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Respond to the discussions post below by explaining how the regulatory environment and the regulations selected by your colleague differ from your state/region. Be specific and provide examples. 150-200 words APA format. 2 intext citation 2 reference ( each post)

#1 discussion.  Pennsylvania’s nurse licensing requirements prioritize assisted living residents’ safety. The Nurse Practice Act (NPA) and other laws guaranteeing competence and public safety govern nursing in the state. Bosse et al. (2017) state that the NPA and other laws regulate nursing. Nevertheless, the Nurse Practice Act—which gave the New Jersey Board of Nursing its legal foundation—had enforcement as one of its main objectives. The BON prioritizes public safety above everything else, but it also considers nurses’ rights. The BON may make its provisions more understandable by creating guidelines and suggestions that adhere to the act’s requirements without going beyond them. There are two critical legal frameworks for advanced practice. The scope and standards of practice, as well as the consensus model, are provided by licensed nurses. 

 The partnership agreement must also include an emergency services plan, a direct communication channel between the APRN and the physician, and a provision for the physician to review the NP’s patient data and records routinely. According to the NCSBN, the Advanced Practice Registered Nurses Board of Nursing in Pennsylvania has outlined these requirements in its rules. Two physicians are required to establish a “collaborative agreement” with an advanced practice registered nurse in Pennsylvania. Doing their work well is their priority. As part of their collaboration agreement, the doctor and the advanced practice registered nurse in New Jersey are legally obligated to assess one patient case every year. It is sufficient that the physician lives in the same town or county as the APRN; their location or area of expertise is not relevant.


#2 discussion . In Virginia, nurse practitioners must obtain dual licensure from both the board of medicine and the board of nursing to practice. Without joint approval from both boards, individuals cannot work as nurse practitioners in the state (Virginia General Assembly, n.d.). Another noteworthy regulation in Virginia is the limitation on the prescription of opioids by APRNs for acute pain treatment, set at a maximum of seven days in both private practice and upon discharge from an emergency department (Virginia Board of Nursing & Virginia Board of Medicine, 2020).

In contrast, in Illinois, APRNs are only permitted to prescribe Schedule II through V controlled substances. Furthermore, they are authorized to write prescriptions for a 30-day supply of Schedule II through V controlled substances but must obtain a separate controlled substance license (Illinois General Assembly, n.d.). While there are similarities in the regulations governing APRNs in Virginia and Illinois, there are notable distinctions. In Virginia, nurse practitioners do not need separate licensure for controlled substances. However, they face restrictions on the duration of opioid prescriptions, limited to seven days for acute pain and emergency department discharge.

These legislative variations influence the prescribing capabilities of APRNs, dictating the scope and duration of prescriptions they can issue. In some emergency department, nurse practitioners frequently opted for alternatives like Ultram instead of opioids, adhering to the regulations that limit opioid prescriptions to a maximum of seven days. Additionally, the requirement for dual licensure from the Board of Medicine and the Board of Nursing in Virginia is a crucial aspect that APRNs must comply with to practice in the state.


#51 Respond by offering one or more additional mitigation strategies or further insight into your colleagues’ assessment of big data opportunities and risks. 150-200 words APA format. 2 intext citation 2 reference ( each post)

#1 discussion. A potential benefit of big data and data mining is using it to determine relationships and discover patterns that may not have been noticed before (McGonigle & Mastrain, 2021). This could be using trends in catheter insertions and CAUTI infection trends to determine better CAUTI prevention methods, whether decreasing the number of straight catheter attempts before inserting a foley or finding a potential opportunity for reeducation on a floor with a particularly high rate of CAUTIs. Another potential benefit is by simplifying nursing workflow analyzing the EHR, and removing duplicate and unnecessary documentation (Glassman, 2017). Simplifying the workflow will allow nurses to focus more time on their patients rather than on superfluous documentation.

            A potential challenge of using big data is being able to break down what is important and needs information rather than what is extra and not important. With such a large amount of data input every day within a hospital, it is very difficult to trim the fat and separate what is important and what is not needed. This can lead to information possibly being misinterpreted within a pattern and creating a false connection. Although a lot of healthcare facilities are adopting the use of big data a percentage of them do not have the understanding to use it effectively. “Evidence shows that only 42% of healthcare organizations surveyed are adopting rigorous analytics approaches to support their decision-making process; only 16% of them have substantial experience using analytics across a broad range of functions” (Yichuan, Kung & Byrd, 2018). To challenge this issue, it is important to give healthcare organizations proper training and education in regards to big data and data mining systems. Through the implementation of nurse informaticists and information technologists, it is possible for health organizations to gain a better understanding by hiring the appropriate people for the job to help run the system as well as educate the rest of the hospital as well.


One potential benefit of using big data as a part of a clinical system is its ability to pull information from various sources without difficulty. This information is collected via the facility’s electronic health record, medical devices and equipment, and/or patient monitoring systems, and is able to be combined. As a result of mass data collection through a variety of routes, there is great potential for improvement in healthcare delivery, cost(s), decision-making, and even patient outcome (Baloch et al., 2023). This improves the efficiency of the healthcare facility and provides a continuous method of collecting complicated data from numerous resources (Baloch et al., 2023).

One potential challenge of using big data as part of a clinical system is the concern of breaking patient confidentiality and privacy (Baloch et al., 2023). Although big data will be able to identify patient care patterns and concerns, it also has great potential for data breaches and the release of information that should be kept private. Despite the improvements that big data collection may allow, maintaining patient confidentiality and the desires of each patient is the main priority (Baloch et al., 2023).

One strategy that I have observed that may effectively mitigate the challenges or risks of using big data would be to carefully and very thoroughly incorporate a release of personal health information for research purposes form. This form would specifically state that the patient’s information from the facility’s electronic health record, medical devices and equipment, and/or patient monitoring systems would be collected, if given informed patient consent. “Informed consent implies the individual’s ability to understand why consent is requested and the potential consequences or outcomes of grant- ing consent” (Lemke, 2013). The form would be carefully explained and signed at the beginning of the patient’s initial visit to the medical facility. It would also be continuously offered and reviewed with each following visit to ensure patient acceptance. “Consent is valid only if freely given and (b) consent is considered voluntarily given only if the client was first informed about the foreseeable implications of consenting” (Fisher, 2016). This would help to ensure that the facility’s big data analysis is within compliance with patient privacy.

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