Please respond to each response with substantial detail that provokes further discussion. Readily offers new interpretations of discussion material. Ideas are expressed clearly, concisely
Discussion question:
1. What data sets would be valuable in gaining knowledge related to the policy you choose? Discuss.
2. How does population based data be used to create community level health policy?
Response: Joanna
1) The policy I chose was sickle cell care expansion. Sickle cell disease (SCD) can lead to several complications where management of the disease becomes complicated. The importance of expanding care to these patients increases the size and capacity of the medical workforce that is trained to treat sickle cell. Data sets that would be valuable in gaining knowledge related to this policy include: Population-based public health surveillance, Medicaid and Health Insurance Program databases, death certificates, hospital discharge and emergency department records, and clinical records or case reports. With this type of data, SCD population prevalence, demographic characteristics, health care access and use, and health outcomes can be identified. Additionally, big data sets can be used to gather data from social media, web visits, call logs, and other sources maximize value .
2) Population-based data assesses community needs that can be used to create community level health policy. This data provides insight to public issues that need more attention where the analysis of this data can be used to assist in population health management in enhancing care, addressing SDOH and improving patient outcomes. According to Milstead (2022), this type of data provides an outline for action. Information like demographics and clinical data are useful in identifying geographic areas of greater need and health issues where there are disparities and inequalities (Stoto et al., 2019). Population data provides important evidence for health policy decision makers but can also help achieve health equity by addressing the need for changing systems and policies that have resulted in health disparities.
Response: Angelica
1. The policy I chose to write about in my advocacy paper was the nurse-to-patient ratio. Specifically, I wrote about how the inclusion of an off-care charge RN on an oncology unit to oversee chemotherapy administration would be beneficial and would help lessen the nurse-to-patient ratio. Logically, patients with a higher acuity would call for more attention from staff. As per Milstead (2022), a data set refers to structured data that can be retrieved via a link or index. Big data refers to very large data sets. As such, “examination of big data enables an organization to identify effective processes, eliminate wasteful processes, improve products and services, enhance the customer experience, and establish a competitive advantage” (Milstead, 2022. p 203). Big data would be an appropriate data set to use because as relayed by Milstead (2022), big data provides a tool to benchmark performance against other organizations, improve patient outcomes, measure innovation and may help with cost-saving opportunities. For the policy I described, comparative effectiveness research would examine the benefits and harms of this method in improving patient care. I think data sets could be pulled from surveying patients about their experience receiving inpatient chemotherapy and from the nurses administering it. We could compare results of HCAPS scores between hospitals that used the extra off-care charge RN to oversee chemotherapy administration and those that did not use the off-care RN. In this way, we would be able to tell if that extra nurse did anything to improve patient experiences, enhance patient outcomes, and lessen the burden for the nurses involved. Furthermore, we would be able to assess cost-effectiveness of the off- care RN by determining how many patients were re-admitted after chemotherapy infusion because of lack of discharge teaching. Sometimes, nurses are so busy with patients that they don’t provide adequate instructions to patients. These patients would return to the hospital because they were sent home with instructions they didn’t understand, further causing the hospital to lose money because if a patient is re-admitted within 30 days of discharge, the hospital does not get paid.
2. Population data contains details such as birth, death, age, sex, annual income, occupation, and language (Fleetwood, 2023). Therefore, if we were to study a specific community and understand what resources they have available to them and what level of education they have, we can better accommodate their needs. For example, if we had a patient population that primarily relied on public transportation as a means to get to and from doctor’s visits, we would have to be mindful when prescribing interventions as they may not be able to access them. Furthermore, in such an area, we might want to make Community Health Centers more accessible to patients and have more resources available in a single location to meet the population’s needs. Such community health programs address disparities in health care by ensuring equal access to health resources for those in lower socioeconomic classes as revealed through population data assessment.
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