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  • 1.
    Afroze, Tonima
    et al.
    KTH, School of Technology and Health (STH).
    Rosén Gardell, Moa
    KTH, School of Technology and Health (STH).
    Algorithm Construction for Efficient Scheduling of Advanced Health Care at Home2015Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    Providing advanced health care at home rather than in a hospital creates a greater quality of life for patients and their families. It also lowers the risk of hospital-acquired infections and accelerates recovery. The overall cost of care per patient is decreased. Manual scheduling of patient visits by health care professionals (HCPs) has become a bottleneck for increased patient capacity at SABH, a ward providing advanced pediatric health care at home (“Sjukhusansluten Avancerad Barnsjukvård i Hemmet” in Swedish), since many parameters need to be taken into account during scheduling. This thesis aims to increase the efficiency of SABH’s daily scheduling of personnel and resources by designing an automated scheduler that constructs a daily schedule and incorporates changes in it when needed in order to remove scheduling as a limitation for increased patient capacity. Requirements on a feasible schedule are identified in cooperation with SABH and literature is investigated about similar areas where the scheduling process has been automated. The scheduling is formulated as a computerized problem and investigated from the perspective of theoretical computer science. We show that the scheduling problem is NP-hard and can therefore not be expected to be solved optimally. The algorithm for scheduling the visits minimizes violations of time windows and travel times, and maximizes person continuity and workload balancing. The algorithm constructs an initial solution that fulfills time constraints using a greedy approach and then uses local search, simulated annealing, and tabu search to iteratively improve the solution. We present an exact rescheduling algorithm that incorporates additional visits after the original schedule has been set. The scheduling algorithm was implemented and tested on real data from SABH. Although we found the algorithm to be efficient, automatic transfer of data from the patient journal system is an imperative for the scheduler to be adopted.

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