Operations Management in Health Care
Part One:
Aligning capacity with demand relates to capacity planning, analysis if resource limitations or excesses are there at all parts or departments at a specific time. Taking an instance where a clinic has 100 hours weekly, while demand is keen on 1400 procedures and 120 hours of patient demand, there is a disconnect or lack of alignment in capacity and demand. This is common in healthcare centers where demand or capacity may be lacking.
Basically, this comprises of mapping supply and demand over a certain period, graphically assessing the information and then coming up with plans for inclusion or removal of capacity. The most notable strategies for handling with capacity limitations may include:
- Increasing capacity in cases the capital permits. This means buying new capital tools that would enable the center to undertake more operations for longer hours. Health centers could increase the labor, increase the swing beds or the size of the rooms. Additionally, certain services could be subcontracted so as to offer more capacity. The application of return on investment has to be made use of in the best way possible. This would ensure that the advantages of increase in capacity are bigger when compared to marginal costs to invest in the increase of space.
- De-bottleneck is another process that would free up space. The application of engineering tools would identify bottlenecks and aim for enhancement methods.
- Reduction of demand where necessary and profitable. This would lead to a decline in services or processes involved or redirect patients to other centers.
- Transfer capacity from other parts, there are times that capacity exists in some areas that may not be required to finance, which can be applied to finance capacity in other parts. For instance, if space is the area of concern, the square foot can be decreased in some departments and offered to others.
The demand for CT scan can be calculated using Microsoft Excel. From the data collected throughout the week, we can predict the demand during the next week. Prediction of future demand can be useful for managers or other staff responsible for handling equipment in order to determine the required capacity i.e. aligning the demand with the capacity. The following is a chart detailing the predicted demand for CT scans in the next week.
The main productivity estimates relevant to the activity are the productivity of the employees and efficiency of the machine. The machine is meant to handle forty five non-emergency cases and ten emergency cases totaling to fifty five. In this case, workers are ninety five percent productive, with the unproductive five percent resulting from frequent natural reasons such as health problems or death of a loved one. The machine is still in a pristine condition and is still very effective thus we cannot conclude that the high demand is due to queues that have resulted from accumulation of patients. The machines operating hours are from 8 a.m. to 6p.m.
The maximum number of CT scans that can be done in a day is 55. During the week, only two days did the number of patients requiring CT scans reach the maximum, i.e. at the beginning of the week and just before the weekend. These can be predicted to be the days when the demand for CT scans reaches its peak, probably because the people are aware that during the weekend they may not have time to visit the hospital and at the beginning of the week more patients are expected after the lag in number during the weekend. The CT scan can therefore be said not to be utilized completely since most days in the week there are no patients who require CT scans.
There seems to be a discrepancy between capacity and demand in the hospital. This is brought about by the big difference between the available resources and the demand for them. As we can see, most of the patients in the hospital do not go for CT scans and this may imply that the CT scan may not be given the highest priority. The management can focus on the other areas of the hospital since CT scan is not very much required. However, it is a vital equipment that cannot be laid off without serious consideration.
In aligning the capacity with demand, I would suggest that the hospital lays off some extra staff working with the department. This is because on a normal basis, the hospital’s CAT scan machine rarely exceeds its capacity thus many employees result to wastage of funds. Since the machine is used significantly daily, there is no need to increase its operating hours or employee’s operating hours.
If additional resources are obtained, the hospital can also take a step add another machine to provide better service to the patients. This will also increase the life of the existing one since it will be used to an optimum level.
Part Two
Productivity is basically a measure of the effectiveness and efficiency of an organization in generating output with the resources available. It is defined as a ratio of output to input. Indicators for productivity used in a surgical department could be divided into two: labor productivity and capital productivity (Beech, 2005). Labor productivity measures the value added per worker and reflects the effectiveness and efficiency of labor in the sale or production of the output, in this case surgeries performed. More surgeons and other support staff may mean faster completion of surgeries or more clients served per unit time.
Capital productivity measures the effectiveness and efficiency of additional capital in the generation of the output (value added per dollar of capital). Capital productivity can result from improvements in the machinery or equipment used, further skills of the workers using the capital and processes among others (Beech, 2005). In this case, an organization can decide to buy latest technology medical equipment that will quicken the work or train their staff to help them handle more cases quickly and efficiently. The services of capital may move from physical capital, involving structures of varied forms or human capital that range from expertise acquired or the intellect of the society. This varies the time and effort that people accord to production from acquiring skills and knowledge that manifests their abilities.
Today’s healthcare sector adds up to about a tenth of the economic activity of the economies, and labour additions play a role in massive shares of its costs, when compared to other industries. It is hence well understood that the measurement, tracking and enhancement of labour productivity in the health industry.
Today’s healthcare arises from an extensive range of human resources from the greatest levels of human capital to the basic levels. The main task of human resources in the CT scans department shows some issues for scoping. It may not be feasible to acquire subset of health services that is basically health human resources productivity. All aspects that comprises human resources has implications that would affect the health center’s productivity in one way or the other.
In an effort to map out the extent of research work in health human resources productivity, we use contemporary methods that would be described extensively. The following is an analysis of two employees in a local hospital who are responsible for carrying out minor surgeries and work on either on the night or day shifts. These two surgeons were each observed independently for two days in the study hospital and data was collected relating to the number of hours worked and surgeries done or number of customers served. The input was measured as the number of the patients attended while the input was measured as the number of hours the employees were working.
Surgeon A: productivity = 10 patients/ 8hours = 1.3 patients per hour
Surgeon B: productivity = 7 patients/6 hours = 1.2 patients per hour
The difference between the two workers is very minimal and may be rounded off to one patient attended in every hour by each surgeon. Details of support staff, the kind of illness and supplies used were assumed to be constant since both surgeons handle similar cases and patients are referred on the basis of surgeon available. For this result to be said to be bad or good, a benchmark or standard is required in order for one to make comparison. This can be made from comparison of the results from observance of best practices or alternatively from comparison with another organization that has proved to be operating at optimal productivity.
These outputs can be improved with some few changes in the surgery department. Improvement in productivity is usually achieved by increasing the output as much as possible while using the least amount of resources available. Reducing the number of staff required to do the operations can be one way of reducing the inputs. Also, the organization can invest in assets that replace human labor such as new technology hardware. The management of the organization should also study the trend in healthcare in the region and strike a balance between assets and labor to optimize productivity. The management needs to employ mathematical analysis of the situation, using concepts such as linear programming and simulation in order to come up with an accurate measure of the productivity and what needs to be increased or reduced in the department.
The hospital can decide to increase the knowledge of the staff by continually training them on the different approaches to perform surgical operations. This way, a lot of time can be saved thus creating space for more patients to be served. Increasing the quality of the services can be another way of ensuring maximum productivity since the more qualified the staff is, the easier and faster it will be to deliver services effectively. However, a major challenge usually arises since most of the time the quality of service in healthcare organizations is not always reflected directly in the output as in other professions.
The process of productivity has to be simple, adding the up inputs and outputs, dividing them and assessing the trend for some time. However, there are issues that can be restricted in the assessment of productivity and these arise from precise aspects of healthcare.
The technical issues arise due to production processes that may call for a number of factor inputs and creates a number of forms of output. Measuring productivity calls for the building of aggregate indexes for inputs and outputs.
Any measure of productivity in the health industry has to begin from the most basic that it is the health results, enhancement or maintenance of the health level of the persons and society that comprises the objective and justification for the health industry. Care that is ill-handled may result to negative aspects like serious harm to patients. The health industry is based on the basic reality that there is need to safeguard the patients from bad care practices.
Part Three
The acquisition activities occur at the manufacturers and distributors premises where the hospital purchases medical supplies after they ran out at the stores. Inventory activities of the drug stocks takes place at the pharmacy where the economic order quantities are calculated based on the demand and various other factors (Beech, 2005). The drugs are also received at the pharmacy and kept ready for issuing to the surgery department and other requesting departments. When the items are out of stock, provisioning is ordered. The receiving department then might further distribute the drugs to the patients being served.
The ordering process requires one to first identify needs; by determining the number of requisition lines for out of stock items and considering the number of urgent orders to suppliers. The number of orders; in this case surgical apparatus is processed and tracked (Beech, 2005). When the items arrive, they are transferred to the storage area. Items out of stock are then replenished from the pharmacy.
Reorder point;
Scalpels;
Normal consumption in units per day; 144 pieces (12 dozens)
Maximum consumption= 150 scalpels
Maximum reorder period= 3.5 months
Lead time=90 days
Safety stock=360 pieces (30dozens) (due to emergency cases)
Reorder point= normal consumption during lead days +safety stock
= 42 dozens
Economic order quantity;
With the assumptions that;
- Lead time is known
- Ordering cost remains constant
- No discount is available as price is fixed
- The whole batch is delivered without delay
- Rate of demand is known
Then EOQ can be determined as follows;
EOQ=sqrt(2*annual demand *cost of ordering per unit/costs of holding)
=sqrt(2*42*4*250/62.5)
= 37 dozens
The quantity being ordered by the hospital is by far more much uneconomical. This is by the proof brought forward by the above calculations. The orders that the hospital was taking were above optimum level which is dangerous for the business.
Improvement strategy
Past records of the hospital dictate that it has remained at a constant financial position; at rest. This should not be the case; constant change should be encouraged so as to capitalize on each of the available avenue (Beech, 2005). It is also to sensitize employees that processes must evolve and thus no single method can be best used in a situation. The number of scalpels kept for emergencies over the number had piled up even leading to some getting destroyed in some cases. This resulted to wastage of resources as inventory was too slow to move.
References
Beech, R. JV.(2005).Health Operations Management: Patient Flow Logistics in Health Care. Psychology Press
