESULTS: The overall mean confidence interval (CI) A1c values for the before- EHR, after-EHR and five-years were 7.07 (6.91 - 7.23), 7.33 (7.14 - 7.52) and 7.19 (7.06 - 7.32), respectively. There was a small but significant increase in A1c values between before-EHR and after-EHR, p = .04; there were no other significant differences. There was a significant decrease in notes missing at least one A1c value, from 42% before-EHR to 16% five-years (p < .001). CONCLUSION: We found that based on patient's A1c values, EHRs did not improve the clinical quality of diabetic care in six months and five years after EHR adoption. To our knowledge, this is the first longitudinal study to directly assess the relationshipbetween the use of an EHR and clinical quality.