Optimization is a structure designed to uphold provision of excellent patient care services to the society amid the prevailing constraints, including resource, time, budget, healthcare features, and patient's characteristics. Such dynamic and complex healthcare problems call for rigorous and systemic approaches, such as optimization, to attain optimal solutions.
Use of Optimization Techniques in Enhancing Healthcare Delivery
Optimization is an operation research technique used to model healthcare operations problems and propose solutions to the issues. Techniques such as linear programming, discrete complex analysis, and dynamic programming are used to solve clinical delivery problems (Wang, 2012). For instance, a health facility can formulate a linear program to maximize medical services while attending to a mix of inpatients and outpatients subject to budget and resource constraints. The facility can then solve the formulated problem using a graphical method, a simulation, or a simplex method.
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Optimization also uses descriptive, prescriptive, and predictive statistics to model problems in the care industry. Descriptive analytics focuses on past data regarding a topic of interest, mainly searching for sequences and patterns of occurrences. The designs are then used to measure the current level of preparedness to tackle such problems. Prescriptive analytics is an evaluation of the effectiveness of existing systems in solving current healthcare problems. Finally, predictive analytics serves as forecasting tools used to focus on the state of the system, diseases, or vaccines in the future.
Value of Optimization Techniques in Providing Patient Care and Safety
Optimization techniques in healthcare help promote convenient, rapid, and quality services. Patients no longer have to stay in long queues, spend several hours in waiting bays, and pay exorbitant fees to see a doctor. For instance, optimizations systems help patients check-in for medical attention, make future appointments with the medical practitioner, download information on their health records, and update their insurance data. Optimization also helps to streamline healthcare facility processes, thereby saving the facility from avoidable expenses. Besides, an optimized healthcare process helps secure patient’s private information and diagnosis through guarding of porous points where data leakages occur. Data security is a critical component of any streamlined system. Optimization leads to a better quality of healthcare services through reduction of failures in medical delivery and prevention of incompliance with clinical practices (Wang, 2012). The technique further prevents diverse outcomes of patient medication, cancellation of clinical procedures, high occupancy rates beyond the required capacity, and failure of achieving healthcare goals.
Healthcare Problems that Lead to the Application of Optimization Techniques
Most of the problems that health care facilities face involve that of decision making. Capacity planning, surgery scheduling, appointment scheduling, and workforce scheduling are some of the issues that healthcare facilities practically encounter every day (Wang, 2012). Other problems include the location of health facility, screening of diseases, vaccine arrangements, organ allocation, and transplant. All these problems regard service delivery decision-making and hence are solved through optimization techniques.
Fictitious Optimization Problem
Our objective is to maximize healthcare avenues given time and budget constraints. We let patient outcomes and patient safety be our decision variables. Also, assume that a doctor has at least 3 hours a day to attend to a single inpatient 2 hours a day to attend to a single outpatient. The hospital pays the doctor at least 5 dollars for each inpatient he attends to and 7 dollars to each outpatient he attends. The optimization model, in this case, is as follows:
Max Z= C1X1+C2X2
Where X1=patient outcome
X2= patient safety
C1= contribution to patient outcome
C2=contribution to patient safety
Reference s
Wang, F. (2012). Measurement, optimization, and impact of health care accessibility: a methodological review. Annals of the Association of American Geographers , 102 (5), 1104-1112.
