Z-WAVE INCLUSION 1. Install batteries and bring the 4-in-1 sensor within direct range of your Z-Wave gateway controller 2. Put your Z-Wave controller in inclusion mode 3. Press and release the Z-Wave button TWICE quickly 4. A new 4-in-1 sensor should appear on your controller's device list Troubleshooting Tips If you are unable to include the Z-Wave sensor to your controller, please try one of the following: Bring the 4-in-1 sensor closer to your ZWave controller Press and release the Z-Wave button quickly several times once you put the controller in the inclusion mode to ensure the command has gone through Put your controller in EXCLUSION mode and press and release the Z-Wave button TWICE quickly, then try adding it to your network again Make sure you are clicking the Z-Wave button located in the small opening on the bottom of the sensor and NOT the tamper switch located above the battery slot Z-WAVE EXCLUSION 1. Bring the 4-in-1 sensor within direct range of your Z-Wave gateway controller 2. Put your Z-Wave controller in exclusion mode 3. Press and release the Z-Wave button TWICE quickly 4. The device should disappear from your controller's device list. The LED indicator will flash 3 times when you take the batteries out and put them back in to indicate the device has been successfully excluded. Please repeat the process following all steps carefully if the LED indicator blinks only once when you re-insert the batteries.

User's Manual for

Objectives To systematically review the literature on quality indicators (QIs) for evaluating trauma care, identify QIs, map their definitions, and examine the evidence base in support of the QIs. Data Sources We searched MEDLINE, EMBASE, CINAHL, Cochrane Database of Systematic Reviews, Cochrane Database of Abstracts of Reviews of Effects, and Cochrane Central Register of Controlled Trials from the earliest available date through January 14, 2009. To increase the sensitivity of the search, we also searched the grey literature and select journals by hand, reviewed reference lists to identify additional studies, and contacted experts in the field. Study Selection and Data Extraction We selected all articles that identified or proposed 1 or more QIs to evaluate the quality of care delivered to patients with major traumatic injuries. Minimum inclusion criteria were a description of 1 or more QIs designed to evaluate patients with major traumatic injuries (defined as multisystem injuries resulting in hospitalization or death) and focused on prehospital care, hospital care, posthospital care, or secondary injury prevention. Data Synthesis The literature search identified 6869 citations. Review of abstracts led to the retrieval of 538 full-text articles for assessment, of which 192 articles were selected for review. Of these, 128 (66.7%) articles were original research, predominantly trauma database case series (57 [29.7%]) and cohort studies (55 [28.6%]), whereas 37 (19.3%) were narrative reviews and 8 (4.2%) were guidelines. A total of 1572 QIs in trauma care were identified and classified into 8 categories: non-American College of Surgeons Committee on Trauma (ACS-COT) audit filters (42.0%), ACS-COT audit filters (19.1%), patient safety indicators (13.2%), trauma center/system criteria (10.2%), indicators measuring or benchmarking outcomes of care (7.4%), peer review (5.5%), general audit measures (1.8%), and guideline availability or adherence (0.8%). Measures of prehospital and hospital processes (60.4%) and outcomes (22.8%) were the most common QIs identified. Posthospital and secondary injury prevention QIs accounted for less than 5% of QIs. Conclusions Many QIs for evaluating the quality of trauma care have been proposed, but the evidence to support these indicators is not strong. Practical recommendations to select QIs to measure the quality of trauma care will require systematic reviews of identified candidate indicators and empirical studies to fill the knowledge gaps for postacute QIs.

/pdf/quality-indicators-for-evaluating-trauma-care-a-scoping-4hrc1feh3e.pdf

Quality indicators for evaluating trauma care: a scoping review.

The number of requests to pre-hospital emergency medical services (PEMS) has increased in Europe over the last 20 years, but epidemiology of PEMS interventions has little be investigated. The aim of this analysis was to describe time trends of PEMS activity in a region of western Switzerland. Use of data routinely and prospectively collected for PEMS intervention in the Canton of Vaud, Switzerland, from 2001 to 2010. This Swiss Canton comprises approximately 10% of the whole Swiss population. We observed a 40% increase in the number of requests to PEMS between 2001 and 2010. The overall rate of requests was 35/1000 inhabitants for ambulance services and 10/1000 for medical interventions (SMUR), with the highest rate among people aged ≥ 80. Most frequent reasons for the intervention were related to medical problems, predominantly unconsciousness, chest pain respiratory distress, or cardiac arrest, whereas severe trauma interventions decreased over time. Overall, 89% were alive after 48 h. The survival rate after 48 h increased regularly for cardiac arrest or myocardial infarction. Routine prospective data collection of prehospital emergency interventions and monitoring of activity was feasible over time. The results we found add to the understanding of determinants of PEMS use and need to be considered to plan use of emergency health services in the near future. More comprehensive analysis of the quality of services and patient safety supported by indicators are also required, which might help to develop prehospital emergency services and new processes of care.

/pdf/trends-of-pre-hospital-emergency-medical-services-activity-l5qvjvec69.pdf

Trends of pre-hospital emergency medical services activity over 10 years: a population-based registry analysis

Background
Physician-staffed pre-hospital units are employed in many Western emergency medical services (EMS) systems. Although these services usually integrate well within their EMS, little is known about the quality of care delivered, the precision of dispatch, and whether the services deliver a higher quality of care to pre-hospital patients. There is no common data set collected to document the activity of physician pre-hospital activity which makes shared research efforts difficult. The aim of this study was to develop a core data set for routine documentation and reporting in physician-staffed pre-hospital services in Europe.

/pdf/a-consensus-based-template-for-documenting-and-reporting-in-4ppdkkp7b7.pdf

A consensus-based template for documenting and reporting in physician-staffed pre-hospital services

The evolution and current state of emergency care in Ghana

Emergency medical services (EMS) systems, and prehospital care are difficult to evaluate. Accordingly, the true efficacy and value of such systems are difficult to determine. The multitude of variations and combinations of involved factors makes standardisation and comparison difficult, and universal indicators are hard to develop. Various attempts have been made to determine valid indicators of effectiveness, but there has been little success. Prehospital care has been seen by some as a single entity. As a result, experience from well resourced first world trauma centres has been taken, by many, to be applicable to all prehospital situations. This article attempts to assist in the development of valid EMS indicators of performance and effectiveness by categorising prehospital scenarios into a classification reflecting the reality of their conditions of practice.

https://emj.bmj.com/content/emermed/20/2/188.full.pdf

C A Benn

Papers

Evaluation of emergency medical services systems: a classification to assist in determination of indicators