Reorganizing adult critical care delivery: The role of regionalization, telemedicine, and community outreach

CRISMA (Clinical Research, Investigation, and Systems Modeling of Acute Illness) Laboratory, Department of Critical Care Medicine, University of Pittsburgh, 3550 Terrace Street, Pittsburgh, PA 15261, USA.
American Journal of Respiratory and Critical Care Medicine (Impact Factor: 13). 03/2010; 181(11):1164-9. DOI: 10.1164/rccm.200909-1441CP
Source: PubMed


Variation in the quality of critical care services across hospitals coupled with an emerging workforce crisis necessitates system-level change in the organization of intensive care. In this review, we evaluate three alternative organizational models that may expand access to high-quality critical care: tiered regionalization, intensive care unit telemedicine, and quality improvement through regional outreach. These models share a potential to increase survival and reduce costs. Yet there are also major barriers to implementation, including the lack of a strong evidence base and the need for significant upfront financial investment. Reorganization of intensive care will also require the support of all involved stakeholders: patients and their families, critical care practitioners, administrative and public health professionals, and policy makers. To varying degrees these models require a central authority to implement and regulate the system, as well as specific legislation, investment in information technology, and financial incentives for providers. The existing evidence does not strongly support exclusive use of a particular model, and creation of a hybrid model that integrates the three complementary approaches is a practical option. A potential framework for implementation involves triage guidelines developed by professional societies leading to demonstration projects and national legislation in support of optimal systems. Additional research is needed to determine the comparative effectiveness and cost implications of these approaches, with a goal of best matching high-quality critical care to patients' needs and professional preferences at the hospital, regional, and national level.

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    • "Effective demand management aims to improve utilization of available bed capacity while optimizing patient and staff outcomes [3] . An established demand management strategy is coordinated networking between hospitals for the referral of critically ill patients to access definitive care [4] [5] . As a result organizational transformation in the form of regionalization, or consolidation, of ICU services is being adopted across clinical networks and within individual hospitals [6] . "
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    ABSTRACT: Objective: To determine an appropriate survey instrument to evaluate the impact of organizational structures on the work environment of intensive care nurses. Background: Internationally the demand for intensive care is increasing. Solely increasing bed capacity is not sustainable. Large capacity multi-specialty Intensive Care Units are emerging as the preferred organizational model with benefits resulting from optimizing operational synergies and economies of scale. The impact of this organizational transition on intensive care nurses is not well understood. An appropriate survey instrument for intensive care nurses is required. Design: Integrative literature review. Data Sources: CINAHL, PubMed, EMBASE and OVID Nursing databases searched for studies published between 2005 and 2013. Review methods: An integrative review and quality assessment of the studies was undertaken to select nurse outcome measures associated with organizational structures across a range of acute and critical care settings. Congruence between nurse outcome measures and nurse survey instruments tested in the literature was assessed to select instruments for further psychometric evaluation. Results: Thirty-one cross sectional quantitative studies, from fourteen countries, were reviewed. Twenty one nurse outcome measures associated with organizational factors were identified and a total of twenty five survey instruments used in the studies reviewed. Assessment of congruence and psychometric properties determined that a combination of two instruments is required to comprehensively assess the organizational environment of nurses working in intensive care units. Conclusion: The environment of nurses working in intensive care is effectively evaluated with an instrument that combines subscales from the Practice Environment Scale-Nurse Work Index and Maslach’s Burnout Inventory.
    12/2014; 3(6):143. DOI:10.5430/jha.v3n6p143
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    • "Telemedicine, broadly defined as the exchange of medical information via electronic communication, may help to fill gaps in intensivist coverage and give all patients access to specialty care 24 hours per day, 7 days per week [6]. It allows real-time exchange of clinical data and direct interaction among critical care providers across long distances and provides decision support to underserviced rural areas, small hospitals without access to intensivists [7], and large hospitals with low-intensity physician-staffing models or nocturnal physician shortages. Some applications also contain decision-support tools to facilitate implementation of best practices and alarms to alert providers to sudden changes in patient status [8-12]. "
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    ABSTRACT: Introduction Telemedicine extends intensivists' reach to critically ill patients cared for by other physicians. Our objective was to evaluate the impact of telemedicine on patients' outcomes. Methods We searched electronic databases through April 2012, bibliographies of included trials, and indexes and conference proceedings in two journals (2001 to 2012). We selected controlled trials or observational studies of critically ill adults or children, examining the effects of telemedicine on mortality. Two authors independently selected studies and extracted data on outcomes (mortality and length of stay in the intensive care unit (ICU) and hospital) and methodologic quality. We used random-effects meta-analytic models unadjusted for case mix or cluster effects and quantified between-study heterogeneity by using I2 (the percentage of total variability across studies attributable to heterogeneity rather than to chance). Results Of 865 citations, 11 observational studies met selection criteria. Overall quality was moderate (mean score on Newcastle-Ottawa scale, 5.1/9; range, 3 to 9). Meta-analyses showed that telemedicine, compared with standard care, is associated with lower ICU mortality (risk ratio (RR) 0.79; 95% confidence interval (CI), 0.65 to 0.96; nine studies, n = 23,526; I2 = 70%) and hospital mortality (RR, 0.83; 95% CI, 0.73 to 0.94; nine studies, n = 47,943; I2 = 72%). Interventions with continuous patient-data monitoring, with or without alerts, reduced ICU mortality (RR, 0.78; 95% CI, 0.64 to 0.95; six studies, n = 21,384; I2 = 74%) versus those with remote intensivist consultation only (RR, 0.64; 95% CI, 0.20 to 2.07; three studies, n = 2,142; I2 = 71%), but effects were statistically similar (interaction P = 0.74). Effects were also similar in higher (RR, 0.83; 95% CI, 0.68 to 1.02) versus lower (RR, 0.69; 95% CI, 0.40 to 1.19; interaction, P = 0.53) quality studies. Reductions in ICU and hospital length of stay were statistically significant (weighted mean difference (telemedicine-control), -0.62 days; 95% CI, -1.21 to -0.04 days and -1.26 days; 95% CI, -2.49 to -0.03 days, respectively; I2 > 90% for both). Conclusions Telemedicine was associated with lower ICU and hospital mortality among critically ill patients, although effects varied among studies and may be overestimated in nonrandomized designs. The optimal telemedicine technology configuration and dose tailored to ICU organization and case mix remain unclear.
    Critical care (London, England) 07/2012; 16(4):R127. DOI:10.1186/cc11429 · 4.48 Impact Factor
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    • "In other models dedicated call centers or point of care act as an intermediary between hospital/heath care professional and patients. Many of the solutions available today on the market follow the above-mentioned model and call center services or point of care are used by the patients just as a complement to the hospital-centerd healthcare services [12] [13] [14] [15]. In the more advanced Personal Health Systems [16] [17] [18] [19] [20] model focused on the empowerment, the ownership of the care service is fully taken by the individual. "
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    ABSTRACT: a b s t r a c t Developments in computational techniques including clinical decision support systems, information pro-cessing, wireless communication and data mining hold new premises in Personal Health Systems. Perva-sive Healthcare system architecture finds today an effective application and represents in perspective a real technological breakthrough promoting a paradigm shift from diagnosis and treatment of patients based on symptoms to diagnosis and treatment based on risk assessment. Such architectures must be able to collect and manage a large quantity of data supporting the physicians in their decision process through a continuous pervasive remote monitoring model aimed to enhance the understanding of the dynamic disease evolution and personal risk. In this work an automatic simple, compact, wireless, per-sonalized and cost efficient pervasive architecture for the evaluation of the stress state of individual sub-jects suitable for prolonged stress monitoring during normal activity is described. A novel integrated processing approach based on an autoregressive model, artificial neural networks and fuzzy logic mod-eling allows stress conditions to be automatically identified with a mobile setting analysing features of the electrocardiographic signals and human motion. The performances of the reported architecture were assessed in terms of classification of stress conditions.
    Computer Communications 06/2012; 35(11):1296-1305. DOI:10.1016/j.comcom.2011.11.015 · 1.70 Impact Factor
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