Robert M. Kaplan

Spatial Turn in Health Research

Developments in geographic science and technology can increase our understanding of disease prevalence, etiology, transmission, and treatment. Spatial analysis using maps to associate geographic information with disease can be traced as far back as the 17th century. Today, recent developments and the widespread diffusion of geospatial data acquisition technologies are enabling creation of highly accurate spatial (and temporal) data relevant to health research. This has the potential to increase our understanding of the prevalence, etiology, transmission, and treatment of many diseases.

Harmonized patient-reported data elements in the electronic health record: supporting meaningful use by primary care action on health behaviors and key psychosocial factors

BACKGROUND Electronic health records (EHR) have the potential to improve patient care through efficient access to complete patient health information. This potential may not be reached because many of the most important determinants of health outcome are rarely included. Successful health promotion and disease prevention requires patient-reported data reflecting health behaviors and psychosocial issues. Furthermore, there is a need to harmonize this information across different EHR systems. METHODS To fill this gap a three-phased process was used to conceptualize, identify and recommend patient-reported data elements on health behaviors and psychosocial factors for the EHR. Expert panels (n=13) identified candidate measures (phase 1) that were reviewed and rated by a wide range of health professionals (n=93) using the grid-enabled measures wiki social media platform (phase 2). Recommendations were finalized through a town hall meeting with key stakeholders including patients, providers, researchers, policy makers, and representatives from healthcare settings (phase 3). RESULTS Nine key elements from three areas emerged as the initial critical patient-reported elements to incorporate systematically into EHR--health behaviors (eg, exercise), psychosocial issues (eg, distress), and patient-centered factors (eg, demographics). Recommendations were also made regarding the frequency of collection ranging from a single assessment (eg, demographic characteristics), to annual assessment (eg, health behaviors), or more frequent (eg, patient goals). CONCLUSIONS There was strong stakeholder support for this initiative reflecting the perceived value of incorporating patient-reported elements into EHR. The next steps will include testing the feasibility of incorporating these elements into the EHR across diverse primary care settings.

Patient-reported measures of psychosocial issues and health behavior should be added to electronic health records

Recent legislation and delivery system reform efforts are greatly expanding the use of electronic health records. For these efforts to reach their full potential, they must actively involve patients and include patient-reported information about such topics as health behavior, preferences, and psychosocial functioning. We offer a plan for including standardized, practical patient-reported measures as part of electronic health records, quality and performance indexes, the primary care medical home, and research collaborations. These measures must meet certain criteria, including being valid, reliable, sensitive to change, and available in multiple languages. Clinicians, patients, and policy makers also must be able to understand the measures and take action based on them. Including more patient-reported items in electronic health records would enhance health, patient-centered care, and the capacity to undertake population-based research.

Likelihood of Null Effects of Large NHLBI Clinical Trials Has Increased over Time.

Background We explore whether the number of null results in large National Heart Lung, and Blood Institute (NHLBI) funded trials has increased over time. Methods We identified all large NHLBI supported RCTs between 1970 and 2012 evaluating drugs or dietary supplements for the treatment or prevention of cardiovascular disease. Trials were included if direct costs >

US general population norms for telephone administration of the SF-36v2

500,000/year, participants were adult humans, and the primary outcome was cardiovascular risk, disease or death. The 55 trials meeting these criteria were coded for whether they were published prior to or after the year 2000, whether they registered in clinicaltrials.gov prior to publication, used active or placebo comparator, and whether or not the trial had industry co-sponsorship. We tabulated whether the study reported a positive, negative, or null result on the primary outcome variable and for total mortality. Results 17 of 30 studies (57%) published prior to 2000 showed a significant benefit of intervention on the primary outcome in comparison to only 2 among the 25 (8%) trials published after 2000 (χ2=12.2,df= 1, p=0.0005). There has been no change in the proportion of trials that compared treatment to placebo versus active comparator. Industry co-sponsorship was unrelated to the probability of reporting a significant benefit. Pre-registration in clinical trials.gov was strongly associated with the trend toward null findings. Conclusions The number NHLBI trials reporting positive results declined after the year 2000. Prospective declaration of outcomes in RCTs, and the adoption of transparent reporting standards, as required by clinicaltrials.gov, may have contributed to the trend toward null findings.

Big Data and Large Sample Size: A Cautionary Note on the Potential for Bias

OBJECTIVE US general population norms for mail administration of the Medical Outcomes Study 36-Item Short Form Version 2 (SF-36v2) were established in 1998. This article reports SF-36v2 telephone-administered norms collected in 2005-2006 for adults aged 35-89 years. STUDY DESIGN AND SETTING The SF-36v2 was administered to 3,844 adults in the National Health Measurement Study (NHMS), a random-digit dial telephone survey. Scale scores and physical and mental component summary (PCS and MCS) scores were computed. RESULTS When compared with 1998 norms (mean=50.00, standard deviation [SD]=10.00), SF-36v2 scores for the 2005-2006 general population tended to be higher: physical functioning (mean=50.68, SD=14.48); role limitations due to physical health problems (mean=49.47, SD=14.71); bodily pain (mean=50.66, SD=16.28); general health perceptions (mean=50.10, SD=16.87); vitality (mean=53.71, SD=15.35); social functioning (mean=51.37, SD=13.93); role limitations due to emotional problems (mean=51.44, SD=13.93); mental health (mean=54.27, SD=13.28); PCS (mean=49.22, SD=15.13); MCS (mean=53.78, SD=13.14). PCS and MCS factor scoring coefficients were similar to those previously reported for the 1998 norms. SF-36v2 norms for telephone administration were created. CONCLUSION The higher scores for NHMS data are likely due to the effect of telephone administration. The 2005-2006 norms can be used as a reference to interpret scale and component summary scores for telephone-administered surveys with the SF-36v2.

Systems Science A Good Investment for the Public’s Health

A number of commentaries have suggested that large studies are more reliable than smaller studies and there is a growing interest in the analysis of “big data” that integrates information from many thousands of persons and/or different data sources. We consider a variety of biases that are likely in the era of big data, including sampling error, measurement error, multiple comparisons errors, aggregation error, and errors associated with the systematic exclusion of information. Using examples from epidemiology, health services research, studies on determinants of health, and clinical trials, we conclude that it is necessary to exercise greater caution to be sure that big sample size does not lead to big inferential errors. Despite the advantages of big studies, large sample size can magnify the bias associated with error resulting from sampling or study design. Clin Trans Sci 2014; Volume #: 1–5

Factors to Inform Clinicians About the End of Life in Severe Chronic Obstructive Pulmonary Disease

This supplement of Health Education & Behavior showcases the current state of the field of systems science applications in health promotion and public health. Behind this work lies a steady stream of public dollars at the federal level. This perspective details nearly a decade of investment by the National Institutes of Health’s Office of Behavioral and Social Sciences Research. These investments have included funding opportunity announcements, training programs, developing resources for researchers, cross-disciplinary fertilization, and publication. While much progress has been made, continuing investment is needed in the future to ensure the viability and sustainability of this young but increasingly important field.

State-Level Variations in Racial Disparities in Life Expectancy

CONTEXT Palliative services have historically been offered to terminal patients with cancer, but much less so in other chronic illnesses such as chronic obstructive pulmonary disease (COPD) because of difficulties in predicting the trajectory to death. OBJECTIVES The goal of this study was to determine if the change over time of the key parameters (trajectory) in patients with severe COPD can independently predict short-term mortality. METHODS We analyzed data from 1218 patients with severe COPD. Multivariate models for trajectory change were used to forecast mortality at 12 months. RESULTS Changes in several variables by defined cutpoints increase significantly and independently the odds of dying in 12 months. The earliest and strongest predictors were the decrease in gait speed by 0.14 m/s or six-minute walk by 50 m (odds ratio [OR] 4.40, P<0.0001). Alternatively, if six-minute walk or gait speed were not used, change toward perceiving a very sedentary state using a single question (OR 3.56, P=0.0007) and decrease in maximal inspiratory pressure greater than 11 cmH2O (OR 2.19, P=0.0217) were predictive, followed by change toward feeling upset or downhearted (OR 2.44, P=0.0250), decrease in room air resting partial pressure of oxygen greater than 5 mmHg (OR 2.46, P=0.0156), and increase in room air resting partial pressure of carbon dioxide greater than 3 mmHg (OR 2.8, P=0.0039). Change over time models were more discriminative (higher c-statistics) than change from baseline models. CONCLUSION The changes in defined variables and patient-reported outcomes by defined cutpoints were independently associated with increased 12-month mortality in patients with severe COPD. These results may inform clinicians when to initiate end-of-life communications and palliative care.

Screening mammography & breast cancer mortality: meta-analysis of quasi-experimental studies.

OBJECTIVE To explore state patterns in the racial life expectancy gap. DATA SOURCES The 1997-2004 Multiple Cause of Death PUF, 2000 U.S. Census. STUDY DESIGN We calculated life expectancy at birth for black and white men and women. DATA EXTRACTION METHODS Data were obtained by the NCHS and U.S. Census Bureau. PRINCIPAL FINDINGS States with small racial differences are due to higher-than-expected life expectancy for blacks or lower-than-expected for whites. States with large disparity are explained by higher-than-average life expectancy among whites or lower-than-average life expectancy among blacks. CONCLUSIONS Heterogeneous state patterns in racial disparity in life expectancy exist. Eliminating disparity in states with large black populations would make the greatest impact nationally.