Medication error in nursing malaysia day,diabetes foot care knowledge questionnaire example,can erectile dysfunction due to diabetes be cured permanently - Easy Way

ABSTRACTAn estimated 300 million radiologic procedures are conducted per year in the United States. The Savvy™ mobile medication workstation from Omnicell should not be confused with ordinary hospital medication carts. This fully integrated solution features Omnicell's Anywhere RN™ software application and a wireless, medical-grade mobile workstation. The Anywhere RN software allows nurses to order medications in quieter areas away from interruptions, assisting in preventing medication errors.
Savvy provides secure transport of medications from the ADC to the point-of-care, creating a critical layer of accountability and addressing ISMP recommendations for safe transport of medications.
Nurses can place all needed patient medications for a medication pass into patient-assigned locking drawers and then move from room to room, instead of returning to the ADC between each patient.
Reduces trips back to the cabinet to record medication waste, which can now be done remotely. Savvy seamlessly integrates the Omnicell ADC, mobile workstation, and bedside point-of-care (BPOC) systems during the medication administration process, to enable a closed-loop process for tracking medication accountability. Savvy is part of the Unity platform of solutions that share a single database, helping to eliminate redundant data entry that can lead to errors.
Eliminates the manual process of labeling drawers: patient-specific drawers (up to 12) are automatically assigned via the software. Features independently locking drawers, which minimizes the risk of administering the wrong medication to a patient.
Omnicell’s unique guiding lights technology helps nurses quickly identify the drawer that has been unlocked, adding speed and convenience to the medication administration process.
Lithium-ion hot-swap battery system (2 batteries) provides up to 18 hours of continuous run time.
Battery charging station conveniently charges depleted battery without having to plug the Savvy unit into a power outlet. Nurses can focus on patients without worrying about running out of power at a critical time.
Nurses help to ensure patient safety, which includes preventing falls and fall related injuries.
Nurses help ensure patient safety, including prevention of falls and fall related injuries. Fall-related injuries are a serious health issue for the aged population (Centers for Disease Control and Prevention [CDC],2007).
In 1995, the American Nurses Association (ANA) Board of Directors commissioned the development of nursing quality indicators that link nursing care and patient outcomes. Health care organizations rely on incident reports for counting the frequency of falls and collecting fall-related data.
Many facilities (VA and non-VA) use an incident report form for falls, specifically designed to collect data based on evidence about factors contributing to fall occurrences (Elkins et al., 2004).
When analyzing effectiveness of fall prevention programs, rates of both fall incidence and severity of injury should be included. This fall rate accounts for changes in patient census so that fall rates can be adjusted for census and then compared across clinical units. Injury analysis by severity levels enables clinical and administrative staff to profile both vulnerability of their patients and effectiveness of patient safety programs.
Increases in the length of time between major injuries are another indicator of the effectiveness of fall reduction programs. In addition to tracking injury and injury severity rates, another performance indicator is the number of days between major injuries.
Clinicians, administrators, and risk managers collaborate to set realistic target goals for reducing rates of falls and fall-related injuries through implementation of patient safety interventions. The National Database of Nursing Quality Indicators® (NDNQI) enables comparison of fall rates and other nurse sensitive indicators for enrolled acute care organizations (American Nurses Association, 2004-2006).
Visual presentation of falls data is an effective method for summarizing and presenting outcomes and trends over time. The control chart provides visual cues that help the viewer understand how the data relate to the process and outcomes of patient care. For example, the control chart in Figure 2 displays the monthly fall rate on one unit in the facility where a pilot fall prevention program was established. During this time the average fall rate dropped to 4.49 falls per 1000 -BDOC on the pilot unit, creating a new center line for the average fall rate. These charts provide nursing staff with visual displays of data indicating the results of nursing and interdisciplinary care. During the assessment phase, monthly fall rate data are entered into the control chart, performance continues to be monitored, and the chart is annotated to determine when the initiatives are introduced relative to trends (within and outside of the control limits). Following is an exemplar of development and implementation of a fall prevention program, using control charts to evaluate its effectiveness and share the outcomes with staff. Prior to the fall prevention program, a comprehensive, coordinated approach to fall prevention did not exist with each unit working in isolation on its fall prevention program. To address these problems, a Process Action Team (PAT) was formed and conducted a comprehensive data analysis to assess the current nature and scope of falls occurring on the long term care units. The falls workgroup was immediately established under the direction of the PAT, and developed a strategic plan to implement and evaluate the impact of the above actions.
Progress made during each phase of deployment and system change was celebrated through a recognition program.
Lastly, a key intervention was implemented to address communication gaps in the information collected about a fall and reporting the fall occurrence among disciplines. As a result of this sheet, anyone on the unit can visually see a patient who fell, and where the staff are in the communication process about the fall occurrence and revising the plan of care to prevent a repeat fall. When using control charts to evaluate the effectiveness of a particular program, the team may want to develop two separate charts for each phase of a process, each with its own mean and upper and lower limits plotted.
The team achieved its patient safety goals by reducing the residents' fall rate and severity of fall-related injury. After this site's participation, the staff's interventions ultimately led to decreased falls and related injuries. When this site first enrolled in the National VHA Falls Quality Improvement Project, quality managers displayed fall rates and injury rates using line graphs, reporting statistics for individual units and for the entire veterans' home. Thus, communication systems were put in place for signage to identify patients at risk for falls, shift reports to communicate patient risk status, and revised charts with more detailed analysis of falls and fall-injury rates. Committed to communication, the quality manager reported the G-Chart data are shared at weekly team meetings. Protecting patients from falls and fall-related injuries requires shared responsibility among health care providers, administrators, and risk managers. The Nursing Home Care Unit, a 160 bed nursing home, highlights implementation and ongoing assessment phases.
Figures 1-5 reflect non-identifiable aggregate data only and are used courtesy of the VAMC at Bath, New York. Patricia Quigley, PhD, MPH, ARNP, CRRN, FAAN, is currently Deputy Director of the VISN 8 Patient Safety Center of Inquiry at the Tampa VA, and assists with oversight for the Clinical Falls Team. Julia Neily, RN, MS, MPH works for the Veterans Health Administration (VHA) National Center for Patient Safety, Field Office in White River Junction, Vermont. Mary E Watson, MSN, APRN.BC has been employed at the Central Arkansas Veterans Healthcare System for 19 years. Department of Veterans Affairs, Veterans Health Administration (VHA) National Center for Patient Safety.
Join the South Park boys on Japan's most ridiculous, humiliating, and totally twisted game show! Jump, jump, jump to the top, top, top with Doodle Jump, the #1 smartphone game of all time! South Park 10South Park 10: The Game is based on some of the most memorable moments from the first 10 seasons. MTV Star FactoryCreate the idols of tomorrow with MTV Star Factory, the game that lets you be the music mogul!
Tiki Towers 2Swing into action with an all-new set of primate puzzles in the fantastic sequel to the award-winning hit. In cardiac catheterization laboratories, radiology, and other diagnostic departments, medications such as contrast media are administered, rates are adjusted for intravenous (IV) fluids, and IV access lines are flushed. Savvy streamlines the medication administration process and provides safe and secure transportation of medications from the automated dispensing cabinet (ADC) to the patient's bedside.
Because clinicians can remotely select patient medications quickly and securely, from any location at any time, their transaction time at the ADC is reduced, providing more time for direct patient care. Nurses can use the Savvy mobile medication workstation, which integrates Omnicell's Anywhere RN software, to request, retrieve, and deliver all of their patients' medications for a medication pass with a single trip to the cabinet, without compromising on security.
The aging Veteran population, like the general population, is at risk for falls and fall related injuries whether at home, in hospitals or in long term care facilities. Nurses make a major contribution to patient safety by assessing fall risk and designing patient-specific fall prevention interventions that reduce risk and prevent falls and fall-related injury. Patient injury rate, noted to be most often caused by falls, was promoted as a nurse sensitive indicator, a measure of quality that links patient outcomes with availability and quality of professional nursing services (ANA, 1995). When a fall occurs in a health care organization, an incident report is completed to record the occurrence and circumstances surrounding a fall. For example, these data might include time of day, location, activity, orthostasis, and incontinence.
Each rate is needed to monitor the effectiveness of fall prevention interventions for a specific population in a specific clinical setting. For example, if 80% of patients who sustain lateral falls fracture their hips, one would suspect a large prevalence of osteoporosis.
Once systems are developed for fall rate tracking and internal comparison, organizations can both identify trends and compare rates to those from national databases. The Uniform Data System for Medical RehabilitationSM (UDSMR) for acute rehabilitation has a quality improvement program to analyze and report inpatients by demographic profile (age, gender, diagnosis) who fall once or more than once during their length of stay. Control charts are a specific kind of run chart intended to assess the amount of variation within a specified measurement range referred to as upper and lower limits of performance and quality control (Wheeler, 2000). An interdisciplinary fall quality improvement team participated in individualized patient fall prevention care planning and fall-rate reporting. Next, new upper and lower control limits were calculated that reduced the amount of variation around the mean.
All parties, nursing staff, administration and risk management, monitor for the desired effects for improved patient safety. For example, using the graph may reveal that a high fall rate in a particular month was related a higher census of patients with stroke on the unit. The program was developed for three long term care units representing 160 beds in a rural 400-bed Veterans Administration Medical Center that provides acute medicine, psychiatry, intermediate medicine, and long term care. Nursing staff assessed patients' risk for falling with a "home grown" risk scale, the incident reporting system was cumbersome and lengthy, and periodic audits suggested that falls were under reported. The team members analyzed medical record data related to the location, severity, time of day, and frequency of falls, and identified residents with multiple falls. For implementation and evaluation, the workgroup used the Plan–Do-Study-Act (PDSA) cycle of planned change (Langley, Nolan, Nolan, Norman & Provost, 1996). Additionally, interdisciplinary environmental rounds were implemented for patient safety and fall prevention.
Thus, the workgroup's successes were an integral part of the medical center’s staff recognition program. Since these fall related information are integral part of the fall prevention program, a unit-based fall data and communication tracking sheet (Figure 4) was developed to monitor fall specific data, and is available to all providers directly responsible for the care of the residents.

This sheet visually displays fall occurrences for nurses and physicians on a unit, and any staff member can easily view the unit’s most recent falls. The first control chart (Figure 2) depicts the "implementation" phase of the previous mentioned key interventions and initiatives where the PDSA cycles were developed and the "ongoing assessment" phase in which analysis and evaluation occurs on the pilot unit. This accomplishment is even more significant because it was achieved while concurrently eliminating use of restraints as a fall prevention measure (Figure 1). This exemplar is included to demonstrate how units can expand data analysis of fall prevention programs beyond fall rates. In 2001, a nurse manager, Director of Nursing Services, and quality manager from the organization participated in the national VHA multi-facility quality improvement project, designed to reduce falls and fall-related injuries among inpatients.
The injury rate was calculated by aggregating all injuries, without differentiation according to severity. According to the Joint Commission International Center for Patient Safety (2006), communication issues were the leading root cause of errors reported between 1995-2004, as well as the sentinel events reported in 2005 (Angood, 2006). Realizing that their long term care veteran population was all high risk for falls, they decided to increase focus on injury prevention, protecting veterans from falls and injury.
The horizontal axis marks each serious injury over a three year period (18 injuries, as indicated on the X axis); the vertical axis displays number of days (0-350 days).
Yet, data analysis using only general fall rates lacks specificity needed to profile effectiveness of fall risk reduction programs and injury prevention methods. This material is the result of work supported with resources and the use of facilities at the VISN 8 Patient Safety Center, Tampa, Fl., and the Field Office of the Veterans Affairs National Center for Patient Safety and the Veterans Affairs Medical Center in White River Junction, Vermont.
MD, Co-Director, VA National Quality Scholars Fellowship Program developed original template for this g-chart.
She has an adjunct faculty appointment at the University of South Florida, College of Nursing. She has worked for the VHA for over 21 years and she has a special interest in fall prevention. She has been functioning in the role of Patient Safety Practitioner since 2000 managing the Fall Prevention Program for a 2 division facility with a total of 550 beds. Wright BSN, RNC (retired) has over 20 years experience in long term care at the Missouri Veterans Home in Mt. She has functioned as an ICU Nurse, Risk Manager, and presently as the Performance Manager.
Swipe your finger across the screen to slash them!TRAINING NEEDS ANALYSIS FORMATAnd develop your no go to help you have.
In addition to specific medications that are used in radiology, high-alert medications such as IV sedatives, vasopressors, and blood coagulation modifiers are given in this setting. Nurses are leading practice innovations to systematically assess patients’ risk for falls and implement population based prevention interventions. Falls have been linked to nurse staffing patterns and thus, some falls are preventable (Potter, Barr, McSweeney, & Sledge 2003). Fractures are the major category of injuries produced by falls with 87% of all fractures in older adults resulting from falls (Magaziner et al., 2000). Reports from the CDC (2005) note that fall-related deaths are higher among men than among women and that the incidence of fall-related injuries in the aging U.S. The ANA asserted nurses' responsibility to assess patients' risk for falls and injury, design and implement risk reduction care plans, and evaluate effectiveness of clinical fall prevention programs. Repeat fallers may account for a large percentage of falls within a single clinical unit of an organization.
If one unit exceeds other units on their monthly fall rates and has higher injury rates, one would target that unit for evaluation and intervention. The Minimum Data Set Resident Assessment Instrument (MDS RAI) (Centers for Medicare and Medicaid, 2006 is required data that certified Medicare or Medicaid facilities must submit to the Centers for Medicare and Medicaid Services (CMS) for certification as a Medicare or Medicaid nursing provider, and for reimbursement. Their usefulness in analyzing falls data is enhanced by the ability to annotate the chart with narrative comments on the graph about when and what actions were implemented to reduce patient falls. They can also be used to assess process measures, such as percent of staff trained in fall prevention. A control chart used for fall rates could include the fall rate (number of falls per 1000 bed days of care) plotted by month for the unit.
The center line (dark solid line) is the mean or average of all the data points previously collected and averaged (Carey & Lloyd). Discussions were held monthly and results of continuous monitoring of number of days without a fall were posted on the unit During the fall prevention program implementation phase, the mean fall rate was 9.75 falls per 1000 bed days of care (BDOC), as portrayed by the center line in the chart.
By viewing the control chart, staff members of the pilot unit were able to visualize the affect of the initiatives that were implemented.
In contrast, the graph may reveal a lower fall rate over months after routine toileting rounds were implemented by the nursing staff; noting the start of the toileting program on the control chart can help analyze changes in fall rates over time. The nursing staff working in an interdisciplinary team lowered the average fall rate by 54% on the pilot unit (Figure 2) and 27% on all three units combined during the implementation phase (Figure 3). This four-part, action-oriented cycle for improvement enables a group to examine barriers to and facilitators of an intervention and assess its outcome before moving to the next step of an improvement plan. The environmental rounds involved staff members from throughout the facility conducting unit surveys with a goal to reduce environmental hazards and provide lessons learned as a part of staff education. Another key intervention, medication reviews, were initiated to heighten the awareness of side effects that may increase fall risk and are now done routinely for patients with frequent falls. This new process is considered an administrative intervention to fill gaps in the fall prevention program, and thus can be tracked for impact on the fall prevention program. Also staff can easily view a resident who experienced multiple falls and track when all elements of the post fall care plan were completed. The team has since used falls data to internally compare ongoing progress in patient safety. As stated in the introduction, fall-related injuries have serious consequences that can include loss of function or death.
Thirty-seven teams from VHA hospitals, Veterans nursing homes and one private facility completed an 8-month facilitated quality improvement project. At this medical center, results of a quarterly root cause analysis examining the root causes about why patients fell, revealed that effective communication (handoff, incident reporting, post fall assessment and data analysis) was a contributing problem. To support this focus, all staff in the long term care facility was educated about fall risks, risks for injury, communication systems and the data reporting methods. As shown in the chart, serious injury #1 occurred about five days after the program started, and serious injury #2 was about three days following #1.
A chart with a continuing upward line depicts ongoing increases in injury-free days, a desired outcome.
Administration and quality management wanted to recognize staff for their efforts and successes. The exemplars of data management, analysis, and reporting for systematic analysis of patient, unit and organizational factors illustrated vital components of program evaluation needed for understanding the effectiveness of patient safety programs surrounding falls.
The views expressed in the article do not necessarily represent the views of the Department of Veterans Affairs (DVA) or of the United States (US) Government. She lead the facility falls workgroup that successfully participated in the VA's collaborative to reduce falls and injuries due to falls. Identifying nurse staffing and patient outcome relationships: A guide for change in care delivery. Nearly 1,000 event reports submitted to the Pennsylvania Patient Safety Authority specifically mentioned medication errors that occurred in care areas providing radiologic services.
To determine the effectiveness of programs, data can be analyzed using a variety of statistical measures to determine program impacts. Knowledge of fall prevention program deployment and evaluation using statistical analysis can help nurses design and test effectiveness of fall prevention programs. Fall rates for residents of long-term care facilities are almost three times higher than for residents living in homes, and more frequently result in fracture, laceration, or the need for acute hospital care (Eakman et al., 2002). Thus, we recommend a sub-analysis of the fall data, to determine what percent of the falls are second, third, fourth or more falls. Of the 80 falls, 5 resulted in a minor injury such as an abrasion, hematoma not requiring medical attention, 3 falls resulted in a major injury, such as a hip fracture, and the remainder resulted in no injury . For example, fall rates for acute care units should be compared with those for other acute care units, those for an organization's dementia populations with similar populations, and so on. These data must be recorded, encoded and transmitted to CMS, or the must be completed for all residents The MDS data are collected within 14 days of admission and quarterly, recording if a resident fell during the assessment interval. This chart helps to put the data display into context for the viewer, such as the staff nurses on the unit, (Wheeler, 2000).
The control limits are determined through statistical methods for calculation standard deviations (3 standard deviations) around the mean. Before implementing any new intervention on a large scale, a small scale test of changes enables a workgroup to test one action at a time, and modify the intervention to fit the environment at the unit level. This type of information complements a control chart, because this sheet provides information about the single fall, whereas a control chart uses averaged data about monthly fall rates.
The chart also demonstrates acceptable fall rates being sustained over time (46 months), (Figure 5).
The first two steps for an injury tracking system are to define types of injuries and stratify severity of injury.
This method of reporting and analyzing aggregated data did not allow for evaluation of trends according to injury severity. Therefore their interdisciplinary falls quality improvement team agreed that strategies were needed to improve effective and detailed communication among providers in efforts to improving their fall prevention program (Neily et al., 2003).
The largest interval was between serious injuries #13 and #14, a difference of about 330 days.
These exemplars have results that are meaningful to patients, clinicians, administrators and policy makers. Quigley is nationally known for her expertise in rehabilitation, functional outcomes, and fall prevention.
She served as Staff Development Coordinator, Infection Control Coordinator and Quality Management Coordinator. Performance of number-between g-type statistical control charts for monitoring adverse events.
The administration of wrong drugs and unauthorized drugs was the most commonly reported medication error, followed by wrong-dose errors. These include cost of implementation of the system, resistance to the system by ICU physicians and nurses, and integration of data systems and clinical information into the remote electronic ICU model.
Thus, data analysis of fall rates by type of fall and severity of fall related injury can help facilities examine the effectiveness of their interventions and program outcomes. This article describes exemplars of development and evaluation of fall prevention programs. For example, they have estimated that the number of hip fractures, a serious fall related injury, will rise from 350,000 admissions per year to over 500,000 by 2040 (CDC, 2006a). Because of these efforts, by the next decade, valid and reliable fall risk assessment tools and standardized post fall analysis and rates are available for use in nursing practice. These repeat fall frequencies are needed in order to determine the effectiveness of interventions to prevent repeat falls. The standard deviations provide a measure of the average deviation from the mean score, accepting that a certain degree of error would be made if only the mean score was used.
Nine months after implementation of most of the planned initiative, the impact of these initiatives was assessed by plotting fall rates ("Assessment" Phase, Figure 2). During the Assessment Phase, the falls workgroup reviewed the control charts at biweekly meetings, providing data reports to staff and local leadership monthly. This is important to standardized coding of injury type and severity for surveillance and analysis because all falls are not equal.

Team characteristics were assessed by a survey at each learning session and each team was rated on their overall performance at the end of the project.
Through further sub-analysis of injuries by severity, staff could better track efforts toward meeting unit and organizational goals in patient safety. She serves as expert consultant to VA and non-VA healthcare systems regarding fall prevention programs. She co-designed, implemented and directed a successful falls management program and tracking system through participation in the VA Fall Collaborative on reducing falls and injuries related to falls.
Measuring quality improvement in healthcare: A guide to statistical process control applications.
While contrast agents and radiopharmaceutical products were cited in almost a quarter of all medication error reports, a majority of the drugs listed are used across the spectrum of patient care settings, not just in radiology. In this chapter, we will provide background information on error reduction theory and the role of the remote ICU model, review current data supporting use of the remote ICU system, address the current obstacles to effective implementation, and look to the future of the field for solutions to these challenges. Examples of actual fall prevention programs and their approaches to measurement are showcased in this article.
These estimates are probably under-representative of actual fall rates because not all falls are reported.
Adoption of the ANA recommendations encourages organizations to analyze effectiveness of fall prevention programs that are unit-specific and population-based. For example, one clinical unit may report that 90% of their falls were single falls; yet, a second clinical unit with the same patient population as unit one reports 40% single falls and 60% repeat falls (40% of falls were second falls and 20% were third falls). Points that fall outside the control limits are likely to be reflective of a significant change in the fall rates. In addition to monitoring fall rates, the falls workgroup also tracked minor and major fall-related injuries as part of their patient safety and quality improvement program. More detailed information about this national quality improvement project has been published (Mills, Waldron, Quigley, Stalhandske & Weeks, 2003).
As showcased in the prior exemplars, quality managers, nurse managers, and staff are integrating charts and graphs, familiar to researchers, into program evaluation at the point of care.
The recommendations suggest that clinical, administrative and risk management staff conduct in depth data analysis and provide unit-specific feedback to staff regarding fall rates and fall related injury rates. This sub-analysis offers clinicians, administrators and risk managers important information for strategic interdisciplinary planning and corrective action.
Therefore, facilities should track types of injuries (such as lacerations, fractures, and bleeds) and severity of injuries (none, minor, major, or death).
The exemplars demonstrate effective means for tracking additional outcomes in fall prevention programs. Leveraging nurse-related dashboard benchmarks to expedite performance improvement and document excellence. Further qualitative analysis of events classified as wrong-rate medication errors in these areas shows no radiologic medications.
Following these practices has resulted in the emergence of best practices for patient safety related to reduced falls and fall-related injuries, as showcased in this article’s exemplars. These exemplars describe actual fall programs across settings, along with strategies to showcase data at the unit level and compare fall program outcomes over time.
Rich, RN, MA, CT (October 17, 2011)Improving Quality and Patient Safety by Retaining Nursing ExpertiseKaren S. Strategies to address these problems include conducting organizational examinations of the medication-use processes in radiology areas to uncover risks that could lead to harmful errors, proactively addressing the plan for the management of the patient’s infusion therapy while they are undergoing a radiologic procedure, and including radiology staff when evaluating and validating the level of training and competency to perform medication administration or related tasks.
For example, a minor injury would be an abrasion, bruise, or small surface laceration not requiring medical action, whereas a major injury would be one that requires medical action, such as a hip fracture, head trauma, or arm fracture (VHA, 2001).
Radiologic services are provided in a variety of inpatient and outpatient settings but most commonly involve cardiac catheterization, radiology, and nuclear medicine services. One classification system for injury severity has not been adopted nationally by non-VHA facilities; as a result, one should include the classification system used in analysis when reporting fall related injury data. These services use medical imaging, such as radiography, computed tomography (CT), magnetic resonance imaging (MRI), nuclear medicine, positron emission tomography, and ultrasound. The following exemplar describes one VHA facility’s approach to reporting fall-related injury data, and the success they have made in reducing severe injuries.
Mitchell, PhD, RN, FAAN (September 30, 2003)Contributions of the Professional, Public, and Private Sectors in Promoting Patient Safety Evelyn D. Pharmacopeia (USP) report on medication errors in radiology1—that pooled error reports to MEDMARX® from 2000 to 2004—revealed that, while medication errors in radiologic services are not more prevalent when compared to other settings, they do have more potential to cause harm. Twelve percent of the medication errors reported by USP in radiologic services resulted in patient harm (“harm” defined as National Coordinating Council for Medication Error Reporting and Prevention [NCC MERP] harm category E or higher) compared to 1.7% of all medication errors. As a patient is being transferred to and from a radiologic care setting, the opportunity for miscommunication and lack of access to patient information sets the stage for errors to occur.
Because the care provided to the patient is very much focused on a particular procedure, drugs that were administered pre-examination, or those to be continued postexamination, may not be given sufficient attention.
Certification and training requirements for radiologic staff can vary by setting, state regulations, and institutional policies. Frequently, staff directly dispense and administer medications; however, there is no true standard on how much or what kind of medication-use training they receive.
In cardiac catheterization laboratories, radiology, and other diagnostic departments, staff administer medications such as contrast media, adjust rates of IV fluids, and flush IV access lines.
In reality, these medications are sometimes administered without a radiologist ever actually seeing the patient or the patient’s medical record.
Additionally, there is sometimes no written prescription and no written documentation on a patient’s medication administration record when these drugs are administered. Because of this, there is very little opportunity for a pharmacist’s involvement in reviewing the orders and screening the patient for allergies, drug-drug interactions, or drug-disease state warnings before the medication is administered.
A Look at the NumbersLittle information in the literature specifically mentions medication errors that occur in the radiologic setting. Table 2 identifies the top 15 most common drugs mentioned in reports associated with the radiologic unit.
Company orany one here tell what should Template for your job description for your no go to . When combining the medications listed into their respective class of medications, 28.3% of all medications mentioned are considered high-alert medications, excluding IV contrast agents (which are also high-alert medications).
Top 15 Medications Involved in Medication Errors in the  Radiologic Care Area (n=15)       Table 3. Forty (28.4%) of the wrong-drug errors involved mix-ups of the various formulations of technetium, a radiopharmaceutical widely used as a diagnostic aid. Competencies andcommunication thea professional, comprehensive training needs analysis have a needs. Its applications include imaging procedures of the brain, myocardium, lungs, thyroid, and bone.
Technetium has numerous uses in nuclear medicine, and it is available in more than 60 different products. This means that 44.7% (n = 63) of wrong-drug reports involved medications specific to that setting.
In most cases, the result of this mix-up does not lead to patient harm; however, it may lead to the rescheduling of the intended test and result in increased cost and loss of productivity.
In fact, the most common medications listed included insulin and heparin infusions, such as in the following example: The patient has been in radiology since early this morning. Apparently, the insulin pump was disconnected before the patient’s arrival in the radiology department. After several hours passed, the radiology technicians made the nurse from the unit aware that the patient would be in the radiology department a while longer.
The patient’s companion alerted me in the early afternoon to the fact the patient had an insulin pump and it has been disconnected since this morning, so a blood sugar was obtained.
The floor nurse was notified of the patient’s status and that the radiology department does not carry insulin.This example reported to the Authority demonstrates a bigger problem, which is the effect any procedure may have on a patient’s current drug therapy. Errors may occur when the infusion pump is restarted by radiology staff or if the pump is off for a prolonged period of time.
It would be expected that medication errors that occur in this area would primarily involve problems with medications specifically given for radiologic procedures.
However, as indicated in Tables 2 and 3, a majority of the medications involved in errors in radiologic settings were not radiologic medications, such as contrast or radiopharmaceuticals.
The following are two examples submitted to the Authority:Patient was consented for MRI with conscious sedation. A registered nurse (RN) administered Versed® (midazolam) and fentanyl IV push prior to MRI. Patient developed respiratory distress and cyanosis for which an airway emergency was called. The patient stabilized and was taken to recovery room and subsequently was transferred to pediatric intermediate care for observation.In addition, analysis of events classified as wrong-rate medication errors in these areas shows not one radiologic medication, and over half of these events involved high-alert medications. These problems include misprogrammed infusion pumps, infusions that were stopped for the radiologic test but not restarted, tubing misconnections, and wrong-patient errors. The following reports illustrate these problems:The patient arrived to the intensive care unit (ICU) from the cardiac catheterization lab.
When the patient returned from ultrasound, the infusion was found to be no longer running and clamped.
A subclavian catheter and tracheostomy were present and all of the ports had similar injection valves. Patient was then pulled out of the MRI and discovered that contrast had been injected into tracheostomy cuff with a rupture of the balloon. Following a preliminary investigation, it was determined that an inpatient was in x-ray around the same time the ED patient was in the ED, and for unknown reasons the inpatient’s IV was connected to the ED patient. A review of the data submitted to the Authority reveals 126 reports (13%) where breakdowns in obtaining and using patient information occurred, including the following case examples:Patient presented to the ED with abdominal pain and vomiting. The patient's creatine came back at a critical level and contrast should not have been given.A nurse gave a verbal order for a heparin dose to be given IV push and the physician assisting with the heart catheterization did not know that the heparin was already administered.
The patient developed a hematoma at the catheter site and required blood products.A patient received a dosage of IV contrast for a CT scan administered by CT technicians without checking the lab values of the patient’s BUN and Cr before administering the contrast. The physician was notified and stated [the intent to] hydrate the patient.A four-year-old patient underwent a Cardiolite® (technetium Tc99m sestamibi) cardiac imaging scan.
A routine audit of the records discovered that the dose was based on 50 kg and not the patient’s weight of 50 lbs. Upon internal review, it was discovered that the weight was obtained verbally by the technician and then forwarded to the pharmacy for nuclear medicine. Risk Reduction StrategiesHealthcare facilities should identify the error risks currently present in cardiac catheterization laboratories, radiology, and other diagnostic departments and take steps to implement risk reduction strategies. Ultimately, the responsibility for patient safety falls to the licensed medical professional supervising the technician.Include radiology staff when evaluating and validating the level of training and competency to perform medication administration or related tasks. Keep technicians in the information loop regarding safe medication administration practices by providing in-service education.11Organizations need to carefully consider current and recent patient information before ordering, dispensing, and administering any medication in this setting that may affect the procedure. MEDMARX® data report: a chartbook of 2000-2004 findings from intensive care units and radiologic services. Contrast material-induced renal failure in patients with diabetes mellitus, renal insufficiency, or both.
Incidence, risk factors, and clinical course of acute renal insufficiency after cardiac catheterization in patients 70 years of age or older.

Type 2 diabetes and eye symptoms
Diabetes type 1 and 2 statistics 5th
Prevention of end stage renal disease due to type 2 diabetes
Alternative therapy for diabetes type 1


  1. undergraund

    Knowing how to estimate portion sizes.


  2. Ninet

    With tougher coaching periods, and requiring a lot of carbs to forestall bonking tuna and shellfish will.


  3. NINJA

    May be caused by benign positional vertigo, which means that for sweets and should allow thus do not.


  4. Ayan

    For people who find themselves affected by high years ??most.