DNP 805 Topic 5 DQ 2 Using the clinical question you identified in the previous discussion question, determine the individual components to that question

DNP 805 Topic 5 DQ 2 Using the clinical question you identified in the previous discussion question, determine the individual components to that question

DNP 805 Topic 5 DQ 2 Using the clinical question you identified in the previous discussion question, determine the individual components to that question

DNP 805 Topic 5 DQ 2 Using the clinical question you identified in the previous discussion question, determine the individual components to that question

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Topic 5 DQ 2

May 12-16, 2022

Using the clinical question you identified in the previous discussion question, determine the individual components to that question and pinpoint the location in the hypothetical database where the information you require will be extracted.

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REPLY TO DISCUSSION

Uploading aspects of a discharge record into a database yields useful data. Care decisions can be guided by providers who can assess a patient’s discharge plans, medications, and history. Specific elements such as discharge instructions, medications or prescriptions, and diagnoses could be made available to all medical providers through a shared database. “Health Current is a health information exchange (HIE) in Arizona that connects communities and information to help partners transform care. The HIE protects patient health information and facilitates patient health information exchange between the HIE and its partner organizations and providers. More detailed information is more meaningful, which leads to better care and outcomes. It enables healthcare transformation ” (HIE, 2022).

The preceding discussion’s clinical problem was chronic heart failure, and the clinical concern is whether they will continue to employ standardized drug therapies that may not be working with the complexity of chronic heart failure (Bai, Yao, Jiang, Bian, Zhou, Sun, Hu, Sun, Xie, & He, 2022). Individual components to this question would be found in the patient’s electronic health records (EHR) within the healthcare system’s database. Individual components include the patient’s name, account number, gender, date of birth, race, religion, residence, and insurance information, admission history and physical, medication list, laboratory findings, nursing records, and physician records. EHRs are designed to hold numerous types and ranges of patient data, such as those stated above, and they have an infinite ability to be customized to the specific needs of the patient, the HCP, and the organization (Alexander, Hoy, & Frith, 2019).

Read Also: DNP 805 Topic 6 DQ 1 Post the technology your patient will use at home and how will you connect with the patient using this technology

References:

Alexander, S., Hoy, H., & Frith, K. (2019). Applied clinical informatics for nurses (2nd ed.). Jones & Bartlett Learning.

Bai, Y., Yao, H., Jiang, X., Bian, S., Zhou, J., Sun, X., Hu, G., Sun, L., Xie, G., & He, K. (2022). Construction of a non-mutually exclusive decision tree for medication recommendation of chronic heart failure. Frontiers in Pharmacology12https://doi.org/10.3389/fphar.2021.758573

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REPLY

This is another great example of how data mining can help to improve the care for heart failure patients. I agree that most of this data is easily abstracted from the electronic medical record. What is your hypothesis for your clinical question. Looking for correlations can help greatly with this dat mining.

The clinical question posed was, “What interventions are effective in reducing nursing turnover among nurses?” This is accomplished by comparing the nursing turnover rate to the leapfrog rating, CMS Stars, Magnet status, mandated patient ratios, workplace violence incidents, employee injuries, and union hospitals. This would enable correlations to be drawn between what makes facilities more appealing to nurses. This information could also be regionalized, because what is important to nurses in California may be very different from what is important to nurses in Mississippi. They enable targeted recruiting and retention techniques. On a smaller scale, some of these have already been investigated. One study, for example, discovered a link between workplace violence and turnover in two large teaching hospitals (Yeh et al., 2020).

Reference

Park, S. H., Gass, S., & Boyle, D. K. (2016). Comparison of Reasons for Nurse Turnover in Magnet ® and Non-Magnet Hospitals. The Journal of Nursing Administration46(5), 284–290.

Yeh, T.-F., Chang, Y.-C., Feng, W.-H., Sclerosis, M., & Yang, C.-C. (2020). Effect of Workplace Violence on Turnover Intention: The Mediating Roles of Job Control, Psychological Demands, and Social Support. Inquiry : A Journal of Medical Care Organization, Provision and Financing57, 46958020969313. https://doi-org.lopes.idm.oclc.org/10.1177/0046958020969313

REPLY

There are many valid points for consideration in data mining related to nursing turnover. Considering the nursing shortage we are in, it is a hot topic and one worth investigating. There are two vital sides to this topic one concerns the nurse and the other concerns care for the patient. I appreciate your data mining considerations have variables that relate to both sides of this issue. In addition to considering the impact on the patient and nurse, the locality is another important factor that you addressed. Because this information can vary from location to location, it would be interesting to compare one region to another. Different factors help to keep staff at the bedside, and compensation is one of those factors (Halim, et al., 2020). With proper data mining techniques, this can be analyzed to entice nurses to stay. With the cost to replace a nurse, the current shortage, and patients who depend on nursing care, this data mining would be fruitful to the nursing profession.

Having elements of a discharge record being uploaded into a database provides useful information. Providers being able to review discharge plans, medications and history of a patient can guide clinical decisions for the best outcomes possible. Specific items such as discharge instructions, medications or prescriptions, and diagnosis could be available to every medical provider via a communal database. “Health Current is the health information exchange (HIE) that helps partners transform care by bringing together communities and information across Arizona. The HIE, provides secure access to patient health information as well as the secure exchange of patient health information between the HIE and its participating organizations and providers. More complete information is more meaningful and leads to better care and better outcomes. It makes healthcare transformation possible” (HIE, 2022).

The clinical problem from the previous discussion was chronic heart failure and the clinical question is if they will continue to use standardized medication treatments that may not be working with the complexity of chronic heart failure (Bai, Yao, Jiang, Bian, Zhou, Sun, Hu, Sun, Xie, & He, 2022). The Individual components to this question would be located in the electronic health records (EHR) of the patient within the database of the healthcare system. The individual components would be the patient demographics which includes the name of the patient, account number, sex, date of birth, race, religion, address, and insurance information, admission history and physical, the medication list, the laboratory results, the nursing records and the physician records. EHRs are designed to hold many types and ranges of patient data such as listed above and it has an endless capability for being customized to the particular needs of the patient and the HCP as well as the organization (Alexander, Hoy, & Frith, 2019).

References:

Alexander, S., Hoy, H., & Frith, K. (2019). Applied clinical informatics for nurses (2nd ed.). Jones & Bartlett Learning.

Bai, Y., Yao, H., Jiang, X., Bian, S., Zhou, J., Sun, X., Hu, G., Sun, L., Xie, G., & He, K. (2022). Construction of a non-mutually exclusive decision tree for medication recommendation of chronic heart failure. Frontiers in Pharmacology12https://doi.org/10.3389/fphar.2021.758573

The clinical question proposed was, what interventions are impactful in improving decreasing nursing turnover among nurses? To do this you look at the nursing turnover rate and comparing it to leapfrog rating, CMS Stars, Magnet status, mandated patient ratios, workplace violence incidents, employee injuries, and union hospitals. This would allow for correlations of what makes facilities more appealing to nurses. This data could also be regionalized, because what is more important to nurses in California may be very different for those in Mississippi. They allows for targeted recruiting and retaining techniques. Some of these have already been studied on a smaller scale. For example, one study determined a correlation with workplace violence and turnover in two large teaching hospitals (Yeh et al., 2020). Another example is Magnet units have lower turnover than units a non-Magnet facilities (Park et al., 2016). What we don’t know is how widespread this is and if it varies across regions. This will add to that ability. Also, how has this changed post pandemic. Have the priories on what is keeping nursing from turning over the same? All are things that can be answered by this database.

Reference

Park, S. H., Gass, S., & Boyle, D. K. (2016). Comparison of Reasons for Nurse Turnover in Magnet ® and Non-Magnet Hospitals. The Journal of Nursing Administration46(5), 284–290.

Yeh, T.-F., Chang, Y.-C., Feng, W.-H., Sclerosis, M., & Yang, C.-C. (2020). Effect of Workplace Violence on Turnover Intention: The Mediating Roles of Job Control, Psychological Demands, and Social Support. Inquiry : A Journal of Medical Care Organization, Provision and Financing57, 46958020969313. https://doi-org.lopes.idm.oclc.org/10.1177/0046958020969313

There are many valid points for consideration in data mining related to nursing turnover. Considering the nursing shortage we are in, it is a hot topic and one worth investigating. There are two vital sides to this topic one concerns the nurse and the other concerns care for the patient. I appreciate your data mining considerations have variables that relate to both sides of this issue. In addition to considering the impact on the patient and nurse, the locality is another important factor that you addressed. Because this information can vary from location to location, it would be interesting to compare one region to another. Different factors help to keep staff at the bedside, and compensation is one of those factors (Halim, et al., 2020). With proper data mining techniques, this can be analyzed to entice nurses to stay. With the cost to replace a nurse, the current shortage, and patients who depend on nursing care, this data mining would be fruitful to the nursing profession.

Reference

Halim, Z., Muhammad M. W. Edwin, C. & Shah, A. (2020). Identifying factors for employee retention using computational techniques; An approach to assist the decision-making. SN Applied Sciences, 2, 1612.

Interesting topic and question Alicia, One that pulls at my emotions dearly when i see how much the bedside nurses are pulled in so many different directions. The early nursing turnover which is now a critical issue that has received worldwide attention and it has a lot of mitigating factors like some of the ones you have mentioned such as the mandated nurse-patient ratios, workplace violence, employee injuries. The aging population has added and increased pressure on the health care system with the increasing need for healthcare services which has continued to increase the need for nurses (Hu, Wang, Lan, & Wu, 2022).  Personally, for me, what I consider the biggest issue is the non-standardized nurse-patient ratios nationally. Hence states like California and some have set ratios of 6 patients per RN while states like NJ base it on acuity so that they could continue to increase the number of patients per RN even when they are not short of RNs. Another issue I have is the incessant rush within healthcare. The rush to get things done especially in the medical units when it is not an emergency. This rush to get things done, does not afford the nurses the time to calmly critically think things through and because of the lack of staff especially the ancillary staff like the nursing assistants to support the nursing work, the nurses, have to do all things which increases the pressure and stress upon the nurses. A study reported that 22% of hospital nurses plan to leave their profession in less than a year because of workplace stress. The stress reduces nursing quality care, increases the re-recruitment costs, and the associated decrease in patient safety and positive outcomes (Hu, Wang, Lan, & Wu, 2022). There is also the negative feeling of the nurses when they have to keep training new staff constantly. These states and facilities forget to realize that, one, they are dealing with human lives and the nurses need to pay attention to the patients to avert any adverse events but when they are pulled in different directions, they are not able to focus on all their patients in a safe manner. An article points to three possible interventions of hope, career identity, job satisfaction that may help to reduce early nurse turnover (Hu, Wang, Lan, & Wu, 2022). The Nurses’ career identity affects their work enthusiasm and is positively associated to their job satisfaction which eventually affects the quality of their work. This is their understanding of the social impact of their profession on their work which is characterized by their feelings, values and their attitude to their work (Hu, Wang, Lan, & Wu, 2022). Hope is a concept that portrays positive motivation based on one’s sense of success from the will power and energy to achieve a set goal. Scholars have shown that hope is particularly important in the face of the intense competition and uncertainty that characterize the present work and career environment. Having high level of hope helps the nurses to appropriately deal with the psychological stress and be able to cope with the difficulties and perhaps decrease the negative impact of dissatisfaction with the job that generates intention to leave. So, when hope is lost or diminished, it becomes difficult to retain the nurse (Hu, Wang, Lan, & Wu, 2022). Likewise, job satisfaction is also a positive emotional reaction that is generated by the nurse individual assessment of their work. It is a negative association and an antecedent to nurse turnover intention (Hu, Wang, Lan, & Wu, 2022). Nurses particularly feel job dissatisfaction when they are constantly overwhelmed and overworked, leaving work 2-3 hours late to catch up on documentation which is worse when they have to come back the next day. This causes extreme lack of adequate sleep, stress and decreased mental cognition when they need it. This affects patient safety and outcome and it is not safe for the nurses either. When they feel that the safety of their nursing license is constantly being placed on the line, they will have the intention to leave. Job satisfaction has a negative association with turnover intention which suggests that improving the job satisfaction of nurses is an important strategy to retain nurses (Hu, Wang, Lan, & Wu, 2022).

References:

Hu, H., Wang, C., Lan, Y., & Wu, X. (2022). Nurses’ turnover intention, hope and career identity: The mediating role of job satisfaction. BMC Nursing21(1). https://doi.org/10.1186/s12912-022-00821-5

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