List and describe two issues associated with healthcare that would bene

John

1. Automating repeatable tasks

There are a number of repeatable tasks involved in administering health care that could be streamlined through automation, both reducing costs and reducing time to treatment. Yesterday, I listened to a speaker describe the implementation of an EHR system to center treating Cancer that had previously run on paper-based processes. She noted that the efficiency of the system was much improved, but that the real win was that the Cancer patients were getting from diagnosis to treatment much faster, improving overall patient outcomes. In implementing the system, a great deal of analytics work was involved in clarifying and mapping out processes so that they could be automated and reported on. 

2. Easing transitions for patients between providers

Placing the patient at the center of healthcare processes will allow healthcare to retain individualized and connected care, even when an increasing number of processes are automated. Since healthcare processes are necessarily guided by a human provider every step of the way, it makes sense that automated processes should be there to aid in information transfer during the handoff of the patient from one provider's care to another. Without special care taken to transfer information between providers in contiguous care, the patient may have a poor client experience or, worse, be harmed as a result of ill-informed treatment. 

Angela

The two issues associated with healthcare that would benefit from the appropriate application of healthcare data analytics are predicting disease – risk management and substance abuse crisis. Data analytics can used to study patterns associated with predicting disease problem by predicting trends in the spread of illness. For example: Covid-19 is an infectious disease caused by the SARS-CoV-2 virus and spread during close contact or by airborne transmission. The healthcare data analytics will help to predict how many cases per day in a specific region to know how dangerous it is so people can be adequately prepared. It also helps hospitals and healthcare staffs prepare enough PPE and beds. The government can give people suggestion regarding social distancing, travelling and remote work or school. Secondly, substance abuse is another issue that needs to be addressed. Substance abuse is an excessive use of psychoactive drugs, such as alcohol, pain medications, or illegal drugs. If misused or overdosing, it can cause serious harm such as physical, emotions, social harm and death. Data analytics can be used to measure cases such as:  overdose death rates involving opioids in a hospital; tobacco, alcohol and drugs uses by students at a university; the number of opioid is given at a hospital within a month. And data help indicate if a person is currently abusing drugs or not and if the hospital has problem with opioid prescription and medication administration. From there, we can have earlier treatment or prevention before they become addictions .We can take a look at this article. The article said – “Oregon Health & Science University Hospital in Portland worked with several partners—including community organizations and a Medicaid accountable care organization—to conduct a needs assessment and subsequent response to substance use disorder in its area. The needs assessment revealed high rates of hospitalization, long lengths of stay, and high readmissions related to substance use disorder” ( Susman, 2017). 

References:

Susman, Katherine.(2017). The opioid crisis: hospital prevention and response. Essential Hospital Institute. 

https://www.carilionclinic.org/sites/default/files/2019-07/Essential_Hospitals_Opioid-Brief_OCR.pdf

Jenny

1. Improving patient engagement

Achieving patient involvement and enhancing risk management tactics in the healthcare practice have many issues. Both patients and doctors can put up obstacles to effective patient involvement. They might not feel at ease seeking medical advice or asking inquiries. Additionally, some people might lack the drive to make essential improvements to their health. To assist patients in achieving their health goals, case managers can greatly benefit from using data analytics. They can come up with new strategies to keep their patients interested in and dedicated to preventative care by researching the most recent trends that are popular in the medical community.

2. Improve health outcomes

The effect of the medical service or intervention on patients' health state is reflected in outcome metrics. Data analytics-based evidence-based care is the way to go. It is possible to considerably benefit from all the rich experience that is accessible in the form of clinical trials, case histories, research articles, etc. with the ability to process large data sets. Better health outcomes will arise from all this emphasis on reflecting on the past and learning from it.

Sam

· Blood pressure monitoring

At my clinic, we are working toward Gold Standard for monitoring blood pressure as set by CMS. We need to improve this metric for our patients. To do this, we use quality dashboards to identify providers who have patients enrolled in the program and then use analytics to find appointments where a patient's BP is recorded or missed. We use this data to find gaps in care that can be improved. Then I work with providers to help them find a flow in their visits to add BP conversations, diet and exercise counseling, and other ways to reduce the number of patients we have with high BPs.

· Depression

Screening patients in primary care for depression is important in order to identify patients who are suffering but have never had a diagnosis of depression in the past. At our clinic, we initiated a program to screen every patient once a calendar year if they don't have depression listed on their problem list, and at every visit, if they do have a diagnosis of depression. Screening for depression is vital because it can be a determinant of health. We use quality analytics to identify screenings from completed PHQ2s and PHQ9s. We also drill down to providers and encounters that screenings occur within. We use this information to help providers improve their screenings and also to track and measure health outcomes from patients with depression.

Claire

One of the most prevalent issues that would benefit from data analytics is patient wait times. There has been an increase in the waiting time required for most patients, necessitating the need to ensure adequate staffing and scheduling in providing patient care (Atchley et al., 2021). The cause of the long-waiting times for the patients is believed to be caused by the resource's mismanagement and in instances where such resources are insufficient.

  The other common issue that can be impacted by data analytics is the issue of misdiagnosis and medication errors that are so prevalent in healthcare settings. These are believed to be prevalent in healthcare settings and may be experienced when nurses are experiencing burnout after working long shifts. The cause is also associated with human error, mainly when the healthcare providers undertake the wrong procedures or even confuse the samples they are testing.

How the Issues Would Benefit

There are various ways through which these issues would benefit from data analytics. The use of data analytics is considered critical since it helps in care coordination. The analytics is also critical as it helps in enhancing improved patient staffing and scheduling, reducing patient waiting times. Similarly, this is also considered vital since it helps reduce readmission rates and gives the patients options for scheduling appointments.

For misdiagnosis, healthcare data analytics is used to ensure that the provision of insight is used in clinical decisions. The use of informed decision-making in healthcare helps eradicate medication error by ensuring an adequate analysis of the patient's records and medication concerns, facilitating effective medication (Dash et al., 2019). 

 References:

Atchley, M. D., Kroll, N. P., & Etcher, L. (2021). Reducing the wait: When time is priceless. The Nurse Practitioner, 46(2), 50-55.

Dash, S., Shakyawar, S. K., Sharma, M., & Kaushik, S. (2019). Big data in healthcare: management, analysis, and future prospects. Journal of Big Data, 6(1), 1-25.

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