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BackgroundThe use of electronic health records (EHR) in clinical settings is considered pivotal to a patient-centered health care delivery system. However, uncertainty in cost recovery from EHR investments remains a significant concern in primary care practices. ObjectiveGuided by the question of “When implemented in primary care practices, what will be the return on investment (ROI) from an EHR implementation?”, the objectives of this study are two-fold: (1) to assess ROI from EHR in primary care practices and (2) to identify principal factors affecting the realization of positive ROI from EHR. We used a break-even point, that is, the time required to achieve cost recovery from an EHR investment, as an ROI indicator of an EHR investment. MethodsGiven the complexity exhibited by most EHR implementation projects, this study adopted a retrospective mixed-method research approach, particularly a multiphase study design approach. For this study, data were collected from community-based primary care clinics using EHR systems. ResultsWe collected data from 17 primary care clinics using EHR systems. Our data show that the sampled primary care clinics recovered their EHR investments within an average period of 10 months (95% CI 6.2-17.4 months), seeing more patients with an average increase of 27% in the active-patients-to-clinician-FTE (full time equivalent) ratio and an average increase of 10% in the active-patients-to-clinical-support-staff-FTE ratio after an EHR implementation. Our analysis suggests, with a 95% confidence level, that the increase in the number of active patients (P=.006), the increase in the active-patients-to-clinician-FTE ratio (P

Wearable sensing has enabled physiological monitoring in everyday life. Clinically, cardiovascular and respiratory monitoring commonly requires separate devices. However, for feasibility in wearable systems, they are integrated into a single device. Since seismocardiography (SCG) records the motion of the chest wall, it has the potential to monitor both vital signs. The primary application of SCG is cardiovascular monitoring. As a result, its ability to detect respiration has been less defined. This study characterizes how SCG is affected by respiration and consequently, how respiratory metrics can be derived from these effects. The sternal motion of 40 subjects was recorded using an inertial measurement unit with a spirometer for reference. Three scenarios were examined with the subject at rest, holding their breath at peak inhalation, and holding their breath when exhaled. Three main aspects of respiratory modulation were explored: amplitude modulation, frequency modulation, and baseline wandering. The SCG amplitude was observed to be dependent on respiratory volume whereas baseline and frequency modulation were dependent on inhalation phase. All three effects were employed separately in the calculation of respiratory rate. Estimations from baseline wandering, amplitude modulation, and heart rate modulation produced r-squared values of 0.71, 0.44, and 0.66, respectively. The accuracy of tidal volume measurement was limited by a high inter-subject variability. Estimation of the respiratory waveform produced an average r-squared of 0.76 using multivariate linear regression. This demonstrates the potential of SCG as a tool for respiratory monitoring within an integrated, non-invasive cardiorespiratory monitoring system from a single point of contact. [ABSTRACT FROM AUTHOR]

The presence and functionality of [beta]-adrenoceptors ([beta]-ARs) were examined in red (RM) and white muscle (WM) membranes isolated from the rainbow trout Oncorhynchus mykiss. Specific binding assays revealed the presence of a single class of binding sites with similar affinities in both muscle types ([K.sub.d] in nM: 0.14 [+ or -] 0.03 and 0.18 [+ or -] 0.03 for RM and WM, respectively) but with a significantly higher number of binding sites in RM compared with WM ([B.sub.max] in fmol/mg protein: 3.22 [+ or -] 0.11 and 2.60 [+ or -] 0.13, respectively). Selective and nonselective [beta]-adrenergic agonists ([beta]-AAs) and antagonists indicated an atypical [beta]-AR pharmacology. This result may represent a nonmammalian [beta]-AR classification or, more likely, the presence of more than one [beta]-AR subtype in trout muscles with similar affinities that could not be kinetically resolved. Adenylyl cyclase (ACase) assays showed a dose-dependent increase in cAMP production as concentrations of [[beta].sub.2]-AAs increased in both muscle membranes with significantly higher basal cAMP production in RM compared with WM (cAMP production in pmol cAMP*mg [protein.sup.-1]*10 [min.sup.-1]: 24.67 [+ or -] 3.06 and 9.64 [+ or -] 3.45, respectively). The agonist-induced increase in cAMP production was blocked by the [beta]-adrenergic antagonist propranolol, while the ACase activator forskolin increased cAMP production by 7- to 14-fold above basal and ~3-fold above all [beta]-AAs tested. This study demonstrated the presence of atypical [[beta].sub.2]-ARs on RM and WM membranes of trout, suggesting that [[beta].sub.2]-AAs may be a tool to enhance protein accretion through this signaling pathway. [beta]-adrenoceptor; adenylyl cyclase; adenosine 3',5'-cyclic monophosphate; Oncorhynchus mykiss

We present a novel seismocardiography (SCG)-based approach for real-time cardio-respiratory activity measurement called the Autocorrelated Differential Algorithm (ADA). Measurements were performed on ten male subjects in the supine position for three 7-minute-long sets each, corresponding to 14,619 heartbeats. The ADA utilized temporal variations, windowing, and autocorrelation to produce physiological measurements corresponding to heart rate (HR), and left ventricular ejection time, and estimations of respiration rate, volume, and phase. The versatility of the ADA was investigated in two contexts: physical exertion and heart rate variability. The accuracy of HR measurements at a sampling frequency of 200 Hz resulted in a correlation coefficient ($r^{2}$) of 0.9808 when compared with a manual annotation of all datasets. Its reproducibility was tested on externally obtained SCG and electrocardiography datasets, which produced an $r^{2}$ of 0.8224. The accuracy and computational time were also characterized by different sampling frequencies to quantify performance. The recommended sampling frequency is 200 Hz corresponding to a computation time of 0.05 s per instantaneous measurement using a standard desktop computer. The ADA delivered real-time SCG measurements with a refresh rate that was dependent on the computational time per measurement, which could be decreased by lowering the sampling frequency. The presented algorithm offers a novel tool toward real-time physiological monitoring in clinical and everyday scenarios. [ABSTRACT FROM AUTHOR]

The characteristics of hepatic β2-adrenoceptors (AR) were examined in rainbow trout (Oncorhynchus mykiss) chased once per day to exhaustion for up to 7 days or fed the repartitioning agents clenbuterol (CLEN) or ractopamine (RACT) that function in mammals as β-agonists. A one-day chase and feeding the CLEN for 37 days resulted in a significant 27% and 33% decrease, respectively, in the number of CGP-binding sites (Bmax) with no significant change in affinity (Kd) of hepatic β2-ARs. Despite the significant decrease in β2-AR numbers with CLEN feeding, no significant differences were found for either β2-AR mRNA levels or adenylyl cyclase (ACase) activities. In addition, CLEN displayed only partial agonist activities as it was found to be more effective at blocking isoproterenol-stimulated cAMP production in isolated hepatocytes than stimulating cAMP production. The small affects of RACT may be related to its low active stereoisomer content and low affinity for the trout β2-AR. Agonist regulation of the trout hepatic β2-ARs may involve down-regulation of the receptors without affecting responsiveness. [Copyright &y& Elsevier]

The presence and functionality of β-adrenoceptors (β-ARs) were examined in red (RM) and white muscle (WM) membranes isolated from the rainbow trout Oncorhynchus mykiss. Specific binding assays revealed the presence of a single class of binding sites with similar affinities in both muscle types (K[sub d] in nM: 0.14 ± 0.03 and 0.18 ± 0.03 for RM and WM, respectively) but with a significantly higher number of binding sites in RM compared with WM (B[sub max] in fmol/mg protein: 3.22 ± 0.11 and 2.60 ± 0.13. respectively). Selective and nonselective β-adrenergic agonists (β-AAs) and antagonists indicated an atypical β-AR pharmacology. This result may represent a nonmammalian β-AR classification or, more likely, the presence of more than one β-AR subtype in trout muscles with similar affinities that could not be kinetically resolved Adenylyl cyclase (ACase) assays showed a dose-dependent increase in cAMP production as concentrations of β[sub 2]-AAs increased in both muscle membranes with significantly higher basal cAMP production in RM compared with WM (cAMP production in pmol cAMP. mg protein. · 10 min[sup -1]: 24.67 ± 3.06 and 9.64 ± 3.45, respectively). The agonist-induced increase in cAMP production was blocked by the β-adrenergic antagonist propranolol, while the ACase activator forskolin increased cAMP production by 7- to 14-fold above basal and ∼3-fold above all β-AAs tested. This study demonstrated the presence of atypical β[sub 2]-ARs on RM and WM membranes of trout, suggesting that β[sub 2]-AAs may be a tool to enhance protein accretion through this signaling pathway. [ABSTRACT FROM AUTHOR]

Cardiography is an indispensable element of health care. However, the accessibility of at-home cardiac monitoring is limited by device complexity, accuracy, and cost. We have developed a real-time algorithm for heart rate monitoring and beat detection implemented in a custom-built, affordable system. These measurements were processed from seismocardiography (SCG) and gyrocardiography (GCG) signals recorded at the sternum, with concurrent electrocardiography (ECG) used as a reference. Our system demonstrated the feasibility of non-invasive electro-mechanical cardiac monitoring on supine, stationary subjects at a cost of $100, and with the SCG–GCG and ECG algorithms decoupled as standalone measurements. Testing was performed on 25 subjects in the supine position when relaxed, and when recovering from physical exercise, to record 23,984 cardiac cycles at heart rates in the range of 36–140 bpm. The correlation between the two measurements had r2 coefficients of 0.9783 and 0.9982 for normal (averaged) and instantaneous (beat identification) heart rates, respectively. At a sampling frequency of 250 Hz, the average computational time required was 0.088 s per measurement cycle, indicating the maximum refresh rate. A combined SCG and GCG measurement was found to improve accuracy due to fundamentally different noise rejection criteria in the mutually orthogonal signals. The speed, accuracy, and simplicity of our system validated its potential as a real-time, non-invasive, and affordable solution for outpatient cardiac monitoring in situations with negligible motion artifact. [ABSTRACT FROM AUTHOR]