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Financial Management And Economics In Health Care

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Financial Management And Economics In Health Care

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  1. ABF module
  2. A) PATIENTS ARE EXPECTED IN THE NEXT YEAR

“DRG

NUMBER OF PATIENTS ARE EXPECTED IN THE NEXT YEAR

NWAU

Overall cost

effective cost

F74A

1600

0.41

1255

E65B

750

0.61

1275

F73B

450

0.44

1140

F76B

450

0.47

1145

E61B

450

0.73

1270

F62B

450

0.8

1135

L63A

350

1.15

1155

F42B

300

1.16

2535

E62A

325

1.16

1255

E62B

300

0.73

1130

5500”

Table 1: The number of patients is expected in the next year

In this given evaluation the number of patients is expected as per the individual DRG The ABF also considers the treatment of patients with acute and severe diseases. Based on the references of Ali et al (2020), activity-based funds and management-based activities are directly proportional to the healthcare industry that is funded by the government on the layout of the activities in the hospital that is the number of cured patients. 

  1. B) NWAU

In this given evaluation the NWAU as per the individual DRG there are F74A, E62B, E62A, F42B, E65B, and all. Also, their inlier is 0.73, 0.41, 0.44, 1.16 so on 

  1. C) National Efficient Price

In this case study there are $5500 is the national effective price, evaluation in the table1.

  1. ABF analysis

(a) Definition of ABF

ABF in the business module stands for (Activity-based funding), this term is basically used in the health sectors. This is the process of funding in the healthcare industry where payment is done for the number and mix of patients that are cured. The funding of the hospital increases if the number of patients cured in the hospital increases. The treatment is directly proportional to the number of cured patients. The ABF also considers the treatment of patients with acute and severe diseases. The activity-based funds and management-based activities are directly proportional to the healthcare industry that is funded by the government on the layout of the activities in the hospital that is the number of cured patients. Activity-based funding is the system that helps the government to analyze the overall record and the respective Project of research that is taking place in the hospital that can lead to the operations cost in the healthcare industry. This healthcare funding has been used in most developing countries for the past thirty years.

This system is mostly used in Canadian countries and in the provinces of Australia. The healthcare services mostly have the aim to cure the patients and the funds on the basis of the treatment can give the concessions to cure the more patients. This framework is classified methodically which helps the system to assist and calculate the total cost that is associated with the healthcare industry. Based on the references of Aragón et al (2022), the funds that are funded by the government by assessing the performance of the healthcare hospital help them to provide the funds effectively and efficiently that is outlined on the basis of the patient's levels of caring. This process also defines the layout of mixed funding of cases, the definition of healthcare is not limited to only taking care of patients and curing disease, the healthcare industry also has a prominent contribution to the maintenance of healthcare, prevention programs, research projects, and teaching skills to residents. 

(b) The module of the ABF model of funding

The funding model that is based on the total activities of the healthcare hospital is the layout of the activities-based funding. This is the method that helps the healthcare industry to get the disbursement of funds on the basis of the total number of patients they have cured. This method is the method that helps the hospital to generate revenue that is directly proportional to the service and patient care. The hospital can generate additional capacity by using the most effective and efficient strategy that can help to generate the highest value in addition. The common method that is the basic policy of objectives for the application of the ABF model is to generate the option for incentives that can help the healthcare hospitals to increase productivity in mass. Under this fundraiser scheme, the healthcare hospitals are paid a similar amount based on the hospital type. The scheme of funding classified the system methodically and the method that is used in the classification is associated with the group of diagnosis. Every single unit of the diagnosis is collected and compared with the other hospitals that have the same range of operating costs. After the collation, the hospital is paid under the ABF model after the valuation is associated with the collected group of diagnoses.

(c) The pricing strategy under the ABF module and the elaboration of the calculation.

In the process to calculate the ABF, the variation that is based on the system and legitimate output in the total number of the module ABF and the co-payments are implemented by using the collection of the group of the diagnosis from the hospital and adjusting the relevant cost in the process. The co-payment is laid by assessing the valuation of the top level that is obtained by assessing the price list of ABFS. According to the view of Bisaga, and To (2021), by applying the approach that is based on the scenario of whether the payment is specified for patients or specified on the institution. The price of the collected group of Diagnoses is adjusted with the help of the clinical practice that is part of the policy of the rising of care-based valuations. In the current situation, the place for the incentive for the price is laid to be (AR-DRG H08B) Z which is laid for the minor complex situations, laparoscopy, and Chloe. In these scenarios, the patients and the price of the case are adjusted in proportion to the incentive cure of these diseases. The final budget setting of the ABF is set with the proposal that is based on the sum total of the acute budget of the hospital that is available with the activities of the upcoming year. So the final price of the activities is set on the basis of the activities that are funded in the current year with the incorporation of calibration so that the sum total of the expected value of ABF for the current year is equal to the total of the budget under the ABF funding schemes. 

  1. “Block funded budgets”

“DRG

THE NUMBER OF PATIENTS IS EXPECTED IN THE NEXT YEAR

Overall cost

Average cost

F74A

1600

1255

313.75

E65B

750

1275

318.75

F73B

450

1140

285

F76B

450

1145

286.25

E61B

450

1270

317.5

F62B

450

1135

283.75

L63A

350

1155

288.75

F42B

300

2535

633.75

E62A

325

1255

313.75

E62B

300

1130

282.5”

Table 2: calculate the average cost 

  1. The current ALOS of the given data has the benchmark that is set on the basis of the disease and the complexity of the situation. The benchmark of the current year is set. The ALOS is the reference to the number of days that patients have to spend in the hospital which is considered on average. According to the view of Engelenet al (2019), the calculation of ALOS is generally done by dividing the number of total days patients stayed by all the numbers of discharges and new case admission in a year. In this scenario, the benchmark of the total number of patients and the number of discharges and admission cases are given and that helps to calculate the total of the average cost. For all kinds of diseases on the basis of complex situations.
  2. The expected number of patients that will stay next year is calculated and helps to assess the efficiency of the healthcare hospitals. (Schmidt et al 2019).All other factors being equal, the shorter duration of stay will deduct per unit of discharge cost and can shift the care of an inpatient to a cheaper alternative for post-recovery. According to the view of Meyer et al (2022), the daily cost of stay is the total cost that is required to stay in the hospital care that is set by the industry and it includes all the care and accommodation for the patients during and post-recovery from the acute diseases. 
  3. The total cost of services that are provided by the healthcare to each patient that includes all the cost of services from treatments to all the post care of the patients. 
  1. 4% increase in the patients

“DRG

NUMBER OF PATIENTS ARE EXPECTED IN THE NEXT YEAR

Overall cost

Average cost

Incresing 4%

F74A

1600

1255

313.75

1664

E65B

750

1275

318.75

780

F73B

450

1140

285

468

F76B

450

1145

286.25

468

E61B

450

1270

317.5

468

F62B

450

1135

283.75

468

L63A

350

1155

288.75

364

F42B

300

2535

633.75

312

E62A

325

1255

313.75

338

E62B

300

1130

282.5

312”

Table 3: 4% increase in the patients

  1. a) Direct payment is the result of this method. According to the view of Nuh et al (2020), if the hospital wants to increase the funds in their account they need to increase the volume of their patients' care if only they have the capacity that is still unused. 
  2. b) Budget gives the proper idea about the cost and the effective use of cost. 
  3. Effective costs are reduced 5% and 10%

“DRG

NATIONAL EFFECTIVE PRICE

Overall cost

effective cost 5% reduce

effective cost 10% reduce

F74A

1255

1192.25

1129.5

E65B

1275

1211.25

1147.5

F73B

1140

1083

1026

F76B

1145

1087.75

1030.5

E61B

1270

1206.5

1143

F62B

1135

1078.25

1021.5

L63A

1155

1097.25

1039.5

F42B

2535

2408.25

2281.5

E62A

1255

1192.25

1129.5

E62B

1130

1073.5

1017”

Table 4: Calculation of effective costs are reduced 5% and 10% 

As per the calculation of this deduction in the overall cost are give the idea about effective cost control of the health care industry. 

  1. “Analysis of the benchmark and discuss the expected number of patients”.
  2. A) ALOS

In the given figure 5, an analysis of the daily cost in the healthcare system Effective costs are reducing 5%, and 10% in the daily cost. In the given case study ALOS is given and the benchmark is given in this case study, as per the report there is 1 benchmark in F742A and the company meets this benchmark. The E65B benchmark is given 3 but the company crosses the benchmark that gives the most effective sales in that particular drug. In the F73B benchmark and the sales are the same like 2. The largest benchmark is in the E62A, which are 10, but the sales of that particular DRG is 11, this DRG crosses the limit of sales. (Oleribe, et al 2019), 

  1. B) The number of patients expected in the next year

If the company uses DRG increases by about 4%, This indicator helps to increase the total capacity of the hospital and can increase productivity, and the expected number of patients can be increased over the next year.

7. ABF

 (a) Disadvantages of the funding model of ABF 

  • The implementation of this model can increase the total cost of the hospital because of the increased volume. (Parra-Rizo and Sanchi 2020),
  • The issue is to assess the appropriate fund amount for the hospitals. 

Advantages of the funding model of ABF 

  • The same amount is paid to the hospital with the same kinds.
  • Help to set the transparency and efficiency of the hospitals. 

(b) The risk of ABF

is that it increases the cost that is needed to implement this module to collect the group of diagnoses. The increase in the volume cannot be done in the small healthcare units. 

  1. Discussion of Reflection

In this case study I analyzed all the possible outcomes of the financial magnet in the healthcare industry. I discuss the ABF budget and the method of block funding for the healthcare sectors. This report has helped me to analyze the methods of funding in hospitals.(Patel et al 2022). The area of coverage was the assessment of the funding model that is implemented in the hospitals that help the sectors to get the allocation of the funds on the basis of the patient care and how the hospitals can increase their capacity to get more patients cured that can increase the total number of expected patients for the next year. Alongside this, I also analyzed the disadvantages that can increase the cost of implementation of such a model of budget in the hospitals. 

References

  • Ali, F., El-Sappagh, S., Islam, S. R., Kwak, D., Ali, A., Imran, M., & Kwak, K. S. (2020). A smart healthcare monitoring system for heart disease prediction based on ensemble deep learning and feature fusion. Information Fusion, 63, 208-222. Retrieved on 25 April from: https://drive.google.com/file/d/1k4vJkixVRE1IgmiZnxqVGmhZHzi1Z4KZ/view
  • Aragón, M. J., Chalkley, M., &Kreif, N. (2022). The long?run effects of diagnosis related group payment on hospital lengths of stay in a publicly funded health care system: Evidence from 15 years of micro data. Health Economics, 31(6), 956-972. Retrieved on 25 April from: https://onlinelibrary.wiley.com/doi/pdf/10.1002/hec.4479
  • Bisaga, I., & To, L. S. (2021). Funding and delivery models for modern energy cooking services in displacement settings: a review. Energies, 14(14), 4176. Retrieved on 25 April from: https://www.mdpi.com/1996-1073/14/14/4176/pdf
  • Engelen, L., Chau, J., Young, S., Mackey, M., Jeyapalan, D., & Bauman, A. (2019). Is activity-based working impacting health, work performance and perceptions? A systematic review. Building research & information, 47(4), 468-479. Retrieved on 25 April from: https://www.tandfonline.com/doi/pdf/10.1080/09613218.2018.1440958
  • Meyer, J., McDowell, C., Lansing, J., Brower, C., Smith, L., Tully, M., & Herring, M. (2020). Changes in physical activity and sedentary behavior in response to COVID-19 and their associations with mental health in 3052 US adults. International journal of environmental research and public health, 17(18), 6469. Retrieved on 25 April from: https://www.mdpi.com/1660-4601/17/18/6469/pdf
  • Nuh, M., Nyorong, M., &Nadapdap, T. P. (2022). Analysis of the Utilization of Capitation Funds for the National Health Insurance Program at the KutePanang Health Center. Journal La Medihealtico, 3(3), 226-237. Retrieved on 25 April from: http://newinera.com/index.php/JournalLaMedihealtico/article/download/666/587
  • Oleribe, O. O., Momoh, J., Uzochukwu, B. S., Mbofana, F., Adebiyi, A., Barbera, T., ... & Taylor-Robinson, S. D. (2019). Identifying key challenges facing healthcare systems in Africa and potential solutions. International journal of general medicine, 395-403. Retrieved on 25 April from: https://www.tandfonline.com/doi/pdf/10.2147/IJGM.S223882
  • Parra-Rizo, M. A., &Sanchis-Soler, G. (2020). Satisfaction with life, subjective well-being and functional skills in active older adults based on their level of physical activity practice. International journal of environmental research and public health, 17(4), 1299. Retrieved on 25 April from: https://www.mdpi.com/1660-4601/17/4/1299/pdf
  • Patel, D., Williams, W. O., Wright, C., Taylor-Aidoo, N., Song, W., Marandet, A., &DiNenno, E. A. (2022). HIV Testing Services Outcomes in CDC-Funded Health Departments During COVID-19. JAIDS Journal of Acquired Immune Deficiency Syndromes, 91(2), 117-121. Retrieved on 25 April from: https://stacks.cdc.gov/view/cdc/122662/cdc_122662_DS1.pdf
  • Schmidt, M., Schmidt, S. A. J., Adelborg, K., Sundbøll, J., Laugesen, K., Ehrenstein, V., &Sørensen, H. T. (2019). The Danish health care system and epidemiological research: from health care contacts to database records. Clinical epidemiology, 563-591. Retrieved on 25 April from: https://dam-oclc.bac-lac.gc.ca/download?is_thesis=1&oclc_number=1334506447&id=fe90b64a-731c-47fd-a112-e7d759486205&fileName=Duncan_Andrea_Lynn_202106_PhD_thesis.pdf
  • Slater, J. (2019). A Health Outcomes Resource Standard (HORSt) for Australian State Public Health Funding Distributions. Retrieved on 25 April from: https://ro.uow.edu.au/cgi/viewcontent.cgi?article=1829&context=theses1
  • Thomas, E. E., Haydon, H. M., Mehrotra, A., Caffery, L. J., Snoswell, C. L., Banbury, A., & Smith, A. C. (2022). Building on the momentum: sustaining telehealth beyond COVID-19. Journal of telemedicine and telecare, 28(4), 301-308. Retrieved on 25 April from: https://journals.sagepub.com/doi/pdf/10.1177/1357633X20960638
  • World Health Organization. (2019). Intervention guidebook for implementing and monitoring activities to reduce missed opportunities for vaccination. Retrieved on 25 April from: https://apps.who.int/iris/bitstream/handle/10665/330101/9789241516310-eng.pdf
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