An Adaptive Healthcare Organization Can Effectively Respond to Medical Crises.

Healthcare systems are challenged by unexpected medical crises. Established frameworks and approaches to guide healthcare institutions during these crises are limited in their effectiveness. We propose an Adaptive Healthcare Organization (AHO) system as a framework focused on the dynamic nature of healthcare delivery. Based on seven key capabilities, the AHO framework can guide single and multi-institutional healthcare organizations to adapt in real time to an unexpected medical crisis and improve their efficiency and effectiveness.

Integration of patient experience factors improves readmission prediction.

Many readmission prediction models have marginal accuracy and are based on clinical and demographic data that exclude patient response data. The objective of this study was to evaluate the accuracy of a 30-day hospital readmission prediction model that incorporates patient response data capturing the patient experience. This was a prospective cohort study of 30-day hospital readmissions. A logistic regression model to predict readmission risk was created using patient responses obtained during interviewer-administered questionnaires as well as demographic and clinical data. Participants (N = 846) were admitted to 2 inpatient adult medicine units at Massachusetts General Hospital from 2012 to 2016. The primary outcome was the accuracy (measured by receiver operating characteristic) of a 30-day readmission risk prediction model. Secondary analyses included a readmission-focused factor analysis of individual versus collective patient experience questions. Of 1754 eligible participants, 846 (48%) were enrolled and 201 (23.8%) had a 30-day readmission. Demographic factors had an accuracy of 0.56 (confidence interval [CI], 0.50-0.62), clinical disease factors had an accuracy of 0.59 (CI, 0.54-0.65), and the patient experience factors had an accuracy of 0.60 (CI, 0.56-0.64). Taken together, their combined accuracy of receiver operating characteristic = 0.78 (CI, 0.74-0.82) was significantly more accurate than these factors were individually. The individual accuracy of patient experience, demographic, and clinical data was relatively poor and consistent with other risk prediction models. The combination of the 3 types of data significantly improved the ability to predict 30-day readmissions. This study suggests that more accurate 30-day readmission risk prediction models can be generated by including information about the patient experience.

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.

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.

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.

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.

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.

Electronic physiologic and subjective data acquisition in home-dwelling heart failure patients: An assessment of patient use and perception of usability.

BACKGROUND: The current approach to the outpatient management of heart failure involves patients recollecting what has happened to them since their last clinic visit. But patients' recollection of their symptoms may not be sufficiently accurate to optimally manage their disease. Most of what is known about heart failure is related to patients' diurnal symptoms and activities. Some mobile electronic technologies can operate continuously to collect data from the time patients go to bed until they get up in the morning. We were therefore interested to evaluate if patients would use a system of selected patient-facing devices to collect physiologic and subjective state data in and around the patients' period of sleep, and if there were differences in device use and perceptions of usability at the device level METHODS: This descriptive observational study of home-dwelling patients with heart failure, between 21 and 90 years of age, enrolled in an outpatient heart failure clinic was conducted between December 2014 and June 2015. Patients received five devices, namely, body weight scale, blood pressure device, an iPad-based subjective states assessment, pulse oximeter, and actigraph, to collect their physiologic (body weight, blood pressure, heart rate, blood oxygen saturation, and physical activity) and subjective state data (symptoms and subjective states) at home for the next six consecutive nights. Use was defined as the ratio of observed use over expected use, where 1.0 is observed equals expected. Usability was determined by the overall System Usability Scale score. RESULTS: Participants were 39 clinical heart failure patients, mean age 68.1 (SD, 12.3), 72% male, 62% African American. The ratio of observed over expected use for the body weight scale, blood pressure device, iPad application, pulse oximeter and actigraph was 0.8, 1.0, 1.1, 0.9, and 1.9, respectively. The mean overall System Usability Scale score for each device were 84.5, 89.7, 85.7, 87.6, and 85.2, respectively. CONCLUSIONS: Patients were able to use all of the devices and they rated the usability of all the devices higher than expected. Our study provides support for at-home patient-collected physiologic and subjective state data. To our knowledge, this is the first study to assess the use and usability of electronic objective and subjective data collection devices in heart failure patients' homes overnight.