WRITING GROUP MEMBERS Emelia J. Benjamin, MD, SCM, FAHA Michael J. Blaha, MD, MPH Stephanie E. Chiuve, ScD Mary Cushman, MD, MSc, FAHA Sandeep R. Das, MD, MPH, FAHA Rajat Deo, MD, MTR Sarah D. de Ferranti, MD, MPH James Floyd, MD, MS Myriam Fornage, PhD, FAHA Cathleen Gillespie, MS Carmen R. Isasi, MD, PhD, FAHA Monik C. Jiménez, ScD, SM Lori Chaffin Jordan, MD, PhD Suzanne E. Judd, PhD Daniel Lackland, DrPH, FAHA Judith H. Lichtman, PhD, MPH, FAHA Lynda Lisabeth, PhD, MPH, FAHA Simin Liu, MD, ScD, FAHA Chris T. Longenecker, MD Rachel H. Mackey, PhD, MPH, FAHA Kunihiro Matsushita, MD, PhD, FAHA Dariush Mozaffarian, MD, DrPH, FAHA Michael E. Mussolino, PhD, FAHA Khurram Nasir, MD, MPH, FAHA Robert W. Neumar, MD, PhD, FAHA Latha Palaniappan, MD, MS, FAHA Dilip K. Pandey, MBBS, MS, PhD, FAHA Ravi R. Thiagarajan, MD, MPH Mathew J. Reeves, PhD Matthew Ritchey, PT, DPT, OCS, MPH Carlos J. Rodriguez, MD, MPH, FAHA Gregory A. Roth, MD, MPH Wayne D. Rosamond, PhD, FAHA Comilla Sasson, MD, PhD, FAHA Amytis Towfighi, MD Connie W. Tsao, MD, MPH Melanie B. Turner, MPH Salim S. Virani, MD, PhD, FAHA Jenifer H. Voeks, PhD Joshua Z. Willey, MD, MS John T. Wilkins, MD Jason HY. Wu, MSc, PhD, FAHA Heather M. Alger, PhD Sally S. Wong, PhD, RD, CDN, FAHA Paul Muntner, PhD, MHSc On behalf of the American Heart Association Statistics Committee and Stroke Statistics Subcommittee Heart Disease and Stroke Statistics—2017 Update

Heart Disease and Stroke Statistics—2017 Update: A Report From the American Heart Association

BIOMEDICAL RESEARCH POLICY COMMITTEE REPORT WAS PUBLISHED AS A SUPPLEMENT TO THE AUGUSTJOURNAL OF MEDICAL EDUCATION. A REPRINT IS ENCLOSED. REQUESTS FOR ADDITIONAL COPIES SHOULD BE ADDRESSED TO THISOFFICE. -COPIES ARE BEING SENT TO MEMBERS OF CONGRESS AND THE KEY MEMBERS OF THE ADMINISTRATION. CALLING UPON-YOUR SENATORSAND CONGRESSMEN TO TELL THE STORY OF THE ROLE. OF MEDICAL SCHOOLS IN BIOMEDICAL RESEARCH AND HEALTH CARE IS IMPORTANT.I STRONGLY URGE THAT YOU MAKE AN 411 APPOINTMENT TO SEE YOUR CONGRESSIONAL REPRESENTATIVES WHILE YOU ARE IN WASHINGTON FOR THE COUNCIL MEETINGON OCTOBER 29. UPON REQUEST WE CAN SUPPLY THE NAMES OF APPOINTMENT SECRETARIES AND PHONE NUMBERS OF YOUR SENATORS AND CONGRESSMEN. APPROPRIATIONS COMMITTEE ACTED WITH EXTRAORDINARY ALACRITY THIS YEAR. THE-NIH APPROPRIATION WAS INCREASED BY 242 MILLION DOLLARSOVER 1971, REPRESENTING A 142 MILLION DOLLAR INCREASE OVER. THE ADMINISTRATION BUDGET, THE BLUE SHEET ASCRIBES APPROPRIATIONS OUTCOME TO THE EFFECTIVENESS OF THE COALITION FOR HEALTH FUNDING UNDER THE LEADERSHIP OF JOHN A. D. COOPER.

The Association of American Medical Colleges

Background: A number of recent advances in our understanding of thyroid physiology may shed light on why some patients feel unwell while taking levothyroxine monotherapy. The purpose of this task force was to review the goals of levothyroxine therapy, the optimal prescription of conventional levothyroxine therapy, the sources of dissatisfaction with levothyroxine therapy, the evidence on treatment alternatives, and the relevant knowledge gaps. We wished to determine whether there are sufficient new data generated by well-designed studies to provide reason to pursue such therapies and change the current standard of care. This document is intended to inform clinical decision-making on thyroid hormone replacement therapy; it is not a replacement for individualized clinical judgment. Methods: Task force members identified 24 questions relevant to the treatment of hypothyroidism. The clinical literature relating to each question was then reviewed. Clinical reviews were supplemented, when relevant, with related...

Guidelines for the Treatment of Hypothyroidism: Prepared by the American Thyroid Association Task Force on Thyroid Hormone Replacement

A Qualitative Study

The accurate measurement of blood pressure (BP) is essential for the diagnosis and management of hypertension. This article provides an updated American Heart Association scientific statement on BP measurement in humans. In the office setting, many oscillometric devices have been validated that allow accurate BP measurement while reducing human errors associated with the auscultatory approach. Fully automated oscillometric devices capable of taking multiple readings even without an observer being present may provide a more accurate measurement of BP than auscultation. Studies have shown substantial differences in BP when measured outside versus in the office setting. Ambulatory BP monitoring is considered the reference standard for out-of-office BP assessment, with home BP monitoring being an alternative when ambulatory BP monitoring is not available or tolerated. Compared with their counterparts with sustained normotension (ie, nonhypertensive BP levels in and outside the office setting), it is unclear whether adults with white-coat hypertension (ie, hypertensive BP levels in the office but not outside the office) have increased cardiovascular disease risk, whereas those with masked hypertension (ie, hypertensive BP levels outside the office but not in the office) are at substantially increased risk. In addition, high nighttime BP on ambulatory BP monitoring is associated with increased cardiovascular disease risk. Both oscillometric and auscultatory methods are considered acceptable for measuring BP in children and adolescents. Regardless of the method used to measure BP, initial and ongoing training of technicians and healthcare providers and the use of validated and calibrated devices are critical for obtaining accurate BP measurements.

Measurement of Blood Pressure in Humans: A Scientific Statement From the American Heart Association.

BACKGROUND AND OBJECTIVES Trust and satisfaction in the physician-patient relationship is the cornerstone of family medicine. Today, computers are playing an increasingly prominent role in the delivery of health care, yet recent data detailing their effect on the physician-patient relationship are limited. For physicians to "first do no harm," it is critical to determine that computers used at the point of care do not decrease patient satisfaction, because this is a good proxy for the physician-patient relationship. This study assessed patients' views of computer use and its effect on patient satisfaction in a family medicine clinic before and after implementation of an electronic environment developed by our institution. METHODS A survey was mailed to patients who had been evaluated at a family medicine clinic for hypertension, high blood pressure without hypertension, or hyperlipidemia. These diseases were selected because they are common and require strong physician-patient relationships for successful treatment. The survey assessed patients' overall satisfaction with health care received at the clinic and their opinions about how their physician's computer use affected their visit. This survey was compared with a survey done in 1995 at the same clinic, before adoption of the electronic environment. RESULTS A total of 478 patients were enrolled in the study; 304 (63.6%) of these returned surveys. A majority of the patients (74.6%) thought that the computer had an overall positive impact on the quality of care provided. There was a positive association between a physician's computer skills, as rated by patients, and the patients' satisfaction with the computer's effect on the visit. There were no differences in overall satisfaction between the 1995 survey and the current survey. CONCLUSIONS This study shows that physician competence with computers plays an important role in patient satisfaction and that computers can be integrated into the office visit without a detrimental effect on patient satisfaction. Surprisingly, patient familiarity with computers was shown to have a slight negative correlation with patient satisfaction. These findings are significant in view of research indicating that compliance, health outcomes, perception of physician competence, and malpractice suits are all related to physicians' interpersonal skills and patient satisfaction.

21st-century health care: the effect of computer use by physicians on patient satisfaction at a family medicine clinic.

Purpose: Hospital readmissions within 30 days of initial discharge occur frequently. In studies of elderly patients receiving Medicare, readmissions have been associated with poor-quality inpatient care, ineffective hospital-to-home transitions, patient characteristics, disease burden, and socioeconomic status. Among adult family medicine patients spanning a wide age range, we hypothesize that previous hospitalizations, length of stay, number of discharge medications, medical comorbidities, and patient demographics are associated with a greater risk of hospital readmission within 30 days. Methods: A retrospective case-control study of 276 family medicine inpatients was conducted to determine the factors associated with 30-day readmission. Bivariate statistics were computed and a multivariate analysis using logistic regression was performed to determine the independent effects of each factor. Results: Patients readmitted within 30 days had more hospitalizations, more emergency department visits, longer hospital stays, more comorbidities, and more discharge medications and were less likely to be married. Multivariate logistic regression found that hospitalization within the previous 12 months (odds ratio, 2.71) and long hospital stays (odds ratio, 2.16) were associated with 30-day readmission; being married (odds ratio, 0.54) had a protective effect. Conclusions: This study demonstrates that factors previously found to be associated with 30-day readmission among elderly patients receiving Medicare also apply to family medicine patients of all ages. It also demonstrates prior hospitalizations, length of stay, and marital status are useful proxies for many more complicated factors, such as disease burden, medical complexity, and social issues, that influence hospital readmission.

Predictors of Thirty-Day Readmission Among Hospitalized Family Medicine Patients

Background: Collaborative care management (CCM) has been shown to have superior outcomes to usual care (UC) for depressed patients with a fixed end point. This study was a survival analysis over time comparing CCM with UC using remission (9-item Patient Health Questionnaire [PHQ-9] score Methods: A retrospective cohort study of 7340 patients with depression cared for at 4 outpatient primary care clinics was conducted from March 2008 through June 2013. All adult patients diagnosed with depression (International Classification of Diseases, 9th Revision [ICD-9], codes 296.2–3) or dysthymia (ICD-9 code 300.4) with an initial PHQ-9 score ≥10 were included. CCM was implemented at all clinics between 2008 and 2010. Kaplan-Meyer survival curves for time to remission and PDSs were plotted. A Cox proportional hazards model was used to adjust for expected differences between patients choosing CCM versus UC. Results: Median time to remission was 86 days (95% confidence interval [CI], 81–91 days) for the CCM group versus 614 days (95% CI, 565–692 days) for the UC group. Likewise, median duration of PDSs was 31 days (95% CI, 30–33 days) for the CCM group versus 154 days (95% CI, 138–182 days) for the UC group. In the Cox proportional hazards model, which controlled for covariates such as age, sex, race, diagnosis, and initial PHQ-9 score, CCM was associated with faster remission (hazard ratio of the CCM group [HRCCM], 2.48; 95% CI, 2.31–2.65). Conclusions: This study demonstrated that patients enrolled in CCM have a faster rate of remission and a shorter duration of PDSs than patients choosing UC.

Time to Remission for Depression with Collaborative Care Management (CCM) in Primary Care

Rationale, aims and objectives
Hospital readmission within 30 days of discharge occurs in almost 20% of US Medicare patients and may be a marker of poor quality inpatient care, ineffective hospital to home transitions, or disease severity. Within a patient centered medical home, care transition interventions may only be practical from cost and staffing perspectives if targeted at patients with the greatest risk of readmission. Various scoring algorithms attempt to predict patients at risk for 30-day readmission, but head-to-head comparison of performance is lacking. Compare published scoring algorithms which use generally available electronic medical record data on the same set of hospitalized primary care patients.

Methods
The LACE index, the LACE+ index, the HOSPITAL score, and the readmission risk score were computed on a consecutive cohort of 26,278 hospital admissions. Classifier performance was assessed by plotting receiver operating characteristic curves comparing the computed score with the actual outcome of death or readmission within 30 days. Statistical significance of differences in performance was assessed using bootstrapping techniques.

Results
Correct readmission classification on this cohort was moderate with the following c-statistics: Readmission risk score 0.666; LACE 0.680; LACE+ 0.662; and HOSPITAL 0.675. There was no statistically significant difference in performance between classifiers.

Conclusions
Logistic regression based classifiers yield only moderate performance when utilized to predict 30-day readmissions. The task is difficult due to the variety of underlying causes for readmission, nonlinearity, and the arbitrary time period of concern. More sophisticated classification techniques may be necessary to increase performance and allow patient centered medical homes to effectively focus efforts to reduce readmissions.

Comparing performance of 30‐day readmission risk classifiers among hospitalized primary care patients

Purpose: The chronic disease model suggests continuity of care and team-based care can improve outcomes for multimorbidity patients and reduce hospitalizations. Continuity of care following admission has had mixed effects on readmission rates; however, its effect before admission has not been well studied. Increased outpatient care organization and continuity before admission is hypothesized to reduce the odds of readmission. Methods: In a cohort of 14,662 primary care patients from a Patient-Centered Medical Home (PCMH) practice, continuity of care in the 12 months before admission was assessed using 3 established metrics; usual provider continuity (UPC), dispersion continuity of care (COC), and sequence continuity (SECON). In addition, because these established metrics may not accurately reflect continuity in planned team-based care, a new metric called visit entropy (VE) was used to quantify the disorganization of visits. Multivariate logistic regression was performed to examine the relationship between readmission within 30 days and continuity while controlling for known readmission risk factors abstracted from an electronic medical record. Results: Higher VE was associated with readmission (odds ratio, 1.10; 95% confidence interval, 1.02 to 1.19). The continuity measures of UPC, COC, and SECON were not associated with readmission. Conclusions: Disorganized medical care, characterized by a higher VE, is associated with higher odds of readmission among hospitalized primary care patients. An association between traditional measures of continuity (UPC, COC, and SECON) and readmission was not found.

Gregory M. Garrison

Papers

21st-century health care: the effect of computer use by physicians on patient satisfaction at a family medicine clinic.

Predictors of Thirty-Day Readmission Among Hospitalized Family Medicine Patients

Time to Remission for Depression with Collaborative Care Management (CCM) in Primary Care

Comparing performance of 30‐day readmission risk classifiers among hospitalized primary care patients

Visit Entropy Associated with Hospital Readmission Rates