"How did you get to this number?" Stakeholder needs for implementing predictive analytics: a pre-implementation qualitative study.

OBJECTIVE: Predictive analytics are potentially powerful tools, but to improve healthcare delivery, they must be carefully integrated into healthcare organizations. Our objective was to identify facilitators, challenges, and recommendations for implementing a novel predictive algorithm which aims to prospectively identify patients with high preventable utilization to proactively involve them in preventative interventions. MATERIALS AND METHODS: In preparation for implementing the predictive algorithm in 3 organizations, we interviewed 3 stakeholder groups: health systems operations (eg, chief medical officers, department chairs), informatics personnel, and potential end users (eg, physicians, nurses, social workers). We applied thematic analysis to derive key themes and categorize them into the dimensions of Sittig and Singh's original sociotechnical model for studying health information technology in complex adaptive healthcare systems. Recruiting and analysis were conducted iteratively until thematic saturation was achieved. RESULTS: Forty-nine interviews were conducted in 3 healthcare organizations. Technical components of the implementation (hardware and software) raised fewer concerns than alignment with sociotechnical factors. Stakeholders wanted decision support based on the algorithm to be clear and actionable and incorporated into current workflows. However, how to make this disease-independent classification tool actionable was perceived as a challenge, and appropriate patient interventions informed by the algorithm appeared likely to require substantial external and institutional resources. Stakeholders also described the criticality of trust, credibility, and interpretability of the predictive algorithm. CONCLUSIONS: Although predictive analytics can classify patients with high accuracy, they cannot advance healthcare processes and outcomes without careful implementation that takes into account the sociotechnical system. Key stakeholders have strong perceptions about facilitators and challenges to shape successful implementation.

Drivers of preventable high health care utilization: a qualitative study of patient, physician and health system leader perspectives.

OBJECTIVES: A small percentage of patients account for the bulk of population health care utilization and costs in many countries including the United States (US). In the US, 5% of the population has high health care utilization accounting for nearly 50% of health care costs. A subset of this utilization is deemed preventable, and thus potentially cost saving to patients as well as to the health care system. This study sought to identify drivers of preventable utilization from the perspectives of three stakeholder groups in the US: health system leaders; high-need, high-cost (HNHC) patients or their primary caregivers; and physicians. METHODS: We performed a qualitative study using interviews of health system leaders and focus groups of HNHC patients, caregivers and physicians. We used a mixed inductive deductive approach to analyse transcripts and identify themes. RESULTS: We identified three key drivers of preventable high health care utilization: (1) unmet behavioural health needs, (2) socio-economic determinants of health and (3) challenges associated with accessing health care delivery systems. CONCLUSIONS: To be potentially more effective, interventions to reduce preventable high health care utilization should incorporate the perspectives of patients, health system leaders and physicians. Particularly important to stakeholders is increased access to mental-health resources, support for patients with low socio-economic resources and systemic changes that reduce wait times for primary care visits and allow providers more time during patient visits.

Image Sharing Technologies and Reduction of Imaging Utilization: A Systematic Review and Meta-analysis.

INTRODUCTION: Image sharing technologies may reduce unneeded imaging by improving provider access to imaging information. A systematic review and meta-analysis were conducted to summarize the impact of image sharing technologies on patient imaging utilization. METHODS: Quantitative evaluations of the effects of PACS, regional image exchange networks, interoperable electronic heath records, tools for importing physical media, and health information exchange systems on utilization were identified through a systematic review of the published and gray English-language literature (2004-2014). Outcomes, standard effect sizes (ESs), settings, technology, populations, and risk of bias were abstracted from each study. The impact of image sharing technologies was summarized with random-effects meta-analysis and meta-regression models. RESULTS: A total of 17 articles were included in the review, with a total of 42 different studies. Image sharing technology was associated with a significant decrease in repeat imaging (pooled effect size [ES] = -0.17; 95% confidence interval [CI] = [-0.25, -0.09]; P < .001). However, image sharing technology was associated with a significant increase in any imaging utilization (pooled ES = 0.20; 95% CI = [0.07, 0.32]; P = .002). For all outcomes combined, image sharing technology was not associated with utilization. Most studies were at risk for bias. CONCLUSIONS: Image sharing technology was associated with reductions in repeat and unnecessary imaging, in both the overall literature and the most-rigorous studies. Stronger evidence is needed to further explore the role of specific technologies and their potential impact on various modalities, patient populations, and settings.

Illness representations of cancer among healthy residents of Kolkata, India.

Cancer illness representations and screening history among residents of Kolkata, India, were investigated along with socio-demographic characteristics in an effort to understand possible motivations for health behavior. A total of 106 participants were recruited from community locations in Kolkata, India and completed surveys including demographics, the illness perception questionnaire-revised (IPQ-R), and previous experience with cancer and screening practices. Participants were 51.5% college educated, 57% female, 51.5% full-time employed with average age of 32.7 years (R: 18-60 years). Descriptive statistics were generated for the subscales of the IPQ-R, cancer-screening practices and cancer experience. Correlation analyses were conducted to investigate associations between cancer representations and socio-demographic variables. Univariate ANOVAs were calculated to determine gender differences in IPQ-R subscales and differences between participants who knew someone diagnosed with cancer versus those who did not. While 76% of participants knew someone with cancer, only 5% of the sample engaged in cancer screening. Participants perceived cancer as a serious illness with negative emotional valence. Younger age (r(100)=-.36, p<0.001) and male gender (F(1, 98)=5.22, p=0.01, η2=0.05) were associated with better illness coherence. Males also reported greater personal control (F(1, 98)=5.34, p=0.02, η2=0.05) were associated with better illness coherence. Low screening rates precluded analyses of the relationship between illness representations and cancer screening. Cancer was viewed as a threatening and uncontrollable disease among this sample of educated, middle class Kolkata residents. This view may act as a barrier to seeking cancer screening. Public awareness campaigns aimed at improving understanding of the causes, symptoms and consequences of cancer might reduce misunderstandings and fear, especially among women and older populations, who report less comprehension of cancer.

Cardiomyocyte proliferation contributes to heart growth in young humans.

The human heart is believed to grow by enlargement but not proliferation of cardiomyocytes (heart muscle cells) during postnatal development. However, recent studies have shown that cardiomyocyte proliferation is a mechanism of cardiac growth and regeneration in animals. Combined with evidence for cardiomyocyte turnover in adult humans, this suggests that cardiomyocyte proliferation may play an unrecognized role during the period of developmental heart growth between birth and adolescence. We tested this hypothesis by examining the cellular growth mechanisms of the left ventricle on a set of healthy hearts from humans aged 0-59 y (n = 36). The percentages of cardiomyocytes in mitosis and cytokinesis were highest in infants, decreasing to low levels by 20 y. Although cardiomyocyte mitosis was detectable throughout life, cardiomyocyte cytokinesis was not evident after 20 y. Between the first year and 20 y of life, the number of cardiomyocytes in the left ventricle increased 3.4-fold, which was consistent with our predictions based on measured cardiomyocyte cell cycle activity. Our findings show that cardiomyocyte proliferation contributes to developmental heart growth in young humans. This suggests that children and adolescents may be able to regenerate myocardium, that abnormal cardiomyocyte proliferation may be involved in myocardial diseases that affect this population, and that these diseases might be treatable through stimulation of cardiomyocyte proliferation.