Right-Sizing Technology in the Era of Consumer-Driven Health Care.
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ABSTRACT:
SUBMITTER: Deak E
PROVIDER: S-EPMC7132510 | biostudies-literature | 2017 Aug
REPOSITORIES: biostudies-literature
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Right-Sizing Technology in the Era of Consumer-Driven Health Care.
Deak Eszter E Marlowe Elizabeth M EM
Clinical microbiology newsletter 20170719 15
Technology for modern clinical and public health microbiology laboratories has evolved at an impressive rate over the last two decades. Contemporary diagnostics can rapidly provide powerful data that can impact patient lives and support infectious disease outbreak investigations. At the same time, dramatic changes to health care delivery are putting new pressures on a system that is now focusing on patient-centric, value-driven, convenient care. For laboratories, balancing all these demands in a ...[more]
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Project description:ImportanceCharacteristics of a health care system can facilitate forgoing of health care owing to economic reasons and can influence population health. Whether health insurance deductibles are associated with forgoing of health care in a consumer-driven health care system with universal coverage, such as the Swiss health system, remains to be determined.ObjectiveTo assess the association between insurance plan deductibles and forgoing of health care with consideration of socioeconomic factors.Design, setting, and participantsThis cross-sectional study was conducted in Geneva, Switzerland, using data collected from January 1, 2007, to December 31, 2019. Population-based samples were obtained yearly through random stratified sampling by age and sex of the general population aged 20 to 74 years. Participants were invited to an appointment at 1 of the 3 study sites in Geneva, where they completed a sociodemographic and health questionnaire.ExposuresInsurance plan deductible level.Main outcomes and measuresThe main outcome was forgoing of health care owing to economic reasons. Unadjusted and multivariable Poisson models were used to assess the association between deductible level and forgoing of health care. Differences in forgoing health care across the range of health insurance deductibles or household income levels were quantified using the relative index of inequality (RII).ResultsThe study group included 11 872 participants (5974 [50.3%] male; median age, 48.1 years [interquartile range, 38.7-59.1 years]); 1146 (9.7%) reported forgoing health care. Participants with high-deductible plans reported forgoing health care more frequently than those with low-deductible plans (331 [13.5%] vs 591 [8.7%]). In adjusted analysis, higher-deductible plans were associated with a greater likelihood of forgoing health care (RII, 2.2; 95% CI, 1.7-3.0; P < .001) independently of socioeconomic status, known comorbidities, and cardiovascular risk factors. Deductible level was associated with forgoing of health care among participants younger than 40 years (RII, 2.5; 95% CI, 1.6-4.0; P < .001) and those aged 40 to 64 years (RII, 1.9; 95% CI, 1.3-2.9; P = .002) but not among those older than 65 years (RII, 2.9; 95% CI, 0.8-10.4; P = .11).Conclusions and relevanceIn this cross-sectional study, high insurance plan deductibles were associated with forgoing of health care independent of socioeconomic status and preexisting conditions in a universal consumer-driven health care system with good population outcomes in Switzerland. Uncovering health care system design features that could lead to suboptimal population care may help decision makers improve their current health care system design to achieve better outcomes.
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Project description:Arguments are proposed that researchers using longitudinal data should consider more and less complex statistical model alternatives to their initially chosen techniques in an effort to "right-size" the model to the data at hand. Such model comparisons may alert researchers who use poorly fitting, overly parsimonious models to more complex, better-fitting alternatives and, alternatively, may identify more parsimonious alternatives to overly complex (and perhaps empirically underidentified and/or less powerful) statistical models. A general framework is proposed for considering (often nested) relationships between a variety of psychometric and growth curve models. A 3-step approach is proposed in which models are evaluated based on the number and patterning of variance components prior to selection of better-fitting growth models that explain both mean and variation-covariation patterns. The orthogonal free curve slope intercept (FCSI) growth model is considered a general model that includes, as special cases, many models, including the factor mean (FM) model (McArdle & Epstein, 1987), McDonald's (1967) linearly constrained factor model, hierarchical linear models (HLMs), repeated-measures multivariate analysis of variance (MANOVA), and the linear slope intercept (linearSI) growth model. The FCSI model, in turn, is nested within the Tuckerized factor model. The approach is illustrated by comparing alternative models in a longitudinal study of children's vocabulary and by comparing several candidate parametric growth and chronometric models in a Monte Carlo study.
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Project description:BACKGROUND:Compassion is a vital component to the achievement of positive health outcomes, particularly in mental health care. The rise of digital technologies may influence the delivery of compassionate care, and thus this relationship between compassion and digital health care needs to be better understood. OBJECTIVE:This scoping review aimed to identify existing digital technologies being used by patients and health professionals in the delivery of mental health care, understand how digital technologies are being used in the delivery of compassionate mental health care, and determine the facilitators of and barriers to digital technology use among patients and health professionals in the delivery of compassionate mental health care. METHODS:We conducted this scoping review through a search of Cumulative Index to Nursing and Allied Health Literature, Medical Literature Analysis and Retrieval System Online (MEDLINE), MEDLINE In-Process and EPub Ahead of Print, PsycINFO, and Web of Science for articles published from 1990 to 2019. RESULTS:Of the 4472 articles screened, 37 articles were included for data extraction. Telemedicine was the most widely used technology by mental health professionals. Digital technologies were described as facilitating compassionate care and were classified using a conceptual model to identify each digital intersection with compassionate care. Facilitators of and barriers to providing compassionate care through digital technology were identified, including increased safety for providers, health care professional perceptions and abilities, and the use of picture-in-picture feedback to evaluate social cues. CONCLUSIONS:Implementing digital technology into mental health care can improve the current delivery of compassionate care and create novel ways to provide compassion. However, as this is a new area of study, mental health professionals and organizations alike should be mindful that compassionate human-centered care is maintained in the delivery of digital health care. Future research could develop tools to facilitate and evaluate the enactment of compassion within digital health care.
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