Velkommen

To construct the structural model of the routing in and out of queue

One of the major elements in improving efficiency in the delivery of health care services is patient flow. Good patient flow means that patient queuing is minimized International Journal of Academic Research in Business and Social Sciences February, ISSN:- IJARBSS– Impact Factor:. Allocated by queue system Global Impact Factor, Australia and poor patient flow means that patients suffer considerable queuing delays Hall et. al,. This process is sketched in Fig. International Journal of Academic Research in Business and Social Sciences February, ISSN:- IJARBSS– Impact Factor:. Allocated by Global Impact Factor, Australia www. hrmars. com Flow Chart for AGA OPD The Average Daily Attendance ADA was estimated using both secondary and primary data from the OPD. 



Effective resource allocation and capacity planning are determined by patient flow because it informs the demand for health care services Murray,. Queuing theory provides exact or queue system software approximate estimation of performance measures for such systems based upon specific probability assumptions. In a hospital, these assumptions rarely hold, and so results are approximated Cochran& Bharti,. RESEARCH METHODOLOGY The study adopts a descriptive, observational and ex post facto case study approach. In depth review of hospital OPD attendance records from January to June was made. Interviews with management, doctors, and records staff were conducted to validate the secondary data and to gather information required to construct the structural model of the routing in and out of OPD.



Direct observations were used to model patient average arrival and length of stay. Questionnaires were also used to gather information on daily arrival rates, patients’ view on queuing at the hospital, waiting time to consult a doctor, etc. The survey population of the study was the entire out-patients of AGA Hospital in Quasi during the period of the study. In all, patients were surveyed for this study. Purpose sampling, a non-probability sampling technique in which the researcher selects a group of people because they have particular traits that the researcher wants to study was used. The out-patient department queue system software was selected because it had the greatest queuing challenge compared to the other units in the hospital.

The survey revealed that patients arrive at the outpatient department and drop their hospital card in a box and wait their turn. A nurse then attends to them and allocates a consulting room. From the consulting room, patients are sent to the laboratory and the radiology department for laboratory tests or medical imaging. Those who do not require these for diagnosis are given treatment and proceed to the data entry clerk with their prescriptions, entries are done and they collect their drugs from the pharmacy and go back home. Those who return from the laboratory and radiology department also go through this same process. Patients who require admission are directly admitted to the ward from the consulting room and care continues from there. Secondary data from January to June gave a daily average of patients See Fig.



Looking at the secondary data, the distribution of the attendance was the customer queue system software free busiest on Mondays and Fridays. Accordingly, using the worst case scenario and within the limit of resource capacity, an observational study was done on the other four days to establish the OPD attendance i. e., to and June; and th and th of July. The ADA derived from the data was patients. Noting that the difference between the secondary and primary values was not that significant, barely per cent, the ADA from the observational study i. e., the worst case scenario was used.