Waiting time analysis in a paediatric outpatient clinic in South East Nigeria

Anyanwu, Onyinye Uchenna; Ezeonu, Thecla; Orji, Lauretta; Ezeanosike, Obumneme; Ikegwuonu, Charles; Omeje, Kenneth; Asiegbu, Vivian; Onwe, Emeka Ogah; Onyire, Benson Nnamdi

doi:10.36472/msd.v8i2.459

Cited by 3 publications

(5 citation statements)

References 15 publications

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“…To calculate the probabilities for these defined fuzzy sets, X i ( P), X i ( Q), X i ( R)expressions are defined in ( 23)-(25). For computation of these expressions,expansion up to some specific degree term of exponential membership functions has been used.vary the results in [1,2,3,47]and the present model suggests the fast service than the other models i.e. patients' waiting time is lesser than the others' work (1)(2)(3)(4) .…”

Section: Resultsmentioning

confidence: 83%

“…For computation of these expressions,expansion up to some specific degree term of exponential membership functions has been used.vary the results in [1,2,3,47]and the present model suggests the fast service than the other models i.e. patients' waiting time is lesser than the others' work (1)(2)(3)(4) . The variance of the result with (7) is due to take into account the fuzzy linear programming.…”

Section: Resultsmentioning

confidence: 83%

“…Statistical package for the social sciences for windows version 23.0 was used to manipulate the data. The results in (2) show that the mean time spent in the hospital with standard deviation was 142.58±23.17 minutes and divided as in different stages was as 113.15±18.01 minutes -waiting time, 24.43±10.38 minutes -consultation time, nurse's bay -23.79±6.47 minutes and in the queue -22.94±8.98 minutes. Most of the respondents (66.6%) were highly satisfied with the service provided by facilities in the healthcare service facility and 45.2 minutes was the mean waiting time.…”

Section: Introductionmentioning

confidence: 97%

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Setting up Waiting Time Targets for Out Patients using Fuzzy Linear Programming

Kumar¹,

Pandey²

2023

IJST

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Objective: To introduce fuzzy linear programming to find the patients' waiting time by satisfying some defined satisfaction targets of patients at out-patient department (OPD) of a healthcare unit. Method: The concept of tolerance limit has been used for obtaining fuzzy linear programming formulation. Fuzzy linear programming is transformed into its equivalent crisp linear programming. The software TORA 3.0 is then used to solve the obtained crisp linear programming. Findings: Waiting times for patients at their different satisfaction targets have been obtained by solving equivalent crisp linear programming. The solution of the present model suggests that At least 95.30 % patients should be checked-up within half an hour of their appointment and all of them should be checked up within 45 minutes for punctual patients and at least 26.51 % of them should be checked up within half an hour of their arrival and all of them should be checked up within 45 minutes for late patients. Due to assumption of tolerance limit, patients' satisfaction targets regarding waiting time are relaxed up to predefined limits. Consequently the efficiency of healthcare unit increases in the proportion of relaxed limits. Novelty: Patients' waiting time with satisfying targets have already been obtained using statistical analyses and classical linear programming. In this article we introduce the fuzzy linear programming to get waiting time for patients by fuzzifying the patients' satisfaction constraints which are indeed novel idea in setting patients' waiting time. Furthermore, some crisp constraints are also included to make the waiting time standards consistent for patients.

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Section: Resultsmentioning

confidence: 83%

Section: Resultsmentioning

confidence: 83%

Section: Introductionmentioning

confidence: 97%

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Setting up Waiting Time Targets for Out Patients using Fuzzy Linear Programming

Kumar¹,

Pandey²

2023

IJST

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“…The typical amount of waiting time that patients can tolerate from the moment they leave the registration desk until they receive the last service they require is around 90 minutes. (Abdus-salam et al, 2021;Al-Harajin et al, 2019;Alrasheedi et al, 2019;Anyanwu et al, 2021;Sharma et al, 2022).…”

Section: Patient Satisfication Based On Waiting Timementioning

confidence: 99%

Waiting Time : Problems From The Past, Present and Future

Iskandar

Sundari

2023

jika

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Waktu tunggu yang lama merupakan permasalahan yang terjadi hampir diseluruh fasilitas pelayanan kesehatan. Waktu tunggu yang lama merupakan permasalahan yang sudah ada sejak dahulu namun hingga saat ini masih belum terselesaikan. Salah satu faktor penyebab permasalahan ini terjadi dikarenakan fasilitas pelayanan kesehatan selalu berupaya meningkatkan angka kunjungan pasien namun tidak diikuti dengan peningkatan kemampuan pelayanan baik dari segi sumber daya manusia maupun sarana dan prasarana. Waktu tunggu yang lama nantinya akan berdampak pada tingkat kepuasan pasien. Kepuasan pasien merupakan faktor kunci dalam menjalankan bisnis dibidang jasa pelayanan kesehatan. Jenis penelitian ini merupakan penelitian kuantitatif dengan metode observasional analitik yang menggunakan kuesioner sebagai instrumen pengambilan data. Kuesioner penelitian tentang kepuasan menggunakan skala likert 1-5. Peneliti juga melakukan pengambilan data secara aktual terkait waktu tunggu terhadap 139 responden klinik penyakit dalam dengan cara mengikuti responden mulai dari loket antrian hingga responden meninggalkan fasilitas pelayanan kesehatan. Besaran sampel penelitian dihitung menggunakan software epi-info dengan metode pengambilan sampel consecutive sampling. Analisis data menggunakan metode chi-square pada software SPSS 21 menemukan bahwa dengan rerata waktu tunggu selama 315 menit tidak berpengaruh terhadap kepuasan pasien, hal ini dikarenakan terdapat faktor-faktor lain yang dapat mempengaruhi kepuasan pasien selain waktu tunggu. This open access article is under the CC-BY-SA license.

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“…5 Studies done in the primary care setting in Nigeria used a standard of 30 minutes waiting time as recommended by the Institute of Medicine. 6,7 Consultation time is measured as the time between the first greeting and the dismissal of a patient from the consultation room. 8 It is an integral component of primary care practice and a central factor in medical practice.…”

Section: Introductionmentioning

confidence: 99%

Turnaround Time of Consults in a Primary Care System in Rural Philippines: A Descriptive Retrospective Cohort Study

2023

Acta Med Philipp

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Background. Turnaround time is an integral component of primary healthcare and is a key performance indicator of healthcare delivery. It is defined as the time patients spend during a healthcare facility visit. In this study, turnaround time is defined as the time elapsed from registration to the end of consultation.Objectives. This study aimed to determine the turnaround time of consults in the primary care system in a rural site in the Philippines, and compare turnaround time during the pre-pandemic and COVID-19 pandemic periods.Methods. This is a retrospective cohort study of patients seen at the primary care facility under the Philippine Primary Care Studies (PPCS) rural site from April 2019 to March 2021. Patients included in this study were chosen through random sampling. Electronic medical records (EMR) of these patients were reviewed. Turnaround time was computed electronically from time of registration to end of consultation. Descriptive statistics was used to summarize data and report turnaround time. The turnaround time before and during the pandemic was compared using an independent sample t-test (if normally distributed) or Mann Whitney U test (if not normally distributed). A p-value of <0.05 was considered statistically significant. Results.A random sample of 342 patients out of the total 45,501 patient consults seen at the rural primary healthcare facility from April 2019 to March 2021 were included in this study. The median turnaround time was 29.0 minutes (interquartile range [IQR] 68.3), with range of 0.9 to 437.2 minutes. During the pre-pandemic period, the median turnaround time of consults is 29.3 minutes (IQR 70.4) which is 1.8 minutes longer than the pandemic period which showed median turnaround time of 27.5 minutes (IQR 72.7). The difference between the two time periods was not statistically significant (P = 0.39). Conclusion.The study showed that the median turnaround time of medical consults was 29.0 minutes, which was shorter by 80 minutes compared to other published Philippine studies. The turnaround time did not differ significantly in the pandemic and pre-pandemic period, despite new policies and systems that were implemented during the pandemic.

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Waiting time analysis in a paediatric outpatient clinic in South East Nigeria

Cited by 3 publications

References 15 publications

Setting up Waiting Time Targets for Out Patients using Fuzzy Linear Programming

Setting up Waiting Time Targets for Out Patients using Fuzzy Linear Programming

Waiting Time : Problems From The Past, Present and Future

Turnaround Time of Consults in a Primary Care System in Rural Philippines: A Descriptive Retrospective Cohort Study

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